Search results for: fatigue reliability

Authors: Hande Burcu Deniz

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People in the U.S. spend a considerable portion of their time indoors. This makes it crucial to provide environments that support the well-being of people. Restorative environments aim to help people recover their cognitive resources that were spent due to intensive use of directed attention. Spending time in nature and taking a nap are two of the best ways to restore these resources. However, they are not possible to do most of the time. The problem is that many studies have revealed how nature and spending time in natural contexts can help boost restoration, but there are fewer studies conducted to understand how cognitive resources can be restored in interior settings. This study aims to explore the answer to this question: which qualities of interiors increase the restorativeness of an interior setting and how do they mediate restorativeness of an interior. To do this, a phenomenological qualitative study was conducted. The study was interested in the definition of attention restoration and the experiences of the phenomena. As the themes emerged, they were analyzed to match with Attention Restoration Theory components (being away, extent, fascination, compatibility) to examine how interior design elements mediate the restorativeness of an interior. The data was gathered from semi-structured interviews with international residents of Minnesota. The interviewees represent young professionals who work in Minnesota and often experience mental fatigue. Also, they have less emotional connections with places in Minnesota, which enabled data to be based on the physical qualities of a space rather than emotional connections. In the interviews, participants were asked about where they prefer to be when they experience mental fatigue. Next, they were asked to describe the physical qualities of the places they prefer to be with reasons. Four themes were derived from the analysis of interviews. The themes are in order according to their frequency. The first, and most common, the theme was “connection to outside”. The analysis showed that people need to be either physically or visually connected to recover from mental fatigue. Direct connection to nature was reported as preferable, whereas urban settings were the secondary preference along with interiors. The second theme emerged from the analysis was “the presence of the artwork,” which was experienced differently by the interviewees. The third theme was “amenities”. Interviews pointed out that people prefer to have the amenities that support desired activity during recovery from mental fatigue. The last theme was “aesthetics.” Interviewees stated that they prefer places that are pleasing to their eyes. Additionally, they could not get rid of the feeling of being worn out in places that are not well-designed. When we matched the themes with the four art components (being away, extent, fascination, compatibility), some of the interior qualities showed overlapping since they were experienced differently by the interviewees. In conclusion, this study showed that interior settings have restorative potential, and they are multidimensional in their experience.

Keywords: attention restoration, fatigue, interior design, qualitative study, restorative environments

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Authors: Pooja Rani, G. S. Mahapatra, S. K. Pandey

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In this paper, we propose a novel approach of Neural Network and Particle Swarm Optimization methods for software reliability prediction. We first explain how to apply compound function in neural network so that we can derive a Flexible Logistic (S-shaped) Growth Curve (FLGC) model. This model mathematically represents software failure as a random process and can be used to evaluate software development status during testing. To avoid trapping in local minima, we have applied Particle Swarm Optimization method to train proposed model using failure test data sets. We drive our proposed model using computational based intelligence modeling. Thus, proposed model becomes Neuro-Particle Swarm Optimization (NPSO) model. We do test result with different inertia weight to update particle and update velocity. We obtain result based on best inertia weight compare along with Personal based oriented PSO (pPSO) help to choose local best in network neighborhood. The applicability of proposed model is demonstrated through real time test data failure set. The results obtained from experiments show that the proposed model has a fairly accurate prediction capability in software reliability.

Keywords: software reliability, flexible logistic growth curve model, software cumulative failure prediction, neural network, particle swarm optimization

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Authors: Jinyong Yao, Hongzhi Li, Chao Du, Jiao Li

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Reliability of long-term storage products is related to the availability of the whole system, and the evaluation of storage life is of great necessity. These products are usually highly reliable and little failure information can be collected. In this paper, an analytical method based on data from accelerated storage life test is proposed to evaluate the reliability index of the long-term storage products. Firstly, singularities are eliminated by data normalization and residual analysis. Secondly, with the pre-processed data, the degradation path model is built to obtain the pseudo life values. Then by life distribution hypothesis, we can get the estimator of parameters in high stress levels and verify failure mechanisms consistency. Finally, the life distribution under the normal stress level is extrapolated via the acceleration model and evaluation of the true average life available. An application example with the camera stabilization device is provided to illustrate the methodology we proposed.

