scholarly journals Power profiling and the power-duration relationship in cycling: a narrative review

2021 ◽  
Author(s):  
Peter Leo ◽  
James Spragg ◽  
Tim Podlogar ◽  
Justin S. Lawley ◽  
Iñigo Mujika
Keyword(s):  
Data Analysis ◽  
Power Output ◽  
Performance Testing ◽  
Field Testing ◽  
Work Capacity ◽  
Threshold Power ◽  
Parameter Estimates ◽  
Practical Applications ◽  
Power Profiling ◽  
Duration Relationship

AbstractEmerging trends in technological innovations, data analysis and practical applications have facilitated the measurement of cycling power output in the field, leading to improvements in training prescription, performance testing and race analysis. This review aimed to critically reflect on power profiling strategies in association with the power-duration relationship in cycling, to provide an updated view for applied researchers and practitioners. The authors elaborate on measuring power output followed by an outline of the methodological approaches to power profiling. Moreover, the deriving a power-duration relationship section presents existing concepts of power-duration models alongside exercise intensity domains. Combining laboratory and field testing discusses how traditional laboratory and field testing can be combined to inform and individualize the power profiling approach. Deriving the parameters of power-duration modelling suggests how these measures can be obtained from laboratory and field testing, including criteria for ensuring a high ecological validity (e.g. rider specialization, race demands). It is recommended that field testing should always be conducted in accordance with pre-established guidelines from the existing literature (e.g. set number of prediction trials, inter-trial recovery, road gradient and data analysis). It is also recommended to avoid single effort prediction trials, such as functional threshold power. Power-duration parameter estimates can be derived from the 2 parameter linear or non-linear critical power model: P(t) = W′/t + CP (W′—work capacity above CP; t—time). Structured field testing should be included to obtain an accurate fingerprint of a cyclist’s power profile.

Physical Demands and Performance Indicators in Male Professional Cyclists During a Grand Tour: WorldTour Versus ProTeam Category

2021 ◽  
pp. 1-9
Author(s):  
Xabier Muriel ◽  
Pedro L. Valenzuela ◽  
Manuel Mateo-March ◽  
Jesús G. Pallarés ◽  
Alejandro Lucia ◽  
...  
Keyword(s):  
Power Output ◽  
Performance Indicators ◽  
Cycling Performance ◽  
Threshold Power ◽  
Grand Tour ◽  
Physical Demands ◽  
Physical Demand ◽  
Stress Score ◽  
And Performance ◽  
Training Stress

Purpose: To compare the physical demands and performance indicators of male professional cyclists of 2 different categories (Union Cycliste Internationale WorldTour [WT] and ProTeam [PT]) during a cycling grand tour. Methods: A WT team (n = 8, 31.4 [5.4] y) and a PT team (n = 7, 26.9 [3.3] y) that completed “La Vuelta 2020” volunteered to participate. Participants’ power output (PO) was registered, and measures of physical demand and physiological performance (kilojoules spent, training stress score, time spent at different PO bands/zones, and mean maximal PO [MMP] for different exertion durations) were computed. Results: WT achieved a higher final individual position than PT (31 [interquartile range = 33] vs 71 [59], P = .004). WT cyclists showed higher mean PO and kilojoule values than their PT peers and spent more time at high-intensity PO values (>5.25 W·kg−1) and zones (91%–120% of individualized functional threshold power) (Ps < .05). Although no differences were found for MMP values in the overall analysis (P > .05), subanalyses revealed that the between-groups gap increased through the race, with WT cyclists reaching higher MMP values for ≥5-minute efforts in the second and third weeks (Ps < .05). Conclusions: Despite the multifactorial nature of cycling performance, WT cyclists spend more time at high intensities and show higher kilojoules and mean PO than their PT referents during a grand tour. Although the highest MMP values attained during the whole race might not differentiate between WT and PT cyclists, the former achieve higher MMP values as the race progresses.

scholarly journals Three-dimensional stable lithium metal anode with nanoscale lithium islands embedded in ionically conductive solid matrix

