Probability and interval hybrid reliability analysis based on adaptive local approximation of projection outlines using support vector machine

This paper investigates structural reliability analysis with both random and interval variables, which is defined as a three‐classification problem and handled by support vector machine (SVM). First, it is determined that projection outlines on the limit‐state surface are crucial for describing separating hyperplanes of the three‐classification problem. Compared with the whole limit‐state surface, the region of projection outlines are much smaller. It will be beneficial to reduce the number of update points and the computational cost if SVM update concentrates on refining the approximate projection outlines. An adaptive local approximation method is developed to realize that the initial built SVM model is sequentially updated by adding new training samples located around the projection outlines. Using this method, the separating hyperplanes can be accurately and efficiently approximated by SVM. Finally, a new method is proposed to evaluate the failure probability interval based on Monte Carlo simulation and the refined SVM.     

Structural Analysis with Fuzzy Variables

Abstract: The analysis of existing structures requires engineers to model two types of uncertainty, cognitive and non-cognitive. The objective of this paper is to reexamine structural analysis methods by considering the cognitive type of uncertainty. Two analytical approaches are proposed for this purpose: (1) combining the displacement method with fuzzy arithmetic and (2) considering all possible permutations of extreme values of any uncertain variables in a structure using the displacement method. The first approach, which is based on fuzzy arithmetic, requires less computing time as compared with the permutations method but only obtains approximate solutions. However, the second approach produces the exact solution. For the purpose of illustration, the modulus of elasticity E is assumed to be an uncertain variable and is modeled as a triangular fuzzy number. The structural behavior was investigated due to this cognitive uncertainty in E. The results based on the second approach show that if E is a triangular fuzzy number, the member forces can be either fuzzy numbers or crisp values, depending on the structural type. In addition, modified definitions for fuzzy division and fuzzy subtraction are proposed in this paper. Applications of these modified definitions and proposed methods are also presented.     

SHM-based F-AHP bridge rating system with application to Tsing Ma Bridge

This paper aims at developing a structural health monitoring (SHM)-based bridge rating method for bridge inspection of long-span cable-supported bridges. The fuzzy based analytic hierarchy approach is employed, and the hierarchical structure for synthetic rating of each structural component of the bridge is proposed. The criticality and vulnerability analyses are performed largely based on the field measurement data from the SHM system installed in the bridge to offer relatively accurate condition evaluation of the bridge and to reduce uncertainties involved in the existing rating method. The procedures for determining relative weighs and fuzzy synthetic ratings for both criticality and vulnerability are then suggested. The fuzzy synthetic decisions for inspection are made in consideration of the synthetic ratings of all structural components. The SHM-based bridge rating method is finally applied to the Tsing Ma suspension bridge in Hong Kong as a case study. The results show that the proposed method is feasible and it can be used in practice for longspan cable-supported bridges with SHM system.     

Solid waste management under uncertainty: a generalized fuzzy linear programming approach

In this study, a generalized fuzzy linear programming (GFLP) method is developed to identify optimal waste-flow-allocation schemes under uncertainty. A stepwise interactive algorithm (SIA) is advanced to solve the GFLP model and generate solutions expressed as fuzzy sets. This solution method can handle fuzzy sets with known membership functions, regardless of the shapes of these functions. Moreover, solutions expressed as fuzzy sets can also be obtained through SIA. The developed method is applied to a case study of waste allocation planning problem under uncertainty. The results indicate that reasonable solutions can be obtained for planning waste allocation practices. Compared with interval solutions derived from interval linear programming method, the fuzzy solutions obtained through GFLP can provide more information. Therefore, the decision-makers can make tradeoffs between system stability and plausibility and thus identify desired policies for solid waste planning under uncertainty.     

