Identifikasi Faktor-Faktor Penyebab Berkontribusi Terjadinya Kegagalan Konstruksi Jalan dengan Metode Fault Tree Analysis (FTA)

Kegagalan konstruksi merupakan suatu kondisi penyimpangan, kesalahan dan kerusakan dari hasil pekerjaan konstruksi yang dapat mengakibatkan keruntuhan bangunan atau konstruksi. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang berkontribusi terjadinya kegagalan struktur jalan Bukit Manggis Kabupaten Solok Selatan menurut persepsi para stakeholder proyek. Metode penelitian menggunakan metode deskriptif kualitatif melalui observasi di lokasi proyek dan wawancara mendalam kepada para stakeholder. Hasil data wawancara dianalisis menggunakan metode Fault Tree Analysis (FTA) dan Methode for Obtaining Cut Set (MOCUS). Berdasarkan hasil identifikasi, di peroleh 7 (tujuh) faktor-faktor yang berkontribusi terjadinya kegagalan pada struktur jalan yaitu; (1) Perencanaan, (2) Pelaksanaan, (3) Bencana alam, (4) Komunikasi, (5) Budaya organisasi, (6) Biaya serta (7) Kondisi iklim. Faktor-faktor kegagalan konstruksi paling dominan menurut persepsi stakeholder adalah bencana alam, kondisi iklim, budaya organisasi dan komunikasi. Maka dari itu, diharapkan masing-masing stakeholder memberikan perhatian khusus terhadap faktor penyebab yang telah diidentifikasi.

Risk Analysis of Instability Failure of Earth–Rock Dams Based on the Fuzzy Set Theory

Determining the anti-sliding instability risk of earth–rock dams involves the analysis of complex uncertain factors, which are mostly regarded as random variables in traditional analysis methods. In fact, fuzziness and randomness are two inseparable uncertainty factors influencing the stability of earth–rock dams. Most previous research only focused on the randomness or the fuzziness of individual variables. Moreover, dam systems present a fuzzy transition from a stable state into a failure state. Therefore, both fuzziness and randomness of the influencing factors should be considered in the same framework, where the instability of an earth–rock dam is regarded as a mixed process. In this paper, a fuzzy risk model of instability of earth–rock dams is established by considering the randomness and fuzziness of parameters and the failure criteria comprehensively. We obtained the probability threshold of instability risk of earth–rock dams by Monte-Carlo simulation after the fuzzy parameters were transformed into interval numbers by cut set levels. By applying the proposed model to the instability analysis of the Longxingsi Reservoir, the calculation results showed that the lower limits of risk probability under different cut set levels exceeded the instability risk standard of grade C for earth–rock dams. Compared with the traditional risk determination value, the risk interval obtained with the proposed methods reflects different degrees of dam instability risk and can provide reference for dam structure safety assessment and management.

Research on Site Selection Method of Battery Energy Storage System Based on Critical CutSet Identification

Under different operating conditions, the influence of energy storage battery on the power grid is different, and the location and capacity determination methods are also different. Therefore, how to scientifically and reasonably select the location is of great significance. This paper proposes a candidate set identification method for the most vulnerable branch and critical cut set of power system transient stability based on branch potential energy, and uses the improved comprehensive index to identify the critical cut set. This method does not need to wait for the end of time domain simulation to determine the most vulnerable lines and critical cut sets, thus providing the basis for the location of battery energy storage system (BESS). Through the power system comprehensive analysis program (PSASP) simulation, the accuracy of theoretical analysis and engineering practicability are verified.

