Accurate energy model for WSN node and its optimal design

With the development of CMOS and MEMS technologies, the implementation of a large number of wireless distributed micro-sensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. For better understanding of the design tradeoffs of wireless sensor network （WSN）, a more accurate energy model for wireless sensor node is proposed, and an optimal design method of energy efficient wireless sensor node is described as well. Different from power models ever shown which assume the power cost of each component in WSN node is constant, the new one takes into account the energy dissipation of circuits in practical physical layer. It shows that there are some parameters, such as data rate, carrier frequency, bandwidth, Tsw, etc, which have a significant effect on the WSN node energy consumption per useful bit （EPUB）. For a given quality specification, how energy consumption can be reduced by adjusting one or more of these parameters is shown.

MODELING, VALIDATION AND OPTIMAL DESIGN OF THE CLAMPING FORCE CONTROL VALVE USED IN CONTINUOUSLY VARIABLE TRANSMISSION

Associated dynamic performance of the clamping force control valve used in continuously variable transmission （CVT） is optimized. Firstly, the structure and working principle of the valve are analyzed, and then a dynamic model is set up by means of mechanism analysis. For the purpose of checking the validity of the modeling method, a prototype workpiece of the valve is manufactured for comparison test, and its simulation result follows the experimental result quite well. An associated performance index is founded considering the response time, overshoot and saving energy, and five structural parameters are selected to adjust for deriving the optimal associated performance index. The optimization problem is solved by the genetic algorithm （GA） with necessary constraints. Finally, the properties of the optimized valve are compared with those of the prototype workpiece, and the results prove that the dynamic performance indexes of the optimized valve are much better than those of the prototype workpiece.

Load optimal design for a primary test stand facility based on a zero-dimensional load model

In order to couple the numerical simulation of a primary test stand driver with an optimal load design, a zero- dimensional wire array load model is designed based on the Saturn load model using PSPICE, which is an upgraded version of the Simulation Program with Integrated Circuit Emphasis （SPICE） designed by the ORCAD Corporation to perform circuit simulations. This paper calculates different load parameters and discusses factors influencing the driving current curve. With appropriate driving current curves chosen, further magneto-hydrodynamic calculations are carried out and discussed to provide the best results for experiments. The suggested optimal load parameters play an important role in experimental load design.

Improved Genetic Optimization Algorithm with Subdomain Model for Multi-objective Optimal Design of SPMSM

For an optimal design of a surface-mounted permanent magnet synchronous motor(SPMSM),many objective functions should be considered.The classical optimization methods,which have been habitually designed based on magnetic circuit law or finite element analysis(FEA),have inaccuracy or calculation time problems when solving the multi-objective problems.To address these problems,the multi-independent-population genetic algorithm(MGA)combined with subdomain(SD)model are proposed to improve the performance of SPMSM such as magnetic field distribution,cost and efficiency.In order to analyze the flux density harmonics accurately,the accurate SD model is first established.Then,the MGA with time-saving SD model are employed to search for solutions which belong to the Pareto optimal set.Finally,for the purpose of validation,the electromagnetic performance of the new design motor are investigated by FEA,comparing with the initial design and conventional GA optimal design to demonstrate the advantage of MGA optimization method.

Spatial batch optimal design based on self-learning Gaussian process models for LPCVD processes

Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.

Optimal Design of Tank Sheets Based on Parametric Modeling

Optimal design of the tank has a significant effect on reducing the weight of a launch vehicle’s structure.In this paper,the key characteristics of a stiffened shell are identified from the design requirements,focusing on the influence of the internal pressure on the axial compression load-bearing capacity.The computing method of the ultimate load of the stiffened shell,the parametric modeling method and the surrogate modeling technique for optimal design are reviewed.An optimization process applicable to the stiffened shell was developed and applied in the optimization work for the tanks of solid-liquid bundled launch vehicle,so a better weight reduction effect could be achieved.

The Construction of Locally D-Optimal Designs by Canonical Forms to an Extension for the Logistic Model

Logistic regression models for binary response problems are present in a wide variety of industrial, biological, social and medical experiments;therefore, optimum designs are a valuable tool for experimenters, leading to estimators of parameters with minimum variance. Our interest in this contribution is to provide explicit formulae for the D-optimal designs as a function of the unknown parameters for the logistic model where q is an indicator variable. We have considered an experiment based on the dose-response to a fly insecticide in which males and females respond in different ways, proposed in Atkinson et al. (1995) [1]. To find the D-optimal designs, this problem has been reduced to a canonical form.