Keywords: accelerated storage life test, failure mechanisms consistency, life distribution, reliability

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Authors: Seyedmohsen Mortazavi

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The purpose of this research is to investigate the personality types of internal auditors on the quality of financial reporting in companies admitted to the Tehran Stock Exchange. Personality type is one of the issues that emphasizes the field of auditors' behavior, and this field has attracted the attention of shareholders and stock companies today, because the auditors' personality can affect the type of financial reporting and its quality. The research is applied in terms of purpose and descriptive and correlational in terms of method, and a researcher-made questionnaire was used to check the research hypotheses. The statistical population of the research is all the auditors, accountants and financial managers of the companies admitted to the Tehran Stock Exchange, and due to their large number and the uncertainty of their exact number, 384 people have been considered as a statistical sample using Morgan's table. The researcher-made questionnaire was approved by experts in the field, and then its validity and reliability were obtained using software. For the validity of the questionnaire, confirmatory factor analysis was first examined, and then using divergent and convergent validity; Fornell-Larker and cross-sectional load test of the validity of the questionnaire were confirmed; Then, the reliability of the questionnaire was examined using Cronbach's alpha and composite reliability, and the results of these two tests showed the appropriate reliability of the questionnaire. After checking the validity and reliability of the research hypotheses, PLS software was used to check the hypotheses. The results of the research showed that the personalities of internal auditors can affect the quality of financial reporting; The personalities investigated in this research include neuroticism, extroversion, flexibility, agreeableness and conscientiousness, all of these personality types can affect the quality of financial reporting.

Keywords: flexibility, quality of financial reporting, agreeableness, conscientiousness

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Authors: Ming Wen, Nasim Nezamoddini

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Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: finite element analysis, FEA, random vibration fatigue, process automation, analytical hierarchy process, AHP, TOPSIS, multiple-criteria decision-making, MCDM

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Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

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Authors: Yu-Chien Huang, Shu-Chen Yang

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Introduction: Parenting style, non-attachment, and inferiority are important topics in psychology, but the related research on nonattachment is still lacking. Therefore, the purposes of this study were to explore the relationship between parenting style, nonattachment, and inferiority. Methods: We conducted a correlational study, and three instruments were utilized to collect data: parenting style scale, nonattachment scale, and inferiority scale. The inter-reliability Cronbach's α used in this research indicated good inter item reliability and the test-retest reliability that showed a good consistency. The data were analyzed using the descriptive statistics, Chi-square test, one way ANOVA, Pearson’s correlation, and regression analysis. Results: A total of 200 participators were tested in this research. As a result of the study, inferiority had a positive correlation with authoritarian parenting style; nonattachment had a negative correlation with authoritarian parenting style; and with inferiority, the hypothesis was supported. In the linear mediation models, nonattachment was found to be partially mediated the relationship between authoritarian parenting style and inferiority. Conclusion: These findings imply that interventions aimed at enhancing nonattachment as a way to improve inferiority are a good strategy.

Keywords: inferiority, nonattachment, parenting style, psychology

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Authors: Paramita Sekar Ayu, Sunjaya Deni Kurniadi, Yamazaki Chiho, Hilfi Lukman, Koyama Hiroshi

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Social cohesion, or closeness among members of society, is an important determinant of population health. A cohesive society is a crucial societal condition for a positive life evaluation and subjective wellbeing, and people living in a cohesive society are happier and more satisfied with life and achieve better health status. The objective of this study was to compose and validate a questionnaire for measuring social cohesion with Rasch analysis. We develop a set of 13 questions to measure 4 dimensions of social cohesion. Random samples of 166 Bandung citizens’ were selected to answer the questionnaire. To evaluate the questionnaire’s validity and reliability, Rasch analysis (a psychometric model for analyzing categorical data on questionnaire responses) was carried out using Winsteps version 3.75.0. Rasch analysis was performed on the response given to 13 items included in the questionnaire. The reliability coefficient, Cronbach’s alpha was 0.70, model RMSE 0.08, SD 0.54, separation 7.14, and reliability of 0.98. ‘Kohesif-Ques’ is a useful instrument to assess social cohesion.

