多源数据协同定量遥感产品生产系统的领域模型

大数据技术中的一个难点是如何统筹多源异构的数据。在多源数据协同定量遥感产品生产系统中,不同传感器数据的协同使用为生产系统的各个环节都带来了许多的问题,例如异构数据文件的统一表示和调度,繁杂生产流程的统一抽象等。领域驱动设计是一种应对软件核心复杂性的设计方式。领域驱动是指在设计过程中经过不断的迭代,逐渐提炼出一套灵活优雅的领域模型。领域模型专注于分析问题领域本身,发掘重要的业务领域概念,并建立业务领域概念之间的关系。本文在不断实践的基础上提出了一组较成熟的领域模型,该模型用一种统一的方式解决了多源数据协同生产系统中各方面的问题,并显著地降低了系统集成的难度和工作量,且为新数据源的加入预留了灵活性。     

基于光谱特征的月球岩性分类方法研究——以Apollo 16登月区域为例

利用NASA行星数据系统提供Apollo计划登月点采样线路影像数据,通过与嫦娥二号CCD数据、印度M~3数据空间校正获得采样路线坐标。开展嫦娥二号CCD数据与印度M~3数据MAP(后验概率)融合并选择Apollo 15、Apollo 16-62231的LSCC测得的标准岩石双向反射率光谱与M~3、嫦娥二号进行交叉定标。本文采用月球岩石光谱谱型全特征分析方法,选取涵盖Apollo计划登月获取的36个基站主要岩性87种、285件岩石样品,利用校正后的M~3数据分析月球典型岩石各阶吸收反射特征,建立月球典型岩石标准遥感影像光谱库,此后应用Apollo 623个岩石样品进行对比得到很好结果,同时完成Apollo 16登月点周围领域岩性分布图,并讨论了研究区的岩石成因,Apollo 16区域形成于高地大撞击,在早期的研究中已经被用于划分月球年代,本文方法对于月球岩石类别研究与理解月球的岩浆演化具有重要的研究价值。     

Stability and capsizing analysis of nonlinear ship rolling in wind and stochastic beam seas

Considering the actual seaway condition, stability and capsizing of nonlinear ship rolling system in stochastic beam seas is of significant importance for voyage safety. Safe zone are defined in the phase space plan of the unperturbed Hamilton system to qualitatively distinguish ship motions as capsize and noncapsize. Capsize events are defined by solutions passing out of the safe zone. The probability of such an occurrence is studied by virtue of the random Melnikov function and the concept of phase space flux. In this paper, besides conventional wave excitation, the effect of wind load is also taken into account. The introduction of wind load will lead to asymmetry, in other words, it transforms the symmetric heteroclinic orbits into asymmetric homoclinic orbits. For asymmetric dynamical system, the orbital analytic solutions and its power spectrum are not readily available, and the technique of discrete time Fourier transformation (DTFT) is used. In the end, as verification of theoretical critical significant wave height, capsizing probability contour diagram is generated by means of numerical simulation. The contour diagram shows that these analytical methods provide reliable and predictive results about the likelihood of a vessel capsizing in a given seaway condition.     

Oil dispersal modelling: reanalysis of the Rena oil spill using open-source modelling tools

ABSTRACT

Oil spill forecast modelling is typically used immediately after a spill to predict oil dispersal and promote mobilisation of more effective response operations. The aim of this work was to map oil dispersal after the grounding of the MV Rena on Astrolabe Reef and to verify the results against observations. Model predictions were broadly consistent with observed distribution of oil contamination. However, some hot spots of oil accumulation, likely due to surf-zone and rip current circulation, were not well represented. Additionally, the model was run with 81 differing wind conditions to show that the events occurring during the grounding represented the typical likely behaviour of an oil spill on Astrolabe Reef. Oil dispersal was highly dependent on prevailing wind patterns; more accurate prediction would require better observations of local wind patterns. However, comparison of predictions with observations indicated that the GNOME model was an effective low-cost approach.     

逻辑回归模型在边坡稳定性分析中的应用

采用逻辑回归模型和确定性系数CF建立概率模型,使用收集到的22个边坡实例,将重度、内聚力、坡角、坡高、内摩擦角和孔隙压力比六个影响因子作为自变量,边坡状态作为因变量,应用SPSS取不同的滑坡概率P与不滑坡概率1-P的比值的自然对数Z进行回归分析。将获得的滑坡概率拟合模型反馈到样本参数上,对比其误差,选取Z=±10时的函数模型对另外8组边坡进行验证,证明预测模型的合理性。     

An Innovative Bias-Correction Approach to CMA-GD Hourly QuantitativePrecipitation Forecasts

This paper proposes a simple and powerful optimal integration (OPI) method for improving hourly quantitative precipitation forecasts (QPFs, 0-24 h) of a single-model by integrating the benefits of different bias- corrected methods using the high-resolution CMA-GD model from the Guangzhou Institute of Tropical and Marine Meteorology of China Meteorological Administration (CMA). Three techniques are used to generate multi-method calibrated members for OPI: deep neural network (DNN), frequency-matching (FM), and optimal threat score (OTS). The results are as follows: (1) The QPF using DNN follows the basic physical patterns of CMA-GD. Despite providing superior improvements for clear-rainy and weak precipitation, DNN cannot improve the predictions for severe precipitation, while OTS can significantly strengthen these predictions. As a result, DNN and OTS are the optimal members to be incorporated into OPI. (2) Our new approach achieves state-of-the-art performances on a single model for all magnitudes of precipitation. Compared with the CMA-GD, OPI improves the TS by 2.5%, 5.4%, 7.8%, 8.3%, and 6.1% for QPFs from clear-rainy to rainstorms in the verification dataset. Moreover, OPI shows good stability in the test dataset. (3) It is also noted that the rainstorm pattern of OPI relies heavily on the original model and that OPI cannot correct for deviations in the location of severe precipitation. Therefore, improvements in predicting severe precipitation using this method should be further realized by improving the numerical model’s forecasting capability.     