结构方案设计模糊多属性决策的模糊贴近度方法

结构方案设计具有典型的“软科学”决策特点,需要运用“软设计”理论和“软计算”方法进行此类问题的求解。结构方案设计的问题求解过程包括方案生成、方案评价和方案决策三个子过程。其中,结构方案的决策属于典型的多属性决策问题,决策过程中需要运用决策者的偏好信息和方案属性的不确定性信息,因此,采用传统的多准则决策理论不能对此问题进行有效的求解。为此,本文建立了结构方案设计的模糊多属性决策模型,给出了属性模糊满意度矩阵的确定方法,以有效地处理模糊信息。为了克服直接采用欧式距离确定偏好最优方案的缺点,提出了一个基于模糊贴近度的模糊多属性决策方法,并给出了具体的求解程序。以某大跨空间结构方案设计为例,说明了结构设计方案优选的决策过程。实例应用的结果表明,本文提出的方法可以有效地处理不确定性环境下结构方案的优选决策问题。     

Fuzzy critical chain method for project scheduling under resource constraints and uncertainty

This paper develops a fuzzy critical chain method for project scheduling under resource constraints and uncertainty. The method consists of developing a desirable deterministic schedule under resource constraints, and adding a project buffer (PB) to the end of the schedule to deal with uncertainty. The size of the project buffer is determined by computations with fuzzy numbers. During project execution, the proposed method focuses on the penetration level in the project buffer, and dynamically updates the schedule to provide a more accurate schedule for actual progress. The use of a project buffer makes the method akin to critical chain project management (CCPM), although no feeding buffers are used. The proposed method is useful for both project planning and execution.     

Calibration of Structural Models Using Fuzzy Mathematics

Abstract: A calibration model is presented that quantifies the uncertainties associated with structural free vibration analysis. System identification objectives and fuzzy set mathematics are integrated to formulate an analysis methodology that enables the a priori prediction of the most probable sources of modeling error. By first developing fundamental fuzzy sets defining uncertainty in structural parameters such as stiffness and design loading, higher-level fuzzy sets governing dynamic behavior are obtained using the vertex method. Uncertainty in the dynamic parameters (natural frequency, frequency ratio, and structural response) are each represented using fuzzy mathematics, where membership functions are determined by performing multiple dynamic analyses involving confidence levels of model assumptions. A numerical example is presented to demonstrate the calibration model for a 13-story steel structure located in San Jose, California. Results show that the calibration model is capable of quantifying uncertainties in structural properties and behavior without requiring the measured data necessary for conventional system identification procedures.     

A grey fuzzy multiobjective programming approach for the optimal planning of a reservoir watershed. Part B: Application

The conflict between environmental protection of reservoir water quality and economic development by different uses of land within a watershed is a problem that constantly bothers the public officials in regional planning. Besides, the uncertainties regarding to the fuzzy goals in decision making and the impreciseness of parameter values always create additional difficulties in systems analysis. This paper applies the grey fuzzy multiobjective linear programming (GFMOLP) method for the evaluation of sustainable management strategies for optimal land development in a reservoir watershed. In particular, it demonstrates how uncertain messages in water resources management systems can be quantified by specific fuzzy membership functions and grey numbers in a multiobjective analytical framework. A case study of the planning for land-use programs in the Tweng-Wen reservoir watershed in Taiwan was prepared for the purpose of demonstration.     

合肥市派河污水规划方案模糊综合评价

污水系统规划领域中,含有大量无法定量表示的因素。采用层次分析(AHP)法与多层次模糊综合评判模型相结合的方法对合肥市派河污水系统规划方案进行评价。在分析污水系统规划影响因素的基础上,建立了由1个目标层、4个准则层和16个指标层组成的3层次16个因素的综合评价体系。运用AHP法确定了各因素的权重,运用模糊综合评价模型对2个污水系统规划方案进行了科学的评价,得出最佳规划方案。结果表明,该评价方法在实际规划和决策过程中具有可行性和合理性,进一步提高了污水工程决策的科学性。     

Patent analysis-based fuzzy inference system for technological strategy planning

This paper describes a technological strategy planning method that integrates patent analysis techniques with a fuzzy inference system (FIS). The method differentiates itself from the traditional technological management decision-making tools in its knowledge base. Instead of eliciting knowledge from domain experts, the proposed method adopts global patent databases as sources of knowledge for strategy planning. The patent analysis techniques are employed to evaluate the technological competitiveness of a firm in a specific technology domain. A FIS for technological strategy planning is developed. Critical attributes for inputs of the FIS including Patent Quantity (PQ), Revealed Patent Advantage (RPA), Patent Activity (PA), Be Cited Rate (BCR), and Relative Citation Index (RCI) are obtained with patent analysis techniques. Fuzzy decision rules are collected and summarized from published literature. A case study on precast concrete technology (PCT) is conducted. Two construction firms are selected for case study to illustrate the applicability of the proposed method under different scenarios. It is concluded from the case study that the proposed method provides a useful and systematic approach for construction firm to plan effective technological strategies.     

