塞式喷管多参数性能优化计算

从影响塞式喷管推力性能的因素中总结出内喷管倾角、内膨胀比、总膨胀比、燃气总压和飞行高度这五个主要因素 ,并以推力最大为目标函数运用枚举和逐层优化的方法对上述五个参数的取值进行优化计算 ,提出了对这五个参数进行优化取值的方法并得到了相关结论。其结论可为实际的塞式喷管发动机设计研制提供部分的理论依据 。

Nitrogen Mineralization Potentials of Upland Soils inCentral China

Nitrogen mineralization potentials of 15 soil samples were studied by the methods of soil asrobic incuba-tion, and the correlation between the potentials and the amounts of nitrogen taken up by rye grass (Lolium.multifiorum Lam.) in pot culture was calculated. The soils were collected from Hubei Province in Cen-tral China. Soil nitrogen mineralization potentials (N_O) were calculated and optimized by a quick-BASICprogram. N_O ranged from 60 mg kg￣(-1) to 340 mg kg￣(-1), which accounted for 9.1% to 34.6% of the totalnitrogen content. Among the examined soils, yellow-brown soil collected from Wuhan had the largest N_Oand brown-red soil from Xianning had the smallest one. The mineralization rate constants (k) ranged from0.00556 d￣(-1) to 0.01280 d￣(-1) , in average 0.00882 d￣(-1) . Chao soil from Wuhan had the greatest k while yellow-cinnamon soil from Zhaoyang had the smallest one. There were apparent differences between mineralizationparameters (N_O and k) optimized and non-optimized ones. Optimized N_O had a better correlation thannon-optimized N_O with the amount of nitrogen accumulated in the aerial parts of rye grass. N_O , N_O × k andN_t(accumulated mineralized nitrogen within time t) could be used as indexes of soil nitrogen supply. Amongthem N_t was the best, which was significantly correlated with the amounts of nitrogen accumulated in theaerial parts of rye grass harvested at three different times.

A Fairness Resource Allocation Algorithm for Coverage and Capacity Optimization in Wireless Self-Organized Network

To achieve the higher resource efficiency, Coverage and Capacity Optimization(CCO) as an important role of the network self-healing and self-optimization, has become a focus topic in wireless Self-Organized Network(SON). In this paper, a novel CCO scheme is proposed to maximize utility function of the integrated coverage and capacity. It starts with the analysis on the throughput proportional fairness(PF) algorithm and then proposes the novel Coverage and Capacity Proportional Fairness(CCPF) allocation algorithm along with a proof of the algorithms convergence. This proposed algorithm is applied in a coverage capacity optimization scheme which can guarantee the reasonable network capacity by the coverage range accommodation. Next, we simulate the proposed CCO scheme based on telecom operators' real network data and compare with three typical resource allocation algorithms: round robin(RR), proportional fairness(PF) and max C/I. In comparison of the PF algorithm, the numerical results show that our algorithm increases the average throughput by 1.54 and 1.96 times with constructed theoretical data and derived real network data respectively.

Hybrid particle swarm optimization with chaotic search for solving integer and mixed integer programming problems

A novel chaotic search method is proposed,and a hybrid algorithm combining particle swarm optimization(PSO) with this new method,called CLSPSO,is put forward to solve 14 integer and mixed integer programming problems.The performances of CLSPSO are compared with those of other five hybrid algorithms combining PSO with chaotic search methods.Experimental results indicate that in terms of robustness and final convergence speed,CLSPSO is better than other five algorithms in solving many of these problems.Furthermore,CLSPSO exhibits good performance in solving two high-dimensional problems,and it finds better solutions than the known ones.A performance index(PI) is introduced to fairly compare the above six algorithms,and the obtained values of(PI) in three cases demonstrate that CLSPSO is superior to all the other five algorithms under the same conditions.

Spherical parametrization of genus-zero meshes by minimizing discrete harmonic energy

The problem of spherical parametrization is that of mapping a genus-zero mesh onto a spherical surface. For a given mesh, different parametrizations can be obtained by different methods. And for a certain application, some parametrization results might behave better than others. In this paper, we will propose a method to parametrize a genus-zero mesh so that a surface fitting algorithm with PHT-splines can generate good result. Here the parametrization results are obtained by minimizing discrete har- monic energy subject to spherical constraints. Then some applications are given to illustrate the advantages of our results. Based on PHT-splines, parametric surfaces can be constructed efficiently and adaptively to fit genus-zero meshes after their spherical parametrization has been obtained.

