Evaluation of a Progressive Failure Analysis Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Sleight, David W.; Knight, Norman F., Jr.; Wang, John T.

1997-01-01

A progressive failure analysis methodology has been developed for predicting the nonlinear response and failure of laminated composite structures. The progressive failure analysis uses C plate and shell elements based on classical lamination theory to calculate the in-plane stresses. Several failure criteria, including the maximum strain criterion, Hashin's criterion, and Christensen's criterion, are used to predict the failure mechanisms. The progressive failure analysis model is implemented into a general purpose finite element code and can predict the damage and response of laminated composite structures from initial loading to final failure.

Thermal barrier coating life prediction model

NASA Technical Reports Server (NTRS)

Pilsner, B. H.; Hillery, R. V.; Mcknight, R. L.; Cook, T. S.; Kim, K. S.; Duderstadt, E. C.

1986-01-01

The objectives of this program are to determine the predominant modes of degradation of a plasma sprayed thermal barrier coating system, and then to develop and verify life prediction models accounting for these degradation modes. The program is divided into two phases, each consisting of several tasks. The work in Phase 1 is aimed at identifying the relative importance of the various failure modes, and developing and verifying life prediction model(s) for the predominant model for a thermal barrier coating system. Two possible predominant failure mechanisms being evaluated are bond coat oxidation and bond coat creep. The work in Phase 2 will develop design-capable, causal, life prediction models for thermomechanical and thermochemical failure modes, and for the exceptional conditions of foreign object damage and erosion.

Improvement of Progressive Damage Model to Predicting Crashworthy Composite Corrugated Plate

NASA Astrophysics Data System (ADS)

Ren, Yiru; Jiang, Hongyong; Ji, Wenyuan; Zhang, Hanyu; Xiang, Jinwu; Yuan, Fuh-Gwo

2018-02-01

To predict the crashworthy composite corrugated plate, different single and stacked shell models are evaluated and compared, and a stacked shell progressive damage model combined with continuum damage mechanics is proposed and investigated. To simulate and predict the failure behavior, both of the intra- and inter- laminar failure behavior are considered. The tiebreak contact method, 1D spot weld element and cohesive element are adopted in stacked shell model, and a surface-based cohesive behavior is used to capture delamination in the proposed model. The impact load and failure behavior of purposed and conventional progressive damage models are demonstrated. Results show that the single shell could simulate the impact load curve without the delamination simulation ability. The general stacked shell model could simulate the interlaminar failure behavior. The improved stacked shell model with continuum damage mechanics and cohesive element not only agree well with the impact load, but also capture the fiber, matrix debonding, and interlaminar failure of composite structure.

A quantitative model of honey bee colony population dynamics.

PubMed

Khoury, David S; Myerscough, Mary R; Barron, Andrew B

2011-04-18

Since 2006 the rate of honey bee colony failure has increased significantly. As an aid to testing hypotheses for the causes of colony failure we have developed a compartment model of honey bee colony population dynamics to explore the impact of different death rates of forager bees on colony growth and development. The model predicts a critical threshold forager death rate beneath which colonies regulate a stable population size. If death rates are sustained higher than this threshold rapid population decline is predicted and colony failure is inevitable. The model also predicts that high forager death rates draw hive bees into the foraging population at much younger ages than normal, which acts to accelerate colony failure. The model suggests that colony failure can be understood in terms of observed principles of honey bee population dynamics, and provides a theoretical framework for experimental investigation of the problem.

Predicting Failure Progression and Failure Loads in Composite Open-Hole Tension Coupons

NASA Technical Reports Server (NTRS)

Arunkumar, Satyanarayana; Przekop, Adam

2010-01-01

Failure types and failure loads in carbon-epoxy [45n/90n/-45n/0n]ms laminate coupons with central circular holes subjected to tensile load are simulated using progressive failure analysis (PFA) methodology. The progressive failure methodology is implemented using VUMAT subroutine within the ABAQUS(TradeMark)/Explicit nonlinear finite element code. The degradation model adopted in the present PFA methodology uses an instantaneous complete stress reduction (COSTR) approach to simulate damage at a material point when failure occurs. In-plane modeling parameters such as element size and shape are held constant in the finite element models, irrespective of laminate thickness and hole size, to predict failure loads and failure progression. Comparison to published test data indicates that this methodology accurately simulates brittle, pull-out and delamination failure types. The sensitivity of the failure progression and the failure load to analytical loading rates and solvers precision is demonstrated.

Predictors of treatment failure in young patients undergoing in vitro fertilization.

PubMed

Jacobs, Marni B; Klonoff-Cohen, Hillary; Agarwal, Sanjay; Kritz-Silverstein, Donna; Lindsay, Suzanne; Garzo, V Gabriel

2016-08-01

The purpose of the study was to evaluate whether routinely collected clinical factors can predict in vitro fertilization (IVF) failure among young, "good prognosis" patients predominantly with secondary infertility who are less than 35 years of age. Using de-identified clinic records, 414 women <35 years undergoing their first autologous IVF cycle were identified. Logistic regression was used to identify patient-driven clinical factors routinely collected during fertility treatment that could be used to model predicted probability of cycle failure. One hundred ninety-seven patients with both primary and secondary infertility had a failed IVF cycle, and 217 with secondary infertility had a successful live birth. None of the women with primary infertility had a successful live birth. The significant predictors for IVF cycle failure among young patients were fewer previous live births, history of biochemical pregnancies or spontaneous abortions, lower baseline antral follicle count, higher total gonadotropin dose, unknown infertility diagnosis, and lack of at least one fair to good quality embryo. The full model showed good predictive value (c = 0.885) for estimating risk of cycle failure; at ≥80 % predicted probability of failure, sensitivity = 55.4 %, specificity = 97.5 %, positive predictive value = 95.4 %, and negative predictive value = 69.8 %. If this predictive model is validated in future studies, it could be beneficial for predicting IVF failure in good prognosis women under the age of 35 years.

Limited improvement of incorporating primary circulating prostate cells with the CAPRA score to predict biochemical failure-free outcome of radical prostatectomy for prostate cancer.

PubMed

Murray, Nigel P; Aedo, Socrates; Fuentealba, Cynthia; Jacob, Omar; Reyes, Eduardo; Novoa, Camilo; Orellana, Sebastian; Orellana, Nelson

2016-10-01

To establish a prediction model for early biochemical failure based on the Cancer of the Prostate Risk Assessment (CAPRA) score, the presence or absence of primary circulating prostate cells (CPC) and the number of primary CPC (nCPC)/8ml blood sample is detected before surgery. A prospective single-center study of men who underwent radical prostatectomy as monotherapy for prostate cancer. Clinical-pathological findings were used to calculate the CAPRA score. Before surgery blood was taken for CPC detection, mononuclear cells were obtained using differential gel centrifugation, and CPCs identified using immunocytochemistry. A CPC was defined as a cell expressing prostate-specific antigen and P504S, and the presence or absence of CPCs and the number of cells detected/8ml blood sample was registered. Patients were followed up for up to 5 years; biochemical failure was defined as a prostate-specific antigen>0.2ng/ml. The validity of the CAPRA score was calibrated using partial validation, and the fractional polynomial Cox proportional hazard regression was used to build 3 models, which underwent a decision analysis curve to determine the predictive value of the 3 models with respect to biochemical failure. A total of 267 men participated, mean age 65.80 years, and after 5 years of follow-up the biochemical-free survival was 67.42%. The model using CAPRA score showed a hazards ratio (HR) of 5.76 between low and high-risk groups, that of CPC with a HR of 26.84 between positive and negative groups, and the combined model showed a HR of 4.16 for CAPRA score and 19.93 for CPC. Using the continuous variable nCPC, there was no improvement in the predictive value of the model compared with the model using a positive-negative result of CPC detection. The combined CAPRA-nCPC model showed an improvement of the predictive performance for biochemical failure using the Harrell׳s C concordance test and a net benefit on DCA in comparison with either model used separately. The use of primary CPC as a predictive factor based on their presence or absence did not predict aggressive disease or biochemical failure. Although the use of a combined CAPRA-nCPC model improves the prediction of biochemical failure in patients undergoing radical prostatectomy for prostate cancer, this is minimal. The use of the presence or absence of primary CPCs alone did not predict aggressive disease or biochemical failure. Copyright © 2016 Elsevier Inc. All rights reserved.

Predictors of incident heart failure in patients after an acute coronary syndrome: The LIPID heart failure risk-prediction model.

PubMed

Driscoll, Andrea; Barnes, Elizabeth H; Blankenberg, Stefan; Colquhoun, David M; Hunt, David; Nestel, Paul J; Stewart, Ralph A; West, Malcolm J; White, Harvey D; Simes, John; Tonkin, Andrew

2017-12-01

Coronary heart disease is a major cause of heart failure. Availability of risk-prediction models that include both clinical parameters and biomarkers is limited. We aimed to develop such a model for prediction of incident heart failure. A multivariable risk-factor model was developed for prediction of first occurrence of heart failure death or hospitalization. A simplified risk score was derived that enabled subjects to be grouped into categories of 5-year risk varying from <5% to >20%. Among 7101 patients from the LIPID study (84% male), with median age 61years (interquartile range 55-67years), 558 (8%) died or were hospitalized because of heart failure. Older age, history of claudication or diabetes mellitus, body mass index>30kg/m 2 , LDL-cholesterol >2.5mmol/L, heart rate>70 beats/min, white blood cell count, and the nature of the qualifying acute coronary syndrome (myocardial infarction or unstable angina) were associated with an increase in heart failure events. Coronary revascularization was associated with a lower event rate. Incident heart failure increased with higher concentrations of B-type natriuretic peptide >50ng/L, cystatin C>0.93nmol/L, D-dimer >273nmol/L, high-sensitivity C-reactive protein >4.8nmol/L, and sensitive troponin I>0.018μg/L. Addition of biomarkers to the clinical risk model improved the model's C statistic from 0.73 to 0.77. The net reclassification improvement incorporating biomarkers into the clinical model using categories of 5-year risk was 23%. Adding a multibiomarker panel to conventional parameters markedly improved discrimination and risk classification for future heart failure events. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Evaluation of a Multi-Axial, Temperature, and Time Dependent (MATT) Failure Model

NASA Technical Reports Server (NTRS)

Richardson, D. E.; Anderson, G. L.; Macon, D. J.; Rudolphi, Michael (Technical Monitor)

2002-01-01

To obtain a better understanding the response of the structural adhesives used in the Space Shuttle's Reusable Solid Rocket Motor (RSRM) nozzle, an extensive effort has been conducted to characterize in detail the failure properties of these adhesives. This effort involved the development of a failure model that includes the effects of multi-axial loading, temperature, and time. An understanding of the effects of these parameters on the failure of the adhesive is crucial to the understanding and prediction of the safety of the RSRM nozzle. This paper documents the use of this newly developed multi-axial, temperature, and time (MATT) dependent failure model for modeling failure for the adhesives TIGA 321, EA913NA, and EA946. The development of the mathematical failure model using constant load rate normal and shear test data is presented. Verification of the accuracy of the failure model is shown through comparisons between predictions and measured creep and multi-axial failure data. The verification indicates that the failure model performs well for a wide range of conditions (loading, temperature, and time) for the three adhesives. The failure criterion is shown to be accurate through the glass transition for the adhesive EA946. Though this failure model has been developed and evaluated with adhesives, the concepts are applicable for other isotropic materials.

Detecting failure of climate predictions

USGS Publications Warehouse

Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

2016-01-01

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty1, 2. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies3. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

Predictions of structural integrity of steam generator tubes under normal operating, accident, an severe accident conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Majumdar, S.

1997-02-01

Available models for predicting failure of flawed and unflawed steam generator tubes under normal operating, accident, and severe accident conditions are reviewed. Tests conducted in the past, though limited, tended to show that the earlier flow-stress model for part-through-wall axial cracks overestimated the damaging influence of deep cracks. This observation was confirmed by further tests at high temperatures, as well as by finite-element analysis. A modified correlation for deep cracks can correct this shortcoming of the model. Recent tests have shown that lateral restraint can significantly increase the failure pressure of tubes with unsymmetrical circumferential cracks. This observation was confirmedmore » by finite-element analysis. The rate-independent flow stress models that are successful at low temperatures cannot predict the rate-sensitive failure behavior of steam generator tubes at high temperatures. Therefore, a creep rupture model for predicting failure was developed and validated by tests under various temperature and pressure loadings that can occur during postulated severe accidents.« less

A model for the progressive failure of laminated composite structural components

NASA Technical Reports Server (NTRS)

Allen, D. H.; Lo, D. C.

1991-01-01

Laminated continuous fiber polymeric composites are capable of sustaining substantial load induced microstructural damage prior to component failure. Because this damage eventually leads to catastrophic failure, it is essential to capture the mechanics of progressive damage in any cogent life prediction model. For the past several years the authors have been developing one solution approach to this problem. In this approach the mechanics of matrix cracking and delamination are accounted for via locally averaged internal variables which account for the kinematics of microcracking. Damage progression is predicted by using phenomenologically based damage evolution laws which depend on the load history. The result is a nonlinear and path dependent constitutive model which has previously been implemented to a finite element computer code for analysis of structural components. Using an appropriate failure model, this algorithm can be used to predict component life. In this paper the model will be utilized to demonstrate the ability to predict the load path dependence of the damage and stresses in plates subjected to fatigue loading.

A Bayesian network approach for modeling local failure in lung cancer

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Craft, Jeffrey; Lozi, Rawan Al; Vaidya, Manushka; Meng, Yifan; Deasy, Joseph O.; Bradley, Jeffrey D.; El Naqa, Issam

2011-03-01

Locally advanced non-small cell lung cancer (NSCLC) patients suffer from a high local failure rate following radiotherapy. Despite many efforts to develop new dose-volume models for early detection of tumor local failure, there was no reported significant improvement in their application prospectively. Based on recent studies of biomarker proteins' role in hypoxia and inflammation in predicting tumor response to radiotherapy, we hypothesize that combining physical and biological factors with a suitable framework could improve the overall prediction. To test this hypothesis, we propose a graphical Bayesian network framework for predicting local failure in lung cancer. The proposed approach was tested using two different datasets of locally advanced NSCLC patients treated with radiotherapy. The first dataset was collected retrospectively, which comprises clinical and dosimetric variables only. The second dataset was collected prospectively in which in addition to clinical and dosimetric information, blood was drawn from the patients at various time points to extract candidate biomarkers as well. Our preliminary results show that the proposed method can be used as an efficient method to develop predictive models of local failure in these patients and to interpret relationships among the different variables in the models. We also demonstrate the potential use of heterogeneous physical and biological variables to improve the model prediction. With the first dataset, we achieved better performance compared with competing Bayesian-based classifiers. With the second dataset, the combined model had a slightly higher performance compared to individual physical and biological models, with the biological variables making the largest contribution. Our preliminary results highlight the potential of the proposed integrated approach for predicting post-radiotherapy local failure in NSCLC patients.