Optimal Design and Dynamic Simulation of Mountain Bike with Rear Suspension

This paper investigates the dynamic design methodology of mountain bikes with rear suspension. Firstly, a multi-rigid body dynamic model of rider and mountain bike coupled system is constructed. The rider model includes 19 skeletons, 18 joints and 118 main muscles. Secondly, to validate the feasibility of the model, an experiment test is designed to reflect the real cycling status. Finally, aiming at enhancing the performance of the rider vibration comfort, the scale parameters of rear suspension are optimized with computer simulation and uniform design. The mathematical model in the vibration performance and the design variables is constructed with regression analysis. The result shows that when the length of side link is 90 mm, the length of connected rod is 336.115 1 mm and the included angle between absorber and side link is 60°, the mountain bike has better vibration comfort. This study and relevant conclusions are of practical importance to the design of the mountain bike＇s rear suspension system.

Optimal Design of Rotary Tool based on ANSYS Workbench

Rotary tool of garbage crusher is the key component of the whole mechanism, which is of vital importance to tool design and analysis. Based on ANSYS Workbench 3D modeling, we carried on finite element analysis to tool, and used the method of goal driven optimization to optimize the rotary tool. The optimization proves that the optimized maximum equivalent stress is 544.14 MPa, the quality is less, and the optimized rotary tool size is more reasonable. So it provided reasonable and scientific reference frame to the structural design of rotary tool.

OPTIMAL DESIGN OF HOUSING ATTICS WITH INTEGRATED SOLAR COLLECTORS

In order to reduce the increasing energy consumption for the domestic demands of existing single-family housing and take advantage of frequent building enlargements,this paper presents a methodology and supporting software tool for determining the optimal design configuration of an attic with integrated solar collectors.The analysis procedure is based on parametric modeling,energy simulation and the use of evolutionary algorithms for finding optimal designs.It has been implemented as a Web-platform for public use that provides users with a proposal of an attic shape with maximum solar energy collection,maximum living space and minimum construc-tion envelope for each house according its size and orientation.The attic integrates PV,thermal and hybrid solar panels on one side of the roof.This paper describes the methodology and software design,asssment of the Web-platform usage and case-studies to verify its behavior.In a matter of minutes,the Web-platform enables users to select a specific attic design for each house that has integrated solar collectors that can produce energy to cover almost 100%of domestic energy consumption.The attics designed provide a nearly 30%increase in living space through the extension of one to four rooms,and the construction cost of the envelope is similar to that of a standard housing extension.

Optimal Design of Equivalent Water Depth Truncated Mooring System Based on Baton Pattern Simulated Annealing Algorithm

The highest similarity degree of static characteristics including both horizontal and vertical restoring force-displacement characteristics of total mooring system, as well as the tension-displacement characteristics of the representative single mooring line between the truncated and full depth system are obtained by annealing simulation algorithm for hybrid discrete variables （ASFHDV, in short）. A“baton” optimization approach is proposed by utilizing ASFHDV. After each baton of optimization, if a few dimensional variables reach the upper or lower limit, the boundary of certain dimensional variables shall be expanded. In consideration of the experimental requirements, the length of the upper mooring line should not be smaller than 8 m, and the diameter of the anchor chain on the bottom should be larger than 0.03 m. A 100000 t turret mooring FPSO in the water depth of 304 m, with the truncated water depth being 76 m, is taken as an example of equivalent water depth truncated mooring system optimal design and calculation, and is performed to obtain the conformation parameters of the truncated mooring system. The numerical results indicate that the present truncated mooring system design is successful and effective.

Towards Energy Efficient Shape Rolling:Roll Pass Optimal Design and Case Studies

Shape rolling is widely employed in the production of long workpieces with appropriate cross-section profiles for other industrial applications. In the development of shape rolling systems, roll pass design (RPD) plays an essential role on the quality control of products, service life of rolls, productivity of rolling systems, as well as energy consumption of rolling operations. This study attempts to establish a generic strategy based on hybrid modeling and an improved genetic algorithm, to support the optimizations of RPD and shape rolling operations at a systematic perspective. Objectives include improving the quality and efficiency of RPD, reducing energy consumption of shape rolling, as well as releasing the demands on costly trails and expert knowledge in RPD. Hybrid modeling based on cross-disciplinary knowledge is developed to overcome the limitations of isolated single-disciplinary models. And conventional genetic algorithm is improved for the implementation of optimal design. Targeting to integrate empirical data and published reliable solutions into optimizations, a parameters estimation method is proposed to transfer the initially misaligned models into a uniform pattern. A tool based on the Matlab platform is developed to demonstrate the optimal design operations, with case studies involved to validate the proposed methodology.

A New D-optimal Design Scheme for the Identification of Cubic Polynomials

In this paper, the limitations of the single cube D-optimal design scheme is studied, and a double cube D-optimal design scheme is suggested in order to overcome the limitations. For a sort of incomplete cubic polynomials, the test design of the identification is developed with this new scheme, and the comparation with the single cube scheme is also given. This scheme is shown to be perfectly suitable for the optimal identification of the complete cubic polynomials.

