Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

非常规气藏储层改造体积评价方法研究

为精确描述非常规气藏压裂后的复杂流动特征及定量评价储层改造体积（SRV），利用自主研发的缝网重构算法“破裂树生长法”建立压后缝网模型，并以此为基础提出了使用拟稳态流动时特定的压力等值线来确定SRV范围的定量评价方法，最后以长宁201井区为例进行了矿场实例分析。该方法根据微地震监测点的位置，重构出微裂缝网的连通关系。在复杂微裂缝网的基础上建立离散裂缝地质模型并进行生产数值模拟，根据数值模拟结果的压力分布精确划定SRV的范围。利用该方法计算出长宁201井区的SRV体积为0.052 1 km3，以该缝网模型的数值模拟产量预测结果符合实际生产规律，方法实用性较好。     

Predictive environmental hydrogen embrittlement on fracture toughness of commercial ferritic steels with hydrogen-modified fracture strain model

In this work, a practical numerical model with few parameters was proposed for the prediction of environmental hydrogen embrittlement. The proposed method adopts hydrogen enhanced plasticity-based mechanism in a fracture strain model to describe hydrogen embrittlement. Fracture toughness degradation of three commercial steels SA372J70, AISI4130 and X80 in high pressure hydrogen environment were investigated. Firstly, governing equations for hydrogen distribution and material damage evolution was established. Hydrogen enhanced localized flow softening effect was coupled within fracture strain dependency on stress triaxiality. Then, the numerical implementation and identification process of model parameters was described. Model parameters of the investigated steels were determined based on experiment results from literatures. Finally, with the calibrated model, fracture toughness reduction of the steels was predicted in a wide range of hydrogen pressure. The prediction results were compared with experimental results. Reasonable accuracy was reached. The proposed method is an attempt to reach balance between physical accurate prediction and engineering practicality. It is promising to provide a simplified numerical tool for the design and fit for service evaluation of hydrogen storage vessels.     

Experimental study and model predictions on helium release in an enclosure with single or multiple vents

This paper presents experiments performed at Canadian Nuclear Laboratories (CNL) to examine the dispersion behaviour of helium in a polycarbonate enclosure that was representative of a residential parking garage. The purpose was to gain a better understanding of the effect of buoyancy- or wind-driven natural ventilation on hydrogen dispersion behaviour. Although hydrogen dispersion studies have been reported extensively in the literature, gaps still exist in predictive methods for hazard analysis. Helium, a simulant for hydrogen, was injected near the centre of the floor with a flow rate ranging from 5 to 75 standard litres per minute through an upward-facing nozzle, resulting in an injection Richardson number ranging between 10^?1 and 10². The location of the nozzle varied from the bottom of the enclosure to near the ceiling to examine the impact of the nozzle elevation on the development of a stratified layer in the upper region of the enclosure. When the injection nozzle was placed at a sufficiently low elevation, the vertical helium profile always consisted of a homogenous layer at the top overlaying a stratified layer at the bottom. To simulate outdoor environmental conditions, a fan was placed in front of each vent to examine the effect of opposing or assisting wind on the dispersion. The helium transients in the uniform layer predicted with analytical models were in good agreement with the measured transients for most tests. Model improvements are required for adequately predicting transients with primarily stratified profiles or strong opposing wind.     

Removing data and using metafounders alleviates biases for all traits in Lacaune dairy sheep predictions

