煤气化过程中单颗粒吸收剂脱硫反应模型概述

对煤气化过程中吸收剂脱硫反应的气固反应模型进行了概述.气固反应模型大致可分为未反应缩核模型,晶粒模型、孔模型及逾渗模型等几种基本型式.未反应缩核模型结构比较简单,可以作为其它模型的基础和组成部分,晶粒模型应用较为广泛且已经得到了充分的发展和改进,孔模型侧重于颗粒内部孔隙特性对反应影响的分析,逾渗模型则基于孔模型将逾渗理论引入来描述脱硫反应过程.     

基于BSC高校教育信息化评价模型的构建

根据高校教育信息化的发展实际,结合平衡计分卡的方法,构建了高校信息化评价指标体系.同时,采用层次分析法法确定指标的权重,针对高校信息化评价指标体系中包括定性指标和定量指标的特点,构建了基于BSC的高校教育信息化模糊综合评价模型.     

改进灰色模型在中长期电力负荷预测中的应用

针对中长期电力系统负荷预测,在前人已有成果的基础之上,对普通灰色模型进行了改进.一方面对历史数据进行二次平滑处理,大大消除了干扰因素;另一方面利用带有马尔可夫链符号估计的残差修正技术对未来残差的符号进行预测以修正灰色模型的预测结果.以某地区多年以来的历史数据为基础,建立了数学模型,通过实际数据计算表明:改进后的灰色负荷预测方法可以应用于电力系统中长期负荷预测,而且较普通灰色预测模型在预测精度上有着明显的提高,尤其是对于较远时间的负荷预测有着较为理想的预测精度,表明了该种方法的有效性和实用性.     

Simulation and optimization of SOFC-BCHP system

As the prime motor of dispersed energy system, the high-temperature solid oxide fuel cells (SOFC) are high efficient with large heat recovery. This study presents a simulation of SOFC building-based cooling, heat and power (BCHP) system, which can meet basic requirements in power and heating (cooling) of the designated customers. The peak power load can be met by power grid, while the peak heating (cooling) load requirement can be met by backup equipments. In order to solve the economic dispatch problem of the energy system, a restricted nonlinear optimization model has been developed. The production costs can be minimized via both the equality constraints of customer’s heat and power demands, and other inequality constrains of equipments’ capacities. The sequential quadratic programming method has been used to search the solution. The study indicates that the model can be used to optimize the system’s capacities and run strategy. An office building case has been computed, and it is indicated that the model can be served in design and optimization of SOFC-BCHP system.     

Application of ACO algorithm in protein structure prediction

The hydrophobic-polar (HP) lattice model is an important simplified model for studying protein folding. In this paper, we present an improved ACO algorithm for the protein structure prediction. In the algorithm, the "lone"ethod is applied to deal with the infeasible structures, and the "oint mutation and reconstruction"ethod is applied in local search phase. The empirical results show that the presented method is feasible and effective to solve the problem of protein structure prediction, and notable improvements in CPU time are obtained.     

Seepage-stress coupling constitutive model of anisotropic soft rock

To provide a seepage-stress coupling constitutive model that can directly describe the seepage-stress coupling relationship, a series of one-dimensional seepage-stress coupling tests on two kinds of soft rock (argillaceous siltstone and brown mudstone) were performed by using an MTS-815.02 tri-axial rock mechanics test system, with which the stress—strain curves according to the seepage variation were obtained. Based on the experimental results and by employing Hooke’s law, the formulation of the coefficient of strain-dependent permeability was presented and introduced to establish a coupling model. In addition, the mathematical expression and the incremental formulation for coupling model were advanced, in which five parameters that can be respectively determined by using the experimental results were included. The calculated results show that the proposed coupling model is capable of simulating the stress—strain relationship with considering the seepage-stress coupling in the nonlinear elastic stage of two kinds of soft rock. Foundation item: Projects(50378069, 50639090) supported by the National Natural Science Foundation of China; Project(50639090) supported by the Joint Fund of Yalong River Hydropower Development, China     

Nonlinear behavior of concrete beams with hybrid FRP and stainless steel reinforcements

The full-range behavior of partially bonded, together with partially prestressed concrete beams containing fiber reinforced polymer (FRP) tendons and stainless steel reinforcing bars was simulated using a simplified theoretical model. The model assumes that a section in the beam has a trilinear moment—curvature relationship characterized by three particular points, initial cracking of concrete, yielding of non-prestressed steel, and crushing of concrete or rupturing of prestressing tendons. Predictions from the model were compared with the limited available test data, and a reasonable agreement was obtained. A detailed parametric study of the behavior of the prestressed concrete beams with hybrid FRP and stainless steel reinforcements was conducted. It can be concluded that the deformability of the beam can be enhanced by increasing the ultimate compressive strain of concrete, unbonded length of tendon, percentage of compressive reinforcement and partial prestress ratio, and decreasing the effective prestress in tendons, and increasing in ultimate compressive strain of concrete is the most efficient one. The deformability of the beam is almost directly proportional to the concrete ultimate strain provided the failure mode is concrete crushing, even though the concrete ultimate strain has less influence on the load-carrying capacity. Foundation item: Project (50478502) supported by the National Natural Science Foundation of China     

Support vector machine forecasting method improved by chaotic particle swarm optimization and its application

By adopting the chaotic searching to improve the global searching performance of the particle swarm optimization (PSO), and using the improved PSO to optimize the key parameters of the support vector machine (SVM) forecasting model, an improved SVM model named CPSO-SVM model was proposed. The new model was applied to predicting the short term load, and the improved effect of the new model was proved. The simulation results of the South China Power Market’s actual data show that the new method can effectively improve the forecast accuracy by 2.23% and 3.87%, respectively, compared with the PSO-SVM and SVM methods. Compared with that of the PSO-SVM and SVM methods, the time cost of the new model is only increased by 3.15 and 4.61 s, respectively, which indicates that the CPSO-SVM model gains significant improved effects. Foundation item: Project(70572090) supported by the National Natural Science Foundation of China     

Effective prediction of DEA model by neural network

In this paper,a fast neural network model for the forecasting of effective points by DEA model is proposed,which is based on the SPDS training algorithm.The SPDS training algorithm overcomes the drawbacks of slow convergent speed and partially minimum result for BP algorithm.Its training speed is much faster and its forecasting precision is much better than those of BP algorithm.By numeric examples,it is showed that adopting the neural network model in the forecasting of effective points by DEA model is valid.     

Spacecraft formation control strategy on Sun-Earth Lissajous orbit

To carry out the deep space exploration tasks near Sun-Earth Libration point L2, the CRTBP dynamic model was built up and the numerical conditional quasi-periodic orbit (Lissajous orbit) was computed near L2. Then, a formation controller was designed with linear matrix inequality to overcome the difficulty of parameter tuning. To meet the demands of formation accuracy and present thruster’s capability, a threshold scheme was adopted for formation control. Finally, some numerical simulations and analysis were completed to demonstrate the feasibility of the proposed control strategy.