Fuzzy based decision support method for selection of sustainable wastewater treatment technologies

Inadequate decision support tools have led to selection of inappropriate wastewater treatment technologies.The objectives of this research were to investigate performance data for wastewater treatment technologies,develop a Decision Support Method(DSM)for evaluating performance of technologies,and to validate the developed method.The method was developed through evaluation of performance of wastewater treatment technologies against environmental and economic indicators.Fuzzy logic techniques in form of linguistic variables were applied in order to support decision making under uncertainty.The DSM relied on performance evaluation in order to rate effectiveness of wastewater treatment technologies.DSM was validated through a training tool in ED-WAVE,a model developed by a consortium of European and Asian countries.The reliance of the DSM on performance evaluation was an improvement on the existing decision support tools such as ED-WAVE that relied on retrieval of past performance data.As DSM integrated environmental and economic factors in evaluating wastewater treatment technologies,it was thus able to select a process that was not only environmentally sustainable but also economically affordable.

Analysis of the Improvement Methods for Equipment Maintenance Support

According to military requirement, and based on the problems of equipmentmaintenance support methods in high-tech battles, each element supporting equipment maintenance isanalyzed, and the methods for improving equipment maintenance are proposed.

Light-Weighted Decision Support Framework for Selecting Cloud Service Providers

Multi-criteria decision making(MCDM)is a technique used to achieve better outcomes for some complex business-related problems,whereby the selection of the best alternative can be made in as many cases as possible.This paper proposes a model,the multi-criteria decision support method,that allows both service providers and consumers to maximize their profits while preserving the best matching process for resource allocation and task scheduling.The increasing number of service providers with different service provision capabilities creates an issue for consumers seeking to select the best service provider.Each consumer seeks a service provider based on various preferences,such as price,service quality,and time to complete the tasks.In the literature,the problem is viewed from different perspectives,such as investigating how to enhance task scheduling and the resource allocation process,improve consumers’trust,and deal with network problems.This paper offers a novel model that considers the preferences of both service providers and consumers to find the best available service provider for each consumer.First,the model adopts the best-worst method(BWM)to gather and prioritize tasks based on consumers’and service providers’preferences.Then,the model calculates and matches similarities between the sets of tasks from the consumer’s side with the sets of tasks from the provider’s side to select the best service provider for each consumer using the two proposed algorithms.The complexity of the two algorithms is found to be O(n3).

Casing life prediction using Borda and support vector machine methods

Eight casing failure modes and 32 risk factors in oil and gas wells are given in this paper. According to the quantitative analysis of the influence degree and occurrence probability of risk factors, the Borda counts for failure modes are obtained with the Borda method. The risk indexes of failure modes are derived from the Borda matrix. Based on the support vector machine （SVM）, a casing life prediction model is established. In the prediction model, eight risk indexes are defined as input vectors and casing life is defined as the output vector. The ideal model parameters are determined with the training set from 19 wells with casing failure. The casing life prediction software is developed with the SVM model as a predictor. The residual life of 60 wells with casing failure is predicted with the software, and then compared with the actual casing life. The comparison results show that the casing life prediction software with the SVM model has high accuracy.

Computer System Reliability Allocation Method and Supporting Tool

This paper presents a computer system reliability allocation method that is based on the theory of statistic and Markovian chain,which can be used to allocate reliability to subsystem, to hybrid system and software modules. A relevant supporting tool built by us is introduced.

Novel Design Method of COG Measurement System Via Supporting Reaction Method

Center of gravity(COG)is an important parameter of projectiles and rockets,for which supporting reaction method(or support reaction method)is an important COG measurement method.Based on this supporting reaction method a novel design method is proposed to determine the key design parameters of the COG measurement system.The method can quantitatively analyze the influence of the design parameters on the COG accuracy,in the measurement system designed with supporting reaction method.Using the principle of static balance,the error propagation theory,and the system accuracy analysis method,the equal-range required sensor precision(RSP)surface and non-equal-range required sensor pair precision(RSPP)adapted surface are adopted.The influence of random errors(like sensor accuracy and distance calibration accuracy)is analyzed.The selection strategy of equal-range and non-equal-range sensors is chosen,and then the recommended calibration accuracy values are obtained.For the quality detection accuracy of±0.6 kg and the axial COG detection accuracy of±1.5 mm,the RSP surface is drawn by the proposed method,and the force sensor with±0.23 kg detection accuracy is selected.The experimental verification meets the accuracy requirements and verifies the effectiveness of the proposed design method for the system parameters of the COG measurement equipment.

