集成电路可制造性设计理论与统计最优化方法统一模型的研究

文中系统地介绍了集成电路可制造性设计的基本概念，讨论了ＩＣ发展趋势和ＶＬＳＩ的极限，以及功能设计向优化设计过渡的必然性。综合考虑了电路制造的参数成品率极大，最佳容差设计，调整设计和制造费用极小化问题，提出了建立在不可微规划框架上的统计最优化方法的统一模型。该模型可以包含目前确定性统计最优化的基本类型，为统计最优化的进一步发展开辟了新径。

序列凸化下的电路DCTT统计最优化方法

基于集成电路成品率极大中心设计，最佳容差设计，最佳调整设计和生产费用极小化设计的一体化模型（ＤＣＴＴ模型），该文给出了函数序列凸化下求解ＤＣＴＴ的有效方法。该方法应用确定性方法和正交最优化方法相结合，将容差域的２￣ｎ个顶点离散为ｎ＋１个约束条件，并利用不可微规划直接得到ＤＣＴＴ问题的最优解。该方法较好地解决了较大规模的集成电路统计最优化问题。

重组二硫键异构酶在大肠杆菌中表达条件的统计优化

二硫键形成蛋白A (disulfidebondformationproteinA ,DsbA)是大肠杆菌周质胞腔中辅助多种含有二硫键的蛋白质正确折叠并具有生物学活性的一种二硫键异构酶.通过统计实验设计的方法将生产重组DsbA的发酵过程进行了优化.首先通过Plackett Burman设计挑选出了对DsbA表达量影响较大的四个因素,然后再利用杂合设计进行实验,并通过拟合得到了响应曲面函数,但该函数的驻点是鞍点,因此不具有全局的极值.最后通过约束优化得到了较佳的实验点,在该实验点下DsbA的表达量比基本培养条件下提高了5 0 .14 % .

Simplex Latics体系在优化炎痛喜康透皮吸收剂中的应用

使用ＳｉｍｐｌｅｘＬａｔｔｉｃｅ统计优化方法，对炎痛喜康透皮吸收剂的处方进行了优选。在３因素４水平上，通过７次实验，结合微机编程外推至２００次以上的指标响应范围，得出最优化处方。并经实验证明预测的响应指标－－剥离粘性、表面粘性、透皮量与实验值吻合性好，这说明Ｓｉｍ－ｐｌｅｘＬａｔｉｃｅ适用于炎痛喜康透皮吸收剂的背材的体外优化。

喷丸零件高精度尺寸公差分配方法的研究

通过尺寸链计算,初步确定机械加工尺寸和喷丸增长量公差,再通过统计法求解封闭环与各组成环之间的关系,合理分配机械加工尺寸和喷丸增长量公差,有效地保证了产品的加工质量,为喷丸类零件在工艺编制时尺寸公差分配提供了一种科学的方法,同时为产品设计提供了一定的数据支撑。

地下水环境监测系统的设计

介绍了地下水环境监测的现状、特点和设计地下水环境监测系统的目的,详细阐述了地下水环境监测系统的站位布设、采样频率和时间分配、监测项目,以及地下水采样井的布设。

Optimal operation of water supply systems with tanks based on genetic algorithm

In view of the poor water supply system’s network properties, the system’s complicated network hydraulic equations were replaced by macroscopic nodal pressure model and the model of relationship between supply flow and water source head. By using pump-station pressure head and initial tank water levels as decision variables, the model of optimal allocation of water supply between pump-sources was developed. Genetic algorithm was introduced to deal with the model of optimal allocation of water supply. Methods for handling each constraint condition were put forward, and overcome the shortcoming such as premature convergence of genetic algorithm; a solving method was brought forward in which genetic algorithm was combined with simulated annealing technology and self-adaptive crossover and mutation probabilities were adopted. An application example showed the feasibility of this algorithm.

