An improved multidisciplinary feasible method using DACE approximation approach

Multidisciplinary feasible method (MDF) is conventional method to multidisciplinary optimization (MDO) and well-understood by users. It reduces the dimensions of the multidisciplinary optimization problem by using the design variables as independent optimization variables. However, at each iteration of the conventional optimization procedure, multidisciplinary analysis (MDA) is numerously performed that results in extreme expense and low optimization efficiency. The intrinsic weakness of MDF is due to the times that it loop fixed-point iterations in MDA, which drive us to improve MDF by building inexpensive approximations as surrogates for expensive MDA. An simple example is presented to demonstrate the usefulness of the improved MDF. Results show that a significant reduction in the number of multidisciplinary analysis required for optimization is obtained as compared with original MDF and the efficiency of optimization is increased.

Homotopy Continuous Method for Weak Efficient Solution of Multiobjective Optimization Problem with Feasible Set Unbounded Condition

In this paper, we propose a homotopy continuous method (HCM) for solving a weak efficient solution of multiobjective optimization problem (MOP) with feasible set unbounded condition, which is arising in Economical Distributions, Engineering Decisions, Resource Allocations and other field of mathematical economics and engineering problems. Under the suitable assumption, it is proved to globally converge to a weak efficient solution of (MOP), if its x-branch has no weak infinite solution.

A SUPERLINEARLY CONVERGENT SPLITTING FEASIBLE SEQUENTIAL QUADRATIC OPTIMIZATION METHOD FOR TWO-BLOCK LARGE-SCALE SMOOTH OPTIMIZATION

This paper discusses the two-block large-scale nonconvex optimization problem with general linear constraints.Based on the ideas of splitting and sequential quadratic optimization(SQO),a new feasible descent method for the discussed problem is proposed.First,we consider the problem of quadratic optimal(QO)approximation associated with the current feasible iteration point,and we split the QO into two small-scale QOs which can be solved in parallel.Second,a feasible descent direction for the problem is obtained and a new SQO-type method is proposed,namely,splitting feasible SQO(SF-SQO)method.Moreover,under suitable conditions,we analyse the global convergence,strong convergence and rate of superlinear convergence of the SF-SQO method.Finally,preliminary numerical experiments regarding the economic dispatch of a power system are carried out,and these show that the SF-SQO method is promising.

A SUPERLINEARLY AND QUADRATICALLY CONVERGENT SQP TYPE FEASIBLE METHOD FOR CONSTRAINED OPTIMIZATION

A new SQP type feasible method for inequality constrained optimization is presented,it is a combination of a master algorithm and an auxiliary algorithm which is taken only in finite iterations.The directions of the master algorithm are generated by only one quadratic programming, and its step\|size is always one, the directions of the auxiliary algorithm are new “second\|order” feasible descent. Under suitable assumptions,the algorithm is proved to possess global and strong convergence, superlinear and quadratic convergence.

An Efficient Method for Reliability-based Multidisciplinary Design Optimization

Design for modem engineering system is becoming multidisciplinary and incorporates practical uncertainties; therefore, it is necessary to synthesize reliability analysis and the multidisciplinary design optimization （MDO） techniques for the design of complex engineering system. An advanced first order second moment method-based concurrent subspace optimization approach is proposed based on the comparison and analysis of the existing multidisciplinary optimization techniques and the reliability analysis methods. It is seen through a canard configuration optimization for a three-surface transport that the proposed method is computationally efficient and practical with the least modification to the current deterministic optimization process.

EFFICIENT METHOD FOR MULTIDISCIPLINARY DESIGN OPTIMIZATION BY CONSIDERING UNCERTAINTY

A new reliability-based multidisciplinary design optimization （RBMDO） framework is proposed by combining the single-loop-based reliability analysis （SLBRA） method with multidisciplinary feasible （MDF） method. The Kriging approximate model with updating is introduced to reduce the computational cost of MDF caused by the complex structure. The computational efficiency is remarkably improved as the lack of iterative process during reliability analysis. Special attention is paid to a turbine blade design optimization by adopting the proposed method. Results show that the method is much more efficient than the commonly used double-loop based RBMDO method. It is feasible and efficient to apply the method to the engineering design.