A modified cut-set method for mechanical subassembly identification

Purpose The purpose of this paper is to perform a comparative assessment on working of the existed subassembly identification (SI) methods, which are widely practiced during the product development stage and to propose an improved method for solving the SI problem in assembly sequence planning (ASP). Design/methodology/approach The cut-set method is found as a suitable method among various knowledge-based methods such as the theory of loops, theory of connectors and theory of clusters for the workability enhancement to meet the current requirements. Necessary product information is represented in the matrix format by replacing the traditional AND/OR graphs and the advanced predicates are included in the evaluation criteria. Findings The prominent methods in SI are followed a few of the predicates to avoid complexity in solution generation. The predicate consideration is found as the most influencing factor in eliminating the infeasible part combinations at SI. However, the quality of identified subassemblies without advanced predicates is not influencing the solution generation phase but practical applicability is affecting adversely. Originality/value The capability of performing SI by the cut-set method is improved to deal with the complex assembly configurations. The improved method is tested by applying on different assembly configurations and the effectiveness is compared with other existent methods of ASP along with the conventional method.

Research on Reliability Optimization Design of Mechanical Structure Based on Computational Intelligence

In order to extend the actual service life of mechanical equipment components and realize the reasonable protection of applied structural components, the reliability optimization design of mechanical structure based on computational intelligence is studied. With the help of wavelet neural network, the established reliability and reliability index are obtained, and then the basic theory of reliability and computational intelligence technology are studied through the reliability optimization of mechanical zero structure. On this basis, the application concepts of reliability design method are defined, and the final calculation result of reliability optimization value is obtained by combining fuzzy set and level cut set, so as to realize the reliability optimization design of mechanical structure based on computational intelligence. The experimental results show that, compared with the traditional design method, the optimization design method supported by computational intelligence technology can better improve the disadvantages of mechanical structure object, and has strong practical application value in extending the reliability application time.

An Improved FFIP Method Based on Mathematical Logic and SysML

In recent years, the model-based safety analysis (MBSA) has been developing continuously. The Functional Failure Identification and Propagation (FFIP) method is a graphics processing technology which supports the analysis of fault propagation paths before making costly design commitments. However, the traditional FFIP has some deficiencies. In this paper, we extend the functional failure logic (FFL) in the FFIP and introduce the concept of deviation. So, FFIP can be used to analyze the failure process of the systems and make the logical analysis of functional failure easier. Based on the extended FFL, we present a new overview of the FFIP. The FFIP is improved by using mathematical logic and Systems Modeling Language (SysML). The standard expression of FFL is realized, which is conducive to the subsequent modeling and modification. Additionally, we use the failure logic analysis in the FFIP to improve the state machine diagram (SMD) in SysML. Finally, the improved FFIP method is used to analyze the fault propagation paths of the system and Simulink is used for simulation. The fault tree is generated according to the simulation results, the minimum cut set is calculated, and the key failure parts of the system are obtained.

Parallel FCM clustering algorithm of fuzzy number based on cut set

Aiming at the problem of complex method and low efficiency of fuzzy numbers in classification processing, a parallel Fuzzy CMeans (FCM) clustering method based on cut set is proposed. Firstly, according to the decomposition theorem, the fuzzy numbers are divided horizontally into the form of the union of interval numbers, and then the interval numbers are transformed into the determined “real” data, and the parallel FCM clustering algorithm is used to classify the fuzzy numbers. The theoretical analysis and application show that the method has good classification accuracy and efficiency for fuzzy data clustering.

Research on hesitant fuzzy clustering method based on fuzzy matroids

In this paper, to improve the situation of singleness of selecting results in hesitant fuzzy set decision-making and expand the range of choices for decision makers, we construct a hesitant fuzzy set clustering algorithm combined with fuzzy matroid operation. The algorithm synthesizes the r-cut set, fuzzy shrinking matroids in the fuzzy matroids and the operational properties of the fuzzy derived matroids, the r value also is used to connect the two types of fuzzy matroids to form a clustering algorithm. Finally, we apply the algorithm to the hesitant fuzzy set decision-making of job seekers choosing recruitment websites, each recruitment website as an optional scheme is divided into three categories of excellent to inferior schemes to provide job seekers with ideas and methods for favorably selecting recruitment websites.