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Estimation of an Elite Road Cyclist Performance in Different Positions Based on Numerical Simulations and Analytical Procedures.

ABSTRACT: The aim of this study was to use numerical simulations and analytical procedures to compare a cyclist's performance in three different cycling positions. An elite level road cyclist competing at a national level was recruited for this research. The bicycle was 7 kg and the cyclist 55 kg. A 3D scan was taken of the subject on the competition bicycle, wearing race gear and helmet in the upright position, in the handlebar drops (dropped position) and leaning on the elbows (elbows position). Numerical simulations by computer fluid dynamics in Fluent CFD code assessed the coefficient of drag at 11.11 m/s. Following that, a set of assumptions were employed to assess cycling performance from 1 to 22 m/s. Drag values ranged between 0.16 and 99.51 N across the different speeds and positions. The cyclist mechanical power in the elbows position differed from the upright position between 0 and 23% and from the dropped position from 0 to 21%. The cyclist's energy cost in the upright position differed 2 to 16% in comparison to the elbows position and the elbows position had less 2 to 14% energy cost in comparison to the dropped position. The estimated time of arrival was computed for a 220,000 m distance and it varied between 7,715.03 s (2 h:8 min:24 s) and 220,000 s (61 h:6 min:40 s) across the different speeds and positions. In the elbows position, is expected that a cyclist may improve the winning time up to 23% in comparison to he upright and dropped position across the studied speeds.

SUBMITTER: Forte P

PROVIDER: S-EPMC7272685 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Project description:Computational modeling and simulation have become essential tools in the quest to better understand the brain's makeup and to decipher the causal interrelations of its components. The breadth of biochemical and biophysical processes and structures in the brain has led to the development of a large variety of model abstractions and specialized tools, often times requiring high performance computing resources for their timely execution. What has been missing so far was an in-depth analysis of the complexity of the computational kernels, hindering a systematic approach to identifying bottlenecks of algorithms and hardware. If whole brain models are to be achieved on emerging computer generations, models and simulation engines will have to be carefully co-designed for the intrinsic hardware tradeoffs. For the first time, we present a systematic exploration based on analytic performance modeling. We base our analysis on three in silico models, chosen as representative examples of the most widely employed modeling abstractions: current-based point neurons, conductance-based point neurons and conductance-based detailed neurons. We identify that the synaptic modeling formalism, i.e. current or conductance-based representation, and not the level of morphological detail, is the most significant factor in determining the properties of memory bandwidth saturation and shared-memory scaling of in silico models. Even though general purpose computing has, until now, largely been able to deliver high performance, we find that for all types of abstractions, network latency and memory bandwidth will become severe bottlenecks as the number of neurons to be simulated grows. By adapting and extending a performance modeling approach, we deliver a first characterization of the performance landscape of brain tissue simulations, allowing us to pinpoint current bottlenecks for state-of-the-art in silico models, and make projections for future hardware and software requirements.

Project description:BackgroundElite athletes may suffer from impaired immune function and gastro-intestinal (GI) symptoms, which may affect their health and may impede their performance. These symptoms may be reduced by multi-strain probiotic supplementation. Therefore, the aim of the current study is to examine the effects of probiotic supplementation on aerobic fitness characteristics, inflammatory markers and incidence and severity of GI symptoms in elite cyclists.MethodsTwenty-seven male cyclists, ranked elite or category 1 level competitions, were randomly assigned to a multi-strain probiotic-supplemented group (E, n = 11) or placebo group (C, n = 16). All participants visited the laboratory at the beginning of the study and following 90 d of supplementation/placebo. Prior to testing, all participants completed a GI symptoms questionnaire and underwent physical and medical examination, and anthropometric measurements. Venous blood was drawn for inflammatory markers analysis. The cyclists then underwent maximal oxygen consumption (VO2max) test and time-to-fatigue (TTF) test at 85 % of maximal power, 3 h following the VO2max test. All testing procedures were repeated after 90 d of probiotic / placebo treatment (double blind design).ResultsLower incidence of nausea, belching, and vomiting (P < 0.05) at rest, and decreased incidence of GI symptoms during training were found in E group vs. C Group, respectively (∆GI -0.27 ± 0.47 % vs. 0.08 ± 0.29 %, P = 0.03), no significant changes were observed in the incidence of total overall GI symptoms (∆GI -5.6 ± 14.7 % vs. 2.6 ± 11.6 %, P = 0.602) Mean rate of perceived exertion (RPE) values during the TTF were lower in E group (∆RPE: -0.3 ± 0.9 vs. 0.8 ± 1.5, P = 0.04). No significant changes were measured between and within groups in VO2max and TTF values, mean levels of C-reactive protein (CRP), IL-6-and tumor necrosis factor alpha (TNFα) values following treatment.ConclusionsProbiotics supplementation may have beneficial effects on GI symptoms in elite cyclists. Future studies, using higher doses and during different training seasons, might help understanding the effects of probiotic supplementation on elite athletes' health and performance.Trial registrationNIH clinicaltrial.gov #NCT02756221 Registered 25 April 2016.

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Estimation of an Elite Road Cyclist Performance in Different Positions Based on Numerical Simulations and Analytical Procedures.

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