Vibration reliability analysis for aeroengine compressor blade based on support vector machine response surface method

To ameliorate reliability analysis efficiency for aeroengine components, such as compressor blade, support vector machine response surface method(SRSM) is proposed. SRSM integrates the advantages of support vector machine(SVM) and traditional response surface method(RSM), and utilizes experimental samples to construct a suitable response surface function(RSF) to replace the complicated and abstract finite element model. Moreover, the randomness of material parameters, structural dimension and operating condition are considered during extracting data so that the response surface function is more agreeable to the practical model. The results indicate that based on the same experimental data, SRSM has come closer than RSM reliability to approximating Monte Carlo method(MCM); while SRSM(17.296 s) needs far less running time than MCM(10958 s) and RSM(9840 s). Therefore,under the same simulation conditions, SRSM has the largest analysis efficiency, and can be considered a feasible and valid method to analyze structural reliability.

Time-variant reliability analysis of three-dimensional slopes based on Support Vector Machine method

In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. A new reliability analysis approach was presented based on three-dimensional Morgenstern-Price method to investigate three-dimensional effect of landslide in stability analyses. To obtain the reliability index, Support Vector Machine (SVM) was applied to approximate the performance function. The time-consuming of this approach is only 0.028% of that using Monte-Carlo method at the same computation accuracy. Also, the influence of time effect of shearing strength parameters of slope soils on the long-term reliability of three-dimensional slopes was investigated by this new approach. It is found that the reliability index of the slope would decrease by 52.54% and the failure probability would increase from 0.000 705% to 1.966%. In the end, the impact of variation coefficients of c and f on reliability index of slopes was taken into discussion and the changing trend was observed.

REQUIREMENTS AND DESIGN METHOD FOR MATCHING AIRCRAFT GUNS WITH THEIR SUPPORTING STRUCTURE

In aircraft structural dynamic design the matching of guns with their supporting structure is one of the most important tasks on which hinges the success or failure of the structural design. The design curves for matching guns with their supporting structure can be obtained from response calculations of the plate-spring system supporting the gun on the ground,the model structure tested on the ground and the actual structure.A set of matching curves is given for engineering application.Then,the matching design can be accomplished by means of impact load spectrograms so as to perform an optimal structural design and to make further improvements on dynamic design program.

Elaboration of an Easy Aqueous Sol-Gel Method for the Synthesis of Micro- and Mesoporous <i>γ</i>-Al₂O₃Supports

An aqueous sol-gel method for the synthesis of γ-Al2O3 supports has been developed for the use in tar reforming applications. It was determined the influences of two different aluminum precursors (aluminum sec-butoxide (Al[OCH(CH3)CH2CH3]3) and aluminum nitrate (Al(NO3)3)) on the textural and crystallographic properties of Al2O3 supports. Only the formation of γ-Al2O3 is aimed in order to use these alumina materials as catalytic supports, because it presents high specific surface area and pore volume values. Additionally, the synthesis of γ-Al2O3 was realized with the use of a functionalized silicon precursor, [3-(2-aminoethylamino)propyl]trimethoxysilane, called EDAS. By the presence of an ethylenediamine group in this molecule, it is possible to chelate metallic ions and to highly increase their dispersion at a molecular level during the synthesis of metallic catalysts supported on alumina, which is an asset for catalytic applications. So it was developed a synthesis sol-gel procedure for the cogelation between the functionalized silicon alkoxide EDAS and alumina precursor. The alumina supports synthesized with Al(NO3)3 as precursor presented higher porous values than the ones obtained with aluminium sec-butoxide precursor. Since nitrate salts are much easier to handle than alkoxides, these observations allowed validating Al(NO3)3 as aluminum source for the future synthesis procedures for metallic catalysts supported on alumina.

