自密实混凝土工作性简易量化评价参数的研究与实践

为便捷评价SCC工作性,通过L型仪与坍落度仪两者评价参数间的关联性研究,得出:基于坍落度仪的SCC工作性简易量化评价参数是{2.5 s≤t_(50),t<3.5 s,0.35Sl_t/Sf_t<0.38};创建SCC钢筋间隙通过自填充性高敏感性立体模型,提出浇筑工作性、多元复合粉体、水粉比概念及"2比"SCC设计新构思;归纳得出SCC研究若干规则。

基于径向基小波神经网络的装备保障方案评价模型

针对装备保障方案评价的实际问题,利用小波函数的多分辨率分析和逐层逼近能力,建立了基于径向基小波神经网络的装备保障方案评价方法。通过对装备保障方案中评价参数的量化,建立评价参数的样本库。将各种性能指标输入到训练好的网络,客观地评价保障方案的性能。以陆军防空旅装备保障方案为例,组织保障领域的专家对评价参数进行综合研讨,得到量化的参数值,然后使用新方法对其进行评价。仿真结果表明,径向基小波神经网络具有良好的非线性映射能力和泛化性能,能够比较准确地对装备保障方案做出评价。

基于人工神经网络的放热规律的量化预测

利用AVL-Fire建立了高压共轨柴油机燃烧系统仿真模型,通过台架试验验证仿真模型的基础上,分析了混合气浓度场和温度场动态分布特性并将燃烧过程划分为预混合和扩散燃烧分界点,提出燃烧始点、预混合燃烧速率、扩散燃烧速率及燃烧持续期等量化评价参数。建立了预测量化评价参数的人工神经网络(ANN)模型,预测分析发动机控制参数对放热规律评价参数的影响。研究结果表明:当采用"5-18-4"型神经网络结构模型并采用trainlm算法时,预测的鲁棒性、响应性和收敛精度均良好,所创建的ANN模型可以很好地预测放热规律。

强化内部审计监督确保企业健康发展

加强企业内部审计,发挥职能作用,实施有效监督,是维护国家、企业和职工的利益的根本要求,也是企业保持长期健康稳定发展的必然需求。强化内部审计监督,必须得到领导的大力支持,常抓不懈,持之以恒;必须严格财务收支审计,促进企业规范管理和依法经营,确保企业经营成果真实性;必须推行经济责任审计,做到方法切实可行,部门协调联动,结果实事求是,为领导决策提供有力的决策依据;必须坚持规范运作,充分利用现代化办公手段,提高内审工作的技术含量,有效地堵塞经营管理中的漏洞。

Evaluation of surface textures and skid resistance of pervious concrete pavement

Surface textures had long been recognized as primary factors to provide the skid resistance on pavements; however, no measurement of skid resistance on pervious concrete pavement with various surface texture parameters had been made. Fractal geometry was introduced in the present work to accurately simulate transect contour curves of pervious concrete specimens through fractal interpolation. It is proved that its fractal dimension (D) can be adopted to measure the skid resistance on pervious concrete pavement, overcoming the shortcomings of both macrotexture depth (DT ) and British portable pendulum number (NBP). Combined with Fujikawa-Koike tire/road contact model, the optimization method of all surface textures was recommended for designing and constructing excellently skid-resistant and noise-absorptive pervious concrete pavement. In addition, evaluating of the abrasion process and attenuation of the surface textures on concrete pavement slabs was also the focus of this work based on accelerated abrasion test. Results show that the surface textures on pervious concrete pavement slabs is extremely durable, compared to those on conventional grooved or exposed aggregate concrete pavement slabs.

New Li-ion Battery Evaluation Research Based on Thermal Property and Heat Generation Behavior of Battery

We do a new Li-ion battery evaluation research on the effects of cell resistance and polariza- tion on the energy loss in batteries based on thermal property and heat generation behavior of battery. Series of 18650 cells with different capacities and electrode materials are evalu- ated by measuring input and output energy which change with charge-discharge time and current. Based on the results of these tests, we build a model of energy loss in cells＇ charge- discharge process, which include Joule heat and polarization heat impact factors. It was reported that Joule heat was caused by cell resistance, which included De-resistance and reaction resistance, and reaction resistance could not be easily obtained through routine test method. Using this new method, we can get the total resistance R and the polarization parameter U. The relationship between R, η, and temperature is also investigated in order to build a general model for series of different Li-ion batteries, and the research can be used in the performance evaluation, state of charge prediction and the measuring of consistency of the batteries.

Evaluating the Performances of GAMIL1.0 and GAMIL2.0 during TWP-ICE with CAPT

CAPT and Atmospheric （Climate Change Prediction Radiation Measurement Program Program （CCPP-ARM） Parameterization Testbed） has been a valu- able tool to assess climate models in recent years, and the Tropical Warm Pool-International Cloud Experiment （TWP-ICE） has collected comprehensive measurements to verify its physical parameterizations. The present study evaluates the performances of the two GAMIL （grid-point atmospheric model of lAP LASG） versions during TWP-ICE using CAPT. The results indicate that GAMIL2.0 reproduced better shifts of clouds and rainfall during three distinct monsoon phases than GAMIL1.0, although both of them simulated the large-scale dynamical states well, which are mainly attributable to the different convective parameterizations.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.