Designing optimal number of receiving traces based on simulation model

Currently, the selection of receiving traces in geometry design is mostly based on the horizontal layered medium hypothesis, which is unable to meet survey requirements in a complex area. This paper estimates the optimal number of receiving traces in field geometry using a numerical simulation based on a field test conducted in previous research （Zhu et al., 2011）. A mathematical model is established for total energy and average efficiency energy using fixed trace spacing and optimal receiving traces are estimated. Seismic data acquired in a complex work area are used to verify the correctness of the proposed method. Results of model data calculations and actual data processing show that results are in agreement. This indicates that the proposed method is reasonable, correct, sufficiently scientific, and can be regarded as a novel method for use in seismic geometry design in complex geological regions.

LIMIT THEOREMS AND OPTIMAL DESIGN WITH ADAPTIVE URN MODELS

In this paper we study urn model, using some available estimates of successes probabilities, and adding particle parameter, we establish adaptive models. We obtain some strong convergence theorems, rates of convergence, asymptotic normality of components in the urn, and estimates. With these asymptotical results, we show that the adaptive designs given in this paper are asymptotically optimal designs.

THE OPTIMAL DESIGN BASED ON RELIABILITY OF WATER DISTRIBUTION SYSTEM BY LINEAR MODEL

In this paper, a new technique are developed for optimal design of water distribution system besed on reliability. It applies a linear programming algorithm to the optimal design based on reliability. Within a small optimal search step range,the objective function and constraints can be expressed in the first order Taylor-expanding form,and three sub-models (a steady-state simulation model, a reliability model and a linear optimization model) are linked each in optimal searches. Thus, a traditional non linear problem can be solved by a linear model, the computing burden is significantly decreased. Therefore, the linear optimal model developed by the paper has more practical significance.

Assembly Variation Identification of High Pressure Spool by Response Surface Based Model Updating Using IV-optimal Designs

This article, in order to improve the assembly of the high-pressure spool, presents an assembly variation identification method achieved by response surface method （RSM）-based model updating using IV-optimal designs. The method involves screening out non-relevant assembly parameters using IV-optimal designs and the preload of the joints is chosen as the input features and modal frequency is the only response feature. Emphasis is placed on the construction of response surface models including the interactions between the bolted joints by which the non-linear relationship between the assembly variation caused by the changes ofpreload and the output frequency variation is established. By achieving an optimal process of selected variables in the model, assembly variation can be identified. With a case study of the laboratory bolted disks as an example, the proposed method is verified and it gives enough accuracy in variation identification. It has been observed that the first-order response surface models considering the interactions between the bolted joints based on the IV-optimal criterion are adequate for assembly purposes.

基于D-optimal法优化香菇菌种培养基质配方的研究

为了筛选和优化香菇原种及栽培种的培养基质配方,采用D-optimal设计方法,以麦粒和木屑不同配比为原料优化香菇原种培养基质,以木屑、玉米芯、麸皮不同配比为原料优化香菇栽培种培养基质,以香菇品种L808作为供试菌种,分别以其菌丝萌发期、菌丝长速、满袋期为评价指标,通过对各评价指标的测量,建立了各配比基质与香菇培养基质配方响应值之间的回归模型,从而科学的优化出香菇原种及栽培种栽培基质的配方。试验结果表明,香菇原种栽培基质最优配方为50%麦粒+50%木屑;香菇栽培种栽培基质最优配方为37.69%玉米芯+23.33%麸皮+38.98%木屑。在以上2个配方的栽培基质接种后,香菇菌丝的生长旺盛,萌发期短、满袋期短,且理化性质较优,说明优化得到的栽培基质配方具有较高的可行性,该设计方法也在优化培养料配比上是科学并且可行的。

Theoretical model and optimal design of silicon micromachined ultrasonic imaging transducers

A theoretical model and mathematical description for silicon micromachined elec- trostatic or capacitive ultrasonic imaging transducers have been developed. Ac- cording to the model the basic performance parameters of such a transducer, such as natural frequencies, eigenfunctions, resonance and anti-resonance frequencies, and the mechanical impedance of the diaphragm can be predicted from the ge- ometry of the transducer and property parameters of materials used. The paper reveals that this type of transducers has two basic operation modes, correspond- ing to the resonance of a mass-spring oscillator comprised of the diaphragm and the air cushion, and the first-order bending mode of the diaphragm itself respec- tively, and presents an optimal method for extending the bandwidth by making the two modes coupled, and thereby provides a theoretical basis for the optimal de- sign.