L70 life prediction for solid state lighting using Kalman Filter and Extended Kalman Filter based models

Energy Technology Data Exchange (ETDEWEB)

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-08-08

Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life

Shelf Life Prediction for Canned Gudeg using Accelerated Shelf Life Testing (ASLT) Based on Arrhenius Method

Science.gov (United States)

Nurhayati, R.; Rahayu NH, E.; Susanto, A.; Khasanah, Y.

2017-04-01

Gudeg is traditional food from Yogyakarta. It is consist of jackfruit, chicken, egg and coconut milk. Gudeg generally have a short shelf life. Canning or commercial sterilization is one way to extend the shelf life of gudeg. This aims of this research is to predict the shelf life of Andrawinaloka canned gudeg with Accelerated Shelf Life Test methods, Arrhenius model. Canned gudeg stored at three different temperature, there are 37, 50 and 60°C for two months. Measuring the number of Thio Barbituric Acid (TBA), as a critical aspect, were tested every 7 days. Arrhenius model approach is done with the equation order 0 and order 1. The analysis showed that the equation of order 0 can be used as an approach to estimating the shelf life of canned gudeg. The storage of Andrawinaloka canned gudeg at 30°C is predicted untill 21 months and 24 months for 25°C.

Probabilistic Fatigue Life Prediction of Bridge Cables Based on Multiscaling and Mesoscopic Fracture Mechanics

Directory of Open Access Journals (Sweden)

Zhongxiang Liu

2016-04-01

Full Text Available Fatigue fracture of bridge stay-cables is usually a multiscale process as the crack grows from micro-scale to macro-scale. Such a process, however, is highly uncertain. In order to make a rational prediction of the residual life of bridge cables, a probabilistic fatigue approach is proposed, based on a comprehensive vehicle load model, finite element analysis and multiscaling and mesoscopic fracture mechanics. Uncertainties in both material properties and external loads are considered. The proposed method is demonstrated through the fatigue life prediction of cables of the Runyang Cable-Stayed Bridge in China, and it is found that cables along the bridge spans may have significantly different fatigue lives, and due to the variability, some of them may have shorter lives than those as expected from the design.

Life prediction for white OLED based on LSM under lognormal distribution

Science.gov (United States)

Zhang, Jianping; Liu, Fang; Liu, Yu; Wu, Helen; Zhu, Wenqing; Wu, Wenli; Wu, Liang

2012-09-01

In order to acquire the reliability information of White Organic Light Emitting Display (OLED), three groups of OLED constant stress accelerated life tests (CSALTs) were carried out to obtain failure data of samples. Lognormal distribution function was applied to describe OLED life distribution, and the accelerated life equation was determined by Least square method (LSM). The Kolmogorov-Smirnov test was performed to verify whether the white OLED life meets lognormal distribution or not. Author-developed software was employed to predict the average life and the median life. The numerical results indicate that the white OLED life submits to lognormal distribution, and that the accelerated life equation meets inverse power law completely. The estimated life information of the white OLED provides manufacturers and customers with important guidelines.

[Prediction of life expectancy for prostate cancer patients based on the kinetic theory of aging of living systems].

Science.gov (United States)

Viktorov, A A; Zharinov, G M; Neklasova, N Ju; Morozova, E E

2017-01-01

The article presents a methodical approach for prediction of life expectancy for people diagnosed with prostate cancer based on the kinetic theory of aging of living systems. The life expectancy is calculated by solving the differential equation for the rate of aging for three different stage of life - «normal» life, life with prostate cancer and life after combination therapy for prostate cancer. The mathematical model of aging for each stage of life has its own parameters identified by the statistical analysis of healthcare data from the Zharinov's databank and Rosstat CDR NES databank. The core of the methodical approach is the statistical correlation between growth rate of the prostate specific antigen level (PSA-level) or the PSA doubling time (PSA DT) before therapy, and lifespan: the higher the PSA DT is, the greater lifespan. The patients were grouped under the «fast PSA DT» and «slow PSA DT» categories. The satisfactory matching between calculations and experiment is shown. The prediction error of group life expectancy is due to the completeness and reliability of the main data source. A detailed monitoring of the basic health indicators throughout the each person life in each analyzed group is required. The absence of this particular information makes it impossible to predict the individual life expectancy.

Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture

Science.gov (United States)

Li, Lingling; Wang, Pengchong; Chao, Kuei-Hsiang; Zhou, Yatong; Xie, Yang

2016-01-01

The remaining useful life (RUL) prediction of Lithium-ion batteries is closely related to the capacity degeneration trajectories. Due to the self-charging and the capacity regeneration, the trajectories have the property of multimodality. Traditional prediction models such as the support vector machines (SVM) or the Gaussian Process regression (GPR) cannot accurately characterize this multimodality. This paper proposes a novel RUL prediction method based on the Gaussian Process Mixture (GPM). It can process multimodality by fitting different segments of trajectories with different GPR models separately, such that the tiny differences among these segments can be revealed. The method is demonstrated to be effective for prediction by the excellent predictive result of the experiments on the two commercial and chargeable Type 1850 Lithium-ion batteries, provided by NASA. The performance comparison among the models illustrates that the GPM is more accurate than the SVM and the GPR. In addition, GPM can yield the predictive confidence interval, which makes the prediction more reliable than that of traditional models. PMID:27632176

Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

Directory of Open Access Journals (Sweden)

Ye Tian

2014-01-01

Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

The life prediction study of Rokkasho reprocessing plant materials

International Nuclear Information System (INIS)

Kiuchi, K.; Yano, M.; Takizawa, M.; Shibata, S.

1998-01-01

The life prediction study of major equipment materials used in heavily corrosive nitric acid solutions of the RRP was carried out. The nitric acid recovery made of type 304ULC austenitic steel and the dissolver made of type 705 metallic zirconium are selected on the present study. This study is composed of major three programs, namely, the mock-up tests by small-sized equipments simulated to the practical design, laboratory tests for examining corrosion controlling factors by small specimens and to establish the data base system for the life prediction. Important parameters on this study was extracted with analyzing the past data of the life prediction on the Tokai reprocessing equipments. The mock-ups design was made by considering the quantitative evaluation of the most important parts on objective equipments, namely, heat conducting tubes in an acid recovery evaporator and a thermal jacket in a dissolver. From pre-examinations, the effects of radioactive species, nitric acid solution chemistry, the corrosion mechanisms were elucidated. Mock-up testing conditions corrosion monitoring methods and a data base concept for the the life prediction were selected from pre-examination data by referencing the plant operation planning. (author)

Remaining useful life prediction based on noisy condition monitoring signals using constrained Kalman filter

International Nuclear Information System (INIS)

Son, Junbo; Zhou, Shiyu; Sankavaram, Chaitanya; Du, Xinyu; Zhang, Yilu

2016-01-01

In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. - Highlights: • A computationally efficient constrained Kalman filter is proposed. • Proposed filter is integrated into an online failure prognosis framework. • A set of proper constraints significantly improves the failure prediction accuracy. • Promising results are reported in the application of battery failure prognosis.

Development of a Late-Life Dementia Prediction Index with Supervised Machine Learning in the Population-Based CAIDE Study.

Science.gov (United States)

Pekkala, Timo; Hall, Anette; Lötjönen, Jyrki; Mattila, Jussi; Soininen, Hilkka; Ngandu, Tiia; Laatikainen, Tiina; Kivipelto, Miia; Solomon, Alina

2017-01-01

This study aimed to develop a late-life dementia prediction model using a novel validated supervised machine learning method, the Disease State Index (DSI), in the Finnish population-based CAIDE study. The CAIDE study was based on previous population-based midlife surveys. CAIDE participants were re-examined twice in late-life, and the first late-life re-examination was used as baseline for the present study. The main study population included 709 cognitively normal subjects at first re-examination who returned to the second re-examination up to 10 years later (incident dementia n = 39). An extended population (n = 1009, incident dementia 151) included non-participants/non-survivors (national registers data). DSI was used to develop a dementia index based on first re-examination assessments. Performance in predicting dementia was assessed as area under the ROC curve (AUC). AUCs for DSI were 0.79 and 0.75 for main and extended populations. Included predictors were cognition, vascular factors, age, subjective memory complaints, and APOE genotype. The supervised machine learning method performed well in identifying comprehensive profiles for predicting dementia development up to 10 years later. DSI could thus be useful for identifying individuals who are most at risk and may benefit from dementia prevention interventions.

A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines

Directory of Open Access Journals (Sweden)

Paulino José García Nieto

2016-05-01

Full Text Available Remaining useful life (RUL estimation is considered as one of the most central points in the prognostics and health management (PHM. The present paper describes a nonlinear hybrid ABC–MARS-based model for the prediction of the remaining useful life of aircraft engines. Indeed, it is well-known that an accurate RUL estimation allows failure prevention in a more controllable way so that the effective maintenance can be carried out in appropriate time to correct impending faults. The proposed hybrid model combines multivariate adaptive regression splines (MARS, which have been successfully adopted for regression problems, with the artificial bee colony (ABC technique. This optimization technique involves parameter setting in the MARS training procedure, which significantly influences the regression accuracy. However, its use in reliability applications has not yet been widely explored. Bearing this in mind, remaining useful life values have been predicted here by using the hybrid ABC–MARS-based model from the remaining measured parameters (input variables for aircraft engines with success. A correlation coefficient equal to 0.92 was obtained when this hybrid ABC–MARS-based model was applied to experimental data. The agreement of this model with experimental data confirmed its good performance. The main advantage of this predictive model is that it does not require information about the previous operation states of the aircraft engine.

Thermomechanical fatigue life prediction of high temperature components

Energy Technology Data Exchange (ETDEWEB)

Seifert, Thomas; Hartrott, Philipp von; Riedel, Hermann; Siegele, Dieter [Fraunhofer-Inst. fuer Werkstoffmechanik (IWM), Freiburg (Germany)

2009-07-01

The aim of the work described in this paper is to provide a computational method for fatigue life prediction of high temperature components, in which the time and temperature dependent fatigue crack growth is a relevant damage mechanism. The fatigue life prediction is based on a law for microcrack growth and a fracture mechanics estimate of the cyclic crack tip opening displacement. In addition, a powerful model for nonisothermal cyclic plasticity is employed, and an efficient laboratory test procedure is proposed for the determination of the model parameters. The models are efficiently implemented into finite element programs and are used to predict the fatigue life of a cast iron exhaust manifold and a notch in the perimeter of a turbine rotor made of a ferritic/martensitic 10%-chromium steel. (orig.)

Life Prediction on a T700 Carbon Fiber Reinforced Cylinder with Limited Accelerated Life Testing Data

OpenAIRE

Ma Xiaobing; Zhang Yongbo

2015-01-01

An accelerated life testing investigation was conducted on a composite cylinder that consists of aluminum alloy and T700 carbon fiber. The ultimate failure stress predictions of cylinders were obtained by the mixing rule and verified by the blasting static pressure method. Based on the stress prediction of cylinder under working conditions, the constant stress accelerated life test of the cylinder was designed. However, the failure data cannot be sufficiently obtained by the accelerated life ...

Taylor Series-Based Long-Term Creep-Life Prediction of Alloy 617

International Nuclear Information System (INIS)

Yin, Song Nan; Kim, Woo Gon; Kim, Yong Wan; Park, Jae Young; Kim, Soen Jin

2010-01-01

In this study, a Taylor series (T-S) model based on the Arrhenius, McVetty, and Monkman-Grant equations was developed using a mathematical analysis. In order to reduce fitting errors, the McVetty equation was transformed by considering the first three terms of the Taylor series equation. The model parameters were accurately determined by a statistical technique of maximum likelihood estimation, and this model was applied to the creep data of alloy 617. The T-S model results showed better agreement with the experimental data than other models such as the Eno, exponential, and L-M models. In particular, the T-S model was converted into an isothermal Taylor series (IT-S) model that can predict the creep strength at a given temperature. It was identified that the estimations obtained using the converted ITS model was better than that obtained using the T-S model for predicting the long-term creep life of alloy 617

[Research on engine remaining useful life prediction based on oil spectrum analysis and particle filtering].

Science.gov (United States)

Sun, Lei; Jia, Yun-xian; Cai, Li-ying; Lin, Guo-yu; Zhao, Jin-song

2013-09-01

The spectrometric oil analysis(SOA) is an important technique for machine state monitoring, fault diagnosis and prognosis, and SOA based remaining useful life(RUL) prediction has an advantage of finding out the optimal maintenance strategy for machine system. Because the complexity of machine system, its health state degradation process can't be simply characterized by linear model, while particle filtering(PF) possesses obvious advantages over traditional Kalman filtering for dealing nonlinear and non-Gaussian system, the PF approach was applied to state forecasting by SOA, and the RUL prediction technique based on SOA and PF algorithm is proposed. In the prediction model, according to the estimating result of system's posterior probability, its prior probability distribution is realized, and the multi-step ahead prediction model based on PF algorithm is established. Finally, the practical SOA data of some engine was analyzed and forecasted by the above method, and the forecasting result was compared with that of traditional Kalman filtering method. The result fully shows the superiority and effectivity of the

One- and two-stage Arrhenius models for pharmaceutical shelf life prediction.

Science.gov (United States)

Fan, Zhewen; Zhang, Lanju

2015-01-01

One of the most challenging aspects of the pharmaceutical development is the demonstration and estimation of chemical stability. It is imperative that pharmaceutical products be stable for two or more years. Long-term stability studies are required to support such shelf life claim at registration. However, during drug development to facilitate formulation and dosage form selection, an accelerated stability study with stressed storage condition is preferred to quickly obtain a good prediction of shelf life under ambient storage conditions. Such a prediction typically uses Arrhenius equation that describes relationship between degradation rate and temperature (and humidity). Existing methods usually rely on the assumption of normality of the errors. In addition, shelf life projection is usually based on confidence band of a regression line. However, the coverage probability of a method is often overlooked or under-reported. In this paper, we introduce two nonparametric bootstrap procedures for shelf life estimation based on accelerated stability testing, and compare them with a one-stage nonlinear Arrhenius prediction model. Our simulation results demonstrate that one-stage nonlinear Arrhenius method has significant lower coverage than nominal levels. Our bootstrap method gave better coverage and led to a shelf life prediction closer to that based on long-term stability data.

Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network

Science.gov (United States)

Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat

2015-05-01

Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.

Remaining useful life prediction based on variation coefficient consistency test of a Wiener process

Directory of Open Access Journals (Sweden)

Juan LI

2018-01-01

Full Text Available High-cost equipment is often reused after maintenance, and whether the information before the maintenance can be used for the Remaining Useful Life (RUL prediction after the maintenance is directly determined by the consistency of the degradation pattern before and after the maintenance. Aiming at this problem, an RUL prediction method based on the consistency test of a Wiener process is proposed. Firstly, the parameters of the Wiener process estimated by Maximum Likelihood Estimation (MLE are proved to be biased, and a modified unbiased estimation method is proposed and verified by derivation and simulations. Then, the h statistic is constructed according to the reciprocal of the variation coefficient of the Wiener process, and the sampling distribution is derived. Meanwhile, a universal method for the consistency test is proposed based on the sampling distribution theorem, which is verified by simulation data and classical crack degradation data. Finally, based on the consistency test of the degradation model, a weighted fusion RUL prediction method is presented for the fuel pump of an airplane, and the validity of the presented method is verified by accurate computation results of real data, which provides a theoretical and practical guidance for engineers to predict the RUL of equipment after maintenance.

Probabilistic fatigue life prediction methodology for notched components based on simple smooth fatigue tests

Energy Technology Data Exchange (ETDEWEB)

Wu, Z. R.; Li, Z. X. [Dept.of Engineering Mechanics, Jiangsu Key Laboratory of Engineering Mechanics, Southeast University, Nanjing (China); Hu, X. T.; Xin, P. P.; Song, Y. D. [State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing (China)

2017-01-15

The methodology of probabilistic fatigue life prediction for notched components based on smooth specimens is presented. Weakestlink theory incorporating Walker strain model has been utilized in this approach. The effects of stress ratio and stress gradient have been considered. Weibull distribution and median rank estimator are used to describe fatigue statistics. Fatigue tests under different stress ratios were conducted on smooth and notched specimens of titanium alloy TC-1-1. The proposed procedures were checked against the test data of TC-1-1 notched specimens. Prediction results of 50 % survival rate are all within a factor of two scatter band of the test results.

An Analytical Model for Fatigue Life Prediction Based on Fracture Mechanics and Crack Closure

DEFF Research Database (Denmark)

Ibsø, Jan Behrend; Agerskov, Henning

1996-01-01

test specimens are compared with fatigue life predictions using a fracture mechanics approach. In the calculation of the fatigue life, the influence of the welding residual stresses and crack closure on the fatigue crack growth is considered. A description of the crack closure model for analytical...... of the analytical fatigue lives. Both the analytical and experimental results obtained show that the Miner rule may give quite unconservative predictions of the fatigue life for the types of stochastic loading studied....... determination of the fatigue life is included. Furthermore, the results obtained in studies of the various parameters that have an influence on the fatigue life, are given. A very good agreement between experimental and analytical results is obtained, when the crack closure model is used in determination...

An Analytical Model for Fatigue Life Prediction Based on Fracture Mechanics and Crack Closure

DEFF Research Database (Denmark)

Ibsø, Jan Behrend; Agerskov, Henning

1996-01-01

test specimens are compared with fatigue life predictions using a fracture mechanics approach. In the calculation of the fatigue life, the influence of the welding residual stresses and crack closure on the fatigue crack growth is considered. A description of the crack closure model for analytical...... determination of the fatigue life is included. Furthermore, the results obtained in studies of the various parameters that have an influence on the fatigue life, are given. A very good agreement between experimental and analytical results is obtained, when the crack closure model is used in determination...... of the analytical fatigue lives. Both the analytical and experimental results obtained show that the Miner rule may give quite unconservative predictions of the fatigue life for the types of stochastic loading studied....

Prediction of thermal fatigue life of ceramics

International Nuclear Information System (INIS)

Kamiya, N.; Kamigaito, O.

1979-01-01

On the assumption that the thermal fatigue life of ceramics is determined mainly by the duration over which a crack reaches a small critical length, a prediction of the life was made by application of fracture mechanics to ceramics based on subcritical crack growth. Approximated formulae were derived. Experimental examination showed that the formulae proved to be valid for glass, sintered mullite under moderate shock severity, and zirconia. Data given by other authors also prove their validity. The deviation of the life from the formulae for sintered mullite under a thermal shock of extremely low severty, suggests that a certain mechanism, for example strengthening, is needed to understand the life of the sintered mullite. (author)

Lithium-ion battery remaining useful life prediction based on grey support vector machines

Directory of Open Access Journals (Sweden)

Xiaogang Li

2015-12-01

Full Text Available In this article, an improved grey prediction model is proposed to address low-accuracy prediction issue of grey forecasting model. The first step is using a trigonometric function to transform the original data sequence to smooth the data, which is called smoothness of grey prediction model, and then a grey support vector machine model by integrating the improved grey model with support vector machine is introduced. At the initial stage of the model, trigonometric functions and accumulation generation operation can be used to preprocess the data, which enhances the smoothness of the data and reduces the associated randomness. In addition, support vector machine is implemented to establish a prediction model for the pre-processed data and select the optimal model parameters via genetic algorithms. Finally, the data are restored through the ‘regressive generate’ operation to obtain the forecasting data. To prove that the grey support vector machine model is superior to the other models, the battery life data from the Center for Advanced Life Cycle Engineering are selected, and the presented model is used to predict the remaining useful life of the battery. The predicted result is compared to that of grey model and support vector machines. For a more intuitive comparison of the three models, this article quantifies the root mean square errors for these three different models in the case of different ratio of training samples and prediction samples. The results show that the effect of grey support vector machine model is optimal, and the corresponding root mean square error is only 3.18%.

Prediction of Quality of Life of Non–Insulin-Dependent Diabetic Patients Based on Perceived Social Support

Directory of Open Access Journals (Sweden)

Hossein Shareh

2012-04-01

Full Text Available Background: The objective of this study was to predic quality of life based on perceived social support components in non–insulin-dependent diabetic patients.Materials and Method: Fifty patients with non–insulin-dependent diabetes mellitus from Al-Zahra diabetic center in Shiraz participated in a cross-sectional study via survey instrument. All subjects completed multidimensional scale of perceived social support (MSPSS and world health organization quality of life- brief (WHOQOL-BREF questionnaires. Results: On the basis of stepwise multiple regression analysis friends and family dimensions of perceived social support were the best predictors of the quality of life and its dimensions (p<0.01.Conclusion: Friends and family dimensions of perceived social support have significant contributions in predicting quality of life of patients with non–insulin-dependent diabetes mellitus.

A method for uncertainty quantification in the life prediction of gas turbine components

Energy Technology Data Exchange (ETDEWEB)

Lodeby, K.; Isaksson, O.; Jaervstraat, N. [Volvo Aero Corporation, Trolhaettan (Sweden)

1998-12-31

A failure in an aircraft jet engine can have severe consequences which cannot be accepted and high requirements are therefore raised on engine reliability. Consequently, assessment of the reliability of life predictions used in design and maintenance are important. To assess the validity of the predicted life a method to quantify the contribution to the total uncertainty in the life prediction from different uncertainty sources is developed. The method is a structured approach for uncertainty quantification that uses a generic description of the life prediction process. It is based on an approximate error propagation theory combined with a unified treatment of random and systematic errors. The result is an approximate statistical distribution for the predicted life. The method is applied on life predictions for three different jet engine components. The total uncertainty became of reasonable order of magnitude and a good qualitative picture of the distribution of the uncertainty contribution from the different sources was obtained. The relative importance of the uncertainty sources differs between the three components. It is also highly dependent on the methods and assumptions used in the life prediction. Advantages and disadvantages of this method is discussed. (orig.) 11 refs.

High temperature strength data-base of SUS304 steel and a study on life prediction method under ceep-fatigue interaction

International Nuclear Information System (INIS)

Matsubara, Masaaki; Nitta, Akito; Ogata, Takashi; Kuwabara, Kazuo

1985-01-01

As a part of ''Study for practical use of Tank Type FBR'', ''Practical use of inelastic analysis method to FBR structural design'' is carried out as a cooperative study for three years from 1984. In this cooperative study, to establish the life prediction method under creep-fatigue interaction is one of the most important theme. To attain this purpose, many different type tests are planned and then conducted. By the way, to use these many data rapidly and effectively, it is necessary to make a data base. So in this work, we developed the simple data base of high temperature strength. And the data of SUS304 obtained at this place to this day are inputted into this data base. Next, we investigated about five life prediction methods under creep-fatigue interaction, Frequency Modified Method, Ostergren Method, Strain Range Partitioning Method, Damage Rate Approach and Strain Energy Parameter Method. As a result, Strain Range Partitioning Method can predict the lives within Factor of 2. In the other four methods, it is supported that material constants in the prediction formula are dependent on temperature. (author)

Prediction of residual life of low-cycle fatigue in austenitic stainless steel based on indentation test

International Nuclear Information System (INIS)

Yonezu, Akio; Touda, Yuya; Kim, HakGui; Yoneda, Keishi; Sakihara, Masayuki; Minoshima; Kohji

2011-01-01

In this study, a method to predict residual life of low-cycle fatigue in austenitic stainless steel (SUS316NG) was proposed based on indentation test. Low-cycle fatigue tests for SUS316NG were first conducted based on uniaxial tensile-compressive loading under the control of true strain range. Applied strain ranges were varied from about 3 to 12%. Their hysteresis loops of stress and strain were monitored during the fatigue tests. Plastic deformation range in hysteresis loop at each cycle could be roughly expressed by bi-linear hardening rule, whose plastic properties involve yield stress and work-hardening coefficient. The cyclic plastic properties were found to be dependent on the number of cycles and applied strain range, due to work-hardening. We experimentally investigated the empirical relationship between the plastic properties and number of cycles for each applied strain range. It is found that the relationship quantitatively predicts the applied strain range and number of cycles, when the plastic properties, or yield stress and work-hardening coefficient were known. Indentation tests were applied to the samples subjected to low cycle fatigue test, in order to quantitatively determine the plastic properties. The estimated properties were assigned to the proposed relationship, yielding the applied strain range and the cycle numbers. The proposed method was applied to the several stainless steel samples subjected to low cycle fatigue tests, suggesting that their residual lives could be reasonably predicted. Our method is thus useful for predicting the residual life of low-cycle fatigue in austenitic stainless steel. (author)

Service life prediction and cementitious composites

DEFF Research Database (Denmark)

Stoklund Larsen, E.

The present Ph.D.thesis describes and discusses the applicability of a systematic methodology recommended by CIB W80/RILEM-PSL for sevice life prediction. The report describes the most important inherent and environmental factors affecting the service life of structures of cementitious composites....... On the basis of this discription of factors and experience from a test programme described in SBI Report 222, Service life prediction and fibre reinforced cementitious composites, the applicabillity of the CIB/RILEM methodology is discussed....

Towards a unified fatigue life prediction method for marine structures

CERN Document Server

Cui, Weicheng; Wang, Fang

2014-01-01

In order to apply the damage tolerance design philosophy to design marine structures, accurate prediction of fatigue crack growth under service conditions is required. Now, more and more people have realized that only a fatigue life prediction method based on fatigue crack propagation (FCP) theory has the potential to explain various fatigue phenomena observed. In this book, the issues leading towards the development of a unified fatigue life prediction (UFLP) method based on FCP theory are addressed. Based on the philosophy of the UFLP method, the current inconsistency between fatigue design and inspection of marine structures could be resolved. This book presents the state-of-the-art and recent advances, including those by the authors, in fatigue studies. It is designed to lead the future directions and to provide a useful tool in many practical applications. It is intended to address to engineers, naval architects, research staff, professionals and graduates engaged in fatigue prevention design and survey ...

A summary of methods of predicting reliability life of nuclear equipment with small samples

International Nuclear Information System (INIS)

Liao Weixian

2000-03-01

Some of nuclear equipment are manufactured in small batch, e.g., 1-3 sets. Their service life may be very difficult to determine experimentally in view of economy and technology. The method combining theoretical analysis with material tests to predict the life of equipment is put forward, based on that equipment consists of parts or elements which are made of different materials. The whole life of an equipment part consists of the crack forming life (i.e., the fatigue life or the damage accumulation life) and the crack extension life. Methods of predicting machine life has systematically summarized with the emphasis on those which use theoretical analysis to substitute large scale prototype experiments. Meanwhile, methods and steps of predicting reliability life have been described by taking into consideration of randomness of various variables and parameters in engineering. Finally, the latest advance and trends of machine life prediction are discussed

End-of-Discharge and End-of-Life Prediction in Lithium-Ion Batteries with Electrochemistry-Based Aging Models

Science.gov (United States)

Daigle, Matthew; Kulkarni, Chetan S.

2016-01-01

As batteries become increasingly prevalent in complex systems such as aircraft and electric cars, monitoring and predicting battery state of charge and state of health becomes critical. In order to accurately predict the remaining battery power to support system operations for informed operational decision-making, age-dependent changes in dynamics must be accounted for. Using an electrochemistry-based model, we investigate how key parameters of the battery change as aging occurs, and develop models to describe aging through these key parameters. Using these models, we demonstrate how we can (i) accurately predict end-of-discharge for aged batteries, and (ii) predict the end-of-life of a battery as a function of anticipated usage. The approach is validated through an experimental set of randomized discharge profiles.

Life Prediction Issues in Thermal/Environmental Barrier Coatings in Ceramic Matrix Composites

Science.gov (United States)

Shah, Ashwin R.; Brewer, David N.; Murthy, Pappu L. N.

2001-01-01

Issues and design requirements for the environmental barrier coating (EBC)/thermal barrier coating (TBC) life that are general and those specific to the NASA Ultra-Efficient Engine Technology (UEET) development program have been described. The current state and trend of the research, methods in vogue related to the failure analysis, and long-term behavior and life prediction of EBCITBC systems are reported. Also, the perceived failure mechanisms, variables, and related uncertainties governing the EBCITBC system life are summarized. A combined heat transfer and structural analysis approach based on the oxidation kinetics using the Arrhenius theory is proposed to develop a life prediction model for the EBC/TBC systems. Stochastic process-based reliability approach that includes the physical variables such as gas pressure, temperature, velocity, moisture content, crack density, oxygen content, etc., is suggested. Benefits of the reliability-based approach are also discussed in the report.

Towards a Universal Biology: Is the Origin and Evolution of Life Predictable?

Science.gov (United States)

Rothschild, Lynn J.

2017-01-01

The origin and evolution of life seems an unpredictable oddity, based on the quirks of contingency. Celebrated by the late Stephen Jay Gould in several books, "evolution by contingency" has all the adventure of a thriller, but lacks the predictive power of the physical sciences. Not necessarily so, replied Simon Conway Morris, for convergence reassures us that certain evolutionary responses are replicable. The outcome of this debate is critical to Astrobiology. How can we understand where we came from on Earth without prophesy? Further, we cannot design a rational strategy for the search for life elsewhere - or to understand what the future will hold for life on Earth and beyond - without extrapolating from pre-biotic chemistry and evolution. There are several indirect approaches to understanding, and thus describing, what life must be. These include philosophical approaches to defining life (is there even a satisfactory definition of life?), using what we know of physics, chemistry and life to imagine alternate scenarios, using different approaches that life takes as pseudoreplicates (e.g., ribosomal vs non-ribosomal protein synthesis), and experimental approaches to understand the art of the possible. Given that: (1) Life is a process based on physical components rather than simply an object; (2). Life is likely based on organic carbon and needs a solvent for chemistry, most likely water, and (3) Looking for convergence in terrestrial evolution we can predict certain tendencies, if not quite "laws", that provide predictive power. Biological history must obey the laws of physics and chemistry, the principles of natural selection, the constraints of an evolutionary past, genetics, and developmental biology. This amalgam creates a surprising amount of predictive power in the broad outline. Critical is the apparent prevalence of organic chemistry, and uniformity in the universe of the laws of chemistry and physics. Instructive is the widespread occurrence of

Life prediction methodology for thermal-mechanical fatigue and elevated temperature creep design

Science.gov (United States)

Annigeri, Ravindra

Nickel-based superalloys are used for hot section components of gas turbine engines. Life prediction techniques are necessary to assess service damage in superalloy components resulting from thermal-mechanical fatigue (TMF) and elevated temperature creep. A new TMF life model based on continuum damage mechanics has been developed and applied to IN 738 LC substrate material with and without coating. The model also characterizes TMF failure in bulk NiCoCrAlY overlay and NiAl aluminide coatings. The inputs to the TMF life model are mechanical strain range, hold time, peak cycle temperatures and maximum stress measured from the stabilized or mid-life hysteresis loops. A viscoplastic model is used to predict the stress-strain hysteresis loops. A flow rule used in the viscoplastic model characterizes the inelastic strain rate as a function of the applied stress and a set of three internal stress variables known as back stress, drag stress and limit stress. Test results show that the viscoplastic model can reasonably predict time-dependent stress-strain response of the coated material and stress relaxation during hold times. In addition to the TMF life prediction methodology, a model has been developed to characterize the uniaxial and multiaxial creep behavior. An effective stress defined as the applied stress minus the back stress is used to characterize the creep recovery and primary creep behavior. The back stress has terms representing strain hardening, dynamic recovery and thermal recovery. Whenever the back stress is greater than the applied stress, the model predicts a negative creep rate observed during multiple stress and multiple temperature cyclic tests. The model also predicted the rupture time and the remaining life that are important for life assessment. The model has been applied to IN 738 LC, Mar-M247, bulk NiCoCrAlY overlay coating and 316 austenitic stainless steel. The proposed model predicts creep response with a reasonable accuracy for wide range of

MEMS based shock pulse detection sensor for improved rotary Stirling cooler end of life prediction

Science.gov (United States)

Hübner, M.; Münzberg, M.

2018-05-01

The widespread use of rotary Stirling coolers in high performance thermal imagers used for critical 24/7 surveillance tasks justifies any effort to significantly enhance the reliability and predictable uptime of those coolers. Typically the lifetime of the whole imaging device is limited due to continuous wear and finally failure of the rotary compressor of the Stirling cooler, especially due to failure of the comprised bearings. MTTF based lifetime predictions, even based on refined MTTF models taking operational scenario dependent scaling factors into account, still lack in precision to forecast accurately the end of life (EOL) of individual coolers. Consequently preventive maintenance of individual coolers to avoid failures of the main sensor in critical operational scenarios are very costly or even useless. We have developed an integrated test method based on `Micro Electromechanical Systems', so called MEMS sensors, which significantly improves the cooler EOL prediction. The recently commercially available MEMS acceleration sensors have mechanical resonance frequencies up to 50 kHz. They are able to detect solid borne shock pulses in the cooler structure, originating from e.g. metal on metal impacts driven by periodical forces acting on moving inner parts of the rotary compressor within wear dependent slack and play. The impact driven transient shock pulse analyses uses only the high frequency signal <10kHz and differs therefore from the commonly used broadband low frequencies vibrational analysis of reciprocating machines. It offers a direct indicator of the individual state of wear. The predictive cooler lifetime model based on the shock pulse analysis is presented and results are discussed.

Remaining useful life prediction based on the Wiener process for an aviation axial piston pump

Directory of Open Access Journals (Sweden)

Xingjian Wang

2016-06-01

Full Text Available An aviation hydraulic axial piston pump’s degradation from comprehensive wear is a typical gradual failure model. Accurate wear prediction is difficult as random and uncertain characteristics must be factored into the estimation. The internal wear status of the axial piston pump is characterized by the return oil flow based on fault mechanism analysis of the main frictional pairs in the pump. The performance degradation model is described by the Wiener process to predict the remaining useful life (RUL of the pump. Maximum likelihood estimation (MLE is performed by utilizing the expectation maximization (EM algorithm to estimate the initial parameters of the Wiener process while recursive estimation is conducted utilizing the Kalman filter method to estimate the drift coefficient of the Wiener process. The RUL of the pump is then calculated according to the performance degradation model based on the Wiener process. Experimental results indicate that the return oil flow is a suitable characteristic for reflecting the internal wear status of the axial piston pump, and thus the Wiener process-based method may effectively predicate the RUL of the pump.

A study on the fatigue life prediction of tire belt-layers using probabilistic method

International Nuclear Information System (INIS)

Lee, Dong Woo; Park, Jong Sang; Lee, Tae Won; Kim, Seong Rae; Sung, Ki Deug; Huh, Sun Chul

2013-01-01

Tire belt separation failure is occurred by internal cracks generated in *1 and *2 belt layers and by its growth. And belt failure seriously affects tire endurance. Therefore, to improve the tire endurance, it is necessary to analyze tire crack growth behavior and predict fatigue life. Generally, the prediction of tire endurance is performed by the experimental method using tire test machine. But it takes much cost and time to perform experiment. In this paper, to predict tire fatigue life, we applied deterministic fracture mechanics approach, based on finite element analysis. Also, probabilistic analysis method based on statistics using Monte Carlo simulation is presented. Above mentioned two methods include a global-local finite element analysis to provide the detail necessary to model explicitly an internal crack and calculate the J-integral for tire life prediction.

A computational approach for thermomechanical fatigue life prediction of dissimilarly welded superheater tubes

Energy Technology Data Exchange (ETDEWEB)

Krishnasamy, Ram-Kumar; Seifert, Thomas; Siegele, Dieter [Fraunhofer-Institut fuer Werkstoffmechanik (IWM), Freiburg im Breisgau (Germany)

2010-07-01

In this paper a computational approach for fatigue life prediction of dissimilarly welded superheater tubes is presented and applied to a dissimilar weld between tubes made of the nickel base alloy Alloy617 tube and the 12% chromium steel VM12. The approach comprises the calculation of the residual stresses in the welded tubes with a multi-pass dissimilar welding simulation, the relaxation of the residual stresses in a post weld heat treatment (PWHT) simulation and the fatigue life prediction using the remaining residual stresses as initial condition. A cyclic fiscoplasticity model is used to calculate the transient stresses and strains under thermocyclic service loadings. The fatigue life is predicted with a damage parameter which is based on fracture mechanics. The adjustable parameters of the model are determined based on LCF and TMF experiments. The simulations show, that the residual stresses that remain after PWHT further relax in the first loading cycles. The predicted fatigue lives depend on the residual stresses and, thus, on the choice of the loading cycle in which the damage parameter is evaluated. It the first loading cycle, where residual stresses are still present, is considered, lower fatigue lives are predicted compared to predictions considering loading cycles with relaxed residual stresses. (orig.)

Time-dependent fatigue--phenomenology and life prediction

International Nuclear Information System (INIS)

Coffin, L.F.

1979-01-01

The time-dependent fatigue behavior of materials used or considered for use in present and advanced systems for power generation is outlined. A picture is first presented to show how basic mechanisms and phenomenological information relate to the performance of the component under consideration through the so-called local strain approach. By this means life prediction criteria and design rules can be formulated utilizing laboratory test information which is directly translated to predicting the performance of a component. The body of phenomenological information relative to time-dependent fatigue is reviewed. Included are effects of strain range, strain rate and frequency, environment and wave shape, all of which are shown to be important in developing both an understanding and design base for time dependent fatigue. Using this information, some of the current methods being considered for the life prediction of components are reviewed. These include the current ASME code case, frequency-modified fatigue equations, strain range partitioning, the damage function method, frequency separation and damage rate equations. From this review, it is hoped that a better perspective on future directions for basic material science at high temperature can be achieved

Solid-state lighting life prediction using extended Kalman filter

Energy Technology Data Exchange (ETDEWEB)

Lall, Pradeep [Auburn Univ., AL (United States); Wei, Junchao [Auburn Univ., AL (United States); Davis, Lynn [RTI International, Durham, NC (United States)

2013-07-16

-80 test data for various LEDs have been used for model development. System state has been described in state space form using the measurement of the feature vector, velocity of feature vector change and the acceleration of the feature vector change. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. The measured state variable has been related to the underlying damage using physics-based models. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have been compared with the TM-21 model predictions and experimental data.

Innovative predictive maintenance concepts to improve life cycle management

NARCIS (Netherlands)

Tinga, Tiedo

2014-01-01

For naval systems with typically long service lives, high sustainment costs and strict availability requirements, an effective and efficient life cycle management process is very important. In this paper four approaches are discussed to improve that process: physics of failure based predictive

Fatigue life prediction and strength degradation of wind turbine rotor blade composites

NARCIS (Netherlands)

Nijssen, R.P.L.

2006-01-01

Wind turbine rotor blades are subjected to a large number of highly variable loads, but life predictions are typically based on constant amplitude fatigue behaviour. Therefore, it is important to determine how service life under variable amplitude fatigue can be estimated from constant amplitude

Application of the strain energy for fatigue life prediction (LCF) of metals by the energy-based criterion

International Nuclear Information System (INIS)

Shahram Shahrooi; Ibrahim Henk Metselaar; Zainul Huda; Ghezavati, H.R.

2009-01-01

Full text: In this study, the plastic strain energy under multiaxial fatigue condition has been calculated in the cyclic plasticity models by the stress-strain hysteresis loops. Then, using the results of these models, the fatigue lives in energy-based fatigue model is predicted and compared to experimental data. Moreover, a weighting factor on shear plastic work is presented to decrease the life factors in the model fatigue. (author)

Thermo-mechanical fatigue behaviour and life prediction of C-1023 ...

African Journals Online (AJOL)

user

Mechanical strain-cycles to failure curves for 890-1055 ºC temperature range. ... could be ascribed to creep strain accumulation at high temperatures coinciding ... It is common in engineering applications to rely on life prediction models based ...

General life satisfaction predicts dementia in community living older adults: a prospective cohort study.

Science.gov (United States)

Peitsch, Lorraine; Tyas, Suzanne L; Menec, Verena H; St John, Philip D

2016-07-01

Low life satisfaction predicts adverse outcomes, and may predict dementia. The objectives were: (1) to determine if life satisfaction predicts dementia over a five year period in those with normal cognition at baseline; and (2) to determine if different aspects of life satisfaction differentially predict dementia. Secondary analysis of an existing population-based cohort study with initial assessment in 1991 and follow-up five years later. Initially, 1,751 adults age 65+ living in the community were sampled from a representative sampling frame. Of these, 1,024 were alive and had complete data at time 2, of whom 96 were diagnosed with dementia. Life satisfaction was measured using the Terrible-Delightful scale, which measures overall life satisfaction on a 7-point scale, as well as various aspects of life satisfaction (e.g. friendships, finances, etc.) Dementia was diagnosed by clinical examination using DSM-IIIR criteria. Logistic regression models were constructed for the outcome of dementia at time 2, and adjusted for age, gender, education, and comorbidities. Overall life satisfaction predicted dementia five years later, at time 2. The unadjusted Odds Ratio (OR; 95% confidence interval) for dementia at time 2 was 0.72 (0.55, 0.95) per point. The adjusted OR for dementia was 0.70 (0.51, 0.96). No individual item on the life satisfaction scale predicted dementia. However, the competing risk of mortality was very high for some items. A global single-item measure of life satisfaction predicts dementia over a five year period in older adults without cognitive impairment.

Life-Space Predicts Health Care Utilization in Community-Dwelling Older Adults.

Science.gov (United States)

Kennedy, Richard E; Williams, Courtney P; Sawyer, Patricia; Lo, Alexander X; Connelly, Kay; Nassel, Ariann; Brown, Cynthia J

2017-09-01

To determine whether decline in life-space mobility predicts increased health care utilization among community-dwelling older adults. Health care utilization (number of emergency department [ED] visits and hospitalizations) was self-reported during monthly interviews among 419 community-dwelling African American and non-Hispanic White adults aged 75 years and older in The University of Alabama at Birmingham (UAB) Study of Aging II. Life-space was measured using the UAB Life-Space Assessment. Generalized estimating equations were used to examine associations of life-space at the beginning of each interval with health care utilization over the 1-month interval. Overall, 400 participants were followed for 36 months. A 10-point decrease in life-space was associated with 14% increased odds of an ED visit and/or hospitalization over the next month, adjusting for demographics, transportation difficulty, comorbidity, and having a doctor visit in the last month. Life-space is a practical alternative in predicting future health care utilization to performance-based measures, which can be difficult to incorporate into clinical or public health practice.

Fatigue crack growth and life prediction under mixed-mode loading

Science.gov (United States)

Sajith, S.; Murthy, K. S. R. K.; Robi, P. S.

2018-04-01

Fatigue crack growth life as a function of crack length is essential for the prevention of catastrophic failures from damage tolerance perspective. In damage tolerance design approach, principles of fracture mechanics are usually applied to predict the fatigue life of structural components. Numerical prediction of crack growth versus number of cycles is essential in damage tolerance design. For cracks under mixed mode I/II loading, modified Paris law (d/a d N =C (ΔKe q ) m ) along with different equivalent stress intensity factor (ΔKeq) model is used for fatigue crack growth rate prediction. There are a large number of ΔKeq models available for the mixed mode I/II loading, the selection of proper ΔKeq model has significant impact on fatigue life prediction. In the present investigation, the performance of ΔKeq models in fatigue life prediction is compared with respect to the experimental findings as there are no guidelines/suggestions available on the selection of these models for accurate and/or conservative predictions of fatigue life. Within the limitations of availability of experimental data and currently available numerical simulation techniques, the results of present study attempt to outline models that would provide accurate and conservative life predictions. Such a study aid the numerical analysts or engineers in the proper selection of the model for numerical simulation of the fatigue life. Moreover, the present investigation also suggests a procedure to enhance the accuracy of life prediction using Paris law.

How long will my mouse live? Machine learning approaches for prediction of mouse life span.

Science.gov (United States)

Swindell, William R; Harper, James M; Miller, Richard A

2008-09-01

Prediction of individual life span based on characteristics evaluated at middle-age represents a challenging objective for aging research. In this study, we used machine learning algorithms to construct models that predict life span in a stock of genetically heterogeneous mice. Life-span prediction accuracy of 22 algorithms was evaluated using a cross-validation approach, in which models were trained and tested with distinct subsets of data. Using a combination of body weight and T-cell subset measures evaluated before 2 years of age, we show that the life-span quartile to which an individual mouse belongs can be predicted with an accuracy of 35.3% (+/-0.10%). This result provides a new benchmark for the development of life-span-predictive models, but improvement can be expected through identification of new predictor variables and development of computational approaches. Future work in this direction can provide tools for aging research and will shed light on associations between phenotypic traits and longevity.

Application of structural reliability and risk assessment to life prediction and life extension decision making

International Nuclear Information System (INIS)

Meyer, T.A.; Balkey, K.R.; Bishop, B.A.