2017 ◽  
Vol 114 (18) ◽  
pp. 4613-4618 ◽  
Author(s):  
Dingchang Lin ◽  
Jie Zhao ◽  
Jie Sun ◽  
Hongbin Yao ◽  
Yayuan Liu ◽  
...  
Keyword(s):  
High Power ◽  
Power Output ◽  
Three Dimensional ◽  
Rechargeable Batteries ◽  
Solid Matrix ◽  
Side Reactions ◽  
Surface Protection ◽  
Metal Anode ◽  
Practical Applications ◽  
Significant Step

Rechargeable batteries based on lithium (Li) metal chemistry are attractive for next-generation electrochemical energy storage. Nevertheless, excessive dendrite growth, infinite relative dimension change, severe side reactions, and limited power output severely impede their practical applications. Although exciting progress has been made to solve parts of the above issues, a versatile solution is still absent. Here, a Li-ion conductive framework was developed as a stable “host” and efficient surface protection to address the multifaceted problems, which is a significant step forward compared with previous host concepts. This was fulfilled by reacting overstoichiometry of Li with SiO. The as-formed LixSi–Li2O matrix would not only enable constant electrode-level volume, but also protect the embedded Li from direct exposure to electrolyte. Because uniform Li nucleation and deposition can be fulfilled owing to the high-density active Li domains, the as-obtained nanocomposite electrode exhibits low polarization, stable cycling, and high-power output (up to 10 mA/cm2) even in carbonate electrolytes. The Li–S prototype cells further exhibited highly improved capacity retention under high-power operation (∼600 mAh/g at 6.69 mA/cm2). The all-around improvement on electrochemical performance sheds light on the effectiveness of the design principle for developing safe and stable Li metal anodes.

scholarly journals Analisis Pengaruh Perubahan Beban Generator Terhadap Efsiensi Kinerja PLTU Bosowa Energi Jeneponto Unit 2

2021 ◽  
Vol 18 (2) ◽  
pp. 241
Author(s):  
Andreas Pangkung ◽  
Herman Nawir ◽  
Aditya Nugraha Adji Santoso
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Fuel Consumption ◽  
Power Output ◽  
Power Plants ◽  
Calorific Value ◽  
Input Power ◽  
Steam Power ◽  
Steam Power Plants ◽  
Efficiency Performance

This study aims to determine the effect of changes in generator load on efficiency performance in steam power plants and to determine the amount of input power in the boiler. Data collection was carried out at PT. Bosowa Energi PLTU Jeneponto. The data are the power output, fuel consumption, and the calorific value of the fuel. Then perform data analysis by calculating input power and efficiency. From the result of the study, the highest efficiency is on May 20, 2018 at 18.00 with a load of 90.00 MW, namely 55.68% and the lowest efficiency is on May 12, 2018 at 03.00 with a load of 64.98 MW, namely 22.69%. The highest boiler input power based on the analysis results was on May 3, 2018 at 20.00, namely 356.61 MW, and the lowest boiler input power based on the analysis was on May 15, 2018 at 07.00, namely 128.14 MW.

scholarly journals How to improve parameter estimates in GLM-based fMRI data analysis: cross-validated Bayesian model averaging

2016 ◽  
Author(s):  
Joram Soch ◽  
Achim Pascal Meyer ◽  
John-Dylan Haynes ◽  
Carsten Allefeld
Keyword(s):  
Data Analysis ◽  
Model Selection ◽  
Bayesian Model ◽  
Bayesian Model Averaging ◽  
Model Averaging ◽  
Bayesian Model Selection ◽  
Fmri Data ◽  
Parameter Estimates ◽  
Fmri Data Analysis ◽  
Level Analysis

