Pro-agility unpacked: Variability, comparability and diagnostic value

Change of direction (COD) is an important component of athlete performance and measuring and comparing athletes is an integral aspect of strength and conditioning practice. This article aimed to determine pro-agility shuttle utility, by quantifying variability and normative values for different sports, skill-levels and positions. Limitations of the pro-agility shuttle are identified, as are future research directions. A total of 67 studies were included for review. Pro-agility shuttle reliability was reported in 10 studies across 6 sports; however, comprehensive reliability statistics were absent in most papers. Additionally, only reliability of total-time from stopwatch and timing lights were reported. Data of 32,891 subjects in 12 sports (American football, basketball, cricket, general athletes, hockey, lacrosse, recreational athletes, resistance-trained athletes, rugby, soccer, swimming, and tennis) were extracted and aggregated, establishing sport, skill-level (elite, sub-elite, and novice) and positional normative values, where practical. Elite athletes showed the fastest performance times, whereas sub-elite and novice athletes showed similar spreads in performance, suggesting similar athletic capabilities. In conclusion, the pro-agility shuttle currently has limited diagnostic value and the variability of smaller performance sub-components within pro-agility shuttle should be examined. Furthermore, the value of other technologies such as smart phone, inertial sensor or radar should be investigated.

A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties

In reliability-based multidisciplinary design optimization, both aleatory and epistemic uncertainties may exist in multidisciplinary systems simultaneously. The uncertainty propagation through coupled subsystems makes multidisciplinary reliability analysis computationally expensive. In order to improve the efficiency of multidisciplinary reliability analysis under aleatory and epistemic uncertainties, a comprehensive reliability index that has clear geometric meaning under multisource uncertainties is proposed. Based on the comprehensive reliability index, a sequential multidisciplinary reliability analysis method is presented. The method provides a decoupling strategy based on performance measure approach (PMA), probability theory and convex model. In this strategy, the probabilistic analysis and convex analysis are decoupled from each other and performed sequentially. The probabilistic reliability analysis is implemented sequentially based on the concurrent subspace optimization (CSSO) and PMA, and the non-probabilistic reliability analysis is replaced by convex model extreme value analysis, which improves the efficiency of multidisciplinary reliability analysis with aleatory and epistemic uncertainties. A mathematical example and an engineering application are demonstrated to verify the effectiveness of the proposed method.

Impact of Large-Scale Mobile Electric Vehicle Charging in Smart Grids: A Reliability Perspective

The charging load of electric vehicles (EVs) is characterized by uncertainty and flexibility, which burdens the distribution network, especially when there is a high penetration of distributed generation (DG) in smart grids. Large-scale EV mobility integration not only affects smart grid operation reliability but also the reliability of EV charging services. This paper aims at estimating the comprehensive impacts caused by spatial-temporal EV charging from the perspective of both electricity system reliability and EV charging service reliability. First, a comprehensive reliability index system, including two novel indexes quantifying EV charging service reliability, is proposed. Then, considering traffic constraints and users’ charging willingness, a spatial-temporal charging load model is introduced. In the coupled transportation and grid framework, the reliability impacts from plenty of operation factors are analyzed. Moreover, the electricity system reliability and EV charging service reliability correlated with DG integration are discussed. A coupled transportation grid system is adopted to demonstrate the effectiveness and practicability of the proposed method. The numerical results analyze reliability impacts from EV penetration level, trip chain, EV battery capacity, DG installation location, and capacity. The proposed studies reveal that when the EV capacity ratio to DG capacity is 3:1, the system reliability reaches the maximum level.