Analysis of textile-reinforced concrete structures under consideration of non-traditional uncertainty models

This article is a contribution towards the innovative development and practical application of structures reinforced by means of textile fabrics. Textile reinforcement embedded in fine-grained concrete not only finds application in new structures but may also be used for the additional strengthening of existing steel-reinforced concrete (RC) structures.

The article focuses on a FE-model suitable for folded-plate structures. This so-called multi-reference-plane model (MRM) is capable of describing the structural behavior of RC structures strengthened by textile-reinforced concrete (TRC) layers, because those are characterized by a multi-Kirchhoff kinematics. New TRC structures may also be analyzed with the aid of the MRM as structures with one reference plane only.

Experimental and numerical investigations demonstrate that structural responses of TRC structures are highly dependent on the spatial and temporal variation of the uncertain material and geometric data. For this reason the present paper concentrates on the generalized uncertainty modeling of material and geometric parameters with the aid of fuzzy and fuzzy random functions. The uncertainty models and the MRM are combined in the framework of the fuzzy stochastic finite element method (FSFEM). The introduced models are applied to three examples.     

Damage Pattern Recognition for Structural Health Monitoring Using Fuzzy Similarity Prescription

Abstract:   Structural health monitoring (SHM) is a systematic method for non-destructive evaluation of a structure's performance by sensing, extracting, patterning, and recognizing features of the structural response. Most SHM approaches focus on statistical analysis for damage identification considering only random uncertainties. This article introduces a method that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness which are statistically non-describable. The proposed method deals primarily with epistemic uncertainty. The method improves damage identification by performing damage pattern recognition using fuzzy sets. In this approach, healthy observations are used to construct a fuzzy set representing healthy performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed. Thus, an optimal group of fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. Piecewise linear functions are used as fuzzy membership functions representing the states of healthy and damaged. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fuzzy pattern recognition based on maximum approaching degree. A case study for damage pattern recognition of a model steel bridge is presented and discussed. The approach is capable of identifying damage patterns accurately.     

Approximation approach for personal estimation in safety analysis of existing structures

Different studies in recent years show that many structural failures are due to errors in planning, design, construction and utilization. These are difficult to quantify and have not been considered in probabilistic design methodologies (reliability theory). In practice the designer must use his practical experiences, the actual conditions and the pure speculations when evaluating safety factor values. Therefore, the reliability of structures is not only an objective but also a subjective concept, which is a property of the designer's state of knowledge. They need a way of combining all the subjective information, which are of multivalued nature and come from multiple sourcesof estimates.

In this study an inferential method applying fuzzy set and fuzzy logic to analyze safety of the existing structures is presented.     

一种新的模糊网络计算方法

基于对模糊网络计算方法的研究，提出了新的网络参数计算和关键线路判断方法。新方法将L-R三角模糊数引入到网络时间参数计算，并且采用模糊数大小排序的方法确定关键线路。算例说明，新方法是有效的、易操作的。     

Fuzzy-based optimised subset simulation for reliability analysis of engineering structures

This paper presents a numerical strategy for the efficient reliability assessment of engineering structures with random variables and fuzzy variables using fuzzy based optimised subset simulation (SS) approach. The proposed method relies on the performance function of the structure, which involves probability distribution functions and fuzzy variables for the modelling of the structural system. The values of the fuzzy variables for every alpha level are first obtained using the membership function. Therefore, the set values of the fuzzy variable bound the reliability of the structure, and this is evaluated using optimisation and efficient SS approach. The rationale behind the proposed strategy is to locate a failure domain or region where the objective function is minimised or maximised and compute the reliability using SS. The proposed algorithm in this study inherits the benefits of direct Monte Carlo approach in propagating the uncertainties associated with structural parameters but also demonstrate more robustness against the latter. The methodology can be applied to any engineering structures, and the applicability is demonstrated here, using a buried pipeline.     