LISP-PCHORD:An Enhanced Pointer-Based DHT to Support LISP

Aiming to efficiently support theLocator/Identifier Separation Protocol(LISP),in this paper,we present an enhanced pointerbased DHT mapping system:LISP-PCHORD.The system creates a pointer space to build ontop of standard DHTs.Mappings within thepointer space are(Endpoint Identifiers(EID),pointers) where the pointer is the address ofthe root node(the physical node that stores themappings) of the corresponding(EID,RoutingLocators(RLOCs)) mappings.In addition toenabling architectural qualities such as scalability and reliability,the proposed LISP-PCHORDcan copy with flat EIDs such as self-certifyingEIDs.The performance of the mapping systemplays a key role in LISP;however,DHT-basedapproaches for LISP seldom consider the mismatch problem that heavily damages the system performance in terms of lookup latency.In order to mitigate the mismatch problem andachieve optimal performance,we propose anoptimization design method that seeks an optimal matching relationship between P-nodes(nodes within the pointer space) and the physical nodes on the basis of the given lookuptraffic matrix.In order to find the optimal matching relationship,we provide two solutions:a linear programming method and a geneticalgorithm.Finally,we evaluate the performance of the proposed scheme and compare itwith that of LISP-DHT.

Statistical evaluation and optimization of zinc electrolyte hot purification process by Taguchi method

The neutral zinc sulfate solution obtained from hydrometallurgical process of Angouran zinc concentrate has cadmium, nickel and cobalt impurities, that must be purified before electrowinning. Therefore, cadmium and nickel are usually cemented out by addition of zinc dust and remained nickel and cobalt cemented out at second stage with zinc powder and arsenic trioxide. In this research, a new approach is described for determination of effective parameters and optimization of zinc electrolyte hot purification process using statistical design of experiments. The Taguchi method based on orthogonal array design（OAD） has been used to arrange the experimental runs. The experimental conditions involved in the work are as follows： the temperature range of 70-90 ℃ for reaction temperature（T）, 30-90 min for reaction time（t）, 2-4 g/L for zinc powder mass concentration（M）, one to five series for zinc dust particle size distributions（S1-S5）, and 0.1-0.5 g/L（C） for arsenic trioxide mass concentration. Optimum conditions for hot purification obtained in this work are T4（85 ℃）, t4=75 min, M4=3.5 g/L, S4（Serie 4）, and C2=0.2 g/L.

Parameter design and performance analysis of zero inertia continuously variable transmission system

In order to solve the problem of weak power performance of vehicle equipped with continuously variable transmission(CVT) system working under transient operating conditions, a new CVT equipped with planetary gear mechanism and flywheel was researched, a design method of transmission parameter optimization was proposed, and the comprehensive matching control strategy was established for the new transmission system. Fuzzy controllers for throttle opening and CVT speed ratio were designed, and power performance and fuel economy of both vehicles respectively equipped with conventional CVT system and new transmission system wrere compared and analyzed by simulation. The results show that power performance and fuel economy of the vehicle equipped with new transmission system are better than that equipped with conventional CVT, thus the rationality of the parameter design method and control algorithm are verified.

Statistical approach for the culture conditions optimization of magnetotactic bacteria for magnetic cells production

The culture of Magnetospirillum magneticum WM-1 depends on several control factors that have great effect on the magnetic cells concentration. Investigation into the optimal culture conditions needs a large number of experiments So it is desirable to minimize the number of experiments and maximize the information gained from them. The orthogonal design of experiments and mathematical statistical method are considered as effective methods to optimize the culture condition of magnetotactic bacteria WMol for high magnetic cells concentration. The effects of the four factors, such as pH value of medium, oxygen concentration of gas phase in the serum bottle, C：C （mtartaric acid： m=succinic acid） ratio and NaNO3 concentration, are simultaneously investigated by only sixteen experiments through the orthogonal design L16（44） method. The optimal culture condition is obtained. At the optimal culture condition （ pH 7.0, an oxygen concentration 4.0%, C：C （mtartaric acid： m=succinic acid） ratio 1：2 and NaNO3 100 mg 1^-1）, the magnetic cells concentration is promoted tO 6.5×10^7 cells ml^-1, approximately 8.3% higher than that under the initial conditions. The pH value of medium is a very important factor for magnetic cells concentration. It can be Proved that the orthogonal design of experiment is of 90% confidence. Ferric iron uptake follows MichaelisoMenten kinetics with a Km of 2.5 pM and a Vmax of 0.83 min^-1.