Keywords: rasch analysis, rasch model, social cohesion, quesionnaire

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Marina Charalambous, Phivos Phylactou, Thekla Elriz, Loukia Psychogios, Jean-Marie Annoni

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Background: Evidence-based practices for the evaluation and treatment of people with aphasia (PWA) in Greek are mainly impairment-based. Functional and multimodal communication is usually under assessed and neglected by clinicians. This study explores the adaptation and psychometric testing of the Greek (GR) version of The Scenario Test. The Scenario Test assesses the everyday functional communication of PWA in an interactive multimodal communication setting with the support of an active communication facilitator. Aims: To define the reliability and validity of The Scenario Test GR and discuss its clinical value. Methods & Procedures: The Scenario Test-GR was administered to 54 people with chronic stroke (6+ months post-stroke): 32 PWA and 22 people with stroke without aphasia. Participants were recruited from Greece and Cyprus. All measures were performed in an interview format. Standard psychometric criteria were applied to evaluate reliability (internal consistency, test-retest, and interrater reliability) and validity (construct and known – groups validity) of the Scenario Test GR. Video analysis was performed for the qualitative examination of the communication modes used. Outcomes & Results: The Scenario Test-GR shows high levels of reliability and validity. High scores of internal consistency (Cronbach’s α = .95), test-retest reliability (ICC = .99), and interrater reliability (ICC = .99) were found. Interrater agreement in scores on individual items fell between good and excellent levels of agreement. Correlations with a tool measuring language function in aphasia (the Aphasia Severity Rating Scale of the Boston Diagnostic Aphasia Examination), a measure of functional communication (the Communicative Effectiveness Index), and two instruments examining the psychosocial impact of aphasia (the Stroke and Aphasia Quality of Life questionnaire and the Aphasia Impact Questionnaire) revealed good convergent validity (all ps< .05). Results showed good known – groups validity (Mann-Whitney U = 96.5, p < .001), with significantly higher scores for participants without aphasia compared to those with aphasia. Conclusions: The psychometric qualities of The Scenario Test-GR support the reliability and validity of the tool for the assessment of functional communication for Greek-speaking PWA. The Scenario Test-GR can be used to assess multimodal functional communication, orient aphasia rehabilitation goal setting towards the activity and participation level, and be used as an outcome measure of everyday communication. Future studies will focus on the measurement of sensitivity to change in PWA with severe non-fluent aphasia.

Keywords: the scenario test GR, functional communication assessment, people with aphasia (PWA), tool validation

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Authors: Amir Mahyar Khorasani, Ian Gibson, Moshe Goldberg, Mohammad Masoud Movahedi, Guy Littlefair

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One of the important factors in manufacturing processes especially machining operations is surface quality. Improving this parameter results in improving fatigue strength, corrosion resistance, creep life and surface friction. The reliability and clearance of removable joints such as thread and nuts are highly related to the surface roughness. In this work, the effect of different cutting parameters such as cutting fluid pressure, feed rate and cutting speed on the surface quality of the crest of thread in the high-speed milling of Brass C3600 have been determined. Two popular neural networks containing MLP and RBF coupling with Taguchi L32 have been used to model surface roughness which was shown to be highly adept for such tasks. The contribution of this work is modelling surface roughness on the crest of the thread by using precise profilometer with nanoscale resolution. Experimental tests have been carried out for validation and approved suitable accuracy of the proposed model. Also analysing the interaction of parameters two by two showed that the most effective cutting parameter on the surface value is feed rate followed by cutting speed and cutting fluid pressure.