Fault-Tolerant Computing with Heterogeneous Hardening Modes

Fault-tolerance using (full-scale) redundancy-based techniques has been employed to detect and correct reliability errors (i.e., soft errors), but they pose significant area and power overhead. On the other hand, due to the masking and the error tolerance properties at different system layers and of different applications, respectively, reliable heterogeneous architectures have been emerged as an attractive design choice for power-efficient dependable computing platforms. This chapter discusses the building blocks of such computing systems, based on both embedded and superscalar processors, with different reliability (fault-tolerant) modes at the architecture layer to memories like caches, for heterogeneous in-order and out-of-order processors. We provide a comprehensive reliability, i.e., soft error, vulnerability analysis of different components in in-order and out-of-order processors, e.g., caches. We also discuss different methodologies to improve the performance and power of such a system by analyzing these vulnerabilities. Moreover, we show how such heterogeneous hardware-level hardening modes can further be complemented by software-level techniques that can be realized using a reliability-driven compiler (as introduced in Chapter “Dependable Software Generation and Execution on Embedded Systems”).

Application of the Methods for Comprehensive Reliability Analysis of District Heating Systems

The general idea of the methodology for the comprehensive reliability analysis of district heating systems (DHS), developed earlier by the author of this paper, is a joint considering and modelling of each technological processes, including fuel supply to heat sources (HS), generation of heat energy by these HS and its distribution on district heating network (HN). For solving this problem different methods and models are applied: statistical testing method, Markov random processes, methods of the theory of hydraulic circuits, basic laws of district heating and heat transfer processes, etc. In this paper the main attention is paid to the results of the practical application of methods and models of a comprehensive reliability analysis of DHS using the example of calculations performed for the actual DHS scheme of the Shelekhov city (Irkutsk region, Russia). Different stages of the case study are considered, including preparation of initial data, simulation modelling of fuel supply to HS, modelling of the Markov random process describing operate of DHS, calculation of post-failure modes in HN, evaluation of nodal reliability indices (RI), decomposition analysis of reliability. Based on the analysis of calculation results some preliminary directions are formulated to the increase of reliability for studied DHS. These data are the basis for a comprehensive reliability synthesis (optimization) of DHS, the solution of which is the subject of special perspective stage in development of the research.

Improved Semi-Quantitative Reliability-Based Method for Assessment of Pipeline Dents With Stress Risers

Dents, especially those interacting with stress risers, can pose integrity threats to pipeline systems. Regulations in Canada and the United States mandate the repair of dents based on depth and interaction with stress risers, however, there have been cases in the past where dents that have passed these criteria have ended up in loss of containment. Recent industry’s recommendations regarding dent integrity analysis are predominantly based on strain, and the dent-fatigue models have been proven to be limited in their application. Additionally, these models or methodologies are generally deterministic which may not fully account for uncertainties associated with pipe properties and in-line inspection (ILI) tool measurement. Enbridge Liquid Pipelines Inc. had previously presented a framework to support system wide dent assessment with an efficient probabilistic-based calibrated semi-quantitative analysis method for dents (SQuAD), which elicits potentially injurious features from thousands of features within a system in a reasonable analysis timeframe. This paper expands on the authors’ previous work and presents several improvements that have since been made to the SQuAD model to address the limitations in the initial version of the model. The previous version of SQuAD was strain-based and did not explicitly account for pressure-cycling induced, fatigue-based failure quantitatively. An approximate circle fitting method was adopted for estimating the dent’s radii of curvature in order to calculate strains. In the improved model, filtering techniques have been employed to reduce the noise in the ILI-reported data while preserving the dent shape. Furthermore, a simplified FEA process has been developed to calculate the stresses within a dent due to pressure cycles, thus the fatigue-based Probability of Failure (PoF) of a dent can now be estimated using S-N approach. The filtered data allows for better accuracy in quantifying the radius of curvature of dents as reported by ILI tools, which are used for calculating dent strain as recommended in the updated version of ASME B31.8, Appendix R. Finally, the feasibility of applying this improved SQuAD model is discussed from an operator’s perspective. The improvements allow the enhanced SQuAD model to be used as an effective screening tool on a system-wide basis as part of a comprehensive, reliability-based dent assessment framework.