AbstractIn functional magnetic resonance imaging (fMRI), model quality of general linear models (GLMs) for first-level analysis is rarely assessed. In recent work (Soch et al., 2016: “How to avoid mismodelling in GLM-based fMRI data analysis: cross-validated Bayesian model selection”, NeuroImage, vol. 141, pp. 469-489; DOI: 10.1016/j. neuroimage.2016.07.047), we have introduced cross-validated Bayesian model selection (cvBMS) to infer the best model for a group of subjects and use it to guide second-level analysis. While this is the optimal approach given that the same GLM has to be used for all subjects, there is a much more efficient procedure when model selection only addresses nuisance variables and regressors of interest are included in all candidate models. In this work, we propose cross-validated Bayesian model averaging (cvBMA) to improve parameter estimates for these regressors of interest by combining information from all models using their posterior probabilities. This is particularly useful as different models can lead to different conclusions regarding experimental effects and the most complex model is not necessarily the best choice. We find that cvBMS can prevent not detecting established effects and that cvBMA can be more sensitive to experimental effects than just using even the best model in each subject or the model which is best in a group of subjects.

Experience with Field Testings of SHE on Research Catchments

1984 ◽  
Vol 15 (4-5) ◽  
pp. 283-294 ◽  
Author(s):  
Børge Storm ◽  
K. Høgh Jensen
Keyword(s):  
New Zealand ◽  
Soil Water ◽  
Flow Model ◽  
Complete System ◽  
Field Testing ◽  
Practical Applications ◽  
Extensive Field ◽  
Soil Water Flow ◽  
Hydrologic System ◽  
The Individual

The development of the European Hydrologic System (SHE) has now reached such a stage, that it is ready for practical applications. Extensive field testings and associated developments have been carried out in recent years. The testings have included the complete system as well as the individual components. Particular emphasis has been given to the development and testing of the soil water flow model. The paper demonstrates results from a field testing of SHE on the Wye Catchment in Britain, as well as examples of applications on small experimental catchments in Germany and New Zealand.

Spatial Effects and Ecological Inference

2002 ◽  
Vol 10 (3) ◽  
pp. 276-297 ◽  
Author(s):  
Luc Anselin ◽  
Wendy K. Tam Cho
Keyword(s):  
Data Analysis ◽  
Spatial Autocorrelation ◽  
Random Coefficient ◽  
Parameter Estimates ◽  
Spatial Effects ◽  
Ecological Inference ◽  
Simulation Experiments ◽  
Coefficient Variation ◽  
Inference Methods

This paper examines the role of spatial effects in ecological inference. Both formally and through simulation experiments, we consider the problems associated with ecological inference and cross-level inference methods in the presence of increasing degrees of spatial autocorrelation. Past assessments of spatial autocorrelation in aggregate data analysis focused on unidimensional, one-directional processes that are not representative of the full complexities caused by spatial autocorrelation. Our analysis is more complete and representative of true forms of spatial autocorrelation and pays particular attention to the specification of spatial autocorrelation in models with random coefficient variation. Our assessment focuses on the effects of this specification on the bias and precision of parameter estimates.

Integrating Experimental Data Analysis Through Online Modules

2013 ◽  
Author(s):  
Kumer V. Singh ◽  
Fazeel Khan ◽  
Neal S. Birchfield
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
Student Perceptions ◽  
Mechanical Vibration ◽  
Mode Shapes ◽  
Wide Audience ◽  
Practical Applications ◽  
Learning Modules ◽  
Assessment Plans ◽  
Experimental Data Analysis

In various universities, including Miami University (MU), an undergraduate course in vibrations may be offered in a lecture-only format. However, several concepts in vibrations, such as natural frequencies, damping, mode shapes etc., may be improved immensely from experimental demonstrations and hands-on activities for students to fully grasp the concept and its application. In recent years, several online experiments and resources have been developed in the area of dynamical systems and controls in order to provide an experiential learning environment. With the support of the National Science Foundation, a series of Computational-Experimental (ComEx) learning modules are being developed for integrating experimental, computational and validation studies in the mechanical and manufacturing engineering curriculum at MU. These learning modules are web based and are intended for dissemination to a wide audience extending beyond the students at MU. In this paper, salient features of these online learning modules, which integrate experimental data analysis for mechanical vibration course, are presented. Three different group activities associated with these modules are presented with specific details of the activities, assessment plans, and student perceptions of the modules. The content of these modules is evolving based on feedback from students and external, expert evaluators. It is anticipated that such learning studios can be used by instructors who teach lecture based vibration and control courses, and this resource will yield more insight into the theory, computation and practical applications of essential concepts in this area.

