Predicting fatigue life by numerical methods was almost impossible in the field of rubber materials. One of the reasons is that there is not obvious fracture criteria caused by nonstandardization of material and excessively various way of mixing process. But, tearing energy as fracture factor can be applied to a rubber-like material regardless of different types of fillers, relative to other fracture factors and the crack growth process of rubber could be considered as the whole fatigue failure process by the existence of potential defects in industrial rubber components. This characteristic of fatigue failure could make it possible to predict the fatigue life of rubber components in theoretical way. FESEM photographs of the surface of industrial rubber components were analyzed for verifying the existence and distribution of potential defects. For the prediction of fatigue life, theoretical way of evaluating tearing energy for the general shape of test-piece was proposed. Also, algebraic expression for the prediction of fatigue life was derived from the rough cut growth rate equation and verified by comparing with experimental fatigue lives of dumbbell fatigue specimen in various loading condition.
KSII Transactions on Internet and Information Systems (TIIS)
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v.13
no.10
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pp.5058-5077
/
2019
Traditional regenerating codes are designed to tolerate node failures with optimal bandwidth overhead. However, there are many types of partial failures inside the node, such as latent sector failures. Recently, proposed regenerating codes can also repair intra-node failures with node-level redundancy but incur significant bandwidth and I/O overhead. In this paper, we construct a new scheme of regenerating codes, called IR-RBT codes, which employs intra-node redundancy to tolerate intra-node failures and serve as the help data for other nodes during the repair operation. We propose 2 algorithms for assigning the intra-node redundancy and RBT-Helpers according to the failure probability of each node, which can flexibly adjust the helping relationship between nodes to address changes in the actual situation. We demonstrate that the IR-RBT codes improve the bandwidth and I/O efficiency during intra-node failure repair over traditional regenerating codes but sacrifice the storage efficiency.
Purpose : The demand for higher fuel economy vehicles has helped develop fuel-efficient vehicles such as a CVVL called continuous variable valve lift. Existing CVVL has been applying DC type motor to control intake valve, but recently some car parts manufacturers have been developing a BLDC type CVVL motor for improvements of endurance performance. The purpose of this study is to find the potential failure mechanism of the CVVL BLDC moto in early stage of development based on the design properties and design the accelerated life test model. Methods : CVVL BLDC is consist of brushs, coil, magnetic, PCB, bearing and so on. Each component has a latent failure mechanism caused by temperature, humidity, vibration. By analysis result of the failure mechanism, thermal fatigue is the most important factor of a durability of CVVL BLDC motor. So, we designed a new accelerated life test model for guarantee of the CVVL BLDC motor. Results : A crack occurred on via hole in test using the conditions we designed, so we did change the design to avoid this failure. The via hole dimension is changed a little larger, as a result we achieve improvements in reliability of the CVVL BLDC motor. By applying various kinds and extreme level of stresses, we can find the operating limits of products. Conclusion : In thesis, We analyzed the failure mechanism of CVVL BLDC and designed an accelerated life test method to give a guarantee for reliability. Based on the test results, we could improve the reliability of developments by change of design.
The international nuclear industry has undergone a lot of changes since the Fukushima, Chernobyl and TMI nuclear power plant accidents. However, there are still large and small component deficiencies at nuclear power plants in the world. There are many causes of electrical equipment defects. There are also factors that cause component failures due to human errors. This paper analyzed the root causes of failure and types of human error in 300 cases of electrical component failures. We analyzed the operating experience of electrical components by methods of root causes in K-HPES (Korean-version of Human Performance Enhancement System) and by methods of human error types in HuRAM+ (Human error-Related event root cause Analysis Method Plus). As a result of analysis, the most electrical component failures appeared as circuit breakers and emergency generators. The major causes of failure showed deterioration and contact failure of electrical components by human error of operations management. The causes of direct failure were due to aged components. Types of human error affecting the causes of electrical equipment failure are as follows. The human error type group I showed that errors of commission (EOC) were 97%, the human error type group II showed that slip/lapse errors were 74%, and the human error type group III showed that latent errors were 95%. This paper is meaningful in that we have approached the causes of electrical equipment failures from a comprehensive human error perspective and found a countermeasure against the root cause. This study will help human performance enhancement in nuclear power plants. However, this paper has done a lot of research on improving human performance in the maintenance field rather than in the design and construction stages. In the future, continuous research on types of human error and prevention measures in the design and construction sector will be required.
