Influence of rest interval duration on muscular power production in the lower-body power profile

There is a paucity of evidence-based support for the allocation of rest interval duration between incremental loads in the assessment of the load-power profile. We examined the effect of rest interval duration on muscular power production in the load-power profile and sought to determine if greater rest is required with increasing load (i.e., variable rest interval). Ten physically trained men completed 4 experimental conditions in a crossover balanced design. Participants performed jump squats across incremental loads (0-60 kg) on 4 occasions, with an allocated recovery interval of 1, 2, 3, or 4 minutes. The mean log-transformed power output at each load was used for comparison between conditions (rest intervals). Unloaded jump squats (0 kg) maximized power output at each condition. The maximal mechanical power output was 66.6 ± 6.5 W·kg (1 minute), 66.2 ± 5.2 W·kg (2 minutes), 67.1 ± 5.9 W·kg (3 minutes), and 66.2 ± 6.5 W·kg (4 minutes). Trivial or unclear differences in power output were observed between rest intervals at each incremental load. As expected, power declined per 10 kg increment in load, the magnitude of decrease was 13.9-14.5% (confidence limits [CL]: ±1.3-2.0%) and 13.4-14.6% (CL: ±2.4-3.9%) for relative peak and mean power, respectively, yet differences in power output between conditions were likely insubstantial. The prescription of rest intervals between loads that are longer than 1 minute have a likely negligible effect on muscular power production in the jump squat incremental load-power profile. Practitioners should select either a 1- to 4-minute rest interval to best accommodate the logistical constraints of their monitoring sessions.

A rationale for assessing the lower-body power profile in team sport athletes

Training at the load that maximizes peak mechanical power (Pmax) is considered superior for the development of power. We aimed to identify the Pmax load ('optimal load') in the jump squat and to quantify small, moderate, large, and very large substantial differences in power output across a spectrum of loads to identify loads that are substantially different to the optimal, and lastly, to investigate the nature of power production (load-force-velocity profiles). Professional Australian Rules Football (ARF; n = 16) and highly trained Rugby Union (RU; n = 20) players (subdivided into stronger [SP] vs. weaker [WP] players) performed jump squats across incremental loads (0-60 kg). Substantial differences in peak power (W·kg(-1)) were quantified as 0.2-2.0 of the log transformed between-athlete SD at each load, backtransformed and expressed as a percent with 90% confidence limits (CL). A 0-kg jump squat maximized peak power (ARF: 57.7 ± 10.8 W·kg(-1); RU: 61.4 ± 8.5 W·kg(-1); SP: 64.4 ± 7.5 W·kg(-1); WP: 54.8 ± 9.5 W·kg(-1)). The range for small to very large substantial differences in power output was 4.5-55.9% (CL: ×/÷1.36) and 2.8-32.4% (CL: ×/÷1.31) in ARF and RU players, whereas in SP and WP, it was 3.7-43.1% (CL: ×/÷1.32) and 4.3-51.7% (CL: ×/÷1.36). Power declined per 10-kg increment in load, 14.1% (CL: ±1.6) and 10.5% (CL: ±1.5) in ARF and RU players and 12.8% (CL: ±1.9) and 11.3% (CL: ±1.7) in SP and WP. The use of a 0-kg load is superior for the development of jump squat maximal power, with moderate to very large declines in power output observed at 10- to 60-kg loads. Yet, performance of heavier load jump squats that are substantially different to the optimal load are important in the development of sport-specific force-velocity qualities and should not be excluded.

Combustion simulations for a self controlling variable compression ratio connecting rod

Variable compression ratio enables an engine to achieve increased efficiency at part loads, where the majority of driving occurs, without sacrificing full load power requirements or increasing the risk of engine knock. Although over 100 patents and patent applications exist none of these systems has been commercialized yet due to issues related to feasibility, cost and frictional loss. A new approach of a self controlling variable compression ratio connecting rod is presented that does not need a friction intensive external activation and that could even be retrofitted. The potential in fuel consumption and exhaust emission reduction as well as increased power and torque output for this concept has been verified in combustion simulations utilizing the latest research results related to the dynamic heat transfer in the combustion chamber from Professor Kleinschmidt from the University of Siegen, Germany. The self controlling variable compression ratio connecting rod allows the con rod to compress at high load conditions thereby increasing cylinder volume to alleviate combustion pressures and temperatures and therefore limit knock onset. The biggest efficiency gains can be achieved at medium load where the reduction of heat loss during the compression of the connecting rod plays a major role additional to the well known efficiency gains of an increased compression ratio. The combustion simulation results shows fuel consumption can be reduced by between 3% and 5% during part load and wide open throttle operation at various engine speeds. Emissions are also reduced significantly; particularly NOx and CO emissions were reduced by up to 35%.The self controlling variable compression ratio connecting rod allows the con rod to compress at high load conditions thereby increasing cylinder volume to alleviate combustion pressures and temperatures and therefore limit knock onset. The biggest efficiency gains can be achieved at medium load where the reduction of heat loss during the compression of the connecting rod plays a major role additional to the well known efficiency gains of an increased compression ratio.The combustion simulation results shows fuel consumption can be reduced by between 3% and 5% during part load and wide open throttle operation at various engine speeds. Emissions are also reduced significantly; particularly NOx and CO emissions were reduced by up to 35%.