Theoretical and experimental studies of a piezoelectric ring energy harvester

2019 ◽  
Vol 30 (7) ◽  
pp. 998-1009 ◽  
Author(s):  
XF Zhang ◽  
HS Tzou
Keyword(s):  
Energy Harvesting ◽  
Power Output ◽  
Output Voltage ◽  
Laboratory Experiments ◽  
Electromechanical Coupling ◽  
Energy Harvester ◽  
Experimental Studies ◽  
Design Parameters ◽  
Resistive Load ◽  
Practical Applications

Based on the electromechanical coupling of piezoelectricity, a piezoelectric ring energy harvester is designed and tested in this study, such that the harvester can be used to power electric devices in the closed-circuit condition. Output energies across the external resistive load are evaluated when the ring energy harvester is subjected to harmonic excitations, and various design parameters are discussed to maximize the power output. In order to validate the theoretical energy harvesting results, laboratory experiments are conducted. Comparing experiment results with theoretical ones, the errors between them are under 10% for the output voltage. Laboratory experiments demonstrate that the ring energy harvester is workable in practical applications.

Research on Portable Field-Testing Device of Infrared Thermal Imager Performance

2013 ◽  
Vol 823 ◽  
pp. 354-357
Author(s):  
Xiao Dan Gao
Keyword(s):  
Performance Test ◽  
Low Cost ◽  
Performance Testing ◽  
Field Testing ◽  
Infrared Light ◽  
Optical Parameters ◽  
Thermal Imager ◽  
Testing Device ◽  
Temperature Feedback ◽  
Infrared Thermal Imager

Performance test of infrared thermal imager is very significant for its working life and field maintenance, but available test equipment is huge volume, strict requirements for environment and user, high cost in use. According to the deficiency of field testing of infrared thermal imager performance, the method was put forward that using high precise temperature feedback controlled thermoelectric cooling module to instead expensive blackbody furnace. The techniques were adopted in the method such as infrared light signals simulation, optical-electric signals auto-detecting, image processing and the fusion of multi-detecting signals. The performance testing device of infrared thermal imager with low cost, convenient to field testing and maintenance was designed, the design broke the traditional model that the test of infrared thermal imager must be under the given condition, and the testing of electric and optical parameters should be separated. Keywords:infrared thermal imager; performance test; simulating infrared target; temperature feedback control

Optimal Sensor Placement Methodology for Identification with Unmeasured Excitation

2001 ◽  
Vol 123 (4) ◽  
pp. 677-686 ◽  
Author(s):  
Ka-Veng Yuen ◽  
Lambros S. Katafygiotis ◽  
Costas Papadimitriou ◽  
Neil C. Mickleborough
Keyword(s):  
Structural Model ◽  
Model Updating ◽  
Cost Effective ◽  
Ambient Vibration ◽  
Entropy Measure ◽  
Parameter Estimates ◽  
Earthquake Excitation ◽  
Practical Applications ◽  
Ambient Vibration Tests ◽  
Sensor Configuration

A methodology is presented for designing cost-effective optimal sensor configurations for structural model updating and health monitoring purposes. The optimal sensor configuration is selected such that the resulting measured data are most informative about the condition of the structure. This selection is based on an information entropy measure of the uncertainty in the model parameter estimates obtained using a statistical system identification method. The methodology is developed for the uncertain excitation case encountered in practical applications for which data are to be taken either from ambient vibration tests or from other uncertain excitations such as earthquake and wind. Important issues related to robustness of the optimal sensor configuration to uncertainties in the structural model are addressed. The theoretical developments are illustrated by designing the optimal configuration for a simple 8-DOF chain-like model of a structure subjected to an unmeasured base excitation and a 40-DOF truss model subjected to wind/earthquake excitation.

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