基于硝化棉助燃的含能粘合剂爆热特征值测试研究

为了表征含能粘合剂的能量特性,开展了含能粘合剂的燃烧热、生成焓与爆热特征值的测试研究并评估了将其作为含能粘合剂能量特性量化指标的合理性,探索了利用硝化棉(NC)助燃来测试含能粘合剂爆热特征值的方法。结果表明:当含能粘合剂/NC质量比达到1∶5时,绝大多数含能粘合剂可以充分燃烧;以硝化棉为助燃物可准确测取含能粘合剂的爆热特征值,所测聚硝酸酯基缩水甘油醚(PGN)与聚乙烯醇硝酸酯(PVN)的爆热特征值分别为3164、4713 kJ·kg^(-1),与文献值的相对误差均小于5%;燃烧热不能准确反映含能粘合剂的能量优势,采用爆热特征值可较好地表征含能粘合剂的能量特性,避免了生成焓正负之分导致估值体系自我矛盾的缺点;在隔绝氧气的条件下,含能粘合剂能量贡献值从小到大依次为GETPE<FATPE<GAP<PBAMO<NC(12%)<PGN <PVN。

深基坑支护理念演进和设计方法改进剖析

基于我国30多年建设实践,分析现有深基坑支护临时性理念、与主体结构相结合理念实施的优点和不足,提出促进基坑支护工程高质量发展的永久化理念。结合济南某基坑工程,阐释三个理念的逐次提升和相应支护结构的计算内容,定义适应与主体结构相结合理念、永久化理念的结构岩土化、岩土结构化设计方法;重点分析土钉墙与抗浮锚杆相结合的复合土钉墙的设计,以及抗浮锚杆与外伸支撑、水平楼板永久支护结构中抗浮锚杆的力学性状与耐久性,分析了永久支护对于地下室外墙受力机制的影响,阐释深基坑支护理念演化方向和与之适应的设计改进内容。对于反思我国岩土与结构设计管理体制,促进基坑与基础设计理论和方法进步,推动“新发展理念”在基坑工程的实践具有导向价值。

顶棒支撑法复位髓内钉固定治疗难复性股骨转子间骨折的临床效果

目的分析顶棒支撑法复位髓内钉固定治疗难复性股骨转子间骨折的临床效果。方法于2020年8月至2022年8月在南阳市中心医院收集病例展开研究,将严格按照纳排标准筛选的106例难复性股骨转子间骨折患者作为研究对象,根据随机数字表法分为研究组与对照组,各53例。对照组接受切开或有限切开复位结合髓内钉固定治疗,研究组接受顶棒支撑法复位髓内钉固定。统计对比两组患者围手术期情况、骨折复位质量、术后恢复情况;对比两组患者术前、术后6个月髋关节功能评分;对比两组并发症发生率。结果研究组手术时间、骨折复位时间较对照组短,手术出血量较对照组少(P<0.05)。研究组骨折复位质量优于对照组(P<0.05)。研究组骨折愈合、开始负重和住院时间较对照组短(P<0.05)。术后6个月,两组髋关节功能评分均较术前提高,研究组高于对照组(P<0.05)。研究组并发症发生率[5.66%(3/53)]较对照组[18.87%(10/53)]低(P<0.05)。结论采用顶棒支撑法复位髓内钉固定治疗难复性股骨转子间骨折可减轻对机体的创伤,降低并发症发生率,提高复位效果,促进骨折愈合和髋关节功能恢复。

数据驱动儿童专科医院大型医疗设备运行评价体系建设

目的探索通过数据采集及分析评价儿童专科医院大型医疗设备运行水平的方法,提出大型医疗设备使用及配置建议。方法通过物联网终端采集设备运行数据,结合医院HIS、RIS、HRP等系统数据,建立儿童专科医院大型医疗设备评价指标体系,运用CRITIC法对单类、单台设备数据进行量化评价。结果医院大数据平台实现了对单台大型设备运行数据纵向分析并形成可视化图表,通过PC端及移动端展示。申康市级平台数据分析,实现对儿童专科医院大型设备运行水平的综合量化评价及使用配置建议。结论通过数据采集及分析,实现儿童专科医院大型设备运行评价体系建设,提升大型设备管理水平。

Krylov Iterative Methods for Support Vector Machines to Classify Galaxy Morphologies