Keywords: artificial neural networks, cutting conditions, high-speed machining, surface roughness, thread milling

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Authors: Young-Doo Kwon, Seong-Hwa Jun, Dong-Jin Lee, Hyung-Seok Lee

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Ball joints support and guide certain automotive parts that move relative to the frame of the vehicle. Such ball joints are covered and protected from dust, mud, and other interfering materials by ball-joint boots made of rubber—a flexible and near-incompressible material. The boots may experience twisting and bending deformations because of the motion of the joint arm. Thus, environmental and endurance tests of ball-joint boots apply both bending and twisting deformations. In this study, environmental and endurance testing was simulated via the finite element method performed by using a commercial software package. The ranges of principal stress and principal strain values that are known to directly affect the fatigue lives of the parts were sought. By defining these ranges, the number of iterative tests and modifications of the materials and dimensions of the boot can be decreased. Therefore, instead of performing actual part tests, manufacturers can perform standard fatigue tests in trials of different materials by applying only the defined range of stress or strain values.

Keywords: boot, endurance tests, rubber, FEA

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Raed KOUTA, José-Alcebiades-Ernesto HLUNGUANE, Eric Châtele

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The search for and exploitation of new fossil energy resources is taking place in the context of the gradual depletion of existing deposits. Despite the adoption of international targets to combat global warming, the demand for fuels continues to grow, contradicting the movement towards an energy-efficient society. The increase in the share of offshore in global hydrocarbon production tends to compensate for the depletion of terrestrial reserves, thus constituting a major challenge for the players in the sector. Through the economic potential it represents, and the energy independence it provides, offshore exploitation is also a challenge for States such as Mozambique, which have large maritime areas and whose environmental wealth must be considered. The exploitation of new reserves on economically viable terms depends on available technologies. The development of deep and ultra-deep offshore requires significant research and development efforts. Progress has also been made in managing the multiple risks inherent in this activity. Our study proposes a reliability approach to develop products and processes designed to live at sea. Indeed, the context of an offshore platform requires highly reliable solutions to overcome the difficulties of access to the system for regular maintenance and quick repairs and which must resist deterioration and degradation processes. One of the characteristics of failures that we consider is the actual conditions of use that are considered 'extreme.' These conditions depend on time and the interactions between the different causes. These are the two factors that give the degradation process its dynamic character, hence the need to develop dynamic reliability models. Our work highlights mathematical models that can explicitly manage interactions between components and process variables. These models are accompanied by numerical resolution methods that help to structure a dynamic reliability approach in a physical and probabilistic context. The application developed makes it possible to evaluate the reliability, availability, and maintainability of a floating storage and unloading platform for liquefied natural gas production.

Keywords: dynamic reliability, offshore plateform, stochastic process, uncertainties

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Authors: H. M. Ferreira, H. Cockings, D. F. Gordon

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Climate change is driving a transition in the energy sector, with low-carbon energy sources such as hydrogen (H2) emerging as an alternative to fossil fuels. However, the successful implementation of a hydrogen economy requires an expansion of hydrogen production, transportation and storage capacity. The costs associated with this transition are high but can be partly mitigated by adapting the current oil and natural gas networks, such as pipeline, an important component of the hydrogen infrastructure, to transport pure or blended hydrogen. Steel pipelines are designed to withstand fatigue, one of the most common causes of pipeline failure. However, it is well established that some materials, such as steel, can fail prematurely in service when exposed to hydrogen-rich environments. Therefore, it is imperative to evaluate how defects (e.g. inclusions, dents, and pre-existing cracks) will interact with hydrogen under cyclic loading and, ultimately, to what extent hydrogen induced failure will limit the service conditions of steel pipelines. This presentation will explore how the exposure of API 5L X65 to a hydrogen-rich environment and cyclic loads will influence its susceptibility to hydrogen induced failure. That evaluation will be performed by a combination of several techniques such as hydrogen permeation testing (ISO 17081:2014), fatigue crack growth (FCG) testing (ISO 12108:2018 and AFGROW modelling), combined with microstructural and fractographic analysis. The development of a FCG test setup coupled with an electrochemical cell will be discussed, along with the advantages and challenges of measuring crack growth rates in electrolytic hydrogen environments. A detailed assessment of several electrolytic charging conditions will also be presented, using hydrogen permeation testing as a method to correlate the different charging settings to equivalent hydrogen concentrations and effective diffusivity coefficients, not only on the base material but also on the heat affected zone and weld of the pipelines. The experimental work is being complemented with AFGROW, a useful FCG modelling software that has helped inform testing parameters and which will also be developed to ultimately help industry experts perform structural integrity analysis and remnant life characterisation of pipeline steels under representative conditions. The results from this research will allow to conclude if there is an acceleration of the crack growth rate of API 5L X65 under the influence of a hydrogen-rich environment, an important aspect that needs to be rectified instandards and codes of practice on pipeline integrity evaluation and maintenance.