1987-01-01

There can be numerous uncertainties involved in performing component life assessments. In addition, sufficient data may be unavailable to make a useful life prediction. Structural Reliability and Risk Assessment (SRRA) is primarily an analytical methodology or tool that quantifies the impact of uncertainties on the structural life of plant components and can address the lack of data in component life prediction. As a prelude to discussing the technical aspects of SRRA, a brief review of general component life prediction methods is first made so as to better develop an understanding of the role of SRRA in such evaluations. SRRA is then presented as it is applied in component life evaluations with example applications being discussed for both nuclear and non-nuclear components

A study of fatigue life prediction for automotive spot weldment using local strain approach

International Nuclear Information System (INIS)

Lee, Song In; Yu, Hyo Sun; Na, Sung Hun; Na, Eui Gyun

2000-01-01

The fatigue crack initiation life is studied on automotive spot weldment made from cold rolled carbon steel(SPC) sheet by using DCPDM and local strain approach. It can be found that the fatigue crack initiation behavior in spot weldment can be definitely detected by DCPDM system. The local stresses and strains are estimated by elastic-plastic FEM analysis and the alternative approximate method based on Neuber's rule were applied to predict the fatigue life of spot weldment. A satisfactory correlation between the predicted life and experimental life can be found in spot weldment within a factor of 4

Physics based modeling of a series parallel battery pack for asymmetry analysis, predictive control and life extension

Science.gov (United States)

Ganesan, Nandhini; Basu, Suman; Hariharan, Krishnan S.; Kolake, Subramanya Mayya; Song, Taewon; Yeo, Taejung; Sohn, Dong Kee; Doo, Seokgwang

2016-08-01

Lithium-Ion batteries used for electric vehicle applications are subject to large currents and various operation conditions, making battery pack design and life extension a challenging problem. With increase in complexity, modeling and simulation can lead to insights that ensure optimal performance and life extension. In this manuscript, an electrochemical-thermal (ECT) coupled model for a 6 series × 5 parallel pack is developed for Li ion cells with NCA/C electrodes and validated against experimental data. Contribution of the cathode to overall degradation at various operating conditions is assessed. Pack asymmetry is analyzed from a design and an operational perspective. Design based asymmetry leads to a new approach of obtaining the individual cell responses of the pack from an average ECT output. Operational asymmetry is demonstrated in terms of effects of thermal gradients on cycle life, and an efficient model predictive control technique is developed. Concept of reconfigurable battery pack is studied using detailed simulations that can be used for effective monitoring and extension of battery pack life.

Failure analysis and seal life prediction for contacting mechanical seals

Science.gov (United States)

Sun, J. J.; He, X. Y.; Wei, L.; Feng, X.

2008-11-01

Fault tree analysis method was applied to quantitatively investigate the causes of the leakage failure of mechanical seals. It is pointed out that the change of the surface topography is the main reasons causing the leakage of mechanical seals under the condition of constant preloads. Based on the fractal geometry theory, the relationship between the surface topography and working time were investigated by experiments, and the effects of unit load acting on seal face on leakage path in a mechanical seal were analyzed. The model of predicting seal life of mechanical seals was established on the basis of the relationship between the surface topography and working time and allowable leakage. The seal life of 108 mechanical seal operating at the system of diesel fuel storage and transportation was predicted and the problem of the condition monitoring for the long-period operation of mechanical seal was discussed by this method. The research results indicate that the method of predicting seal life of mechanical seals is feasible, and also is foundation to make scheduled maintenance time and to achieve safe-reliability and low-cost operation for industrial devices.

Predicting the residual life of plant equipment - Why worry

International Nuclear Information System (INIS)

Jaske, C.E.

1985-01-01

Predicting the residual life of plant equipment that has been in service for 20 to 30 years or more is a major concern of many industries. This paper reviews the reasons for increased concern for residual-life assessment and the general procedures used in performing such assessments. Some examples and case histories illustrating procedures for assessing remaining service life are discussed. Areas where developments are needed to improve the technology for remaining-life estimation are pointed out. Then, some of the critical issues involved in residual-life assessment are identified. Finally, the future role of residual-life prediction is addressed

Prediction Model and Principle of End-of-Life Threshold for Lithium Ion Batteries Based on Open Circuit Voltage Drifts

International Nuclear Information System (INIS)

Cui, Yingzhi; Yang, Jie; Du, Chunyu; Zuo, Pengjian; Gao, Yunzhi; Cheng, Xinqun; Ma, Yulin; Yin, Geping

2017-01-01

Highlights: •Open circuit voltage evolution over ageing of lithium ion batteries is deciphered. •The mechanism responsible for the end-of-life (EOL) threshold is elaborated. •A new prediction model of EOL threshold with improved accuracy is developed. •This EOL prediction model is promising for the applications in electric vehicles. -- Abstract: The end-of-life (EOL) of a lithium ion battery (LIB) is defined as the time point when the LIB can no longer provide sufficient power or energy to accomplish its intended function. Generally, the EOL occurs abruptly when the degradation of a LIB reaches the threshold. Therefore, current prediction methods of EOL by extrapolating the early degradation behavior often result in significant errors. To address this problem, this paper analyzes the reason for the EOL threshold of a LIB with shallow depth of discharge. It is found that the sudden appearance of EOL threshold results from the drift of open circuit voltage (OCV) at the end of both shallow depth and full discharges. Further, a new EOL threshold prediction model with highly improved accuracy is developed based on the OCV drifts and their evolution mechanism, which can effectively avoid the misjudgment of EOL threshold. The accuracy of this EOL threshold prediction model is verified by comparing with experimental results. The EOL threshold prediction model can be applied to other battery chemistry systems and its possible application in electric vehicles is finally discussed.

Degradation model and application in life prediction of rotating-mechanism

International Nuclear Information System (INIS)

Zhou Yuhui

2009-01-01

The degradation data can provide additional information beyond that provided by the failure observations, both sets of observations need to be considered when doing inference on the statistical parameters of the product and system lifetime distributions. By the degradation model showing the wear out failure, the predicted results of mechanism life is more accurate. Strength is one of the important capabilities of the rotating mechanism. In this paper, the degradation data of strength are described as a stochastic process model. Accelerated tests expose the products to greater environmental stress levels so that we can obtain lifetime and degradation measurements in a more timely fashion. Using the Best Linear Unbiased Estimation (BLUE) Method, the parameters under the degradation path were estimated from the accelerated life test (ALT) data of the rotating mechanism. Based on solving the singularity of degradation equation, at any time the reliability is estimated by the using the strength-stress interference theory. So we can predict the life of the rotating mechanism. (authors)

Fatigue life prediction in composites

CSIR Research Space (South Africa)

Huston, RJ

1994-01-01

Full Text Available Because of the relatively large number of possible failure mechanisms in fibre reinforced composite materials, the prediction of fatigue life in a component is not a simple process. Several mathematical and statistical models have been proposed...

Teachers' assessments of children aged eight predict life satisfaction in adolescence.

Science.gov (United States)

Honkanen, Meri; Meri, Honkanen; Hurtig, Tuula; Tuula, Hurtig; Taanila, Anja; Anja, Taanila; Moilanen, Irma; Irma, Moilanen; Koponen, Hannu; Hannu, Koponen; Mäki, Pirjo; Pirjo, Mäki; Veijola, Juha; Juha, Veijola; Puustjärvi, Anita; Anita, Puustjärvi; Ebeling, Hanna; Hanna, Ebeling; Koivumaa-Honkanen, Heli; Heli, Koivumaa-Honkanen

2011-09-01

The objective was to investigate how teachers' assessments of children predict life satisfaction in adolescence. This is a prospective cohort study on the population-based Northern Finland Birth Cohort 1986 (n = 8,959). Information was gathered from parents, teachers and adolescents using questionnaires at the age of 7, 8 and 15. Response rates were 80-90%. Emotional and behavioural problems were assessed with Rutter Children's Behavioural Questionnaires for teachers (RB2) and parents (RA2) during the first grade at age 8. At adolescence, self-reported life satisfaction was measured with a question including five response alternatives. According to teachers' assessments, 13.9% of the children had high emotional or behavioural problems (RB2 ≥9). These assessments predicted life dissatisfaction in adolescence (OR(crude) = 1.77; 95% CI 1.43-2.20) in several models including also health behaviour and use of psychotropic medicine. However, introducing all the significant variables in the same model, RB2 lost its significance (OR = 1.28; 0.96-1.70), but good school achievement assessed by teachers was still a significant predictor. Life satisfaction in adolescence was associated with a variety of favourable concurrent factors. In conclusion teachers' assessments of children during the first school year predicted life satisfaction in adolescence. In mental health promotion, teachers' early assessments should be utilized for the benefit of children.

Prediction of Combine Economic Life Based on Repair and Maintenance Costs Model

Directory of Open Access Journals (Sweden)

A Rohani

2014-09-01

Full Text Available Farm machinery managers often need to make complex economic decisions on machinery replacement. Repair and maintenance costs can have significant impacts on this economic decision. The farm manager must be able to predict farm machinery repair and maintenance costs. This study aimed to identify a regression model that can adequately represent the repair and maintenance costs in terms of machine age in cumulative hours of use. The regression model has the ability to predict the repair and maintenance costs for longer time periods. Therefore, it can be used for the estimation of the economic life. The study was conducted using field data collected from 11 John-Deer 955 combine harvesters used in several western provinces of Iran. It was found that power model has a better performance for the prediction of combine repair and maintenance costs. The results showed that the optimum replacement age of John-Deer 955 combine was 54300 cumulative hours.

Fatigue life prediction in woven carbon fabric polyester composites

International Nuclear Information System (INIS)

Khan, Z.; Al-Sulaiman, F.S.; Farooqi, J.K.

1999-01-01

An analytical model, based on stiffness degradation during fatigue loading, which has been used for fatigue life predictions in the Fiber Reinforced Plastics (FRP), is employed to examine its validity to the fatigue life predictions in the Woven Fabric Reinforced Plastics. The rate of stiffness degradation (dE/dN) has been obtained from the constant amplitude fatigue testing of 8-ply coupons made from prepreg plain-weave woven carbon-carbon fabric having a polyester resin as the matrix material. The test coupons had three different ply stacking sequences, namely, the unidirectional (0)8,and two off axis plied (0,0,+45,-45)s, and (+45,-45,0,0)s orientations. The estimated fatigue lives obtained from the damage rate function dD/dN, which in turn was a function of the stiffness degradation rate dE/dN, were compared with the experimentally observed fatigue life data. It is shown that the stiffness degradation model provides reasonably good correlation between the analytically determined fatigue lives and the experimentally observed fatigue for the plain-weave woven Carbon-Carbon Fabric Reinforced Plastic Composites. (author)

Fatigue life prediction of rotor blade composites: Validation of constant amplitude formulations with variable amplitude experiments

International Nuclear Information System (INIS)

Westphal, T; Nijssen, R P L

2014-01-01

The effect of Constant Life Diagram (CLD) formulation on the fatigue life prediction under variable amplitude (VA) loading was investigated based on variable amplitude tests using three different load spectra representative for wind turbine loading. Next to the Wisper and WisperX spectra, the recently developed NewWisper2 spectrum was used. Based on these variable amplitude fatigue results the prediction accuracy of 4 CLD formulations is investigated. In the study a piecewise linear CLD based on the S-N curves for 9 load ratios compares favourably in terms of prediction accuracy and conservativeness. For the specific laminate used in this study Boerstra's Multislope model provides a good alternative at reduced test effort

Fatigue life prediction of rotor blade composites: Validation of constant amplitude formulations with variable amplitude experiments

Science.gov (United States)

Westphal, T.; Nijssen, R. P. L.

2014-12-01

The effect of Constant Life Diagram (CLD) formulation on the fatigue life prediction under variable amplitude (VA) loading was investigated based on variable amplitude tests using three different load spectra representative for wind turbine loading. Next to the Wisper and WisperX spectra, the recently developed NewWisper2 spectrum was used. Based on these variable amplitude fatigue results the prediction accuracy of 4 CLD formulations is investigated. In the study a piecewise linear CLD based on the S-N curves for 9 load ratios compares favourably in terms of prediction accuracy and conservativeness. For the specific laminate used in this study Boerstra's Multislope model provides a good alternative at reduced test effort.

A proposal of parameter to predict biaxial fatigue life for CF8M cast stainless steels

International Nuclear Information System (INIS)

Park, Joong Cheul; Kwon, Jae Do

2005-01-01

Biaxial low cycle fatigue test was carried out to predict fatigue life under combined axial-torsional loading condition which is that of in-phase and out-of-phase for CF8M cast stainless steels. Fatemi Socie(FS) parameter which is based on critical plane approach is not only one of methods but also the best method that can predict fatigue life under biaxial loading condition. But the result showed that, biaxial fatigue life prediction by using FS parameter with several different parameters for the CF8M cast stainless steels is not conservative but best results. So in this present research, we proposed new fatigue life prediction parameter considering effective shear stress instead of FS parameter which considers the maximum normal stress acting on maximum shear strain and its effectiveness was verified

Energy Dissipation-Based Method for Fatigue Life Prediction of Rock Salt

Science.gov (United States)

He, Mingming; Huang, Bingqian; Zhu, Caihui; Chen, Yunsheng; Li, Ning

2018-05-01

The fatigue test for rock salt is conducted under different stress amplitudes, loading frequencies, confining pressures and loading rates, from which the evaluation rule of the dissipated energy is revealed and analysed. The evolution of energy dissipation under fatigue loading is divided into three stages: the initial stage, the second stage and the acceleration stage. In the second stage, the energy dissipation per cycle remains stable and shows an exponential relation with the stress amplitude; the failure dissipated energy only depends on the mechanical behaviour of the rock salt and confining pressure, but it is immune to the loading conditions. The energy dissipation of fatigued rock salt is discussed, and a novel model for fatigue life prediction is proposed on the basis of energy dissipation. A simple model for evolution of the accumulative dissipated energy is established. Its prediction results are compared with the test results, and the proposed model is validated.

The construction of life prediction models for the design of Stirling engine heater components

Science.gov (United States)

Petrovich, A.; Bright, A.; Cronin, M.; Arnold, S.

1983-01-01

The service life of Stirling-engine heater structures of Fe-based high-temperature alloys is predicted using a numerical model based on a linear-damage approach and published test data (engine test data for a Co-based alloy and tensile-test results for both the Co-based and the Fe-based alloys). The operating principle of the automotive Stirling engine is reviewed; the economic and technical factors affecting the choice of heater material are surveyed; the test results are summarized in tables and graphs; the engine environment and automotive duty cycle are characterized; and the modeling procedure is explained. It is found that the statistical scatter of the fatigue properties of the heater components needs to be reduced (by decreasing the porosity of the cast material or employing wrought material in fatigue-prone locations) before the accuracy of life predictions can be improved.

Life prediction of steam generator tubing due to stress corrosion crack using Monte Carlo Simulation

International Nuclear Information System (INIS)

Hu Jun; Liu Fei; Cheng Guangxu; Zhang Zaoxiao

2011-01-01

Highlights: → A life prediction model for SG tubing was proposed. → The initial crack length for SCC was determined. → Two failure modes called rupture mode and leak mode were considered. → A probabilistic life prediction code based on Monte Carlo method was developed. - Abstract: The failure of steam generator tubing is one of the main accidents that seriously affects the availability and safety of a nuclear power plant. In order to estimate the probability of the failure, a probabilistic model was established to predict the whole life-span and residual life of steam generator (SG) tubing. The failure investigated was stress corrosion cracking (SCC) after the generation of one through-wall axial crack. Two failure modes called rupture mode and leak mode based on probabilistic fracture mechanics were considered in this proposed model. It took into account the variance in tube geometry and material properties, and the variance in residual stresses and operating conditions, all of which govern the propagations of cracks. The proposed model was numerically calculated by using Monte Carlo Simulation (MCS). The plugging criteria were first verified and then the whole life-span and residual life of the SG tubing were obtained. Finally, important sensitivity analysis was also carried out to identify the most important parameters affecting the life of SG tubing. The results will be useful in developing optimum strategies for life-cycle management of the feedwater system in nuclear power plants.

Prediction of composite fatigue life under variable amplitude loading using artificial neural network trained by genetic algorithm

Science.gov (United States)

Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung

2018-04-01

Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

Predicting life-history adaptations to pollutants

Energy Technology Data Exchange (ETDEWEB)

Maltby, L. [Univ. of Sheffield (United Kingdom). Dept. of Animal and Plant Sciences

1995-12-31

Animals may adapt to pollutant stress so that individuals from polluted environments are less susceptible than those from unpolluted environments. In addition to such direct adaptations, animals may respond to pollutant stress by life-history modifications; so-called indirect adaptations. This paper will demonstrate how, by combining life-history theory and toxicological data, it is possible to predict stress-induced alterations in reproductive output and offspring size. Pollutant-induced alterations in age-specific survival in favor of adults and reductions in juvenile growth, conditions are predicted to select for reduced investment in reproduction and the allocation of this investment into fewer, larger offspring. Field observations on the freshwater crustaceans, Asellus aquaticus and Gammarus pulex, support these predictions. Females from metal-polluted sites had lower investment in reproduction and produced larger offspring than females of the same species from unpolluted sites. Moreover, interpopulation differences in reproductive biology persisted in laboratory cultures indicating that they had a genetic basis and were therefore due to adaptation rather than acclimation. The general applicability of this approach will be considered.

Service life prediction of exterior plastics vision for the future

CERN Document Server

Martin, Jon; Chapin, J

2015-01-01

This book defines the current state-of-the-art for predicting the lifetime of plastics exposed to weather and outlines future research needed to advance this important field of study. Coverage includes progress in developing new science and test methods to determine how materials respond to weather exposure. This book is ideal for researchers and professionals working in the field of service life prediction. This book also: Examines numerous consensus standards that affect commercial products allowing readers to see the future of standards related to service life prediction Provides the scientific foundation for the latest commercially viable instruments Presents groundbreaking research, including the blueprint of a new test method that will significantly shorten the service life prediction process time Covers two of the latest verified predictive models, which demonstrate realized-potential to transform the field

Recent Methodologies for Creep Deformation Analysis and Its Life Prediction

International Nuclear Information System (INIS)

Kim, Woo-Gon; Park, Jae-Young; Iung

2016-01-01

To design the high-temperature creeping materials, various creep data are needed for codification, as follows: i) stress vs. creep rupture time for base metals and weldments (average and minimum), ii) stress vs. time to 1% total strain (average), iii) stress vs. time to onset of tertiary creep (minimum), and iv) constitutive eqns. for conducting time- and temperature- dependent stress-strain (average), and v) isochronous stress-strain curves (average). Also, elevated temperature components such as those used in modern power generation plant are designed using allowable stress under creep conditions. The allowable stress is usually estimated on the basis of up to 10"5 h creep rupture strength at the operating temperature. The master curve of the “sinh” function was found to have a wider acceptance with good flexibility in the low stress ranges beyond the experimental data. The proposed multi-C method in the LM parameter revealed better life prediction than a single-C method. These improved methodologies can be utilized to accurately predict the long-term creep life or strength of Gen-IV nuclear materials which are designed for life span of 60 years

Method and apparatus to predict the remaining service life of an operating system

Science.gov (United States)

Greitzer, Frank L.; Kangas, Lars J.; Terrones, Kristine M.; Maynard, Melody A.; Pawlowski, Ronald A. , Ferryman; Thomas A.; Skorpik, James R.; Wilson, Bary W.

2008-11-25

A method and computer-based apparatus for monitoring the degradation of, predicting the remaining service life of, and/or planning maintenance for, an operating system are disclosed. Diagnostic information on degradation of the operating system is obtained through measurement of one or more performance characteristics by one or more sensors onboard and/or proximate the operating system. Though not required, it is preferred that the sensor data are validated to improve the accuracy and reliability of the service life predictions. The condition or degree of degradation of the operating system is presented to a user by way of one or more calculated, numeric degradation figures of merit that are trended against one or more independent variables using one or more mathematical techniques. Furthermore, more than one trendline and uncertainty interval may be generated for a given degradation figure of merit/independent variable data set. The trendline(s) and uncertainty interval(s) are subsequently compared to one or more degradation figure of merit thresholds to predict the remaining service life of the operating system. The present invention enables multiple mathematical approaches in determining which trendline(s) to use to provide the best estimate of the remaining service life.

Fatigue Life Prediction of Package of Suspension Automotive Under Random Vibration Based on Road Roughness

Directory of Open Access Journals (Sweden)

Kazem Reza Kashyzadeh

2015-09-01

Full Text Available The impact of a suitable suspension system for passenger comfort and vehicle steering is an obvious order and direct impact on the safety of passengers must be considered, to do so different kinds of tests must be exerted, one of these is fatigue testing which is one of the most significant ones. Another issue is the high cost in practical ways, and to cope with this issue various ways must be assessed and analyzed, one of the best and the most efficient ways is modelling and testing in virtual software environments. In the present paper, predict fatigue life of suspension component and package of automotive suspension are the main purposes. First, using MATLAB software, road roughness according to the intercity roads for constant vehicle velocity (100 Km/h has been studied. After that frequency response of components has been analysed, its critical points determined to calculate the fatigue life of the part, and the amount of critical stress obtained based on Von Misses, Tresca and Max Principle criterion for a quarter car model (passive suspension System in 206 Peugeot. Fatigue life of the vehicle components are calculated in terms of kilo-Meters in specialized fatigue software such as 116944, 92638.9, 46388.9 and 191388.9 Km respectively wheel hub, pitman arm, suspension arm and package of suspension. Finally, to prove the given results of the finite element method compared with reported results by other researchers and the results match very well with those.

Life prediction of Ni-base superalloy

Indian Academy of Sciences (India)

mean stress exponent, n, and the mean activation energy for creep were calculated from the experimental results. The accelerated creep life of the alloy was evaluated by using iso-stress parametric equations and Monkman–Grant method. Keywords. ... This alloy is age-hardenable by a fine dispersion of γ par- ticles, which ...

Shelf-life dating of shelf-stable strawberry juice based on survival analysis of consumer acceptance information.

Science.gov (United States)

Buvé, Carolien; Van Bedts, Tine; Haenen, Annelien; Kebede, Biniam; Braekers, Roel; Hendrickx, Marc; Van Loey, Ann; Grauwet, Tara

2018-07-01

Accurate shelf-life dating of food products is crucial for consumers and industries. Therefore, in this study we applied a science-based approach for shelf-life assessment, including accelerated shelf-life testing (ASLT), acceptability testing and the screening of analytical attributes for fast shelf-life predictions. Shelf-stable strawberry juice was selected as a case study. Ambient storage (20 °C) had no effect on the aroma-based acceptance of strawberry juice. The colour-based acceptability decreased during storage under ambient and accelerated (28-42 °C) conditions. The application of survival analysis showed that the colour-based shelf-life was reached in the early stages of storage (≤11 weeks) and that the shelf-life was shortened at higher temperatures. None of the selected attributes (a * and ΔE * value, anthocyanin and ascorbic acid content) is an ideal analytical marker for shelf-life predictions in the investigated temperature range (20-42 °C). Nevertheless, an overall analytical cut-off value over the whole temperature range can be selected. Colour changes of strawberry juice during storage are shelf-life limiting. Combining ASLT with acceptability testing allowed to gain faster insight into the change in colour-based acceptability and to perform shelf-life predictions relying on scientific data. An analytical marker is a convenient tool for shelf-life predictions in the context of ASLT. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Reinforcement Corrosion: Numerical Simulation and Service Life Prediction

DEFF Research Database (Denmark)

Michel, Alexander

defects and b) define the end of service life once reinforcement corrosion is initiated neglecting corrosion processes during the propagation stage. The goal of this work was to develop a framework for the service life prediction of reinforced concrete covering initiation and propagation of chloride......Modelling of deterioration processes in concrete structures plays an increasing role in the design of reinforced concrete structures. Large sums are spent every year to ensure the durability of concrete structures, especially towards reinforcement corrosion. Improved durability provides increased...... structural reliability, economical improvements in form of less need for maintenance and repair as well as increased sustainability due to an increased energy and resource efficiency. Several service life prediction models dealing with reinforcement corrosion in concrete structurescan be found...

Life history theory predicts fish assemblage response to hydrologic regimes.

Science.gov (United States)

Mims, Meryl C; Olden, Julian D

2012-01-01

The hydrologic regime is regarded as the primary driver of freshwater ecosystems, structuring the physical habitat template, providing connectivity, framing biotic interactions, and ultimately selecting for specific life histories of aquatic organisms. In the present study, we tested ecological theory predicting directional relationships between major dimensions of the flow regime and life history composition of fish assemblages in perennial free-flowing rivers throughout the continental United States. Using long-term discharge records and fish trait and survey data for 109 stream locations, we found that 11 out of 18 relationships (61%) tested between the three life history strategies (opportunistic, periodic, and equilibrium) and six hydrologic metrics (two each describing flow variability, predictability, and seasonality) were statistically significant (P history strategies, with 82% of all significant relationships observed supporting predictions from life history theory. Specifically, we found that (1) opportunistic strategists were positively related to measures of flow variability and negatively related to predictability and seasonality, (2) periodic strategists were positively related to high flow seasonality and negatively related to variability, and (3) the equilibrium strategists were negatively related to flow variability and positively related to predictability. Our study provides important empirical evidence illustrating the value of using life history theory to understand both the patterns and processes by which fish assemblage structure is shaped by adaptation to natural regimes of variability, predictability, and seasonality of critical flow events over broad biogeographic scales.

Fatigue-creep life prediction for a notched specimen of 2[1]/[4]Cr-1Mo steel at 600 C

International Nuclear Information System (INIS)

Inoue, Tatsuo; Sakane, Masao; Fukuda, Yoshio; Igari, Toshihide; Miyahara, Mitsuo; Okazaki, Masakazu

1994-01-01

This paper presents the life prediction of 2[1]/[4]Cr-1Mo notched specimens subjected to fast-fast, slow-slow and hold-time loadings at 600 C. The crack initiation lives of notched specimens were estimated based on the local stress-strain calculated by inelastic finite element analyses. For the life prediction, combinations of seven different constitutive models and five fatigue-creep damage laws were used. The applicability of the constitutive model and damage law is discussed. The constitutive models predict similar stress-strain relations at the notch root, leading to similar predicted lives. The damage model, however, has a much larger influence on the life prediction. ((orig.))

A residual life prediction model based on the generalized σ -N curved surface

OpenAIRE

Zongwen AN; Xuezong BAI; Jianxiong GAO

2016-01-01

In order to investigate change rule of the residual life of structure under random repeated load, firstly, starting from the statistic meaning of random repeated load, the joint probability density function of maximum stress and minimum stress is derived based on the characteristics of order statistic (maximum order statistic and minimum order statistic); then, based on the equation of generalized σ -N curved surface, considering the influence of load cycles number on fatigue life, a relation...

New considerations on variability of creep rupture data and life prediction

International Nuclear Information System (INIS)

Kim, Seon Jin; Jeong, Won Taek; Kong, Yu Sik

2009-01-01

This paper deals with the variability analysis of short term creep rupture test data based on the previous creep rupture tests and the possibility of the creep life prediction. From creep tests performed by constant uniaxial stresses at 600, 650 and 700 .deg. C elevated temperature, in order to investigate the variability of short-term creep rupture data, the creep curves were analyzed for normalized creep strain divided by initial strain. There are some variability in thee creep rupture data. And, the difference between general creep curves and normalized creep curves were obtained. The effects of the creep rupture time and state steady creep rate on the Weibull distribution parameters were investigated. There were good relation between normal Weibull parameters and normalized Weibull parameters. Finally, the predicted creep life were compared with the Monkman-Grant model.

New Considerations on Variability of Creep Rupture Data and Life Prediction

International Nuclear Information System (INIS)

Jung, Won Taek; Kong, Yu Sik; Kim, Seon Jin

2009-01-01

This paper deals with the variability analysis of short term creep rupture test data based on the previous creep rupture tests and the possibility of the creep life prediction. From creep tests performed by constant uniaxial stresses at 600, 650 and 700 .deg. C elevated temperature, in order to investigate the variability of short-term creep rupture data, the creep curves were analyzed for normalized creep strain divided by initial strain. There are some variability in the creep rupture data. And, the difference between general creep curves and normalized creep curves were obtained. The effects of the creep rupture time (RT) and steady state creep rate (SSCR) on the Weibull distribution parameters were investigated. There were good relation between normal Weibull parameters and normalized Weibull parameters. Finally, the predicted creep life were compared with the Monkman-Grant model

Programming Useful Life Prediction (PULP), Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements. Relying on...

Development of a clinical prediction model to calculate patient life expectancy: the measure of actuarial life expectancy (MALE).

Science.gov (United States)

Clarke, M G; Kennedy, K P; MacDonagh, R P

2009-01-01

To develop a clinical prediction model enabling the calculation of an individual patient's life expectancy (LE) and survival probability based on age, sex, and comorbidity for use in the joint decision-making process regarding medical treatment. A computer software program was developed with a team of 3 clinicians, 2 professional actuaries, and 2 professional computer programmers. This incorporated statistical spreadsheet and database access design methods. Data sources included life insurance industry actuarial rating factor tables (public and private domain), Government Actuary Department UK life tables, professional actuarial sources, and evidence-based medical literature. The main outcome measures were numerical and graphical display of comorbidity-adjusted LE; 5-, 10-, and 15-year survival probability; in addition to generic UK population LE. Nineteen medical conditions, which impacted significantly on LE in actuarial terms and were commonly encountered in clinical practice, were incorporated in the final model. Numerical and graphical representations of statistical predictions of LE and survival probability were successfully generated for patients with either no comorbidity or a combination of the 19 medical conditions included. Validation and testing, including actuarial peer review, confirmed consistency with the data sources utilized. The evidence-based actuarial data utilized in this computer program design represent a valuable resource for use in the clinical decision-making process, where an accurate objective assessment of patient LE can so often make the difference between patients being offered or denied medical and surgical treatment. Ongoing development to incorporate additional comorbidities and enable Web-based access will enhance its use further.

Patterns, Entropy, and Predictability of Human Mobility and Life

Science.gov (United States)

Qin, Shao-Meng; Verkasalo, Hannu; Mohtaschemi, Mikael; Hartonen, Tuomo; Alava, Mikko

2012-01-01

Cellular phones are now offering an ubiquitous means for scientists to observe life: how people act, move and respond to external influences. They can be utilized as measurement devices of individual persons and for groups of people of the social context and the related interactions. The picture of human life that emerges shows complexity, which is manifested in such data in properties of the spatiotemporal tracks of individuals. We extract from smartphone-based data for a set of persons important locations such as “home”, “work” and so forth over fixed length time-slots covering the days in the data-set (see also [1], [2]). This set of typical places is heavy-tailed, a power-law distribution with an exponent close to −1.7. To analyze the regularities and stochastic features present, the days are classified for each person into regular, personal patterns. To this are superimposed fluctuations for each day. This randomness is measured by “life” entropy, computed both before and after finding the clustering so as to subtract the contribution of a number of patterns. The main issue that we then address is how predictable individuals are in their mobility. The patterns and entropy are reflected in the predictability of the mobility of the life both individually and on average. We explore the simple approaches to guess the location from the typical behavior, and of exploiting the transition probabilities with time from location or activity A to B. The patterns allow an enhanced predictability, at least up to a few hours into the future from the current location. Such fixed habits are most clearly visible in the working-day length. PMID:23300542

[Prediction method of rural landscape pattern evolution based on life cycle: a case study of Jinjing Town, Hunan Province, China].

Science.gov (United States)

Ji, Xiang; Liu, Li-Ming; Li, Hong-Qing

2014-11-01

Taking Jinjing Town in Dongting Lake area as a case, this paper analyzed the evolution of rural landscape patterns by means of life cycle theory, simulated the evolution cycle curve, and calculated its evolution period, then combining CA-Markov model, a complete prediction model was built based on the rule of rural landscape change. The results showed that rural settlement and paddy landscapes of Jinjing Town would change most in 2020, with the rural settlement landscape increased to 1194.01 hm2 and paddy landscape greatly reduced to 3090.24 hm2. The quantitative and spatial prediction accuracies of the model were up to 99.3% and 96.4%, respectively, being more explicit than single CA-Markov model. The prediction model of rural landscape patterns change proposed in this paper would be helpful for rural landscape planning in future.

Fatigue crack initiation and growth life prediction with statistical consideration

International Nuclear Information System (INIS)

Kwon, J.D.; Choi, S.H.; Kwak, S.G.; Chun, K.O.

1991-01-01

Life prediction or residual life prediction of structures or machines is one of the most strongly world wide needed problems as requirement in the stage of slowly developing economy which comes after rapidly and highly developing stage. For the purpose of statistical life prediction, fatigue test was conducted under the 3 stress levels, and for each stress level, 20 specimens are used. The statistical properties of the crack growth parameter m and C in the fatigue crack growth law of da/dN = C(ΔK) m , and the relationship between m and C, and the statistical distribution pattern of fatigue crack initiation, growth and fracture lives can be obtained by experimental results

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

Science.gov (United States)

Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

2015-10-01

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley

RandomForest4Life: a Random Forest for predicting ALS disease progression.

Science.gov (United States)

Hothorn, Torsten; Jung, Hans H

2014-09-01

We describe a method for predicting disease progression in amyotrophic lateral sclerosis (ALS) patients. The method was developed as a submission to the DREAM Phil Bowen ALS Prediction Prize4Life Challenge of summer 2012. Based on repeated patient examinations over a three- month period, we used a random forest algorithm to predict future disease progression. The procedure was set up and internally evaluated using data from 1197 ALS patients. External validation by an expert jury was based on undisclosed information of an additional 625 patients; all patient data were obtained from the PRO-ACT database. In terms of prediction accuracy, the approach described here ranked third best. Our interpretation of the prediction model confirmed previous reports suggesting that past disease progression is a strong predictor of future disease progression measured on the ALS functional rating scale (ALSFRS). We also found that larger variability in initial ALSFRS scores is linked to faster future disease progression. The results reported here furthermore suggested that approaches taking the multidimensionality of the ALSFRS into account promise some potential for improved ALS disease prediction.

Nonlinear-drifted Brownian motion with multiple hidden states for remaining useful life prediction of rechargeable batteries

Science.gov (United States)

Wang, Dong; Zhao, Yang; Yang, Fangfang; Tsui, Kwok-Leung

2017-09-01

Brownian motion with adaptive drift has attracted much attention in prognostics because its first hitting time is highly relevant to remaining useful life prediction and it follows the inverse Gaussian distribution. Besides linear degradation modeling, nonlinear-drifted Brownian motion has been developed to model nonlinear degradation. Moreover, the first hitting time distribution of the nonlinear-drifted Brownian motion has been approximated by time-space transformation. In the previous studies, the drift coefficient is the only hidden state used in state space modeling of the nonlinear-drifted Brownian motion. Besides the drift coefficient, parameters of a nonlinear function used in the nonlinear-drifted Brownian motion should be treated as additional hidden states of state space modeling to make the nonlinear-drifted Brownian motion more flexible. In this paper, a prognostic method based on nonlinear-drifted Brownian motion with multiple hidden states is proposed and then it is applied to predict remaining useful life of rechargeable batteries. 26 sets of rechargeable battery degradation samples are analyzed to validate the effectiveness of the proposed prognostic method. Moreover, some comparisons with a standard particle filter based prognostic method, a spherical cubature particle filter based prognostic method and two classic Bayesian prognostic methods are conducted to highlight the superiority of the proposed prognostic method. Results show that the proposed prognostic method has lower average prediction errors than the particle filter based prognostic methods and the classic Bayesian prognostic methods for battery remaining useful life prediction.

The accuracy of dysphoric and nondepressed groups' predictions of life events.

Science.gov (United States)

Kapçi, E G; Cramer, D

1998-11-01

The phenomenon of depressive realism was examined in relation to the future prediction of positive and negative life events. A group of dysphoric (n = 20) and nondepressed (n = 38) British undergraduates participated in a prospective study lasting 3 months. Partly consistent with the depressive realism hypotheses, dysphoric participants were more realistic concerning the negative life events they would experience, but they were less realistic concerning the negative life events they would not experience. Although no difference was found for predicting the occurrence of positive life events, dysphoric participants were found to be more realistic concerning positive life events that they would not experience.

Neural Network Modeling to Predict Shelf Life of Greenhouse Lettuce

Directory of Open Access Journals (Sweden)

Wei-Chin Lin

2009-04-01

Full Text Available Greenhouse-grown butter lettuce (Lactuca sativa L. can potentially be stored for 21 days at constant 0°C. When storage temperature was increased to 5°C or 10°C, shelf life was shortened to 14 or 10 days, respectively, in our previous observations. Also, commercial shelf life of 7 to 10 days is common, due to postharvest temperature fluctuations. The objective of this study was to establish neural network (NN models to predict the remaining shelf life (RSL under fluctuating postharvest temperatures. A box of 12 - 24 lettuce heads constituted a sample unit. The end of the shelf life of each head was determined when it showed initial signs of decay or yellowing. Air temperatures inside a shipping box were recorded. Daily average temperatures in storage and averaged shelf life of each box were used as inputs, and the RSL was modeled as an output. An R2 of 0.57 could be observed when a simple NN structure was employed. Since the "future" (or remaining storage temperatures were unavailable at the time of making a prediction, a second NN model was introduced to accommodate a range of future temperatures and associated shelf lives. Using such 2-stage NN models, an R2 of 0.61 could be achieved for predicting RSL. This study indicated that NN modeling has potential for cold chain quality control and shelf life prediction.

Fatigue-creep life prediction of 21/4Cr-1Mo steel under combined tension-torsion at 600degC

International Nuclear Information System (INIS)

Inoue, Tatsuo; Kishi, Shigeru; Koto, Hiroyuki; Takahashi, Yukio.

1991-01-01

From the above discussion on the comparison between predicted and experimental lives in this project, the followings are suggested. The Mises equivalent stress is not a successful parameter to describe the multiaxial fatigue-creep damage, while the Huddleston's stress gives better prediction. SRP, Ostergren method and Lemaitre-Plumtree-Chaboche method give comparatively good estimation of life, though these methods predict more or less the greater damage than the experiment under pure torsion and in-phase cycling, and cannot predict the life under out-of-phase cycling. The reason is considered to be owing to employment of the Mises equivalent strain, which might be possibly improved by using more sophisticated equivalent strain such as the strain defined on the Γ-plane. The life prediction based on the analytical stress-strain relation gives almost similar results as that based on the experimental data. It suggests the applicability of the inelastic constitutive moeles to give the fundamental data for life prediction. The subcommittee wishes to express her gratitude to the head Committee on High Temperature Strength, JSMS, for supporting the project, and acknowledgement is due to the Ministry of Education and Culture for providing Grant-in-Aid for Co-operative Research A (No. 61302036 and 01302026). (author)

Risk Factors Analysis and Death Prediction in Some Life-Threatening Ailments Using Chi-Square Case-Based Reasoning (χ2 CBR) Model.

Science.gov (United States)

Adeniyi, D A; Wei, Z; Yang, Y

2018-01-30

A wealth of data are available within the health care system, however, effective analysis tools for exploring the hidden patterns in these datasets are lacking. To alleviate this limitation, this paper proposes a simple but promising hybrid predictive model by suitably combining the Chi-square distance measurement with case-based reasoning technique. The study presents the realization of an automated risk calculator and death prediction in some life-threatening ailments using Chi-square case-based reasoning (χ 2 CBR) model. The proposed predictive engine is capable of reducing runtime and speeds up execution process through the use of critical χ 2 distribution value. This work also showcases the development of a novel feature selection method referred to as frequent item based rule (FIBR) method. This FIBR method is used for selecting the best feature for the proposed χ 2 CBR model at the preprocessing stage of the predictive procedures. The implementation of the proposed risk calculator is achieved through the use of an in-house developed PHP program experimented with XAMP/Apache HTTP server as hosting server. The process of data acquisition and case-based development is implemented using the MySQL application. Performance comparison between our system, the NBY, the ED-KNN, the ANN, the SVM, the Random Forest and the traditional CBR techniques shows that the quality of predictions produced by our system outperformed the baseline methods studied. The result of our experiment shows that the precision rate and predictive quality of our system in most cases are equal to or greater than 70%. Our result also shows that the proposed system executes faster than the baseline methods studied. Therefore, the proposed risk calculator is capable of providing useful, consistent, faster, accurate and efficient risk level prediction to both the patients and the physicians at any time, online and on a real-time basis.

Fatigue mechanics - An assessment of a unified approach to life prediction

International Nuclear Information System (INIS)

Newman, J.C. Jr.; Phillips, E.P.; Swain, M.H.; Everett, R.A. Jr.

1992-01-01

Consideration is given to the development of a total-life prediction methodology for aerospace structures based solely on crack propagation from a microstructural defect at stress concentrations. Crack-growth lives were calculated for a given loading condition by integrating the crack-growth-rate-against-delta K relationships for crack growth from a microstructural defect size to failure. Both small- and large-crack growth rate data were used. The assessment was based on data on 2024-T3 aluminum alloy, 2090-T8E41 aluminum-lithium alloy, annealed Ti-6Al-4V titanium alloy, and high-strength 4340 steel under either constant-amplitude or spectrum loading. Good agreement was found between fatigue lives measured on notched specimens with those computed from the total-life analysis. 29 refs

Fatigue properties of JIS H3300 C1220 copper for strain life prediction

Science.gov (United States)

Harun, Muhammad Faiz; Mohammad, Roslina

2018-05-01

The existing methods for estimating strain life parameters are dependent on the material's monotonic tensile properties. However, a few of these methods yield quite complicated expressions for calculating fatigue parameters, and are specific to certain groups of materials only. The Universal Slopes method, Modified Universal Slopes method, Uniform Material Law, the Hardness method, and Medians method are a few existing methods for predicting strain-life fatigue based on monotonic tensile material properties and hardness of material. In the present study, nine methods for estimating fatigue life and properties are applied on JIS H3300 C1220 copper to determine the best methods for strain life estimation of this ductile material. Experimental strain-life curves are compared to estimations obtained using each method. Muralidharan-Manson's Modified Universal Slopes method and Bäumel-Seeger's method for unalloyed and low-alloy steels are found to yield batter accuracy in estimating fatigue life with a deviation of less than 25%. However, the prediction of both methods only yield much better accuracy for a cycle of less than 1000 or for strain amplitudes of more than 1% and less than 6%. Manson's Original Universal Slopes method and Ong's Modified Four-Point Correlation method are found to predict the strain-life fatigue of copper with better accuracy for a high number of cycles of strain amplitudes of less than 1%. The differences between mechanical behavior during monotonic and cyclic loading and the complexity in deciding the coefficient in an equation are probably the reason for the lack of a reliable method for estimating fatigue behavior using the monotonic properties of a group of materials. It is therefore suggested that a differential approach and new expressions be developed to estimate the strain-life fatigue parameters for ductile materials such as copper.

Statistical characterization of pitting corrosion process and life prediction

International Nuclear Information System (INIS)

Sheikh, A.K.; Younas, M.

1995-01-01

In order to prevent corrosion failures of machines and structures, it is desirable to know in advance when the corrosion damage will take place, and appropriate measures are needed to mitigate the damage. The corrosion predictions are needed both at development as well as operational stage of machines and structures. There are several forms of corrosion process through which varying degrees of damage can occur. Under certain conditions these corrosion processes at alone and in other set of conditions, several of these processes may occur simultaneously. For a certain type of machine elements and structures, such as gears, bearing, tubes, pipelines, containers, storage tanks etc., are particularly prone to pitting corrosion which is an insidious form of corrosion. The corrosion predictions are usually based on experimental results obtained from test coupons and/or field experiences of similar machines or parts of a structure. Considerable scatter is observed in corrosion processes. The probabilities nature and kinetics of pitting process makes in necessary to use statistical method to forecast the residual life of machine of structures. The focus of this paper is to characterization pitting as a time-dependent random process, and using this characterization the prediction of life to reach a critical level of pitting damage can be made. Using several data sets from literature on pitting corrosion, the extreme value modeling of pitting corrosion process, the evolution of the extreme value distribution in time, and their relationship to the reliability of machines and structure are explained. (author)

Prediction of pavement remaining service life based on repetition of load and permanent deformation

Science.gov (United States)

Usman, R. S.; Setyawan, A.; Suprapto, M.

2018-03-01

One of the methods which was applied in the assessment of flexible pavement performance was mechanistic method assuming structures of road pavement to become multi-layer structure for flexible pavement, that the vehicle load working on the pavement layer under repetition with power failure worth 1 (one) unit which was assumed as evenly distributed static load, and therefore the pavement material would provide response in the form of stress, strain, and deflection. This is closely related in order to assess the structure of flexible pavement and to predict the remaining service life on the roads of Pulau Indah sta 0 + 000 to sta. 0 + 845 in Kota Kupang, Nusa Tenggara Timur. The performance appraisal indicator which was used was fatigue cracking happening bottom of the asphalt layer and permanent deformation (rutting) on the surface of subgrade. The strain estimate on the flexible pavement layer structure needs carefulness and high accuracy and therefore a software like KENPAVE which produces horizontal tensile strain of 8,802E-05 and vertical compressive strain of 2,642E-04 was used. By applying equation of The Asphalt Instituteit was obtained repetition of permit load when reaching fatigue cracking (Nf) was 16.071.516 ESAL and permanent deformation (rutting) was 14.703.867 ESAL and also it was predicted the remaining service life of pavement applied the equation of AASTHO 1993 by considering Traffic Multiplier factor (TM 1.8, TM 1.9 and TM 2.0) obtained the remaining life service due to fatigue of 5.51% in the year of 13th (TM 1.8), 7.95% in the year of12th (TM 1.9) and 3.11% (TM 2.0) in the year of 12th, also the remaining service life due to rutting of 4.69% in the year of 12th(TM 1.8), 7.79% in the year of 11th (TM 1.9), and 2.94 in the year of 11th (TM 2.0).