寒区渠基黏土热参数最优概率分布

为分析寒区渠基黏土热参数的随机分布特征及概率分布模型,以寒区渠基黏土的导热系数为样本,结合经典分布拟合法、多项式逼近法、最大熵法和正态信息扩散法,分别对寒区渠基黏土热参数的概率分布规律进行了研究。首先通过分析热参数的离散性,并比较概率分布曲线、拟合检验值和累计概率分布值,对不同方法描述热参数随机性的优劣进行了评价;然后,基于寒区渠基黏土热学参数对温度的敏感性,提出了一个可以达到理想拟合精度的寒区渠基黏土热参数概率推断的区间取值标准。研究结果表明：寒区渠基黏土的热参数具有随机变量的特征;正态信息扩散法可以描述热参数样本的随机波动性;在4种方法中,正态信息扩散法的拟合精度最高。使用3.5σ法,将[μ-3.5σ,μ+3.5σ]（μ为随机变量的均值,σ为标准差）作为概率函数推断时的取值区间,同时考虑偏度的影响,可使得累计概率值达到1.000 0的精度,能够较准确地推断热参数的概率分布函数。     

Reducing wind power curtailment in China: comparing the roles of coal power flexibility and improved dispatch

Renewable energy curtailment is a critical issue in China, impeding the country’s transition to clean energy and its ability to meet its climate goals. This paper analyzes the impacts of more flexible coal-fired power generation and improved power dispatch towards reducing wind power curtailment. A unit commitment model for power dispatch is used to conduct the analysis, with different scenarios demonstrating the relative impacts of more flexible coal-fired generation and improved power dispatch. Overall, while we find both options are effective in reducing wind power curtailment, we find that improved power dispatch is more effective: (1) the effect of ramping down coal-fired generators to reduce wind power curtailment lessens as the minimum output of coal-fired generation is decreased; and (2) as a result, at higher wind capacity levels, wind curtailment is much more significantly reduced with improved power dispatch than with decreased minimum output of coal-fired generation.

Key policy insights

• China should emphasize both coal power flexibility and dispatch in its policies to minimize renewable power curtailment and promote clean energy transition.

• China should accelerate the process of implementing spot market and marginal cost-based economic dispatch, while making incremental improvements to the existing equal share dispatch in places not ready for spot market.

• A key step in improving of dispatch is incorporating renewable power forecasts into the unit commitment process and updating the daily unit commitment based on the latest forecast result.

• China should expand the coal power flexibility retrofit programme and promote the further development of the ancillary service market to encourage more flexibility from coal-fired generation.

     

卫星地面站雷电直击效应防护设计探讨

卫星地面站雷电防护工程通常采用接闪杆作为天线主体的雷电直击效应防护措施,接闪杆的高度不仅影响其保护范围,而且影响其截闪概率。通过计算年预计雷击次数对截闪概率进行量化分析,结果表明,截闪概率近似与接闪杆高度平方成正比,采用过高的接闪杆将增大地面站遭受雷击电磁脉冲损坏的风险。为优化接闪杆设计,定义了保护体积的概念,并利用折线法与滚球法分别计算了三维立体空间内的保护范围。结果表明:接闪杆的保护范围与高度呈现非线性相关,当接闪杆超过一定高度(折线法超过30m,滚球法超过0.8倍滚球半径)后,对保护范围的影响十分有限;当接闪杆高度低于0.4倍滚球半径时,滚球法保护范围较大,反之则折线法保护范围较大。对接闪杆接闪瞬间周边的磁场强度分析结果表明,无屏蔽环境下地面站电子系统与接闪杆的常规距离远小于两者的理论安全距离,实际工程中难以通过增大接闪杆与卫星地面站的间距消除雷击电磁脉冲危害。为降低这一风险,卫星地面站直击雷防护应优先采用天线自带接闪杆的方式,条件不具备时也应尽量避免采用单支高大接闪杆,可选取适当的计算方法,采用多支较低接闪杆共同防护的方案。     

基于小波长短期记忆网络的风电功率超短期概率预测

随着大规模的风电并网,风电所具有的间歇性与随机性对电力系统的稳定性产生了很大的影响,风电功率预测成为当前解决该问题重要的方式之一.本文利用长短期记忆（LSTM）网络良好的时序记忆特性,将小波分解技术与LSTM深度网络结合,提出基于小波长短期记忆网络的风电功率超短期概率预测模型.首先通过小波分解技术将原始时间序列进行平稳化处理,再建立各子序列样本的LSTM网络预测模型,借助最大似然估计法估计预测误差的高斯分布函数,最终实现对未来4 h时刻的风电功率概率区间预测.最后,采用中国东北某风电场数据对所提方法进行算例分析,结果表明,将小波分解与深度学习方法结合可以较好地提高预测的精度,提高概率预测的区间可靠性.