Uncertain Multidisciplinary Design Optimization on Next Generation Subsea Production System by Using Surrogate Model and Interval Method

The innovative Next Generation Subsea Production System(NextGen SPS)concept is a newly proposed petroleum development solution in ultra-deep water areas.The definition of NextGen SPS involves several disciplines,which makes the design process difficult.In this paper,the definition of NextGen SPS is modeled as an uncertain multidisciplinary design optimization(MDO)problem.The deterministic optimization model is formulated,and three concerning disciplines—cost calculation,hydrodynamic analysis and global performance analysis are presented.Surrogate model technique is applied in the latter two disciplines.Collaborative optimization(CO)architecture is utilized to organize the concerning disciplines.A deterministic CO framework with two disciplinelevel optimizations is proposed firstly.Then the uncertainties of design parameters and surrogate models are incorporated by using interval method,and uncertain CO frameworks with triple loop and double loop optimization structure are established respectively.The optimization results illustrate that,although the deterministic MDO result achieves higher reduction in objective function than the uncertain MDO result,the latter is more reliable than the former.

An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

In uncertainty analysis and reliability-based multidisciplinary design and optimization(RBMDO)of engineering structures,the saddlepoint approximation(SA)method can be utilized to enhance the accuracy and efficiency of reliability evaluation.However,the random variables involved in SA should be easy to handle.Additionally,the corresponding saddlepoint equation should not be complicated.Both of them limit the application of SA for engineering problems.The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments.However,the traditional moment matching method is not very accurate generally.In order to take advantage of the SA method and the moment matching method to enhance the efficiency of design and optimization,a fourth-moment saddlepoint approximation(FMSA)method is introduced into RBMDO.In FMSA,the approximate cumulative generating functions are constructed based on the first four moments of the limit state function.The probability density function and cumulative distribution function are estimated based on this approximate cumulative generating function.Furthermore,the FMSA method is introduced and combined into RBMDO within the framework of sequence optimization and reliability assessment,which is based on the performance measure approach strategy.Two engineering examples are introduced to verify the effectiveness of proposed method.

On Application of Mathematic Idea and Method in English Grammar Teaching and Learning

English grammar is at any time the important part of English learning,even if under the implementation of the New Course Standard.However,English grammar is considered to be difficult due to its complexity.My paper here is to explore and study the application of mathematic ideas and methods in English grammar teaching and learning,helping to facilitate the students to master the regularities,accuracy and systematization of English grammar,to improve learning efficiency,to enhance the learners' logic thinking,and at the same time,pointing out the specific strategies in practical use,which can be of great significance to the students' innovation and creativity and the students' development of the ability of cross-subject study advocated by both the Quality-Education and New Curriculum Standard.

Effect of Variable Selection on Multidisciplinary Design Optimization:a Flight Vehicle Example

Different multidisciplinary design optimization （MDO） problems are formulated and compared. Two MDO formulations are applied to a sounding rocket in order to optimize the performance of the rocket. In the MDO of the referred vehicle, three disciplines have been considered, which are trajectory, propulsion and aerodynamics. A special design structure matrix is developed to assist data exchange between disciplines. This design process uses response surface method （RSM） for multidisciplinary optimization of the rocket. The RSM is applied to the design in two categories： the propulsion model and the system level. In the propulsion model, RSM determines an approximate mathematical model of the engine output parameters as a function of design variables. In the system level, RSM fits a surface of objective function versus design variables. In the first MDO problem formulation, two design variables are selected to form propulsion discipline. In the second one, three new design variables from geometry are added and finally, an optimization method is applied to the response surface in the system level in order to find the best result. Application of the first developed multidisciplinary design optimization procedure increased accessible altitude （performance index） of the referred sounding rocket by twenty five percents and the second one twenty nine.

Two-phase Method without Any Artificial Variable

A method is provided to achieve an initial basic feasible solution of a linear programming in this paper. This method dose not need introducing any artificial variable, but needs only solving an auxiliary linear programming. Compared with the traditional two-phase method, it has advantages of saving the memories and reducing the computational efforts.