One-Dimensional Simulations for Spall in Metals with Intra- and Inter-grain failure models

NASA Astrophysics Data System (ADS)

Ferri, Brian; Dwivedi, Sunil; McDowell, David

2017-06-01

The objective of the present work is to model spall failure in metals with coupled effect of intra-grain and inter-grain failure mechanisms. The two mechanisms are modeled by a void nucleation, growth, and coalescence (VNGC) model and contact-cohesive model respectively. Both models were implemented in a 1-D code to simulate spall in 6061-T6 aluminum at two impact velocities. The parameters of the VNGC model without inter-grain failure and parameters of the cohesive model without intra-grain failure were first determined to obtain pull-back velocity profiles in agreement with experimental data. With the same impact velocities, the same sets of parameters did not predict the velocity profiles when both mechanisms were simultaneously activated. A sensitivity study was performed to predict spall under combined mechanisms by varying critical stress in the VNGC model and maximum traction in the cohesive model. The study provided possible sets of the two parameters leading to spall. Results will be presented comparing the predicted velocity profile with experimental data using one such set of parameters for the combined intra-grain and inter-grain failures during spall. Work supported by HDTRA1-12-1-0004 gran and by the School of Mechanical Engineering GTA.

Failure Models and Criteria for FRP Under In-Plane or Three-Dimensional Stress States Including Shear Non-Linearity

NASA Technical Reports Server (NTRS)

Pinho, Silvestre T.; Davila, C. G.; Camanho, P. P.; Iannucci, L.; Robinson, P.

2005-01-01

A set of three-dimensional failure criteria for laminated fiber-reinforced composites, denoted LaRC04, is proposed. The criteria are based on physical models for each failure mode and take into consideration non-linear matrix shear behaviour. The model for matrix compressive failure is based on the Mohr-Coulomb criterion and it predicts the fracture angle. Fiber kinking is triggered by an initial fiber misalignment angle and by the rotation of the fibers during compressive loading. The plane of fiber kinking is predicted by the model. LaRC04 consists of 6 expressions that can be used directly for design purposes. Several applications involving a broad range of load combinations are presented and compared to experimental data and other existing criteria. Predictions using LaRC04 correlate well with the experimental data, arguably better than most existing criteria. The good correlation seems to be attributable to the physical soundness of the underlying failure models.

Climate change, species distribution models, and physiological performance metrics: predicting when biogeographic models are likely to fail.

PubMed

Woodin, Sarah A; Hilbish, Thomas J; Helmuth, Brian; Jones, Sierra J; Wethey, David S

2013-09-01

Modeling the biogeographic consequences of climate change requires confidence in model predictions under novel conditions. However, models often fail when extended to new locales, and such instances have been used as evidence of a change in physiological tolerance, that is, a fundamental niche shift. We explore an alternative explanation and propose a method for predicting the likelihood of failure based on physiological performance curves and environmental variance in the original and new environments. We define the transient event margin (TEM) as the gap between energetic performance failure, defined as CTmax, and the upper lethal limit, defined as LTmax. If TEM is large relative to environmental fluctuations, models will likely fail in new locales. If TEM is small relative to environmental fluctuations, models are likely to be robust for new locales, even when mechanism is unknown. Using temperature, we predict when biogeographic models are likely to fail and illustrate this with a case study. We suggest that failure is predictable from an understanding of how climate drives nonlethal physiological responses, but for many species such data have not been collected. Successful biogeographic forecasting thus depends on understanding when the mechanisms limiting distribution of a species will differ among geographic regions, or at different times, resulting in realized niche shifts. TEM allows prediction of the likelihood of such model failure.

Light water reactor lower head failure analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rempe, J.L.; Chavez, S.A.; Thinnes, G.L.

1993-10-01

This document presents the results from a US Nuclear Regulatory Commission-sponsored research program to investigate the mode and timing of vessel lower head failure. Major objectives of the analysis were to identify plausible failure mechanisms and to develop a method for determining which failure mode would occur first in different light water reactor designs and accident conditions. Failure mechanisms, such as tube ejection, tube rupture, global vessel failure, and localized vessel creep rupture, were studied. Newly developed models and existing models were applied to predict which failure mechanism would occur first in various severe accident scenarios. So that a broadermore » range of conditions could be considered simultaneously, calculations relied heavily on models with closed-form or simplified numerical solution techniques. Finite element techniques-were employed for analytical model verification and examining more detailed phenomena. High-temperature creep and tensile data were obtained for predicting vessel and penetration structural response.« less

Micromechanics of failure waves in glass. 2: Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Espinosa, H.D.; Xu, Y.; Brar, N.S.

1997-08-01

In an attempt to elucidate the failure mechanism responsible for the so-called failure waves in glass, numerical simulations of plate and rod impact experiments, with a multiple-plane model, have been performed. These simulations show that the failure wave phenomenon can be modeled by the nucleation and growth of penny-shaped shear defects from the specimen surface to its interior. Lateral stress increase, reduction of spall strength,and progressive attenuation of axial stress behind the failure front are properly predicted by the multiple-plane model. Numerical simulations of high-strain-rate pressure-shear experiments indicate that the model predicts reasonably well the shear resistance of the materialmore » at strain rates as high as 1 {times} 10{sup 6}/s. The agreement is believed to be the result of the model capability in simulating damage-induced anisotropy. By examining the kinetics of the failure process in plate experiments, the authors show that the progressive glass spallation in the vicinity of the failure front and the rate of increase in lateral stress are more consistent with a representation of inelasticity based on shear-activated flow surfaces, inhomogeneous flow, and microcracking, rather than pure microcracking. In the former mechanism, microcracks are likely formed at a later time at the intersection of flow surfaces, in the case of rod-on-rod impact, stress and radial velocity histories predicted by the microcracking model are in agreement with the experimental measurements. Stress attenuation, pulse duration, and release structure are properly simulated. It is shown that failure wave speeds in excess to 3,600 m/s are required for adequate prediction in rod radial expansion.« less

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information

PubMed Central

Wang, Xiaohong; Wang, Lizhi

2017-01-01

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system. PMID:28926930

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information.

PubMed

Wang, Jingbin; Wang, Xiaohong; Wang, Lizhi

2017-09-15

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system.

Nuclear Graphite - Fracture Behavior and Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burchell, Timothy D; Battiste, Rick; Strizak, Joe P

2011-01-01

Evidence for the graphite fracture mechanism is reviewed and discussed. The roles of certain microstructural features in the graphite fracture process are reported. The Burchell fracture model is described and its derivation reported. The successful application of the fracture model to uniaxial tensile data from several graphites with widely ranging structure and texture is reported. The extension of the model to multiaxial loading scenarios using two criteria is discussed. Initially, multiaxial strength data for H-451 graphite were modeled using the fracture model and the Principle of Independent Action. The predicted 4th stress quadrant failure envelope was satisfactory but the 1stmore » quadrant predictions were not conservative and thus were unsatisfactory. Multiaxial strength data from the 1st and 4th stress quadrant for NBG-18 graphite are reported. To improve the conservatism of the predicted 1st quadrant failure envelope for NBG-18 the Shetty criterion has been applied to obtain the equivalent critical stress intensity factor, KIc (Equi), for each applied biaxial stress ratio. The equivalent KIc value is used in the Burchell fracture model to predict the failure envelope. The predicted 1st stress quadrant failure envelope is conservative and thus more satisfactory than achieved previously using the fracture model combined with the Principle of Independent Action.« less

Is it beneficial to approximate pre-failure topography to predict landslide susceptibility with empirical models?

NASA Astrophysics Data System (ADS)

Steger, Stefan; Schmaltz, Elmar; Glade, Thomas

2017-04-01

Empirical landslide susceptibility maps spatially depict the areas where future slope failures are likely due to specific environmental conditions. The underlying statistical models are based on the assumption that future landsliding is likely to occur under similar circumstances (e.g. topographic conditions, lithology, land cover) as past slope failures. This principle is operationalized by applying a supervised classification approach (e.g. a regression model with a binary response: landslide presence/absence) that enables discrimination between conditions that favored past landslide occurrences and the circumstances typical for landslide absences. The derived empirical relation is then transferred to each spatial unit of an area. Literature reveals that the specific topographic conditions representative for landslide presences are frequently extracted from derivatives of digital terrain models at locations were past landslides were mapped. The underlying morphology-based landslide identification becomes possible due to the fact that the topography at a specific locality usually changes after landslide occurrence (e.g. hummocky surface, concave and steep scarp). In a strict sense, this implies that topographic predictors used within conventional statistical landslide susceptibility models relate to post-failure topographic conditions - and not to the required pre-failure situation. This study examines the assumption that models calibrated on the basis of post-failure topographies may not be appropriate to predict future landslide locations, because (i) post-failure and pre-failure topographic conditions may differ and (ii) areas were future landslides will occur do not yet exhibit such a distinct post-failure morphology. The study was conducted for an area located in the Walgau region (Vorarlberg, western Austria), where a detailed inventory consisting of shallow landslides was available. The methodology comprised multiple systematic comparisons of models generated on the basis of post-failure conditions (i.e. the standard approach) with models based on an approximated pre-failure topography. Pre-failure topography was approximated by (i) erasing the area of mapped landslide polygons within a digital terrain model and (ii) filling these "empty" areas by interpolating elevation points located outside the mapped landslides. Landslide presence information was extracted from the respective landslide scarp locations while an equal number of randomly sampled points represented landslide absences. After an initial exploratory data analysis, mixed-effects logistic regression was applied to model landslide susceptibility on the basis of two predictor sets (post-failure versus pre-failure predictors). Furthermore, all analyses were separately conducted for five different modelling resolutions to elaborate the suspicion that the degree of generalization of topographic parameters may as well play a role on how the respective models may differ. Model evaluation was conducted by means of multiple procedures (i.e. odds ratios, k-fold cross validation, permutation-based variable importance, difference maps of predictions). The results revealed that models based on highest resolutions (e.g. 1 m, 2.5 m) and post-failure topography performed best from a purely quantitative perspective. A confrontation of models (post-failure versus pre-failure based models) based on an identical modelling resolution exposed that validation results, modelled relationships as well as the prediction pattern tended to converge with a decreasing raster resolution. Based on the results, we concluded that an approximation of pre-failure topography does not significantly contribute to improved landslide susceptibility models in the case (i) the underlying inventory consists of small landslide features and (ii) the models are based on coarse raster resolutions (e.g. 25 m). However, in the case modelling with high raster resolutions is envisaged (e.g. 1 m, 2.5 m) or the inventory mainly consists of larger events, a reconstruction of pre-failure conditions might be highly expedient, even though conventional validation results might indicate an opposite tendency. Finally, we recommend to consider that topographic predictors highly useful to detect past slope movements (e.g. roughness) are not necessarily valuable to predict future slope instabilities.

Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION Trial.

PubMed

Kalscheur, Matthew M; Kipp, Ryan T; Tattersall, Matthew C; Mei, Chaoqun; Buhr, Kevin A; DeMets, David L; Field, Michael E; Eckhardt, Lee L; Page, C David

2018-01-01

Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in heart failure patients with reduced left ventricular function and intraventricular conduction delay. However, individual outcomes vary significantly. This study sought to use a machine learning algorithm to develop a model to predict outcomes after CRT. Models were developed with machine learning algorithms to predict all-cause mortality or heart failure hospitalization at 12 months post-CRT in the COMPANION trial (Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure). The best performing model was developed with the random forest algorithm. The ability of this model to predict all-cause mortality or heart failure hospitalization and all-cause mortality alone was compared with discrimination obtained using a combination of bundle branch block morphology and QRS duration. In the 595 patients with CRT-defibrillator in the COMPANION trial, 105 deaths occurred (median follow-up, 15.7 months). The survival difference across subgroups differentiated by bundle branch block morphology and QRS duration did not reach significance ( P =0.08). The random forest model produced quartiles of patients with an 8-fold difference in survival between those with the highest and lowest predicted probability for events (hazard ratio, 7.96; P <0.0001). The model also discriminated the risk of the composite end point of all-cause mortality or heart failure hospitalization better than subgroups based on bundle branch block morphology and QRS duration. In the COMPANION trial, a machine learning algorithm produced a model that predicted clinical outcomes after CRT. Applied before device implant, this model may better differentiate outcomes over current clinical discriminators and improve shared decision-making with patients. © 2018 American Heart Association, Inc.

Risk factors for the treatment outcome of retreated pulmonary tuberculosis patients in China: an optimized prediction model.

PubMed

Wang, X-M; Yin, S-H; Du, J; Du, M-L; Wang, P-Y; Wu, J; Horbinski, C M; Wu, M-J; Zheng, H-Q; Xu, X-Q; Shu, W; Zhang, Y-J

2017-07-01

Retreatment of tuberculosis (TB) often fails in China, yet the risk factors associated with the failure remain unclear. To identify risk factors for the treatment failure of retreated pulmonary tuberculosis (PTB) patients, we analyzed the data of 395 retreated PTB patients who received retreatment between July 2009 and July 2011 in China. PTB patients were categorized into 'success' and 'failure' groups by their treatment outcome. Univariable and multivariable logistic regression were used to evaluate the association between treatment outcome and socio-demographic as well as clinical factors. We also created an optimized risk score model to evaluate the predictive values of these risk factors on treatment failure. Of 395 patients, 99 (25·1%) were diagnosed as retreatment failure. Our results showed that risk factors associated with treatment failure included drug resistance, low education level, low body mass index (6 months), standard treatment regimen, retreatment type, positive culture result after 2 months of treatment, and the place where the first medicine was taken. An Optimized Framingham risk model was then used to calculate the risk scores of these factors. Place where first medicine was taken (temporary living places) received a score of 6, which was highest among all the factors. The predicted probability of treatment failure increases as risk score increases. Ten out of 359 patients had a risk score >9, which corresponded to an estimated probability of treatment failure >70%. In conclusion, we have identified multiple clinical and socio-demographic factors that are associated with treatment failure of retreated PTB patients. We also created an optimized risk score model that was effective in predicting the retreatment failure. These results provide novel insights for the prognosis and improvement of treatment for retreated PTB patients.

Baseline Hemodynamics and Response to Contrast Media During Diagnostic Cardiac Catheterization Predict Adverse Events in Heart Failure Patients.