WHAT PREDICTS A SUCCESSFUL LIFE? A LIFE-COURSE MODEL OF WELL-BEING*

Science.gov (United States)

Layard, Richard; Clark, Andrew E.; Cornaglia, Francesca; Powdthavee, Nattavudh; Vernoit, James

2014-01-01

Policy-makers who care about well-being need a recursive model of how adult life-satisfaction is predicted by childhood influences, acting both directly and (indirectly) through adult circumstances. We estimate such a model using the British Cohort Study (1970). We show that the most powerful childhood predictor of adult life-satisfaction is the child’s emotional health, followed by the child’s conduct. The least powerful predictor is the child’s intellectual development. This may have implications for educational policy. Among adult circumstances, family income accounts for only 0.5% of the variance of life-satisfaction. Mental and physical health are much more important. PMID:25422527

Shelf life prediction of radiation sterilized polymeric materials

International Nuclear Information System (INIS)

Sandford, Craig; Woo, Lecon

1988-01-01

The functional properties of many polymers employed in medical disposables are unaffected by sterilizing doses of ionizing radiation. However, some materials (PVC, polypropylene, cellulosics, etc.) undergo undesirable changes which continue to occur for the shelf life of the product. In many cases, conventional accelerated aging techniques do not accurately predict the real time properties of the materials. As real time aging is not generally practical, it has become necessary to develop accelerated aging techniques which can predict the functional properties of a material for the shelf life of the product. This presentation will address issues involved in developing these tests. Real time physical property data is compared to data generated by various acceleration methods. (author)

Fracture Mechanics Prediction of Fatigue Life of Aluminum Highway Bridges

DEFF Research Database (Denmark)

Rom, Søren; Agerskov, Henning

2015-01-01

Fracture mechanics prediction of the fatigue life of aluminum highway bridges under random loading is studied. The fatigue life of welded joints has been determined from fracture mechanics analyses and the results obtained have been compared with results from experimental investigations. The fati......Fracture mechanics prediction of the fatigue life of aluminum highway bridges under random loading is studied. The fatigue life of welded joints has been determined from fracture mechanics analyses and the results obtained have been compared with results from experimental investigations...... against fatigue in aluminum bridges, may give results which are unconservative. Furthermore, it was in both investigations found that the validity of the results obtained from Miner's rule will depend on the distribution of the load history in tension and compression....

Predicting Bullying: Exploring the Contributions of Childhood Negative Life Experiences in Predicting Adolescent Bullying Behavior.

Science.gov (United States)

Connell, Nadine M; Morris, Robert G; Piquero, Alex R

2016-07-01

Although there has been much interest in research on aggression and in particular bullying, a relatively less charted area of research has centered on articulating a better understanding of the mechanisms and processes by which persons are at increased risk for bullying. Furthermore, those studies that have investigated the linkages between childhood experiences and bullying perpetration have been limited with respect to definitional and operational issues, reliance on cross-sectional data, and the lack of assessing competing explanations of bullying perpetration. Using five waves of data from a community-based longitudinal sample of children followed through age 18 (N = 763), the current study examines the extent to which childhood negative life events in a variety of domains predict adolescent bullying. Results show that early childhood experiences, particularly those within the family and school domains, may alter life trajectories and can act as predictors for later adolescent bullying, thereby underscoring the potential importance that relatively minor experiences can have over the long term. Implications for future research based on these analyses are examined. © The Author(s) 2015.

International Space Station Bacteria Filter Element Post-Flight Testing and Service Life Prediction

Science.gov (United States)

Perry, J. L.; von Jouanne, R. G.; Turner, E. H.

2003-01-01

The International Space Station uses high efficiency particulate air (HEPA) filters to remove particulate matter from the cabin atmosphere. Known as Bacteria Filter Elements (BFEs), there are 13 elements deployed on board the ISS's U.S. Segment. The pre-flight service life prediction of 1 year for the BFEs is based upon performance engineering analysis of data collected during developmental testing that used a synthetic dust challenge. While this challenge is considered reasonable and conservative from a design perspective, an understanding of the actual filter loading is required to best manage the critical ISS Program resources. Thus testing was conducted on BFEs returned from the ISS to refine the service life prediction. Results from this testing and implications to ISS resource management are discussed. Recommendations for realizing significant savings to the ISS Program are presented.

The Fatigue Life Prediction of Train Wheel Rims Containing Spherical Inclusions

Science.gov (United States)

Li, Yajie; Chen, Huanguo; Cai, Li; Chen, Pei; Qian, Jiacheng; Wu, Jianwei

2018-03-01

It is a common phenomenon that fatigue crack initiation occurs frequently in the inclusions of wheel rims. Research on the fatigue life of wheel rims with spherical inclusions is of great significance on the reliability of wheels. To find the danger point and working condition of a wheel, the stress state of the wheel rim with spherical inclusions was analyzed using the finite element method. Results revealed that curve conditions are dangerous. The critical plane method, based on the cumulative fatigue damage theory, was used to predict the fatigue life of the wheel rim and whether it contained spherical inclusions or not under curve conditions. It was found that the fatigue life of the wheel rim is significantly shorter when the wheel rim contains spherical inclusions. Analysis of the results can provide a theoretical basis and technical support for train operations and maintenance.

Understanding, Predicting, and Preventing Life Changing and Life Threatening Health Changes among Aging Veterans and Civilians with Spinal Cord Injury

Science.gov (United States)

2017-10-01

AWARD NUMBER: W81XWH-16-1-0629 TITLE: Understanding, Predicting, and Preventing Life -Changing and Life -Threatening Health Changes among Aging...Annual 3. DATES COVERED 30 Sep 2016 - 29 Sep 2017 4. TITLE AND SUBTITLE Understanding, Predicting, and Preventing Life -Changing and Life ... hope of preventing them. Our purpose is to better understand the how and why of the development of negative health spirals and how they may best be

Prediction method for cavitation erosion based on measurement of bubble collapse impact loads

International Nuclear Information System (INIS)

Hattori, S; Hirose, T; Sugiyama, K

2009-01-01

The prediction of cavitation erosion rates is important in order to evaluate the exact life of components. The measurement of impact loads in bubble collapses helps to predict the life under cavitation erosion. In this study, we carried out erosion tests and the measurements of impact loads in bubble collapses with a vibratory apparatus. We evaluated the incubation period based on a cumulative damage rule by measuring the impact loads of cavitation acting on the specimen surface and by using the 'constant impact load - number of impact loads curve' similar to the modified Miner's rule which is employed for fatigue life prediction. We found that the parameter Σ(F i α xn i ) (F i : impact load, n i : number of impacts and α: constant) is suitable for the evaluation of the erosion life. Moreover, we propose a new method that can predict the incubation period under various cavitation conditions.

Ratcheting and low cycle fatigue behavior of SA333 steel and their life prediction

International Nuclear Information System (INIS)

Paul, Surajit Kumar; Sivaprasad, S.; Dhar, S.; Tarafder, S.

2010-01-01

Ratcheting and low cycle fatigue (LCF) experiments have been conducted at 25 o C temperature in laboratory environment under different loading conditions. SA333 steel exhibits cyclic hardening throughout its life during LCF. It is found that ratcheting strain increases with both increasing mean stress and stress amplitude. It has also been noticed that plastic strain amplitude and plastic strain energy decrease with increase in mean stress at constant stress amplitude. Ratcheting and LCF life in the range of 10 2 -10 5 cycles have been predicted with the help of a mean stress-based fatigue lifing equation.

Prediction of the Service Life of a Reinforced Concrete Column under Chloride Environment

Directory of Open Access Journals (Sweden)

Mohammad K. Alkam

2015-01-01

Full Text Available In the present investigation, service life of a reinforced concrete column exposed to chloride environment has been predicted. This study has been based on numerical simulation of chloride ion diffusion in a concrete column during its anticipated life span. The simulation process has included the concrete cover replacement whenever chloride ion concentration has reached the critical threshold value at the reinforcement surface. Repair scheduling of the concrete column under consideration has been discussed. Effects of the concrete cover thickness and the water cement ratio on the service life of the concrete column at hand have been presented. A new approach for arranging locations of reinforcement steel bars has been introduced. This approach is intended to prolong the service life of the concrete column under consideration against chloride induced corrosion.

Creep-fatigue life prediction method using Diercks equation for Cr-Mo steel

International Nuclear Information System (INIS)

Sonoya, Keiji; Nonaka, Isamu; Kitagawa, Masaki

1990-01-01

For dealing with the situation that creep-fatigue life properties of materials do not exist, a development of the simple method to predict creep-fatigue life properties is necessary. A method to predict the creep-fatigue life properties of Cr-Mo steels is proposed on the basis of D. Diercks equation which correlates the creep-fatigue lifes of SUS 304 steels under various temperatures, strain ranges, strain rates and hold times. The accuracy of the proposed method was compared with that of the existing methods. The following results were obtained. (1) Fatigue strength and creep rupture strength of Cr-Mo steel are different from those of SUS 304 steel. Therefore in order to apply Diercks equation to creep-fatigue prediction for Cr-Mo steel, the difference of fatigue strength was found to be corrected by fatigue life ratio of both steels and the difference of creep rupture strength was found to be corrected by the equivalent temperature corresponding to equal strength of both steels. (2) Creep-fatigue life can be predicted by the modified Diercks equation within a factor of 2 which is nearly as precise as the accuracy of strain range partitioning method. Required test and analysis procedure of this method are not so complicated as strain range partitioning method. (author)

Novel Approach for Lithium-Ion Battery On-Line Remaining Useful Life Prediction Based on Permutation Entropy

Directory of Open Access Journals (Sweden)

Luping Chen

2018-04-01

Full Text Available The degradation of lithium-ion battery often leads to electrical system failure. Battery remaining useful life (RUL prediction can effectively prevent this failure. Battery capacity is usually utilized as health indicator (HI for RUL prediction. However, battery capacity is often estimated on-line and it is difficult to be obtained by monitoring on-line parameters. Therefore, there is a great need to find a simple and on-line prediction method to solve this issue. In this paper, as a novel HI, permutation entropy (PE is extracted from the discharge voltage curve for analyzing battery degradation. Then the similarity between PE and battery capacity are judged by Pearson and Spearman correlation analyses. Experiment results illustrate the effectiveness and excellent similar performance of the novel HI for battery fading indication. Furthermore, we propose a hybrid approach combining Variational mode decomposition (VMD denoising technique, autoregressive integrated moving average (ARIMA, and GM(1,1 models for RUL prediction. Experiment results illustrate the accuracy of the proposed approach for lithium-ion battery on-line RUL prediction.

Predicting the creep life and failure mode of low-alloy steel weldments

Energy Technology Data Exchange (ETDEWEB)

Brear, J M; Middleton, C J; Aplin, P F [ERA Technology Ltd., Leatherhead (United Kingdom)

1999-12-31

This presentation reviews and consolidates experience gained through a number of research projects and practical plant assessments in predicting both the life and the likely failure mode and location in low alloy steel weldments. The approach adopted begins with the recognition that the relative strength difference between the microstructural regions is a key factor controlling both life and failure location. Practical methods based on hardness measurement and adaptable to differing weld geometries are presented and evidence for correlations between hardness ratio, damage accumulation and strain development is discussed. Predictor diagrams relating weld life and failure location to the service conditions and the hardness of the individual microstructural constituents are suggested and comments are given on the implications for identifying the circumstances in which Type IV cracking is to be expected. (orig.) 6 refs.

Predicting the creep life and failure mode of low-alloy steel weldments

Energy Technology Data Exchange (ETDEWEB)

Brear, J.M.; Middleton, C.J.; Aplin, P.F. [ERA Technology Ltd., Leatherhead (United Kingdom)

1998-12-31

This presentation reviews and consolidates experience gained through a number of research projects and practical plant assessments in predicting both the life and the likely failure mode and location in low alloy steel weldments. The approach adopted begins with the recognition that the relative strength difference between the microstructural regions is a key factor controlling both life and failure location. Practical methods based on hardness measurement and adaptable to differing weld geometries are presented and evidence for correlations between hardness ratio, damage accumulation and strain development is discussed. Predictor diagrams relating weld life and failure location to the service conditions and the hardness of the individual microstructural constituents are suggested and comments are given on the implications for identifying the circumstances in which Type IV cracking is to be expected. (orig.) 6 refs.

LCF life prediction for waspaloy in the creep-fatigue interaction regime

International Nuclear Information System (INIS)

Yeom, Jong Taek; Park, Nho Kwang

2001-01-01

This paper describes the empirical rule of strain rate modified linear accumulation of creep damage(SRM rule) for Low-Cycle Fatigue(LCF) life prediction of Waspaloy in the creep-fatigue interaction regime and Chaboche type unified viscoplastic model predicting the stress-strain response in various cyclic loading conditions. The comparison of the experimental data and the predictions for strain controlled LCF tests carried out for various strain ranges at 600 .deg. C and 650 .deg. C was made. Chaboche type unified viscoplastic model described efficiently the inelastic deformation behavior during LCF tests. Crack-initiation lifting method to predict the material life was investigated with Strain Rate Modification(SRM) rule. The application of SRM rule to LCF tests on Waspaloy indicated a good agreement between measured and predicted cycles to failure

Life prediction and mechanical reliability of NT551 silicon nitride

Science.gov (United States)

Andrews, Mark Jay

The inert strength and fatigue performance of a diesel engine exhaust valve made from silicon nitride (Si3N4) ceramic were assessed. The Si3N4 characterized in this study was manufactured by Saint Gobain/Norton Industrial Ceramics and was designated as NT551. The evaluation was made utilizing a probabilistic life prediction algorithm that combined censored test specimen strength data with a Weibull distribution function and the stress field of the ceramic valve obtained from finite element analysis. The major assumptions of the life prediction algorithm are that the bulk ceramic material is isotropic and homogeneous and that the strength-limiting flaws are uniformly distributed. The results from mechanical testing indicated that NT551 was not a homogeneous ceramic and that its strength were functions of temperature, loading rate, and machining orientation. Fractographic analysis identified four different failure modes; 2 were identified as inhomogeneities that were located throughout the bulk of NT551 and were due to processing operations. The fractographic analysis concluded that the strength degradation of NT551 observed from the temperature and loading rate test parameters was due to a change of state that occurred in its secondary phase. Pristine and engine-tested valves made from NT551 were loaded to failure and the inert strengths were obtained. Fractographic analysis of the valves identified the same four failure mechanisms as found with the test specimens. The fatigue performance and the inert strength of the Si3N 4 valves were assessed from censored and uncensored test specimen strength data, respectively. The inert strength failure probability predictions were compared to the inert strength of the Si3N4 valves. The inert strength failure probability predictions were more conservative than the strength of the valves. The lack of correlation between predicted and actual valve strength was due to the nonuniform distribution of inhomogeneities present in NT

Early Adolescent Affect Predicts Later Life Outcomes.

Science.gov (United States)

Kansky, Jessica; Allen, Joseph P; Diener, Ed

2016-07-01

Subjective well-being as a predictor for later behavior and health has highlighted its relationship to health, work performance, and social relationships. However, the majority of such studies neglect the developmental nature of well-being in contributing to important changes across the transition to adulthood. To examine the potential role of subjective well-being as a long-term predictor of critical life outcomes, we examined indicators of positive and negative affect at age 14 as predictors of relationship, adjustment, self-worth, and career outcomes a decade later at ages 23 to 25, controlling for family income and gender. We utilised multi-informant methods including reports from the target participant, close friends, and romantic partners in a demographically diverse community sample of 184 participants. Early adolescent positive affect predicted fewer relationship problems (less self-reported and partner-reported conflict, and greater friendship attachment as rated by close peers) and healthy adjustment to adulthood (lower levels of depression, anxiety, and loneliness). It also predicted positive work functioning (higher levels of career satisfaction and job competence) and increased self-worth. Negative affect did not significantly predict any of these important life outcomes. In addition to predicting desirable mean levels of later outcomes, early positive affect predicted beneficial changes across time in many outcomes. The findings extend early research on the beneficial outcomes of subjective well-being by having an earlier assessment of well-being, including informant reports in measuring a large variety of outcome variables, and by extending the findings to a lower socioeconomic group of a diverse and younger sample. The results highlight the importance of considering positive affect as an important component of subjective well-being distinct from negative affect. © 2016 The International Association of Applied Psychology.

A case study of remaining storage life prediction using stochastic filtering with the influence of condition monitoring

International Nuclear Information System (INIS)

Wang, Zhaoqiang; Hu, Changhua; Wang, Wenbin; Zhou, Zhijie; Si, Xiaosheng

2014-01-01

Some systems may spend most of their time in storage, but once needed, must be fully functional. Slow degradation occurs when the system is in storage, so to ensure the functionality of these systems, condition monitoring is usually conducted periodically to check the condition of the system. However, taking the condition monitoring data may require putting the system under real testing situation which may accelerate the degradation, and therefore, shorten the storage life of the system. This paper presents a case study of condition-based remaining storage life prediction for gyros in the inertial navigation system on the basis of the condition monitoring data and the influence of the condition monitoring data taking process. A stochastic-filtering-based degradation model is developed to incorporate both into the prediction of the remaining storage life distribution. This makes the predicted remaining storage life depend on not only the condition monitoring data but also the testing process of taking the condition monitoring data, which the existing prognostic techniques and algorithms did not consider. The presented model is fitted to the real condition monitoring data of gyros testing using the maximum likelihood estimation method for parameter estimation. Comparisons are made with the model without considering the process of taking the condition monitoring data, and the results clearly demonstrate the superiority of the newly proposed model

Fatigue Life Prediction of Self-Piercing Rivet Joints Between Magnesium and Aluminum Alloys

Directory of Open Access Journals (Sweden)

Kang Hong-Tae

2018-01-01

Full Text Available Various light materials including aluminum alloys and magnesium alloys are being used to reduce the weight of vehicle structures. Joining of dissimilar materials is always a challenging task to construct a solid structure. Self-piercing rivet (SPR joint is one of various joining methods for dissimilar materials. Front shock tower structures were constructed with magnesium alloy (AM60 joined to aluminum alloy (Al6082 by SPR joints. To evaluate the durability performance of the SPR joints in the structures, fatigue tests of the front shock tower structures were conducted with constant amplitude loadings. Furthermore, this study investigated fatigue life prediction method of SPR joints and compared the fatigue life prediction results with that of experimental results. For fatigue life prediction of the SPR joints in the front shock tower structures, lap-shear and cross-tension specimens of SPR joint were constructed and tested to characterize the fatigue properties of the SPR joint. Then, the SPR joint was represented with area contact method (ACM in finite element (FE models. The load-life curves of the lap-shear and cross-tension specimens were converted to a structural stress-life (S-N curve of the SPR joints. The S-N curve was used to predict fatigue life of SPR joints in the front shock tower structures. The test results and the prediction results were well correlated.

Half-life predictions for decay modes of superheavy nuclei

International Nuclear Information System (INIS)

Duarte, S.B.; Tavares, O.A.P.; Goncalves, M.; Rodriguez, O.; Guzman, F.; Barbosa, T.N.; Garcia, F.; Dimarco, A.

2004-09-01

We applied the Effective Liquid Drop Model (ELDM) to predict the alpha-decay, cluster emission and cold fission half-life-values of nuclei in the region of Superheavy Elements (SHE). The present calculations have been made in the region of the ZN-plane defined by 155 <=N <=220 and 110<=Z<=135. Shell effects are included via the Q-value of the corresponding decay case. We report the results of a systematic calculation of the half-life for the three nuclear decay modes in a region of the ZN-plane where superheavy elements are expected to be found. Results have shown that, among the decay modes investigated here, the alpha decay is the dominant one. i.e, the decay mode of smallest half-lives. Half-life predictions for alpha decay, cluster emission and cold fission for the isotopic family of the most recent SHE detected of Z=115 and for the isotopic family of the already consolidated SHE of Z=111 are presented. (author)

A New Approach to Predict the Fish Fillet Shelf-Life in Presence of Natural Preservative Agents.

Science.gov (United States)

Giuffrida, Alessandro; Giarratana, Filippo; Valenti, Davide; Muscolino, Daniele; Parisi, Roberta; Parco, Alessio; Marotta, Stefania; Ziino, Graziella; Panebianco, Antonio

2017-04-13

Three data sets concerning the behaviour of spoilage flora of fillets treated with natural preservative substances (NPS) were used to construct a new kind of mathematical predictive model. This model, unlike other ones, allows expressing the antibacterial effect of the NPS separately from the prediction of the growth rate. This approach, based on the introduction of a parameter into the predictive primary model, produced a good fitting of observed data and allowed characterising quantitatively the increase of shelf-life of fillets.

Prediction of inelastic behavior and creep-fatigue life of perforated plates

International Nuclear Information System (INIS)

Igari, Toshihide; Yamauchi, Masafumi; Nomura, Shinichi.

1992-01-01

Prediction methods of macroscopic and local stress-strain behaviors of perforated plates in plastic and creep regime are proposed in this paper, and are applied to the creep-fatigue life prediction of perforated plates. Both equivalent-solid-plate properties corresponding to the macroscopic behavior and the stress-strain concentration around a hole were obtained by assuming the analogy between plasticity and creep and also by extending the authors' proposal in creep condition. The perforated plates which were made of Hastelloy XR were subjected to the strain-controlled cyclic test at 950degC in air in order to experimentally obtain the macroscopic behavior such as the cyclic stress-strain curve and creep-fatigue life around a hole. The results obtained are summarized as follows. (1) The macroscopic behavior of perforated plates including cyclic stress-strain behavior and relaxation is predictable by using the proposed method in this paper. (2) The creep-fatigue life around a hole can be predicted by using the proposed method for stress-strain concentration around a hole. (author)

A new hybrid method for the prediction of the remaining useful life of a lithium-ion battery

International Nuclear Information System (INIS)

Chang, Yang; Fang, Huajing; Zhang, Yong

2017-01-01

Highlights: •The proposed prognostic method can make full use of historical information. •The method of obtaining historical error data is discussed in detail. •Comparative experiments based on data-driven and model-based methods are performed. •Battery working with different discharging currents is considered. -- Abstract: The lithium-ion battery has become the main power source of many electronic devices, it is necessary to know its state-of-health and remaining useful life to ensure the reliability of electronic device. In this paper, a novel hybrid method with the thought of error-correction is proposed to predict the remaining useful life of lithium-ion battery, which fuses the algorithms of unscented Kalman filter, complete ensemble empirical mode decomposition (CEEMD) and relevance vector machine. Firstly, the unscented Kalman filter algorithm is adopted to obtain a prognostic result based on an estimated model and produce a raw error series. Secondly, a new error series is constructed by analyzing the decomposition results of the raw error series obtained by CEEMD method. Finally, the new error series is utilized by relevance vector machine regression model to predict the prognostic error which is adopted to correct the prognostic result obtained by unscented Kalman filter. Remaining useful life prediction experiments for batteries with different rated capacities and discharging currents are performed to show the high reliability of the proposed hybrid method.

The Role of Big Five Personality Factors and Defense Mechanisms in Predicting Quality of Life in Sexually Dysfunctional Female Patients

Directory of Open Access Journals (Sweden)

S. salary

2015-06-01

Full Text Available Sexual dysfunction can lead to behavioral problems and reduction in a person's quality of life. In 50 % of patients with personality disorders, there is also sexual dysfunction. Psychoanalysis approach attributes the cause of sexual dysfunction to a kind of fundamental anxiety as well as the use of immature mechanisms in these patients. The purpose of this study was to investigate the role of big five personality traits and defensive mechanisms in predicting these patients' quality of life. Statistical sample of this research included 80 women attending sexual health and family clinics of Shahed University using accessible sampling during 2010 and 2011. These subjects were given the Neo Personality Inventory Traits, Defensive Mechanisms, and the World Health organization Quality of Life Questionnaires to answer. The findings showed that personality traits could predict the quality of life in woman with sexual dysfunction. Moreover, among those five personality traits, neuroticism (:./24 P=./04 and conscientiousness(:./31 P=./03 were able to predict the quality of life while predictability rate of both factors was 37% of variance on the whole (p=0/05. Based on regression analysis, there was a significant relationship between the quality of life and defensive mechanisms so that using more mature defensive mechanisms (:./37 P=./006 and immature defensive mechanisms (:-./31 P= ./02 could significantly predict quality of life (p=0/0001. Also, neurotic defensive mechanisms were not significant predictors of these women' quality of life. (;./04 P=./78.

Methodology for formulating predictions of stress corrosion cracking life

International Nuclear Information System (INIS)

Yamauchi, Kiyoshi; Hattori, Shigeo; Shindo, Takenori; Kuniya, Jiro

1994-01-01

This paper presents a methodology for formulating predictions to evaluate the stress corrosion cracking (SCC) potential of each light-water reactor component, where an index is introduced as a life index or F index. The index denotes the SCC time ratio of a given SCC system to be evaluated against a reference SCC system. The life index is expressed by the products of several subdivided life indexes, which correspond to each SCC influencing factor. Each subdivided life index is constructed as a function containing the influencing factor variable, obtained by analyzing experimental SCC life data. The methodology was termed the subdivided factor method. Application of the life index to SCC life data and field data showed that it was effective for evaluating the SCC potential, i.e. the SCC life. Accordingly, the proposed methodology can potentially describe a phenomenon expressed by a function which consists of the variables of several influencing factors whether there are formulae which unite as a physical model or not. ((orig.))

Service life prediction and fibre reinforced cementitious composites

DEFF Research Database (Denmark)

Stoklund Larsen, E.

The present Ph.D.thesis addresses the service life concept on the fibre reinforced cementitious composites. The advantages and problems of adding fibre to a cementitious matrix and the influence on service life are described. In SBI Report 221, Service life prediction and cementitious somposites......, the factors affecting the pure cementitious composite are described. Different sizes and types of fibre reinforced crmentitious composites have been chosen to illustrate different ageing and deterioration mechanisms. Some ageing mechanisms can be accelerated and others cannot which is demonstrated in a test...... programme. Moisture, micro structural and mechanical properties were measured before, during and after ageing, with the purpose of giving a detailed "picture" of the materials during ageing....

Predicting employment status and subjective quality of life in patients with schizophrenia

Directory of Open Access Journals (Sweden)

Haruo Fujino

2016-03-01

Full Text Available Although impaired social functioning, particularly poor employment status, is a cardinal feature of patients with schizophrenia and leads to decreased quality of life (QOL, few studies have addressed the relationship between these two clinical issues. The aim of this study was to determine whether employment status predicts subjective QOL and to evaluate a model in which functional capacity mediates the relationship between general cognitive performance and employment status. Ninety-three patients with schizophrenia were administered a comprehensive battery of cognitive tests, the UCSD Performance-based Skills Assessment-Brief version (UPSA-B, the Social Functioning Scale (SFS, and the Subjective Quality of Life Scale (SQLS. First, we evaluated a model for predicting the employment/occupation subscale score of the SFS using path analysis, and the model fitted well (χ2 (4 = 3.6, p = 0.46; CFI = 1.0; RMSEA < 0.001, with 90% CIs: 0–0.152. Employment status was predicted by negative symptoms and functional capacity, which was in turn predicted by general cognitive performance. Second, we added subjective QOL to this model. In a final path model, QOL was predicted by negative symptoms and employment status. This model also satisfied good fit criteria (χ2 (7 = 10.3, p = 0.17; CFI = 0.987; RMSEA = 0.072, with 90% CIs: 0–0.159. The UPSA-B and SFS scores were moderately correlated with most measures of cognitive performance. These results support the notion that better employment status enhances subjective QOL in patients with schizophrenia.

Personality predicts recurrence of late-life depression.

Science.gov (United States)

Steunenberg, Bas; Beekman, Aartjan T F; Deeg, Dorly J H; Kerkhof, Ad J F M

2010-06-01

To examine the association of personality with recurrence of depression in later life. A subsample of 91 subjects from the Longitudinal Aging Study Amsterdam (LASA; baseline sample size n=3107; aged > or = 55 years) depressed at baseline, who had recovered in the course of three years (first follow-up cycle) was identified. 41 (45%) respondents experienced a recurrence during the subsequent six years. The influences of personality and late life stress (demographic factors, health and social factors) on recurrence were investigated prospectively. Recurrence of depression was associated with a high level of neuroticism and low level of mastery, residual depressive symptoms at time of recovery, female gender, pain complaints and feelings of loneliness. In multivariable analysis entering all predictors significant in single variable analysis, residual depressive symptoms and lack of mastery remained significantly associated with recurrence. In predicting the recurrence of depression in later life, the direct effects of personality remain important and comparable in strength with other late life stressors related to recurrence. Copyright 2009 Elsevier B.V. All rights reserved.

Shelf life prediction of canned fried-rice using accelerated shelf life testing (ASLT) arrhenius method

Science.gov (United States)

Kurniadi, M.; Bintang, R.; Kusumaningrum, A.; Nursiwi, A.; Nurhikmat, A.; Susanto, A.; Angwar, M.; Triwiyono; Frediansyah, A.

2017-12-01

Research on shelf-life prediction of canned fried rice using Accelerated Shelf-life Test (ASLT) of Arrhenius model has been conducted. The aim of this research to predict shelf life of canned-fried rice products. Lethality value of 121°C for 15 and 20 minutes and Total Plate count methods are used to determine time and temperatures of sterilization process.Various storage temperatures of ASLT Arrhenius method were 35, 45 and 55°C during 35days. Rancidity is one of the derivation quality of canned fried rice. In this research, sample of canned fried rice is tested using rancidity value (TBA). TBA value was used as parameter which be measured once a week periodically. The use of can for fried rice without any chemical preservative is one of the advantage of the product, additionaly the use of physicalproperties such as temperature and pressure during its process can extend the shelf life and reduce the microbial contamination. The same research has never done before for fried rice as ready to eat meal. The result showed that the optimum conditions of sterilization process were 121°C,15 minutes with total plate count number of 9,3 × 101 CFU/ml. Lethality value of canned fried rice at 121°C,15 minutes was 3.63 minutes. The calculated Shelf-life of canned fried rice using Accelerated Shelf-life Test (ASLT) of Arrhenius method was 10.3 months.

Predicting life satisfaction in Angolan elderly: The moderating effect of gender

Directory of Open Access Journals (Sweden)

2014-03-01

Full Text Available A considerable amount of research has been done to explain life satisfaction in the elderly, and there is growing empirical evidence on the best predictors of life satisfaction. When studying elderly's lifesatisfaction and its predictors, gender differences have been found in several studies, including significant interactions with widowhood, for example. In this context, the present study aims were: (1 to test for the gender invariance in a life satisfaction measure; (2 to predict life satisfaction using several variables related to the aging process; and (3 to test the potential moderator effects due to gender in this prediction. Participants were 1003 Angolan elderly. Several multi-group (men vs. women MIMIC structural models were tested. First, results showed that there is gender invariance for the measurement of life satisfaction. Second, results found no moderation effects on key variables of the aging process. In other words, the estimated effects of psychosocial variables on life satisfaction remain the same for both genders. The discussion relates these results to the existing literature and posits the contributions of the study.

A new approach to predict the fish fillet shelf-life in presence of natural preservative agents

Directory of Open Access Journals (Sweden)

Alessandro Giufffrida

2017-06-01

Full Text Available Three data sets concerning the behaviour of spoilage flora of fillets treated with natural preservative substances (NPS were used to construct a new kind of mathematical predictive model. This model, unlike other ones, allows expressing the antibacterial effect of the NPS separately from the prediction of the growth rate. This approach, based on the introduction of a parameter into the predictive primary model, produced a good fitting of observed data and allowed characterising quantitatively the increase of shelf-life of fillets.

A review on fatigue life prediction methods for anti-vibration rubber materials

Directory of Open Access Journals (Sweden)

Xiaoli WANG

2016-08-01

Full Text Available Anti-vibration rubber, because of its superior elasticity, plasticity, waterproof and trapping characteristics, is widely used in the automotive industry, national defense, construction and other fields. The theory and technology of predicting fatigue life is of great significance to improve the durability design and manufacturing of anti-vibration rubber products. According to the characteristics of the anti-vibration rubber products in service, the technical difficulties for analyzing fatigue properties of anti-vibration rubber materials are pointed out. The research progress of the fatigue properties of rubber materials is reviewed from three angles including methods of fatigue crack initiation, fatigue crack propagation and fatigue damage accumulation. It is put forward that some nonlinear characteristics of rubber under fatigue loading, including the Mullins effect, permanent deformation and cyclic stress softening, should be considered in the further study of rubber materials. Meanwhile, it is indicated that the fatigue damage accumulation method based on continuum damage mechanics might be more appropriate to solve fatigue damage and life prediction problems for complex rubber materials and structures under fatigue loading.

Continuum damage mechanics based approach to the fatigue life prediction of cast aluminium alloy with considering the effect of porosity

Directory of Open Access Journals (Sweden)

Wang Xiaojia

2018-01-01

Full Text Available A damage mechanics based approach is applied for the study of fatigue behaviour of high pressure die cast ADC12 aluminium alloy. A damage coupled elastoplastic constitutive model is presented according to the concept of effective stress and the hypothesis of strain equivalence. An elastic fatigue damage model taking into account the pore-induced stress concentration is developed to investigate fatigue damage evolution of the specimens subjected to cyclic loading. The predicted lives for the specimens with different sizes of pores are consistent with the experimental data. The pore-induced fatigue damage and the variation of fatigue life along with the size of pores are also investigated.

A model for life predictions of nickel-base superalloys in high-temperature low cycle fatigue

Science.gov (United States)

Romanoski, Glenn R.; Pelloux, Regis M.; Antolovich, Stephen D.

1988-01-01

Extensive characterization of low-cycle fatigue damage mechanisms was performed on polycrystalline Rene 80 and IN100 tested in the temperature range from 871 to 1000 C. Low-cycle fatigue life was found to be dominated by propagation of microcracks to a critical size governed by the maximum tensile stress. A model was developed which incorporates a threshold stress for crack extension, a stress-based crack growth expression, and a failure criterion. The mathematical equivalence between this mechanistically based model and the strain-life low-cycle fatigue law was demonstrated using cyclic stress-strain relationships. The model was shown to correlate the high-temperature low-cycle fatigue data of the different nickel-base superalloys considered in this study.

Life Prediction/Reliability Data of Glass-Ceramic Material Determined for Radome Applications

Science.gov (United States)

Choi, Sung R.; Gyekenyesi, John P.

2002-01-01

Brittle materials, ceramics, are candidate materials for a variety of structural applications for a wide range of temperatures. However, the process of slow crack growth, occurring in any loading configuration, limits the service life of structural components. Therefore, it is important to accurately determine the slow crack growth parameters required for component life prediction using an appropriate test methodology. This test methodology also should be useful in determining the influence of component processing and composition variables on the slow crack growth behavior of newly developed or existing materials, thereby allowing the component processing and composition to be tailored and optimized to specific needs. Through the American Society for Testing and Materials (ASTM), the authors recently developed two test methods to determine the life prediction parameters of ceramics. The two test standards, ASTM 1368 for room temperature and ASTM C 1465 for elevated temperatures, were published in the 2001 Annual Book of ASTM Standards, Vol. 15.01. Briefly, the test method employs constant stress-rate (or dynamic fatigue) testing to determine flexural strengths as a function of the applied stress rate. The merit of this test method lies in its simplicity: strengths are measured in a routine manner in flexure at four or more applied stress rates with an appropriate number of test specimens at each applied stress rate. The slow crack growth parameters necessary for life prediction are then determined from a simple relationship between the strength and the applied stress rate. Extensive life prediction testing was conducted at the NASA Glenn Research Center using the developed ASTM C 1368 test method to determine the life prediction parameters of a glass-ceramic material that the Navy will use for radome applications.

Prediction of material creep behaviour for strain based life assessment applications

Energy Technology Data Exchange (ETDEWEB)

Rantala, J H; Hurst, R C [EC JRC IAM, Petten (Netherlands); Bregani, F [ENEL, Milan (Italy)

1999-12-31

In this work the idea of using constant load uniaxial creep test results instead of constant stress results for developing a CDM creep model for the P92 material is demonstrated. Due to limited availability of creep test results this work is based on incomplete test data and a general stress rupture line. In spite of these limitations a material creep model was developed for use in a FE analysis. Using P91 material as an example, a method is proposed to account for differences in strain evolution as a function of stress which normally manifests itself as lower strain values at low stresses in a normalised time-strain plot. This allows the CDM model to be used both in FE analysis and in strain-based life assessment engineering calculations. (orig.) 3 refs.

Prediction of material creep behaviour for strain based life assessment applications

Energy Technology Data Exchange (ETDEWEB)

Rantala, J.H.; Hurst, R.C. [EC JRC IAM, Petten (Netherlands); Bregani, F. [ENEL, Milan (Italy)

1998-12-31

In this work the idea of using constant load uniaxial creep test results instead of constant stress results for developing a CDM creep model for the P92 material is demonstrated. Due to limited availability of creep test results this work is based on incomplete test data and a general stress rupture line. In spite of these limitations a material creep model was developed for use in a FE analysis. Using P91 material as an example, a method is proposed to account for differences in strain evolution as a function of stress which normally manifests itself as lower strain values at low stresses in a normalised time-strain plot. This allows the CDM model to be used both in FE analysis and in strain-based life assessment engineering calculations. (orig.) 3 refs.

The fatigue life prediction of aluminium alloy using genetic algorithm and neural network

Science.gov (United States)

Susmikanti, Mike

2013-09-01

The behavior of the fatigue life of the industrial materials is very important. In many cases, the material with experiencing fatigue life cannot be avoided, however, there are many ways to control their behavior. Many investigations of the fatigue life phenomena of alloys have been done, but it is high cost and times consuming computation. This paper report the modeling and simulation approaches to predict the fatigue life behavior of Aluminum Alloys and resolves some problems of computation. First, the simulation using genetic algorithm was utilized to optimize the load to obtain the stress values. These results can be used to provide N-cycle fatigue life of the material. Furthermore, the experimental data was applied as input data in the neural network learning, while the samples data were applied for testing of the training data. Finally, the multilayer perceptron algorithm is applied to predict whether the given data sets in accordance with the fatigue life of the alloy. To achieve rapid convergence, the Levenberg-Marquardt algorithm was also employed. The simulations results shows that the fatigue behaviors of aluminum under pressure can be predicted. In addition, implementation of neural networks successfully identified a model for material fatigue life.

Method for estimating capacity and predicting remaining useful life of lithium-ion battery

International Nuclear Information System (INIS)

Hu, Chao; Jain, Gaurav; Tamirisa, Prabhakar; Gorka, Tom

2014-01-01

Highlights: • We develop an integrated method for the capacity estimation and RUL prediction. • A state projection scheme is derived for capacity estimation. • The Gauss–Hermite particle filter technique is used for the RUL prediction. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the capacity of Li-ion battery and predict the remaining useful life (RUL) throughout the whole life-time. This paper presents an integrated method for the capacity estimation and RUL prediction of Li-ion battery used in implantable medical devices. A state projection scheme from the author’s previous study is used for the capacity estimation. Then, based on the capacity estimates, the Gauss–Hermite particle filter technique is used to project the capacity fade to the end-of-service (EOS) value (or the failure limit) for the RUL prediction. Results of 10 years’ continuous cycling test on Li-ion prismatic cells in the lab suggest that the proposed method achieves good accuracy in the capacity estimation and captures the uncertainty in the RUL prediction. Post-explant weekly cycling data obtained from field cells with 4–7 implant years further verify the effectiveness of the proposed method in the capacity estimation

Creep life prediction of super heater coils used in coal based thermal power plants subjected to fly ash erosion and oxide scale formation

Science.gov (United States)

Srinivasan, P.; Kushwaha, Shashank

2018-04-01

Super heater coils of the coal based thermal power plants and subjected to severe operating conditions from both steam side and gas side. Formation of oxide scale due to prolonged service lead to temperature raise of the tube and erosion due to fly ash present in the combusted gases leads to tube thinning. Both these factors lead to creep rupture of the coils much before the designed service life. Failure of super heater coils during service of the boiler leads to power loss and huge monitory loss to the power plants. An attempt is made to model the creep damage caused to the super heater coils using heat transfer analysis tube thinning due to erosive wear of the tubes. Combined effects of these parameters are taken into consideration to predict the life of the super heater coils. This model may be used to estimate the life of the coils operating under the severe operating conditions to prevent the unexpected failure of the coils.

Ensemble of data-driven prognostic algorithms for robust prediction of remaining useful life

International Nuclear Information System (INIS)

Hu Chao; Youn, Byeng D.; Wang Pingfeng; Taek Yoon, Joung

2012-01-01

Prognostics aims at determining whether a failure of an engineered system (e.g., a nuclear power plant) is impending and estimating the remaining useful life (RUL) before the failure occurs. The traditional data-driven prognostic approach is to construct multiple candidate algorithms using a training data set, evaluate their respective performance using a testing data set, and select the one with the best performance while discarding all the others. This approach has three shortcomings: (i) the selected standalone algorithm may not be robust; (ii) it wastes the resources for constructing the algorithms that are discarded; (iii) it requires the testing data in addition to the training data. To overcome these drawbacks, this paper proposes an ensemble data-driven prognostic approach which combines multiple member algorithms with a weighted-sum formulation. Three weighting schemes, namely the accuracy-based weighting, diversity-based weighting and optimization-based weighting, are proposed to determine the weights of member algorithms. The k-fold cross validation (CV) is employed to estimate the prediction error required by the weighting schemes. The results obtained from three case studies suggest that the ensemble approach with any weighting scheme gives more accurate RUL predictions compared to any sole algorithm when member algorithms producing diverse RUL predictions have comparable prediction accuracy and that the optimization-based weighting scheme gives the best overall performance among the three weighting schemes.

A method for gear fatigue life prediction considering the internal flow field of the gear pump

Science.gov (United States)

Shen, Haidong; Li, Zhiqiang; Qi, Lele; Qiao, Liang

2018-01-01

Gear pump is the most widely used volume type hydraulic pump, and it is the main power source of the hydraulic system. Its performance is influenced by many factors, such as working environment, maintenance, fluid pressure and so on. It is different from the gear transmission system, the internal flow field of gear pump has a greater impact on the gear life, therefore it needs to consider the internal hydraulic system when predicting the gear fatigue life. In this paper, a certain aircraft gear pump as the research object, aim at the typical failure forms, gear contact fatigue, of gear pump, proposing the prediction method based on the virtual simulation. The method use CFD (Computational fluid dynamics) software to analyze pressure distribution of internal flow field of the gear pump, and constructed the unidirectional flow-solid coupling model of gear to acquire the contact stress of tooth surface on Ansys workbench software. Finally, employing nominal stress method and Miner cumulative damage theory to calculated the gear contact fatigue life based on modified material P-S-N curve. Engineering practice show that the method is feasible and efficient.

Life history and spatial traits predict extinction risk due to climate change

Science.gov (United States)

Pearson, Richard G.; Stanton, Jessica C.; Shoemaker, Kevin T.; Aiello-Lammens, Matthew E.; Ersts, Peter J.; Horning, Ned; Fordham, Damien A.; Raxworthy, Christopher J.; Ryu, Hae Yeong; McNees, Jason; Akçakaya, H. Reşit

2014-03-01

There is an urgent need to develop effective vulnerability assessments for evaluating the conservation status of species in a changing climate. Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change based on the expectation that established assessments such as the IUCN Red List need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened, no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally different from other threats in terms of assessing extinction risks.

SOFT COMPUTING SINGLE HIDDEN LAYER MODELS FOR SHELF LIFE PREDICTION OF BURFI

Directory of Open Access Journals (Sweden)

Sumit Goyal

2012-05-01

Full Text Available Burfi is an extremely popular sweetmeat, which is prepared by desiccating the standardized water buffalo milk. Soft computing feedforward single layer models were developed for predicting the shelf life of burfi stored at 30g.C. The data of the product relating to moisture, titratable acidity, free fatty acids, tyrosine, and peroxide value were used as input variables, and the overall acceptability score as output variable. The results showed excellent agreement between the experimental and the predicted data, suggesting that the developed soft computing model can alternatively be used for predicting the shelf life of burfi.