Parametric optimization and performance comparison of organic Rankine cycle with simulated annealing algorithm

Taking the ratio of heat transfer area to net power and heat recovery efficiency into account, a multi-objective mathematical model was developed for organic Rankine cycle （ORC）. Working fluids considered were R123, R134a, R141b, R227ea and R245fa. Under the given conditions, the parameters including evaporating and condensing pressures, working fluid and cooling water velocities were optimized by simulated annealing algorithm. The results show that the optimal evaporating pressure increases with the heat source temperature increasing. Compared with other working fluids, R123 is the best choice for the temperature range of 100--180℃ and R141 b shows better performance when the temperature is higher than 180 ℃. Economic characteristic of system decreases rapidly with the decrease of heat source temperature. ORC system is uneconomical for the heat source temperature lower than 100℃.

Mobile Internet Applications：Impact on Future Wireless Communications System

Based on the analysis of application status in real network,the trace model of some typical mobile Internet applications data is given and their impact on 2G/3G network is discussed in this paper.Furthermore,in order to support the mobile Internet application efficiently in future,the issues including the impact on the Long Term Evolution (LTE-A) system and some potential solutions for performance optimization are studied.Based on the trace data model of IM traffic,the performacne evaluaiton of LTE-A system shows that some specific configuration machanisms can play an important role in improving network system efficiency in the case of IM traffic.

Effect of Zr content on crack formation and mechanical properties of IN738LC processed by selective laser melting

Two batches of commercial IN738LC alloy powders with different Zr contents were printed under the same parameters.The influences of Zr content(0.024 wt.% and 0.12 wt.%,respectively) in powders on crack density,distribution,formation mechanism and mechanical properties of selective laser melting(SLM)-treated parts were systematically studied.It was found that the crack density(area ratio) increases from 0.15% to 0.87% in the XOY plane and from 0.21% to 1.81% in the XOZ plane along with the Zr content increase from 0.024 wt.% to 0.12 wt.% in the original powders.Solidification cracks are formed along the epitaxially grown <001>-oriented columnar grain boundaries in molten pool center.The ultimate tensile strength of Sample 1(0.024 wt.% Zr) is 1113 MPa,and there are dimples in tensile fracture.With an increase in the Zr content to 0.12 wt.%(Sample 2),the ultimate tensile strength of Sample 2 decreases to 610 MPa,and there are numerous original cracks and exposed columnar grain boundaries in tensile fracture.The optimization of printing parameters of Sample 2 considerably increases the ultimate tensile strength by 55.2% to 947 MPa,and the plasticity is greatly improved.

Performance-based passive control analysis of adjacent structures:Optimization of Maxwell dampers

The performance-based passive control analysis of the Maxwell dampers between one 10-story and one 6-story adjacent RC frames is conducted in this work.Not only the optimal parameters but also the optimal arrangements of the Maxwell dampers are proposed based on the optimal target of making the total exceeding probability of the adjacent structures to be minimal.The applicability of the analytical expressions of the Maxwell damper damping parameters under different seismic performance targets are firstly examined and then the preferable damping parameters of the Maxwell dampers are proposed through the extensive parametric studies.Furthermore,the optimal arranging positions and optimal arranging numbers of the Maxwell dampers between the adjacent buildings are derived based on a large number of seismic fragility analyses,as well.The general arranging laws of the Maxwell dampers between the adjacent buildings are generated based on the discussion of the theoretical method through the simplified plane model.The optimal parameters and optimal arrangement of the Maxwell dampers presented make both the adjacent structures have preferable controlled effects under each seismic performance target which can satisfy the requirements of multi-performance seismic resistance of the modern seismic codes.

Swarm intelligence optimization and its application in geophysical data inversion

The inversions of complex geophysical data always solve multi-parameter, nonlinear, and multimodal optimization problems. Searching for the optimal inversion solutions is similar to the social behavior observed in swarms such as birds and ants when searching for food. In this article, first the particle swarm optimization algorithm was described in detail, and ant colony algorithm improved. Then the methods were applied to three different kinds of geophysical inversion problems： （1） a linear problem which is sensitive to noise, （2） a synchronous inversion of linear and nonlinear problems, and （3） a nonlinear problem. The results validate their feasibility and efficiency. Compared with the conventional genetic algorithm and simulated annealing, they have the advantages of higher convergence speed and accuracy. Compared with the quasi-Newton method and Levenberg-Marquardt method, they work better with the ability to overcome the locally optimal solutions.

Evolutionary Finance： The Case of TEDPIX Tracker Fund Selection

Optimal allocation of financial resources is a critical factor in investment decisions. A proper action in this regard requires the existence of appropriate bases and investing tools and techniques in the capital market. One of these effective methods which is considered as the basis of new investment strategies, in addition to multiple unique features, is called index tracking. By considering the undeniable role of this approach in the future of capital markets, its investigation and implementation have been considered in this research and so the problem of optimal Tehran Exchange Dividend Price Index （TEDPIX） tracker fund selection is studied using a hybrid approach of genetic algorithm and quadratic programming. Neural network was applied to simulate unavailable data. Results illustrate the exactness and acceptable performance of the formed portfolios in several iterations such that achieving similar and even better performance compared to the index is a distinctive characteristic of the proposed algorithm.