PubMed

Denardo, Scott J; Vock, David M; Schmalfuss, Carsten M; Young, Gregory D; Tcheng, James E; O'Connor, Christopher M

2016-07-01

Contrast media administered during cardiac catheterization can affect hemodynamic variables. However, little is documented about the effects of contrast on hemodynamics in heart failure patients or the prognostic value of baseline and changes in hemodynamics for predicting subsequent adverse events. In this prospective study of 150 heart failure patients, we measured hemodynamics at baseline and after administration of iodixanol or iopamidol contrast. One-year Kaplan-Meier estimates of adverse event-free survival (death, heart failure hospitalization, and rehospitalization) were generated, grouping patients by baseline measures of pulmonary capillary wedge pressure (PCWP) and cardiac index (CI), and by changes in those measures after contrast administration. We used Cox proportional hazards modeling to assess sequentially adding baseline PCWP and change in CI to 5 validated risk models (Seattle Heart Failure Score, ESCAPE [Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness], CHARM [Candesartan in Heart Failure: Assessment of Reduction in Mortality and Morbidity], CORONA [Controlled Rosuvastatin Multinational Trial in Heart Failure], and MAGGIC [Meta-Analysis Global Group in Chronic Heart Failure]). Median contrast volume was 109 mL. Both contrast media caused similarly small but statistically significant changes in most hemodynamic variables. There were 39 adverse events (26.0%). Adverse event rates increased using the composite metric of baseline PCWP and change in CI (P<0.01); elevated baseline PCWP and decreased CI after contrast correlated with the poorest prognosis. Adding both baseline PCWP and change in CI to the 5 risk models universally improved their predictive value (P≤0.02). In heart failure patients, the administration of contrast causes small but significant changes in hemodynamics. Calculating baseline PCWP with change in CI after contrast predicts adverse events and increases the predictive value of existing models. Patients with elevated baseline PCWP and decreased CI after contrast merit greatest concern. © 2016 American Heart Association, Inc.

The second Sandia Fracture Challenge. Predictions of ductile failure under quasi-static and moderate-rate dynamic loading

DOE PAGES

Boyce, B. L.; Kramer, S. L. B.; Bosiljevac, T. R.; ...

2016-03-14

Ductile failure of structural metals is relevant to a wide range of engineering scenarios. Computational methods are employed to anticipate the critical conditions of failure, yet they sometimes provide inaccurate and misleading predictions. Challenge scenarios, such as the one presented in the current work, provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Instead of evaluating the predictions of a single simulation approach, the Sandia Fracture Challenge relied on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive modelsmore » to the challenge. This exercise is intended to evaluate the state of health of technologies available for failure prediction. In the first Sandia Fracture Challenge, a wide range of issues were raised in ductile failure modeling, including a lack of consistency in failure models, the importance of shear calibration data, and difficulties in quantifying the uncertainty of prediction [see Boyce et al. (Int J Fract 186:5–68, 2014) for details of these observations]. This second Sandia Fracture Challenge investigated the ductile rupture of a Ti–6Al–4V sheet under both quasi-static and modest-rate dynamic loading (failure in ~ 0.1 s). Like the previous challenge, the sheet had an unusual arrangement of notches and holes that added geometric complexity and fostered a competition between tensile- and shear-dominated failure modes. The teams were asked to predict the fracture path and quantitative far-field failure metrics such as the peak force and displacement to cause crack initiation. Fourteen teams contributed blind predictions, and the experimental outcomes were quantified in three independent test labs. In addition, shortcomings were revealed in this second challenge such as inconsistency in the application of appropriate boundary conditions, need for a thermomechanical treatment of the heat generation in the dynamic loading condition, and further difficulties in model calibration based on limited real-world engineering data. As with the prior challenge, this work not only documents the ‘state-of-the-art’ in computational failure prediction of ductile tearing scenarios, but also provides a detailed dataset for non-blind assessment of alternative methods.« less

The second Sandia Fracture Challenge. Predictions of ductile failure under quasi-static and moderate-rate dynamic loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boyce, B. L.; Kramer, S. L. B.; Bosiljevac, T. R.

Ductile failure of structural metals is relevant to a wide range of engineering scenarios. Computational methods are employed to anticipate the critical conditions of failure, yet they sometimes provide inaccurate and misleading predictions. Challenge scenarios, such as the one presented in the current work, provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Instead of evaluating the predictions of a single simulation approach, the Sandia Fracture Challenge relied on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive modelsmore » to the challenge. This exercise is intended to evaluate the state of health of technologies available for failure prediction. In the first Sandia Fracture Challenge, a wide range of issues were raised in ductile failure modeling, including a lack of consistency in failure models, the importance of shear calibration data, and difficulties in quantifying the uncertainty of prediction [see Boyce et al. (Int J Fract 186:5–68, 2014) for details of these observations]. This second Sandia Fracture Challenge investigated the ductile rupture of a Ti–6Al–4V sheet under both quasi-static and modest-rate dynamic loading (failure in ~ 0.1 s). Like the previous challenge, the sheet had an unusual arrangement of notches and holes that added geometric complexity and fostered a competition between tensile- and shear-dominated failure modes. The teams were asked to predict the fracture path and quantitative far-field failure metrics such as the peak force and displacement to cause crack initiation. Fourteen teams contributed blind predictions, and the experimental outcomes were quantified in three independent test labs. In addition, shortcomings were revealed in this second challenge such as inconsistency in the application of appropriate boundary conditions, need for a thermomechanical treatment of the heat generation in the dynamic loading condition, and further difficulties in model calibration based on limited real-world engineering data. As with the prior challenge, this work not only documents the ‘state-of-the-art’ in computational failure prediction of ductile tearing scenarios, but also provides a detailed dataset for non-blind assessment of alternative methods.« less

Comparison of Damage Path Predictions for Composite Laminates by Explicit and Standard Finite Element Analysis Tools

NASA Technical Reports Server (NTRS)

Bogert, Philip B.; Satyanarayana, Arunkumar; Chunchu, Prasad B.

2006-01-01

Splitting, ultimate failure load and the damage path in center notched composite specimens subjected to in-plane tension loading are predicted using progressive failure analysis methodology. A 2-D Hashin-Rotem failure criterion is used in determining intra-laminar fiber and matrix failures. This progressive failure methodology has been implemented in the Abaqus/Explicit and Abaqus/Standard finite element codes through user written subroutines "VUMAT" and "USDFLD" respectively. A 2-D finite element model is used for predicting the intra-laminar damages. Analysis results obtained from the Abaqus/Explicit and Abaqus/Standard code show good agreement with experimental results. The importance of modeling delamination in progressive failure analysis methodology is recognized for future studies. The use of an explicit integration dynamics code for simple specimen geometry and static loading establishes a foundation for future analyses where complex loading and nonlinear dynamic interactions of damage and structure will necessitate it.

Probabilistic framework for product design optimization and risk management

NASA Astrophysics Data System (ADS)

Keski-Rahkonen, J. K.

2018-05-01

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

Explicit Pore Pressure Material Model in Carbon-Cloth Phenolic

NASA Technical Reports Server (NTRS)

Gutierrez-Lemini, Danton; Ehle, Curt

2003-01-01

An explicit material model that uses predicted pressure in the pores of a carbon-cloth phenolic (CCP) composite has been developed. This model is intended to be used within a finite-element model to predict phenomena specific to CCP components of solid-fuel-rocket nozzles subjected to high operating temperatures and to mechanical stresses that can be great enough to cause structural failures. Phenomena that can be predicted with the help of this model include failures of specimens in restrained-thermal-growth (RTG) tests, pocketing erosion, and ply lifting

Failure Criteria for FRP Laminates in Plane Stress

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Camanho, Pedro P.

2003-01-01

A new set of six failure criteria for fiber reinforced polymer laminates is described. Derived from Dvorak's fracture mechanics analyses of cracked plies and from Puck's action plane concept, the physically-based criteria, denoted LaRC03, predict matrix and fiber failure accurately without requiring curve-fitting parameters. For matrix failure under transverse compression, the fracture plane is calculated by maximizing the Mohr-Coulomb effective stresses. A criterion for fiber kinking is obtained by calculating the fiber misalignment under load, and applying the matrix failure criterion in the coordinate frame of the misalignment. Fracture mechanics models of matrix cracks are used to develop a criterion for matrix in tension and to calculate the associated in-situ strengths. The LaRC03 criteria are applied to a few examples to predict failure load envelopes and to predict the failure mode for each region of the envelope. The analysis results are compared to the predictions using other available failure criteria and with experimental results. Predictions obtained with LaRC03 correlate well with the experimental results.

Prediction of morbidity and mortality in patients with type 2 diabetes.

PubMed

Wells, Brian J; Roth, Rachel; Nowacki, Amy S; Arrigain, Susana; Yu, Changhong; Rosenkrans, Wayne A; Kattan, Michael W

2013-01-01

Introduction. The objective of this study was to create a tool that accurately predicts the risk of morbidity and mortality in patients with type 2 diabetes according to an oral hypoglycemic agent. Materials and Methods. The model was based on a cohort of 33,067 patients with type 2 diabetes who were prescribed a single oral hypoglycemic agent at the Cleveland Clinic between 1998 and 2006. Competing risk regression models were created for coronary heart disease (CHD), heart failure, and stroke, while a Cox regression model was created for mortality. Propensity scores were used to account for possible treatment bias. A prediction tool was created and internally validated using tenfold cross-validation. The results were compared to a Framingham model and a model based on the United Kingdom Prospective Diabetes Study (UKPDS) for CHD and stroke, respectively. Results and Discussion. Median follow-up for the mortality outcome was 769 days. The numbers of patients experiencing events were as follows: CHD (3062), heart failure (1408), stroke (1451), and mortality (3661). The prediction tools demonstrated the following concordance indices (c-statistics) for the specific outcomes: CHD (0.730), heart failure (0.753), stroke (0.688), and mortality (0.719). The prediction tool was superior to the Framingham model at predicting CHD and was at least as accurate as the UKPDS model at predicting stroke. Conclusions. We created an accurate tool for predicting the risk of stroke, coronary heart disease, heart failure, and death in patients with type 2 diabetes. The calculator is available online at http://rcalc.ccf.org under the heading "Type 2 Diabetes" and entitled, "Predicting 5-Year Morbidity and Mortality." This may be a valuable tool to aid the clinician's choice of an oral hypoglycemic, to better inform patients, and to motivate dialogue between physician and patient.

Prediction of failure in notched carbon-fibre-reinforced-polymer laminates under multi-axial loading.

PubMed

Tan, J L Y; Deshpande, V S; Fleck, N A

2016-07-13

A damage-based finite-element model is used to predict the fracture behaviour of centre-notched quasi-isotropic carbon-fibre-reinforced-polymer laminates under multi-axial loading. Damage within each ply is associated with fibre tension, fibre compression, matrix tension and matrix compression. Inter-ply delamination is modelled by cohesive interfaces using a traction-separation law. Failure envelopes for a notch and a circular hole are predicted for in-plane multi-axial loading and are in good agreement with the observed failure envelopes from a parallel experimental study. The ply-by-ply (and inter-ply) damage evolution and the critical mechanisms of ultimate failure also agree with the observed damage evolution. It is demonstrated that accurate predictions of notched compressive strength are obtained upon employing the band broadening stress for microbuckling, highlighting the importance of this damage mode in compression. This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-01-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We apply support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicts model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures are determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations are the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

On the estimation of risk associated with an attenuation prediction

NASA Technical Reports Server (NTRS)

Crane, R. K.

1992-01-01

Viewgraphs from a presentation on the estimation of risk associated with an attenuation prediction is presented. Topics covered include: link failure - attenuation exceeding a specified threshold for a specified time interval or intervals; risk - the probability of one or more failures during the lifetime of the link or during a specified accounting interval; the problem - modeling the probability of attenuation by rainfall to provide a prediction of the attenuation threshold for a specified risk; and an accounting for the inadequacy of a model or models.

Anger, hostility, and hospitalizations in patients with heart failure.

PubMed

Keith, Felicia; Krantz, David S; Chen, Rusan; Harris, Kristie M; Ware, Catherine M; Lee, Amy K; Bellini, Paula G; Gottlieb, Stephen S

2017-09-01

Heart failure patients have a high hospitalization rate, and anger and hostility are associated with coronary heart disease morbidity and mortality. Using structural equation modeling, this prospective study assessed the predictive validity of anger and hostility traits for cardiovascular and all-cause rehospitalizations in patients with heart failure. 146 heart failure patients were administered the STAXI and Cook-Medley Hostility Inventory to measure anger, hostility, and their component traits. Hospitalizations were recorded for up to 3 years following baseline. Causes of hospitalizations were categorized as heart failure, total cardiac, noncardiac, and all-cause (sum of cardiac and noncardiac). Measurement models were separately fit for Anger and Hostility, followed by a Confirmatory Factor Analysis to estimate the relationship between the Anger and Hostility constructs. An Anger model consisted of State Anger, Trait Anger, Anger Expression Out, and Anger Expression In, and a Hostility model included Cynicism, Hostile Affect, Aggressive Responding, and Hostile Attribution. The latent construct of Anger did not predict any of the hospitalization outcomes, but Hostility significantly predicted all-cause hospitalizations. Analyses of individual trait components of each of the 2 models indicated that Anger Expression Out predicted all-cause and noncardiac hospitalizations, and Trait Anger predicted noncardiac hospitalizations. None of the individual components of Hostility were related to rehospitalizations or death. The construct of Hostility and several components of Anger are predictive of hospitalizations that were not specific to cardiac causes. Mechanisms common to a variety of health problems, such as self-care and risky health behaviors, may be involved in these associations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predicting Failure of Glyburide Therapy in Gestational Diabetes

PubMed Central

Harper, Lorie M.; Glover, Angelica V.; Biggio, Joseph R.; Tita, Alan

2016-01-01

Objective We sought to develop a prediction model to identify women with gestational diabetes (GDM) who require insulin to achieve glycemic control. Study Design Retrospective cohort of all singletons with GDM treated with glyburide 2007–2013. Glyburide failure was defined as reaching glyburide 20 mg/day and receiving insulin. Glyburide success was defined as any glyburide dose without insulin and >70% of visits with glycemic control. Multivariable logistic regression analysis was performed to create a prediction model. Results Of 360 women, 63 (17.5%) qualified as glyburide failure and 157 (43.6%) glyburide success. The final prediction model for glyburide failure included prior GDM, GDM diagnosis ≤26 weeks, 1-hour GCT ≥228 mg/dL, 3-hour GTT 1-hour value ≥221 mg/dL, ≥7 post-prandial blood sugars >120 mg/dL in the week glyburide started, and ≥1 blood sugar >200 mg/dL. The model accurately classified 81% of subjects. Conclusions Women with GDM who will require insulin can be identified at initiation of pharmacologic therapy. PMID:26796130

Predicting failure of glyburide therapy in gestational diabetes.

PubMed

Harper, L M; Glover, A V; Biggio, J R; Tita, A

2016-05-01

We sought to develop a prediction model to identify women with gestational diabetes (GDM) who require insulin to achieve glycemic control. Retrospective cohort of all singletons with GDM treated with glyburide from 2007 to 2013. Glyburide failure was defined as reaching glyburide 20 mg day(-1) and receiving insulin. Glyburide success was defined as any glyburide dose without insulin and >70% of visits with glycemic control. Multivariable logistic regression analysis was performed to create a prediction model. Of the 360 women, 63 (17.5%) qualified as glyburide failure and 157 (43.6%) as glyburide success. The final prediction model for glyburide failure included prior GDM, GDM diagnosis ⩽26 weeks, 1-h glucose challenge test ⩾228 mg dl(-1), 3-h glucose tolerance test 1-h value ⩾221 mg dl(-1), ⩾7 postprandial blood sugars >120 mg dl(-1) in the week glyburide started and ⩾1 blood sugar >200 mg dl(-1). The model accurately classified 81% of subjects. Women with GDM who will require insulin can be identified at the initiation of pharmacological therapy.