WASTE FLOW ALLOCATION PLANNING THROUGH A GREY FUZZY QUADRATIC PROGRAMMING APPROACH

This paper proposes a grey fuzzy quadratic programming (GFQP) approach as a means for optimization analysis under uncertainty. The method combines the ideas of grey fuzzy linear programming (GFLP) and fuzzy quadratic programming (FQP) within a general optimization famework. It improves upon the previous GFLP method by using n grey control variables, ® (A,j (i = 1,2,..., n), for n constraints instead of one ® (X) for n constraints in order to incorporate the independent properties of the stipulation uncertainties; it also improves upon the FQP method by further introducing grey numbers for coefficients in A and C to effectively reflect the lefthand side uncertainties. Compared with the GFLP method, the GFQP approach is helpful for better satisfying model objective/constraints and providing grey solutions with higher system certainty and lower system cost; compared with the FQP method, more information of the independent uncertain features of not only the stipulations but also the lefthand side coefficients are effectively reflected in the GFQP method.

The GFQP modelling approach is applied to a hypothetical case study of waste flow allocation planning under uncertainty, with the input model stipulations fluctuating within wide intervals and having independent uncertain characteristics. The results indicated that reasonable solutions have been generated. Comparisons between the GFQP and FQP/GFLP solutions are also provided, which demonstrate that the GFQP method could better reflect system uncertainties and provide more realistic and applicable solutions with lower system uncertainties and higher system benefits.     

Cost estimation of structural skeleton using an interactive automation algorithm: A conceptual approach

This paper addresses a new concept for generating bills of quantities (B.o.Qs) using AutoCAD drawings for a building project, which demonstrates the application of Industry Foundation Class (IFC), developed by International Alliance for Interoperability (IAI). The procedure considers types of materials and the structural shapes of the AutoCAD drawings to compute the cost of the structural skeleton elements using interactive automation. The main concept focuses on using layer computation of the AutoCAD drawing after converting it into a drawing inter-exchangeable file format (DXF). Once the coordinates are detected, it is easier to determine the area and volume for any structural shape, including circles and polygons. The extracting method is a new technique for structural engineers and quantity surveyors to estimate required material for beam, columns, slabs and foundations. The algorithm extracts and recognizes the layers and objects from a two dimensional DXF drawing along with the coordinates information. The results obtained using this technique are more accurate and reliable than manual procedures or any other traditional techniques. In this paper, an automated and interactive procedure for B.o.Q computation is demonstrated. The process involves a user-friendly interface, dynamic linking to the structural drawings and tracking of B.o.Q modifications at the same time.     

Cost estimation of structural skeleton using an interactive automation algorithm: A conceptual approach

This paper addresses a new concept for generating bills of quantities (B.o.Qs) using AutoCAD drawings for a building project, which demonstrates the application of Industry Foundation Class (IFC), developed by International Alliance for Interoperability (IAI). The procedure considers types of materials and the structural shapes of the AutoCAD drawings to compute the cost of the structural skeleton elements using interactive automation. The main concept focuses on using layer computation of the AutoCAD drawing after converting it into a drawing inter-exchangeable file format (DXF). Once the coordinates are detected, it is easier to determine the area and volume for any structural shape, including circles and polygons. The extracting method is a new technique for structural engineers and quantity surveyors to estimate required material for beam, columns, slabs and foundations. The algorithm extracts and recognizes the layers and objects from a two dimensional DXF drawing along with the coordinates information. The results obtained using this technique are more accurate and reliable than manual procedures or any other traditional techniques. In this paper, an automated and interactive procedure for B.o.Q computation is demonstrated. The process involves a user-friendly interface, dynamic linking to the structural drawings and tracking of B.o.Q modifications at the same time.     

巴基斯坦体育馆四柱支承空间网架的设计及施工

本文主要介绍建设在巴基斯坦的体育馆工程的四柱支承网架的选型与在各种荷载下的计算方法及其结果分析。在计算方法上对空间桁架矩阵位移法与网格梁差分法以及模型网架试验结果作了对比分析。在设计及施工方面对网架结构的布置及主要节点构造设计和主要顶升施工技术作了扼要介绍。     

基于模糊逻辑与神经网络的高层结构半主动控制

根据剪切型结构动力特性提出AVSD开关控制律。把开关控制律作为专家知识,利用模糊逻辑转化为模糊控制规则。为了进行时滞和结构动力特性时变的控制补偿,采用神经网络在线自适应跟踪辨识方法进行在线辨识和响应预测。最后以某框架结构为例进行仿真分析,结果表明这一方法控制效果及鲁棒性好、实际应用方便可靠。