Distance saturation product predicts health-related quality of life among sarcoidosis patients.

Science.gov (United States)

Bourbonnais, Julie M; Malaisamy, Subramanian; Dalal, Bhavinkumar D; Samarakoon, Priyan C; Parikh, Swapna R; Samavati, Lobelia

2012-06-13

Sarcoidosis is a chronic disease with different phenotypic manifestations. Health-related quality of life is an important aspect in sarcoidosis, yet difficult to measure. The objective of this study was to identify clinical markers predictive of poor quality of life in sarcoidosis patients that can be followed over time and targeted for intervention. We assessed the quality of life of 162 patients with confirmed sarcoidosis in a prospective, cross-sectional study using the Sarcoidosis Health Questionnaire (SHQ) and Short Form-36 Health Survey (SF-36). We evaluated the validity of these questionnaires and sought to identify variables that would best explain the performance scores of the patients. On multivariate regression analyses, the very best composite model to predict total scores from both surveys was a model containing the distance-saturation product and Borg Dyspnea Scale score at the end of a 6-min walk test. This model could better predict SF-36 scores (R² = 0.33) than SHQ scores (R² = 0.24). Substitution of distanced walked in 6 min for the distance-saturation product in this model resulted in a lesser ability to predict both scores (R² = 0.26 for SF-36; R² = 0.22 for SHQ). Both the SHQ and SF-36 surveys are valuable tools in the assessment of health-related quality of life in sarcoidosis patients. The best model to predict quality of life among these patients, as determined by regression analyses, included the distance-saturation product and Borg score after the 6-min walk test. Both variables represent easily obtainable clinical parameters that can be followed over time and targeted for intervention.

Life Prediction of Large Lithium-Ion Battery Packs with Active and Passive Balancing

Energy Technology Data Exchange (ETDEWEB)

Shi, Ying [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Smith, Kandler A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zane, Regan [Utah State University; Anderson, Dyche [Ford Motor Company

2017-07-03

Lithium-ion battery packs take a major part of large-scale stationary energy storage systems. One challenge in reducing battery pack cost is to reduce pack size without compromising pack service performance and lifespan. Prognostic life model can be a powerful tool to handle the state of health (SOH) estimate and enable active life balancing strategy to reduce cell imbalance and extend pack life. This work proposed a life model using both empirical and physical-based approaches. The life model described the compounding effect of different degradations on the entire cell with an empirical model. Then its lower-level submodels considered the complex physical links between testing statistics (state of charge level, C-rate level, duty cycles, etc.) and the degradation reaction rates with respect to specific aging mechanisms. The hybrid approach made the life model generic, robust and stable regardless of battery chemistry and application usage. The model was validated with a custom pack with both passive and active balancing systems implemented, which created four different aging paths in the pack. The life model successfully captured the aging trajectories of all four paths. The life model prediction errors on capacity fade and resistance growth were within +/-3% and +/-5% of the experiment measurements.

Fatigue life prediction for a cold worked T316 stainless steel

International Nuclear Information System (INIS)

Manjoine, M.J.

1983-01-01

Permanent damage curves of initiation-life and propagation-life which predict the fatigue life of specimens of a cold-worked type 316 stainless steel under complex strain-range histories were generated by a limited test program. Analysis of the test data showed that fatigue damage is not linear throughout life and that propagation life is longer than initiation-life at high strain ranges but is shorter at low strain ranges. If permanent damage has been initiated by prior history and/or fabrication, propagation to a given life can occur at a lower strain range than that estimated from the fatigue curves for constant CSR. (author) [pt

Structural health monitoring for fatigue life prediction of orthotropic brdige decks

NARCIS (Netherlands)

Pijpers, R.J.M.; Pahlavan, P.L.; Paulissen, J.H.; Hakkesteegt, H.C.; Jansen, T.H.

2013-01-01

Infrastructure asset owners are more and more confronted with structures reaching the end of their structural life. Structural Health Monitoring (SHM) systems should provide up-to-date information about the actual condition, as well predict the structural life and required maintenance of the assets

Study on effect of mean stress on fatigue life prediction of thin film structure

Energy Technology Data Exchange (ETDEWEB)

Shin, Myung Soo [Ahtti Co., Seongnam (Korea, Republic of); Park, Jun Hyu [Tongmyong University, Busan (Korea, Republic of); Kim, Jung Yup [Korea Institute of Machinery and Materials, Daejeon (Korea, Republic of)

2016-04-15

This paper describes the effect of mean stress on fatigue life prediction of structure made with thin film. It is well known that the mean stress influences fatigue life prediction of mechanical structure. We investigated a reasonable method for considering mean stress when fatigue strength assessment of micro structure of thin film should be performed. Fatigue tests of smooth specimen of beryllium-copper (BeCu) thin film were performed in ambient air at R = 0.1 with 5 Hz. A micro probe was designed and made with BeCu thin film by the precision press process. Fatigue tests of micro structure were performed with 5 Hz frequency, in ambient air to verify the fatigue life predicted by computer simulation through FE analysis. The fatigue life predicted by the Sa -N curve modified by Goodman method with principal stress through FE analysis shows a more reasonable result than other methods.

Study on effect of mean stress on fatigue life prediction of thin film structure

International Nuclear Information System (INIS)

Shin, Myung Soo; Park, Jun Hyu; Kim, Jung Yup

2016-01-01

This paper describes the effect of mean stress on fatigue life prediction of structure made with thin film. It is well known that the mean stress influences fatigue life prediction of mechanical structure. We investigated a reasonable method for considering mean stress when fatigue strength assessment of micro structure of thin film should be performed. Fatigue tests of smooth specimen of beryllium-copper (BeCu) thin film were performed in ambient air at R = 0.1 with 5 Hz. A micro probe was designed and made with BeCu thin film by the precision press process. Fatigue tests of micro structure were performed with 5 Hz frequency, in ambient air to verify the fatigue life predicted by computer simulation through FE analysis. The fatigue life predicted by the Sa -N curve modified by Goodman method with principal stress through FE analysis shows a more reasonable result than other methods

The prediction of reliability and residual life of reactor pressure components

International Nuclear Information System (INIS)

Nemec, J.; Antalovsky, S.

1978-01-01

The paper deals with the problem of PWR pressure components reliability and residual life evaluation and prediction. A physical model of damage cumulation which serves as a theoretical basis for all considerations presents two major aspects. The first one describes the dependence of the degree of damage in the crack leading-edge in pressure components on the reactor system load-time history, i.e. on the number of transient loads. Both stages, fatigue crack initiation and growth through the wall until the critical length is reached, are investigated. The crack is supposed to initiate at the flaws in a strength weld joint or in the bimetallic weld of the base ferritic steel and the austenitic stainless overlay cladding. The growth rates of developed cracks are analysed in respect to different load-time histories. Important cyclic properties of some steels are derived from the low-cycle fatigue theory. The second aspect is the load-time history-dependent process of precipitation, deformation and radiation aging, characterized entirely by the critical crack-length value mentioned above. The fracture point, defined by the equation ''crack-length=critical value'' and hence the residual life, can be evaluated using this model and verified by in-service inspection. The physical model described is randomized by considering all the parameters of the model as random. Monte Carlo methods are applied and fatigue crack initiation and growth is simulated. This permits evaluation of the reliability and residual life of the component. The distributions of material and load-time history parameters are needed for such simulation. Both the deterministic and computer-simulated probabilistic predictions of reliability and residual life are verified by prior-to-failure sequential testing of data coming from in-service NDT periodical inspections. (author)

Imagining life with an ostomy: Does a video intervention improve quality-of-life predictions for a medical condition that may elicit disgust?☆

Science.gov (United States)

Angott, Andrea M.; Comerford, David A.; Ubel, Peter A.

2014-01-01

Objective To test a video intervention as a way to improve predictions of mood and quality-of-life with an emotionally evocative medical condition. Such predictions are typically inaccurate, which can be consequential for decision making. Method In Part 1, people presently or formerly living with ostomies predicted how watching a video depicting a person changing his ostomy pouch would affect mood and quality-of-life forecasts for life with an ostomy. In Part 2, participants from the general public read a description about life with an ostomy; half also watched a video depicting a person changing his ostomy pouch. Participants’ quality-of-life and mood forecasts for life with an ostomy were assessed. Results Contrary to our expectations, and the expectations of people presently or formerly living with ostomies, the video did not reduce mood or quality-of-life estimates, even among participants high in trait disgust sensitivity. Among low-disgust participants, watching the video increased quality-of-life predictions for ostomy. Conclusion Video interventions may improve mood and quality-of-life forecasts for medical conditions, including those that may elicit disgust, such as ostomy. Practice implications Video interventions focusing on patients’ experience of illness continue to show promise as components of decision aids, even for emotionally charged health states such as ostomy. PMID:23177398

DNA Sequencing and Predictions of the Cosmic Theory of Life

Science.gov (United States)

Wickramasinghe, N. Chandra

The theory of cometary panspermia, developed by the late Sir Fred Hoyle and the present author argues that life originated cosmically as a unique event in one of a great multitude of comets or planetary bodies in the Universe. Life on Earth did not originate here but was introduced by impacting comets, and its further evolution was driven by the subsequent acquisition of cosmically derived genes. Explicit predictions of this theory published in 1979-1981, stating how the acquisition of new genes drives evolution, are compared with recent developments in relation to horizontal gene transfer, and the role of retroviruses in evolution. Precisely-stated predictions of the theory of cometary panspermia are shown to have been verified.

Computational models for residual creep life prediction of power plant components

International Nuclear Information System (INIS)

Grewal, G.S.; Singh, A.K.; Ramamoortry, M.

2006-01-01

All high temperature - high pressure power plant components are prone to irreversible visco-plastic deformation by the phenomenon of creep. The steady state creep response as well as the total creep life of a material is related to the operational component temperature through, respectively, the exponential and inverse exponential relationships. Minor increases in the component temperature can thus have serious consequences as far as the creep life and dimensional stability of a plant component are concerned. In high temperature steam tubing in power plants, one mechanism by which a significant temperature rise can occur is by the growth of a thermally insulating oxide film on its steam side surface. In the present paper, an elegantly simple and computationally efficient technique is presented for predicting the residual creep life of steel components subjected to continual steam side oxide film growth. Similarly, fabrication of high temperature power plant components involves extensive use of welding as the fabrication process of choice. Naturally, issues related to the creep life of weldments have to be seriously addressed for safe and continual operation of the welded plant component. Unfortunately, a typical weldment in an engineering structure is a zone of complex microstructural gradation comprising of a number of distinct sub-zones with distinct meso-scale and micro-scale morphology of the phases and (even) chemistry and its creep life prediction presents considerable challenges. The present paper presents a stochastic algorithm, which can be' used for developing experimental creep-cavitation intensity versus residual life correlations for welded structures. Apart from estimates of the residual life in a mean field sense, the model can be used for predicting the reliability of the plant component in a rigorous probabilistic setting. (author)

Life prediction of advanced materials for gas turbine application

Energy Technology Data Exchange (ETDEWEB)

Zamrik, S.Y.; Ray, A.; Koss, D.A. [Pennsylvania State Univ., University Park, PA (United States)

1995-10-01

Most of the studies on the low cycle fatigue life prediction have been reported under isothermal conditions where the deformation of the material is strain dependent. In the development of gas turbines, components such as blades and vanes are exposed to temperature variations in addition to strain cycling. As a result, the deformation process becomes temperature and strain dependent. Therefore, the life of the component becomes sensitive to temperature-strain cycling which produces a process known as {open_quotes}thermomechanical fatigue, or TMF{close_quotes}. The TMF fatigue failure phenomenon has been modeled using conventional fatigue life prediction methods, which are not sufficiently accurate to quantitatively establish an allowable design procedure. To add to the complexity of TMF life prediction, blade and vane substrates are normally coated with aluminide, overlay or thermal barrier type coatings (TBC) where the durability of the component is dominated by the coating/substrate constitutive response and by the fatigue behavior of the coating. A number of issues arise from TMF depending on the type of temperature/strain phase cycle: (1) time-dependent inelastic behavior can significantly affect the stress response. For example, creep relaxation during a tensile or compressive loading at elevated temperatures leads to a progressive increase in the mean stress level under cyclic loading. (2) the mismatch in elastic and thermal expansion properties between the coating and the substrate can lead to significant deviations in the coating stress levels due to changes in the elastic modulii. (3) the {open_quotes}dry{close_quotes} corrosion resistance coatings applied to the substrate may act as primary crack initiation sites. Crack initiation in the coating is a function of the coating composition, its mechanical properties, creep relaxation behavior, thermal strain range and the strain/temperature phase relationship.

Development of Reliability Based Life Prediction Methods for Thermal and Environmental Barrier Coatings in Ceramic Matrix Composites

Science.gov (United States)

Shah, Ashwin

2001-01-01

Literature survey related to the EBC/TBC (environmental barrier coating/thermal barrier coating) fife models, failure mechanisms in EBC/TBC and the initial work plan for the proposed EBC/TBC life prediction methods development was developed as well as the finite element model for the thermal/stress analysis of the GRC-developed EBC system was prepared. Technical report for these activities is given in the subsequent sections.

An analytical method to predict fatigue life of thermoplastics in uniaxial loading: sensitivity to wave type, frequency and stress amplitude

NARCIS (Netherlands)

Janssen, R.P.M.; Govaert, L.E.; Meijer, H.E.H.

2008-01-01

A method is presented that allows fatigue life predictions on the basis of creep life data. The approach is based on the assumption that the time-dependent failure of polymers is determined by the intrinsic strain softening that is initiated when a critical threshold value of the plastic strain is

Knowledge-Based Systems in Biomedicine and Computational Life Science

CERN Document Server

Jain, Lakhmi

2013-01-01

This book presents a sample of research on knowledge-based systems in biomedicine and computational life science. The contributions include: ·         personalized stress diagnosis system ·         image analysis system for breast cancer diagnosis ·         analysis of neuronal cell images ·         structure prediction of protein ·         relationship between two mental disorders ·         detection of cardiac abnormalities ·         holistic medicine based treatment ·         analysis of life-science data  

A Critical Plane-energy Model for Multiaxial Fatigue Life Prediction of Homogeneous and Heterogeneous Materials

Science.gov (United States)

Wei, Haoyang

A new critical plane-energy model is proposed in this thesis for multiaxial fatigue life prediction of homogeneous and heterogeneous materials. Brief review of existing methods, especially on the critical plane-based and energy-based methods, are given first. Special focus is on one critical plane approach which has been shown to work for both brittle and ductile metals. The key idea is to automatically change the critical plane orientation with respect to different materials and stress states. One potential drawback of the developed model is that it needs an empirical calibration parameter for non-proportional multiaxial loadings since only the strain terms are used and the out-of-phase hardening cannot be considered. The energy-based model using the critical plane concept is proposed with help of the Mroz-Garud hardening rule to explicitly include the effect of non-proportional hardening under fatigue cyclic loadings. Thus, the empirical calibration for non-proportional loading is not needed since the out-of-phase hardening is naturally included in the stress calculation. The model predictions are compared with experimental data from open literature and it is shown the proposed model can work for both proportional and non-proportional loadings without the empirical calibration. Next, the model is extended for the fatigue analysis of heterogeneous materials integrating with finite element method. Fatigue crack initiation of representative volume of heterogeneous materials is analyzed using the developed critical plane-energy model and special focus is on the microstructure effect on the multiaxial fatigue life predictions. Several conclusions and future work is drawn based on the proposed study.

Optimization of Steamed Meals Based on Composite Flour (Taro, Banana, Green Bean) and Its Predicted Shelf Life

Science.gov (United States)

Sunarmani; Setyadjit; Ermi, S.

2018-05-01

Ongol-ongol is for food diversification by mixing composite flour of taro, banana and mung bean, then was steamed by hot air. The purpose of this study was to find out the optimum way to produce ‘ongol-ongol’ from composite flour and to know the storage life by prediction method. The research consisted of two stages, namely the determination of the optimum formula of ‘ongol-ongol’ with Design Expert DX 8.1.6 software and the estimation of product shelf life of the optimum formula by ASLT (Accelerated Shelf Life Test) method. The optimum formula of the steamed meal was produced from composite flour and arenga flour with ratio of 50: 50 and flour to water ratio of 1: 1. The proximate content of steamed meal of optimum formula is 36.53% moisture content, ash content of 1,36%, fat content of 14.48%, protein level of 28.5%, and carbohydrate of 44.77% (w/w). Energy Value obtained from 100 g of ‘ongol-ongol’ was 320.8 Kcal. Recommended for steamed meal storage life is 12.54 days at ambient temperature.

Simulation work of fatigue life prediction of rubber automotive components

International Nuclear Information System (INIS)

Samad, M S A; Ali, Aidy

2010-01-01

The usage of rubbers has always been so important, especially in automotive industries. Rubbers have a hyper elastic behaviour which is the ability to withstand very large strain without failure. The normal applications for rubbers are used for shock absorption, sound isolation and mounting. In this study, the predictions of fatigue life of an engine mount of rubber automotive components were presented. The finite element analysis was performed to predict the critical part and the strain output were incorporated into fatigue model for prediction. The predicted result shows agreement in term of failure location of rubber mount.

Assessment and propagation of mechanical property uncertainties in fatigue life prediction of composite laminates

DEFF Research Database (Denmark)

Castro, Oscar; Branner, Kim; Dimitrov, Nikolay Krasimirov

2018-01-01

amplitude loading cycles. Fatigue life predictions of unidirectional and multi-directional glass/epoxy laminates are carried out to validate the proposed model against experimental data. The probabilistic fatigue behavior of laminates is analyzed under constant amplitude loading conditions as well as under......A probabilistic model for estimating the fatigue life of laminated composite materials considering the uncertainty in their mechanical properties is developed. The uncertainty in the material properties is determined from fatigue coupon tests. Based on this uncertainty, probabilistic constant life...... diagrams are developed which can efficiently estimate probabilistic É›-N curves at any load level and stress ratio. The probabilistic É›-N curve information is used in a reliability analysis for fatigue limit state proposed for estimating the probability of failure of composite laminates under variable...

Development of laboratory acceleration test method for service life prediction of concrete structures

International Nuclear Information System (INIS)

Cho, M. S.; Song, Y. C.; Bang, K. S.; Lee, J. S.; Kim, D. K.

1999-01-01

Service life prediction of nuclear power plants depends on the application of history of structures, field inspection and test, the development of laboratory acceleration tests, their analysis method and predictive model. In this study, laboratory acceleration test method for service life prediction of concrete structures and application of experimental test results are introduced. This study is concerned with environmental condition of concrete structures and is to develop the acceleration test method for durability factors of concrete structures e.g. carbonation, sulfate attack, freeze-thaw cycles and shrinkage-expansion etc

Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads

Science.gov (United States)

Parlos, Alexander G.; Toliyat, Hamid A.

2005-01-01

An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.

A Predictive Framework for Thermomechanical Fatigue Life of High Silicon Molybdenum Ductile Cast Iron Based on Considerations of Strain Energy Dissipation

Science.gov (United States)

Avery, Katherine R.

Isothermal low cycle fatigue (LCF) and anisothermal thermomechanical fatigue (TMF) tests were conducted on a high silicon molybdenum (HiSiMo) cast iron for temperatures up to 1073K. LCF and out-of-phase (OP) TMF lives were significantly reduced when the temperature was near 673K due to an embrittlement phenomenon which decreases the ductility of HiSiMo at this temperature. In this case, intergranular fracture was predominant, and magnesium was observed at the fracture surface. When the thermal cycle did not include 673K, the failure mode was predominantly transgranular, and magnesium was not present on the fracture surface. The in-phase (IP) TMF lives were unaffected when the thermal cycle included 673K, and the predominant failure mode was found to be transgranular fracture, regardless of the temperature. No magnesium was present on the IP TMF fracture surfaces. Thus, the embrittlement phenomenon was found to contribute to fatigue damage only when the temperature was near 673K and a tensile stress was present. To account for the temperature- and stress-dependence of the embrittlement phenomenon on the TMF life of HiSiMo cast iron, an original model based on the cyclic inelastic energy dissipation is proposed which accounts for temperature-dependent differences in the rate of fatigue damage accumulation in tension and compression. The proposed model has few empirical parameters. Despite the simplicity of the model, the predicted fatigue life shows good agreement with more than 130 uniaxial low cycle and thermomechanical fatigue tests, cyclic creep tests, and tests conducted at slow strain rates and with hold times. The proposed model was implemented in a multiaxial formulation and applied to the fatigue life prediction of an exhaust manifold subjected to severe thermal cycles. The simulation results show good agreement with the failure locations and number of cycles to failure observed in a component-level experiment.

Evaluation of creep-fatigue life prediction methods for low-carbon/nitrogen-added SUS316

International Nuclear Information System (INIS)

Takahashi, Yukio

1998-01-01

Low-carbon/medium nitrogen 316 stainless steel called 316FR is a principal candidate for the high-temperature structural materials of a demonstration fast reactor plant. Because creep-fatigue damage is a dominant failure mechanism of the high-temperature materials subjected to thermal cycles, it is important to establish a reliable creep-fatigue life prediction method for this steel. Long-term creep tests and strain-controlled creep-fatigue tests have been conducted at various conditions for two different heats of the steel. In the constant load creep tests, both materials showed similar creep rupture strength but different ductility. The material with lower ductility exhibited shorter life under creep-fatigue loading conditions and correlation of creep-fatigue life with rupture ductility, rather than rupture strength, was made clear. Two kinds of creep-fatigue life prediction methods, i.e. time fraction rule and ductility exhaustion method were applied to predict the creep-fatigue life. Accurate description of stress relaxation behavior was achieved by an addition of 'viscous' strain to conventional creep strain and only the latter of which was assumed to contribute to creep damage in the application of ductility exhaustion method. The current version of the ductility exhaustion method was found to have very good accuracy in creep-fatigue life prediction, while the time fraction rule overpredicted creep-fatigue life as large as a factor of 30. To make a reliable estimation of the creep damage in actual components, use of ductility exhaustion method is strongly recommended. (author)

An adaptive-order particle filter for remaining useful life prediction of aviation piston pumps

Directory of Open Access Journals (Sweden)

Tongyang LI

2018-05-01

Full Text Available An accurate estimation of the remaining useful life (RUL not only contributes to an effective application of an aviation piston pump, but also meets the necessity of condition based maintenance (CBM. For the current RUL evaluation methods, a model-based method is inappropriate for the degradation process of an aviation piston pump due to difficulties of modeling, while a data-based method rarely presents high-accuracy prediction in a long period of time. In this work, an adaptive-order particle filter (AOPF prognostic process is proposed aiming at improving long-term prediction accuracy of RUL by combining both kinds of methods. A dynamic model is initialized by a data-driven or empirical method. When a new observation comes, the prior state distribution is approximated by a current model. The order of the current model is updated adaptively by fusing the information of the observation. Monte Carlo simulation is employed for estimating the posterior probability density function of future states of the pump’s degradation. With updating the order number adaptively, the method presents a higher precision in contrast with those of traditional methods. In a case study, the proposed AOPF method is adopted to forecast the degradation status of an aviation piston pump with experimental return oil flow data, and the analytical results show the effectiveness of the proposed AOPF method. Keywords: Adaptive prognosis, Condition based maintenance (CBM, Particle filter (PF, Piston pump, Remaining useful life (RUL

A Reliability-Based Determination of Economic Life of Marine power plants

International Nuclear Information System (INIS)

Atua, K.

1999-01-01

The reliability-based life approach is utilized. Selective failure modes of marine power plants are used for illustration. A case study of the Egyptian Commercial Fleet owned by the Public Sector Company was analyzed and used to establish a demonstration of the expected economic life based on local operating and maintenance conditions. The data acquired is analyzed and failure trend is derived for each failure mode. Probabilistic techniques are used to randomly generate numbers and times of occurrence of different failure modes. The reliability analysis is performed on the life span expected by the manufacture to predict the total number of failures, dependent failures, and cost of failures. Total expenditure due to random failure and cost of scheduled maintenance together with the annual income are utilized (using the time value of money) to determine the economic life of the plant. Conclusions are derived and recommendations for the enhancement of this work in the future are made

Survey on damage mechanics models for fatigue life prediction

NARCIS (Netherlands)

Silitonga, S.; Maljaars, J.; Soetens, F.; Snijder, H.H.

2013-01-01

Engineering methods to predict the fatigue life of structures have been available since the beginning of the 20th century. However, a practical problem arises from complex loading conditions and a significant concern is the accuracy of the methods under variable amplitude loading. This paper

Long-term Creep Life Prediction for Type 316LN Stainless Steel

International Nuclear Information System (INIS)

Kim, Woo Gon; Ryu, Woo Seog; Kim, Sung Ho; Lee, Chan Bok

2007-01-01

Since Sodium Fast Cooled Reactor (SFR) components are designed to be use for more than 30 years at a high temperature of 550 .deg. C, one of the most important properties of these components is the long term creep behavior. To accurately predict the long-term creep life of the components, it is essential to achieve reliable long-term test data beyond their design life. But, it is difficult to actually obtain long duration data because it is time-consuming work. So far, a variety of time-temperature parameters (TTPs) have been developed to predict a long-term creep life from shorter-time tests at higher temperatures. Among them, the Larson-Miller, the Orr-Sherby-Dorn, the Manson-Harferd and the Manson-Succop parameters have been typically used. None of these parameters has an overwhelming preference, and they have certain inherent restrictions imposed on their data in the application of the TTPs parameters. Meanwhile, it has been reported that the Minimum Commitment Method (MCM) proposed by Manson and Ensign has a greater flexibility for a creep rupture analysis. Thus, the MCM will be useful as another approach. Until now, the applicability of the MCM has not been investigated for type 316LN SS because of insufficient creep data. In this paper, the MCM was applied to predict a long-term creep life of type 316LN stainless steel (SS). Lots of creep rupture data was collected through literature surveys and the experimental data of KAERI. Using the short-term experimental data for under 2,000 hours, a longer-time rupture above 105 hours was predicted by the MCM at temperatures from 550 .deg. C to 800 .deg. C

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Science.gov (United States)

Daigle, Matthew John; Goebel, Kai Frank

2010-01-01

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Prediction of multiaxial fatigue life for notched specimens of titanium alloy TC4

Energy Technology Data Exchange (ETDEWEB)

Wu, Z. R.; Li, Z. X. [Southeast University, Nanjing (China); Hu, X. T.; Song, Y. D. [Nanjing University, Nanjing (China)

2016-05-15

Both the proportional and nonproportional multiaxial fatigue tests were conducted on two kinds of notched specimens of titanium alloy TC4. The multiaxial fatigue critical area of notched specimen is considered as the location experiencing the maximum damage. It is unsatisfactory to predict the multiaxial fatigue life with the local stress and strain in the fatigue critical area. The critical distance concepts are employed in the multiaxial life prediction method for notched specimens. The proposed method was checked by the test data of TC4 notched specimens. The prediction results are almost within a factor of three scatter band of the test results.

"Engage" therapy: Prediction of change of late-life major depression.

Science.gov (United States)

Alexopoulos, George S; O'Neil, Robert; Banerjee, Samprit; Raue, Patrick J; Victoria, Lindsay W; Bress, Jennifer N; Pollari, Cristina; Arean, Patricia A

2017-10-15

Engage grew out of the need for streamlined psychotherapies that can be accurately used by community therapists in late-life depression. Engage was based on the view that dysfunction of reward networks is the principal mechanism mediating depressive symptoms. Accordingly, Engage uses "reward exposure" (exposure to meaningful activities) and assumes that repeated activation of reward networks will normalize these systems. This study examined whether change in a behavioral activation scale, an index of reward system function, predicts change in depressive symptomatology. The participants (N = 48) were older adults with major depression treated with 9 weekly sessions of Engage and assessed 27 weeks after treatment. Depression was assessed with the 24-item Hamilton Depression Rating Scale (HAM-D) and behavioral activation with the four subscales of Behavioral Activation for Depression Scale (activation, avoidance/rumination, work impairment, social impairment) at baseline, 6 weeks (mid-treatment), 9 weeks (end of treatment), and 36 weeks. Change only in the Activation subscale during successive periods of assessment predicted depression severity (HAM-D) at the end of each period (F 1, 47 = 21.05, psocial support. Change in behavioral activation predicts improvement of depressive symptoms and signs in depressed older adults treated with Engage. Copyright © 2017. Published by Elsevier B.V.

A novel health indicator for on-line lithium-ion batteries remaining useful life prediction

Science.gov (United States)

Zhou, Yapeng; Huang, Miaohua; Chen, Yupu; Tao, Ye

2016-07-01

Prediction of lithium-ion batteries remaining useful life (RUL) plays an important role in an intelligent battery management system. The capacity and internal resistance are often used as the batteries health indicator (HI) for quantifying degradation and predicting RUL. However, on-line measurement of capacity and internal resistance are hardly realizable due to the not fully charged and discharged condition and the extremely expensive cost, respectively. Therefore, there is a great need to find an optional way to deal with this plight. In this work, a novel HI is extracted from the operating parameters of lithium-ion batteries for degradation modeling and RUL prediction. Moreover, Box-Cox transformation is employed to improve HI performance. Then Pearson and Spearman correlation analyses are utilized to evaluate the similarity between real capacity and the estimated capacity derived from the HI. Next, both simple statistical regression technique and optimized relevance vector machine are employed to predict the RUL based on the presented HI. The correlation analyses and prediction results show the efficiency and effectiveness of the proposed HI for battery degradation modeling and RUL prediction.

A Probabilistic Approach to Predict Thermal Fatigue Life for Ball Grid Array Solder Joints

Science.gov (United States)

Wei, Helin; Wang, Kuisheng

2011-11-01

Numerous studies of the reliability of solder joints have been performed. Most life prediction models are limited to a deterministic approach. However, manufacturing induces uncertainty in the geometry parameters of solder joints, and the environmental temperature varies widely due to end-user diversity, creating uncertainties in the reliability of solder joints. In this study, a methodology for accounting for variation in the lifetime prediction for lead-free solder joints of ball grid array packages (PBGA) is demonstrated. The key aspects of the solder joint parameters and the cyclic temperature range related to reliability are involved. Probabilistic solutions of the inelastic strain range and thermal fatigue life based on the Engelmaier model are developed to determine the probability of solder joint failure. The results indicate that the standard deviation increases significantly when more random variations are involved. Using the probabilistic method, the influence of each variable on the thermal fatigue life is quantified. This information can be used to optimize product design and process validation acceptance criteria. The probabilistic approach creates the opportunity to identify the root causes of failed samples from product fatigue tests and field returns. The method can be applied to better understand how variation affects parameters of interest in an electronic package design with area array interconnections.

Thermal Cycling Life Prediction of Sn-3.0Ag-0.5Cu Solder Joint Using Type-I Censored Data

Directory of Open Access Journals (Sweden)

Jinhua Mi

2014-01-01

Full Text Available Because solder joint interconnections are the weaknesses of microelectronic packaging, their reliability has great influence on the reliability of the entire packaging structure. Based on an accelerated life test the reliability assessment and life prediction of lead-free solder joints using Weibull distribution are investigated. The type-I interval censored lifetime data were collected from a thermal cycling test, which was implemented on microelectronic packaging with lead-free ball grid array (BGA and fine-pitch ball grid array (FBGA interconnection structures. The number of cycles to failure of lead-free solder joints is predicted by using a modified Engelmaier fatigue life model and a type-I censored data processing method. Then, the Pan model is employed to calculate the acceleration factor of this test. A comparison of life predictions between the proposed method and the ones calculated directly by Matlab and Minitab is conducted to demonstrate the practicability and effectiveness of the proposed method. At last, failure analysis and microstructure evolution of lead-free solders are carried out to provide useful guidance for the regular maintenance, replacement of substructure, and subsequent processing of electronic products.

Aluminum 7075-T6 fatigue data generation and probabilistic life prediction formulation

OpenAIRE

Kemna, John G.

1998-01-01

Approved for public release; distribution is unlimited. The life extension of aging fleet aircraft requires an assessment of the safe-life remaining after refurbishment. Risk can be estimated by conventional deterministic fatigue analysis coupled with a subjective factor of safety. Alternatively, risk can be quantitatively and objectively predicted by probabilistic analysis. In this investigation, a general probabilistic life formulation is specialized for constant amplitude, fully reverse...

Integrated Design Software Predicts the Creep Life of Monolithic Ceramic Components

Science.gov (United States)

1996-01-01

Significant improvements in propulsion and power generation for the next century will require revolutionary advances in high-temperature materials and structural design. Advanced ceramics are candidate materials for these elevated-temperature applications. As design protocols emerge for these material systems, designers must be aware of several innate features, including the degrading ability of ceramics to carry sustained load. Usually, time-dependent failure in ceramics occurs because of two different, delayedfailure mechanisms: slow crack growth and creep rupture. Slow crack growth initiates at a preexisting flaw and continues until a critical crack length is reached, causing catastrophic failure. Creep rupture, on the other hand, occurs because of bulk damage in the material: void nucleation and coalescence that eventually leads to macrocracks which then propagate to failure. Successful application of advanced ceramics depends on proper characterization of material behavior and the use of an appropriate design methodology. The life of a ceramic component can be predicted with the NASA Lewis Research Center's Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design programs. CARES/CREEP determines the expected life of a component under creep conditions, and CARES/LIFE predicts the component life due to fast fracture and subcritical crack growth. The previously developed CARES/LIFE program has been used in numerous industrial and Government applications.

Prediction of expected years of life using whole-genome markers.

Directory of Open Access Journals (Sweden)

Gustavo de los Campos

Full Text Available Genetic factors are believed to account for 25% of the interindividual differences in Years of Life (YL among humans. However, the genetic loci that have thus far been found to be associated with YL explain a very small proportion of the expected genetic variation in this trait, perhaps reflecting the complexity of the trait and the limitations of traditional association studies when applied to traits affected by a large number of small-effect genes. Using data from the Framingham Heart Study and statistical methods borrowed largely from the field of animal genetics (whole-genome prediction, WGP, we developed a WGP model for the study of YL and evaluated the extent to which thousands of genetic variants across the genome examined simultaneously can be used to predict interindividual differences in YL. We find that a sizable proportion of differences in YL--which were unexplained by age at entry, sex, smoking and BMI--can be accounted for and predicted using WGP methods. The contribution of genomic information to prediction accuracy was even higher than that of smoking and body mass index (BMI combined; two predictors that are considered among the most important life-shortening factors. We evaluated the impacts of familial relationships and population structure (as described by the first two marker-derived principal components and concluded that in our dataset population structure explained partially, but not fully the gains in prediction accuracy obtained with WGP. Further inspection of prediction accuracies by age at death indicated that most of the gains in predictive ability achieved with WGP were due to the increased accuracy of prediction of early mortality, perhaps reflecting the ability of WGP to capture differences in genetic risk to deadly diseases such as cancer, which are most often responsible for early mortality in our sample.

Longitudinal Prediction of Quality-of-Life Scores and Locomotion in Individuals With Traumatic Spinal Cord Injury.

Science.gov (United States)

Hiremath, Shivayogi V; Hogaboom, Nathan S; Roscher, Melissa R; Worobey, Lynn A; Oyster, Michelle L; Boninger, Michael L

2017-12-01

To examine (1) differences in quality-of-life scores for groups based on transitions in locomotion status at 1, 5, and 10 years postdischarge in a sample of people with spinal cord injury (SCI); and (2) whether demographic factors and transitions in locomotion status can predict quality-of-life measures at these time points. Retrospective case study of the National SCI Database. Model SCI Systems Centers. Individuals with SCI (N=10,190) from 21 SCI Model Systems Centers, identified through the National SCI Model Systems Centers database between the years 1985 and 2012. Subjects had FIM (locomotion mode) data at discharge and at least 1 of the following: 1, 5, or 10 years postdischarge. Not applicable. FIM-locomotion mode; Severity of Depression Scale; Satisfaction With Life Scale; and Craig Handicap Assessment and Reporting Technique. Participants who transitioned from ambulation to wheelchair use reported lower participation and life satisfaction, and higher depression levels (P.05) or life satisfaction (P>.05) compared with those who transitioned from wheelchair to ambulation. Demographic factors and locomotion transitions predicted quality-of-life scores at all time points (P<.05). The results of this study indicate that transitioning from ambulation to wheelchair use can negatively impact psychosocial health 10 years after SCI. Clinicians should be aware of this when deciding on ambulation training. Further work to characterize who may be at risk for these transitions is needed. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Data-Based Predictive Control with Multirate Prediction Step

Science.gov (United States)

Barlow, Jonathan S.

2010-01-01

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

A naive Bayes model for robust remaining useful life prediction of lithium-ion battery

International Nuclear Information System (INIS)

Ng, Selina S.Y.; Xing, Yinjiao; Tsui, Kwok L.

2014-01-01

Highlights: • Robustness of RUL predictions for lithium-ion batteries is analyzed quantitatively. • RUL predictions of the same battery over cycle life are evaluated. • RUL predictions of batteries over different operating conditions are evaluated. • Naive Bayes (NB) is proposed for predictions under constant discharge environments. • Its robustness and accuracy are compared with that of support vector machine (SVM). - Abstract: Online state-of-health (SoH) estimation and remaining useful life (RUL) prediction is a critical problem in battery health management. This paper studies the modeling of battery degradation under different usage conditions and ambient temperatures, which is seldom considered in the literature. Li-ion battery RUL prediction under constant operating conditions at different values of ambient temperature and discharge current are considered. A naive Bayes (NB) model is proposed for RUL prediction of batteries under different operating conditions. It is shown in this analysis that under constant discharge environments, the RUL of Li-ion batteries can be predicted with the NB method, irrespective of the exact values of the operating conditions. The case study shows that the NB generates stable and competitive prediction performance over that of the support vector machine (SVM). This also suggests that, while it is well known that the environmental conditions have big impact on the degradation trend, it is the changes in operating conditions of a Li-ion battery over cycle life that makes the Li-ion battery degradation and RUL prediction even more difficult

Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions.

Science.gov (United States)

Hauri, D D; Huss, A; Zimmermann, F; Kuehni, C E; Röösli, M

2013-10-01

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Fatigue Life Analysis and Prediction of 316L Stainless Steel Under Low Cycle Fatigue Loading

Energy Technology Data Exchange (ETDEWEB)

Oh, Hyeong; Myung, NohJun; Choi, Nak-Sam [Hanyang Univ., Seoul (Korea, Republic of)

2016-12-15

In this study, a strain-controlled fatigue test of widely-used 316L stainless steel with excellent corrosion resistance and mechanical properties was conducted, in order to assess its fatigue life. Low cycle fatigue behaviors were analyzed at room temperature, as a function of the strain amplitude and strain ratio. The material was hardened during the initial few cycles, and then was softened during the long post period, until failure occurred. The fatigue life decreased with increasing strain amplitude. Masing behavior in the hysteresis loop was shown under the low strain amplitude, whereas the high strain amplitude caused non-Masing behavior and reduced the mean stress. Low cycle fatigue life prediction based on the cyclic plastic energy dissipation theory, considering Masing and non-Masing effects, showed a good correlation with the experimental results.

Fatigue life prediction method for contact wire using maximum local stress

Energy Technology Data Exchange (ETDEWEB)

Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean [Sungkyunkwan University, Suwon (Korea, Republic of); Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon [Korea Railroad Research Institute, Uiwang (Korea, Republic of)

2015-01-15

Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

Fatigue life prediction method for contact wire using maximum local stress

International Nuclear Information System (INIS)

Kim, Yong Seok; Haochuang, Li; Seok, Chang Sung; Koo, Jae Mean; Lee, Ki Won; Kwon, Sam Young; Cho, Yong Hyeon

2015-01-01

Railway contact wires supplying electricity to trains are exposed to repeated mechanical strain and stress caused by their own weight and discontinuous contact with a pantograph during train operation. Since the speed of railway transportation has increased continuously, railway industries have recently reported a number of contact wire failures caused by mechanical fatigue fractures instead of normal wear, which has been a more common failure mechanism. To secure the safety and durability of contact wires in environments with increased train speeds, a bending fatigue test on contact wire has been performed. The test equipment is too complicated to evaluate the fatigue characteristics of contact wire. Thus, the axial tension fatigue test was performed for a standard specimen, and the bending fatigue life for the contact wire structure was then predicted using the maximum local stress occurring at the top of the contact wire. Lastly, the tested bending fatigue life of the structure was compared with the fatigue life predicted by the axial tension fatigue test for verification.

FORMULASI TEPUNG PENYALUT BERBASIS TEPUNG JAGUNG DAN PENENTUAN UMUR SIMPANNYA DENGAN PENDEKATAN KADAR AIR KRITIS [Formulation of Corn Flour-Based Batter and Prediction of Its Shelf Life using Critical Moisture Approach

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Sugiyono1*

2010-12-01

Full Text Available The objectives of this study were to obtain the best formula for corn flour-based batter and to predict its shelf life using critical moisture approach. According to a hedonic test, the best batter formula was composed of 60% corn flour, 12.5% rice flour, 12.5% tapioca starch, and 15% glutinous rice flour. Addition of glutinous rice flour in the formula changed the proportion of amylose and amylopectin in the batter. As a result, the retrogradation of the batter decreased and the texture of its fried product was preferred. A critical moisture approach was used to predict the shelf life of the batter. The critical moisture content of the batter was 0.16 g H2O/g solid.The isotherm sorption phenomenon of the batter was best described using Hasley model. The shelf life of the product was 7 months when packaged in polypropylene (0,07 g/m2day.mmHg at 85% RH.

Academic Life Satisfaction Scale (ALSS) and Its Effectiveness in Predicting Academic Success

Science.gov (United States)

Kumar, P.K. Sudheesh; P., Dileep

2006-01-01

This study is undertaken to examine the effectiveness of a newly constructed psychometric instrument to assess Academic Life Satisfaction along with the components of Emotional Intelligence. The Academic Life Satisfaction Scale is used to predict the scholastic achievement as an index of Academic success. The investigators found that Academic Life…

Basic traits predict the prevalence of personality disorder across the life span: the example of psychopathy.

Science.gov (United States)

Vachon, David D; Lynam, Donald R; Widiger, Thomas A; Miller, Joshua D; McCrae, Robert R; Costa, Paul T

2013-05-01

Personality disorders (PDs) may be better understood in terms of dimensions of general personality functioning rather than as discrete categorical conditions. Personality-trait descriptions of PDs are robust across methods and settings, and PD assessments based on trait measures show good construct validity. The study reported here extends research showing that basic traits (e.g., impulsiveness, warmth, straightforwardness, modesty, and deliberation) can re-create the epidemiological characteristics associated with PDs. Specifically, we used normative changes in absolute trait levels to simulate age-related differences in the prevalence of psychopathy in a forensic setting. Results demonstrated that trait information predicts the rate of decline for psychopathy over the life span; discriminates the decline of psychopathy from that of a similar disorder, antisocial PD; and accurately predicts the differential decline of subfactors of psychopathy. These findings suggest that basic traits provide a parsimonious account of PD prevalence across the life span.

Support vector machine based estimation of remaining useful life: current research status and future trends

International Nuclear Information System (INIS)

Huang, Hong Zhong; Wang, Hai Kun; Li, Yan Feng; Zhang, Longlong; Liu, Zhiliang

2015-01-01

Estimation of remaining useful life (RUL) is helpful to manage life cycles of machines and to reduce maintenance cost. Support vector machine (SVM) is a promising algorithm for estimation of RUL because it can easily process small training sets and multi-dimensional data. Many SVM based methods have been proposed to predict RUL of some key components. We did a literature review related to SVM based RUL estimation within a decade. The references reviewed are classified into two categories: improved SVM algorithms and their applications to RUL estimation. The latter category can be further divided into two types: one, to predict the condition state in the future and then build a relationship between state and RUL; two, to establish a direct relationship between current state and RUL. However, SVM is seldom used to track the degradation process and build an accurate relationship between the current health condition state and RUL. Based on the above review and summary, this paper points out that the ability to continually improve SVM, and obtain a novel idea for RUL prediction using SVM will be future works.

Decomposition Technique for Remaining Useful Life Prediction

Science.gov (United States)

Saha, Bhaskar (Inventor); Goebel, Kai F. (Inventor); Saxena, Abhinav (Inventor); Celaya, Jose R. (Inventor)

2014-01-01

The prognostic tool disclosed here decomposes the problem of estimating the remaining useful life (RUL) of a component or sub-system into two separate regression problems: the feature-to-damage mapping and the operational conditions-to-damage-rate mapping. These maps are initially generated in off-line mode. One or more regression algorithms are used to generate each of these maps from measurements (and features derived from these), operational conditions, and ground truth information. This decomposition technique allows for the explicit quantification and management of different sources of uncertainty present in the process. Next, the maps are used in an on-line mode where run-time data (sensor measurements and operational conditions) are used in conjunction with the maps generated in off-line mode to estimate both current damage state as well as future damage accumulation. Remaining life is computed by subtracting the instance when the extrapolated damage reaches the failure threshold from the instance when the prediction is made.