Incessant Allocation Method for Solving Transportation Problems

Industries require planning in transporting their products from production centres to the users end with minimal transporting cost to maximize profit. This process is known as Transportation Problem which is used to analyze and minimize transportation cost. This problem is well discussed in operation research for its wide application in various fields, such as scheduling, personnel assignment, product mix problems and many others, so that this problem is really not confined to transportation or distribution only. In the solution procedure of a transportation problem, finding an initial basic feasible solution is the prerequisite to obtain the optimal solution. Again, development is a continuous and endless process to find the best among the bests. The growing complexity of management calls for development of sound methods and techniques for solution of the problems. Considering these factors, this research aims to propose an algorithm “Incessant Allocation Method” to obtain an initial basic feasible solution for the transportation problems. Several numbers of numerical problems are also solved to justify the method. Obtained results show that the proposed algorithm is effective in solving transportation problems.

Multidisciplinary Approach for a Basement Aquifer Location in Tanda Region, Côte d’Ivoire

The lack of knowledge about fracture systems in Tanda region has led to an approximative establishment of drilling and so a difficult access to groundwater. Thus, a multidisciplinary approach including satellite imagery and electrical resistivity method was conducted with the main objective to locate productive fractures of water in the study area. Indeed, 195-54, 195-55, 196-54, and 196-55 scenes of Landsat 7 ETM+ satellite images were used. Also, sixty-two (62) vertical electrical soundings (VES) of the Schlumberger configuration and hundred twenty-nine (129) electrical trailing (ET) were performed with a resistivity-meter SYSCAL Pro. Thanks to different treatments applied to satellite images, structural lineaments have been extracted whose main directions are N00-10 (N-S), N90-100 (E-W), N70-80 and N100-110. The interpretation of electrical trailing data made it possible to validate the lineament map by the determination of the fracturing directions. Those are NW-SE, N-S, NE-SW and to some extent E-W. The result of the electrical sounding data showed the presence of three geoelectric layers comprising firstly cuirass and lateritic clays and possibly topsoil, secondly sands and/or clay sandstone and firdly either granites or sandstones or schists. The second geoelectrical layer corresponds to the potential aquifer because of its relatively low electrical resistivity values (13 Ω·m to 180 or 240 Ω·m). In addition, drillings established at the right of these geological structures provided an average water yield of 4.22 m3·h-1, sufficient for rural hydraulic. Moreover, these results made it possible to obtain a correlation between drilling productivity and the major directions of fracturing. This indicates that the most productive directions are in order of importance NE-SW, NW-SE, E-W and finally N-S. They also correspond to the major fracturing directions of Tanda region. These results are encouraging and contribute to a better implementation of future drilling in this region.

A Modified Projection Method for Linear Feasibility Problems

In this paper, we present a modified projection method for the linear feasibility problems （LFP）. Compared with the existing methods, the new method adopts a surrogate technique to obtain new iteration instead of the line search procedure with fixed stepsize. For the new method, we first show its global convergence under the condition that the solution set is nonempty, and then establish its linear convergence rate. Preliminary numerical experiments show that this method has good performance.

Improvement of decocting method for Kampo medicines using a microwave oven to extend its applications in clinical practice

Decoction of Kampo medicines plays an important role in clinical practice, especially in individualized treatment, while the inconvenience and a long time requirement of the decocting process are impediments to its widespread use in Japan. In this study, we improved the decocting method by using a microwave oven such as those found in most kitchens. To validate the feasibility and safety of this new method, we decocted kakkonto, which is the most widely used formula in clinical treatment in Japan, and keishikabushito, which contains toxic components using a microwave oven. Regarding the contents of 8 characteristic components in the kakkonto decoction and the contents of 6 toxic components in the keishikabushito decoction as indices, and with the extraction and detoxification effects equal to those of the conventional decocting method as targets, we optimized the decocting conditions with Response Surface Methods. With this new method, it took 35 min to obtain almost the same extraction effect for kakkonto as with the conventional decocting method, which takes 40 min;meanwhile, it took only 45 min to detoxify keishikabushito, which takes 60 min using the conventional decocting method. Decocting Kampo medicines with a microwave oven is feasible and as safe as the conventional decocting method. It is a convenient, safe, time-saving method, and may be applied widely in clinical practice. This innovation should allow more patients to benefit from decoction and the individualized treatment it offers.