Keywords: AFGROW, electrolytic hydrogen charging, fatigue crack growth, hydrogen, pipeline, steel

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Authors: Kalyan Deepak Kolla, Ketan Paua, Rajkumar Bhagate

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Transmission dynamics occupy major role in customer perception of the product in both senses of touch and quality of sound. The quantity and quality of sound perceived is more concerned with the whine noise of the gears engaged. Whine noise is tonal in nature and tonal noises cause fatigue and irritation to customers, which in turn affect the quality of the product. Transmission error is the usual suspect for whine noise, which can be caused due to misalignments, tolerances, manufacturing variabilities. In-cabin noise is also more sensitive to the gear design. As the details of the gear tooth design and manufacturing are in microns, anything out of the tolerance zone, either in design or manufacturing, will cause a whine noise. This will also cause high variation in stress and deformation due to change in the load and leads to the fatigue failure of the gears. Hence gear design and development take priority in the transmission development process. This paper aims to study such variability by considering five pairs of helical spur gears and their effect on the transmission error, contact pattern and vibration level on the transmission.

Keywords: gears, whine noise, manufacturing variability, mount vibration variability

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Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

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The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

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Authors: Federico Valenzuela-Beltran, Sonia E. Ruiz, Alfredo Reyes-Salazar, Juan Bojorquez

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A reliability-based methodology which uses structural demand hazard curves to consider the increment of the ductility demands of structures with tilting is proposed. The approach considers the effect of two orthogonal components of the ground motions as well as the influence of soil-structure interaction. The approach involves the calculation of ductility demand hazard curves for symmetric systems and, alternatively, for systems with different degrees of asymmetry. To get this objective, demand hazard curves corresponding to different global ductility demands of the systems are calculated. Next, Uniform Exceedance Rate Spectra (UERS) are developed for a specific mean annual rate of exceedance value. Ratios between UERS corresponding to asymmetric and to symmetric systems located in soft soil of the valley of Mexico are obtained. Results indicate that the ductility demands corresponding to tilted structures may be several times higher than those corresponding to symmetric structures, depending on several factors such as tilting angle and vibration period of structure and soil.

Keywords: asymmetric yielding, seismic performance, structural reliability, tilted structures

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Authors: Ya L. V., Benjamin Ong Wei Lin, Wanli Niu, Benjamin Seah Chin Tat