A comparison of methods to calculate the optimal load for maximal power output in the power clean

The aim of this study was to compare three calculation methods to determine the load that maximises power output in the power clean. Five male athletes (height=179.8 10.5cms, weight 91 .8 8.8kg, power dean 1RM = 117.0 20.5kg) performed two per cleans at 10% increments from 50% to 100% of 1RM. Bar displacement data was collected using a Ballistic Measurement System (BMS) and vertical ground reaction force (VGRF) data was measured by a Kistler 9287B Force Plate. Power output was calculated for BMS (system mass), BMS (bar mass) and VGRF/BMS system mass. Optimal load was determined to be 70% for the BMS (system mass) and VGRF BMS (system mass) methods and 90% for the BMS (bar mass) method. Sports scientists should be aware of the technical issues underlying these findings due to the practical ramifications for athlete testing and training.

Short-term load and wind power forecasting using neural network-based prediction intervals

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Effects of load modeling in power distribution system with distributed wind generation

This paper presents the impact of different types of load models in distribution network with distributed wind generation. The analysis is carried out for a test distribution system representative of the Kumamoto area in Japan. Firstly, this paper provides static analysis showing the impact of static load on distribution system. Then, it investigates the effects of static as well as composite load based on the load composition of IEEE task force report [1] through an accurate time-domain analysis. The analysis shows that modeling of loads has a significant impact on the voltage dynamics of the distribution system with distributed generation.

Electricity load and price forecasting with influential factors in a deregulated power industry

With the emergence of smart power grid and distributed generation technologies in recent years, there is need to introduce new advanced models for forecasting. Electricity load and price forecasts are two primary factors needed in a deregulated power industry. The performances of the demand response programs are likely to be deteriorated in the absence of accurate load and price forecasting. Electricity generation companies, system operators, and consumers are highly reliant on the accuracy of the forecasting models. However, historical prices from the financial market, weekly price/load information, historical loads and day type are some of the explanatory factors that affect the accuracy of the forecasting. In this paper, a neural network (NN) model that considers different influential factors as feedback to the model is presented. This model is implemented with historical data from the ISO New England. It is observed during experiments that price forecasting is more complicated and hence less accurate than the load forecasting.

Optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers

For multiple heterogeneous multicore server processors across clouds and data centers, the aggregated performance of the cloud of clouds can be optimized by load distribution and balancing. Energy efficiency is one of the most important issues for large-scale server systems in current and future data centers. The multicore processor technology provides new levels of performance and energy efficiency. The present paper aims to develop power and performance constrained load distribution methods for cloud computing in current and future large-scale data centers. In particular, we address the problem of optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers. Our strategy is to formulate optimal power allocation and load distribution for multiple servers in a cloud of clouds as optimization problems, i.e., power constrained performance optimization and performance constrained power optimization. Our research problems in large-scale data centers are well-defined multivariable optimization problems, which explore the power-performance tradeoff by fixing one factor and minimizing the other, from the perspective of optimal load distribution. It is clear that such power and performance optimization is important for a cloud computing provider to efficiently utilize all the available resources. We model a multicore server processor as a queuing system with multiple servers. Our optimization problems are solved for two different models of core speed, where one model assumes that a core runs at zero speed when it is idle, and the other model assumes that a core runs at a constant speed. Our results in this paper provide new theoretical insights into power management and performance optimization in data centers.

