937 resultados para Critical power
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Active network scanning injects traffic into a network and observes responses to draw conclusions about the network. Passive network analysis works by looking at network meta data or by analyzing traffic as it traverses a fixed point on the network. It may be infeasible or inappropriate to scan critical infrastructure networks. Techniques exist to uniquely map assets without resorting to active scanning. In many cases, it is possible to characterize and identify network nodes by passively analyzing traffic flows. These techniques are considered in particular with respect to their application to power industry critical infrastructure.
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PURPOSE: This study investigated the efficacy of an intermittent critical power model, termed the "work-balance" (W'BAL) model, during high-intensity exercise in hypoxia. METHODS: Eleven trained, male cyclists (mean ± SD; age 27 ± 6.6 yr, V[Combining Dot Above]O2peak 4.79 ± 0.56 L.min) completed a maximal ramp test and a 3 min "all-out" test to determine critical power (CP) and work performed above CP (W'). On another day an intermittent exercise test to task failure was performed. All procedures were performed in normoxia (NORM) and hypoxia (HYPO; FiO2 ≈ 0.155) in a single-blind, randomized and counter-balanced experimental design. The W'BAL model was used to calculate the minimum W' (W'BALmin) achieved during the intermittent test. W'BALmin in HYPO was also calculated using CP + W' derived in NORM (N+H). RESULTS: In HYPO there was an 18% decrease in V[Combining Dot Above]O2peak (4.79 ± 0.56 vs 3.93 ± 0.47 L.min ; P<0.001) and a 9% decrease in CP (347 ± 45 vs 316 ± 46 W; P<0.001). No significant change for W' occurred (13.4 ± 3.9 vs 13.7 ± 4.9 kJ; P=0.69; NORM vs HYPO). The change in V[Combining Dot Above]O2peak was significantly correlated with the change in CP (r = 0.72; P=0.01). There was no difference between NORM and HYPO for W'BALmin (1.1 ± 0.9 kJ vs 1.2 ± 0.6 kJ). The N+H analysis grossly overestimated W'BALmin (7.8 ± 3.4 kJ) compared with HYPO (P<0.001). CONCLUSION: The W'BAL model produced similar results in hypoxia and normoxia, but only when model parameters were determined under the same environmental conditions as the performance task. Application of the W'BAL model at altitude requires a modification of the model, or that CP and W' are measured at altitude.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The aim of the present study was to verify the applicability of anaerobic work capacity (AWC) determined from the critical power model in elite table tennis players. Eight male international level table tennis players participated in the study. The tests undertaken were: 1) A critical frequency test used to determinate the anaerobic work capacity; 2) Wingate tests were performed using leg and arm ergometers. AWC corresponded to 99.5 +/- 29.1 table tennis balls. AWC was not related to peak (r = -0.25), mean (r = -0.02), relative peak (r = -0.49) or relative mean power (r = 0.01), nor fatigue index (r = -0.52) (Wingate leg ergometer). Similar correlations for peak (r = -0.34), mean (r = -0.04), relative peak (r = -0.49), relative mean power (r = -0.14) and peak blood lactate concentration (r = -0.08) were determined in the Wingate arm ergometer test. Based on these results the AWC determined by a modified critical power test was not a good index for measurement of anaerobic capacity in table tennis players.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Aim. - This study aimed to test if investigate whether the anaerobic work capacity is replenished while exercising at critical power intensity. Then, a known exercise duration, which demands high anaerobic energy contribution, was compared to intermittent exercise duration with passive and active (cycling at critical power intensity) rest periods.Methods. - Nine participants performed five sessions of testing. From the 1st to the 3rd sessions, individuals cycled continuously at different workloads (P-high, P-intermediate and P-low) in order to estimate the critical power and the anaerobic work capacity. The 4th and 5th sessions were performed in order to determine the influence of anaerobic work capacity replenishment oil exercise duration. They consisted of manipulating the resting type (passive or active) between two cycling efforts. The total exercise duration was determined by the sum of the two cycling efforts duration.Results. - The exercise duration under passive resting condition (408.0 +/- 42.0 s) was longer (p<0.05) than known exercise duration at P-intermediate (T-intermediate = 305.8 +/- 30.5 s) and than exercise duration performed under active resting conditions (T-active = 304.4 +/- 30.7s). However, there was no significant difference between T-intermediate and T-active.Conclusion. - These results demonstrated indirect evidence that the anaerobic work capacity is not replenished while exercising at critical power intensity. (C) 2008 Elsevier Masson SAS. All rights reserved.