The development of techniques for determining the residual life time prediction on NPP equipment

International Nuclear Information System (INIS)

Antonov, Alexander V.; Dagaev, Alexander V.; Volnikov, Ivan S.

1999-01-01

The problem of determining the residual life prediction of NPP equipment is presently highly pressing. NPP residual life resources are 30 years, but for particular equipment it is much less. Thus, residual life resource for equipment of control and protection system of NPP unit is 5-10 years. The NPP equipment is expensive and its replacing requires much expense. Hence an urgent problem is to study residual life resources of equipment on the basis of statistic information obtained during operation. Deterministic approach of determining residual life resources for particular equipment is widely known in the literature. Physical and statistical models are also being developed for determining the residual life, e.g. the model (loading-bearing capability). The present work offers the techniques of the residual life determination reasoning from statistic information of functioning objects in the process of operation. To put the techniques into effect it is necessary to have information about the time of operation of a group of objects of the same type, the number of failures; it is desirable to know failure operating time, order of the object replacement and the reason which caused the replacement (failure or planned preventive maintenance). Metrics is based on studying the parameters for the series of failures resulted from real statistic data. Then we can proceed to distribution density of the failure working time. For this purpose the Voltarra's equation of the second order is solved f(t) = ω(t) + ∫ 0 t f(t - τ)ω(τ)dτ. Since statistics of data sampling related to failure is small due to difficulties in solution of Voltaire's equation, the authors offer moderate method of solution for the above equation. After distribution density of the failure working time is determined the calculation of equipment residual life is made by the following formula: T τ (t) 1/P(τ)∫ 0 ∞ P(t)dt. The proposed techniques are realised as the software. In the course of working

Fuzzy Activity Based Life Cycle Costing For Repairable Equipment

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Mulubrhan Freselam

2016-01-01

Full Text Available Life-cycle cost (LCC is the much known method used for decision making that considers all costs in the life of a system or equipment. Predicting LCCs is fraught with potential errors, owing to the uncertainty in future events, future costs, interest rates, and even hidden costs. These uncertainties have a direct impact on the decision making. Activity based LCC is used to identify the activities and cost drivers in acquisition, operation and maintenance phase. This activity based LCC is integrated with fuzzy set theory and interval mathematics to model these uncertainties. Day–Stout–Warren (DSW algorithm and the vertex method are then used to evaluate competing alternatives. A case of two pumps (Pump A and Pump B are taken and their LCC is analysed using the developed model. The equivalent annual cost of Pump B is greater than Pump A, which leads the decision maker to choose Pump A over Pump B.

Impact evaluation of rolling contact fatigue life models

International Nuclear Information System (INIS)

Choi, Young Sik; Yang, Xiaoping

2012-01-01

Since the accurate prediction of fatigue life has a significant value, many researchers have attempted to develop a reliable fatigue life model. Recently, rolling contact fatigue life models incorporating machining impact were developed. These models have contributed to a significant improvement in prediction accuracy as compared with earlier models, thus representing a major step forward in the modeling effort. This paper compares the prediction accuracy of these models with that of the prediction method in International Standards. When α is set to 0.25, the observed improvement of prediction accuracy as measured by variance of prediction errors due to these models over that due to prediction method in International Standards is statistically significant. Impact analyses of such improvement are conducted to illustrate its value. It is further noted that while difference was observed between the variance of prediction errors due to the crack initiation life model based on a dislocation model and that due to the crack initiation life model based on a local stress-life curve, the observed difference is not statistically significant

Above-knee prosthesis design based on fatigue life using finite element method and design of experiment.

Science.gov (United States)

Phanphet, Suwattanarwong; Dechjarern, Surangsee; Jomjanyong, Sermkiat

2017-05-01

The main objective of this work is to improve the standard of the existing design of knee prosthesis developed by Thailand's Prostheses Foundation of Her Royal Highness The Princess Mother. The experimental structural tests, based on the ISO 10328, of the existing design showed that a few components failed due to fatigue under normal cyclic loading below the required number of cycles. The finite element (FE) simulations of structural tests on the knee prosthesis were carried out. Fatigue life predictions of knee component materials were modeled based on the Morrow's approach. The fatigue life prediction based on the FE model result was validated with the corresponding structural test and the results agreed well. The new designs of the failed components were studied using the design of experimental approach and finite element analysis of the ISO 10328 structural test of knee prostheses under two separated loading cases. Under ultimate loading, knee prosthesis peak von Mises stress must be less than the yield strength of knee component's material and the total knee deflection must be lower than 2.5mm. The fatigue life prediction of all knee components must be higher than 3,000,000 cycles under normal cyclic loading. The design parameters are the thickness of joint bars, the diameter of lower connector and the thickness of absorber-stopper. The optimized knee prosthesis design meeting all the requirements was recommended. Experimental ISO 10328 structural test of the fabricated knee prosthesis based on the optimized design confirmed the finite element prediction. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Prediction of inelastic behavior and creep-fatigue life of perforated plates

International Nuclear Information System (INIS)

Igari, Toshihide; Setoguchi, Katsuya; Nakano, Shohki; Nomura, Shinichi

1991-01-01

Prediction methods of macroscopic and local stress-strain behavior of perforated plates in plastic and creep regime which are proposed by the authors are applied to the inelastic analysis and creep-fatigue life prediction of perforated cylinder subjected to cyclic thermal stress. Stress-strain behavior of perforated cylinder is analyzed by modeling the perforated portion to cylinder with equivalent-solid-plate properties. Creep-fatigue lives at around a hole of perforated plates are predicted by using the local stress-strain behavior and are compared with experimentally observed lives. (author)

A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

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Wen-An Yang

2016-01-01

Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

Do Proxies for the Neurotransmitter Cortisol Predict Adaptation to Life with Chronic Pain?

Science.gov (United States)

Deamond, Wade

Among the numerous difficulties encountered by chronic pain patients, impulsive and dysfunctional decision-making complicate their already difficult life situations yet remains relatively understudied. This study examined a recently published neurobiological decision making model that identifies eight specific neurotransmitters and hormones (Dopamine, Testosterone, Endogenous Opioids Glutamate, Serotonin, Norepinephrine, Cortisol, and GABA) linked to unsound decision making related to cognitive, motivational and emotional dysregulation (Nussbaum et al., 2011) (see Appendix 2). The Perceived Stress Scale (PSS), a proxy for the cortisol element in the pharmacological decision making model was analyzed for the neurotransmitter's relationship to functionality and quality of life in a group of 37 chronic pain patients. Participants were comprised of males and females ranging from 23 to 52 years of age and were classified with respect to levels of adjustment to living with chronic pain based on the Quality of Life Scale (QLS), the Dartmouth WONCA COOP Charts and the Global Assessment of Functioning (GAF). The Iowa Gambling Task (IGT) and Frontal System Behavioral Scale (FSBS) measured decision making related to immediate gratification and daily living respectively. Results suggest that emotional dysregulation, as measured by the PSS is a significant predictor for adaptation to life with chronic pain and the PSS is superior to predicting adaptation to life with chronic pain than reported levels of pain as measured by the McGill Pain Questionnaire.

Evaluation of creep residual life for modified 9Cr-1Mo steel based on Omega method

International Nuclear Information System (INIS)

Nonaka, Isamu; Torihata, Shoji; Kihara, Shigemitu; Umaki, Hideo; Maruyama, Kouichi.

1997-01-01

In order to study the accuracy of creep residual life prediction by the Omega method which is based on creep deformation, a series of creep tests on modified 9Cr-1Mo steel were conducted at 500degC, 550degC and 600degC, and the Omega method was applied to the residual life estimation. The main results obtained are as follows: (1) There was a obvious linear portion, which corresponded to the tertiary creep, in the relationship between logarithm of strain and strain. So it was easy to define the Omega value as a gradient of linear portion. (2) It was proved that the Omega value depended on stress and temperature in such a way as it was the larger, the lower the stress and the lower the temperature. (3) By using the Omega value and strain rate which were determined experimentally, the residual life could be predicted within a factor of 1.5 at the stage of 50% and 80% of actual life. It was confirmed that the accuracy of this method was higher than that of the former method based on rupture time. (4) To apply this method to the residual life evaluation of operating plant materials, the Omega value has to be determined in the lower stress condition. So it is important to develop the extrapolation method of the Omega value based on the laboratory acceleration test to the longer service life. (author)

Anisotropic Elastoplastic Damage Mechanics Method to Predict Fatigue Life of the Structure

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Hualiang Wan

2016-01-01

Full Text Available New damage mechanics method is proposed to predict the low-cycle fatigue life of metallic structures under multiaxial loading. The microstructure mechanical model is proposed to simulate anisotropic elastoplastic damage evolution. As the micromodel depends on few material parameters, the present method is very concise and suitable for engineering application. The material parameters in damage evolution equation are determined by fatigue experimental data of standard specimens. By employing further development on the ANSYS platform, the anisotropic elastoplastic damage mechanics-finite element method is developed. The fatigue crack propagation life of satellite structure is predicted using the present method and the computational results comply with the experimental data very well.

USING CONDITION MONITORING TO PREDICT REMAINING LIFE OF ELECTRIC CABLES

International Nuclear Information System (INIS)

LOFARO, R.; SOO, P.; VILLARAN, M.; GROVE, E.

2001-01-01

Electric cables are passive components used extensively throughout nuclear power stations to perform numerous safety and non-safety functions. It is known that the polymers commonly used to insulate the conductors on these cables can degrade with time; the rate of degradation being dependent on the severity of the conditions in which the cables operate. Cables do not receive routine maintenance and, since it can be very costly, they are not replaced on a regular basis. Therefore, to ensure their continued functional performance, it would be beneficial if condition monitoring techniques could be used to estimate the remaining useful life of these components. A great deal of research has been performed on various condition monitoring techniques for use on electric cables. In a research program sponsored by the U.S. Nuclear Regulatory Commission, several promising techniques were evaluated and found to provide trendable information on the condition of low-voltage electric cables. These techniques may be useful for predicting remaining life if well defined limiting values for the aging properties being measured can be determined. However, each technique has advantages and limitations that must be addressed in order to use it effectively, and the necessary limiting values are not always easy to obtain. This paper discusses how condition monitoring measurements can be used to predict the remaining useful life of electric cables. The attributes of an appropriate condition monitoring technique are presented, and the process to be used in estimating the remaining useful life of a cable is discussed along with the difficulties that must be addressed

Physics-based Modeling Tools for Life Prediction and Durability Assessment of Advanced Materials, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The technical objectives of this program are: (1) to develop a set of physics-based modeling tools to predict the initiation of hot corrosion and to address pit and...

Fatigue, fracture, and life prediction criteria for composite materials in magnets

International Nuclear Information System (INIS)

Wong, F.M.G.

1990-06-01

An explosively-bonded copper/Inconel 718/copper laminate conductor was proposed to withstand the severe face compression stresses in the central core of the Alcator C-MOD tokamak toroidal field (TF) magnet. Due to the severe duty of the TF magnet, it is critical that an accurate estimate of useful life be determined. As part of the effort to formulate an appropriate life prediction, fatigue crack growth experiments were performed on the laminate as well as its components. Metallographic evaluation of the laminate interface revealed many shear bands in the Inconel 718. Shear bands and shear band cracks were produced in the Inconel 718 as a result of the explosion bonding process. These shear bands were shown to have a detrimental effect on the crack growth behavior of the laminate, by significantly reducing the load carrying capability of the reinforcement layer and providing for easy crack propagation paths. Fatigue crack growth rate was found not only to be dependent on temperature but also on orientation. Fatigue cracks grew faster in directions which contained shear bands in the plane of the propagating crack. Fractography showed crack advancement by fatigue cracking in the Inconel 718 and ductile tearing of the copper at the interface. However, further away from the interfaces, the copper exhibited fatigue striations indicating that cracks were now propagating by fatigue. Laminate life prediction results showed a strong dependence on shear band orientation, and exhibited little variation between room temperature and 77 degree K. Predicted life of this laminate was lower when the crack propagation was along a shear band than when crack propagation was across the shear bands. Shear bands appear to have a dominating effect on crack growth behavior

Measurement techniques and instruments suitable for life-prediction testing of photovoltaic arrays. Interim report

Energy Technology Data Exchange (ETDEWEB)

Noel, G.T.; Sliemers, F.A.; Deringer, G.C.; Wood, V.E.; Wilkes, K.E.; Gaines, G.B.; Carmichael, D.C.

1978-01-15

The validation of a service life of 20 years for low-cost photovoltaic arrays must be accomplished through accelerated life-prediction tests. A methodology for such tests has been developed in a preceding study. The results discussed consist of the initial identification and assessment of all known measurement techniques and instruments that might be used in these life-prediction tests. Array failure modes, relevant materials property changes, and primary degradation mechanisms are discussed as a prerequisite to identifying suitable measurement techniques and instruments. Candidate techniques and instruments are identified on the basis of extensive reviews of published and unpublished information. These methods are organized in six measurement categories--chemical, electrical, optical, thermal, mechanical, and ''other physicals''. Using specified evaluation criteria, the most promising techniques and instruments for use in life-prediction tests of arrays are then selected. These recommended techniques and their characteristics are described. Recommendations are made regarding establishment of the adequacy, particularly with respect to precision, of the more fully developed techniques for this application, and regarding the experimental evaluation of promising developmental techniques. Measurement needs not satisfied by presently available techniques/instruments are also identified.

A proposal of predictive methods of crack propagation life and remaining life of structural metal under creep-fatigue interacted conditions by use of X-ray profile analysis

International Nuclear Information System (INIS)

Ohnami, M.; Sakane, M.; Nishino, S.

1987-01-01

The following two series of studies are described: One is crack propagation life prediction in high-temperature low-cycle fatigue tests under triangular and trapezoidal strain or stress waves for austenitic stainless steel by X-ray fractography. Another is remaining life prediction of the steel under creep-fatigue interacted conditions by applying the concept of the remaining life diagram and X-ray profile analysis. Particle size and microstrain obtained by X-ray profile analysis were effective nondestructive parameters for estimating crack propagation life and remaining life in creep-fatigue interaction

Cyclic softening as a parameter for prediction of remnant creep rupture life of a Indian reduced activation ferritic–martensitic (IN-RAFM) steel subjected to fatigue exposures

Energy Technology Data Exchange (ETDEWEB)

Sarkar, Aritra, E-mail: aritra@igcar.gov.in [Metallurgy and Materials Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Vijayanand, V.D.; Shankar, Vani; Parameswaran, P.; Sandhya, R.; Laha, K.; Mathew, M.D.; Jayakumar, T. [Metallurgy and Materials Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Rajendrakumar, E. [Institute for Plasma Research, Bhat, Gandhinagar, Gujarat (India)

2014-12-15

Sequential fatigue-creep tests were conducted on Indian reduced activation ferritic–martensitic steel at 823 K leading to sharp decrease in residual creep life with increase in prior fatigue exposures. Extensive recovery of martensitic-lath structure taking place during fatigue deformation, manifested as cyclic softening in the cyclic stress response, shortens the residual creep life. Based on the experimental results, cyclic softening occurring during fatigue stage can be correlated with residual creep life, evolving in an empirical model which predicts residual creep life as a function of cyclic softening. Predicted creep lives for specimens pre-cycled at various strain amplitudes are explained on the basis of mechanism of cyclic softening.

Influences of cyclic deformation on creep property and creep-fatigue life prediction considering them

International Nuclear Information System (INIS)

Takahashi, Yukio

2009-01-01

Evaluation of creep-fatigue is essential in design and life management of high-temperature components in power generation plants. Cyclic deformation may alter creep property of the materials and its consideration may improve predictability of creep-fatigue failure life. To understand them, creep tests were conducted for the materials subjected to cyclic loading and their creep rupture and deformation behaviors were compared with those of as-received materials. Both 316FR and modified 9Cr-1Mo steel were tested. (1) Creep rupture time and elongation generally tend to decrease with cyclic loading in both materials, and especially elongation of 316FR drastically decreases by being cyclically deformed. (2) Amount of primary creep deformation decreases by cyclic loading and the ways to improve its predictability were developed. (3) Use of creep rupture ductility after cyclic deformation, instead of that of as-received material, brought about clear improvement of life prediction in a modified ductility exhaustion approach. (author)

A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

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Fernando Sánchez Lasheras

2015-03-01

Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

Surrogate inaccuracy in predicting older adults' desire for life-sustaining interventions in the event of decisional incapacity: is it due in part to erroneous quality-of-life assessments?

Science.gov (United States)

Bravo, Gina; Sene, Modou; Arcand, Marcel

2017-07-01

Family members are often called upon to make decisions for an incapacitated relative. Yet they have difficulty predicting a loved one's desire to receive treatments in hypothetical situations. We tested the hypothesis that this difficulty could in part be explained by discrepant quality-of-life assessments. The data come from 235 community-dwelling adults aged 70 years and over who rated their quality of life and desire for specified interventions in four health states (current state, mild to moderate stroke, incurable brain cancer, and severe dementia). All ratings were made on Likert-type scales. Using identical rating scales, a surrogate chosen by the older adult was asked to predict the latter's responses. Linear mixed models were fitted to determine whether differences in quality-of-life ratings between the older adult and surrogate were associated with surrogates' inaccuracy in predicting desire for treatment. The difference in quality-of-life ratings was a significant predictor of prediction inaccuracy for the three hypothetical health states (p quality of life compared to the older adult, the more he or she overestimated the older adult's desire to be treated. Discrepant quality-of-life ratings are associated with surrogates' difficulty in predicting desire for life-sustaining interventions in hypothetical situations. This finding underscores the importance of discussing anticipated quality of life in states of cognitive decline, to better prepare family members for making difficult decisions for their loved ones. ISRCTN89993391.

Menopausal symptoms: do life events predict severity of symptoms in peri- and post-menopause?

Science.gov (United States)

Pimenta, Filipa; Leal, Isabel; Maroco, João; Ramos, Catarina

2012-08-01

Hormonal changes during menopausal transition are linked to physical and psychological symptoms' emergence. This study aims to explore if life events predict menopausal symptoms. This cross-sectional research encompasses a community sample of 992 women who answered to socio-demographic, health, menopause-related and lifestyle questionnaires; menopausal symptoms and life events were assessed with validated instruments. Structural equation modeling was used to build a causal model. Menopausal status predicted only three symptoms: skin/facial hair changes (β=.136; p=.020), sexual (β=.157; p=.004) and, marginally, vasomotor symptoms (β=.094; p=.054). Life events predicted depressive mood (β=-.391; p=.002), anxiety (β=-.271; p=.003), perceived cognitive impairment (β=-.295; p=.003), body shape changes (β=-.136; p=.031), aches/pain (β=-.212; p=.007), skin/facial hair changes (β=-.171; p=.021), numbness (β=-.169; p=.015), perceived loss of control (β=-.234; p=.008), mouth, nails and hair changes (β=-.290; p=.004), vasomotor (β=-.113; p=.044) and sexual symptoms (β=-.208; p=.009). Although women in peri- and post-menopausal manifested higher symptoms' severity than their pre-menopausal counterparts, only three of the menopausal symptoms assessed were predicted by menopausal status. Since the vast majority of menopausal symptoms' severity was significantly influenced by the way women perceived their recent life events, it is concluded that the symptomatology exacerbation, in peri- and post-menopausal women, might be due to life conditions and events, rather than hormonal changes (nonetheless, the inverse influence should be investigated in future studies). Therefore, these should be accounted for in menopause-related clinical and research settings. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Comparing Structural Identification Methodologies for Fatigue Life Prediction of a Highway Bridge

Directory of Open Access Journals (Sweden)

Sai G. S. Pai

2018-01-01

Full Text Available Accurate measurement-data interpretation leads to increased understanding of structural behavior and enhanced asset-management decision making. In this paper, four data-interpretation methodologies, residual minimization, traditional Bayesian model updating, modified Bayesian model updating (with an L∞-norm-based Gaussian likelihood function, and error-domain model falsification (EDMF, a method that rejects models that have unlikely differences between predictions and measurements, are compared. In the modified Bayesian model updating methodology, a correction is used in the likelihood function to account for the effect of a finite number of measurements on posterior probability–density functions. The application of these data-interpretation methodologies for condition assessment and fatigue life prediction is illustrated on a highway steel–concrete composite bridge having four spans with a total length of 219 m. A detailed 3D finite-element plate and beam model of the bridge and weigh-in-motion data are used to obtain the time–stress response at a fatigue critical location along the bridge span. The time–stress response, presented as a histogram, is compared to measured strain responses either to update prior knowledge of model parameters using residual minimization and Bayesian methodologies or to obtain candidate model instances using the EDMF methodology. It is concluded that the EDMF and modified Bayesian model updating methodologies provide robust prediction of fatigue life compared with residual minimization and traditional Bayesian model updating in the presence of correlated non-Gaussian uncertainty. EDMF has additional advantages due to ease of understanding and applicability for practicing engineers, thus enabling incremental asset-management decision making over long service lives. Finally, parallel implementations of EDMF using grid sampling have lower computations times than implementations using adaptive sampling.

Prediction of Lumen Output and Chromaticity Shift in LEDs Using Kalman Filter and Extended Kalman Filter Based Models

Energy Technology Data Exchange (ETDEWEB)

Lall, Pradeep; Wei, Junchao; Davis, J Lynn

2014-06-24

Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have

Revealing life-history traits by contrasting genetic estimations with predictions of effective population size.

Science.gov (United States)

Greenbaum, Gili; Renan, Sharon; Templeton, Alan R; Bouskila, Amos; Saltz, David; Rubenstein, Daniel I; Bar-David, Shirli

2017-12-22

Effective population size, a central concept in conservation biology, is now routinely estimated from genetic surveys and can also be theoretically predicted from demographic, life-history, and mating-system data. By evaluating the consistency of theoretical predictions with empirically estimated effective size, insights can be gained regarding life-history characteristics and the relative impact of different life-history traits on genetic drift. These insights can be used to design and inform management strategies aimed at increasing effective population size. We demonstrated this approach by addressing the conservation of a reintroduced population of Asiatic wild ass (Equus hemionus). We estimated the variance effective size (N ev ) from genetic data (N ev =24.3) and formulated predictions for the impacts on N ev of demography, polygyny, female variance in lifetime reproductive success (RS), and heritability of female RS. By contrasting the genetic estimation with theoretical predictions, we found that polygyny was the strongest factor affecting genetic drift because only when accounting for polygyny were predictions consistent with the genetically measured N ev . The comparison of effective-size estimation and predictions indicated that 10.6% of the males mated per generation when heritability of female RS was unaccounted for (polygyny responsible for 81% decrease in N ev ) and 19.5% mated when female RS was accounted for (polygyny responsible for 67% decrease in N ev ). Heritability of female RS also affected N ev ; hf2=0.91 (heritability responsible for 41% decrease in N ev ). The low effective size is of concern, and we suggest that management actions focus on factors identified as strongly affecting Nev, namely, increasing the availability of artificial water sources to increase number of dominant males contributing to the gene pool. This approach, evaluating life-history hypotheses in light of their impact on effective population size, and contrasting

Numerical analysis of rolling contact fatigue crack initiation and fatigue life prediction of the railway crossing

OpenAIRE

Xin, L.; Markine, V.L.; Shevtsov, I.

2015-01-01

The procedure for analysing rolling contact fatigue crack initiation and fatigue life prediction of the railway turnout crossing is developed. A three-dimensional finite element (FE) model is used to obtain stress and strain results, considering the dynamic effects of wheel-crossing rolling contact. Material model accounting for elastic- plastic isotropic and kinematic hardening effects is adopted. The results from FE analysis are combined with J-S fatigue model that is based on critical plan...

Creep-fatigue life prediction for different heats of Type 304 stainless steel by linear-damage rule, strain-range partitioning method, and damage-rate approach

International Nuclear Information System (INIS)

Maiya, P.S.

1978-07-01

The creep-fatigue life results for five different heats of Type 304 stainless steel at 593 0 C (1100 0 F), generated under push-pull conditions in the axial strain-control mode, are presented. The life predictions for the various heats based on the linear-damage rule, strain-range partitioning method, and damage-rate approach are discussed. The appropriate material properties required for computation of fatigue life are also included

Predicting quality of life in pediatric asthma: the role of emotional competence and personality.

Science.gov (United States)

Lahaye, Magali; Van Broeck, Nady; Bodart, Eddy; Luminet, Olivier

2013-05-01

The present study examined the predictive value of emotional competence and the five-factor model of personality on the quality of life of children with asthma. Participants were 90 children (M age = 11.73, SD = 2.60) having controlled and partly controlled asthma, undergoing everyday treatment. Children filled in questionnaires assessing emotional competence and quality of life. Parents completed questionnaires assessing the personality of their child. Results showed that two emotional competences, bodily awareness and verbal sharing of emotions, were related to the quality of life of children with asthma. Moreover, one personality trait, benevolence, was associated with children's quality of life. Regression analyses showed that the predictive value of these three dimensions remained significant over and above asthma control and socio-demographic variables frequently associated with the quality of life of children with asthma (age, gender, and educational level of parents). These findings emphasize the importance of alerting the clinician who works with children with asthma to observe and assess the child's expression of emotions, attention to bodily sensations, and benevolence.

Shelf life prediction of apple brownies using accelerated method

Science.gov (United States)

Pulungan, M. H.; Sukmana, A. D.; Dewi, I. A.

2018-03-01

The aim of this research was to determine shelf life of apple brownies. Shelf life was determined with Accelerated Shelf Life Testing method and Arrhenius equation. Experiment was conducted at 25, 35, and 45°C for 30 days. Every five days, the sample was analysed for free fatty acid (FFA), water activity (Aw), and organoleptic acceptance (flavour, aroma, and texture). The shelf life of the apple brownies based on FFA were 110, 54, and 28 days at temperature of 25, 35, and 45°C, respectively.

Modeling size effects on fatigue life of a zirconium-based bulk metallic glass under bending

International Nuclear Information System (INIS)

Yuan Tao; Wang Gongyao; Feng Qingming; Liaw, Peter K.; Yokoyama, Yoshihiko; Inoue, Akihisa

2013-01-01

A size effect on the fatigue-life cycles of a Zr 50 Cu 30 Al 10 Ni 10 (at.%) bulk metallic glass has been observed in the four-point-bending fatigue experiment. Under the same bending-stress condition, large-sized samples tend to exhibit longer fatigue lives than small-sized samples. This size effect on the fatigue life cannot be satisfactorily explained by the flaw-based Weibull theories. Based on the experimental results, this study explores possible approaches to modeling the size effects on the bending-fatigue life of bulk metallic glasses, and proposes two fatigue-life models based on the Weibull distribution. The first model assumes, empirically, log-linear effects of the sample thickness on the Weibull parameters. The second model incorporates the mechanistic knowledge of the fatigue behavior of metallic glasses, and assumes that the shear-band density, instead of the flaw density, has significant influence on the bending fatigue-life cycles. Promising predictive results provide evidence of the potential validity of the models and their assumptions.

Predicting tool life in turning operations using neural networks and image processing

Science.gov (United States)

Mikołajczyk, T.; Nowicki, K.; Bustillo, A.; Yu Pimenov, D.

2018-05-01

A two-step method is presented for the automatic prediction of tool life in turning operations. First, experimental data are collected for three cutting edges under the same constant processing conditions. In these experiments, the parameter of tool wear, VB, is measured with conventional methods and the same parameter is estimated using Neural Wear, a customized software package that combines flank wear image recognition and Artificial Neural Networks (ANNs). Second, an ANN model of tool life is trained with the data collected from the first two cutting edges and the subsequent model is evaluated on two different subsets for the third cutting edge: the first subset is obtained from the direct measurement of tool wear and the second is obtained from the Neural Wear software that estimates tool wear using edge images. Although the complete-automated solution, Neural Wear software for tool wear recognition plus the ANN model of tool life prediction, presented a slightly higher error than the direct measurements, it was within the same range and can meet all industrial requirements. These results confirm that the combination of image recognition software and ANN modelling could potentially be developed into a useful industrial tool for low-cost estimation of tool life in turning operations.

Psychological approach to successful ageing predicts future quality of life in older adults

Directory of Open Access Journals (Sweden)

Iliffe Steve

2011-03-01

Full Text Available Abstract Background Public policies aim to promote well-being, and ultimately the quality of later life. Positive perspectives of ageing are underpinned by a range of appraoches to successful ageing. This study aimed to investigate whether baseline biological, psychological and social aproaches to successful ageing predicted future QoL. Methods Postal follow-up in 2007/8 of a national random sample of 999 people aged 65 and over in 1999/2000. Of 496 valid addresses of survivors at follow-up, the follow-up response rate was 58% (287. Measures of the different concepts of successful ageing were constructed using baseline indicators. They were assessed for their ability to independently predict quality of life at follow-up. Results Few respondents achieved all good scores within each of the approaches to successful ageing. Each approach was associated with follow-up QoL when their scores were analysed continuously. The biomedical (health approach failed to achieve significance when the traditional dichotomous cut-off point for successfully aged (full health, or not (less than full health, was used. In multiple regression analyses of the relative predictive ability of each approach, only the psychological approach (perceived self-efficacy and optimism retained significance. Conclusion Only the psychological approach to successful ageing independently predicted QoL at follow-up. Successful ageing is not only about the maintenance of health, but about maximising one's psychological resources, namely self-efficacy and resilience. Increasing use of preventive care, better medical management of morbidity, and changing lifestyles in older people may have beneficial effects on health and longevity, but may not improve their QoL. Adding years to life and life to years may require two distinct and different approaches, one physical and the other psychological. Follow-up health status, number of supporters and social activities, and self-rated active ageing

A kernel principal component analysis–based degradation model and remaining useful life estimation for the turbofan engine

Directory of Open Access Journals (Sweden)

Delong Feng

2016-05-01

Full Text Available Remaining useful life estimation of the prognostics and health management technique is a complicated and difficult research question for maintenance. In this article, we consider the problem of prognostics modeling and estimation of the turbofan engine under complicated circumstances and propose a kernel principal component analysis–based degradation model and remaining useful life estimation method for such aircraft engine. We first analyze the output data created by the turbofan engine thermodynamic simulation that is based on the kernel principal component analysis method and then distinguish the qualitative and quantitative relationships between the key factors. Next, we build a degradation model for the engine fault based on the following assumptions: the engine has only had constant failure (i.e. no sudden failure is included, and the engine has a Wiener process, which is a covariate stand for the engine system drift. To predict the remaining useful life of the turbofan engine, we built a health index based on the degradation model and used the method of maximum likelihood and the data from the thermodynamic simulation model to estimate the parameters of this degradation model. Through the data analysis, we obtained a trend model of the regression curve line that fits with the actual statistical data. Based on the predicted health index model and the data trend model, we estimate the remaining useful life of the aircraft engine as the index reaches zero. At last, a case study involving engine simulation data demonstrates the precision and performance advantages of this prediction method that we propose. At last, a case study involving engine simulation data demonstrates the precision and performance advantages of this proposed method, the precision of the method can reach to 98.9% and the average precision is 95.8%.

A Human Life-Stage Physiologically Based Pharmacokinetic and Pharmacodynamic Model for Chlorpyrifos: Development and Validation

Energy Technology Data Exchange (ETDEWEB)

Smith, Jordan N.; Hinderliter, Paul M.; Timchalk, Charles; Bartels, M. J.; Poet, Torka S.

2014-08-01

Sensitivity to chemicals in animals and humans are known to vary with age. Age-related changes in sensitivity to chlorpyrifos have been reported in animal models. A life-stage physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model was developed to computationally predict disposition of CPF and its metabolites, chlorpyrifos-oxon (the ultimate toxicant) and 3,5,6-trichloro-2-pyridinol (TCPy), as well as B-esterase inhibition by chlorpyrifos-oxon in humans. In this model, age-dependent body weight was calculated from a generalized Gompertz function, and compartments (liver, brain, fat, blood, diaphragm, rapid, and slow) were scaled based on body weight from polynomial functions on a fractional body weight basis. Blood flows among compartments were calculated as a constant flow per compartment volume. The life-stage PBPK/PD model was calibrated and tested against controlled adult human exposure studies. Model simulations suggest age-dependent pharmacokinetics and response may exist. At oral doses ≥ 0.55 mg/kg of chlorpyrifos (significantly higher than environmental exposure levels), 6 mo old children are predicted to have higher levels of chlorpyrifos-oxon in blood and higher levels of red blood cell cholinesterase inhibition compared to adults from equivalent oral doses of chlorpyrifos. At lower doses that are more relevant to environmental exposures, the model predicts that adults will have slightly higher levels of chlorpyrifos-oxon in blood and greater cholinesterase inhibition. This model provides a computational framework for age-comparative simulations that can be utilized to predict CPF disposition and biological response over various postnatal life-stages.

A new crack growth model for life prediction under random loading

International Nuclear Information System (INIS)

Lee, Ouk Sub; Chen, Zhi Wei

1999-01-01

The load interaction effect in variable amplitude fatigue test is a very important issue for correctly predicting fatigue life. Some prediction methods for retardation are reviewed and the problems discussed. The so-called 'under-load' effect is also of importance for a prediction model to work properly under random load spectrum. A new model that is simple in form but combines overload plastic zone and residual stress considerations together with Elber's closure concept is proposed to fully take account of the load-interaction effects including both over-load and under-load effects. Applying this new model to complex load sequence is explored here. Simulations of tests show the improvement of the new model over other models. The best prediction (mostly closely resembling test curve) is given by the newly proposed Chen-Lee model

Improvement of life prediction accuracy by introduction of strain-rate effect into modified ductility exhaustion method

International Nuclear Information System (INIS)

Takahashi, Yukio

1994-01-01

It is important to use a reliable creep-fatigue damage evaluation method to prevent failures due to creep-fatigue damage accumulated during operation life in the structural design for fast breeder reactor plants. In this study, slow strain-rate fatigue tests were conducted for SUS316 steel for fast breeder application (316FR) and the improvement of creep-fatigue life estimation method was proposed based on test results. Main results can be summarized as follows: (1) In the slow strain-rate fatigue tests, life reduction caused by creep damage was observed as in the case of strain-hold creep-fatigue tests. (2) Strain-rate dependency of creep damage was introduced into the modified ductility exhaustion method previously proposed by the author. Good agreement of predicted lives with observed lives was achieved for SUS304 and 316FR steels with the method proposed here. (author)

Prediction-based dynamic load-sharing heuristics

Science.gov (United States)

Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

1993-01-01

The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

Remaining useful life prediction of degrading systems subjected to imperfect maintenance: Application to draught fans

Science.gov (United States)

Wang, Zhao-Qiang; Hu, Chang-Hua; Si, Xiao-Sheng; Zio, Enrico

2018-02-01

Current degradation modeling and remaining useful life prediction studies share a common assumption that the degrading systems are not maintained or maintained perfectly (i.e., to an as-good-as new state). This paper concerns the issues of how to model the degradation process and predict the remaining useful life of degrading systems subjected to imperfect maintenance activities, which can restore the health condition of a degrading system to any degradation level between as-good-as new and as-bad-as old. Toward this end, a nonlinear model driven by Wiener process is first proposed to characterize the degradation trajectory of the degrading system subjected to imperfect maintenance, where negative jumps are incorporated to quantify the influence of imperfect maintenance activities on the system's degradation. Then, the probability density function of the remaining useful life is derived analytically by a space-scale transformation, i.e., transforming the constructed degradation model with negative jumps crossing a constant threshold level to a Wiener process model crossing a random threshold level. To implement the proposed method, unknown parameters in the degradation model are estimated by the maximum likelihood estimation method. Finally, the proposed degradation modeling and remaining useful life prediction method are applied to a practical case of draught fans belonging to a kind of mechanical systems from steel mills. The results reveal that, for a degrading system subjected to imperfect maintenance, our proposed method can obtain more accurate remaining useful life predictions than those of the benchmark model in literature.

Prediction of fatigue life under service loading using the relative method

International Nuclear Information System (INIS)

Buch, A.

1982-01-01

Fatigue life estimates obtained with the local strain approach (LSA) and with the conventional nominal stress approach (NSA) were compared with experimental results obtained on notched AlCuMg2 aircraft material specimens with flight simulation random tensile loading. The effect of change of the reference stress, of the loading program and of some changes in the loading frequency distribution, on the ratio Nsub(exp)/Nsub(pred) was investigated. A material strain-life curve, a cyclic stress-strain curve. The Neuber-Topper rule Ksub(sigma) x Ksub(epsilon) = K 2 = const. and a K value estimated with an exact two-parameter notch factor formula for the case R = 0, N = 10 7 were used for life predictions. (orig./RW) [de

Ambulation in adults with myelomeningocele. Is it possible to predict the level of ambulation in early life?

DEFF Research Database (Denmark)

Seitzberg, A.; Lind, M.; Biering-Sørensen, Fin

2008-01-01

OBJECTIVE: The objective of this study was to evaluate the prediction of ambulation in adults with myelomeningocele from muscle strength testing and ambulation in early life. MATERIALS AND METHODS: Fifty-two myelomeningocele (MMC) individuals at the age 18-37 years at follow-up were studied....... Information on muscle strength and ambulatory function in early life was retrieved from medical records. The motor levels determined by the muscle strength were used to predict ambulatory function later in life. At follow-up, a clinical examination was performed. RESULTS: Of 20 MMC individuals assessed...... life than predicted. Good strength in quadriceps muscles gave significant better prospect for adult walking. Of the 52 participants, 41 retained their ambulation status from 5-8 years of age. CONCLUSION: For MMC individuals with motor levels L3-L5, adult ambulatory function cannot be determined from...

Exposure to stressful life events during pregnancy predicts psychotic experiences via behaviour problems in childhood.

Science.gov (United States)

Betts, Kim S; Williams, Gail M; Najman, Jakob M; Scott, James; Alati, Rosa

2014-12-01

Exposure to stressful life events during pregnancy has been associated with later schizophrenia in offspring. We explore how prenatal stress and neurodevelopmental abnormalities in childhood associate to increase the risk of later psychotic experiences. Participants from the Mater University Study of Pregnancy (MUSP), an Australian based, pre-birth cohort study were examined for lifetime DSM-IV positive psychotic experiences at 21 years by a semi-structured interview (n = 2227). Structural equation modelling suggested psychotic experiences were best represented with a bifactor model including a general psychosis factor and two group factors. We tested for an association between prenatal stressful life events with the psychotic experiences, and examined for potential moderation and mediation by behaviour problems and cognitive ability in childhood. Prenatal stressful life events predicted psychotic experiences indirectly via behaviour problems at child age five years, and this relationship was not confounded by maternal stressful life events at child age five. We found no statistical evidence for an interaction between prenatal stressful life events and behaviour problems or cognitive ability. The measurable effect of prenatal stressful life events on later psychotic experiences in offspring manifested as behaviour problems by age 5. By identifying early abnormal behavioural development as an intermediary, this finding further confirms the role of prenatal stress to later psychotic disorders. Copyright © 2014 Elsevier Ltd. All rights reserved.

Numerical and experimental verification of a new model for fatique life

International Nuclear Information System (INIS)

Svensson, T.; Holmgren, M.

1991-01-01

A new model for fatigue life prediction has been investigated in this report. The model is based on Palmgren-Miners rule in combination with level crossing. Data from literature and experimental data generated in this project have been compared with fatigue life prediction made with the new model. The data have also been compared with traditional fatigue life estimations base on the rain flow count method. The fatigue life predicted with the new model often agree better with actual life than predictions made with the RFC-method. This is especially pronounced when the loading sequence is very irregular. The new method is both fast and simple to use. (au)

Fatigue Life Prediction in Rapid Die Casting - Preliminary Work in View of Current Research

International Nuclear Information System (INIS)

Chuan Huat Ng; Grote, Karl-Heinrich; Baehr, Ruediger

2007-01-01

Numerical simulation technique as a prediction tool is slowly adopted in metal casting industry for predicting design modelling solidification analysis. The reasons for this activity is found in the need to further enhance the geometrical design and mechanical properties of the tool design and the correct prediction methodology to fulfil industrial needs. The present state of numerical simulation capabilities in rapid die casting technologies is reviewed and the failure mode mechanisms of thermal fatigue, aimed at developing a numerical simulation with a systematic design guidance for predicting the thermal cyclic loading analysis and improvement is presented along with several other methods. The economic benefits of a numerical simulation technique in die casting are limited to tool life time, mechanical properties and design guidance. The extensive computer capabilities of a numerical simulation with a systematic design guidance methodology are exploited to provide a solution for flexible design, mechanical properties and mould life time. Related research carried out worldwide by different organisations and academic institutions are discussed

Structure life prediction at high temperature: present and future capabilities

International Nuclear Information System (INIS)

Chaboche, J.L.

1987-01-01

The life prediction techniques for high temperature conditions include several aspects which are considered successively in this article. Crack initiation criteria themselves, defined for the isolated volume element (the tension-compression specimen for example), including parametric relationships and continuous damage approaches and calculation of local stress and strain fields in the structure and their evolution under cyclic plasticity, which poses several difficult problems to obtain stabilized cyclic solutions are examined. The use of crack initiation criteria or damage rules from the result of the cyclic inelastic analysis and the prediction of crack growth in the structure are considered. Different levels are considered for the predictive tools: the classical approach, future methods presently under development and intermediate rules, which are already in use. Several examples are given on materials and components used either in the nuclear industry or in gas turbine engines. (author)

Multi-Axial Damage Index and Accumulation Model for Predicting Fatigue Life of CMC Materials, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The fatigue life of CMCs must be well characterized for the safe and reliable use of these materials as integrated TPS components. Existing fatigue life prediction...

Trust-based collective view prediction

CERN Document Server

Luo, Tiejian; Xu, Guandong; Zhou, Jia

2013-01-01

Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users' past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View

Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows

Science.gov (United States)

Huber, K.; Dänicke, S.; Rehage, J.; Sauerwein, H.; Otto, W.; Rolle-Kampczyk, U.; von Bergen, M.

2016-01-01

The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life. PMID:27089826

A human life-stage physiologically based pharmacokinetic and pharmacodynamic model for chlorpyrifos: development and validation.

Science.gov (United States)

Smith, Jordan Ned; Hinderliter, Paul M; Timchalk, Charles; Bartels, Michael J; Poet, Torka S

2014-08-01

Sensitivity to some chemicals in animals and humans are known to vary with age. Age-related changes in sensitivity to chlorpyrifos have been reported in animal models. A life-stage physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) model was developed to predict disposition of chlorpyrifos and its metabolites, chlorpyrifos-oxon (the ultimate toxicant) and 3,5,6-trichloro-2-pyridinol (TCPy), as well as B-esterase inhibition by chlorpyrifos-oxon in humans. In this model, previously measured age-dependent metabolism of chlorpyrifos and chlorpyrifos-oxon were integrated into age-related descriptions of human anatomy and physiology. The life-stage PBPK/PD model was calibrated and tested against controlled adult human exposure studies. Simulations suggest age-dependent pharmacokinetics and response may exist. At oral doses ⩾0.6mg/kg of chlorpyrifos (100- to 1000-fold higher than environmental exposure levels), 6months old children are predicted to have higher levels of chlorpyrifos-oxon in blood and higher levels of red blood cell cholinesterase inhibition compared to adults from equivalent doses. At lower doses more relevant to environmental exposures, simulations predict that adults will have slightly higher levels of chlorpyrifos-oxon in blood and greater cholinesterase inhibition. This model provides a computational framework for age-comparative simulations that can be utilized to predict chlorpyrifos disposition and biological response over various postnatal life stages. Copyright © 2013 Elsevier Inc. All rights reserved.

Life estimation I and C cable insulation materials based on accelerated life testing accelerated life testing

International Nuclear Information System (INIS)

Santhosh, T.V.; Ramteke, P.K.; Shrestha, N.B.; Ahirwar, A.K.; Gopika, V.