Bias in dairy genetic evaluations, when it exists, has to be understood and properly addressed. The origin of biases is not always clear. We analyzed 40 yr of records from the Lacaune dairy sheep breeding program to evaluate the extent of bias, assess possible corrections, and emit hypotheses on its origin. The data set included 7 traits (milk yield, fat and protein contents, somatic cell score, teat angle, udder cleft, and udder depth) with records from 600,000 to 5 million depending on the trait, ～1,900,000 animals, and ～5,900 genotyped elite artificial insemination rams. For the ～8% animals with missing sire, we fit 25 unknown parent groups. We used the linear regression method to compare “partial” and “whole” predictions of young rams before and after progeny testing, with 7 cut-off points, and we obtained estimates of their bias, (over)dispersion, and accuracy in early proofs. We tried (1) several scenarios as follows: multiple or single trait, the “official” (routine) evaluation, which is a mixture of both single and multiple trait, and “deletion” of data before 1990; and (2) several models as follows: BLUP and single-step genomic (SSG)BLUP with fixed unknown parent groups or metafounders, where, for metafounders, their relationship matrix gamma was estimated using either a model for inbreeding trend, or base allele frequencies estimated by peeling. The estimate of gamma obtained by modeling the inbreeding trend resulted in an estimated increase of inbreeding, based on markers, faster than the pedigree-based one. The estimated genetic trends were similar for most models and scenarios across all traits, but were shrunken when gamma was estimated by peeling. This was due to shrinking of the estimates of metafounders in the latter case. Across scenarios, all traits showed bias, generally as an overestimate of genetic trend for milk yield and an underestimate for the other traits. As for the slope, it showed overdispersion of estimated breeding values for all traits. Using multiple-trait models slightly reduced the overestimate of genetic trend and the overdispersion, as did including genomic information (i.e., SSGBLUP) when the gamma matrix was estimated by the model for inbreeding trend. However, only deletion of historical data before 1990 resulted in elimination of both kind of biases. The SSGBLUP resulted in more accurate early proofs than BLUP for all traits. We considered that a snowball effect of small errors in each genetic evaluation, combined with selection, may have resulted in biased evaluations. Improving statistical methods reduced some bias but not all, and a simple solution for this data set was to remove historical records.     

Liquefaction behavior of fiber-reinforced calcareous sands in unidirectional and multidirectional simple shear tests

A study on the liquefaction resistance of calcareous sands reinforced with polypropylene fibers was reported. Stress-controlled cyclic simple shear tests were conducted on specimens prepared at a relative density of 50%, with and without fiber reinforcements. The liquefaction behavior was investigated by considering the effects of fiber contents ranging from 0% to 1%, fiber lengths varying from 3 mm to 12 mm and loading patterns. The results indicated that increasing fiber content and fiber length resulted in a decrease in the deformation, a reduction in pore pressure accumulation rate, and improved the liquefaction resistance of calcareous sands. Additionally, the risk of soil liquefaction could be significantly reduced when the fiber content was greater than 0.8%. The multidirectional loading had a considerable effect in reducing the liquefaction resistance compared to unidirectional loading. Further, the stiffness degradation of calcareous sands decreased with increasing fiber content and fiber length. The pore pressure generated in the cyclic tests was analyzed and was found to be affected by fiber content. A pore pressure prediction model was proposed to obtain the pore pressure characteristics of fiber-reinforced calcareous sands under various fiber content conditions.     

风险矩阵法在A水泥工厂风险分级的应用初探

本文介绍“风险矩阵法”进行风险分级工作的基本思路，结合水泥厂的生产特点通过危险有害因素辨识，获得危险源分布情况，采用风险矩阵法对风险进行评估，按风险值将风险等级划分为重大风险、较大风险、一般风险和低风险，为水泥生产企业的安全风险分级工作提供参考。     

地表径流速度对城市内涝影响规律

为分析地表径流速度对城市内涝的影响,采用一维地下排水管网与二维城区地形的动态耦合模型,选取大连市某排水区块作为研究区域,设置4种地表径流速度10种设计降雨场景,模拟分析在不同重现期设计降雨及不同地表径流速度下研究区的内涝积水特性。结果表明:随着地表径流速度降低,管道排水压力变小,管道排水达标率最高可提升48.05%,且降雨重现期越短,地表径流流速对管道排水压力的削减效果越明显;地表径流流速对检查井溢流量影响显著,随着地表径流速度降低,检查井溢流量峰值最高可减小2 750 m~3,峰现时间最长可滞后56 min,同时随着降雨重现期增长,地表径流流速对检查井溢流量的削减效果减弱;研究区低、高风险区淹没面积随地表径流速度降低,最高可分别减小1.64万、8.37万m~2,但中风险区淹没面积变化反复。     

一种基于实时几何测距的船桥主动防撞方法

本文提出一种基于实时几何测距的船桥主动防撞方法。该方法对船的改动量甚微,仅需维持多项距离矩阵,通过告警逻辑矩阵进行展示与告警,能起到很好的船桥防撞提示效果。