Subject specific finite element modeling of periprosthetic femoral fracture using element deactivation to simulate bone failure.

PubMed

Miles, Brad; Kolos, Elizabeth; Walter, William L; Appleyard, Richard; Shi, Angela; Li, Qing; Ruys, Andrew J

2015-06-01

Subject-specific finite element (FE) modeling methodology could predict peri-prosthetic femoral fracture (PFF) for cementless hip arthoplasty in the early postoperative period. This study develops methodology for subject-specific finite element modeling by using the element deactivation technique to simulate bone failure and validate with experimental testing, thereby predicting peri-prosthetic femoral fracture in the early postoperative period. Material assignments for biphasic and triphasic models were undertaken. Failure modeling with the element deactivation feature available in ABAQUS 6.9 was used to simulate a crack initiation and propagation in the bony tissue based upon a threshold of fracture strain. The crack mode for the biphasic models was very similar to the experimental testing crack mode, with a similar shape and path of the crack. The fracture load is sensitive to the friction coefficient at the implant-bony interface. The development of a novel technique to simulate bone failure by element deactivation of subject-specific finite element models could aid prediction of fracture load in addition to fracture risk characterization for PFF. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Strength Evaluation and Failure Prediction of Short Carbon Fiber Reinforced Nylon Spur Gears by Finite Element Modeling

NASA Astrophysics Data System (ADS)

Hu, Zhong; Hossan, Mohammad Robiul

2013-06-01

In this paper, short carbon fiber reinforced nylon spur gear pairs, and steel and unreinforced nylon spur gear pairs have been selected for study and comparison. A 3D finite element model was developed to simulate the multi-axial stress-strain behaviors of the gear tooth. Failure prediction has been conducted based on the different failure criteria, including Tsai-Wu criterion. The tooth roots, where has stress concentration and the potential for failure, have been carefully investigated. The modeling results show that the short carbon fiber reinforced nylon gear fabricated by properly controlled injection molding processes can provide higher strength and better performance.

Do heart and respiratory rate variability improve prediction of extubation outcomes in critically ill patients?

PubMed Central

2014-01-01

Introduction Prolonged ventilation and failed extubation are associated with increased harm and cost. The added value of heart and respiratory rate variability (HRV and RRV) during spontaneous breathing trials (SBTs) to predict extubation failure remains unknown. Methods We enrolled 721 patients in a multicenter (12 sites), prospective, observational study, evaluating clinical estimates of risk of extubation failure, physiologic measures recorded during SBTs, HRV and RRV recorded before and during the last SBT prior to extubation, and extubation outcomes. We excluded 287 patients because of protocol or technical violations, or poor data quality. Measures of variability (97 HRV, 82 RRV) were calculated from electrocardiogram and capnography waveforms followed by automated cleaning and variability analysis using Continuous Individualized Multiorgan Variability Analysis (CIMVA™) software. Repeated randomized subsampling with training, validation, and testing were used to derive and compare predictive models. Results Of 434 patients with high-quality data, 51 (12%) failed extubation. Two HRV and eight RRV measures showed statistically significant association with extubation failure (P <0.0041, 5% false discovery rate). An ensemble average of five univariate logistic regression models using RRV during SBT, yielding a probability of extubation failure (called WAVE score), demonstrated optimal predictive capacity. With repeated random subsampling and testing, the model showed mean receiver operating characteristic area under the curve (ROC AUC) of 0.69, higher than heart rate (0.51), rapid shallow breathing index (RBSI; 0.61) and respiratory rate (0.63). After deriving a WAVE model based on all data, training-set performance demonstrated that the model increased its predictive power when applied to patients conventionally considered high risk: a WAVE score >0.5 in patients with RSBI >105 and perceived high risk of failure yielded a fold increase in risk of extubation failure of 3.0 (95% confidence interval (CI) 1.2 to 5.2) and 3.5 (95% CI 1.9 to 5.4), respectively. Conclusions Altered HRV and RRV (during the SBT prior to extubation) are significantly associated with extubation failure. A predictive model using RRV during the last SBT provided optimal accuracy of prediction in all patients, with improved accuracy when combined with clinical impression or RSBI. This model requires a validation cohort to evaluate accuracy and generalizability. Trial registration ClinicalTrials.gov NCT01237886. Registered 13 October 2010. PMID:24713049

Thermal barrier coating life prediction model development

NASA Technical Reports Server (NTRS)

Hillery, R. V.; Pilsner, B. H.; Mcknight, R. L.; Cook, T. S.; Hartle, M. S.

1988-01-01

This report describes work performed to determine the predominat modes of degradation of a plasma sprayed thermal barrier coating system and to develop and verify life prediction models accounting for these degradation modes. The primary TBC system consisted of a low pressure plasma sprayed NiCrAlY bond coat, an air plasma sprayed ZrO2-Y2O3 top coat, and a Rene' 80 substrate. The work was divided into 3 technical tasks. The primary failure mode to be addressed was loss of the zirconia layer through spalling. Experiments showed that oxidation of the bond coat is a significant contributor to coating failure. It was evident from the test results that the species of oxide scale initially formed on the bond coat plays a role in coating degradation and failure. It was also shown that elevated temperature creep of the bond coat plays a role in coating failure. An empirical model was developed for predicting the test life of specimens with selected coating, specimen, and test condition variations. In the second task, a coating life prediction model was developed based on the data from Task 1 experiments, results from thermomechanical experiments performed as part of Task 2, and finite element analyses of the TBC system during thermal cycles. The third and final task attempted to verify the validity of the model developed in Task 2. This was done by using the model to predict the test lives of several coating variations and specimen geometries, then comparing these predicted lives to experimentally determined test lives. It was found that the model correctly predicts trends, but that additional refinement is needed to accurately predict coating life.

Simulation Assisted Risk Assessment: Blast Overpressure Modeling

NASA Technical Reports Server (NTRS)

Lawrence, Scott L.; Gee, Ken; Mathias, Donovan; Olsen, Michael

2006-01-01

A probabilistic risk assessment (PRA) approach has been developed and applied to the risk analysis of capsule abort during ascent. The PRA is used to assist in the identification of modeling and simulation applications that can significantly impact the understanding of crew risk during this potentially dangerous maneuver. The PRA approach is also being used to identify the appropriate level of fidelity for the modeling of those critical failure modes. The Apollo launch escape system (LES) was chosen as a test problem for application of this approach. Failure modes that have been modeled and/or simulated to date include explosive overpressure-based failure, explosive fragment-based failure, land landing failures (range limits exceeded either near launch or Mode III trajectories ending on the African continent), capsule-booster re-contact during separation, and failure due to plume-induced instability. These failure modes have been investigated using analysis tools in a variety of technical disciplines at various levels of fidelity. The current paper focuses on the development and application of a blast overpressure model for the prediction of structural failure due to overpressure, including the application of high-fidelity analysis to predict near-field and headwinds effects.

Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.

2012-12-01

Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).

A predictive model for failure properties of thermoset resins

NASA Technical Reports Server (NTRS)

Caruthers, James M.; Bowles, Kenneth J.

1989-01-01

A predictive model for the three-dimensional failure behavior of engineering polymers has been developed in a recent NASA-sponsored research program. This model acknowledges the underlying molecular deformation mechanisms and thus accounts for the effects of different chemical compositions, crosslink density, functionality of the curing agent, etc., on the complete nonlinear stress-strain response including yield. The material parameters required by the model can be determined from test-tube quantities of a new resin in only a few days. Thus, we can obtain a first-order prediction of the applicability of a new resin for an advanced aerospace application without synthesizing the large quantities of material needed for failure testing. This technology will effect order-of-magnitude reductions in the time and expense required to develop new engineering polymers.

Alchemy and uncertainty: What good are models?

Treesearch

F.L. Bunnell

1989-01-01

Wildlife-habitat models are increasing in abundance, diversity, and use, but symptoms of failure are evident in their application, including misuse, disuse, failure to test, and litigation. Reasons for failure often relate to the different purposes managers and researchers have for using the models to predict and to aid understanding. This paper examines these two...

Posttest analysis of the 1:6-scale reinforced concrete containment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pfeiffer, P.A.; Kennedy, J.M.; Marchertas, A.H.

A prediction of the response of the Sandia National Laboratories 1:6- scale reinforced concrete containment model test was made by Argonne National Laboratory. ANL along with nine other organizations performed a detailed nonlinear response analysis of the 1:6-scale model containment subjected to overpressurization in the fall of 1986. The two-dimensional code TEMP-STRESS and the three-dimensional NEPTUNE code were utilized (1) to predict the global response of the structure, (2) to identify global failure sites and the corresponding failure pressures and (3) to identify some local failure sites and pressure levels. A series of axisymmetric models was studied with the two-dimensionalmore » computer program TEMP-STRESS. The comparison of these pretest computations with test data from the containment model has provided a test for the capability of the respective finite element codes to predict global failure modes, and hence serves as a validation of these codes. Only the two-dimensional analyses will be discussed in this paper. 3 refs., 10 figs.« less

A simple nonlocal damage model for predicting failure of notched laminates

NASA Technical Reports Server (NTRS)

Kennedy, T. C.; Nahan, M. F.

1995-01-01

The ability to predict failure loads in notched composite laminates is a requirement in a variety of structural design circumstances. A complicating factor is the development of a zone of damaged material around the notch tip. The objective of this study was to develop a computational technique that simulates progressive damage growth around a notch in a manner that allows the prediction of failure over a wide range of notch sizes. This was accomplished through the use of a relatively simple, nonlocal damage model that incorporates strain-softening. This model was implemented in a two-dimensional finite element program. Calculations were performed for two different laminates with various notch sizes under tensile loading, and the calculations were found to correlate well with experimental results.

NASA Structural Analysis Report on the American Airlines Flight 587 Accident - Local Analysis of the Right Rear Lug

NASA Technical Reports Server (NTRS)

Raju, Ivatury S; Glaessgen, Edward H.; Mason, Brian H; Krishnamurthy, Thiagarajan; Davila, Carlos G

2005-01-01

A detailed finite element analysis of the right rear lug of the American Airlines Flight 587 - Airbus A300-600R was performed as part of the National Transportation Safety Board s failure investigation of the accident that occurred on November 12, 2001. The loads experienced by the right rear lug are evaluated using global models of the vertical tail, local models near the right rear lug, and a global-local analysis procedure. The right rear lug was analyzed using two modeling approaches. In the first approach, solid-shell type modeling is used, and in the second approach, layered-shell type modeling is used. The solid-shell and the layered-shell modeling approaches were used in progressive failure analyses (PFA) to determine the load, mode, and location of failure in the right rear lug under loading representative of an Airbus certification test conducted in 1985 (the 1985-certification test). Both analyses were in excellent agreement with each other on the predicted failure loads, failure mode, and location of failure. The solid-shell type modeling was then used to analyze both a subcomponent test conducted by Airbus in 2003 (the 2003-subcomponent test) and the accident condition. Excellent agreement was observed between the analyses and the observed failures in both cases. From the analyses conducted and presented in this paper, the following conclusions were drawn. The moment, Mx (moment about the fuselage longitudinal axis), has significant effect on the failure load of the lugs. Higher absolute values of Mx give lower failure loads. The predicted load, mode, and location of the failure of the 1985-certification test, 2003-subcomponent test, and the accident condition are in very good agreement. This agreement suggests that the 1985-certification and 2003- subcomponent tests represent the accident condition accurately. The failure mode of the right rear lug for the 1985-certification test, 2003-subcomponent test, and the accident load case is identified as a cleavage-type failure. For the accident case, the predicted failure load for the right rear lug from the PFA is greater than 1.98 times the limit load of the lugs. I.

Structural Analysis of the Right Rear Lug of American Airlines Flight 587

NASA Technical Reports Server (NTRS)

Raju, Ivatury S.; Glaessgen, Edward H.; Mason, Brian H.; Krishnamurthy, Thiagarajan; Davila, Carlos G.

2006-01-01

A detailed finite element analysis of the right rear lug of the American Airlines Flight 587 - Airbus A300-600R was performed as part of the National Transportation Safety Board s failure investigation of the accident that occurred on November 12, 2001. The loads experienced by the right rear lug are evaluated using global models of the vertical tail, local models near the right rear lug, and a global-local analysis procedure. The right rear lug was analyzed using two modeling approaches. In the first approach, solid-shell type modeling is used, and in the second approach, layered-shell type modeling is used. The solid-shell and the layered-shell modeling approaches were used in progressive failure analyses (PFA) to determine the load, mode, and location of failure in the right rear lug under loading representative of an Airbus certification test conducted in 1985 (the 1985-certification test). Both analyses were in excellent agreement with each other on the predicted failure loads, failure mode, and location of failure. The solid-shell type modeling was then used to analyze both a subcomponent test conducted by Airbus in 2003 (the 2003-subcomponent test) and the accident condition. Excellent agreement was observed between the analyses and the observed failures in both cases. The moment, Mx (moment about the fuselage longitudinal axis), has significant effect on the failure load of the lugs. Higher absolute values of Mx give lower failure loads. The predicted load, mode, and location of the failure of the 1985- certification test, 2003-subcomponent test, and the accident condition are in very good agreement. This agreement suggests that the 1985-certification and 2003-subcomponent tests represent the accident condition accurately. The failure mode of the right rear lug for the 1985-certification test, 2003-subcomponent test, and the accident load case is identified as a cleavage-type failure. For the accident case, the predicted failure load for the right rear lug from the PFA is greater than 1.98 times the limit load of the lugs.

Predicting remaining life by fusing the physics of failure modeling with diagnostics

NASA Astrophysics Data System (ADS)

Kacprzynski, G. J.; Sarlashkar, A.; Roemer, M. J.; Hess, A.; Hardman, B.

2004-03-01

Technology that enables failure prediction of critical machine components (prognostics) has the potential to significantly reduce maintenance costs and increase availability and safety. This article summarizes a research effort funded through the U.S. Defense Advanced Research Projects Agency and Naval Air System Command aimed at enhancing prognostic accuracy through more advanced physics-of-failure modeling and intelligent utilization of relevant diagnostic information. H-60 helicopter gear is used as a case study to introduce both stochastic sub-zone crack initiation and three-dimensional fracture mechanics lifing models along with adaptive model updating techniques for tuning key failure mode variables at a local material/damage site based on fused vibration features. The overall prognostic scheme is aimed at minimizing inherent modeling and operational uncertainties via sensed system measurements that evolve as damage progresses.

Review on failure prediction techniques of composite single lap joint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ab Ghani, A.F., E-mail: ahmadfuad@utem.edu.my; Rivai, Ahmad, E-mail: ahmadrivai@utem.edu.my

2016-03-29

Adhesive bonding is the most appropriate joining method in construction of composite structures. The use of reliable design and prediction technique will produce better performance of bonded joints. Several papers from recent papers and journals have been reviewed and synthesized to understand the current state of the art in this area. It is done by studying the most relevant analytical solutions for composite adherends with start of reviewing the most fundamental ones involving beam/plate theory. It is then extended to review single lap joint non linearity and failure prediction and finally on the failure prediction on composite single lap joint.more » The review also encompasses the finite element modelling part as tool to predict the elastic response of composite single lap joint and failure prediction numerically.« less

A micromechanics-based strength prediction methodology for notched metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1992-01-01

An analytical micromechanics based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and post fatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

A micromechanics-based strength prediction methodology for notched metal-matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.