基于全纯嵌入法的配电网光伏接纳能力评估方法

针对大规模分布式光伏接入给配电网带来的电压越限风险,提出了一种基于改进全纯嵌入法的光伏接纳能力评估方法。首先,引入离散-聚合方法对时序数据进行处理,利用所生成极端场景集代替原序列进行接纳能力评估;其次,在传统全纯嵌入模型基础上构建了自定义方向模型,进一步推导了满足电压约束的可行域范围,并将节点Sigma轨迹与可行域边界相交作为单次运算下光伏最大接纳容量的判据;然后,利用蒙特卡罗模拟生成相互独立的光伏接入方案,使用所提判据确定各方案下极端场景集对应的接纳容量;最后,统计计算结果,获取光伏接纳容量的累计分布曲线,以此确定电压越限风险下系统的光伏接纳能力。在IEEE 33节点配电网系统上验证了所提方法的有效性和可行性。

Dependability Evaluation of a Vehicle System by Simulation Method

The vehicle system studied in this paper is a type of complex repairable system in which the subsystems follow various failure distributions and conform to arbitrary failure and repair distributions.The failure data of subsystems are sometimes lacking,and the reliability test sample sizes tend to be small.Monte-Carlo technique combined with Bayes method is used to evaluate its dependability(reliability and maintainability).Following the "first-in,first-out" queuing rule,the logic relation of dependability is established by means of repairing priority and event lists.Simulation outputs the entire history of a mission,statistics of reliability and maintainability parameters and provides the basic data for system reliability design and maintainability management.

MDT联合PBL教学在神经科住院医师培训中的应用及对医师临床思维能力的影响分析

目的探究神经科住院医师培训中应用多学科协作(multidisciplinary team,MDT)联合以问题为导向的教学方法(problem-based learning,PBL)的效果及对医师临床思维能力的影响。方法选取2022年3月—2023年3月潍坊医学院附属医院46名参加神经科住院医师培训的住院医师作为研究对象按照入科顺序分为两组,各23名。对照组(2022年3—9月)采取常规教学模式培训,研究组(2022年10月—2023年3月)采取MDT联合PBL教学模式培训,对比综合成绩评分、自学能力评分、临床思维能力评分及教学满意度评分。结果研究组医师综合成绩(理论知识、临床实践操作能力)评分、自学能力评分、临床思维能力评分均高于对照组,差异有统计学意义(P均<0.05)。组间教学满意度比较,研究组为100.00%(23/23)明显高于对照组73.91%(17/23),差异有统计学意义(χ^(2)=4.792,P<0.05)。结论MDT联合PBL教学用于神经科住院医师培训,可丰富医师理论知识,增强实践操作能力,提高自学能力及临床思维能力,教学满意度高。

多学科融合下的“微机原理与接口技术”课程体系建设

“微机原理与接口技术”课程是电子信息类专业的专业必修课。目前,西安工业大学“微机原理与接口技术”课程体系与其他学科交融性较差,课程内容与实际工程问题脱轨严重。为了拓展课程的广度与实用性,以西安工业大学“微机原理与接口技术”课程现有课程体系为背景,指出了现有课程体系的缺点,并从实施多维度课程培养模式、优化重组新课程内容、强化综合实践能力培养、完善考核形式等四方面提出了一些改革措施,形成了多学科融合下的课程培养方案,进一步强化了学生的工程实践能力,激发了学生的创新意识及动手能力,以期为多学科交叉融合课程培养体系的建设提供一定的参考。

多学科融合的妇产科在线PBL与传统PBL教学法的比较研究

目的探讨基于问题的学习(problem-based learning,PBL)教学法中,在线PBL教学法在多学科融合背景下的妇产科教学中的效果。方法选取2022年4月在广州医科大学附属第三医院行PBL见习的203名学生,根据教学方法不同分为试验组(n=153)和对照组(n=50),试验组采用在线PBL教学法,对照组采用传统PBL教学法。导师使用标准化表格对学生进行能力评估,包括参与度、对案例的准备、文献查阅能力、创新思维能力、解决问题能力、批判思维能力、归纳整理能力、沟通表达能力、团队合作能力,并进行比较分析。结果与对照组相比,试验组的学生创新思维能力[(7.99±0.82)分vs.(7.60±0.73)分]、解决问题能力[(8.46±0.75)分vs.(8.08±0.88)分]、批判思维能力[(7.93±0.82)分vs.(7.58±0.81)分]更高,差异有统计学意义(P<0.05)。结论在多学科融合的妇产科教学中,与传统PBL教学法相比,在线PBL教学法有助于本科生在学习中创新思维能力,解决问题能力和批判思维能力的培养,是一种较佳的教学模式。