Load frequency control of power systems with electric vehicles and diverse transmission links using distributed functional observers

This paper presents a load frequency control scheme using electric vehicles (EVs) to help thermal turbine units to provide the stability fluctuated by load demands. First, a general framework for deriving a state-space model for general power system topologies is given. Then, a detailed model of a four-area power system incorporating a smart and renewable discharged EVs system is presented. The areas within the system are interconnected via a combination of alternating current/high voltage direct current links and thyristor controlled phase shifters. Based on some recent development on functional observers, novel distributed functional observers are designed, one at each local area, to implement any given global state feedback controller. The designed observers are of reduced order and dynamically decoupled from others in contrast to conventional centralized observer (CO)-based controllers. The proposed scheme can cope better against accidental failures than those CO-based controllers. Extensive simulations and comparisons are given to show the effectiveness of the proposed control scheme.

The effect of laser power density on the fatigue life of laser-shock-peened 7050 aluminium alloy

Laser shock peening (LSP) is an innovative surface treatment method that can result in significant improvement in the fatigue life of many metallic components. The process produces very little or no surface profile modification while producing a considerably deeper compressive residual stress layer than traditional shot peening operations. The work discussed here was designed to: (a) quantify the fatigue life improvement achieved by LSP in a typical high strength aircraft aluminium alloy and (b) identify any technological risks associated with its use. It is shown that when LSP conditions are optimal for the material and specimen configuration, a —three to four times increase in fatigue life over the as-machined specimens could be achieved for a representative fighter aircraft loading spectrum when applied at a representative load level. However, if the process parameters are not optimal for the material investigated here, fatigue lives of LSP treated specimens may be reduced instead of increased due to the occurrence of internal cracking. This paper details the effect of laser power density on fatigue life of 7050-T7451 aluminium alloy by experimental and numerical analysis.

Design of a distributed power system stabiliser

A new design method for a distributed power system stabiliser for interconnected power systems is introduced in this paper. The stabiliser is of a low order, dynamic and robust. To generate the required local control signals, each local stabiliser requires information about either the rotor speed or the load angle of the other subsystems. A simple MATLAB based design algorithm is given and used on a three-machine unstable power system. The resulting stabiliser is simulated and sample results are presented.

Design of a distributed power system stabiliser

A new design method for a distributed power system stabiliser for interconnected power systems is introduced in this paper. The stabiliser is of a low order, dynamic and robust. To generate the required local control signals, each local stabiliser requires information about either the rotor speed or the load angle of the other subsystems. A simple MATLAB based design algorithm is given and used on a three-machine unstable power system. The resulting stabiliser is simulated and sample results are presented.

Power analysis and simulation of a vehicle under combined loads

This paper presents an analytical model of fuel consumption (AMFC) to coordinate the driving power and manage the overall fuel consumption for an internal combustion engine vehicle. The model calculates the different loads applied on the vehicle including road-slope, road-friction, wind-drag, accessories, and mechanical losses. Also, it solves the combustion equation of the engine under different working conditions including various fuel compositions, excess airs and air inlet temperatures. Then it determines the contribution of each load to signify the energy distribution and power flows of the vehicle. Unlike the conventional models in which the vehicle speed needs to be given as an input, the developed model can predict the vehicle speed and acceleration under different working conditions by allowing the speed to vary within a predefined range only. Furthermore, the model indicates the ways to minimises the vehicles' fuel consumption under various driving conditions. The results show that the model has the potential to assist in the vehicle energy management.

Effect of posture on high-intensity constant-load cycling performance in men and women

The time sustained during a graded cycle exercise is ~10% longer in an upright compared with a supine posture. However, during constant-load cycling this effect is unknown. Therefore, we tested the postural effect on the performance of high-intensity constant-load cycling. Twenty-two active subjects (11 men, 11 women) performed two graded tests (one upright, one supine), and of those 22, 10 subjects (5 men, 5 women) performed three high-intensity constant-load tests (one upright, two supine). To test the postural effect on performance at the same absolute intensity, during the upright and one of the supine constant-load tests subjects cycled at 80% of the peak power output achieved during the upright graded test. To test the postural effect on performance at the same relative intensities, during the second supine test subjects cycled at 80% of the peak power output achieved during the supine graded test. Exercise time on the graded and absolute intensity constant-load tests for all subjects was greater (P<0.05) in the upright compared with supine posture (17.9±3.5 vs. 16.1±3.1 min for graded; 13.2±8.7 vs. 5.2±1.9 min for constant-load). This postural effect at the same absolute intensity was larger in men (19.4±8.5 upright vs. 6.6±1.6 supine, P<0.001) than women (7.1±2 upright vs. 3.9±1.4 supine, P>0.05) and it was correlated (P<0.05) with both the difference in VO₂ between positions during the first minute of exercise (r=0.67) and the height of the subjects (r=0.72). In conclusion, there is a very large postural effect on performance during constant-load cycling exercise and this effect is significantly larger in men than women.