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The aim of this study was to test if the critical power model can be used to determine the critical rest interval (CRI) between vertical jumps. Ten males performed intermittent countermovement jumps on a force platform with different resting periods (4.1 +/- 0.3 s, 5.0 +/- 0.4 s, 5.9 +/- 0.6 s). Jump trials were interrupted when participants could no longer maintain 95% of their maximal jump height. After interruption, number of jumps, total exercise duration and total external work were computed. Time to exhaustion (s) and total external work (J) were used to solve the equation Work = a + b . time. The CRI (corresponding to the shortest resting interval that allowed jump height to be maintained for a long time without fatigue) was determined dividing the average external work needed to jump at a fixed height (J) by b parameter (J/s). in the final session, participants jumped at their calculated CRI. A high coefficient of determination (0.995 +/- 0.007) and the CRI (7.5 +/- 1.6 s) were obtained. In addition, the longer the resting period, the greater the number of jumps (44 13, 71 28, 105 30, 169 53 jumps; p<0.0001), time to exhaustion (179 +/- 50, 351 +/- 120, 610 +/- 141, 1,282 +/- 417 s; p<0.0001) and total external work (28.0 +/- 8.3, 45.0 +/- 16.6, 67.6 +/- 17.8, 111.9 +/- 34.6 kJ; p<0.0001). Therefore, the critical power model may be an alternative approach to determine the CRI during intermittent vertical jumps.
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The characterization of the hyperbolic power-time (P-tlim) relationship using a two-parameter model implies that exercise tolerance above the asymptote (Critical Power; CP), i.e. within the severe intensity domain, is determined by the curvature (W') of the relationship. The purposes of this study were (1) to test whether the amount of work above CP (W>CP) remains constant for varied work rate experiments of high volatility change and (2) to ascertain whether W' determines exercise tolerance within the severe intensity domain. Following estimation of CP (208 ± 19 W) and W' (21.4 ± 4.2 kJ), 14 male participants (age: 26 ± 3; peak [Formula: see text]: 3708 ± 389 ml.min-1) performed two experimental trials where the work rate was initially set to exhaust 70% of W' in 3 ('THREE') or 10 minutes ('TEN') before being subsequently dropped to CP plus 10 W. W>CP for TEN (104 ± 22% W') and W' were not significantly different (P>0.05) but lower than W>CP for THREE (119 ± 17% W', P<0.05). For both THREE (r = 0.71, P<0.01) and TEN (r = 0.64, P<0.01), a significant bivariate correlation was found between W' and tlim. W>CP and tlim can be greater than predicted by the P-tlim relationship when a decrement in the work rate of high-volatility is applied. Exercise tolerance can be enhanced through a change in work rate within the severe intensity domain. W>CP is not constant.
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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.
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The aim of this study was to investigate whether the maximal power output (Pmax) during an incremental test was dependent on the curvature constant (W') of the power-time relationship. Thirty healthy male subjects (maximal oxygen uptake = 3.58 ± 0.40 L·min(-1)) performed a ramp incremental cycling test to determine the maximal oxygen uptake and Pmax, and 4 constant work rate tests to exhaustion to estimate 2 parameters from the modeling of the power-time relationship (i.e., critical power (CP) and W'). Afterwards, the participants were ranked according to their magnitude of W'. The median third was excluded to form a high W' group (HIGH, n = 10), and a low W' group (LOW, n = 10). Maximal oxygen uptake (3.84 ± 0.50 vs. 3.49 ± 0.37 L·min(-1)) and CP (213 ± 22 vs. 200 ± 29 W) were not significantly different between HIGH and LOW, respectively. However, Pmax was significantly greater for the HIGH (337 ± 23 W) than for the LOW (299 ± 40 W). Thus, in physically active individuals with similar aerobic parameters, W' influences the Pmax during incremental testing.