Large catalogues of classified galaxy images have been useful in many studies of the universe in astronomy. There are too many objects to classify manually in the Sloan Digital Sky Survey, one of the premier data sources in astronomy. Therefore, efficient machine learning and classification algorithms are required to automate the classifying process. We propose to apply the Support Vector Machine (SVM) algorithm to classify galaxy morphologies and Krylov iterative methods to improve runtime of the classification. The accuracy of the classification is measured on various categories of galaxies from the survey. A three-class algorithm is presented that makes use of multiple SVMs. This algorithm is used to assign the categories of spiral, elliptical, and irregular galaxies. A selection of Krylov iterative solvers are compared based on their efficiency and accuracy of the resulting classification. The experimental results demonstrate that runtime can be significantly improved by utilizing Krylov iterative methods without impacting classification accuracy. The generalized minimal residual method (GMRES) is shown to be the most efficient solver to classify galaxy morphologies.

考虑湿度应力的深部软岩隧道大变形控制研究

为探明深部高地应力软岩隧道大变形产生机理,制定适应大变形控制措施,以月直山隧道为工程依托,首先明确求解围岩形变压力与松动压力的Kastner与Caquot公式,基于岩体弹塑性力学与连续介质理论建立围岩湿度应力解析解,采用收敛-约束法绘制出3种围岩应力作用下围岩与初期支护特征曲线,分析断面变形过程中围岩与支护结构相互作用规律及3种应力占比演化规律。分别以混凝土与型钢钢架作为二衬支护结构对月直山隧道围岩稳定性进行计算分析,明确考虑湿度应力与松动压力条件下隧道二衬最优支护时机与支护参数,以支护结构安全系数FS评判出最优支护方案并对隧道软岩大变形进行治理。结果表明:当围岩径向位移达到550 mm时,仅考虑形变压力Pi时围岩对支护结构的压力P仅为0.813 MPa,考虑湿度应力Pw与松动压力Pa时P增大为1.372 MPa,湿度应力与松动应力总占比达40.7%,仅考虑形变压力而设计的支护结构不满足围岩稳定性要求;根据“卸压支护”理念,确定以“位移释放峰值upeak=0.325 m”与“间距d=0.7 m”作为增设第二层钢架的最佳支护时机与支护参数,现场二次钢架设置24天后使围岩变形收敛于50.8 mm,围岩大变形得到控制,研究成果可为今后相关隧道工程设计与施工提供参考。

A Review of the Key Points in the Design of Small-Radius Curved Ramp Bridges

This article explores the fundamentals of small-radius curved ramp bridges.It covers the selection of box girder spans,support methods,and forms,along with design optimization techniques for this type of bridge structure.The purpose of this paper is to provide robust support for enhancing the design quality of these bridges and ensuring their efficacy in real-world applications.

基于空间投影和聚类划分的SVR加速算法

数据不仅能产生价值,还对统计学的科学发展提供了动力。随着科技的飞速发展,海量数据得以涌现,但大规模的数据会导致很多传统处理方法很难满足各领域对数据分析的需求。面对海量数据时代学习算法的低效性,分治法通常被认为是解决这一问题最直接、最广泛使用的策略。SVR是一种强大的回归算法,在模式识别和数据挖掘等领域有广泛应用。然而在处理大规模数据时,SVR训练效率低。为此,该文利用分治思想提出一种基于空间投影和聚类划分的SVR加速算法(PKM-SVR)。利用投影向量将数据投影到二维空间;利用聚类方法将数据空间划分为k个互不相交的区域;在每个区域上训练SVR模型;利用每个区域的SVR模型预测落入同一区域的待识别样本。在标准数据集上与传统的数据划分方法进行对比实验,实验结果表明该算法训练速度较快,并表现出更好的预测性能。

基于广域信息处理的配电网故障隔离技术研究

针对分布式电源并入配电网后,传统算法进行故障检测时存在定位准确度偏低、反应速度较慢的问题,文中基于广域信息处理技术提出了一种配电网故障隔离方法。该方法采用模态分解算法将故障复杂信号分解为多种类基础小信号,使用支持向量机对这些小信号进行数据分类。但由于传统支持向量机的收敛速度较慢,因此通过引入粒子群算法对其参数加以优化,从而提升模型的运算速度。实验结果表明,在加入分布式电源的电网中,所提算法的故障定位准确率为96.7%,平均运行时间则为43.9 s,且这两项参数在对比算法中均为最优。由此证明,该算法可应用于实际工程中,为配电网故障隔离提供技术支撑。