1993-01-01

An analytical micromechanics-based strength prediction methodology was developed to predict failure of notched metal matrix composites. The stress-strain behavior and notched strength of two metal matrix composites, boron/aluminum (B/Al) and silicon-carbide/titanium (SCS-6/Ti-15-3), were predicted. The prediction methodology combines analytical techniques ranging from a three-dimensional finite element analysis of a notched specimen to a micromechanical model of a single fiber. In the B/Al laminates, a fiber failure criteria based on the axial and shear stress in the fiber accurately predicted laminate failure for a variety of layups and notch-length to specimen-width ratios with both circular holes and sharp notches when matrix plasticity was included in the analysis. For the SCS-6/Ti-15-3 laminates, a fiber failure based on the axial stress in the fiber correlated well with experimental results for static and postfatigue residual strengths when fiber matrix debonding and matrix cracking were included in the analysis. The micromechanics-based strength prediction methodology offers a direct approach to strength prediction by modeling behavior and damage on a constituent level, thus, explicitly including matrix nonlinearity, fiber matrix debonding, and matrix cracking.

The Prognostic Accuracy of Suggested Predictors of Failure of Medical Management in Patients With Nontuberculous Spinal Epidural Abscess.

PubMed

Stratton, Alexandra; Faris, Peter; Thomas, Kenneth

2018-05-01

Retrospective cohort study. To test the external validity of the 2 published prediction criteria for failure of medical management in patients with spinal epidural abscess (SEA). Patients with SEA over a 10-year period at a tertiary care center were identified using ICD-10 (International Classification of Diseases, 10th Revision) diagnostic codes; electronic and paper charts were reviewed. The incidence of SEA and the proportion of patients with SEA that were treated medically were calculated. The rate of failure of medical management was determined. The published prediction models were applied to our data to determine how predictive they were of failure in our cohort. A total of 550 patients were identified using ICD-10 codes, 160 of whom had a magnetic resonance imaging-confirmed diagnosis of SEA. The incidence of SEA was 16 patients per year. Seventy-five patients were found to be intentionally managed medically and were included in the analysis. Thirteen of these 75 patients failed medical management (17%). Based on the published prediction criteria, 26% (Kim et al) and 45% (Patel et al) of our patients were expected to fail. Published prediction models for failure of medical management of SEA were not valid in our cohort. However, once calibrated to our cohort, Patel's model consisting of positive blood culture, presence of diabetes, white blood cells >12.5, and C-reactive protein >115 was the better model for our data.

Development of failure model for nickel cadmium cells

NASA Technical Reports Server (NTRS)

Gupta, A.

1980-01-01

The development of a method for the life prediction of nickel cadmium cells is discussed. The approach described involves acquiring an understanding of the mechanisms of degradation and failure and at the same time developing nondestructive evaluation techniques for the nickel cadmium cells. The development of a statistical failure model which will describe the mechanisms of degradation and failure is outlined.

Model-Biased, Data-Driven Adaptive Failure Prediction

NASA Technical Reports Server (NTRS)

Leen, Todd K.

2004-01-01

This final report, which contains a research summary and a viewgraph presentation, addresses clustering and data simulation techniques for failure prediction. The researchers applied their techniques to both helicopter gearbox anomaly detection and segmentation of Earth Observing System (EOS) satellite imagery.

Predicting Renal Failure Progression in Chronic Kidney Disease Using Integrated Intelligent Fuzzy Expert System.

PubMed

Norouzi, Jamshid; Yadollahpour, Ali; Mirbagheri, Seyed Ahmad; Mazdeh, Mitra Mahdavi; Hosseini, Seyed Ahmad

2016-01-01

Chronic kidney disease (CKD) is a covert disease. Accurate prediction of CKD progression over time is necessary for reducing its costs and mortality rates. The present study proposes an adaptive neurofuzzy inference system (ANFIS) for predicting the renal failure timeframe of CKD based on real clinical data. This study used 10-year clinical records of newly diagnosed CKD patients. The threshold value of 15 cc/kg/min/1.73 m(2) of glomerular filtration rate (GFR) was used as the marker of renal failure. A Takagi-Sugeno type ANFIS model was used to predict GFR values. Variables of age, sex, weight, underlying diseases, diastolic blood pressure, creatinine, calcium, phosphorus, uric acid, and GFR were initially selected for the predicting model. Weight, diastolic blood pressure, diabetes mellitus as underlying disease, and current GFR(t) showed significant correlation with GFRs and were selected as the inputs of model. The comparisons of the predicted values with the real data showed that the ANFIS model could accurately estimate GFR variations in all sequential periods (Normalized Mean Absolute Error lower than 5%). Despite the high uncertainties of human body and dynamic nature of CKD progression, our model can accurately predict the GFR variations at long future periods.

SU-F-R-46: Predicting Distant Failure in Lung SBRT Using Multi-Objective Radiomics Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Z; Folkert, M; Iyengar, P

2016-06-15

Purpose: To predict distant failure in lung stereotactic body radiation therapy (SBRT) in early stage non-small cell lung cancer (NSCLC) by using a new multi-objective radiomics model. Methods: Currently, most available radiomics models use the overall accuracy as the objective function. However, due to data imbalance, a single object may not reflect the performance of a predictive model. Therefore, we developed a multi-objective radiomics model which considers both sensitivity and specificity as the objective functions simultaneously. The new model is used to predict distant failure in lung SBRT using 52 patients treated at our institute. Quantitative imaging features of PETmore » and CT as well as clinical parameters are utilized to build the predictive model. Image features include intensity features (9), textural features (12) and geometric features (8). Clinical parameters for each patient include demographic parameters (4), tumor characteristics (8), treatment faction schemes (4) and pretreatment medicines (6). The modelling procedure consists of two steps: extracting features from segmented tumors in PET and CT; and selecting features and training model parameters based on multi-objective. Support Vector Machine (SVM) is used as the predictive model, while a nondominated sorting-based multi-objective evolutionary computation algorithm II (NSGA-II) is used for solving the multi-objective optimization. Results: The accuracy for PET, clinical, CT, PET+clinical, PET+CT, CT+clinical, PET+CT+clinical are 71.15%, 84.62%, 84.62%, 85.54%, 82.69%, 84.62%, 86.54%, respectively. The sensitivities for the above seven combinations are 41.76%, 58.33%, 50.00%, 50.00%, 41.67%, 41.67%, 58.33%, while the specificities are 80.00%, 92.50%, 90.00%, 97.50%, 92.50%, 97.50%, 97.50%. Conclusion: A new multi-objective radiomics model for predicting distant failure in NSCLC treated with SBRT was developed. The experimental results show that the best performance can be obtained by combining all features.« less

Observations, models, and mechanisms of failure of surface rocks surrounding planetary surface loads

NASA Technical Reports Server (NTRS)

Schultz, R. A.; Zuber, M. T.

1994-01-01

Geophysical models of flexural stresses in an elastic lithosphere due to an axisymmetric surface load typically predict a transition with increased distance from the center of the load of radial thrust faults to strike-slip faults to concentric normal faults. These model predictions are in conflict with the absence of annular zones of strike-slip faults around prominent loads such as lunar maria, Martian volcanoes, and the Martian Tharsis rise. We suggest that this paradox arises from difficulties in relating failure criteria for brittle rocks to the stress models. Indications that model stresses are inappropriate for use in fault-type prediction include (1) tensile principal stresses larger than realistic values of rock tensile strength, and/or (2) stress differences significantly larger than those allowed by rock-strength criteria. Predictions of surface faulting that are consistent with observations can be obtained instead by using tensile and shear failure criteria, along with calculated stress differences and trajectories, with model stress states not greatly in excess of the maximum allowed by rock fracture criteria.

Very High Cycle Fatigue Failure Analysis and Life Prediction of Cr-Ni-W Gear Steel Based on Crack Initiation and Growth Behaviors.

PubMed

Deng, Hailong; Li, Wei; Sakai, Tatsuo; Sun, Zhenduo

2015-12-02

The unexpected failures of structural materials in very high cycle fatigue (VHCF) regime have been a critical issue in modern engineering design. In this study, the VHCF property of a Cr-Ni-W gear steel was experimentally investigated under axial loading with the stress ratio of R = -1, and a life prediction model associated with crack initiation and growth behaviors was proposed. Results show that the Cr-Ni-W gear steel exhibits the constantly decreasing S-N property without traditional fatigue limit, and the fatigue strength corresponding to 10⁸ cycles is around 485 MPa. The inclusion-fine granular area (FGA)-fisheye induced failure becomes the main failure mechanism in the VHCF regime, and the local stress around the inclusion play a key role. By using the finite element analysis of representative volume element, the local stress tends to increase with the increase of elastic modulus difference between inclusion and matrix. The predicted crack initiation life occupies the majority of total fatigue life, while the predicted crack growth life is only accounts for a tiny fraction. In view of the good agreement between the predicted and experimental results, the proposed VHCF life prediction model involving crack initiation and growth can be acceptable for inclusion-FGA-fisheye induced failure.

Round-robin analysis of the behavior of a 1:6-scale reinforced concrete containment model pressurized to failure: Posttest evaluations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clauss, D.B.

A 1:6-scale model of a reinforced concrete containment building was pressurized incrementally to failure at a remote site at Sandia National Laboratories. The response of the model was recorded with more than 1000 channels of data (primarily strain and displacement measurements) at 37 discrete pressure levels. The primary objective of this test was to generate data that could be used to validate methods for predicting the performance of containment buildings subject to loads beyond their design basis. Extensive analyses were conducted before the test to predict the behavior of the model. Ten organizations in Europe and the US conducted independentmore » analyses of the model and contributed to a report on the pretest predictions. Predictions included structural response at certain predetermined locations in the model as well as capacity and failure mode. This report discusses comparisons between the pretest predictions and the experimental results. Posttest evaluations that were conducted to provide additional insight into the model behavior are also described. The significance of the analysis and testing of the 1:6-scale model to performance evaluations of actual containments subject to beyond design basis loads is also discussed. 70 refs., 428 figs., 24 tabs.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hobbs, Michael L.

We previously developed a PETN thermal decomposition model that accurately predicts thermal ignition and detonator failure [1]. This model was originally developed for CALORE [2] and required several complex user subroutines. Recently, a simplified version of the PETN decomposition model was implemented into ARIA [3] using a general chemistry framework without need for user subroutines. Detonator failure was also predicted with this new model using ENCORE. The model was simplified by 1) basing the model on moles rather than mass, 2) simplifying the thermal conductivity model, and 3) implementing ARIA’s new phase change model. This memo briefly describes the model,more » implementation, and validation.« less

A Novel Multiscale Physics Based Progressive Failure Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.; Bednarcyk, Brett A.; Collier, Craig S.; Yarrington, Phillip W.

2008-01-01

A variable fidelity, multiscale, physics based finite element procedure for predicting progressive damage and failure of laminated continuous fiber reinforced composites is introduced. At every integration point in a finite element model, progressive damage is accounted for at the lamina-level using thermodynamically based Schapery Theory. Separate failure criteria are applied at either the global-scale or the microscale in two different FEM models. A micromechanics model, the Generalized Method of Cells, is used to evaluate failure criteria at the micro-level. The stress-strain behavior and observed failure mechanisms are compared with experimental results for both models.

Degradation Prediction Model Based on a Neural Network with Dynamic Windows

PubMed Central

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

A Plasticity Model to Predict the Effects of Confinement on Concrete

NASA Astrophysics Data System (ADS)

Wolf, Julie

A plasticity model to predict the behavior of confined concrete is developed. The model is designed to implicitly account for the increase in strength and ductility due to confining a concrete member. The concrete model is implemented into a finite element (FE) model. By implicitly including the change in the strength and ductility in the material model, the confining material can be explicitly included in the FE model. Any confining material can be considered, and the effects on the concrete of failure in the confinement material can be modeled. Test data from a wide variety of different concretes utilizing different confinement methods are used to estimate the model parameters. This allows the FE model to capture the generalized behavior of concrete under multiaxial loading. The FE model is used to predict the results of tests on reinforced concrete members confined by steel hoops and fiber reinforced polymer (FRP) jackets. Loading includes pure axial load and axial load-moment combinations. Variability in the test data makes the model predictions difficult to compare but, overall, the FE model is able to capture the effects of confinement on concrete. Finally, the FE model is used to compare the performance of steel hoop to FRP confined sections, and of square to circular cross sections. As expected, circular sections are better able to engage the confining material, leading to higher strengths. However, higher strains are seen in the confining material for the circular sections. This leads to failure at lower axial strain levels in the case of the FRP confined sections. Significant differences are seen in the behavior of FRP confined members and steel hoop confined members. Failure in the FRP members is always determined by rupture in the composite jacket. As a result, the FRP members continue to take load up to failure. In contrast, the steel hoop confined sections exhibit extensive strain softening before failure. This comparison illustrates the usefulness of the concrete model as a tool for designers. Overall, the concrete model provides a flexible and powerful method to predict the performance of confined concrete.

Preface to the special volume on the second Sandia Fracture Challenge

DOE PAGES

Kramer, Sharlotte Lorraine Bolyard; Boyce, Brad

2016-01-01

In this study, ductile failure of structural metals is a pervasive issue for applications such as automotive manufacturing, transportation infrastructures, munitions and armor, and energy generation. Experimental investigation of all relevant failure scenarios is intractable, requiring reliance on computation models. Our confidence in model predictions rests on unbiased assessments of the entire predictive capability, including the mathematical formulation, numerical implementation, calibration, and execution.

A Novel MiRNA-Based Predictive Model for Biochemical Failure Following Post-Prostatectomy Salvage Radiation Therapy

PubMed Central

Stegmaier, Petra; Drendel, Vanessa; Mo, Xiaokui; Ling, Stella; Fabian, Denise; Manring, Isabel; Jilg, Cordula A.; Schultze-Seemann, Wolfgang; McNulty, Maureen; Zynger, Debra L.; Martin, Douglas; White, Julia; Werner, Martin; Grosu, Anca L.; Chakravarti, Arnab

2015-01-01

Purpose To develop a microRNA (miRNA)-based predictive model for prostate cancer patients of 1) time to biochemical recurrence after radical prostatectomy and 2) biochemical recurrence after salvage radiation therapy following documented biochemical disease progression post-radical prostatectomy. Methods Forty three patients who had undergone salvage radiation therapy following biochemical failure after radical prostatectomy with greater than 4 years of follow-up data were identified. Formalin-fixed, paraffin-embedded tissue blocks were collected for all patients and total RNA was isolated from 1mm cores enriched for tumor (>70%). Eight hundred miRNAs were analyzed simultaneously using the nCounter human miRNA v2 assay (NanoString Technologies; Seattle, WA). Univariate and multivariate Cox proportion hazards regression models as well as receiver operating characteristics were used to identify statistically significant miRNAs that were predictive of biochemical recurrence. Results Eighty eight miRNAs were identified to be significantly (p<0.05) associated with biochemical failure post-prostatectomy by multivariate analysis and clustered into two groups that correlated with early (≤ 36 months) versus late recurrence (>36 months). Nine miRNAs were identified to be significantly (p<0.05) associated by multivariate analysis with biochemical failure after salvage radiation therapy. A new predictive model for biochemical recurrence after salvage radiation therapy was developed; this model consisted of miR-4516 and miR-601 together with, Gleason score, and lymph node status. The area under the ROC curve (AUC) was improved to 0.83 compared to that of 0.66 for Gleason score and lymph node status alone. Conclusion miRNA signatures can distinguish patients who fail soon after radical prostatectomy versus late failures, giving insight into which patients may need adjuvant therapy. Notably, two novel miRNAs (miR-4516 and miR-601) were identified that significantly improve prediction of biochemical failure post-salvage radiation therapy compared to clinico-histopathological factors, supporting the use of miRNAs within clinically used predictive models. Both findings warrant further validation studies. PMID:25760964

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data.

