矿山岩体破坏微震分异速率特征及预警研究

在矿山岩体破坏预警研究中,探究岩体损伤特征规律及给出具体预警参数值对保障矿山安全至关重要。本文以某金属矿山为例,基于微震监测技术建立地压监测系统,结合该矿山某次顶板大范围冒落事件,采用主成分分析法确定最佳统计时间窗口,对顶板冒落事件前后微震时空演化特征进行分析。分析表明微震事件密度云图中心位置与破坏位置相一致,在岩体破坏前微震数量有持续增多,达到峰值后又迅速下降的前兆信息。以微震数量方差表示微震分异程度,以此表征岩体受损程度,采用有限差分法得出微震事件分异速率指标,研究表明岩体破坏过程微震分异速率分为稳定分异阶段、加速分异阶段和岩体破坏3个阶段。稳定分异阶段分异速率呈正态分布,采用Gauss Amp函数对其进行拟合,最终得出置信度为0.99的将区间上限0.306确定为分异速率预警值。该研究为采用微震监测技术的矿山灾害预警系统建立提供理论基础,对矿山安全生产管理具有一定借鉴意义。     

Spatiotemporal symmetry and multifractal structure of head movements during dyadic conversation.

This study examined the influence of sex, social dominance, and context on motion-tracked head movements during dyadic conversations. Windowed cross-correlation analyses found high peak correlation between conversants’ head movements over short (≈2-s) intervals and a high degree of nonstationarity. Nonstationarity in head movements was found to be positively related to the number of men in a conversation. Surrogate data analysis offsetting the conversants’ time series by a large lag was unable to reject the null hypothesis that the observed high peak correlations were unrelated to short-term coordination between conversants. One way that high peak correlations could be observed when 2 time series are offset by a large time lag is for each time series to exhibit self-similarity over a range of scales. Multifractal analysis found small-scale fluctuations to be persistent, τ(q) 0.5. These results are consistent with a view that symmetry is formed between conversants over short intervals and that this symmetry is broken at longer, irregular intervals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Three-dimensional analysis of boreholes considering spatial variability of properties and poroelastoplasticity

In general, analysis of oil producing wells is carried out considering that both hydraulic and mechanical parameters of the rock mass are deterministic. Mechanical and hydraulic properties of rock masses and in particular sedimentary rock masses may show a considerable degree of spatial variability. This paper focuses on the evaluation of the three-dimensional borehole response, particularly of the plastic zone, taking into account the spatial variability of both hydraulic and mechanical properties. The analysis is performed with a developed finite element program that incorporates spatial variability, coupled fluid-mechanical effects and elastoplastic behavior of the rock mass. Examples are shown and conclusions are drawn regarding the effect of spatial variability on the three-dimensional borehole analysis.     

Measuring people intensively.

An overview is provided of measures that are administered repeatedly in daily life. Variations of this methodology have been referred to as ecological momentary assessment, diary methods, daily process measures, and most broadly as intensive repeated measures in naturalistic settings (IRM-NS). Contrasts are drawn between IRM-NS methods on the basis of different sampling strategies, such as time-contingent recording, signal-contingent recording, and event-contingent recording. Common threats to the internal validity, construct validity, and external validity of IRM-NS measures are reviewed, along with ways to reduce these threats. The statistical analysis of IRM-NS data is considered, with a particular focus on the investigation of intraindividual variability. An extended example is provided of an IRM-NS measure, an event-contingent recording method for the assessment of interpersonal behaviour. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Variability reduction through optimal combination of wind/wave resources – An Irish case study

This study presents a methodology to assess the possible benefits of the combination of wind energy with the still unexploited, but quite significant in Ireland, wave energy. An analysis of the raw wind and wave resource at certain locations around the coasts of Ireland shows how they are very low correlated on the South and West Coast, where the waves are dominated by the presence of high energy swells generated by remote westerly wind systems. As a consequence, the integration of wind and waves in combined farms, at these locations, allows the achievement of a more reliable, less variable and more predictable electrical power production. The resulting benefits are particularly clear in the case of a relatively small and quite isolated electrical system such as the Irish one. Here, in fact, high levels of wind penetration strongly increase the requirement of surplus capacity and cause a much lower efficiency for conventional thermal plants.     