2016-01-01

Accelerated Iife tests are becoming increasingly popular in today's industry due to the need for obtaining life data quickly and reliably. Life testing of products under higher stress levels without introducing additional failure modes can provide significant savings of both time and money. Correct analysis of data gathered via such accelerated life testing will yield parameters and other information for the product's life under use stress conditions. To be of practical use in assessing the operational behaviour of cables in NPPs, laboratory ageing aims to mimic the type of degradation observed under operational conditions. Conditions of testing therefore need to be carefully chosen to ensure that the degradation mechanism occurring in the accelerated tests are similar to those which occur in service. This paper presents the results of an investigation in which the elongation-at-break (EAB) measurements were carried on a typical control cable to predict the mean life at service conditions. A low voltage polyvinyl chloride (PVC) insulated and PVC sheathed control cable, used in NPP instrumentation and control (I and C) applications, was subjected thermal ageing at three elevated temperatures

Results of fatigue tests and prediction of fatigue life under superposed stress wave and combined superposed stress wave

International Nuclear Information System (INIS)

Takasugi, Shunji; Horikawa, Takeshi; Tsunenari, Toshiyasu; Nakamura, Hiroshi

1983-01-01

In order to examine fatigue life prediction methods at high temperatures where creep damage need not be taken into account, fatigue tests were carried out on plane bending specimens of alloy steels (SCM 435, 2 1/4Cr-1Mo) under superposed and combined superposed stress waves at room temperature and 500 0 C. The experimental data were compared with the fatigue lives predicted by using the cycle counting methods (range pair, range pair mean and zero-cross range pair mean methods), the modified Goodman's equation and the modified Miner's rule. The main results were as follows. (1) The fatigue life prediction method which is being used for the data at room temperature is also applicable to predict the life at high temperatures. The range pair mean method is especially better than other cycle counting methods. The zero-cross range pair mean method gives the estimated lives on the safe side of the experimental lives. (2) The scatter bands of N-bar/N-barsub(es) (experimental life/estimated life) becomes narrower when the following equation is used instead of the modified Goodman's equation for predicting the effect of mean stress on fatigue life. σ sub(t) = σ sub(a) / (1 - Sigma-s sub(m) / kσ sub(B)) σ sub(t); stress amplitude at zero mean stress (kg/mm 2 ) σ sub(B); tensile strength (kg/mm 2 ) σ sub(m); mean stress (kg/mm 2 ) σ sub(a); stress amplitude (kg/mm 2 ) k; modified coefficient of σ sub(B) (author)

A modelling study for long-term life prediction of carbon steel overpack for geological isolation of High-Level Radioactive Waste

International Nuclear Information System (INIS)

Taniguchi, Naoki; Honda, Akira; Ishikawa, Hirohisa

1996-01-01

Current plans for the geological disposal of High-Level Radioactive Waste (HLW) in Japan include metal overpacks which contain HLW. Overpacks may be required to remain intact for more than several hundred years in order to provide containment of radio nuclides. The main factor limiting the performance of overpacks is considered to be corrosion by groundwater. Carbon steel is one of the candidate material for overpacks. A mathematical model for life prediction of carbon steel overpack has been developed based on corrosion mechanism. General corrosion and localized corrosion are considered because these are likely to initiate in repository conditions. In general corrosion model, the reduction of oxygen and water are considered as cathodic reaction. In localized corrosion model, we have constructed a model which predict the period for localized corrosion based on oxygen transport in bentonite. We also developed a model which predict the propagation rate of localized corrosion that is based on mass balance within the corroding cavity. (author)

Assessment of Predictable Productivity of Nurses Working in Kerman University of Medical Sciences' Teaching Hospitals via the Dimensions of Quality of Work Life.

Science.gov (United States)

Borhani, Fariba; Arbabisarjou, Azizollah; Kianian, Toktam; Saber, Saman

2016-10-01

Despite the existence of a large community of nurses, specific mechanisms have not been developed yet to consider their needs and the quality of their work life. Moreover, few studies have been conducted to analyze the nature of nursing, nursing places or nurses' quality of work life. In this regard, the present study aimed to assess predictable productivity of nurses working in Kerman University of Medical Sciences' teaching hospitals via the dimensions of Quality of Work Life. The present descriptive-correlational study was conducted to assess predictable productivity of nurses via the dimensions of Quality of Work Life. The study's population consisted of all nurses working in different wards of teaching hospitals associated with Kerman University of Medical Sciences. Out of the whole population, 266 nurses were selected based on the simple random sampling method. To collect data, the questionnaires of 'Quality of Nursing Work Life' and 'Productivity' were used after confirming their reliability (test-retest) and content validity. Finally, the collected data were analyzed through the SPSS software (version 16). Although the quality of work life for nurses was average and their productivity was low but the results showed that quality of life is directly related to nurses' productivity. Quality of life and its dimensions are predictive factors in the in the nurses' productivity. It can conclude that by recognizing the nurses' quality of work life situation, it can realize this group productivity and their values to the efficiency of the health system. For the quality of working life improvement and increasing nurses' productivity more efforts are needed by authorities. The findings can be applied by managers of hospitals and nursing services along with head nurses to enhance the quality of health services and nursing profession in general.

The Level of Quality of Work Life to Predict Work Alienation

Science.gov (United States)

Erdem, Mustafa

2014-01-01

The current research aims to determine the level of elementary school teachers' quality of work life (QWL) to predict work alienation. The study was designed using the relational survey model. The research population consisted of 1096 teachers employed at 25 elementary schools within the city of Van in the academic year 2010- 2011, and 346…

Ambulatory fall-risk assessment: amount and quality of daily-life gait predict falls in older adults.

Science.gov (United States)

van Schooten, Kimberley S; Pijnappels, Mirjam; Rispens, Sietse M; Elders, Petra J M; Lips, Paul; van Dieën, Jaap H

2015-05-01

Ambulatory measurements of trunk accelerations can provide valuable information on the amount and quality of daily-life activities and contribute to the identification of individuals at risk of falls. We compared associations between retrospective and prospective falls with potential risk factors as measured by daily-life accelerometry. In addition, we investigated predictive value of these parameters for 6-month prospective falls. One week of trunk accelerometry (DynaPort MoveMonitor) was obtained in 169 older adults (mean age 75). The amount of daily activity and quality of gait were determined and validated questionnaires on fall-risk factors, grip strength, and trail making test were obtained. Six-month fall incidence was obtained retrospectively by recall and prospectively by fall diaries and monthly telephone contact. Among all participants, 35.5% had a history of ≥1 falls and 34.9% experienced ≥1 falls during 6-month follow-up. Logistic regressions showed that questionnaires, grip strength, and trail making test, as well as the amount and quality of gait, were significantly associated with falls. Significant associations differed between retrospective and prospective analyses although odds ratios indicated similar patterns. Predictive ability based on questionnaires, grip strength, and trail making test (area under the curve .68) improved substantially by accelerometry-derived parameters of the amount of gait (number of strides), gait quality (complexity, intensity, and smoothness), and their interactions (area under the curve .82). Daily-life accelerometry contributes substantially to the identification of individuals at risk of falls, and can predict falls in 6 months with good accuracy. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Contribution to life-time predictions of gas turbine components under cyclic load

Energy Technology Data Exchange (ETDEWEB)

Hoelscher, R.

1982-02-15

The low cycle fatique life of gas turbine components is analysed using the turbine blade of the ATAR 101 F jet engine turbine as example. The results show that, among other things thermal stresses during start-up and shut-off cause considerable damage to the material. Tests using a model rig showed that damage caused by material creep and LCF-mechanisms stongly depended on cyclic parameters such as temperature, temperature development, and power etc. Two long-term tests confirm that the Manson model can be used to give a reasonable prediction of turbine blade life.

Life prediction methodology for ceramic components of advanced heat engines. Phase 1: Volume 1, Final report

Energy Technology Data Exchange (ETDEWEB)

Cuccio, J.C.; Brehm, P.; Fang, H.T. [Allied-Signal Aerospace Co., Phoenix, AZ (United States). Garrett Engine Div.] [and others

1995-03-01

Emphasis of this program is to develop and demonstrate ceramics life prediction methods, including fast fracture, stress rupture, creep, oxidation, and nondestructive evaluation. Significant advancements were made in these methods and their predictive capabilities successfully demonstrated.

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.

Science.gov (United States)

Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu

2018-01-19

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model

Directory of Open Access Journals (Sweden)

Jingzhou Xin

2018-01-01

Full Text Available Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA, and generalized autoregressive conditional heteroskedasticity (GARCH. Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS deformation monitoring system demonstrated that: (1 the Kalman filter is capable of denoising the bridge deformation monitoring data; (2 the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3 in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity; the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data

Life prediction of OLED for constant-stress accelerated degradation tests using luminance decaying model

Energy Technology Data Exchange (ETDEWEB)

Zhang, Jianping, E-mail: jpzhanglzu@163.com [College of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai 200090 (China); Li, Wenbin [College of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai 200090 (China); Cheng, Guoliang; Chen, Xiao [Shanghai Tianyi Electric Co., Ltd., Shanghai 201611 (China); Wu, Helen [School of Computing, Engineering and Mathematics, University of Western Sydney, Sydney 2751 (Australia); Herman Shen, M.-H. [Department of Mechanical and Aerospace Engineering, The Ohio State University, OH 43210 (United States)

2014-10-15

In order to acquire the life information of organic light emitting diode (OLED), three groups of constant stress accelerated degradation tests are performed to obtain the luminance decaying data of samples under the condition that the luminance and the current are respectively selected as the indicator of performance degradation and the test stress. Weibull function is applied to describe the relationship between luminance decaying and time, least square method (LSM) is employed to calculate the shape parameter and scale parameter, and the life prediction of OLED is achieved. The numerical results indicate that the accelerated degradation test and the luminance decaying model reveal the luminance decaying law of OLED. The luminance decaying formula fits the test data very well, and the average error of fitting value compared with the test data is small. Furthermore, the accuracy of the OLED life predicted by luminance decaying model is high, which enable rapid estimation of OLED life and provide significant guidelines to help engineers make decisions in design and manufacturing strategy from the aspect of reliability life. - Highlights: • We gain luminance decaying data by accelerated degradation tests on OLED. • The luminance decaying model objectively reveals the decaying law of OLED luminance. • The least square method (LSM) is employed to calculate Weibull parameters. • The plan designed for accelerated degradation tests proves to be feasible. • The accuracy of the OLED life and the luminance decaying fitting formula is high.

Life prediction of OLED for constant-stress accelerated degradation tests using luminance decaying model

International Nuclear Information System (INIS)

Zhang, Jianping; Li, Wenbin; Cheng, Guoliang; Chen, Xiao; Wu, Helen; Herman Shen, M.-H.

2014-01-01

In order to acquire the life information of organic light emitting diode (OLED), three groups of constant stress accelerated degradation tests are performed to obtain the luminance decaying data of samples under the condition that the luminance and the current are respectively selected as the indicator of performance degradation and the test stress. Weibull function is applied to describe the relationship between luminance decaying and time, least square method (LSM) is employed to calculate the shape parameter and scale parameter, and the life prediction of OLED is achieved. The numerical results indicate that the accelerated degradation test and the luminance decaying model reveal the luminance decaying law of OLED. The luminance decaying formula fits the test data very well, and the average error of fitting value compared with the test data is small. Furthermore, the accuracy of the OLED life predicted by luminance decaying model is high, which enable rapid estimation of OLED life and provide significant guidelines to help engineers make decisions in design and manufacturing strategy from the aspect of reliability life. - Highlights: • We gain luminance decaying data by accelerated degradation tests on OLED. • The luminance decaying model objectively reveals the decaying law of OLED luminance. • The least square method (LSM) is employed to calculate Weibull parameters. • The plan designed for accelerated degradation tests proves to be feasible. • The accuracy of the OLED life and the luminance decaying fitting formula is high

Degradation Prediction Model Based on a Neural Network with Dynamic Windows

Science.gov (United States)

Zhang, Xinghui; Xiao, Lei; Kang, Jianshe

2015-01-01

Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully researched, but for some high reliability components, it is very difficult to collect run-to-failure condition monitoring data, i.e., from normal to failure. Only a certain number of condition indicators in certain period can be used to estimate RUL. In addition, some existing prediction methods have problems which block RUL estimation due to poor extrapolability. The predicted value converges to a certain constant or fluctuates in certain range. Moreover, the fluctuant condition features also have bad effects on prediction. In order to solve these dilemmas, this paper proposes a RUL prediction model based on neural network with dynamic windows. This model mainly consists of three steps: window size determination by increasing rate, change point detection and rolling prediction. The proposed method has two dominant strengths. One is that the proposed approach does not need to assume the degradation trajectory is subject to a certain distribution. The other is it can adapt to variation of degradation indicators which greatly benefits RUL prediction. Finally, the performance of the proposed RUL prediction model is validated by real field data and simulation data. PMID:25806873

Study on Blade Fatigue Life of Rotating Power Machinery

Directory of Open Access Journals (Sweden)

Fu Xi

2016-01-01

Full Text Available The linear damage model (LDM is widely applied in engineering calculation, but it does not consider the relationship between damage variable and load parameters. Therefore, the life prediction based on LDM is not satisfied for the aero-engine blades. Besides, it easily brings about error in predicting fatigue life by common nonlinear damage model which neglect the influence of torsional stress. Hence, a modified nonlinear continuum damage model (CDM is put forward based on Chaboche nonlinear damage model in this research. And to determine the damage and fatigue life of TC4 material used in aero-engine blades, axial tension and compression fatigue test is conducted. Compared with LDM results, the fatigue life prediction results of the modified CDM in this work show a good agreement with the tests data. So the correctness of the modified model is verified. Finally, the fatigue life of a certain aero-engine high pressure compressor blade is predicted by the modified nonlinear continuum damage model.

Physician consensus on preventability and predictability of readmissions based on standard case scenarios

DEFF Research Database (Denmark)

van Galen, L. S.; Cooksley, T; Merten, H

2016-01-01

Background: Policy makers struggle with unplanned readmissions as a quality indicator since integrating preventability in such indicators is difficult. Most studies on the preventability of readmissions questioned physicians whether they consider a given readmission to be preventable, from which...... conclusions on factors predicting preventable readmissions were derived. There is no literature on the interobserver agreement of physician judgement. Aim: To assess the degree of agreement among physicians regarding predictability and preventability of medical readmissions. Design: An online survey based...... on eight real-life case scenarios was distributed to European physicians. Methods: Physicians were requested to rate from the first four (index admission) scenarios whether they expected these patients to be readmitted within 30 days (the predictability). The remaining four cases, describing a readmission...

Remaining Useful Life Prediction of Gas Turbine Engine using Autoregressive Model

Directory of Open Access Journals (Sweden)

Ahsan Shazaib

2017-01-01

Full Text Available Gas turbine (GT engines are known for their high availability and reliability and are extensively used for power generation, marine and aero-applications. Maintenance of such complex machines should be done proactively to reduce cost and sustain high availability of the GT. The aim of this paper is to explore the use of autoregressive (AR models to predict remaining useful life (RUL of a GT engine. The Turbofan Engine data from NASA benchmark data repository is used as case study. The parametric investigation is performed to check on any effect of changing model parameter on modelling accuracy. Results shows that a single sensory data cannot accurately predict RUL of GT and further research need to be carried out by incorporating multi-sensory data. Furthermore, the predictions made using AR model seems to give highly pessimistic values for RUL of GT.

Life Prediction of Low Cycle Fatigue for Ni-base Superalloy GTD111 DS at Elevated Temperature

Energy Technology Data Exchange (ETDEWEB)

Kim, Jin Yeol; Yoon, Dong Hyun; Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of); Bae, Si Yeon; Chang, Sung Yong; Chang, Sung Ho [KEPCO Research Institute, Daejeon (Korea, Republic of)

2017-08-15

GTD111 DS of nickel base superalloy has been used for gas turbine blades. In this study, low cycle fatigue test was conducted on the GTD111 DS alloy by setting conditions similar to the real operating environment. The low cycle fatigue tests were conducted at room temperature, 760 °C, 870 °C, and various strain amplitudes. Test results showed that fatigue life decreased with increasing total strain amplitude. Cyclic hardening response was observed at room temperature and 760 °C; however, tests conducted at 870 °C showed cyclic softening response. Stress relaxation was observed at 870 °C because creep effects occurred from holding time. A relationship between fatigue life and total strain range was obtained from the Coffin-Manson method. The fratography using a SEM was carried out at the crack initiation and propagation regions.

TBCs for Gas Turbines under Thermomechanical Loadings: Failure Behaviour and Life Prediction

Directory of Open Access Journals (Sweden)

Herzog R.

2012-10-01

Full Text Available The present contribution gives an overview about recent research on a thermal barrier coating (TBC system consisted of (i an intermetallic MCrAlY-alloy Bondcoat (BC applied by vacuum plasma spraying (VPS and (ii an Yttria Stabilised Zirconia (YSZ top coat air plasma sprayed (APS at Forschungszentrum Juelich, Institute of Energy and Climate Research (IEK-1. The influence of high temperature dwell time, maximum and minimum temperature on crack growth kinetics during thermal cycling of such plasma sprayed TBCs is investigated using infrared pulse thermography (IT, acoustic emission (AE analysis and scanning electron microscopy. Thermocyclic life in terms of accumulated time at maximum temperature decreases with increasing high temperature dwell time and increases with increasing minimum temperature. AE analysis proves that crack growth mainly occurs during cooling at temperatures below the ductile-to-brittle transition temperature of the BC. Superimposed mechanical load cycles accelerate delamination crack growth and, in case of sufficiently high mechanical loadings, result in premature fatigue failure of the substrate. A life prediction model based on TGO growth kinetics and a fracture mechanics approach has been developed which accounts for the influence of maximum and minimum temperature as well as of high temperature dwell time with good accuracy in an extremely wide parameter range.

A new simplified allometric approach for predicting the biological half-life of radionuclides in reptiles

International Nuclear Information System (INIS)

Beresford, N.A.; Wood, M.D.

2014-01-01

A major source of uncertainty in the estimation of radiation dose to wildlife is the prediction of internal radionuclide activity concentrations. Allometric (mass-dependent) relationships describing biological half-life (T 1/2b ) of radionuclides in organisms can be used to predict organism activity concentrations. The establishment of allometric expressions requires experimental data which are often lacking. An approach to predict the T 1/2b in homeothermic vertebrates has recently been proposed. In this paper we have adapted this to be applicable to reptiles. For Cs, Ra and Sr, over a mass range of 0.02–1.5 kg, resultant predictions were generally within a factor of 6 of reported values demonstrating that the approach can be used when measured T 1/2b data are lacking. However, the effect of mass on reptilian radionuclide T 1/2b is minimal. If sufficient measured data are available for a given radionuclide then it is likely that these would give a reasonable estimate of T 1/2b in any reptile species. - Highlights: • An allometric approach to predict radionuclide T 1/2b values in reptiles is derived. • Predictions are generally within a factor of six of measured values. • Radionuclide biological half-life is in-effect mass independent

A Bayesian least-squares support vector machine method for predicting the remaining useful life of a microwave component

Directory of Open Access Journals (Sweden)

Fuqiang Sun

2017-01-01

Full Text Available Rapid and accurate lifetime prediction of critical components in a system is important to maintaining the system’s reliable operation. To this end, many lifetime prediction methods have been developed to handle various failure-related data collected in different situations. Among these methods, machine learning and Bayesian updating are the most popular ones. In this article, a Bayesian least-squares support vector machine method that combines least-squares support vector machine with Bayesian inference is developed for predicting the remaining useful life of a microwave component. A degradation model describing the change in the component’s power gain over time is developed, and the point and interval remaining useful life estimates are obtained considering a predefined failure threshold. In our case study, the radial basis function neural network approach is also implemented for comparison purposes. The results indicate that the Bayesian least-squares support vector machine method is more precise and stable in predicting the remaining useful life of this type of components.

Predicting Liaison: an Example-Based Approach

NARCIS (Netherlands)

Greefhorst, A.P.M.; Bosch, A.P.J. van den

2016-01-01

Predicting liaison in French is a non-trivial problem to model. We compare a memory-based machine-learning algorithm with a rule-based baseline. The memory-based learner is trained to predict whether liaison occurs between two words on the basis of lexical, orthographic, morphosyntactic, and

Decline curve based models for predicting natural gas well performance

Directory of Open Access Journals (Sweden)

Arash Kamari

2017-06-01

Full Text Available The productivity of a gas well declines over its production life as cannot cover economic policies. To overcome such problems, the production performance of gas wells should be predicted by applying reliable methods to analyse the decline trend. Therefore, reliable models are developed in this study on the basis of powerful artificial intelligence techniques viz. the artificial neural network (ANN modelling strategy, least square support vector machine (LSSVM approach, adaptive neuro-fuzzy inference system (ANFIS, and decision tree (DT method for the prediction of cumulative gas production as well as initial decline rate multiplied by time as a function of the Arps' decline curve exponent and ratio of initial gas flow rate over total gas flow rate. It was concluded that the results obtained based on the models developed in current study are in satisfactory agreement with the actual gas well production data. Furthermore, the results of comparative study performed demonstrates that the LSSVM strategy is superior to the other models investigated for the prediction of both cumulative gas production, and initial decline rate multiplied by time.

Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

Science.gov (United States)

Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

2012-04-01

Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

Physiologically-based, predictive analytics using the heart-rate-to-Systolic-Ratio significantly improves the timeliness and accuracy of sepsis prediction compared to SIRS.

Science.gov (United States)

Danner, Omar K; Hendren, Sandra; Santiago, Ethel; Nye, Brittany; Abraham, Prasad

2017-04-01

Enhancing the efficiency of diagnosis and treatment of severe sepsis by using physiologically-based, predictive analytical strategies has not been fully explored. We hypothesize assessment of heart-rate-to-systolic-ratio significantly increases the timeliness and accuracy of sepsis prediction after emergency department (ED) presentation. We evaluated the records of 53,313 ED patients from a large, urban teaching hospital between January and June 2015. The HR-to-systolic ratio was compared to SIRS criteria for sepsis prediction. There were 884 patients with discharge diagnoses of sepsis, severe sepsis, and/or septic shock. Variations in three presenting variables, heart rate, systolic BP and temperature were determined to be primary early predictors of sepsis with a 74% (654/884) accuracy compared to 34% (304/884) using SIRS criteria (p < 0.0001)in confirmed septic patients. Physiologically-based predictive analytics improved the accuracy and expediency of sepsis identification via detection of variations in HR-to-systolic ratio. This approach may lead to earlier sepsis workup and life-saving interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

Using ABAQUS Scripting Interface for Materials Evaluation and Life Prediction

Science.gov (United States)

Powers, Lynn M.; Arnold, Steven M.; Baranski, Andrzej

2006-01-01

An ABAQUS script has been written to aid in the evaluation of the mechanical behavior of viscoplastic materials. The purposes of the script are to: handle complex load histories; control load/displacement with alternate stopping criteria; predict failure and life; and verify constitutive models. Material models from the ABAQUS library may be used or the UMAT routine may specify mechanical behavior. User subroutines implemented include: UMAT for the constitutive model; UEXTERNALDB for file manipulation; DISP for boundary conditions; and URDFIL for results processing. Examples presented include load, strain and displacement control tests on a single element model. The tests are creep with a life limiting strain criterion, strain control with a stress limiting cycle and a complex interrupted cyclic relaxation test. The techniques implemented in this paper enable complex load conditions to be solved efficiently with ABAQUS.

Comparison of LIFE-4 and TEMECH code predictions with TREAT transient test data

International Nuclear Information System (INIS)

Gneiting, B.C.; Bard, F.E.; Hunter, C.W.

1984-09-01

Transient tests in the TREAT reactor were performed on FFTF Reference design mixed-oxide fuel pins, most of which had received prior steady-state irradiation in the EBR-II reactor. These transient test results provide a data base for calibration and verification of fuel performance codes and for evaluation of processes that affect pin damage during transient events. This paper presents a comparison of the LIFE-4 and TEMECH fuel pin thermal/mechanical analysis codes with the results from 20 HEDL TREAT experiments, ten of which resulted in pin failure. Both the LIFE-4 and TEMECH codes provided an adequate representation of the thermal and mechanical data from the TREAT experiments. Also, a criterion for 50% probability of pin failure was developed for each code using an average cumulative damage fraction value calculated for the pins that failed. Both codes employ the two major cladding loading mechanisms of differential thermal expansion and central cavity pressurization which were demonstrated by the test results. However, a detailed evaluation of the code predictions shows that the two code systems weigh the loading mechanism differently to reach the same end points of the TREAT transient results

A Combined High and Low Cycle Fatigue Model for Life Prediction of Turbine Blades

Directory of Open Access Journals (Sweden)

Shun-Peng Zhu

2017-06-01

Full Text Available Combined high and low cycle fatigue (CCF generally induces the failure of aircraft gas turbine attachments. Based on the aero-engine load spectrum, accurate assessment of fatigue damage due to the interaction of high cycle fatigue (HCF resulting from high frequency vibrations and low cycle fatigue (LCF from ground-air-ground engine cycles is of critical importance for ensuring structural integrity of engine components, like turbine blades. In this paper, the influence of combined damage accumulation on the expected CCF life are investigated for turbine blades. The CCF behavior of a turbine blade is usually studied by testing with four load-controlled parameters, including high cycle stress amplitude and frequency, and low cycle stress amplitude and frequency. According to this, a new damage accumulation model is proposed based on Miner’s rule to consider the coupled damage due to HCF-LCF interaction by introducing the four load parameters. Five experimental datasets of turbine blade alloys and turbine blades were introduced for model validation and comparison between the proposed Miner, Manson-Halford, and Trufyakov-Kovalchuk models. Results show that the proposed model provides more accurate predictions than others with lower mean and standard deviation values of model prediction errors.

Life prediction technology of structural materials

International Nuclear Information System (INIS)

Nagata, Norio

1992-01-01

There is empirically the time limit of use in all industrial plants and components. By defining the loss of functions as the expiration of life, if the forecast of life time or residual life of plants and components can be done, a very useful means becomes available for safety and economical efficiency. The life of plants is controlled by the occurrence and extension of defects in materials, and by the life of the material which is placed under most severe condition. Such severe condition is the environment of use itself with high temperature, corrosive environment, load, vibration and so on. The forecast of material life is to quantitatively grasp the damage behavior of materials under such condition, and to carry out the time control of the functions of plants by defect control. The time dependence of material damage such as fatigue damage, creep damage and corrosion damage is discussed. The forecast of material life by empirical knowledge and theoretical inference and the forecast of residual life are explained. Finally, the forecast of the life time of light water reactors is described as those constructed in initial period approach their design life. (K.I.)

Ensemble-based prediction of RNA secondary structures.

Science.gov (United States)

Aghaeepour, Nima; Hoos, Holger H

2013-04-24

Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

Thermomechanical fatigue life prediction for several solders

Science.gov (United States)

Wen, Shengmin

Since solder connections operate at high homologous temperature, solders are high temperature materials. This feature makes their mechanical behavior and fatigue phenomena unique. Based on experimental findings, a physical damage mechanism is introduced for solders. The mechanism views the damage process as a series of independent local damage events characterized by the failure of individual grains, while the structural damage is the eventual percolation result of such local events. Fine's dislocation energy density concept and Mura's microcrack initiation theory are adopted to derive the fatigue formula for an individual grain. A physical damage metric is introduced to describe the material with damage. A unified creep and plasticity constitutive model is adopted to simulate the mechanical behavior of solders. The model is cast into a continuum damage mechanics framework to simulate material with damage. The model gives good agreement with the experimental results of 96.5Pb-3.5Sn and 96.5Sn-3.5Ag solders under uniaxial strain-controlled cyclic loading. The model is convenient for implementation into commercial computational packages. Also presented is a fatigue theory with its failure criterion for solders based on physical damage mechanism. By introducing grain orientation into the fatigue formula, an m-N curve (m is Schmid factor) at constant loading condition is suggested for fatigue of grains with different orientations. A solder structure is defined as fatigued when the damage metric reaches a critical threshold, since at this threshold the failed grains may form a cluster and percolate through the structure according to percolation theory. Fatigue data of 96.5Pb-3.5Sn solder bulk specimens under various uniaxial tension tests were analyzed. Results show that the theory gives consistent predictions under broad conditions, while inelastic strain theory does not. The theory is anisotropic with no size limitation to its application, which could be suitable for

Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

OpenAIRE

Wu, Han-Zhou; Wang, Hong-Xia; Shi, Yun-Qing

2016-01-01

This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on th...

Projecting LED product life based on application

Science.gov (United States)

Narendran, Nadarajah; Liu, Yi-wei; Mou, Xi; Thotagamuwa, Dinusha R.; Eshwarage, Oshadhi V. Madihe

2016-09-01

LED products have started to displace traditional light sources in many lighting applications. One of the commonly claimed benefits for LED lighting products is their long useful lifetime in applications. Today there are many replacement lamp products using LEDs in the marketplace. Typically, lifetime claims of these replacement lamps are in the 25,000-hour range. According to current industry practice, the time for the LED light output to reach the 70% value is estimated according to IESNA LM-80 and TM-21 procedures and the resulting value is reported as the whole system life. LED products generally experience different thermal environments and switching (on-off cycling) patterns when used in applications. Current industry test methods often do not produce accurate lifetime estimates for LED systems because only one component of the system, namely the LED, is tested under a continuous-on burning condition without switching on and off, and because they estimate for only one failure type, lumen depreciation. The objective of the study presented in this manuscript was to develop a test method that could help predict LED system life in any application by testing the whole LED system, including on-off power cycling with sufficient dwell time, and considering both failure types, catastrophic and parametric. The study results showed for the LED A-lamps tested in this study, both failure types, catastrophic and parametric, exist. The on-off cycling encourages catastrophic failure, and maximum operating temperature influences the lumen depreciation rate and parametric failure time. It was also clear that LED system life is negatively affected by on-off switching, contrary to commonly held belief. In addition, the study results showed that most of the LED systems failed catastrophically much ahead of the LED light output reaching the 70% value. This emphasizes the fact that life testing of LED systems must consider catastrophic failure in addition to lumen depreciation, and

Functional Independence in Late-Life: Maintaining Physical Functioning in Older Adulthood Predicts Daily Life Function after Age 80.

Science.gov (United States)

Vaughan, Leslie; Leng, Xiaoyan; La Monte, Michael J; Tindle, Hilary A; Cochrane, Barbara B; Shumaker, Sally A

2016-03-01

We examined physical functioning (PF) trajectories (maintaining, slowly declining, and rapidly declining) spanning 15 years in older women aged 65-80 and protective factors that predicted better current levels and less decline in functional independence outcomes after age 80. Women's Health Initiative extension participants who met criteria (enrolled in either the clinical trial or observational study cohort, >80 years at the data release cutoff, PF survey data from initial enrollment to age 80, and functional independence survey data after age 80) were included in these analyses (mean [SD] age = 84.0 [1.4] years; N = 10,478). PF was measured with the SF-36 (mean = 4.9 occasions). Functional independence was measured by self-reported level of dependence in basic and instrumental activities of daily living (ADLs and IADLs) (mean = 3.4 and 3.3 occasions). Maintaining consistent PF in older adulthood extends functional independence in ADL and IADL in late-life. Protective factors shared by ADL and IADL include maintaining PF over time, self-reported excellent or very good health, no history of hip fracture after age 55, and no history of cardiovascular disease. Better IADL function is uniquely predicted by a body mass index less than 25 and no depression. Less ADL and IADL decline is predicted by better self-reported health, and less IADL decline is uniquely predicted by having no history of hip fracture after age 55. Maintaining or improving PF and preventing injury and disease in older adulthood (ages 65-80) has far-reaching implications for improving late-life (after age 80) functional independence. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Levels of and changes in life satisfaction predict mortality hazards: Disentangling the role of physical health, perceived control, and social orientation.

Science.gov (United States)

Hülür, Gizem; Heckhausen, Jutta; Hoppmann, Christiane A; Infurna, Frank J; Wagner, Gert G; Ram, Nilam; Gerstorf, Denis

2017-09-01

It is well documented that well-being typically evinces precipitous decrements at the end of life. However, research has primarily taken a postdictive approach by knowing the outcome (date of death) and aligning, in retrospect, how well-being has changed for people with documented death events. In the present study, we made use of a predictive approach by examining whether and how levels of and changes in life satisfaction prospectively predict mortality hazards and delineate the role of contributing factors, including health, perceived control, and social orientation. To do so, we applied shared parameter growth-survival models to 20-year longitudinal data from 10,597 participants (n = 1,560 [15%] deceased; age at baseline: M = 44 years, SD = 17, range = 18-98 years) from the national German Socio-Economic Panel Study. Our findings showed that lower levels and steeper declines of life satisfaction each uniquely predicted higher mortality risks. Results also revealed moderating effects of age and perceived control: Life satisfaction levels and changes had stronger predictive effects for mortality hazards among older adults. Perceived control was associated with lower mortality hazards; however, this effect was diminished for those who experienced accelerated life satisfaction decline. Variance decomposition suggests that predictive effects of life satisfaction trajectories were partially unique (3%-6%) and partially shared with physical health, perceived control, and social orientation (17%-19%). Our discussion focuses on the strengths and challenges of a predictive approach to link developmental changes (in life satisfaction) to mortality hazards, and considers implications of our findings for healthy aging. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Residual Stress Estimation and Fatigue Life Prediction of an Autofrettaged Pressure Vessel

Energy Technology Data Exchange (ETDEWEB)

Song, Kyung Jin; Kim, Eun Kyum; Koh, Seung Kee [Kunsan Nat’l Univ., Kunsan (Korea, Republic of)

2017-09-15

Fatigue failure of an autofrettaged pressure vessel with a groove at the outside surface occurs owing to the fatigue crack initiation and propagation at the groove root. In order to predict the fatigue life of the autofrettaged pressure vessel, residual stresses in the autofrettaged pressure vessel were evaluated using the finite element method, and the fatigue properties of the pressure vessel steel were obtained from the fatigue tests. Fatigue life of a pressure vessel obtained through summation of the crack initiation and propagation lives was calculated to be 2,598 cycles for an 80% autofrettaged pressure vessel subjected to a pulsating internal pressure of 424 MPa.

A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades

Directory of Open Access Journals (Sweden)

Zheng-Yong Yu

2017-05-01

Full Text Available As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB and Fatemi-Socie (FS models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models.

Bayesian techniques for fatigue life prediction and for inference in linear time dependent PDEs

KAUST Repository

Scavino, Marco

2016-01-08

In this talk we introduce first the main characteristics of a systematic statistical approach to model calibration, model selection and model ranking when stress-life data are drawn from a collection of records of fatigue experiments. Focusing on Bayesian prediction assessment, we consider fatigue-limit models and random fatigue-limit models under different a priori assumptions. In the second part of the talk, we present a hierarchical Bayesian technique for the inference of the coefficients of time dependent linear PDEs, under the assumption that noisy measurements are available in both the interior of a domain of interest and from boundary conditions. We present a computational technique based on the marginalization of the contribution of the boundary parameters and apply it to inverse heat conduction problems.

Hybrid PSO–SVM-based method for forecasting of the remaining useful life for aircraft engines and evaluation of its reliability

International Nuclear Information System (INIS)

García Nieto, P.J.; García-Gonzalo, E.; Sánchez Lasheras, F.; Cos Juez, F.J. de

2015-01-01

The present paper describes a hybrid PSO–SVM-based model for the prediction of the remaining useful life of aircraft engines. The proposed hybrid model combines support vector machines (SVMs), which have been successfully adopted for regression problems, with the particle swarm optimization (PSO) technique. This optimization technique involves kernel parameter setting in the SVM training procedure, which significantly influences the regression accuracy. However, its use in reliability applications has not been yet widely explored. Bearing this in mind, remaining useful life values have been predicted here by using the hybrid PSO–SVM-based model from the remaining measured parameters (input variables) for aircraft engines with success. A coefficient of determination equal to 0.9034 was obtained when this hybrid PSO–RBF–SVM-based model was applied to experimental data. The agreement of this model with experimental data confirmed its good performance. One of the main advantages of this predictive model is that it does not require information about the previous operation states of the engine. Finally, the main conclusions of this study are exposed. - Highlights: • A hybrid PSO–SVM-based model is built as a predictive model of the RUL values for aircraft engines. • The remaining physical–chemical variables in this process are studied in depth. • The obtained regression accuracy of our method is about 95%. • The results show that PSO–SVM-based model can assist in the diagnosis of the RUL values with accuracy

Statistics-Based Prediction Analysis for Head and Neck Cancer Tumor Deformation

Directory of Open Access Journals (Sweden)

Maryam Azimi

2012-01-01

Full Text Available Most of the current radiation therapy planning systems, which are based on pre-treatment Computer Tomography (CT images, assume that the tumor geometry does not change during the course of treatment. However, tumor geometry is shown to be changing over time. We propose a methodology to monitor and predict daily size changes of head and neck cancer tumors during the entire radiation therapy period. Using collected patients' CT scan data, MATLAB routines are developed to quantify the progressive geometric changes occurring in patients during radiation therapy. Regression analysis is implemented to develop predictive models for tumor size changes through entire period. The generated models are validated using leave-one-out cross validation. The proposed method will increase the accuracy of therapy and improve patient's safety and quality of life by reducing the number of harmful unnecessary CT scans.

Knowledge-based Fragment Binding Prediction

Science.gov (United States)

Tang, Grace W.; Altman, Russ B.

2014-01-01

Target-based drug discovery must assess many drug-like compounds for potential activity. Focusing on low-molecular-weight compounds (fragments) can dramatically reduce the chemical search space. However, approaches for determining protein-fragment interactions have limitations. Experimental assays are time-consuming, expensive, and not always applicable. At the same time, computational approaches using physics-based methods have limited accuracy. With increasing high-resolution structural data for protein-ligand complexes, there is now an opportunity for data-driven approaches to fragment binding prediction. We present FragFEATURE, a machine learning approach to predict small molecule fragments preferred by a target protein structure. We first create a knowledge base of protein structural environments annotated with the small molecule substructures they bind. These substructures have low-molecular weight and serve as a proxy for fragments. FragFEATURE then compares the structural environments within a target protein to those in the knowledge base to retrieve statistically preferred fragments. It merges information across diverse ligands with shared substructures to generate predictions. Our results demonstrate FragFEATURE's ability to rediscover fragments corresponding to the ligand bound with 74% precision and 82% recall on average. For many protein targets, it identifies high scoring fragments that are substructures of known inhibitors. FragFEATURE thus predicts fragments that can serve as inputs to fragment-based drug design or serve as refinement criteria for creating target-specific compound libraries for experimental or computational screening. PMID:24762971

Leaf and life history traits predict plant growth in a green roof ecosystem.

Directory of Open Access Journals (Sweden)

Jeremy Lundholm

Full Text Available Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime's C-S-R strategies for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that

Leaf and life history traits predict plant growth in a green roof ecosystem.

Science.gov (United States)

Lundholm, Jeremy; Heim, Amy; Tran, Stephanie; Smith, Tyler

2014-01-01

Green roof ecosystems are constructed to provide services such as stormwater retention and urban temperature reductions. Green roofs with shallow growing media represent stressful conditions for plant survival, thus plants that survive and grow are important for maximizing economic and ecological benefits. While field trials are essential for selecting appropriate green roof plants, we wanted to determine whether plant leaf traits could predict changes in abundance (growth) to provide a more general framework for plant selection. We quantified leaf traits and derived life-history traits (Grime's C-S-R strategies) for 13 species used in a four-year green roof experiment involving five plant life forms. Changes in canopy density in monocultures and mixtures containing one to five life forms were determined and related to plant traits using multiple regression. We expected traits related to stress-tolerance would characterize the species that best grew in this relatively harsh setting. While all species survived to the end of the experiment, canopy species diversity in mixture treatments was usually much lower than originally planted. Most species grew slower in mixture compared to monoculture, suggesting that interspecific competition reduced canopy diversity. Species dominant in mixture treatments tended to be fast-growing ruderals and included both native and non-native species. Specific leaf area was a consistently strong predictor of final biomass and the change in abundance in both monoculture and mixture treatments. Some species in contrasting life-form groups showed compensatory dynamics, suggesting that life-form mixtures can maximize resilience of cover and biomass in the face of environmental fluctuations. This study confirms that plant traits can be used to predict growth performance in green roof ecosystems. While rapid canopy growth is desirable for green roofs, maintenance of species diversity may require engineering of conditions that favor less

Does folic acid supplementation prevent or promote colorectal cancer? Results from model-based predictions.

Science.gov (United States)

Luebeck, E Georg; Moolgavkar, Suresh H; Liu, Amy Y; Boynton, Alanna; Ulrich, Cornelia M

2008-06-01

Folate is essential for nucleotide synthesis, DNA replication, and methyl group supply. Low-folate status has been associated with increased risks of several cancer types, suggesting a chemopreventive role of folate. However, recent findings on giving folic acid to patients with a history of colorectal polyps raise concerns about the efficacy and safety of folate supplementation and the long-term health effects of folate fortification. Results suggest that undetected precursor lesions may progress under folic acid supplementation, consistent with the role of folate role in nucleotide synthesis and cell proliferation. To better understand the possible trade-offs between the protective effects due to decreased mutation rates and possibly concomitant detrimental effects due to increased cell proliferation of folic acid, we used a biologically based mathematical model of colorectal carcinogenesis. We predict changes in cancer risk based on timing of treatment start and the potential effect of folic acid on cell proliferation and mutation rates. Changes in colorectal cancer risk in response to folic acid supplementation are likely a complex function of treatment start, duration, and effect on cell proliferation and mutations rates. Predicted colorectal cancer incidence rates under supplementation are mostly higher than rates without folic acid supplementation unless supplementation is initiated early in life (before age 20 years). To the extent to which this model predicts reality, it indicates that the effect on cancer risk when starting folic acid supplementation late in life is small, yet mostly detrimental. Experimental studies are needed to provide direct evidence for this dual role of folate in colorectal cancer and to validate and improve the model predictions.

Residual lifetime prediction for lithium-ion battery based on functional principal component analysis and Bayesian approach

International Nuclear Information System (INIS)

Cheng, Yujie; Lu, Chen; Li, Tieying; Tao, Laifa

2015-01-01

Existing methods for predicting lithium-ion (Li-ion) battery residual lifetime mostly depend on a priori knowledge on aging mechanism, the use of chemical or physical formulation and analytical battery models. This dependence is usually difficult to determine in practice, which restricts the application of these methods. In this study, we propose a new prediction method for Li-ion battery residual lifetime evaluation based on FPCA (functional principal component analysis) and Bayesian approach. The proposed method utilizes FPCA to construct a nonparametric degradation model for Li-ion battery, based on which the residual lifetime and the corresponding confidence interval can be evaluated. Furthermore, an empirical Bayes approach is utilized to achieve real-time updating of the degradation model and concurrently determine residual lifetime distribution. Based on Bayesian updating, a more accurate prediction result and a more precise confidence interval are obtained. Experiments are implemented based on data provided by the NASA Ames Prognostics Center of Excellence. Results confirm that the proposed prediction method performs well in real-time battery residual lifetime prediction. - Highlights: • Capacity is considered functional and FPCA is utilized to extract more information. • No features required which avoids drawbacks induced by feature extraction. • A good combination of both population and individual information. • Avoiding complex aging mechanism and accurate analytical models of batteries. • Easily applicable to different batteries for life prediction and RLD calculation.

The role of brain/behavioural systems in prediction of quality of life and coping strategies in cancer patients

Directory of Open Access Journals (Sweden)

Shala Jangi Goujeh Biglou

2014-03-01

Full Text Available Background: It seems that individual differences in personality characteristics are implicated in the incidence and progress of physical diseases and socio-psychological consequences. However, there are a few studies about the role of personality in the prediction of socio-psychological consequences of cancer. The aim of this research was to survey the role of personality in the prediction of socio-psychosocial factors: quality of life and coping strategies. Methods: This research was a descriptive-correlational study in which the sample included fifty cancer patients who were selected through convenience sampling method. To assess the personality differences, quality of life and coping strategies, the Carver and White (1994 BIS/BAS Scales, SF-12 Health Survey and Coping Inventory for Stressful Situation (CISS were used, respectively. The data were analysed by SPSS software using Pearson correlation coefficient and stepwise regression. Results: The findings showed that Both BIS and BAS systems could predict the quality of life (P<0.001, BIS system could explain the emotion-oriented coping strategy (P<0.05 and avoidance-oriented coping stratesy (P<0.01 and BAS system could explain the problem-oriented coping strategy (P<0.001. Conclusion: The findings of this study showed that brain/behavioural systems can predict the quality of life and coping strategies in cancer patients. The identification of these systems in cancer patients can help recognize the persons that are under the risk of poor quality of life or have a higher chance of using inconsistent coping strategies, and execute preventive measures about them.

Size-based predictions of food web patterns

DEFF Research Database (Denmark)

Zhang, Lai; Hartvig, Martin; Knudsen, Kim

2014-01-01

We employ size-based theoretical arguments to derive simple analytic predictions of ecological patterns and properties of natural communities: size-spectrum exponent, maximum trophic level, and susceptibility to invasive species. The predictions are brought about by assuming that an infinite number...... of species are continuously distributed on a size-trait axis. It is, however, an open question whether such predictions are valid for a food web with a finite number of species embedded in a network structure. We address this question by comparing the size-based predictions to results from dynamic food web...... simulations with varying species richness. To this end, we develop a new size- and trait-based food web model that can be simplified into an analytically solvable size-based model. We confirm existing solutions for the size distribution and derive novel predictions for maximum trophic level and invasion...