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The need to refine models for best-estimate calculations, based on good-quality experimental data, has been expressed in many recent meetings in the field of nuclear applications. The modeling needs arising in this respect should not be limited to the currently available macroscopic methods but should be extended to next-generation analysis techniques that focus on more microscopic processes. One of the most valuable databases identified for the thermalhydraulics modeling was developed by the Nuclear Power Engineering Corporation (NUPEC), Japan. From 1987 to 1995, NUPEC performed steady-state and transient critical power and departure from nucleate boiling (DNB) test series based on the equivalent full-size mock-ups. Considering the reliability not only of the measured data, but also other relevant parameters such as the system pressure, inlet sub-cooling and rod surface temperature, these test series supplied the first substantial database for the development of truly mechanistic and consistent models for boiling transition and critical heat flux. Over the last few years the Pennsylvania State University (PSU) under the sponsorship of the U.S. Nuclear Regulatory Commission (NRC) has prepared, organized, conducted and summarized the OECD/NRC Full-size Fine-mesh Bundle Tests (BFBT) Benchmark. The international benchmark activities have been conducted in cooperation with the Nuclear Energy Agency/Organization for Economic Co-operation and Development (NEA/OECD) and Japan Nuclear Energy Safety (JNES) organization, Japan. Consequently, the JNES has made available the Boiling Water Reactor (BWR) NUPEC database for the purposes of the benchmark. Based on the success of the OECD/NRC BFBT benchmark the JNES has decided to release also the data based on the NUPEC Pressurized Water Reactor (PWR) subchannel and bundle tests for another follow-up international benchmark entitled OECD/NRC PWR Subchannel and Bundle Tests (PSBT) benchmark. This paper presents an application of the joint Penn State University/Technical University of Madrid (UPM) version of the well-known subchannel code COBRA-TF, namely CTF, to the critical power and departure from nucleate boiling (DNB) exercises of the OECD/NRC BFBT and PSBT benchmarks
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Over the last few years, the Pennsylvania State University (PSU) under the sponsorship of the US Nuclear Regulatory Commission (NRC) has prepared, organized, conducted, and summarized two international benchmarks based on the NUPEC data—the OECD/NRC Full-Size Fine-Mesh Bundle Test (BFBT) Benchmark and the OECD/NRC PWR Sub-Channel and Bundle Test (PSBT) Benchmark. The benchmarks’ activities have been conducted in cooperation with the Nuclear Energy Agency/Organization for Economic Co-operation and Development (NEA/OECD) and the Japan Nuclear Energy Safety (JNES) Organization. This paper presents an application of the joint Penn State University/Technical University of Madrid (UPM) version of the well-known sub-channel code COBRA-TF (Coolant Boiling in Rod Array-Two Fluid), namely, CTF, to the steady state critical power and departure from nucleate boiling (DNB) exercises of the OECD/NRC BFBT and PSBT benchmarks. The goal is two-fold: firstly, to assess these models and to examine their strengths and weaknesses; and secondly, to identify the areas for improvement.
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We apply well known nonlinear diffraction theory governing focusing of a powerful light beam of arbitrary shape in medium with Kerr nonlinearity to the analysis of femtosecond (fs) laser processing of dielectric in sub-critical (input power less than the critical power of selffocusing) regime. Simple analytical expressions are derived for the input beam power and spatial focusing parameter (numerical aperture) that are required for achieving an inscription threshold. Application of non-Gaussian laser beams for better controlled fs inscription at higher powers is also discussed. © 2007 Optical Society of America.
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Material processing using high-intensity femtosecond (fs) laser pulses is a fast developing technology holding potential for direct writing of multi-dimensional optical structures in transparent media. In this work we re-examine nonlinear diffraction theory in context of fs laser processing of silica in sub-critical (input power less than the critical power of self-focusing) regime. We have applied well known theory, developed by Vlasov, Petrishev and Talanov, that gives analytical description of the evolution of a root-mean-square beam (not necessarily Gaussian) width RRMS(z) in medium with the Kerr nonlinearity.
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Material processing using high-intensity femtosecond (fs) laser pulses is a fast developing technology holding potential for direct writing of multi-dimensional optical structures in transparent media. In this work we re-examine nonlinear diffraction theory in context of fs laser processing of silica in sub-critical (input power less than the critical power of self-focusing) regime. We have applied well known theory, developed by Vlasov, Petrishev and Talanov, that gives analytical description of the evolution of a root-mean-square beam (not necessarily Gaussian) width RRMS(z) in medium with the Kerr nonlinearity.