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This article introduces a methodology that improves reliability and cyclability of 2nd-life Li-ion battery system repurposed as an energy storage system (ESS). Most of the 2nd-life retired battery systems in the market have module/pack-level state-of-health (SOH) indicator, which is utilized for guiding appropriate depth-of-discharge (DOD) in the application of ESS. Due to the lack of cell-level SOH indication, the different degrading behaviors among various cells cannot be identified upon reaching retired status; in the end, considering end-of-life (EOL) loss and pack-level DOD, the repurposed ESS has to be oversized by > 1.5 times to complement the application requirement of reliability and cyclability. This proposed battery grading algorithm, using non-invasive methodology, is able to detect outlier cells based on historical voltage data and calculate cell-level historical maximum temperature data using semi-analytic methodology. In this way, the individual battery cell in the 2nd-life battery system can be graded in terms of SOH on basis of the historical voltage fluctuation and estimated historical maximum temperature variation. These grades will have corresponding DOD grades in the application of the repurposed ESS to enhance system reliability and cyclability. In all, this introduced battery grading algorithm is non-invasive, compatible with all kinds of retired Li-ion battery systems which lack of cell-level SOH indication, as well as potentially being embedded into battery management software for preventive maintenance and real-time cyclability optimization.

Keywords: battery grading algorithm, 2nd-life repurposing battery system, semi-analytic methodology, reliability and cyclability

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Authors: A. Al-Juboori, D. Wexler, H. Li, H. Zhu, C. Lu, A. McCusker, J. McLeod, S. Pannila, Z. Wang

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Squats are a type railhead defect related to rolling contact fatigue (RCF) damage and are considered serious problem affecting a wide range of railway networks across the world. Squats can lead to partial or complete rail failure. Formation mechanics of squats on the surface of rail steel is still a matter of debate. In this work, structural and microstructural observations from ex-service damaged rail both confirms the phases present in white etching layer (WEL) regions and relationship between cracking in WEL and squat defect formation. XRD synchrotron results obtained from the top surfaces of rail regions containing both WEL and squat defects reveal that these regions contain both martensite and retained austenite. Microstructural analysis of these regions revealed the occurrence cracks extending from WEL down into the rail through the squat region. These findings obtained from field rail specimen support the view that WEL contains regions of austenite and martensitic transformation product, and that cracks in this brittle surface layer propagate deeper into the rail as squats originate and grow.

Keywords: squat, white etching layer, rolling contact fatigue, synchrotron diffraction

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Authors: A. R. Alesaadi

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Flexible AC transmission system (FACTS) devices have an important rule on expended electrical transmission networks. These devices can provide control of one or more AC transmission system parameters to enhance controllability and increase power transfer capability. In this paper the effect of these devices on reliability of electrical networks is studied and it is shown that using of FACTS devices can improve the reliability of power networks and power quality in electrical networks, significantly.

Keywords: FACTS devices, power networks, power quality, STATCOM

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Authors: Carine Platat, Fatima Qshadi, Ghofran Kayed, Nour Hussein, Amjad Jarrar, Habiba Ali

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Nowadays, smartphones are very popular. They are offering a variety of easy-to-use and free applications among which step counters and fitness tests. The number of users is huge making of such applications a potentially efficient new strategy to encourage people to become more active. Nonetheless, data on their reliability and validity are very scarce and when available, they are often negative and contradictory. Besides, weight status, which is likely to introduce a bias in the physical activity assessment, was not often considered. Hence, the use of these applications as motivational tool, assessment tool and in research is questionable. PACER is one of the free step counters application. Even though it is one of the best rated free application by users, it has never been tested for reliability and validity. Prior any use of PACER, this remains to be investigated. The objective of this work is to investigate the reliability and validity of the smartphone application PACER in measuring the number of steps and in assessing the cardiorespiratory fitness by the 6 minutes walking test. 20 overweight or obese students (10 male and 10 female) were recruited at the United Arab Emirate University, aged between 18 and 25 years old. Reliability and validity were tested in real life conditions and in controlled conditions by using a treadmill. Test-retest experiments were done with PACER on 2 days separated by a week in real life conditions (24 hours each time) and in controlled conditions (30 minutes on treadmill, 3km/h). Validity was tested against the pedometer OMRON in the same conditions. During treadmill test, video was recorded and steps numbers were compared between PACER, pedometer and video. The validity of PACER in estimating the cardiorespiratory fitness (VO2max) as part of the 6 minutes walking test (6MWT) was studied against the 20m shuttle running test. Reliability was studied by calculating intraclass correlation coefficients (ICC), 95% confidence interval (95%CI) and by Bland-Altman plots. Validity was studied by calculating Spearman correlation coefficient (rho) and Bland-Altman plots. PACER reliability was good in both male and female in real life conditions (p≤10-3) but only in female in controlled conditions (p=0.01). PACER was valid against OMRON pedometer in male and female in real life conditions (rho=0.94, p≤10-3 ; rho=0.64, p=0.01, in male and female respectively). In controlled conditions, PACER was not valid against pedometer. But, PACER was valid against video in female (rho=0.72, p≤10-3). PACER was valid against the shuttle run test in male and female (rho-=0.66, p=0.01 ; rho=0.51, p=0.04) to estimate VO2max. This study provides data on the reliability and viability of PACER in overweight or obese male and female young adults. Globally, PACER was shown as reliable and valid in real life conditions in overweight or obese male and female to count steps and assess fitness. This supports the use of PACER to assess and promote physical activity in clinical follow-up and community interventions.