A couple of previous studies have warned against the use of homogeneous choice models in assessing the effect of reference price since unaccounted for response heterogeneity may result in spurious reference price effects(Chang, Siddarth and Weinberg 1999; Bell and Lattin 2000). According to Meyer and Kahn(1991), not accounting for consideration set heterogeneity may also bias the effect parameters in the choice model. Therefore, failure to account for these two sources of bias, in fact, have cast doubt on the empirical support for reference price effects in general. In view of aforementioned potential sources of bias, the author investigates the robustness of loss aversion effect in the reference-dependent model after accounting for heterogeneity in response as well as consideration set. The proposed model defines individual household's consideration set based on the posterior distribution of preference obtained from the Empirical Bayes approach. In addition, the same posterior distribution is used to form household-specific reference prices. Response heterogeneity correction is carried out via the Latent Class approach. The proposed model outperforms the Reference-Dependent model that includes the reference price measure most often employed in the previous studies. This implies that as a way of simplifying decision task, consumers restrict their consideration set to a subset of available brands not only in making a brand choice but also in forming reference prices.
This study aims to introduce a method for risk assessment analysis aimed at preventing electrical fires within the manufacturing industry. Initially, we provided a functional block diagram illustrating the electrical equipment employed in various processes within a food manufacturing company in Chungcheongbuk-do. Subsequently, we categorized the components of each machine outlined in the functional block diagram and determined the priority of failure for each classified component. Upon implementing the model in the frying process of the food manufacturing company, specific components, including MC, motor, mixer heater, electric wiring, and terminal block, exhibit a risk priority number (RPN) of 40 or higher. This identified an electrical issue within the manufacturing process and environment. Consequently, we propose a methodology to identify latent failure modes that could escalate into fires or systemic issues if not promptly addressed. It is essential to note that while the FMEA presented in this study may not immediately impact food manufacturing, its applicability extends to various workplaces.
KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.
Twenty-three patients with traumatic diaphragmatic injuries treated at the Department of Thoracic and Cardiovascular Surgery, Keimyung University Dongsan Medical Center from Aug. 1978 to Nov. 1990 were reviewed. There were 19 male and 4 female patients. The age distribution was ranged from 1.5 to 72 years, with a mean age of 34.3 years. Sixteen patients had blunt trauma[traffic accident 14, fall down 2], and 7 had penetrating injuries[stab wound 6, broken glass 1]. Sixteen [70 percent]of the injuries occurred on the left side and 7[30 percent] on the right side. Fifteen patients were operated on during the acute phase, 5 patients during the latent phase, 2 patients during the obstructive phase. The surgical approach in 20 patients was through a thoracotomy; in 2 patients, a thoracoabdominal incision was necessary, and in 1 patient, a laparotomy was performed. Herniated organs in thorax included stomach[10], colon[5], small bowel[5], spleen[4], liver[2]. Postoperative complications included wound infection, empyema, pneumonia, hepatitis and respiratory failure. There were 3 postoperative deaths, 2 with cerebral dysfunction and 1 with sepsis.
The thyroid hormones act on nearly every cell in the body. Moreover, the thyroid gland continuously interacts with the ovaries, and the thyroid hormones are involved in almost all phases of reproduction. Thyroid dysfunctions are relatively common among women of reproductive age, and can affect fertility in various ways, resulting in anovulatory cycles, high prolactin levels, and sex hormone imbalances. Undiagnosed and untreated thyroid disease can be a cause of subfertility. Subclinical hypothyroidism (SCH), also known as mild thyroid failure, is diagnosed when peripheral thyroid hormone levels are within the normal reference laboratory range, but serum thyroid-stimulating hormone levels are mildly elevated. Thyroid autoimmunity (TAI) is characterized by the presence of anti-thyroid antibodies, which include anti-thyroperoxidase and anti-thyroglobulin antibodies. SCH and TAI may remain latent, asymptomatic, or even undiagnosed for an extended period. It has also been demonstrated that controlled ovarian hyperstimulation has a significant impact on thyroid function, particularly in women with TAI. In the current review, we describe the interactions between thyroid dysfunctions and subfertility, as well as the proper work-up and management of thyroid dysfunctions in subfertile women.
Precision electronic equipments for outdoor use are composed of sophisticated microcircuits that are extremely vulnerable to lightning-caused voltage spike. This transient voltage spike may cause upset, latent failure or Interference on electronic equipments. In order to develop efficient lightning protection measures on AC power lines of a road traffic controller as a electronic equipment for outdoor use, experimental surge immunity tests were conducted according to IEC standard 801-5. The combination of gas tube arrester and metal-oxide varistor was installed at the input of AC power lines and the silicon avalanche suppressor installed at the output of DC power supply for the lightning protection measures.
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