A marked enhancement in production of amylase by Bacillus amyloliquefaciens in flask fermentation using statistical methods

A total of 126 bacterial strains were isolated from soil samples. Among them, 11 isolates were found positive for amylase production. Strain YL produced the largest zone of clearance on plate assay. The isolate YL was identified as Bacillus sp. based on morphological and physiochemical characterization. According to 16S rRNA gene sequencing data, the closest phylogenetic neighbor of strain YL was Bacillus amyloliquefaciens （99.54%）. After that, an optimization of culture conditions was carried out for the improvement of a-amylase production. Response surface methodology （RSM） was applied to evaluate the effect of medium components including wheat bran, cottonseed extract, yeast extract, starch, NaC1 and CaCl2. Three variables （wheat bran, cottonseed extract, and starch）, which were identified to significantly affect amylase production by Plackett-Burman design were further optimized using response surface methodology of Box-Behnken design （BBD）. The optimal concentrations estimated for each variable related to the maximum of amylase activity （86 kU/mL） were 10.80 g/L wheat bran, 9.90 g/L cottonseed extract, 0.5 g/L starch, 2.0 g/L yeast extract, 5.00 g/L NaCl and 2.00 g/L CaC12. The fermentation using optimized culture medium allowed a significant increase in amylase production （by 3-fold）. The improvement in the a-amylase production after optimization process can be considered adequate for large-scale applications.

Statistical analysis of fracture properties based on particle swarm optimization and Pearson correlation coefficient method

Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.

Heating and Cooling Hybrid System with Gas Mixture Sourced Heat Pump and Heating Boiler

Preliminary investigation shows that air sourced type heat pumps by energy efficiency are competitive with gas boilers having 93% of coefficient of performance （COP） if heat pumps are used in climatic zones, having outside air temperature higher than （-3 ℃ to -5 ℃）. But, in such conditions the heat pump＇s evaporator is covered by ice crust, which cuts off the flow of outside air-heat source through the evaporator of heat pump. For avoiding stating problems it is recommended to use as heat source a mixture of waste warm gases. In this article a high efficiency heating-cooling system is developed, consisting of warm gases mixture sourced heat pump, heating boiler operating simultaneously with heat pump and solar air heater. The heating demand of the served house is shared between boiler and heat pump. Instead of outside air the warm gases mixture enters into evaporator of heat pump. A new construction of heat exchanger was developed. The article presents the structure and principle of operation, as well as the method for optimization and design of suggested system. Analysis proved high energy efficiency and cost effectiveness of the new system.

Multi-objective robust design optimization of a novel negative Poisson's ratio bumper system

Negative Poisson's ratio(NPR) structure has outstanding performances in lightweight and energy absorption, and it can be widely applied in automotive industries. By combining the front anti-collision beam, crash box and NPR structure, a novel NPR bumper system for improving the crashworthiness is first proposed in the work. The performances of the NPR bumper system are detailed studied by comparing to traditional bumper system and aluminum foam filled bumper system. To achieve the rapid design while considering perturbation induced by parameter uncertainties, a multi-objective robust design optimization method of the NPR bumper system is also proposed. The parametric model of the bumper system is constructed by combining the full parametric model of the traditional bumper system and the parametric model of the NPR structure. Optimal Latin hypercube sampling technique and dual response surface method are combined to construct the surrogate models. The multi-objective robust optimization results of the NPR bumper system are then obtained by applying the multi-objective particle swarm optimization algorithm and six sigma criteria. The results yielded from the optimizations indicate that the energy absorption capacity is improved significantly by the NPR bumper system and its performances are further optimized efficiently by the multi-objective robust design optimization method.