PubMed

Golas, Sara Bersche; Shibahara, Takuma; Agboola, Stephen; Otaki, Hiroko; Sato, Jumpei; Nakae, Tatsuya; Hisamitsu, Toru; Kojima, Go; Felsted, Jennifer; Kakarmath, Sujay; Kvedar, Joseph; Jethwani, Kamal

2018-06-22

Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied. The primary aim of this study was to develop a 30-day readmission risk prediction model for heart failure patients discharged from a hospital admission. We used longitudinal electronic medical record data of heart failure patients admitted within a large healthcare system. Feature vectors included structured demographic, utilization, and clinical data, as well as selected extracts of un-structured data from clinician-authored notes. The risk prediction model was developed using deep unified networks (DUNs), a new mesh-like network structure of deep learning designed to avoid over-fitting. The model was validated with 10-fold cross-validation and results compared to models based on logistic regression, gradient boosting, and maxout networks. Overall model performance was assessed using concordance statistic. We also selected a discrimination threshold based on maximum projected cost saving to the Partners Healthcare system. Data from 11,510 patients with 27,334 admissions and 6369 30-day readmissions were used to train the model. After data processing, the final model included 3512 variables. The DUNs model had the best performance after 10-fold cross-validation. AUCs for prediction models were 0.664 ± 0.015, 0.650 ± 0.011, 0.695 ± 0.016 and 0.705 ± 0.015 for logistic regression, gradient boosting, maxout networks, and DUNs respectively. The DUNs model had an accuracy of 76.4% at the classification threshold that corresponded with maximum cost saving to the hospital. Deep learning techniques performed better than other traditional techniques in developing this EMR-based prediction model for 30-day readmissions in heart failure patients. Such models can be used to identify heart failure patients with impending hospitalization, enabling care teams to target interventions at their most high-risk patients and improving overall clinical outcomes.

LS-DYNA Simulation of Hemispherical-punch Stamping Process Using an Efficient Algorithm for Continuum Damage Based Elastoplastic Constitutive Equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salajegheh, Nima; Abedrabbo, Nader; Pourboghrat, Farhang

An efficient integration algorithm for continuum damage based elastoplastic constitutive equations is implemented in LS-DYNA. The isotropic damage parameter is defined as the ratio of the damaged surface area over the total cross section area of the representative volume element. This parameter is incorporated into the integration algorithm as an internal variable. The developed damage model is then implemented in the FEM code LS-DYNA as user material subroutine (UMAT). Pure stretch experiments of a hemispherical punch are carried out for copper sheets and the results are compared against the predictions of the implemented damage model. Evaluation of damage parameters ismore » carried out and the optimized values that correctly predicted the failure in the sheet are reported. Prediction of failure in the numerical analysis is performed through element deletion using the critical damage value. The set of failure parameters which accurately predict the failure behavior in copper sheets compared to experimental data is reported as well.« less

Stochastic damage evolution in textile laminates

NASA Technical Reports Server (NTRS)

Dzenis, Yuris A.; Bogdanovich, Alexander E.; Pastore, Christopher M.

1993-01-01

A probabilistic model utilizing random material characteristics to predict damage evolution in textile laminates is presented. Model is based on a division of each ply into two sublaminas consisting of cells. The probability of cell failure is calculated using stochastic function theory and maximal strain failure criterion. Three modes of failure, i.e. fiber breakage, matrix failure in transverse direction, as well as matrix or interface shear cracking, are taken into account. Computed failure probabilities are utilized in reducing cell stiffness based on the mesovolume concept. A numerical algorithm is developed predicting the damage evolution and deformation history of textile laminates. Effect of scatter of fiber orientation on cell properties is discussed. Weave influence on damage accumulation is illustrated with the help of an example of a Kevlar/epoxy laminate.

Viscoelastic behavior and lifetime (durability) predictions. [for laminated fiber reinforced plastics

NASA Technical Reports Server (NTRS)

Brinson, R. F.

1985-01-01

A method for lifetime or durability predictions for laminated fiber reinforced plastics is given. The procedure is similar to but not the same as the well known time-temperature-superposition principle for polymers. The method is better described as an analytical adaptation of time-stress-super-position methods. The analytical constitutive modeling is based upon a nonlinear viscoelastic constitutive model developed by Schapery. Time dependent failure models are discussed and are related to the constitutive models. Finally, results of an incremental lamination analysis using the constitutive and failure model are compared to experimental results. Favorable results between theory and predictions are presented using data from creep tests of about two months duration.

Meso-Scale Progressive Damage Behavior Characterization of Triaxial Braided Composites under Quasi-Static Tensile Load

NASA Astrophysics Data System (ADS)

Ren, Yiru; Zhang, Songjun; Jiang, Hongyong; Xiang, Jinwu

2018-04-01

Based on continuum damage mechanics (CDM), a sophisticated 3D meso-scale finite element (FE) model is proposed to characterize the progressive damage behavior of 2D Triaxial Braided Composites (2DTBC) with 60° braiding angle under quasi-static tensile load. The modified Von Mises strength criterion and 3D Hashin failure criterion are used to predict the damage initiation of the pure matrix and fiber tows. A combining interface damage and friction constitutive model is applied to predict the interface damage behavior. Murakami-Ohno stiffness degradation scheme is employed to predict the damage evolution process of each constituent. Coupling with the ordinary and translational symmetry boundary conditions, the tensile elastic response including tensile strength and failure strain of 2DTBC are in good agreement with the available experiment data. The numerical results show that the main failure modes of the composites under axial tensile load are pure matrix cracking, fiber and matrix tension failure in bias fiber tows, matrix tension failure in axial fiber tows and interface debonding; the main failure modes of the composites subjected to transverse tensile load are free-edge effect, matrix tension failure in bias fiber tows and interface debonding.

Assessing performance and validating finite element simulations using probabilistic knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dolin, Ronald M.; Rodriguez, E. A.

Two probabilistic approaches for assessing performance are presented. The first approach assesses probability of failure by simultaneously modeling all likely events. The probability each event causes failure along with the event's likelihood of occurrence contribute to the overall probability of failure. The second assessment method is based on stochastic sampling using an influence diagram. Latin-hypercube sampling is used to stochastically assess events. The overall probability of failure is taken as the maximum probability of failure of all the events. The Likelihood of Occurrence simulation suggests failure does not occur while the Stochastic Sampling approach predicts failure. The Likelihood of Occurrencemore » results are used to validate finite element predictions.« less

A Comparative Study of Classification and Regression Algorithms for Modelling Students' Academic Performance

ERIC Educational Resources Information Center

Strecht, Pedro; Cruz, Luís; Soares, Carlos; Mendes-Moreira, João; Abreu, Rui

2015-01-01

Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…

On rate-state and Coulomb failure models

USGS Publications Warehouse

Gomberg, J.; Beeler, N.; Blanpied, M.

2000-01-01

We examine the predictions of Coulomb failure stress and rate-state frictional models. We study the change in failure time (clock advance) Δt due to stress step perturbations (i.e., coseismic static stress increases) added to "background" stressing at a constant rate (i.e., tectonic loading) at time t0. The predictability of Δt implies a predictable change in seismicity rate r(t)/r0, testable using earthquake catalogs, where r0 is the constant rate resulting from tectonic stressing. Models of r(t)/r0, consistent with general properties of aftershock sequences, must predict an Omori law seismicity decay rate, a sequence duration that is less than a few percent of the mainshock cycle time and a return directly to the background rate. A Coulomb model requires that a fault remains locked during loading, that failure occur instantaneously, and that Δt is independent of t0. These characteristics imply an instantaneous infinite seismicity rate increase of zero duration. Numerical calculations of r(t)/r0 for different state evolution laws show that aftershocks occur on faults extremely close to failure at the mainshock origin time, that these faults must be "Coulomb-like," and that the slip evolution law can be precluded. Real aftershock population characteristics also may constrain rate-state constitutive parameters; a may be lower than laboratory values, the stiffness may be high, and/or normal stress may be lower than lithostatic. We also compare Coulomb and rate-state models theoretically. Rate-state model fault behavior becomes more Coulomb-like as constitutive parameter a decreases relative to parameter b. This is because the slip initially decelerates, representing an initial healing of fault contacts. The deceleration is more pronounced for smaller a, more closely simulating a locked fault. Even when the rate-state Δt has Coulomb characteristics, its magnitude may differ by some constant dependent on b. In this case, a rate-state model behaves like a modified Coulomb failure model in which the failure stress threshold is lowered due to weakening, increasing the clock advance. The deviation from a non-Coulomb response also depends on the loading rate, elastic stiffness, initial conditions, and assumptions about how state evolves.

A multidimensional stability model for predicting shallow landslide size and shape across landscapes.

PubMed

Milledge, David G; Bellugi, Dino; McKean, Jim A; Densmore, Alexander L; Dietrich, William E

2014-11-01

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size-frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data.

A multidimensional stability model for predicting shallow landslide size and shape across landscapes

PubMed Central

Milledge, David G; Bellugi, Dino; McKean, Jim A; Densmore, Alexander L; Dietrich, William E

2014-01-01

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size-frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data. PMID:26213663

Prediction of mode of death in heart failure: the Seattle Heart Failure Model.

PubMed

Mozaffarian, Dariush; Anker, Stefan D; Anand, Inder; Linker, David T; Sullivan, Mark D; Cleland, John G F; Carson, Peter E; Maggioni, Aldo P; Mann, Douglas L; Pitt, Bertram; Poole-Wilson, Philip A; Levy, Wayne C

2007-07-24

Prognosis and mode of death in heart failure patients are highly variable in that some patients die suddenly (often from ventricular arrhythmia) and others die of progressive failure of cardiac function (pump failure). Prediction of mode of death may facilitate decisions about specific medications or devices. We used the Seattle Heart Failure Model (SHFM), a validated prediction model for total mortality in heart failure, to assess the mode of death in 10,538 ambulatory patients with New York Heart Association class II to IV heart failure and predominantly systolic dysfunction enrolled in 6 randomized trials or registries. During 16,735 person-years of follow-up, 2014 deaths occurred, which included 1014 sudden deaths and 684 pump-failure deaths. Compared with a SHFM score of 0, patients with a score of 1 had a 50% higher risk of sudden death, patients with a score of 2 had a nearly 3-fold higher risk, and patients with a score of 3 or 4 had a nearly 7-fold higher risk (P<0.001 for all comparisons; 1-year area under the receiver operating curve, 0.68). Stratification of risk of pump-failure death was even more pronounced, with a 4-fold higher risk with a score of 1, a 15-fold higher risk with a score of 2, a 38-fold higher risk with a score of 3, and an 88-fold higher risk with a score of 4 (P<0.001 for all comparisons; 1-year area under the receiver operating curve, 0.85). The proportion of deaths caused by sudden death versus pump-failure death decreased from a ratio of 7:1 with a SHFM score of 0 to a ratio of 1:2 with a SHFM score of 4 (P trend <0.001). The SHFM score provides information about the likely mode of death among ambulatory heart failure patients. Investigation is warranted to determine whether such information might predict responses to or cost-effectiveness of specific medications or devices in heart failure patients.

Thermal barrier coating life prediction model

NASA Technical Reports Server (NTRS)

Hillery, R. V.; Pilsner, B. H.; Cook, T. S.; Kim, K. S.

1986-01-01

This is the second annual report of the first 3-year phase of a 2-phase, 5-year program. The objectives of the first phase are to determine the predominant modes of degradation of a plasma sprayed thermal barrier coating system and to develop and verify life prediction models accounting for these degradation modes. The primary TBC system consists of an air plasma sprayed ZrO-Y2O3 top coat, a low pressure plasma sprayed NiCrAlY bond coat, and a Rene' 80 substrate. Task I was to evaluate TBC failure mechanisms. Both bond coat oxidation and bond coat creep have been identified as contributors to TBC failure. Key property determinations have also been made for the bond coat and the top coat, including tensile strength, Poisson's ratio, dynamic modulus, and coefficient of thermal expansion. Task II is to develop TBC life prediction models for the predominant failure modes. These models will be developed based on the results of thermmechanical experiments and finite element analysis. The thermomechanical experiments have been defined and testing initiated. Finite element models have also been developed to handle TBCs and are being utilized to evaluate different TBC failure regimes.

NASA Langley developments in response calculations needed for failure and life prediction

NASA Technical Reports Server (NTRS)

Housner, Jerrold M.

1993-01-01

NASA Langley developments in response calculations needed for failure and life predictions are discussed. Topics covered include: structural failure analysis in concurrent engineering; accuracy of independent regional modeling demonstrated on classical example; functional interface method accurately joins incompatible finite element models; interface method for insertion of local detail modeling extended to curve pressurized fuselage window panel; interface concept for joining structural regions; motivation for coupled 2D-3D analysis; compression panel with discontinuous stiffener coupled 2D-3D model and axial surface strains at the middle of the hat stiffener; use of adaptive refinement with multiple methods; adaptive mesh refinement; and studies on quantity effect of bow-type initial imperfections on reliability of stiffened panels.

On the State of Stress and Failure Prediction Near Planetary Surface Loads

NASA Astrophysics Data System (ADS)

Schultz, R. A.

1996-03-01

The state of stress surrounding planetary surface loads has been used extensively to predict failure of surface rocks and to invert this information for effective elastic thickness. As demonstrated previously, however, several factors can be important including an explicit comparison between model stresses and rock strength as well as the magnitude of calculated stress. As re-emphasized below, failure to take stress magnitudes into account can lead to erroneous predictions of near-surface faulting. This abstract results from discussions on graben formation at Fall 1995 AGU.

Modeling the ductile fracture and the plastic anisotropy of DC01 steel at room temperature and low strain rates

NASA Astrophysics Data System (ADS)

Tuninetti, V.; Yuan, S.; Gilles, G.; Guzmán, C. F.; Habraken, A. M.; Duchêne, L.