Improving the BER performance of turbo codes with short frame size based on union bound

timizing the formula, the energy for every bit of the codeword is optimized to achieve the minimum BER at high SNR region. At last, an adjustable parameter is employed to compensate the degrada- tions of BER at low and moderate SNR regions. Case studies indicate that the improvements of BER for turbo codes with short frame size are significant at a wide range of SNR

Design of Underwater Robot Lines Based on a Hybrid Automatic Optimization Strategy

In this paper, a hybrid automatic optimization strategy is proposed for the design of underwater robot lines. Isight is introduced as an integration platform. The construction of this platform is based on the user programming and several commercial software including UG6.0, GAMBIT2.4.6 and FLUENT12.0. An intelligent parameter optimization method, the particle swarm optimization, is incorporated into the platform. To verify the strategy proposed, a simulation is conducted on the underwater robot model 5470, which originates from the DTRC SUBOFF project. With the automatic optimization platform, the minimal resistance is taken as the optimization goal;the wet surface area as the constraint condition; the length of the fore-body, maximum body radius and after-body＇s minimum radius as the design variables. With the CFD calculation, the RANS equations and the standard turbulence model are used for direct numerical simulation. By analyses of the simulation results, it is concluded that the platform is of high efficiency and feasibility. Through the platform, a variety of schemes for the design of the lines are generated and the optimal solution is achieved. The combination of the intelligent optimization algorithm and the numerical simulation ensures a global optimal solution and improves the efficiency of the searching solutions.

The Energy Optimization Mathematic Algorithm on Multi-energy Resource Powertrain of Fuel Cell Vehicle

In order to solve the core issue of the energy regulation （ER） on multi-energy resource powertrain of fuel cell vehicle, the work functions of each component were defined; the mathematical algorithm model of energy regulation was established and the relevant solution was found. This algorithm was evaluated successfully on the hardware in loop （FILL） platform under three typical urban running cycles. The results showed ER control target had been realized and the mathematical algorithm was effective and reasonable. Based on the HIL simulation, some conclusions and ER strategies were made. According to the different power component parameters and real time control request, this algorithm should be modified and calibrated for application in the actual control system.

Energy Harvesting From Sea Waves With Consideration of Airy and JONSWAP Theory and Optimization of Energy Harvester Parameters

One of the new methods for powering low-power electronic devices at sea is a wave energy harvesting system. In this method, piezoelectric material is employed to convert the mechanical energy of sea waves into electrical energy. The advantage of this method is based on avoiding a battery charging system. Studies have been done on energy harvesting from sea waves, however, considering energy harvesting with random JONSWAP wave theory, then determining the optimum values of energy harvested is new. This paper does that by implementing the JONSWAP wave model, calculating produced power, and realistically showing that output power is decreased in comparison with the more simple Airy wave model. In addition, parameters of the energy harvester system are optimized using a simulated annealing algorithm, yielding increased produced power.

Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment

Marine ecosystem dynamic models(MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization(PO), which is an important step in model calibration. An effi cient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the effi ciency of model calibration by analyzing and estimating the goodness-of-fi t of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confi dence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientifi c and normative technical framework for the improvement of MEDM skill.

Optimum Parameters of MgZnSSe/ZnSe BRAQ WET

A theoretical basis of optimally designed BRAQWET is pr esented. The optimum parameters of MgZnSSe/ZnSe BRAQWET are obtained by the ca lculation of band-structure according to the depletion approximation.

Self-adapting Scalable Differential Evolution Algorithm

Differential evolution(DE) demonstrates good convergence performance,but it is difficult to choose trial vector generation strategies and associated control parameter values.An improved method,self-adapting scalable DE(SSDE) algorithm,is proposed.Trial vector generation strategies and crossover probability are respectively self-adapted by two operators in this algorithm.Meanwhile,to enhance the convergence rate,vectors selected randomly with the optimal fitness values are introduced to guide searching direction.Benchmark problems are used to verify this algorithm.Compared with other well-known DE algorithms,experiment results indicate that this algorithm is better than other DE algorithms in terms of convergence rate and quality of optimization.

Optimality of Vector Optimization Involving Generalized Type-I Functions in Banach

In this note,new classes of generalized type-I functions are introduced for functions between Banach spaces.These generalized type-I functions are then utilized to establish sufficient optimality conditions and duality results for a vector optimization problem with functions defined on a Banach space.

Density distribution in a heavy-medium cyclone

Heavy-medium cyclones are widely used to upgrade run-of-mine coal.But the understanding of flow in a cyclone containing a dense medium is still incomplete.By introducing turbulent diffusion into calculations of centrifugal settling a theoretical distribution function giving the density field can be deduced.Qualitative analysis of the density field in every part of a cylindrical cyclone suggests an optimum design that has exhibited good separation effectiveness and anti-wear performance when in commercial operation.