Performance reliability prediction for thermal aging based on kalman filtering

International Nuclear Information System (INIS)

Ren Shuhong; Wen Zhenhua; Xue Fei; Zhao Wensheng

2015-01-01

The performance reliability of the nuclear power plant main pipeline that failed due to thermal aging was studied by the performance degradation theory. Firstly, through the data obtained from the accelerated thermal aging experiments, the degradation process of the impact strength and fracture toughness of austenitic stainless steel material of the main pipeline was analyzed. The time-varying performance degradation model based on the state space method was built, and the performance trends were predicted by using Kalman filtering. Then, the multi-parameter and real-time performance reliability prediction model for the main pipeline thermal aging was developed by considering the correlation between the impact properties and fracture toughness, and by using the stochastic process theory. Thus, the thermal aging performance reliability and reliability life of the main pipeline with multi-parameter were obtained, which provides the scientific basis for the optimization management of the aging maintenance decision making for nuclear power plant main pipelines. (authors)

Nuclear grade cable thermal life model by time temperature superposition algorithm based on Matlab GUI

International Nuclear Information System (INIS)

Lu Yanyun; Gu Shenjie; Lou Tianyang

2014-01-01

Background: As nuclear grade cable must endure harsh environment within design life, it is critical to predict cable thermal life accurately owing to thermal aging, which is one of dominant factors of aging mechanism. Purpose: Using time temperature superposition (TTS) method, the aim is to construct nuclear grade cable thermal life model, predict cable residual life and develop life model interactive interface under Matlab GUI. Methods: According to TTS, nuclear grade cable thermal life model can be constructed by shifting data groups at various temperatures to preset reference temperature with translation factor which is determined by non linear programming optimization. Interactive interface of cable thermal life model developed under Matlab GUI consists of superposition mode and standard mode which include features such as optimization of translation factor, calculation of activation energy, construction of thermal aging curve and analysis of aging mechanism., Results: With calculation result comparison between superposition and standard method, the result with TTS has better accuracy than that with standard method. Furthermore, confidence level of nuclear grade cable thermal life with TTS is higher than that with standard method. Conclusion: The results show that TTS methodology is applicable to thermal life prediction of nuclear grade cable. Interactive Interface under Matlab GUI achieves anticipated functionalities. (authors)

The effect of discounting, different mortality reduction schemes and predictive cohort life tables on risk acceptability criteria

International Nuclear Information System (INIS)

Rackwitz, Ruediger

2006-01-01

Technical facilities should be optimal with respect to benefits and cost. Optimization of technical facilities involving risks for human life and limb require an acceptability criterion and suitable discount rates both for the public and the operator depending on for whom the optimization is carried out. The life quality index is presented and embedded into modem socio-economic concepts. A general risk acceptability criterion is derived. The societal life saving cost to be used in optimization as life saving or compensation cost and the societal willingness-to-pay based on the societal value of a statistical life or on the societal life quality index are developed. Different mortality reduction schemes are studied. Also, predictive cohort life tables are derived and applied. Discount rates γ must be long-term averages in view of the time horizon of some 20 to more than 100 years for the facilities of interest and net of inflation and taxes. While the operator may use long-term averages from the financial market for his cost-benefit analysis the assessment of interest rates for investments of the public into risk reduction is more difficult. The classical Ramsey model decomposes the real interest rate (=output growth rate) into the rate of time preference of consumption and the rate of economical growth multiplied by the elasticity of marginal utility of consumption. It is proposed to use a relatively small interest rate of 3% implying a rate of time preference of consumption of about 1%. This appears intergenerationally acceptable from an ethical point of view. Risk-consequence curves are derived for an example

Life Prediction of Spent Fuel Storage Canister Material

Energy Technology Data Exchange (ETDEWEB)

Ballinger, Ronald

2018-04-16

The original purpose of this project was to develop a probabilistic model for SCC-induced failure of spent fuel storage canisters, exposed to a salt-air environment in the temperature range 30-70°C for periods up to and exceeding 100 years. The nature of this degradation process, which involves multiple degradation mechanisms, combined with variable and uncertain environmental conditions dictates a probabilistic approach to life prediction. A final report for the original portion of the project was submitted earlier. However, residual stress measurements for as-welded and repair welds could not be performed within the original time of the project. As a result of this, a no-cost extension was granted in order to complete these tests. In this report, we report on the results of residual stress measurements.

Preadmission quality of life can predict mortality in intensive care unit—A prospective cohort study

DEFF Research Database (Denmark)

Bukan, Ramin I; Møller, Ann M; Henning, Mattias A S

2014-01-01

quality of life, assessed by SF-36 and SF-12, is as good at predicting ICU, 30-, and 90-day mortality as APACHE II in patients admitted to the ICU for longer than 24 hours. This indicates that estimated preadmission quality of life, potentially available in the pre-ICU setting, could aid decision making...... regarding ICU admission and deserves more attention by those caring for critically ill patients....

An Efficient Deterministic Approach to Model-based Prediction Uncertainty

Data.gov (United States)

National Aeronautics and Space Administration — Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the...

Life prediction methods for the combined creep-fatigue endurance

International Nuclear Information System (INIS)

Wareing, J.; Lloyd, G.J.

1980-09-01

The basis and current status of development of the various approaches to the prediction of the combined creep-fatigue endurance are reviewed. It is concluded that an inadequate materials data base makes it difficult to draw sensible conclusions about the prediction capabilities of each of the available methods. Correlation with data for stainless steel 304 and 316 is presented. (U.K.)

Further evaluation of creep-fatigue life prediction methods for low-carbon nitrogen-added 316 stainless steel

International Nuclear Information System (INIS)

Takahashi, Y.

1999-01-01

Low-carbon, medium-nitrogen 316 stainless steel is a principal candidate for a main structural material of a demonstration fast breeder reactor plant in Japan. A number of long-term creep tests and creep-fatigue tests have been conducted for four products of this steel. Two representative creep-fatigue life prediction methods, i.e., time fraction rule and ductility exhaustion method were applied. Total stress relaxation behavior was simulated well by an addition of a viscous strain term to the conventional (primary plus secondary) creep strain, but only the letter was assumed to contribute to creep damage in the ductility exhaustion method. The present ductility exhaustion approach was found to have very good accuracy in creep-fatigue life prediction for all materials tested, while the time fraction rule tended to overpredict failure life as large as a factor of 30. Discussion was made on the reason for this notable difference

A Wear Rule and Cutter Life Prediction Model of a 20-in. TBM Cutter for Granite: A Case Study of a Water Conveyance Tunnel in China

Science.gov (United States)

Liu, Quansheng; Liu, Jianping; Pan, Yucong; Zhang, Xiaoping; Peng, Xingxin; Gong, Qiuming; Du, Lijie

2017-05-01

Disc cutter wear is one of the comprehensive results of the rock-machine interaction in tunnel boring machine (TBM) tunneling. The replacement of the disc cutter is a time-consuming and costly activity that can significantly reduce the TBM utilization ( U) and advance rate (AR), and has a major effect on the total time and cost of TBM tunneling projects. Therefore, the importance of predicting the cutter life accurately can never be overemphasized. Most cutter wear prediction models are only suitable for 17-in. or smaller disc cutters. However, use of large-diameter disc cutters has been an irresistible trend for large-section hard rock TBMs. This study attempts to reveal the genuine wear rule of a 20-in. disc cutter and develop a new empirical model for predicting the cutter life in granite based on field data collected from a water conveyance tunnel constructed by the TBM tunneling method in China. The field data including the actual cutter wear and the geological parameters along the studied tunnel were compiled in a special database that was subjected to statistical analysis to reveal the genuine wear rule of a 20-in. disc cutter and develop the reasonable correlations between some common intact rock parameters and the disc cutter life. These equations were developed based on data from massive to very massive granite with a UCS range of 40-100 MPa, which can be applied for the assessment of the cutter life of a 20-in. disc cutter in similar hard rock projects with similar rock strengths and rock abrasivities.

Life prediction methodology for ceramic components of advanced vehicular heat engines: Volume 1. Final report

Energy Technology Data Exchange (ETDEWEB)

Khandelwal, P.K.; Provenzano, N.J.; Schneider, W.E. [Allison Engine Co., Indianapolis, IN (United States)

1996-02-01

One of the major challenges involved in the use of ceramic materials is ensuring adequate strength and durability. This activity has developed methodology which can be used during the design phase to predict the structural behavior of ceramic components. The effort involved the characterization of injection molded and hot isostatic pressed (HIPed) PY-6 silicon nitride, the development of nondestructive evaluation (NDE) technology, and the development of analytical life prediction methodology. Four failure modes are addressed: fast fracture, slow crack growth, creep, and oxidation. The techniques deal with failures initiating at the surface as well as internal to the component. The life prediction methodology for fast fracture and slow crack growth have been verified using a variety of confirmatory tests. The verification tests were conducted at room and elevated temperatures up to a maximum of 1371 {degrees}C. The tests involved (1) flat circular disks subjected to bending stresses and (2) high speed rotating spin disks. Reasonable correlation was achieved for a variety of test conditions and failure mechanisms. The predictions associated with surface failures proved to be optimistic, requiring re-evaluation of the components` initial fast fracture strengths. Correlation was achieved for the spin disks which failed in fast fracture from internal flaws. Time dependent elevated temperature slow crack growth spin disk failures were also successfully predicted.

Towards a Life Cycle Based Chemical Alternative Assessment (LCAA)

DEFF Research Database (Denmark)

Jolliet, O.; Huang, L.; Overcash, Michael

2017-01-01

approach combines the following elements: a) The manufacturing phase chemical inventory is based on the environmental genome of industrial products database, ensuring mass and energy balance, b) near-field exposure to consumer products during the use phase is determined based on the mass of chemical......There is a need for an operational quantitative screening-level assessment of alternatives, that is life-cycle based and able to serve both Life cycle Assessment (LCA and chemical alternatives assessment (CAA). This presentation therefore aims to develop and illustrate a new approach called “Life...... Cycle Based Chemical Alternative Assessment (LCAA)” that will quantify exposure and life cycle impacts consistently and efficiently over the main life cycle stages. The new LCAA approach is illustrated though a proof-of-concept case study of alternative plasticizers in vinyl flooring. The proposed LCAA...

Wealth and happiness across the world: material prosperity predicts life evaluation, whereas psychosocial prosperity predicts positive feeling.

Science.gov (United States)

Diener, Ed; Ng, Weiting; Harter, James; Arora, Raksha

2010-07-01

The Gallup World Poll, the first representative sample of planet Earth, was used to explore the reasons why happiness is associated with higher income, including the meeting of basic needs, fulfillment of psychological needs, increasing satisfaction with one's standard of living, and public goods. Across the globe, the association of log income with subjective well-being was linear but convex with raw income, indicating the declining marginal effects of income on subjective well-being. Income was a moderately strong predictor of life evaluation but a much weaker predictor of positive and negative feelings. Possessing luxury conveniences and satisfaction with standard of living were also strong predictors of life evaluation. Although the meeting of basic and psychological needs mediated the effects of income on life evaluation to some degree, the strongest mediation was provided by standard of living and ownership of conveniences. In contrast, feelings were most associated with the fulfillment of psychological needs: learning, autonomy, using one's skills, respect, and the ability to count on others in an emergency. Thus, two separate types of prosperity-economic and social psychological-best predict different types of well-being.

Fatigue life prediction of autofrettage tubes using actual material behaviour

International Nuclear Information System (INIS)

Jahed, Hamid; Farshi, Behrooz; Hosseini, Mohammad

2006-01-01

There is a profound Bauschinger effect in the behaviour of high-strength steels used in autofrettaged tubes. This has led to development of methods capable of considering experimentally obtained (actual) material behaviour in residual stress calculations. The extension of these methods to life calculations is presented here. To estimate the life of autofrettaged tubes with a longitudinal surface crack emanating from the bore more accurately, instead of using idealized models, the experimental loading-unloading stress-strain behaviour is employed. The resulting stresses are then used to calculate stress intensity factors by the weight function method as input to fatigue life determination. Fatigue lives obtained using the actual material behaviour are then compared with the results of frequently used ideal models including those considering Bauschinger effect factors and strain hardening in unloading. Using standard fatigue crack growth relationships, life of the vessel is then calculated based on recommended initial and final crack length. It is shown that the life gain due to autofrettage above 70% overstrain is considerable

[A predictive model for the quality of sexual life in hysterectomized women].

Science.gov (United States)

Urrutia, María Teresa; Araya, Alejandra; Rivera, Soledad; Viviani, Paola; Villarroel, Luis

2007-03-01

The effects of hysterectomy on sexuality has been extensively studied. To establish a model to predict the quality of sexual life in hysterectomized women, six months after surgery. Analytical, longitudinal and prospective study of 90 hysterectomized women aged 45+/-7 years. Two structured interviews at the time of surgery and six months later were carried out to determine the characteristics of sexuality and communication within the couple. In the two interviews, communication and the quality of sexual life were described as "good" in 72 and 77% of women, respectively (NS). The variables that had a 40% influence on the quality of sexual life sixth months after surgery, were oophorectomy status, the presence of orgasm, the characteristics of communication and the basal sexuality with the couple. The sexuality of the hysterectomized women will depend, on a great extent, of pre-surgical variables. Therefore, it is important to consider these variables for the education of hysterectomized women.

Study on predicting residual life of elevator links by fracture mechanics approach

Energy Technology Data Exchange (ETDEWEB)

Li Helin; Zhang Yi; Deng Zengjie [China National Petroleum Corp., Xi`an, Shaanxi (China). Tubular Goods Research Center; Jin Dazeng [Xi`an Jiaotong Univ., Xi`an, Shaanxi (China)

1995-12-31

On the basis of investigation, failure and fracture analysis of elevator links, residual life prediction of links using fracture mechanics approach is studied, and mechanical properties, fracture toughness value K{sub IC} and fatigue crack propagation rage da/dN of the steel for elevator links are determined. Using the relation between stress intensity factor K{sub I} and the strain-energy release rate, the two-dimensional conversion thickness finite element method has been used to calculate the stress intensity factors K{sub I} for dangerous sections in the ring part of links. Furthermore, the reliability of calculations of the finite element stress intensity factors K{sub I} for dangerous sections of elevator links and the residual life computation for links are verified by fatigue tests of actual links. Finally, the experimental verification of computed results by 150T link fractured at site indicates that the computed critical crack lengths and residual life tally well with those measured and meet the needs of oil drilling.

Does life satisfaction predict five-year mortality in community-living older adults?

Science.gov (United States)

St John, Philip D; Mackenzie, Corey; Menec, Verena

2015-01-01

Depression and depressive symptoms predict death, but it is less clear if more general measures of life satisfaction (LS) predict death. Our objectives were to determine: (1) if LS predicts mortality over a five-year period in community-living older adults; and (2) which aspects of LS predict death. 1751 adults over the age of 65 who were living in the community were sampled from a representative population sampling frame in 1991/1992 and followed five years later. Age, gender, and education were self-reported. An index of multimorbidity and the Older American Resource Survey measured health and functional status, and the Terrible-Delightful Scale assessed overall LS as well as satisfaction with: health, finances, family, friends, housing, recreation, self-esteem, religion, and transportation. Cox proportional hazards models examined the influence of LS on time to death. 417 participants died during the five-year study period. Overall LS and all aspects of LS except finances, religion, and self-esteem predicted death in unadjusted analyses. In fully adjusted analyses, LS with health, housing, and recreation predicted death. Other aspects of LS did not predict death after accounting for functional status and multimorbidity. LS predicted death, but certain aspects of LS are more strongly associated with death. The effect of LS is complex and may be mediated or confounded by health and functional status. It is important to consider different domains of LS when considering the impact of this important emotional indicator on mortality among older adults.

Extreme Environment Damage Index and Accumulation Model for CMC Laminate Fatigue Life Prediction, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Materials Research & Design (MR&D) is proposing in the SBIR Phase II an effort to develop a tool for predicting the fatigue life of C/SiC composite...

Relation Between Hertz Stress-Life Exponent, Ball-Race Conformity, and Ball Bearing Life

Science.gov (United States)

Zaretsky, Erwin V.; Poplawski, Joseph V.; Root, Lawrence E.

2008-01-01

ANSI/ABMA and ISO standards based on Lundberg-Palmgren bearing life theory are normalized for ball bearings having inner- and outerrace conformities of 52 percent (0.52) and made from pre-1940 bearing steel. The Lundberg-Palmgren theory incorporates an inverse 9th power relation between Hertz stress and fatigue life for ball bearings. The effect of race conformity on ball set life independent of race life is not incorporated into the Lundberg-Palmgren theory. In addition, post-1960 vacuum-processed bearing steel exhibits a 12th power relation between Hertz stress and life. The work reported extends the previous work of Zaretsky, Poplawski, and Root to calculate changes in bearing life--that includes the life of the ball set--caused by race conformity, Hertz stress-life exponent, ball bearing type and bearing series. The bearing fatigue life in actual application will usually be equal to or greater than that calculated using the ANSI/ABMA and ISO standards that incorporate the Lundberg-Palmgren theory. The relative fatigue life of an individual race is more sensitive to changes in race conformity for Hertz stress-life exponent n of 12 than where n = 9. However, when the effects are combined to predict actual bearing life for a specified set of conditions and bearing geometry, the predicted life of the bearing will be greater for a value of n = 12 than n = 9.

NULIFE - the European NoE 'Nuclear Plant Life Prediction'

International Nuclear Information System (INIS)

Cojan, Mihail

2008-01-01

INR Pitesti become on the 29th September 2006 a partner in the European Network of Excellence Nuclear Plant Life Prediction (NULIFE) coordinated by Technical Research Centre of Finland (VTT). The EU's Network of Excellence NULIFE has been launched under the EURATOM FP6 Program with a clear focus on integrating safety-oriented research on materials, structures and systems and exploiting the results of this integration through the production of harmonized lifetime assessment methods. NULIFE will help provide a better common understanding of, and information on, the factors affecting the lifetime of nuclear power plants which, together with associated management methods, will help facilitate extensions to the safe and economic lifetime of existing nuclear power plants. (author)

New paradigm for prediction of radiation life-time of reactor pressure vessel

International Nuclear Information System (INIS)

Kotrechko, S.A.; Meshkov, Yu.Ya.; Neklyudov, I.M.; Revka, V.N.

2011-01-01

New paradigm for prediction of radiation life-time of reactor pressure vessel is presented. Equation for limiting state of reactor pressure vessel wall with crack-like defect is obtained. It is exhibited that the value of critical fluence Φ c may be determined not by shift of critical temperature of fracture of surveillance specimen, which is indirect characteristic, but by direct method, namely, by the condition of initiation of brittle fracture of irradiated metal ahead of a crack in RPV wall. Within the framework of engineering version of LA to fracture the technique for Φ c ascertainment is developed. Prediction of Φ c for WWER pressure vessels demonstrates potentialities of this technique.

Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

Directory of Open Access Journals (Sweden)

Jing Lu

2014-11-01

Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

Early-life exposures predicting onset and resolution of childhood overweight or obesity.

Science.gov (United States)

Kerr, Jessica A; Long, Catherine; Clifford, Susan A; Muller, Joshua; Gillespie, Alanna N; Donath, Susan; Wake, Melissa

2017-10-01

To determine which of multiple early-life exposures predict onset or resolution of overweight/obesity during a 9-year period. Design : longitudinal cohort from three harmonised community-based cohorts enriched for overweight and obesity. Early-life exposures : child-gestational age; delivery; birth weight; breast feeding; solids introduction; baseline body mass index (BMI); waist circumference; diet; activity; global, physical and psychosocial health. Mother-baseline BMI; education; age; neighbourhood disadvantage; concern for child's weight. Outcome : change in BMI category. Analyses : adjusted logistic regression. On average, the 363 children (57% retention) were 6 and 15 years old at baseline and follow-up. Children were classified as 'never' overweight/obese (38%), 'resolving' overweight/obese (15%), 'becoming' overweight/obese (8%) or 'always' overweight/obese (39%). Compared with 'never overweight/obese' children, odds of 'becoming overweight/obese' were greater with higher child (OR 2.33, 95% CI 1.02 to 5.29) and maternal BMI (OR 1.18, CI 1.07 to 1.31), and lower with higher maternal education (OR 0.09, CI 0.02 to 0.34). Compared with 'always overweight/obese' children, odds of 'resolving overweight/obese' were lower with higher maternal BMI (OR 0.87, CI 0.78 to 0.97), and higher with better child physical health (OR 1.06, CI 1.02 to 1.10) and higher maternal age (OR 1.11, CI 1.01 to 1.22) and education (OR 4.07, CI 1.02 to 16.19). Readily available baseline information (child/maternal BMI, maternal age, education and child health) were the strongest predictors of both onset and resolution of overweight/obesity between the primary school and adolescent years. Perinatal, breastfeeding and lifestyle exposures were not strongly predictive. Results could stimulate development of algorithms identifying children most in need of targeted prevention or treatment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under

How do Major, Violent and Nonviolent Opposition Campaigns, Impact Predicted Life Expectancy at birth?

Directory of Open Access Journals (Sweden)

Judith Stoddard

2013-08-01

Full Text Available This study compared the effects of major violent and nonviolent opposition campaigns for regime change, on predicted life expectancy at birth. The study measured life expectancy five and ten years after the campaign ended, so that deaths which occurred during the campaign would not be included in the metric, and thus enabling the study of changes made in the state on the social determinants affecting longevity, after the campaign was over. Life expectancy is one of the best reported World Development Indicators and is considered to be a good indication of the overall health and general living conditions of the state and therefore is an ideal indicator to reflect the changes made in the state following a major campaign. The results of this analysis showed that states have a hard time recovering from a major opposition campaign and initially drop behind the growth trend in the world average for predicted life expectancy at birth. But, the type of campaign that was waged and whether it was successful, greatly affects the state’s ability to recover. Encouragingly by a decade after the campaign ends, states that experienced a nonviolent campaign that was successful had caught up to the world average and inched ahead of it. This shows that on this important development indicator, new governments that were ushered into power by nonviolent social movements, had made positive changes in the state that enabled it to surpass world averages.

An Extrapolation of a Radical Equation More Accurately Predicts Shelf Life of Frozen Biological Matrices.

Science.gov (United States)

De Vore, Karl W; Fatahi, Nadia M; Sass, John E

2016-08-01

Arrhenius modeling of analyte recovery at increased temperatures to predict long-term colder storage stability of biological raw materials, reagents, calibrators, and controls is standard practice in the diagnostics industry. Predicting subzero temperature stability using the same practice is frequently criticized but nevertheless heavily relied upon. We compared the ability to predict analyte recovery during frozen storage using 3 separate strategies: traditional accelerated studies with Arrhenius modeling, and extrapolation of recovery at 20% of shelf life using either ordinary least squares or a radical equation y = B1x(0.5) + B0. Computer simulations were performed to establish equivalence of statistical power to discern the expected changes during frozen storage or accelerated stress. This was followed by actual predictive and follow-up confirmatory testing of 12 chemistry and immunoassay analytes. Linear extrapolations tended to be the most conservative in the predicted percent recovery, reducing customer and patient risk. However, the majority of analytes followed a rate of change that slowed over time, which was fit best to a radical equation of the form y = B1x(0.5) + B0. Other evidence strongly suggested that the slowing of the rate was not due to higher-order kinetics, but to changes in the matrix during storage. Predicting shelf life of frozen products through extrapolation of early initial real-time storage analyte recovery should be considered the most accurate method. Although in this study the time required for a prediction was longer than a typical accelerated testing protocol, there are less potential sources of error, reduced costs, and a lower expenditure of resources. © 2016 American Association for Clinical Chemistry.

Fatigue life prediction of oil ducts under service loads

Energy Technology Data Exchange (ETDEWEB)

Meggiolaro, Marco A.; Castro, Jaime T.P. [Pontificia Univ. Catolica do Rio de Janeiro, RJ (Brazil)

2003-07-01

A methodology to calculate the residual initiation and propagation lives of fatigue cracks in oil pipelines with corrosion-like defects is proposed and applied to predict the residual life of an old duct made of API 5L Gr. B steel, in service for more than 40 years. Since its inauguration, this pipeline has carried several heated products under variable temperatures and pressures. The calculated (nominal) service stresses are very high, due to thermal loads that induce significant bending in curved parts of the duct, with peaks close to the yield strength of the steel. The elastic- plastic fatigue damage at a notch or a corrosion pit root is calculated using the {epsilon}N method, and the effects of surface semi-elliptical cracks in its internal (or external) wall is studied considering appropriate stress intensity factor expressions and the actual service loads. In the presence of surface flaws associated to stress concentration factors of the order of three, a fatigue crack likely will initiate in the pipeline. However, if these surface cracks are small compared to the duct wall thickness, their predicted propagation rates are very low. (author)

Game-Based Life-Long Learning

NARCIS (Netherlands)

Kelle, Sebastian; Sigurðarson, Steinn; Westera, Wim; Specht, Marcus

2010-01-01

Kelle, S., Sigurðarson, S., Westera, W., & Specht, M. (2011). Game-Based Life-Long Learning. In G. D. Magoulas (Ed.), E-Infrastructures and Technologies for Lifelong Learning: Next Generation Environments (pp. 337-349). Hershey, PA: IGI Global.

The Application Law of Large Numbers That Predicts The Amount of Actual Loss in Insurance of Life

Science.gov (United States)

Tinungki, Georgina Maria

2018-03-01

The law of large numbers is a statistical concept that calculates the average number of events or risks in a sample or population to predict something. The larger the population is calculated, the more accurate predictions. In the field of insurance, the Law of Large Numbers is used to predict the risk of loss or claims of some participants so that the premium can be calculated appropriately. For example there is an average that of every 100 insurance participants, there is one participant who filed an accident claim, then the premium of 100 participants should be able to provide Sum Assured to at least 1 accident claim. The larger the insurance participant is calculated, the more precise the prediction of the calendar and the calculation of the premium. Life insurance, as a tool for risk spread, can only work if a life insurance company is able to bear the same risk in large numbers. Here apply what is called the law of large number. The law of large numbers states that if the amount of exposure to losses increases, then the predicted loss will be closer to the actual loss. The use of the law of large numbers allows the number of losses to be predicted better.

Fatigue life prediction in composites using progressive damage modelling under block and spectrum loading

DEFF Research Database (Denmark)

Passipoularidis, Vaggelis; Philippidis, T.P.; Brøndsted, Povl

2010-01-01

series can be simulated. The predictions are validated against fatigue life data both from repeated block tests at a single stress ratio as well as against spectral fatigue using the WISPER, WISPERX and NEW WISPER load sequences on a Glass/Epoxy multidirectional laminate typical of a Wind Turbine Rotor...

Quality of life prediction in children with joint hypermobility syndrome.

Science.gov (United States)

Pacey, Verity; Tofts, Louise; Adams, Roger D; Munns, Craig F; Nicholson, Leslie L

2015-07-01

To assess the child- and parent-reported health-related quality of life (HRQOL) of children with joint hypermobility syndrome (JHS), to compare these with other chronic paediatric conditions and to determine whether symptoms experienced by children with JHS can predict their HRQOL. Eighty-nine children with JHS and one of their parents completed the Pediatric Quality of Life Inventory 4.0 Generic Core Scale, the Multidimensional Fatigue Scale and the Pediatric Pain Questionnaire. Anthropometric measures and reported symptoms were recorded. Child-reported HRQOL scores were compared with parent report, and both child- and parent-reported HRQOL scores of children with JHS were compared with those of children with other chronic conditions. Stepwise multiple regression was undertaken to determine whether any combination of measures could predict HRQOL. Parent- and child-reported HRQOL scores were strongly correlated (r = 0.6-0.84, all P children with JHS perceived lower overall HRQOL (mean difference = 4.44, P = 0.001), physical (mean difference = 7.11, P children. When considered together with previously reported HRQOL scores for children with other chronic conditions, parent and child scores were similarly strongly correlated (r = 0.93, P = 0.001). Multiple regression revealed that 75% of the variance in child-reported HRQOL scores was accounted for by a child's level of pain and fatigue, and presence of stress incontinence symptoms (P Children with JHS experience poor HRQOL and disabling fatigue, with parent scores providing a good proxy. Pain, fatigue and the presence of stress incontinence symptoms have the greatest impact on their HRQOL. © 2015 The Authors. Journal of Paediatrics and Child Health © 2015 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Remaining life prediction of I and C cables for reliability assessment of NPP systems

International Nuclear Information System (INIS)

Santhosh, T.V.; Ghosh, A.K.; Fernandes, B.G.

2012-01-01

Highlights: ► A framework for time dependent reliability prediction of I and C cables for use in PSA of NPP has been developed using stress–strength interference theory. ► The proposed methodology has been illustrated with the accelerated thermal aging data on a typical XLPE cable. ► The behavior of insulation resistance when the degradation process is linear or exponential has also been modeled. ► The reliability index or probability of failure obtained from this approach can be used in system reliability evaluation to account for cable aging for PSA of NPP. - Abstract: Instrumentation and control (I and C) cables are one of the most important components in nuclear power plants (NPPs) because they provide power to safety-related equipment and also to transmit signals to and from various controllers to perform safety operations. I and C cables in NPP are subjected to a variety of aging and degradation stressors that can produce immediate degradation or aging-related mechanisms causing the degradation of cable components over time. Although, there exits several life estimation techniques, currently there is no any standard methodology or an approach toward estimating the time dependent reliability of I and C cables that can be directly used in probabilistic safety assessment (PSA) applications. Hence, the objective of this study is to develop an approach to estimate and confirm the continued acceptable margin in cable insulation life over time subjected to aging. This paper presents a framework based on the structural reliability theory to quantify the life time of I and C cable subjecting to thermal aging. Since cross-linked polyethylene (XLPE) cables are extensively being used in Indian NPPs, the remaining life time evaluations have been carried out for a typical XLPE cable. However, the methodology can be extended to other cables such as polyvinyl chloride (PVC), ethylene propylene rubber (EPR), etc.

Base Oils Biodegradability Prediction with Data Mining Techniques

Directory of Open Access Journals (Sweden)

Malika Trabelsi

2010-02-01

Full Text Available In this paper, we apply various data mining techniques including continuous numeric and discrete classification prediction models of base oils biodegradability, with emphasis on improving prediction accuracy. The results show that highly biodegradable oils can be better predicted through numeric models. In contrast, classification models did not uncover a similar dichotomy. With the exception of Memory Based Reasoning and Decision Trees, tested classification techniques achieved high classification prediction. However, the technique of Decision Trees helped uncover the most significant predictors. A simple classification rule derived based on this predictor resulted in good classification accuracy. The application of this rule enables efficient classification of base oils into either low or high biodegradability classes with high accuracy. For the latter, a higher precision biodegradability prediction can be obtained using continuous modeling techniques.

A method for predicting the fatigue life of pre-corroded 2024-T3 aluminum from breaking load tests

Science.gov (United States)

Gruenberg, Karl Martin

Characterization of material properties is necessary for design purposes and has been a topic of research for many years. Over the last several decades, much progress has been made in identifying metrics to describe fracture mechanics properties and developing procedures to measure the appropriate values. However, in the context of design, there has not been as much success in quantifying the susceptibility of a material to corrosion damage and its subsequent impact on material behavior in the framework of fracture mechanics. A natural next step in understanding the effects of corrosion damage was to develop a link between standard material test procedures and fatigue life in the presence of corrosion. Simply stated, the goal of this investigation was to formulate a cheaper and quicker method for assessing the consequences of corrosion on remaining fatigue life. For this study, breaking load specimens and fatigue specimens of a single nominal gage (0.063″) of aluminum alloy 2024-T3 were exposed to three levels of corrosion. The breaking load specimens were taken from three different material lots, and the fatigue tests were carried out at three stress levels. All failed specimens, both breaking load and fatigue specimens, were examined to characterize the damage state(s) and failure mechanism(s). Correlations between breaking load results and fatigue life results in the presence of corrosion damage were developed using a fracture mechanics foundation and the observed mechanisms of failure. Where breaking load tests showed a decrease in strength due to increased corrosion exposure, the corresponding set of fatigue tests showed a decrease in life. And where breaking load tests from different specimen orientations exhibited similar levels of strength, the corresponding set of fatigue specimens showed similar lives. The spread from shortest to longest fatigue lives among the different corrosion conditions decreased at the higher stress levels. Life predictions based

Application of a Predictive Growth Model of Pseudomonas spp. for Estimating Shelf Life of Fresh Agaricus bisporus.

Science.gov (United States)

Wang, Jianming; Chen, Junran; Hu, Yunfeng; Hu, Hanyan; Liu, Guohua; Yan, Ruixiang

2017-10-01

For prediction of the shelf life of the mushroom Agaricus bisporus, the growth curve of the main spoilage microorganisms was studied under isothermal conditions at 2 to 22°C with a modified Gompertz model. The effect of temperature on the growth parameters for the main spoilage microorganisms was quantified and modeled using the square root model. Pseudomonas spp. were the main microorganisms causing A. bisporus decay, and the modified Gompertz model was useful for modelling the growth curve of Pseudomonas spp. All the bias factors values of the model were close to 1. By combining the modified Gompertz model with the square root model, a prediction model to estimate the shelf life of A. bisporus as a function of storage temperature was developed. The model was validated for A. bisporus stored at 6, 12, and 18°C, and adequate agreement was found between the experimental and predicted data.

Life prediction of different commercial dental implants as influence by uncertainties in their fatigue material properties and loading conditions.

Science.gov (United States)

Pérez, M A

2012-12-01

Probabilistic analyses allow the effect of uncertainty in system parameters to be determined. In the literature, many researchers have investigated static loading effects on dental implants. However, the intrinsic variability and uncertainty of most of the main problem parameters are not accounted for. The objective of this research was to apply a probabilistic computational approach to predict the fatigue life of three different commercial dental implants considering the variability and uncertainty in their fatigue material properties and loading conditions. For one of the commercial dental implants, the influence of its diameter in the fatigue life performance was also studied. This stochastic technique was based on the combination of a probabilistic finite element method (PFEM) and a cumulative damage approach known as B-model. After 6 million of loading cycles, local failure probabilities of 0.3, 0.4 and 0.91 were predicted for the Lifecore, Avinent and GMI implants, respectively (diameter of 3.75mm). The influence of the diameter for the GMI implant was studied and the results predicted a local failure probability of 0.91 and 0.1 for the 3.75mm and 5mm, respectively. In all cases the highest failure probability was located at the upper screw-threads. Therefore, the probabilistic methodology proposed herein may be a useful tool for performing a qualitative comparison between different commercial dental implants. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Life extending control: An interdisciplinary engineering thrust

Science.gov (United States)

Lorenzo, Carl F.; Merrill, Walter C.

1991-01-01

The concept of Life Extending Control (LEC) is introduced. Possible extensions to the cyclic damage prediction approach are presented based on the identification of a model from elementary forms. Several candidate elementary forms are presented. These extensions will result in a continuous or differential form of the damage prediction model. Two possible approaches to the LEC based on the existing cyclic damage prediction method, the measured variables LEC and the estimated variables LEC, are defined. Here, damage estimates or measurements would be used directly in the LEC. A simple hydraulic actuator driven position control system example is used to illustrate the main ideas behind LEC. Results from a simple hydraulic actuator example demonstrate that overall system performance (dynamic plus life) can be maximized by accounting for component damage in the control design.

Design of PH-based accelerated life testing plans under multiple-stress-type

International Nuclear Information System (INIS)

Elsayed, E.A.; Zhang Hao

2007-01-01

Accelerated life testing (ALT) is used to obtain failure time data quickly under high stress levels in order to predict product life performance under design stress conditions. Most of the previous work on designing ALT plans is focused on the application of a single stress. However, as components or products become more reliable due to technological advances, it becomes more difficult to obtain significant amount of failure data within reasonable amount of time using single stress only. Multiple-stress-type ALTs have been employed as a means of overcoming such difficulties. In this paper, we design optimum multiple-stress-type ALT plans based on the proportional hazards model. The optimum combinations of stresses and their levels are determined such that the variance of the reliability estimate of the product over a specified period of time is minimized. The use of the model is illustrated using numerical example, and sensitivity analysis shows that the resultant optimum ALT plan is robust to the deviation in model parameters

Do burnout and work engagement predict depressive symptoms and life satisfaction? A three-wave seven-year prospective study.

Science.gov (United States)

Hakanen, Jari J; Schaufeli, Wilmar B

2012-12-10

Burnout and work engagement have been viewed as opposite, yet distinct states of employee well-being. We investigated whether work-related indicators of well-being (i.e. burnout and work engagement) spill-over and generalize to context-free well-being (i.e. depressive symptoms and life satisfaction). More specifically, we examined the causal direction: does burnout/work engagement lead to depressive symptoms/life satisfaction, or the other way around? Three surveys were conducted. In 2003, 71% of all Finnish dentists were surveyed (n=3255), and the response rate of the 3-year follow-up was 84% (n=2555). The second follow-up was conducted four years later with a response rate of 86% (n=1964). Structural equation modeling was used to investigate the cross-lagged associations between the study variables across time. Burnout predicted depressive symptoms and life dissatisfaction from T1 to T2 and from T2 to T3. Conversely, work engagement had a negative effect on depressive symptoms and a positive effect on life satisfaction, both from T1 to T2 and from T2 to T3, even after adjusting for the impact of burnout at every occasion. The study was conducted among one occupational group, which limits its generalizability. Work-related well-being predicts general wellbeing in the long-term. For example, burnout predicts depressive symptoms and not vice versa. In addition, burnout and work engagement are not direct opposites. Instead, both have unique, incremental impacts on life satisfaction and depressive symptoms. Copyright © 2012 Elsevier B.V. All rights reserved.

Damage-based life prediction model for uniaxial low-cycle stress fatigue of super-elastic NiTi shape memory alloy microtubes

Science.gov (United States)

Song, Di; Kang, Guozheng; Kan, Qianhua; Yu, Chao; Zhang, Chuanzeng

2015-08-01

Based on the experimental observations for the uniaxial low-cycle stress fatigue failure of super-elastic NiTi shape memory alloy microtubes (Song et al 2015 Smart Mater. Struct. 24 075004) and a new definition of damage variable corresponding to the variation of accumulated dissipation energy, a phenomenological damage model is proposed to describe the damage evolution of the NiTi microtubes during cyclic loading. Then, with a failure criterion of Dc = 1, the fatigue lives of the NiTi microtubes are predicted by the damage-based model, the predicted lives are in good agreement with the experimental ones, and all of the points are located within an error band of 1.5 times.

Damage-based life prediction model for uniaxial low-cycle stress fatigue of super-elastic NiTi shape memory alloy microtubes

International Nuclear Information System (INIS)

Song, Di; Kang, Guozheng; Kan, Qianhua; Yu, Chao; Zhang, Chuanzeng

2015-01-01

Based on the experimental observations for the uniaxial low-cycle stress fatigue failure of super-elastic NiTi shape memory alloy microtubes (Song et al 2015 Smart Mater. Struct. 24 075004) and a new definition of damage variable corresponding to the variation of accumulated dissipation energy, a phenomenological damage model is proposed to describe the damage evolution of the NiTi microtubes during cyclic loading. Then, with a failure criterion of D c = 1, the fatigue lives of the NiTi microtubes are predicted by the damage-based model, the predicted lives are in good agreement with the experimental ones, and all of the points are located within an error band of 1.5 times. (paper)

The experience of work-life balance across family-life stages in Switzerland: a cross-sectional questionnaire-based study.

Science.gov (United States)

Wepfer, Ariane G; Brauchli, Rebecca; Jenny, Gregor J; Hämmig, Oliver; Bauer, Georg F

2015-12-24

The division of paid and unpaid labor in families continues to be highly gendered with men doing more paid work and women doing more unpaid care work. This is especially true for life stages with young children. Our study investigates the subjective experience of demands in the work and the private domain and the experience of work-life balance across family-life stages as a consequence of this gendered division of labor. We used data from a survey study on work-life issues and health in four large companies in Switzerland (N = 3664). In line with our hypotheses, subjective work and private demands were predicted by an interaction of family-life stages and gender. Specifically, during the primary child-rearing family-life stages, women experience more private demands than men while men experience more work demands, regardless of level of employment. Furthermore, women who work part time experience more work-life balance than women who work full time and more than men who work part or full time during the primary child-rearing family-life stages. Results are discussed in terms of a gendered work-life experience across the life course and the need for part-time work for both genders. Finally, conclusions are drawn concerning our results' implications for public health considerations.

Factors predicting quality of work life among nurses in tertiary-level hospitals, Bangladesh.

Science.gov (United States)

Akter, N; Akkadechanunt, T; Chontawan, R; Klunklin, A

2018-06-01

This study examined the level of quality of work life and predictability of years of education, monthly income, years of experience, job stress, organizational commitment and work environment on quality of work life among nurses in tertiary-level hospitals in the People's Republic of Bangladesh. There is an acute shortage of nurses worldwide including Bangladesh. Quality of work life is important for quality of patient care and nurse retention. Nurses in Bangladesh are fighting to provide quality care for emerging health problems for the achievement of sustainable development goals. We collected data from 288 randomly selected registered nurses, from six tertiary-level hospitals. All nurses were requested to fill questionnaire consisted of Demographic Data Sheet, Quality of Nursing Work Life Survey, Expanded Nursing Stress Scale, Questionnaire of Organizational Commitment and Practice Environment Scale of the Nursing Work Index. Data were analysed by descriptive statistics and multiple regression. The quality of work life as perceived by nurses in Bangladesh was at moderate level. Monthly income was found as the best predictor followed by work environment, organizational commitment and job stress. A higher monthly income helps nurses to fulfil their personal needs; positive work environment helps to provide quality care to the patients. Quality of work life and predictors measured by self-report only may not reflect the original picture of the quality of work life among nurses. Findings provide information for nursing and health policymakers to develop policies to improve quality of work life among nurses that can contribute to quality of nursing care. This includes the working environment, commitment to the organization and measures to reduce job stress. © 2017 International Council of Nurses.

The influence of temperature on low cycle fatigue behavior of prior cold worked 316L stainless steel (II) : life prediction and failure mechanism

International Nuclear Information System (INIS)

Hong, Seong Gu; Yoon, Sam Son; Lee, Soon Bok

2003-01-01

Tensile and low cycle fatigue tests on prior cold worked 316L stainless steel were carried out at various temperatures from room temperature to 650 deg. C. Fatigue resistance was decreased with increasing temperature and decreasing strain rate. Cyclic plastic deformation, creep, oxidation and interactions with each other are thought to be responsible for the reduction in fatigue resistance. Currently favored life prediction models were examined and it was found that it is important to select a proper life prediction parameter since stress-strain relation strongly depends on temperature. A phenomenological life prediction model was proposed to account for the influence of temperature on fatigue life and assessed by comparing with experimental result. LCF failure mechanism was investigated by observing fracture surfaces of LCF failed specimens with SEM

Phenomenological approach to precise creep life prediction by means of quantitative evaluation of strain rate acceleration in secondary creep

International Nuclear Information System (INIS)

Sato, Hiroyuki; Miyano, Takaya

2010-01-01

A method of creep life prediction by means of Strain-Acceleration-Parameter (SAP), α, is presented. The authors show that the shape of creep curve can be characterized by SAP that reflects magnitude of strain-rate change in secondary creep. The SAP-values, α are evaluated on magnesium-aluminium solution hardened alloys. Reconstruction of creep curves by combinations of SAP and minimum-creep rates are successfully performed, and the curves reasonably agree with experiments. The advantage of the proposed method is that the required parameters evaluated from individual creep curves are directly connected with the minimum creep rate. The predicted times-to-failure agree well with that obtained by experiments, and possibility of precise life time prediction by SAP is pronounced.

Life-Stage Physiologically-Based Pharmacokinetic (PBPK) ...

Science.gov (United States)

This presentation discusses methods used to extrapolate from in vitro high-throughput screening (HTS) toxicity data for an endocrine pathway to in vivo for early life stages in humans, and the use of a life stage PBPK model to address rapidly changing physiological parameters. Adverse outcome pathways (AOPs), in this case endocrine disruption during development, provide a biologically-based framework for linking molecular initiating events triggered by chemical exposures to key events leading to adverse outcomes. The application of AOPs to human health risk assessment requires extrapolation of in vitro HTS toxicity data to in vivo exposures (IVIVE) in humans, which can be achieved through the use of a PBPK/PD model. Exposure scenarios for chemicals in the PBPK/PD model will consider both placental and lactational transfer of chemicals, with a focus on age dependent dosimetry during fetal development and after birth for a nursing infant. This talk proposes a universal life-stage computational model that incorporates changing physiological parameters to link environmental exposures to in vitro levels of HTS assays related to a developmental toxicological AOP for vascular disruption. In vitro toxicity endpoints discussed are based on two mechanisms: 1) Fetal vascular disruption, and 2) Neurodevelopmental toxicity induced by altering thyroid hormone levels in neonates via inhibition of thyroperoxidase in the thyroid gland. Application of our Life-stage computati

Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data

Directory of Open Access Journals (Sweden)

Esther I. Metting

2016-01-01

Full Text Available The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215. Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%. Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool.

Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data

Science.gov (United States)

in ’t Veen, Johannes C.C.M.; Dekhuijzen, P.N. Richard; van Heijst, Ellen; Kocks, Janwillem W.H.; Muilwijk-Kroes, Jacqueline B.; Chavannes, Niels H.; van der Molen, Thys

2016-01-01

The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years) with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD) service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215). Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS) patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%). Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool. PMID:27730177

Childhood asthma-predictive phenotype.

Science.gov (United States)

Guilbert, Theresa W; Mauger, David T; Lemanske, Robert F

2014-01-01

Wheezing is a fairly common symptom in early childhood, but only some of these toddlers will experience continued wheezing symptoms in later childhood. The definition of the asthma-predictive phenotype is in children with frequent, recurrent wheezing in early life who have risk factors associated with the continuation of asthma symptoms in later life. Several asthma-predictive phenotypes were developed retrospectively based on large, longitudinal cohort studies; however, it can be difficult to differentiate these phenotypes clinically as the expression of symptoms, and risk factors can change with time. Genetic, environmental, developmental, and host factors and their interactions may contribute to the development, severity, and persistence of the asthma phenotype over time. Key characteristics that distinguish the childhood asthma-predictive phenotype include the following: male sex; a history of wheezing, with lower respiratory tract infections; history of parental asthma; history of atopic dermatitis; eosinophilia; early sensitization to food or aeroallergens; or lower lung function in early life. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Prediction of creep-fatigue life by use of creep rupture ductility

International Nuclear Information System (INIS)

Yamaguchi, Koji; Suzuki, Naoyuki; Ijima, Kiyoshi; Kanazawa, Kenji

1985-01-01

It was clarified that tension strain hold reduced creep-fatigue life of many engineering materials in different degrees depending on material, temperature and test duration. However the reduction in the life due to holding for various durations could be correlated to the fraction of intergranular facets on fracture surfaces which was considered to be an index of the damage introduced during strain hold. This fraction of intergranular facets by creep-fatigue failure exhibited a direct relation to the creep rupture ductility of the material tested at the same temperature and for the same creep-fatigue life-time. From these results an empirical equation has been derived as follow; (Δ sub(epsilonsub(i)))/Dsub(c).(N sub(h sup(α))) = C, where Δ sub(epsilonsub(i)) is inelastic strain range, Dsub(c) is the creep rupture ductility for the same duration as creep-fatigue life time, Nsub(h) is the creep-fatigue life under tension strain hold conditions, and α and C are constants depending on the material and testing temperature. From the equation the life prediction is possible for a given inelastic strain range Δ sub(epsilonsub(i)) if the constants α and C, and Dsub(c) are known. The value of α was found to be 0.62 and 0.74 for various austenitic stainless steels and NCF800 at 600 0 C and 700 0 C, respectively, and 0.69 for 1 1/4Cr-1/2Mo steel at 600 0 C. The value of C was found to be 0.50 and 0.59 for various austenitic stainless steels and NCF800 at 600 0 C and 700 0 C, respectively, and 0.49 for 1 1/4Cr-1/2Mo steel at 600 0 C. The creep rupture ductility Dsub(c) is available in the NRIM Creep Data Sheets up to 10 5 h for multi-heats of many kinds of heat resistant alloys. (author)

Quality of life after surgical treatment of coarctation in long-term follow-up (CoAFU): Predictive value of clinical variables.

Science.gov (United States)

Bambul Heck, Pinar; Pabst von Ohain, Jelena; Kaemmerer, Harald; Ewert, Peter; Hager, Alfred

2018-01-01

We sought to analyze the quality of life and the predictive value of clinical variables from previous follow-up study in patients late after surgical treatment of aortic coarctation on the quality of life. All patients, who have participated in the prospective cross-sectional COALA Study in 2000 with a structural clinical investigation including blood pressure measurement and symptom-limited exercise test were contacted for the health-related quality of life questionnaire SF-36 from January 2013 through December 2014. From 273 eligible patients, we received data from 135 patients, 9 of them died during the follow-up time at the median age of 46years (range 30-64years). Seventy-four patients did not participate in the study, other 64 patients moved to remote or unknown areas and could not be contacted. Quality of life was good in the fields of physical role and pain. However, patients reported a significant impairment in general health and in health transition, depending on the age. Arterial hypertension and variables from echocardiography or exercise testing from the COALA study were not predictive on functional health status. Quality of life in patients late after aortic coarctation repair is fairly good compared with healthy controls. Impairments in general health and health transition depend mainly on age, can be explained due to numerous comorbidities and reinterventions in long-term. The predictive value of the commonly assessed clinical variables on quality of life is limited. Copyright © 2017. Published by Elsevier B.V.

Thermomechanical Fatigue of Ductile Cast Iron and Its Life Prediction

Science.gov (United States)

Wu, Xijia; Quan, Guangchun; MacNeil, Ryan; Zhang, Zhong; Liu, Xiaoyang; Sloss, Clayton

2015-06-01

Thermomechanical fatigue (TMF) behaviors of ductile cast iron (DCI) were investigated under out-of-phase (OP), in-phase (IP), and constrained strain-control conditions with temperature hold in various temperature ranges: 573 K to 1073 K, 723 K to 1073 K, and 433 K to 873 K (300 °C to 800 °C, 450 °C to 800 °C, and 160 °C to 600 °C). The integrated creep-fatigue theory (ICFT) model was incorporated into the finite element method to simulate the hysteresis behavior and predict the TMF life of DCI under those test conditions. With the consideration of four deformation/damage mechanisms: (i) plasticity-induced fatigue, (ii) intergranular embrittlement, (iii) creep, and (iv) oxidation, as revealed from the previous study on low cycle fatigue of the material, the model delineates the contributions of these physical mechanisms in the asymmetrical hysteresis behavior and the damage accumulation process leading to final TMF failure. This study shows that the ICFT model can simulate the stress-strain response and life of DCI under complex TMF loading profiles (OP and IP, and constrained with temperature hold).

Development and validation of a method to predict coal pillar life in South Africa

Energy Technology Data Exchange (ETDEWEB)

Van Der Merwe, J.N. [Pretoria Univ., Dept. of Mining Engineering (South Africa)

2005-07-01

One of the most difficult aspects of mine closure procedures, is to predict the long term stability of pillars in the case of coal mining. In South African coal mining, pillars have been designed since the late 1960's with the aid of a pillar strength formula based on statistical analysis of failed pillar cases by the well known team of Salamon and Munro. They developed the widely used power formula for pillar strength. Since that time, however, the data base of failed pillars has effectively doubled in size and re-analysis of the new data indicated that the original pillar strength of small pillars may have been over estimated. The data was then extensively re-analysed and a more effective linear formula for pillar strength was found. The most important differences between the two formulae are that the predicted strength of small pillars are lower and the strength of larger pillars, higher with the new formula. However, neither of the two methods explicitly cater for the prediction of the expected time of stability of coal pillars. No direct correlation between the safety factors and the period of stability of pillars could be found. It was then determined that the most frequent mode of pillar failure was by progressive scaling. Using the new formula to determine a minimum value of pillar safety factor (i.e. the safety factor at which failure can be taken as guaranteed to occur), the final sizes - after scaling - at which the failed pillars had to be in order to fail, were determined. The differences between the original dimensions and the postulated final dimensions were then used to calculate a rate of pillar scaling. The rate was then re-applied to the original data bases of both failed and intact pillar cases and distinct differences were found. The projected lives of the failed pillars were substantially shorter than the projected lives of the intact pillars. While this inspired confidence in the procedure, it was still based on an assumed and unproven

Development and validation of a method to predict coal pillar life in South Africa

International Nuclear Information System (INIS)

Van Der Merwe, J.N.

2005-01-01

One of the most difficult aspects of mine closure procedures, is to predict the long term stability of pillars in the case of coal mining. In South African coal mining, pillars have been designed since the late 1960's with the aid of a pillar strength formula based on statistical analysis of failed pillar cases by the well known team of Salamon and Munro. They developed the widely used power formula for pillar strength. Since that time, however, the data base of failed pillars has effectively doubled in size and re-analysis of the new data indicated that the original pillar strength of small pillars may have been over estimated. The data was then extensively re-analysed and a more effective linear formula for pillar strength was found. The most important differences between the two formulae are that the predicted strength of small pillars are lower and the strength of larger pillars, higher with the new formula. However, neither of the two methods explicitly cater for the prediction of the expected time of stability of coal pillars. No direct correlation between the safety factors and the period of stability of pillars could be found. It was then determined that the most frequent mode of pillar failure was by progressive scaling. Using the new formula to determine a minimum value of pillar safety factor (i.e. the safety factor at which failure can be taken as guaranteed to occur), the final sizes - after scaling - at which the failed pillars had to be in order to fail, were determined. The differences between the original dimensions and the postulated final dimensions were then used to calculate a rate of pillar scaling. The rate was then re-applied to the original data bases of both failed and intact pillar cases and distinct differences were found. The projected lives of the failed pillars were substantially shorter than the projected lives of the intact pillars. While this inspired confidence in the procedure, it was still based on an assumed and unproven rate

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

Science.gov (United States)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Optimization of rock-bit life based on bearing failure criteria

International Nuclear Information System (INIS)

Feav, M.J.; Thorogood, J.L.; Whelehan, O.P.; Williamson, H.S.

1992-01-01

This paper reports that recent advances in rock-bit seal technology have allowed greater predictability of bearing life. Cone loss following bearing failure incurs costs related to remedial activities. A risk analysis approach, incorporating bearing-life relationships and the inter-dependence of drilling events, is used to formulate a bit-run cost-optimization method. The procedure enables a choice to be made between elastomeric and metal seals on a lowest-replacement-cost basis. The technique also provides a formal method for assessing the opportunity cost for using a device to detect bit-bearing failures downhole

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder

Science.gov (United States)

Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant’s treatment outcome may help during antidepressant’s selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant’s treatment outcome for the MDD patients. PMID:28152063

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

Science.gov (United States)

Mumtaz, Wajid; Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad; Malik, Aamir Saeed

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.

Lithium iron phosphate based battery – Assessment of the aging parameters and development of cycle life model

International Nuclear Information System (INIS)

Omar, Noshin; Monem, Mohamed Abdel; Firouz, Yousef; Salminen, Justin; Smekens, Jelle; Hegazy, Omar; Gaulous, Hamid; Mulder, Grietus; Van den Bossche, Peter; Coosemans, Thierry; Van Mierlo, Joeri

2014-01-01

Highlights: • Extended life cycle tests. • Investigation of the battery life cycle at different working conditions. • Investigation of the impact fast charging on the battery performances. • Extraction all required relationship for development of a cycle life model. • Development of a new life cycle model. - Abstract: This paper represents the evaluation of ageing parameters in lithium iron phosphate based batteries, through investigating different current rates, working temperatures and depths of discharge. From these analyses, one can derive the impact of the working temperature on the battery performances over its lifetime. At elevated temperature (40 °C), the performances are less compared to at 25 °C. The obtained mathematical expression of the cycle life as function of the operating temperature reveals that the well-known Arrhenius law cannot be applied to derive the battery lifetime from one temperature to another. Moreover, a number of cycle life tests have been performed to illustrate the long-term capabilities of the proposed battery cells at different discharge constant current rates. The results reveal the harmful impact of high current rates on battery characteristics. On the other hand, the cycle life test at different depth of discharge levels indicates that the battery is able to perform 3221 cycles (till 80% DoD) compared to 34,957 shallow cycles (till 20% DoD). To investigate the cycle life capabilities of lithium iron phosphate based battery cells during fast charging, cycle life tests have been carried out at different constant charge current rates. The experimental analysis indicates that the cycle life of the battery degrades the more the charge current rate increases. From this analysis, one can conclude that the studied lithium iron based battery cells are not recommended to be charged at high current rates. This phenomenon affects the viability of ultra-fast charging systems. Finally, a cycle life model has been developed, which

A real-life, ecologically valid test of executive functioning : The executive secretarial task

NARCIS (Netherlands)

Lamberts, Kirsten F.; Evans, Jonathan J.; Spikman, Jacoba M.

2010-01-01

A major goal of neuropsychological assessment is predicting a person's level of functioning in daily life. Making predictions about everyday executive functioning based on tests is problematic because of the contrast between demands made in the test environment and demands made in everyday life

Engaging Physician Learners Through a Web-Based Platform: Individualized End-of-Life Education.

Science.gov (United States)

Bergman, Jonathan; Ballon-Landa, Eric; Lerman, Steven E; Kwan, Lorna; Bennett, Carol J; Litwin, Mark S

2016-09-01

Web-based modules provide a convenient and low-cost education platform, yet should be carefully designed to ensure that learners are actively engaged. In order to improve attitudes and knowledge in end-of-life (EOL) care, we developed a web-based educational module that employed hyperlinks to allow users access to auxiliary resources: clinical guidelines and seminal research papers. Participants took pre-test evaluations of attitudes and knowledge regarding EOL care prior to accessing the educational module, and a post-test evaluation following the module intervention. We recorded the type of hyperlinks (guideline or paper) accessed by learners, and stratified participants into groups based on link type accessed (none, either, or both). We used demographic and educational data to develop a multivariate mixed-effects regression analysis to develop adjusted predictions of attitudes and knowledge. 114 individuals participated. The majority had some professional exposure to EOL care (prior instruction 62%; EOL referral 53%; EOL discussion 56%), though most had no family (68%) or personal experience (51%). On bivariate analysis, non-partnered (p = .04), medical student training level (p = .03), prior palliative care referral (p = .02), having a family member (p = .02) and personal experience of EOL care (p improvements. Auxiliary resources accessible by hyperlink are an effective adjunct to web-based learning in end-of-life care. © The Author(s) 2015.

Towards evaluation and prediction of building sustainability using life cycle behaviour simulation

Directory of Open Access Journals (Sweden)

Marzouk Mohamed

2017-01-01

Full Text Available Nowadays researchers and practitioners are oriented towards questioning how effective are the different building life cycle activities contribution to preserving the environment and fulfilling the need for equilibrium. Terminologies such as Building sustainability and Green Buildings have long been adopted yet the evaluation of such has been driven through the use of rating systems. LEED of the United States, BREEAM of the United Kingdom, and Pearl of the United Arab Emirates are namely good examples of these rating systems. This paper introduces a new approach for evaluation of building life cycle sustainability through simulation of activities interaction and studying its behaviour. The effort focuses on comprehending impact and effect of suitability related activities over the whole building life cycle or period of time. The methodology includes gathering a pool of parameters through benchmarking of five selected rating systems, analytical factorization for the gathered parameters is used to elect the most influencing parameters. Followed by simulation modelling using System dynamics to capture the interaction of the considered parameters. The resulting behaviour obtained from simulation is studied and used in designing a tool for prediction of sustainability.

Thermal aging of some decommissioned reactor components and methodology for life prediction

International Nuclear Information System (INIS)

Chung, H.M.

1989-03-01

Since a realistic aging of cast stainless steel components for end-of-life or life-extension conditions cannot be produced, it is customary to simulate the thermal aging embrittlement by accelerated aging at ∼400 degree C. In this investigation, field components obtained from decommissioned reactors have been examined after service up to 22 yr to provide a benchmark of the laboratory simulation. The primary and secondary aging processes were found to be identical to those of the laboratory-aged specimens, and the kinetic characteristics were also similar. The extent of the aging embrittlement processes and other key factors that are known to influence the embrittlement kinetics have been compared for the decommissioned reactor components and materials aged under accelerated conditions. On the basis of the study, a mechanistic understanding of the causes of the complex behavior in kinetics and activation energy of aging (i.e., the temperature dependence of aging embrittlement between the accelerated and reactor-operating conditions) is presented. A mechanistic correlation developed thereon is compared with a number of available empirical correlations to provide an insight for development of a better methodology of life prediction of the reactor components. 18 refs., 18 figs., 5 tabs

Characterizing Cracking and Permanent Deformation; An Attempt for Predicting the End of the Structural Pavement Life

NARCIS (Netherlands)

Pramesti, F.P.; Molenaar, A.A.A.; van de Ven, M.F.C.

2017-01-01

Durable, therefore sustainable, road needs to attain specific characteristics, among others, resistance to permanent deformation and cracking. Determining the development of both characteristics are important to be able to predict pavement life and performance. In this research, permanent

Prediction of clearance, volume of distribution and half-life by allometric scaling and by use of plasma concentrations predicted from pharmacokinetic constants: a comparative study.

Science.gov (United States)

Mahmood, I

1999-08-01

Pharmacokinetic parameters (clearance, CL, volume of distribution in the central compartment, VdC, and elimination half-life, t1/2beta) predicted by an empirical allometric approach have been compared with parameters predicted from plasma concentrations calculated by use of the pharmacokinetic constants A, B, alpha and beta, where A and B are the intercepts on the Y axis of the plot of plasma concentration against time and alpha and beta are the rate constants, both pairs of constants being for the distribution and elimination phases, respectively. The pharmacokinetic parameters of cefpiramide, actisomide, troglitazone, procaterol, moxalactam and ciprofloxacin were scaled from animal data obtained from the literature. Three methods were used to generate plots for the prediction of clearance in man: dependence of clearance on body weight (simple allometric equation); dependence of the product of clearance and maximum life-span potential (MLP) on body weight; and dependence of the product of clearance and brain weight on body weight. Plasma concentrations of the drugs were predicted in man by use of A, B, alpha and beta obtained from animal data. The predicted plasma concentrations were then used to calculate CL, VdC and t1/2beta. The pharmacokinetic parameters predicted by use of both approaches were compared with measured values. The results indicate that simple allometry did not predict clearance satisfactorily for actisomide, troglitazone, procaterol and ciprofloxacin. Use of MLP or the product of clearance and brain weight improved the prediction of clearance for these four drugs. Except for troglitazone, VdC and t1/2beta predicted for man by use of the allometric approach were comparable with measured values for the drugs studied. CL, VdC and t1/2beta predicted by use of pharmacokinetic constants were comparable with values predicted by simple allometry. Thus, if simple allometry failed to predict clearance of a drug, so did the pharmacokinetic constant

ADHD Symptoms in Middle Adolescence Predict Exposure to Person-Related Life Stressors in Late Adolescence in 5-HTTLPR S-allele Homozygotes.

Science.gov (United States)

Brinksma, Djûke M; Hoekstra, Pieter J; de Bildt, Annelies; Buitelaar, Jan K; van den Hoofdakker, Barbara J; Hartman, Catharina A; Dietrich, Andrea

2017-12-19

Literature suggests that life stressors predict attention-deficit/hyperactivity disorder (ADHD) symptoms and that this relationship is moderated by the serotonin transporter polymorphism (5-HTTLPR). It is less clear whether, on reverse, ADHD symptoms may influence the risk of exposure to life stressors. Furthermore, the role of life stressors may vary across development depending on the type of life stressor. We used threewave longitudinal data of 1,306 adolescents from the general population and clinicreferred cohort of the TRacking Adolescents' Individual Lives Survey. The 5-HTTLPR genotype (SS, LS, LL), parent-reported ADHD symptoms at three time points (T1: Mage = 11.2; T2: Mage = 13.5; T3: Mage = 16.2 years), and the number of personrelated ('dependent') and environment-related ('independent') life stressors occurring between measurements (T1-T2, T2-T3) were assessed. Using path analyses, we examined bidirectional relations between exposure to these life stressors and ADHD symptoms between the separate waves moderated by 5-HTTLPR status. Exposure to life stressors did not predict ADHD symptoms. Rather, we found that in 5-HTTLPR Sallele homozygotes, ADHD symptoms in middle adolescence (T2) predicted exposure to the number of person-related life stressors later in adolescence (T2-T3, p = 0.001). There was no relation with environment-related life stressors. Our study suggests that S-allele homozygotes with higher levels of ADHD symptoms in middle adolescence are more vulnerable to becoming exposed to person-related ('dependent') life stressors in late adolescence. Findings emphasize the need to be aware of social-emotional adversities that may occur in genetically vulnerable adolescents with ADHD symptoms in the transition into adulthood.

A comprehensive energy approach to predict fatigue life in CuAlBe shape memory alloy

International Nuclear Information System (INIS)

Sameallah, S; Kadkhodaei, M; Legrand, V; Saint-Sulpice, L; Arbab Chirani, S

2015-01-01

Stabilized dissipated energy is an effective parameter on the fatigue life of shape memory alloys (SMAs). In this study, a formula is proposed to directly evaluate the stabilized dissipated energy for different values of the maximum and minimum applied stresses, as well as the loading frequency, under cyclic tensile loadings. To this aim, a one-dimensional fully coupled thermomechanical constitutive model and a cycle-dependent phase diagram are employed to predict the uniaxial stress-strain response of an SMA in a specified cycle, including the stabilized one, with no need of obtaining the responses of the previous cycles. An enhanced phase diagram in which different slopes are defined for the start and finish of a backward transformation strip is also proposed to enable the capture of gradual transformations in a CuAlBe shape memory alloy. It is shown that the present approach is capable of reproducing the experimental responses of CuAlBe specimens under cyclic tensile loadings. An explicit formula is further presented to predict the fatigue life of CuAlBe as a function of the maximum and minimum applied stresses as well as the loading frequency. Fatigue tests are also carried out, and this formula is verified against the empirically predicted number of cycles for failure. (paper)

A comprehensive energy approach to predict fatigue life in CuAlBe shape memory alloy

Science.gov (United States)

Sameallah, S.; Legrand, V.; Saint-Sulpice, L.; Kadkhodaei, M.; Arbab Chirani, S.

2015-02-01

Stabilized dissipated energy is an effective parameter on the fatigue life of shape memory alloys (SMAs). In this study, a formula is proposed to directly evaluate the stabilized dissipated energy for different values of the maximum and minimum applied stresses, as well as the loading frequency, under cyclic tensile loadings. To this aim, a one-dimensional fully coupled thermomechanical constitutive model and a cycle-dependent phase diagram are employed to predict the uniaxial stress-strain response of an SMA in a specified cycle, including the stabilized one, with no need of obtaining the responses of the previous cycles. An enhanced phase diagram in which different slopes are defined for the start and finish of a backward transformation strip is also proposed to enable the capture of gradual transformations in a CuAlBe shape memory alloy. It is shown that the present approach is capable of reproducing the experimental responses of CuAlBe specimens under cyclic tensile loadings. An explicit formula is further presented to predict the fatigue life of CuAlBe as a function of the maximum and minimum applied stresses as well as the loading frequency. Fatigue tests are also carried out, and this formula is verified against the empirically predicted number of cycles for failure.

Prediction based on mean subset

DEFF Research Database (Denmark)

Øjelund, Henrik; Brown, P. J.; Madsen, Henrik

2002-01-01

, it is found that the proposed mean subset method has superior prediction performance than prediction based on the best subset method, and in some settings also better than the ridge regression and lasso methods. The conclusions drawn from the Monte Carlo study is corroborated in an example in which prediction......Shrinkage methods have traditionally been applied in prediction problems. In this article we develop a shrinkage method (mean subset) that forms an average of regression coefficients from individual subsets of the explanatory variables. A Bayesian approach is taken to derive an expression of how...... the coefficient vectors from each subset should be weighted. It is not computationally feasible to calculate the mean subset coefficient vector for larger problems, and thus we suggest an algorithm to find an approximation to the mean subset coefficient vector. In a comprehensive Monte Carlo simulation study...

Optimization of Aeroengine Shop Visit Decisions Based on Remaining Useful Life and Stochastic Repair Time

Directory of Open Access Journals (Sweden)

Jing Cai

2016-01-01

Full Text Available Considering the wide application of condition-based maintenance in aeroengine maintenance practice, it becomes possible for aeroengines to carry out their preventive maintenance in just-in-time (JIT manner by reasonably planning their shop visits (SVs. In this study, an approach is proposed to make aeroengine SV decisions following the concept of JIT. Firstly, a state space model (SSM for aeroengine based on exhaust gas temperature margin is developed to predict the remaining useful life (RUL of aeroengine. Secondly, the effect of SV decisions on risk and service level (SL is analyzed, and an optimization of the aeroengine SV decisions based on RUL and stochastic repair time is performed to carry out JIT manner with the requirement of safety and SL. Finally, a case study considering two CFM-56 aeroengines is presented to demonstrate the proposed approach. The results show that predictive accuracy of RUL with SSM is higher than with linear regression, and the process of SV decisions is simple and feasible for airlines to improve the inventory management level of their aeroengines.

Reliability and lifetime predictions of SLC klystrons

International Nuclear Information System (INIS)

Allen, M.A.; Callin, R.S.; Fowkes, W.R.; Lee, T.G.; Vlieks, A.E.

1989-01-01

The energy upgrade of SLAC, with the first of the new 67 MW SLAC Linear Collider (SLC) klystrons, began over four years ago. Today there are over 200 of these klystrons in operation. As a result, there is a wealth of klystron performance and failure information that enables reasonable predictions to be made on life expectancy and reliability. Data from initial tests, follow-up tests and daily operation monitoring on the accelerator is stored for analysis. Presented here are life expectancy predictions with particular emphasis on cathode life. Also, based on this data, the authors will discuss some of the principal modes of failure. 3 refs., 2 figs., 1 tab

Reliability and lifetime predictions of SLC klystrons

International Nuclear Information System (INIS)

Allen, M.A.; Callin, R.S.; Fowkes, W.R.; Lee, T.G.; Vlieks, A.E.

1989-03-01

The energy upgrade of SLAC, with the first of the new 67 MW SLAC Linear Collider (SLC) klystrons, began over four years ago. Today there are over 200 of these klystrons in operation. As a result, there is a wealth klystron performance and failure information that enables reasonable predictions to be made on life expectancy and reliability. Data from initial tests, follow-up tests and daily operation monitoring on the accelerator is stores for analysis. Presented here are life expectancy predictions with particular emphasis on cathode life. Also, based on this data, we will discuss some of the principal modes of failure. 3 refs., 2 figs

Probabilistic approaches to life prediction of nuclear plant structural components

International Nuclear Information System (INIS)

Villain, B.; Pitner, P.; Procaccia, H.

1996-01-01

In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in a assessment of the performance of these structural components, probabilistic methods. The benefits of a probabilistic approach are the clear treatment of uncertainly and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel). (authors)

Probabilistic approaches to life prediction of nuclear plant structural components

International Nuclear Information System (INIS)

Villain, B.; Pitner, P.; Procaccia, H.

1996-01-01

In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in an assessment of the performance of these structural components, probabilistic methods provide an attractive alternative or supplement to more conventional deterministic methods. The benefits of a probabilistic approach are the clear treatment of uncertainty and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel)

Energy based prediction models for building acoustics

DEFF Research Database (Denmark)

Brunskog, Jonas

2012-01-01

In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

Residual life of technical systems; diagnosis, prediction and life extension

International Nuclear Information System (INIS)

Reinertsen, Rune

1996-01-01

The paper presents and discusses research related to residual life of non-repairable and repairable technical systems. Diagnosis of systems and extension of residual life of technical systems are also presented and discussed. This paper concludes that research published describing determination and extension of residual life as well as methods for diagnosis of non-repairable and repairable technical systems, is somewhat limited. Many papers have a rather pragmatic approach. The authors only describe special cases from their own plant and do not provide any explanation of a more academical nature. The other papers are mainly describing very specific applications of statistical models, leaving the more general case out of consideration. One of the main results of this paper is to point out these facts, and thereby identify the need for future research in this area

Predicting Smartphone Battery Life based on Comprehensive and Real-time Usage Data

OpenAIRE

Li, Huoran; Liu, Xuanzhe; Mei, Qiaozhu

2018-01-01

Smartphones and smartphone apps have undergone an explosive growth in the past decade. However, smartphone battery technology hasn't been able to keep pace with the rapid growth of the capacity and the functionality of smartphones and apps. As a result, battery has always been a bottleneck of a user's daily experience of smartphones. An accurate estimation of the remaining battery life could tremendously help the user to schedule their activities and use their smartphones more efficiently. Ex...

Integration of artificial intelligence methods and life cycle assessment to predict energy output and environmental impacts of paddy production.

Science.gov (United States)

Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing

2018-08-01

Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

Extending Theory-Based Quantitative Predictions to New Health Behaviors.

Science.gov (United States)

Brick, Leslie Ann D; Velicer, Wayne F; Redding, Colleen A; Rossi, Joseph S; Prochaska, James O

2016-04-01

Traditional null hypothesis significance testing suffers many limitations and is poorly adapted to theory testing. A proposed alternative approach, called Testing Theory-based Quantitative Predictions, uses effect size estimates and confidence intervals to directly test predictions based on theory. This paper replicates findings from previous smoking studies and extends the approach to diet and sun protection behaviors using baseline data from a Transtheoretical Model behavioral intervention (N = 5407). Effect size predictions were developed using two methods: (1) applying refined effect size estimates from previous smoking research or (2) using predictions developed by an expert panel. Thirteen of 15 predictions were confirmed for smoking. For diet, 7 of 14 predictions were confirmed using smoking predictions and 6 of 16 using expert panel predictions. For sun protection, 3 of 11 predictions were confirmed using smoking predictions and 5 of 19 using expert panel predictions. Expert panel predictions and smoking-based predictions poorly predicted effect sizes for diet and sun protection constructs. Future studies should aim to use previous empirical data to generate predictions whenever possible. The best results occur when there have been several iterations of predictions for a behavior, such as with smoking, demonstrating that expected values begin to converge on the population effect size. Overall, the study supports necessity in strengthening and revising theory with empirical data.

PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

Directory of Open Access Journals (Sweden)

Jiangning Song

Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

Directory of Open Access Journals (Sweden)

Wenbiao Li

2016-04-01

Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

Parent reports of health-related quality of life and heart failure severity score independently predict outcome in children with dilated cardiomyopathy.

Science.gov (United States)

den Boer, Susanna L; Baart, Sara J; van der Meulen, Marijke H; van Iperen, Gabriëlle G; Backx, Ad P; Ten Harkel, Arend D; Rammeloo, Lukas A; du Marchie Sarvaas, Gideon J; Tanke, Ronald B; Helbing, Willem A; Utens, Elisabeth M; Dalinghaus, Michiel

2017-08-01

Dilated cardiomyopathy in children causes heart failure and has a poor prognosis. Health-related quality of life in this patient group is unknown. Moreover, results may provide detailed information of parents' sense of their child's functioning. We hypothesised that health-related quality of life, as rated by parents, and the paediatric heart failure score, as assessed by physicians, have both predictive value on outcome. Methods and results In this prospective study, health-related quality of life was assessed by parent reports: the Infant Toddler Quality of Life questionnaire (0-4 years) or Child Health Questionnaire-Parent Form 50 (4-18 years) at 3-6-month intervals. We included 90 children (median age 3.8 years, interquartile range (IQR) 0.9-12.3) whose parents completed 515 questionnaires. At the same visit, physicians completed the New York University Pediatric Heart Failure Index. Compared with Dutch normative data, quality of life was severely impaired at diagnosis (0-4 years: 7/10 subscales and 4-18 years: 8/11 subscales) and ⩾1 year after diagnosis (3/10 and 6/11 subscales). Older children were more impaired (pFailure Index were independently predictive of the risk of death and heart transplantation (hazard ratio 1.24 per 10% decrease of predicted, 95% confidence interval (CI) 1.06-1.47 and hazard ratio 1.38 per unit, 95% CI 1.19-1.61, respectively). Physical impairment rated by parents and heart failure severity assessed by physicians independently predicted the risk of death or heart transplantation in children with dilated cardiomyopathy.

Arrhenius equation modeling for the shelf life prediction of tomato paste containing a natural preservative.

Science.gov (United States)

Jafari, Seid Mahdi; Ganje, Mohammad; Dehnad, Danial; Ghanbari, Vahid; Hajitabar, Javad

2017-12-01

The shelf life of tomato paste with microencapsulated olive leaf extract was compared with that of samples containing a commercial preservative by accelerated shelf life testing. Based on previous studies showing that olive leaf extract as a rich source of phenolic compounds can have antimicrobial properties, application of its encapsulated form to improve the storage stability of tomato paste is proposed here. Regarding total soluble solids, the control and the sample containing 1000 µg g -1 sodium benzoate had the lowest (Q 10  = 1.63) and highest (Q 10  = 1.88) sensitivity to temperature changes respectively; also, the microencapsulated sample containing 1000 µg g -1 encapsulated olive leaf extract (Q 10  = 1.83) followed the sample containing 1000 µg g -1 sodium benzoate in terms of the highest kinetic rates. In the case of consistency, the lowest and highest activation energies (E a ) corresponded to samples containing 1000 µg g -1 non-encapsulated olive leaf extract and 1000 µg g -1 microencapsulated olive leaf extract respectively. Interestingly, samples containing microencapsulated olive leaf extract could maintain the original quality of the tomato paste very well, while those with non-encapsulated olive leaf extract rated the worst performance (among all specimens) in terms of maintaining their quality indices for a long time period. Overall, the shelf life equation was able to predict the consistency index of all tomato paste samples during long-time storage with high precision. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Entropy-Based Model for Interpreting Life Systems in Traditional Chinese Medicine

Directory of Open Access Journals (Sweden)

Guo-lian Kang

2008-01-01

Full Text Available Traditional Chinese medicine (TCM treats qi as the core of the human life systems. Starting with a hypothetical correlation between TCM qi and the entropy theory, we address in this article a holistic model for evaluating and unveiling the rule of TCM life systems. Several new concepts such as acquired life entropy (ALE, acquired life entropy flow (ALEF and acquired life entropy production (ALEP are propounded to interpret TCM life systems. Using the entropy theory, mathematical models are established for ALE, ALEF and ALEP, which reflect the evolution of life systems. Some criteria are given on physiological activities and pathological changes of the body in different stages of life. Moreover, a real data-based simulation shows life entropies of the human body with different ages, Cold and Hot constitutions and in different seasons in North China are coincided with the manifestations of qi as well as the life evolution in TCM descriptions. Especially, based on the comparative and quantitative analysis, the entropy-based model can nicely describe the evolution of life entropies in Cold and Hot individuals thereby fitting the Yin–Yang theory in TCM. Thus, this work establishes a novel approach to interpret the fundamental principles in TCM, and provides an alternative understanding for the complex life systems.

Fuzzy Life-Extending Control of Anti-Lock Braking System

Directory of Open Access Journals (Sweden)

Ahmed M. El-Garhy

2013-12-01

Full Text Available The repeated operation of the Anti-Lock Braking System (ABS causes accumulation of structural damages in its different subsystems leading to reduction in their functional life time. This paper proposes a Fuzzy Logic based Life-Extending Control (FLEC system for increasing the service life of the ABS. FLEC achieves significant improvement in service life by the trade-off between satisfactory dynamic performance and safe operation. The proposed FLEC incorporates structural damage model of the ABS. The model utilizes the dynamic behavior of the ABS and predicts the wear rates of the brake pads/disc. Based on the predicted wear rates, the proposed fuzzy logic controller modifies its control strategy on-line to keep safe operation leading to increase in service time of the ABS. FLEC is fine tuned via genetic algorithm and its effectiveness is verified through simulations of emergency stops of a passenger vehicle model.

Autoregressive-moving-average hidden Markov model for vision-based fall prediction-An application for walker robot.

Science.gov (United States)

Taghvaei, Sajjad; Jahanandish, Mohammad Hasan; Kosuge, Kazuhiro

2017-01-01

Population aging of the societies requires providing the elderly with safe and dependable assistive technologies in daily life activities. Improving the fall detection algorithms can play a major role in achieving this goal. This article proposes a real-time fall prediction algorithm based on the acquired visual data of a user with walking assistive system from a depth sensor. In the lack of a coupled dynamic model of the human and the assistive walker a hybrid "system identification-machine learning" approach is used. An autoregressive-moving-average (ARMA) model is fitted on the time-series walking data to forecast the upcoming states, and a hidden Markov model (HMM) based classifier is built on the top of the ARMA model to predict falling in the upcoming time frames. The performance of the algorithm is evaluated through experiments with four subjects including an experienced physiotherapist while using a walker robot in five different falling scenarios; namely, fall forward, fall down, fall back, fall left, and fall right. The algorithm successfully predicts the fall with a rate of 84.72%.

Re-conceptualising prenatal life stressors in predicting post-partum depression: cumulative-, specific-, and domain-specific approaches to calculating risk.

Science.gov (United States)

Liu, Cindy H; Tronick, Ed

2013-09-01

Prenatal life stress predicts post-partum depression (PPD); however, studies generally examine individual stressors (a specific approach) or the summation of such exposure (a cumulative approach) and their associations with PPD. Such approaches may oversimplify prenatal life stress as a risk factor for PPD. We evaluated approaches in assessing prenatal life stress as a predictor of PPD diagnosis, including a domain-specific approach that captures cumulative life stress while accounting for stress across different life stress domains: financial, relational, and physical health. The Pregnancy Risk Assessment Monitoring System, a population-based survey, was used to analyse the association of prenatal life stressors with PPD diagnoses among 3566 New York City post-partum women. Specific stressors were not associated with PPD diagnosis after controlling for sociodemographic variables. Exposure to a greater number of stressors was associated with PPD diagnosis, even after adjusting for both sociodemographic variables and specific stressors [odds ratio (OR) = 3.1, 95% confidence interval (CI) = 1.5, 6.7]. Individuals reporting a moderate-to-high number of financial problems along with a moderate-to-high number of physical problems were at greater odds of PPD (OR = 4.2, 95% CI = 1.2, 15.3); those with a moderate-to-high number of problems in all three domains were at over fivefold increased odds of PPD (OR = 5.5, CI = 1.1, 28.5). In assessing prenatal stress, clinicians should consider the extent to which stressors occur across different life domains; this association appears stronger with PPD diagnosis than simple assessments of individual stressors, which typically overestimate risk or cumulative exposures. © 2013 John Wiley & Sons Ltd.

Speech Intelligibility Prediction Based on Mutual Information

DEFF Research Database (Denmark)

Jensen, Jesper; Taal, Cees H.

2014-01-01

This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

Shelf-life prediction models for ready-to-eat fresh cut salads: Testing in real cold chain.

Science.gov (United States)

Tsironi, Theofania; Dermesonlouoglou, Efimia; Giannoglou, Marianna; Gogou, Eleni; Katsaros, George; Taoukis, Petros

2017-01-02

The aim of the study was to develop and test the applicability of predictive models for shelf-life estimation of ready-to-eat (RTE) fresh cut salads in realistic distribution temperature conditions in the food supply chain. A systematic kinetic study of quality loss of RTE mixed salad (lollo rosso lettuce-40%, lollo verde lettuce-45%, rocket-15%) packed under modified atmospheres (3% O 2 , 10% CO 2 , 87% N 2 ) was conducted. Microbial population (total viable count, Pseudomonas spp., lactic acid bacteria), vitamin C, colour and texture were the measured quality parameters. Kinetic models for these indices were developed to determine the quality loss and calculate product remaining shelf-life (SL R ). Storage experiments were conducted at isothermal (2.5-15°C) and non-isothermal temperature conditions (T eff =7.8°C defined as the constant temperature that results in the same quality value as the variable temperature distribution) for validation purposes. Pseudomonas dominated spoilage, followed by browning and chemical changes. The end of shelf-life correlated with a Pseudomonas spp. level of 8 log(cfu/g), and 20% loss of the initial vitamin C content. The effect of temperature on these quality parameters was expressed by the Arrhenius equation; activation energy (E a ) value was 69.1 and 122.6kJ/mol for Pseudomonas spp. growth and vitamin C loss rates, respectively. Shelf-life prediction models were also validated in real cold chain conditions (including the stages of transport to and storage at retail distribution center, transport to and display at 7 retail stores, transport to and storage in domestic refrigerators). The quality level and SL R estimated after 2-3days of domestic storage (time of consumption) ranged between 1 and 8days at 4°C and was predicted within satisfactory statistical error by the kinetic models. T eff in the cold chain ranged between 3.7 and 8.3°C. Using the validated models, SL R of RTE fresh cut salad can be estimated at any point of

Small Crack Growth and Fatigue Life Predictions for High-Strength Aluminium Alloys. Part 1; Experimental and Fracture Mechanics Analysis

Science.gov (United States)

Wu, X. R.; Newman, J. C.; Zhao, W.; Swain, M. H.; Ding, C. F.; Phillips, E. P.

1998-01-01

The small crack effect was investigated in two high-strength aluminium alloys: 7075-T6 bare and LC9cs clad alloy. Both experimental and analytical investigations were conducted to study crack initiation and growth of small cracks. In the experimental program, fatigue tests, small crack and large crack tests A,ere conducted under constant amplitude and Mini-TWIST spectrum loading conditions. A pronounced small crack effect was observed in both materials, especially for the negative stress ratios. For all loading conditions, most of the fatigue life of the SENT specimens was shown to be crack propagation from initial material defects or from the cladding layer. In the analysis program, three-dimensional finite element and A weight function methods were used to determine stress intensity factors and to develop SIF equations for surface and corner cracks at the notch in the SENT specimens. A plastisity-induced crack-closure model was used to correlate small and large crack data, and to make fatigue life predictions, Predicted crack-growth rates and fatigue lives agreed well with experiments. A total fatigue life prediction method for the aluminum alloys was developed and demonstrated using the crack-closure model.

Stuy on Fatigue Life of Aluminum Alloy Considering Fretting

Science.gov (United States)

Yang, Maosheng; Zhao, Hongqiang; Wang, Yunxiang; Chen, Xiaofei; Fan, Jiali

2018-01-01

To study the influence of fretting on Aluminum Alloy, a global finite element model considering fretting was performed using the commercial code ABAQUS. With which a new model for predicting fretting fatigue life has been presented based on friction work. The rationality and effectiveness of the model were validated according to the contrast of experiment life and predicting life. At last influence factor on fretting fatigue life of aerial aluminum alloy was investigated with the model. The results revealed that fretting fatigue life decreased monotonously with the increasing of normal load and then became constant at higher pressures. At low normal load, fretting fatigue life was found to increase with increase in the pad radius. At high normal load, however, the fretting fatigue life remained almost unchanged with changes in the fretting pad radius. The bulk stress amplitude had the dominant effect on fretting fatigue life. The fretting fatigue life diminished as the bulk stress amplitude increased.

Numerical Analysis of Rolling Contact Fatigue Crack Initiation and Fatigue Life Prediction of the Railway Crossing

NARCIS (Netherlands)

Xin, L.; Markine, V.L.; Shevtsov, I.

2015-01-01

The procedure for analysing rolling contact fatigue crack initiation and fatigue life prediction of the railway turnout crossing is developed. A three-dimensional finite element (FE) model is used to obtain stress and strain results, considering the dynamic effects of wheel-crossing rolling contact.

Stress analysis and life prediction of gas turbine blade

Science.gov (United States)

Hsiung, H. C.; Dunn, A. J.; Woodling, D. R.; Loh, D. L.

1988-01-01

A stress analysis procedure is presented for a redesign of the Space Shuttle Main Engine high pressure fuel turbopump turbine blades. The analysis consists of the one-dimensional scoping analysis to support the design layout and the follow-on three-dimensional finite element analysis to confirm the blade design at operating loading conditions. Blade life is evaluated based on high-cycle fatigue and low-cycle fatigue.

Comparisons of prediction models of quality of life after laparoscopic cholecystectomy: a longitudinal prospective study.

Directory of Open Access Journals (Sweden)

Hon-Yi Shi

Full Text Available BACKGROUND: Few studies of laparoscopic cholecystectomy (LC outcome have used longitudinal data for more than two years. Moreover, no studies have considered group differences in factors other than outcome such as age and nonsurgical treatment. Additionally, almost all published articles agree that the essential issue of the internal validity (reproducibility of the artificial neural network (ANN, support vector machine (SVM, Gaussian process regression (GPR and multiple linear regression (MLR models has not been adequately addressed. This study proposed to validate the use of these models for predicting quality of life (QOL after LC and to compare the predictive capability of ANNs with that of SVM, GPR and MLR. METHODOLOGY/PRINCIPAL FINDINGS: A total of 400 LC patients completed the SF-36 and the Gastrointestinal Quality of Life Index at baseline and at 2 years postoperatively. The criteria for evaluating the accuracy of the system models were mean square error (MSE and mean absolute percentage error (MAPE. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and to rank the variables in order of importance. Compared to SVM, GPR and MLR models, the ANN model generally had smaller MSE and MAPE values in the training data set and test data set. Most ANN models had MAPE values ranging from 4.20% to 8.60%, and most had high prediction accuracy. The global sensitivity analysis also showed that preoperative functional status was the best parameter for predicting QOL after LC. CONCLUSIONS/SIGNIFICANCE: Compared with SVM, GPR and MLR models, the ANN model in this study was more accurate in predicting patient-reported QOL and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data.

Trajectories of life satisfaction after TBI: Influence of life roles, age, cognitive disability, and depressive symptoms