Evaluation and Improvement of a SVD-Based Empirical Atmospheric Model

T An empirical atmospheric model (EAM) based on the singular value decomposition (SVD) method is evaluated using the composite El Nino/Southern Oscillation (ENSO) patterns of sea surface temperature (SST) and wind anomalies as the target scenario. Two versions of the SVD-based EAM were presented for comparisons. The first version estimates the wind anomalies in response to SST variations based on modes that were calculated from a pair of global wind and SST fields (i.e., conventional EAM or CEAM). The second version utilizes the same model design but is based on modes that were calculated in a region-wise manner by separating the tropical domain from the remaining extratropical regions (i.e., region-wise EAM or REAM). Our study shows that, while CEAM has shown successful model performance over some tropical areas, such as the equatorial eastern Pacific (EEP), the western North Pacific (WNP), and the tropical Indian Ocean (TIO), its performance over the North Pacific (NP) seems poor. When REAM is used to estimate the wind anomalies instead of CEAM, a marked improvement over NP readily emerges. Analyses of coupled modes indicate that such an improvement can be attributed to a much stronger coupled variability captured by the first region-wise SVD mode at higher latitudes compared with that captured by the conventional one. The newly proposed way of constructing the EAM (i.e., REAM) can be very useful in the coupled studies because it gives the model a wider application beyond the commonly accepted tropical domain.     

Cost impact of dynamically managing generation reserves

Generation reserves are needed to maintain the real time balance between power supply and power demand. Because power is noninventoriable, power generation follows power demand. Demand for power varies considerably depending on the time of day, day of the week and season. The predictable portion of power demand is met by purchasing firm energy on a day ahead or real time market. The random unpredictable portion of demand is met by purchasing a set of online and offline generation reserves on an ancillary market. The total energy purchasing cost includes payments for firm energy and payments for generation reserves. The latter include fixed capacity payments for reserve generation capacities and variable payments for the random energy produced from these reserves. The main contribution of this paper is to present an optimization model that captures the dynamism in the selection of the dispatch interval to determine the amount of firm energy and reserve capacities given a set of market prices. This is done by explicitly including in the model the duration of the dispatch period and the frequency this decision is reevaluated. In this model the randomness of the demand is captured by using a Doubly Truncated Normal Distribution. The cost incurred to activate generation reserves is modeled as a Poisson process. The total model captures the price differences from using different reserve sources. An empirical example is presented to illustrate the cost benefits of using the method proposed in this research with two different strategies: a static strategy and a dynamic strategy. It is shown that dynamically setting generation reserves results in cost savings.     

Short communication: Changes in heart rate variability of dairy cows during conventional milking with nonvoluntary exit

Heart rate variability (HRV), as a physiological measure of animal welfare, was investigated in 36 cows milked in a parallel milking parlor with nonvoluntary exit. Heart rate variability parameters measured during the morning resting (baseline period) were compared with those measured during different stages of the entire milking process. No differences were found in HRV parameters between the baseline period, preparation, and main milking. A considerable reduction in vagal activity was detected during the movement of the cows to the milking parlor (driving) and while cows were in the holding area. The parasympathetic measures of HRV decreased whereas the sympatho-vagal balance increased compared with baseline. The same pattern was observed regarding the stage between removing the teat cups and leaving the milking parlor (waiting). No differences in any sympathetic measures were observed between the baseline period and any of the milking stages. These findings indicate that the milking process itself (preparation and main milking) is not stressful for cows. Decreased parasympathetic activity during driving might be the result of the physical activity of the cows, whereas waiting in the holding area and in the milking stall after milking caused stress for animals.     

Physiological compliance and team performance

Physiological compliance (PC) refers to the correlation between physiological measures of team members over time. The goals of this study were to examine ways of measuring PC in heart rate variability (HRV) data and the relationship between PC and team performance. Teams were tasked with entering both real and simulated rooms and “shooting” individuals with a weapon and identifying individuals without a weapon. The linear correlation and directional agreement PC methods were shown to be the most sensitive to differences in performance, with greater PC being associated with better performance. The correlation method when applied to a measure of respiratory sinus arrhythmia (RSA) revealed a significant difference between high and low performers (t[8] = −2.31, p = 0.03) and the directional agreement applied to inter-beat-intervals and RSA revealed trend-level differences (t[4.62] = −1.86, p = 0.06 and t[8] = −1.68, p = 0.07). These results suggest that PC may have merit for predicting team performance.     

Reliability indicator for layered composites with strongly non-linear behaviour

This paper set out a method to determine safety factors when designing composite laminate with strongly non-linear behaviour. The failure probability is used to assess the laminate reliability.