2016-08-01

This paper presents different extensions of the classical GTN damage model implemented in a finite element code. The goal of this study is to assess these extensions for the numerical prediction of failure of a DC01 steel sheet during a single point incremental forming process, after a proper identification of the material parameters. It is shown that the prediction of failure appears too early compared to experimental results. Though, the use of the Thomason criterion permitted to delay the onset of coalescence and consequently the final failure.

Fracture simulation of restored teeth using a continuum damage mechanics failure model.

PubMed

Li, Haiyan; Li, Jianying; Zou, Zhenmin; Fok, Alex Siu-Lun

2011-07-01

The aim of this paper is to validate the use of a finite-element (FE) based continuum damage mechanics (CDM) failure model to simulate the debonding and fracture of restored teeth. Fracture testing of plastic model teeth, with or without a standard Class-II MOD (mesial-occusal-distal) restoration, was carried out to investigate their fracture behavior. In parallel, 2D FE models of the teeth are constructed and analyzed using the commercial FE software ABAQUS. A CDM failure model, implemented into ABAQUS via the user element subroutine (UEL), is used to simulate the debonding and/or final fracture of the model teeth under a compressive load. The material parameters needed for the CDM model to simulate fracture are obtained through separate mechanical tests. The predicted results are then compared with the experimental data of the fracture tests to validate the failure model. The failure processes of the intact and restored model teeth are successfully reproduced by the simulation. However, the fracture parameters obtained from testing small specimens need to be adjusted to account for the size effect. The results indicate that the CDM model is a viable model for the prediction of debonding and fracture in dental restorations. Copyright © 2011 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Interactive Reliability Model for Whisker-toughened Ceramics

NASA Technical Reports Server (NTRS)

Palko, Joseph L.

1993-01-01

Wider use of ceramic matrix composites (CMC) will require the development of advanced structural analysis technologies. The use of an interactive model to predict the time-independent reliability of a component subjected to multiaxial loads is discussed. The deterministic, three-parameter Willam-Warnke failure criterion serves as the theoretical basis for the reliability model. The strength parameters defining the model are assumed to be random variables, thereby transforming the deterministic failure criterion into a probabilistic criterion. The ability of the model to account for multiaxial stress states with the same unified theory is an improvement over existing models. The new model was coupled with a public-domain finite element program through an integrated design program. This allows a design engineer to predict the probability of failure of a component. A simple structural problem is analyzed using the new model, and the results are compared to existing models.

Predicting Failure Under Laboratory Conditions: Learning the Physics of Slow Frictional Slip and Dynamic Failure

NASA Astrophysics Data System (ADS)

Rouet-Leduc, B.; Hulbert, C.; Riviere, J.; Lubbers, N.; Barros, K.; Marone, C.; Johnson, P. A.

2016-12-01

Forecasting failure is a primary goal in diverse domains that include earthquake physics, materials science, nondestructive evaluation of materials and other engineering applications. Due to the highly complex physics of material failure and limitations on gathering data in the failure nucleation zone, this goal has often appeared out of reach; however, recent advances in instrumentation sensitivity, instrument density and data analysis show promise toward forecasting failure times. Here, we show that we can predict frictional failure times of both slow and fast stick slip failure events in the laboratory. This advance is made possible by applying a machine learning approach known as Random Forests1(RF) to the continuous acoustic emission (AE) time series recorded by detectors located on the fault blocks. The RF is trained using a large number of statistical features derived from the AE time series signal. The model is then applied to data not previously analyzed. Remarkably, we find that the RF method predicts upcoming failure time far in advance of a stick slip event, based only on a short time window of data. Further, the algorithm accurately predicts the time of the beginning and end of the next slip event. The predicted time improves as failure is approached, as other data features add to prediction. Our results show robust predictions of slow and dynamic failure based on acoustic emissions from the fault zone throughout the laboratory seismic cycle. The predictions are based on previously unidentified tremor-like acoustic signals that occur during stress build up and the onset of macroscopic frictional weakening. We suggest that the tremor-like signals carry information about fault zone processes and allow precise predictions of failure at any time in the slow slip or stick slip cycle2. If the laboratory experiments represent Earth frictional conditions, it could well be that signals are being missed that contain highly useful predictive information. 1Breiman, L. Random forests. Machine Learning 45, 5-32 (2001). 2Rouet-Leduc, B. C. Hulbert, N. Lubbers, K. Barros and P. A. Johnson, Learning the physics of failure, in review (2016).

Pilots Rate Augmented Generalized Predictive Control for Reconfiguration

NASA Technical Reports Server (NTRS)

Soloway, Don; Haley, Pam

2004-01-01

The objective of this paper is to report the results from the research being conducted in reconfigurable fight controls at NASA Ames. A study was conducted with three NASA Dryden test pilots to evaluate two approaches of reconfiguring an aircraft's control system when failures occur in the control surfaces and engine. NASA Ames is investigating both a Neural Generalized Predictive Control scheme and a Neural Network based Dynamic Inverse controller. This paper highlights the Predictive Control scheme where a simple augmentation to reduce zero steady-state error led to the neural network predictor model becoming redundant for the task. Instead of using a neural network predictor model, a nominal single point linear model was used and then augmented with an error corrector. This paper shows that the Generalized Predictive Controller and the Dynamic Inverse Neural Network controller perform equally well at reconfiguration, but with less rate requirements from the actuators. Also presented are the pilot ratings for each controller for various failure scenarios and two samples of the required control actuation during reconfiguration. Finally, the paper concludes by stepping through the Generalized Predictive Control's reconfiguration process for an elevator failure.

Predicting the velocity and azimuth of fragments generated by the range destruction or random failure of rocket casings and tankage

NASA Technical Reports Server (NTRS)

Eck, Marshall; Mukunda, Meera

1988-01-01

A calculational method is described which provides a powerful tool for predicting solid rocket motor (SRM) casing and liquid rocket tankage fragmentation response. The approach properly partitions the available impulse to each major system-mass component. It uses the Pisces code developed by Physics International to couple the forces generated by an Eulerian-modeled gas flow field to a Lagrangian-modeled fuel and casing system. The details of the predictive analytical modeling process and the development of normalized relations for momentum partition as a function of SRM burn time and initial geometry are discussed. Methods for applying similar modeling techniques to liquid-tankage-overpressure failures are also discussed. Good agreement between predictions and observations are obtained for five specific events.

Peridynamics for failure and residual strength prediction of fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Colavito, Kyle

Peridynamics is a reformulation of classical continuum mechanics that utilizes integral equations in place of partial differential equations to remove the difficulty in handling discontinuities, such as cracks or interfaces, within a body. Damage is included within the constitutive model; initiation and propagation can occur without resorting to special crack growth criteria necessary in other commonly utilized approaches. Predicting damage and residual strengths of composite materials involves capturing complex, distinct and progressive failure modes. The peridynamic laminate theory correctly predicts the load redistribution in general laminate layups in the presence of complex failure modes through the use of multiple interaction types. This study presents two approaches to obtain the critical peridynamic failure parameters necessary to capture the residual strength of a composite structure. The validity of both approaches is first demonstrated by considering the residual strength of isotropic materials. The peridynamic theory is used to predict the crack growth and final failure load in both a diagonally loaded square plate with a center crack, as well as a four-point shear specimen subjected to asymmetric loading. This study also establishes the validity of each approach by considering composite laminate specimens in which each failure mode is isolated. Finally, the failure loads and final failure modes are predicted in a laminate with various hole diameters subjected to tensile and compressive loads.

Analysis of Discrete-Source Damage Progression in a Tensile Stiffened Composite Panel

NASA Technical Reports Server (NTRS)

Wang, John T.; Lotts, Christine G.; Sleight, David W.

1999-01-01

This paper demonstrates the progressive failure analysis capability in NASA Langley s COMET-AR finite element analysis code on a large-scale built-up composite structure. A large-scale five stringer composite panel with a 7-in. long discrete source damage was analyzed from initial loading to final failure including the geometric and material nonlinearities. Predictions using different mesh sizes, different saw cut modeling approaches, and different failure criteria were performed and assessed. All failure predictions have a reasonably good correlation with the test result.

Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2002-01-01

NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.

Identifying black swans in NextGen: predicting human performance in off-nominal conditions.

PubMed

Wickens, Christopher D; Hooey, Becky L; Gore, Brian F; Sebok, Angelia; Koenicke, Corey S

2009-10-01

The objective is to validate a computational model of visual attention against empirical data--derived from a meta-analysis--of pilots' failure to notice safety-critical unexpected events. Many aircraft accidents have resulted, in part, because of failure to notice nonsalient unexpected events outside of foveal vision, illustrating the phenomenon of change blindness. A model of visual noticing, N-SEEV (noticing-salience, expectancy, effort, and value), was developed to predict these failures. First, 25 studies that reported objective data on miss rate for unexpected events in high-fidelity cockpit simulations were identified, and their miss rate data pooled across five variables (phase of flight, event expectancy, event location, presence of a head-up display, and presence of a highway-in-the-sky display). Second, the parameters of the N-SEEV model were tailored to mimic these dichotomies. The N-SEEV model output predicted variance in the obtained miss rate (r = .73). The individual miss rates of all six dichotomous conditions were predicted within 14%, and four of these were predicted within 7%. The N-SEEV model, developed on the basis of an independent data set, was able to successfully predict variance in this safety-critical measure of pilot response to abnormal circumstances, as collected from the literature. As new technology and procedures are envisioned for the future airspace, it is important to predict if these may compromise safety in terms of pilots' failing to notice unexpected events. Computational models such as N-SEEV support cost-effective means of making such predictions.

Simple Predictive Model of Early Failure among Patients Undergoing First-Time Arteriovenous Fistula Creation.

PubMed

Eslami, Mohammad H; Zhu, Clara K; Rybin, Denis; Doros, Gheorghe; Siracuse, Jeffrey J; Farber, Alik

2016-08-01

Native arteriovenous fistulas (AVFs) have a high 1 year failure rate leading to a need for secondary procedures. We set out to create a predictive model of early failure in patients undergoing first-time AVF creation, to identify failure-associated factors and stratify initial failure risk. The Vascular Study Group of New England (VSGNE) (2010-2014) was queried to identify patients undergoing first-time AVF creation. Patients with early (within 3 months postoperation) AVF failure (EF) or no failure (NF) were compared, failure being defined as any AVF that could not be used for dialysis. A multivariate logistic regression predictive model of EF based on perioperative clinical variables was created. Backward elimination with alpha level of 0.2 was used to create a parsimonious model. We identified 376 first-time AVF patients with follow-up data available in VSGNE. EF rate was 17.5%. Patients in the EF group had lower rates of hypertension (80.3% vs. 93.2%, P = 0.003) and diabetes (47.0% vs. 61.3%, P = 0.039). EF patients were also more likely to have radial artery inflow (57.6% vs. 38.4%, P = 0.011) and have forearm cephalic vein outflow (57.6% vs. 36.5%, P = 0.008). Additionally, the EF group was noted to have significantly smaller mean diameters of target artery (3.1 ± 0.9 vs. 3.6 ± 1.1, P = 0.002) and vein (3.1 ± 0.7 vs. 3.6 ± 0.9, P < 0.001). Multivariate analyses revealed that hypertension, diabetes, and vein larger than 3 mm were protective of EF (P < 0.05). The discriminating ability of this model was good (C-statistic = 0.731) and the model fits the data well (Hosmer-Lemeshow P = 0.149). β-estimates of significant factors were used to create a point system and assign probabilities of EF. We developed a simple model that robustly predicts first-time AVF EF and suggests that anatomical and clinical factors directly affect early AVF outcomes. The risk score has the potential to be used in clinical settings to stratify risk and make informed follow-up plans for AVF patients. Copyright © 2016 Elsevier Inc. All rights reserved.

Narrowing the scope of failure prediction using targeted fault load injection

NASA Astrophysics Data System (ADS)

Jordan, Paul L.; Peterson, Gilbert L.; Lin, Alan C.; Mendenhall, Michael J.; Sellers, Andrew J.

2018-05-01

As society becomes more dependent upon computer systems to perform increasingly critical tasks, ensuring that those systems do not fail becomes increasingly important. Many organizations depend heavily on desktop computers for day-to-day operations. Unfortunately, the software that runs on these computers is written by humans and, as such, is still subject to human error and consequent failure. A natural solution is to use statistical machine learning to predict failure. However, since failure is still a relatively rare event, obtaining labelled training data to train these models is not a trivial task. This work presents new simulated fault-inducing loads that extend the focus of traditional fault injection techniques to predict failure in the Microsoft enterprise authentication service and Apache web server. These new fault loads were successful in creating failure conditions that were identifiable using statistical learning methods, with fewer irrelevant faults being created.

Modeling Dynamic Anisotropic Behaviour and Spall Failure in Commercial Aluminium Alloys AA7010

NASA Astrophysics Data System (ADS)

Mohd Nor, M. K.; Ma'at, N.; Ho, C. S.

2018-04-01

This paper presents a finite strain constitutive model to predict a complex elastoplastic deformation behaviour involves very high pressures and shockwaves in orthotropic materials of aluminium alloys. The previous published constitutive model is used as a reference to start the development in this work. The proposed formulation that used a new definition of Mandel stress tensor to define Hill's yield criterion and a new shock equation of state (EOS) of the generalised orthotropic pressure is further enhanced with Grady spall failure model to closely predict shockwave propagation and spall failure in the chosen commercial aluminium alloy. This hyperelastic-plastic constitutive model is implemented as a new material model in the Lawrence Livermore National Laboratory (LLNL)-DYNA3D code of UTHM's version, named Material Type 92 (Mat92). The implementations of a new EOS of the generalised orthotropic pressure including the spall failure are also discussed in this paper. The capability of the proposed constitutive model to capture the complex behaviour of the selected material is validated against range of Plate Impact Test data at 234, 450 and 895 ms-1 impact velocities.

Immunohistochemical and molecular imaging biomarker signature for the prediction of failure site after chemoradiation for head and neck squamous cell carcinoma.

PubMed

Rasmussen, Gregers Brünnich; Håkansson, Katrin E; Vogelius, Ivan R; Rasmussen, Jacob H; Friborg, Jeppe T; Fischer, Barbara M; Schumaker, Lisa; Cullen, Kevin; Therkildsen, Marianne H; Bentzen, Søren M; Specht, Lena

2017-11-01

To identify a failure site-specific prognostic model by combining immunohistochemistry (IHC) and molecular imaging information to predict long-term failure type in squamous cell carcinoma of the head and neck. Tissue microarray blocks of 196 head and neck squamous cell carcinoma cases were stained for a panel of biomarkers using IHC. Gross tumor volume (GTV) from the PET/CT radiation treatment planning CT scan, maximal Standard Uptake Value (SUVmax) of fludeoxyglucose (FDG) and clinical information were included in the model building using Cox proportional hazards models, stratified for p16 status in oropharyngeal carcinomas. Separate models were built for time to locoregional failure and time to distant metastasis. Higher than median p53 expression on IHC tended toward a risk factor for locoregional failure but was protective for distant metastasis, χ 2 for difference p = .003. The final model for locoregional failure included p53 (HR: 1.9; p: .055), concomitant cisplatin (HR: 0.41; p: .008), β-tubulin-1 (HR: 1.8; p: .08), β-tubulin-2 (HR: 0.49; p: .057) and SUVmax (HR: 2.1; p: .046). The final model for distant metastasis included p53 (HR: 0.23; p: .025), Bcl-2 (HR: 2.6; p: .08), SUVmax (HR: 3.5; p: .095) and GTV (HR: 1.7; p: .063). The models successfully distinguished between risk of locoregional failure and risk of distant metastasis, which is important information for clinical decision-making. High p53 expression has opposite prognostic effects for the two endpoints; increasing risk of locoregional failure, but decreasing the risk of metastatic failure, but external validation of this finding is needed.