Keywords: smartphone application, pacer, reliability, validity, steps, fitness, physical activity

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Authors: Davaakhuu Vandannyam, Amarsaikhan Dashtseren, Oyungoo Badamdorj

Abstract:

Background: Shift work and extended working hours are increasing in many industries and organization's in the world. Over a 24 hour period, the circadian clock regulates sleep/wake patterns, body temperature, hormone levels, digestion and many other functions. Depending on the time of day or night, the human body is programmed for periods of wakefulness and sleep, high and low body temperature, high and low digestive activity and so on. Shift work is highly prevalent in industrialized societies (>20%) but, when it includes night work, it has pronounced negative effects on sleep, subjective and physiological sleepiness, performance, accident risk, as well as on health outcomes such as cardiovascular disease and certain forms of cancer. Method: In this cross-sectional field study, 634 shift work and day work nurses from a plant were involved, with participation rate of 100% (634 nurses). The general health questionnaire (GHQ-28) and RLS, ESS, ISI, FSS were used to evaluate the level of insomnia, sleepiness, fatigue and restless legs syndrome, respectively. Results: As a result of research on some indicators of health risks caused from work shift, it was proven that prevalence of restless legs syndrome was at 5.5% and 25.9% are in risk of becoming sick, 42.3% are in fatigue, 3.5% in high stage of insomnia and 27.4% are sleepy on duty. Insomnia of nurses mainly affected from long-hour shift, dissatisfaction, workload, lose of focus and use of coffee. There is sleepiness lies in the workplace due to number of shifts, unsatisfactory performance and emergency calls between shifts. It has been determined that risk of sickness influenced by number of shifts in a month and long hour shift, dissatisfaction and use of coffee and divisions are causing restless legs syndrome. Conclusions: Among the nurses, it was found that the prevalence of insomnia is 31.6%, sleepiness 27.4%, fatigue 42.3%, restless legs syndrome 35% and stress 25.9%. These factors of shift work affecting health tend to go up as working hours increase and more common among shift work nurses.

Keywords: shiftwork, insomnia, sleepiness, restless

Procedia PDF Downloads 223

Authors: Rajesh Singh, Kailash Kale

Abstract:

In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

Procedia PDF Downloads 365

Authors: Xiang Jia, Zhijun Cheng

Abstract:

