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使用数学功率平衡模型对不同地形上的越野滑雪进行模拟。

A simulation of cross-country skiing on varying terrain by using a mathematical power balance model.

作者信息

Moxnes John F, Sandbakk Oyvind, Hausken Kjell

机构信息

Department for Protection, Norwegian Defence Research Establishment, Kjeller, Norway.

Human Movement Science Program, Norwegian University of Science and Technology, Trondheim, Norway.

出版信息

Open Access J Sports Med. 2013 May 16;4:127-39. doi: 10.2147/OAJSM.S39843. eCollection 2013.

DOI:10.2147/OAJSM.S39843
PMID:24379718
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3872006/
Abstract

The current study simulated cross-country skiing on varying terrain by using a power balance model. By applying the hypothetical inductive deductive method, we compared the simulated position along the track with actual skiing on snow, and calculated the theoretical effect of friction and air drag on skiing performance. As input values in the model, air drag and friction were estimated from the literature, whereas the model included relationships between heart rate, metabolic rate, and work rate based on the treadmill roller-ski testing of an elite cross-country skier. We verified this procedure by testing four models of metabolic rate against experimental data on the treadmill. The experimental data corresponded well with the simulations, with the best fit when work rate was increased on uphill and decreased on downhill terrain. The simulations predicted that skiing time increases by 3%-4% when either friction or air drag increases by 10%. In conclusion, the power balance model was found to be a useful tool for predicting how various factors influence racing performance in cross-country skiing.

摘要

当前的研究通过使用功率平衡模型来模拟在不同地形上的越野滑雪。通过应用假设归纳演绎法,我们将沿赛道的模拟位置与在雪地上的实际滑雪进行了比较,并计算了摩擦和空气阻力对滑雪性能的理论影响。作为模型中的输入值,空气阻力和摩擦是根据文献估算的,而该模型包含了基于一名优秀越野滑雪运动员在跑步机上进行滚轮滑雪测试得出的心率、代谢率和工作率之间的关系。我们通过针对跑步机上的实验数据测试四种代谢率模型来验证这一程序。实验数据与模拟结果吻合良好,在上坡地形工作率增加而下坡地形工作率降低时拟合效果最佳。模拟结果预测,当摩擦或空气阻力增加10%时,滑雪时间会增加3%-4%。总之,功率平衡模型被发现是预测各种因素如何影响越野滑雪比赛成绩的有用工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/4f101ac0bc32/oajsm-4-127Fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/9746264083da/oajsm-4-127Fig1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/c1d9569bfb11/oajsm-4-127Fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/3aa926c057e5/oajsm-4-127Fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/c7ae42ada6e4/oajsm-4-127Fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/5f92764caaf7/oajsm-4-127Fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/4f101ac0bc32/oajsm-4-127Fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/9746264083da/oajsm-4-127Fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/035ce3334a0c/oajsm-4-127Fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/b136bf3a5306/oajsm-4-127Fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/c1d9569bfb11/oajsm-4-127Fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/3aa926c057e5/oajsm-4-127Fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/c7ae42ada6e4/oajsm-4-127Fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/5f92764caaf7/oajsm-4-127Fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ae31/3872006/4f101ac0bc32/oajsm-4-127Fig8.jpg

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