Multi-parameter optimization design, numerical simulation and performance test of mixed-flow pump impeller

On the basis of the three-dimensional design platform of the mixed-flow pump impellers, an optimization design system was developed in this paper by improving the genetic algorithm with application of both strategies of keeping the optimal individu- al and employing the niche. This system took the highest efficiency of the impeller as the optimization objective and employed P, a0, A0h and A0t, which could directly affect the shape and the position of the blade, as optimization parameters. In addition, loss model was used to obtain fast and accurate prediction of the impeller efficiency. The optimization results illustrated that this system had advantages such as high accuracy and fine convergence, thus to effectively improve the design of the mixed-flow pump impellers. Numerical simulation was applied to determine the internal flow fields of the impeller obtained by optimization design, and to analyze both the relative velocity and the pressure distributions. The test results demonstrated that the mixed flow pump had the highest efficiency of 87.2%, the wide and flat high efficiency operation zone, the relatively wide range of blade angle adjustment, fine cavitation performance and satisfied stability.

Uncertainty analysis and probabilistic design optimization of hybrid rocket motors for manned lunar landing

To obtain a conceptual design for a hybrid rocket motor(HRM)to be used as the Ascent Propulsion System in the Apollo lunar module,the deterministic design optimization(DDO)method is applied to the HRM design.Based on the results of an uncertainty analysis of HRMs,an uncertainty-based design optimization(UDO)method is also adopted to improve the design reliability.The HRM design process,which is a multidisciplinary system,is analyzed,and a mathematical model for the system design is established to compute the motor performance from the input parameters,including the input variables and model parameters.The input parameter uncertainties are quantified,and a sensitivity analysis of the model parameter uncertainties is conducted to identify the most important model parameter uncertainties for HRMs.The DDO and probabilistic UDO methods are applied to conceptual designs for an HRM to be used as a substitute for the liquid rocket motor(LRM)of the Ascent Propulsion System.The conceptual design results show that HRMs have several advantages as an alternative to the LRM of the Ascent Propulsion System,including nontoxic propellant combination,small motor volume,and comparable functions,such as restarting and throating.Comparisons of the DDO and UDO results indicate that the UDO method achieves more robust and reliable optimal designs than the DDO method.The probabilistic UDO method can be used to develop better conceptual designs for HRMs.

A priori error estimates of finite volume element method for hyperbolic optimal control problems

In this paper,optimize-then-discretize,variational discretization and the finite volume method are applied to solve the distributed optimal control problems governed by a second order hyperbolic equation.A semi-discrete optimal system is obtained.We prove the existence and uniqueness of the solution to the semidiscrete optimal system and obtain the optimal order error estimates in L ∞(J;L 2)-and L ∞(J;H 1)-norm.Numerical experiments are presented to test these theoretical results.

Design of Off-statistics Axial-flow Fans by Means of Vortex Law Optimization

Off-statistics input data sets are common in axial-flow fans design and may easily result in some violation of the requirements of a good aerodynamic blade design.In order to circumvent this problem,in the present paper,a solution to the radial equilibrium equation is found which minimizes the outlet kinetic energy and fulfills the aerodynamic constraints,thus ensuring that the resulting blade has acceptable aerodynamic performance.The presented method is based on the optimization of a three-parameters vortex law and of the meridional channel size.The aerodynamic quantities to be employed as constraints are individuated and their suitable ranges of variation are proposed.The method is validated by means of a design with critical input data values and CFD analysis.Then,by means of systematic computations with different input data sets,some correlations and charts are obtained which are analogous to classic correlations based on statistical investigations on existing machines.Such new correlations help size a fan of given characteristics as well as study the feasibility of a given design.

Optimal Design for a Retrial Queueing System with State-Dependent Service Rate

This paper considers a single server retrial queue in which a state-dependent service policy is adopted to control the service rate. Customers arrive in the system according to a Poisson process and the service times and inter-retrial times are all exponentially distributed. If the number of customers in orbit is equal to or less than a certain threshold, the service rate is set in a low value and it also can be switched to a high value once this number exceeds the threshold. The stationary distribution and two performance measures are obtained through the partial generating functions. It is shown that this state-dependent service policy degenerates into a classic retrial queueing system without control policy under some conditions. In order to achieve the social optimal strategies, a new reward-cost function is established and the global numerical solutions, obtained by Canonical Particle Swarm Optimization algorithm, demonstrate that the managers can get more benefits if applying this state-dependent service policy compared with the classic model.