The residual lifetime of a product is the operation time between the current time and the time point when the failure happens. The residual lifetime estimation is rather important in reliability analysis. To predict the residual lifetime, it is necessary to assume or verify a particular distribution that the lifetime of the product follows. And the two-parameter Weibull distribution is frequently adopted to describe the lifetime in reliability engineering. Due to the time constraint and cost reduction, a life testing experiment is usually terminated before all the units have failed. Then the censored data is usually collected. In addition, other information could also be obtained for reliability analysis. The expert judgements are considered as it is common that the experts could present some useful information concerning the reliability. Therefore, the residual lifetime is estimated for Weibull distribution by fusing the censored data and expert judgements in this paper. First, the closed-forms concerning the point estimate and confidence interval for the residual lifetime under the Weibull distribution are both presented. Next, the expert judgements are regarded as the prior information and how to determine the prior distribution of Weibull parameters is developed. For completeness, the cases that there is only one, and there are more than two expert judgements are both focused on. Further, the posterior distribution of Weibull parameters is derived. Considering that it is difficult to derive the posterior distribution of residual lifetime, a sample-based method is proposed to generate the posterior samples of Weibull parameters based on the Monte Carlo Markov Chain (MCMC) method. And these samples are used to obtain the Bayes estimation and credible interval for the residual lifetime. Finally, an illustrative example is discussed to show the application. It demonstrates that the proposed method is rather simple, satisfactory, and robust.

Keywords: expert judgements, information fusion, residual lifetime, Weibull distribution

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Authors: Sai Hung Cheung, Zhe Shao

Abstract:

It is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis in view of recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 which brought huge losses of lives and properties. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of a recently proposed moving least squares response surface approach for stochastic sampling and the Subset Simulation algorithm is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface, stochastic simulation, structural reliability tsunami, risk

Procedia PDF Downloads 648

Authors: S. Masoud Barakati, Mohsen Rahmani Haredasht

Abstract:

Recently, the use of T-type nested neutral point clamped (T-NNPC) converter has increased in medium voltage applications. However, the T-NNPC converter architecture's reliability and continuous operation are at risk by including semiconductor switches. Semiconductor switches are a prone option for open-circuit faults. As a result, fault-tolerant converters are required to improve the system's reliability and continuous functioning. This study's primary goal is to provide a fault-tolerant T-NNPC converter configuration. In the proposed design utilizing the cold reservation approach, a redundant phase is considered, which replaces the faulty phase once the fault is diagnosed in each phase. The suggested fault-tolerant configuration can be easily implemented in practical applications due to the use of a simple PWM control mechanism. The performance evaluation of the proposed configuration under different scenarios in the MATLAB-Simulink environment proves its efficiency.

Keywords: T-type nested neutral point clamped converter, reliability, continuous operation, open-circuit faults, fault-tolerant converters

Procedia PDF Downloads 89

Authors: Chante J. De Klerk

Abstract:

The potential of music to facilitate superior performance during high to elite level gymnastics conditioning instigated this research. A team of seven gymnasts completed a fixed conditioning programme eight times, alternating the two variable conditions. Four sessions of each condition were conducted: without music (session 1), with music (session 2), without music (3), with music (4), without music (5), and so forth. Quantitative data were collected in both conditions through physiological monitoring of the gymnasts, and administration of the Situational Motivation Scale (SIMS). Statistical analysis of the physiological data made it possible to quantify the presence as well as the magnitude of the musical intervention’s impact on various aspects of the gymnasts' physiological functioning during conditioning. The SIMS questionnaire results were used to evaluate if their motivation towards conditioning was altered by the intervention. Thematic analysis of qualitative data collected through semi-structured interviews revealed themes reflecting the gymnasts’ sentiments towards the data collection process. Gymnast-specific descriptions and experiences of the team as a whole were integrated with the quantitative data to facilitate greater dimension in establishing the impact of the intervention. The results showed positive physiological, motivational, and emotional effects. In the presence of music, superior sympathetic nervous activation, and energy efficiency, with more economic breathing, dominated the physiological data. Fatigue and arousal levels (emotional and physiological) were also conducive to improved conditioning outcomes compared to conventional conditioning (without music). Greater levels of positive affect and motivation emerged in analysis of both the SIMS and interview data sets. Overall, the intervention was found to promote psychophysiological coherence during the physical activity. In conclusion, a strategically constructed musical intervention, designed to accompany a gymnastics conditioning session for high to elite level gymnasts, has ergogenic potential.

Keywords: arousal, fatigue, gymnastics conditioning, motivation, musical intervention, psychophysiological coherence

Procedia PDF Downloads 70