Simulating Initial and Progressive Failure of Open-Hole Composite Laminates under Tension

NASA Astrophysics Data System (ADS)

Guo, Zhangxin; Zhu, Hao; Li, Yongcun; Han, Xiaoping; Wang, Zhihua

2016-12-01

A finite element (FE) model is developed for the progressive failure analysis of fiber reinforced polymer laminates. The failure criterion for fiber and matrix failure is implemented in the FE code Abaqus using user-defined material subroutine UMAT. The gradual degradation of the material properties is controlled by the individual fracture energies of fiber and matrix. The failure and damage in composite laminates containing a central hole subjected to uniaxial tension are simulated. The numerical results show that the damage model can be used to accurately predicte the progressive failure behaviour both qualitatively and quantitatively.

Development of an Electronic Medical Record Based Alert for Risk of HIV Treatment Failure in a Low-Resource Setting

PubMed Central

Puttkammer, Nancy; Zeliadt, Steven; Balan, Jean Gabriel; Baseman, Janet; Destiné, Rodney; Domerçant, Jean Wysler; France, Garilus; Hyppolite, Nathaelf; Pelletier, Valérie; Raphael, Nernst Atwood; Sherr, Kenneth; Yuhas, Krista; Barnhart, Scott

2014-01-01

Background The adoption of electronic medical record systems in resource-limited settings can help clinicians monitor patients' adherence to HIV antiretroviral therapy (ART) and identify patients at risk of future ART failure, allowing resources to be targeted to those most at risk. Methods Among adult patients enrolled on ART from 2005–2013 at two large, public-sector hospitals in Haiti, ART failure was assessed after 6–12 months on treatment, based on the World Health Organization's immunologic and clinical criteria. We identified models for predicting ART failure based on ART adherence measures and other patient characteristics. We assessed performance of candidate models using area under the receiver operating curve, and validated results using a randomly-split data sample. The selected prediction model was used to generate a risk score, and its ability to differentiate ART failure risk over a 42-month follow-up period was tested using stratified Kaplan Meier survival curves. Results Among 923 patients with CD4 results available during the period 6–12 months after ART initiation, 196 (21.2%) met ART failure criteria. The pharmacy-based proportion of days covered (PDC) measure performed best among five possible ART adherence measures at predicting ART failure. Average PDC during the first 6 months on ART was 79.0% among cases of ART failure and 88.6% among cases of non-failure (p<0.01). When additional information including sex, baseline CD4, and duration of enrollment in HIV care prior to ART initiation were added to PDC, the risk score differentiated between those who did and did not meet failure criteria over 42 months following ART initiation. Conclusions Pharmacy data are most useful for new ART adherence alerts within iSanté. Such alerts offer potential to help clinicians identify patients at high risk of ART failure so that they can be targeted with adherence support interventions, before ART failure occurs. PMID:25390044

Development of an electronic medical record based alert for risk of HIV treatment failure in a low-resource setting.

PubMed

Puttkammer, Nancy; Zeliadt, Steven; Balan, Jean Gabriel; Baseman, Janet; Destiné, Rodney; Domerçant, Jean Wysler; France, Garilus; Hyppolite, Nathaelf; Pelletier, Valérie; Raphael, Nernst Atwood; Sherr, Kenneth; Yuhas, Krista; Barnhart, Scott

2014-01-01

The adoption of electronic medical record systems in resource-limited settings can help clinicians monitor patients' adherence to HIV antiretroviral therapy (ART) and identify patients at risk of future ART failure, allowing resources to be targeted to those most at risk. Among adult patients enrolled on ART from 2005-2013 at two large, public-sector hospitals in Haiti, ART failure was assessed after 6-12 months on treatment, based on the World Health Organization's immunologic and clinical criteria. We identified models for predicting ART failure based on ART adherence measures and other patient characteristics. We assessed performance of candidate models using area under the receiver operating curve, and validated results using a randomly-split data sample. The selected prediction model was used to generate a risk score, and its ability to differentiate ART failure risk over a 42-month follow-up period was tested using stratified Kaplan Meier survival curves. Among 923 patients with CD4 results available during the period 6-12 months after ART initiation, 196 (21.2%) met ART failure criteria. The pharmacy-based proportion of days covered (PDC) measure performed best among five possible ART adherence measures at predicting ART failure. Average PDC during the first 6 months on ART was 79.0% among cases of ART failure and 88.6% among cases of non-failure (p<0.01). When additional information including sex, baseline CD4, and duration of enrollment in HIV care prior to ART initiation were added to PDC, the risk score differentiated between those who did and did not meet failure criteria over 42 months following ART initiation. Pharmacy data are most useful for new ART adherence alerts within iSanté. Such alerts offer potential to help clinicians identify patients at high risk of ART failure so that they can be targeted with adherence support interventions, before ART failure occurs.

Dam-Break Flooding and Structural Damage in a Residential Neighborhood: Performance of a coupled hydrodynamic-damage model

NASA Astrophysics Data System (ADS)

Sanders, B. F.; Gallegos, H. A.; Schubert, J. E.

2011-12-01

The Baldwin Hills dam-break flood and associated structural damage is investigated in this study. The flood caused high velocity flows exceeding 5 m/s which destroyed 41 wood-framed residential structures, 16 of which were completed washed out. Damage is predicted by coupling a calibrated hydrodynamic flood model based on the shallow-water equations to structural damage models. The hydrodynamic and damage models are two-way coupled so building failure is predicted upon exceedance of a hydraulic intensity parameter, which in turn triggers a localized reduction in flow resistance which affects flood intensity predictions. Several established damage models and damage correlations reported in the literature are tested to evaluate the predictive skill for two damage states defined by destruction (Level 2) and washout (Level 3). Results show that high-velocity structural damage can be predicted with a remarkable level of skill using established damage models, but only with two-way coupling of the hydrodynamic and damage models. In contrast, when structural failure predictions have no influence on flow predictions, there is a significant reduction in predictive skill. Force-based damage models compare well with a subset of the damage models which were devised for similar types of structures. Implications for emergency planning and preparedness as well as monetary damage estimation are discussed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lall, Pradeep; Wei, Junchao; Sakalaukus, Peter

A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminousmore » flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.« less

GenSo-EWS: a novel neural-fuzzy based early warning system for predicting bank failures.

PubMed

Tung, W L; Quek, C; Cheng, P

2004-05-01

Bank failure prediction is an important issue for the regulators of the banking industries. The collapse and failure of a bank could trigger an adverse financial repercussion and generate negative impacts such as a massive bail out cost for the failing bank and loss of confidence from the investors and depositors. Very often, bank failures are due to financial distress. Hence, it is desirable to have an early warning system (EWS) that identifies potential bank failure or high-risk banks through the traits of financial distress. Various traditional statistical models have been employed to study bank failures [J Finance 1 (1975) 21; J Banking Finance 1 (1977) 249; J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073]. However, these models do not have the capability to identify the characteristics of financial distress and thus function as black boxes. This paper proposes the use of a new neural fuzzy system [Foundations of neuro-fuzzy systems, 1997], namely the Generic Self-organising Fuzzy Neural Network (GenSoFNN) [IEEE Trans Neural Networks 13 (2002c) 1075] based on the compositional rule of inference (CRI) [Commun ACM 37 (1975) 77], as an alternative to predict banking failure. The CRI based GenSoFNN neural fuzzy network, henceforth denoted as GenSoFNN-CRI(S), functions as an EWS and is able to identify the inherent traits of financial distress based on financial covariates (features) derived from publicly available financial statements. The interaction between the selected features is captured in the form of highly intuitive IF-THEN fuzzy rules. Such easily comprehensible rules provide insights into the possible characteristics of financial distress and form the knowledge base for a highly desired EWS that aids bank regulation. The performance of the GenSoFNN-CRI(S) network is subsequently benchmarked against that of the Cox's proportional hazards model [J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073], the multi-layered perceptron (MLP) and the modified cerebellar model articulation controller (MCMAC) [IEEE Trans Syst Man Cybern: Part B 30 (2000) 491] in predicting bank failures based on a population of 3635 US banks observed over a 21 years period. Three sets of experiments are performed-bank failure classification based on the last available financial record and prediction using financial records one and two years prior to the last available financial statements. The performance of the GenSoFNN-CRI(S) network as a bank failure classification and EWS is encouraging.

A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite

NASA Astrophysics Data System (ADS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-05-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.

A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite

NASA Technical Reports Server (NTRS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-01-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.

The role of microstructure and phase distribution in the failure mechanisms and life prediction model for PSZ coatings

NASA Technical Reports Server (NTRS)

Sisson, R. D., Jr.; Sone, Ichiro; Biederman, R. R.

1985-01-01

Partially Stabilized Zirconia (PSZ) may become widely used for Thermal Barrier Coatings (TBC). Failure of these coatings can occur due to thermal fatigue in oxidizing atmospheres. The failure is due to the strains that develop due to thermal gradients, differences in thermal expansion coefficients, and oxidation of the bond coating. The role of microstructure and the cubic, tetragonal, and monoclinic phase distribution in the strain development and subsequent failure will be discussed. An X-ray diffraction technique for accurate determination of the fraction of each phase in PSZ will be applied to understanding the phase transformations and strain development. These results will be discussed in terms of developing a model for life prediction in PSZ coatings during thermal cycling.

Scale effects in the response and failure of fiber reinforced composite laminates loaded in tension and in flexure

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Kellas, Sotiris; Morton, John

1992-01-01

The feasibility of using scale model testing for predicting the full-scale behavior of flat composite coupons loaded in tension and beam-columns loaded in flexure is examined. Classical laws of similitude are applied to fabricate and test replica model specimens to identify scaling effects in the load response, strength, and mode of failure. Experiments were performed on graphite-epoxy composite specimens having different laminate stacking sequences and a range of scaled sizes. From the experiments it was deduced that the elastic response of scaled composite specimens was independent of size. However, a significant scale effect in strength was observed. In addition, a transition in failure mode was observed among scaled specimens of certain laminate stacking sequences. A Weibull statistical model and a fracture mechanics based model were applied to predict the strength scale effect since standard failure criteria cannot account for the influence of absolute specimen size on strength.

The use of subjective expert opinions in cost optimum design of aerospace structures. [probabilistic failure models

NASA Technical Reports Server (NTRS)

Thomas, J. M.; Hanagud, S.

1975-01-01

The results of two questionnaires sent to engineering experts are statistically analyzed and compared with objective data from Saturn V design and testing. Engineers were asked how likely it was for structural failure to occur at load increments above and below analysts' stress limit predictions. They were requested to estimate the relative probabilities of different failure causes, and of failure at each load increment given a specific cause. Three mathematical models are constructed based on the experts' assessment of causes. The experts' overall assessment of prediction strength fits the Saturn V data better than the models do, but a model test option (T-3) based on the overall assessment gives more design change likelihood to overstrength structures than does an older standard test option. T-3 compares unfavorably with the standard option in a cost optimum structural design problem. The report reflects a need for subjective data when objective data are unavailable.

Application of Interface Technology in Progressive Failure Analysis of Composite Panels

NASA Technical Reports Server (NTRS)

Sleight, D. W.; Lotts, C. G.

2002-01-01

A progressive failure analysis capability using interface technology is presented. The capability has been implemented in the COMET-AR finite element analysis code developed at the NASA Langley Research Center and is demonstrated on composite panels. The composite panels are analyzed for damage initiation and propagation from initial loading to final failure using a progressive failure analysis capability that includes both geometric and material nonlinearities. Progressive failure analyses are performed on conventional models and interface technology models of the composite panels. Analytical results and the computational effort of the analyses are compared for the conventional models and interface technology models. The analytical results predicted with the interface technology models are in good correlation with the analytical results using the conventional models, while significantly reducing the computational effort.

Experimental verification of a progressive damage model for composite laminates based on continuum damage mechanics. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Coats, Timothy William

1994-01-01

Progressive failure is a crucial concern when using laminated composites in structural design. Therefore the ability to model damage and predict the life of laminated composites is vital. The purpose of this research was to experimentally verify the application of the continuum damage model, a progressive failure theory utilizing continuum damage mechanics, to a toughened material system. Damage due to tension-tension fatigue was documented for the IM7/5260 composite laminates. Crack density and delamination surface area were used to calculate matrix cracking and delamination internal state variables, respectively, to predict stiffness loss. A damage dependent finite element code qualitatively predicted trends in transverse matrix cracking, axial splits and local stress-strain distributions for notched quasi-isotropic laminates. The predictions were similar to the experimental data and it was concluded that the continuum damage model provided a good prediction of stiffness loss while qualitatively predicting damage growth in notched laminates.

A unified bond theory, probabilistic meso-scale modeling, and experimental validation of deformed steel rebar in normal strength concrete

NASA Astrophysics Data System (ADS)

Wu, Chenglin

Bond between deformed rebar and concrete is affected by rebar deformation pattern, concrete properties, concrete confinement, and rebar-concrete interfacial properties. Two distinct groups of bond models were traditionally developed based on the dominant effects of concrete splitting and near-interface shear-off failures. Their accuracy highly depended upon the test data sets selected in analysis and calibration. In this study, a unified bond model is proposed and developed based on an analogy to the indentation problem around the rib front of deformed rebar. This mechanics-based model can take into account the combined effect of concrete splitting and interface shear-off failures, resulting in average bond strengths for all practical scenarios. To understand the fracture process associated with bond failure, a probabilistic meso-scale model of concrete is proposed and its sensitivity to interface and confinement strengths are investigated. Both the mechanical and finite element models are validated with the available test data sets and are superior to existing models in prediction of average bond strength (< 6% error) and crack spacing (< 6% error). The validated bond model is applied to derive various interrelations among concrete crushing, concrete splitting, interfacial behavior, and the rib spacing-to-height ratio of deformed rebar. It can accurately predict the transition of failure modes from concrete splitting to rebar pullout and predict the effect of rebar surface characteristics as the rib spacing-to-height ratio increases. Based on the unified theory, a global bond model is proposed and developed by introducing bond-slip laws, and validated with testing of concrete beams with spliced reinforcement, achieving a load capacity prediction error of less than 26%. The optimal rebar parameters and concrete cover in structural designs can be derived from this study.

Spatio-temporal propagation of cascading overload failures in spatially embedded networks

NASA Astrophysics Data System (ADS)

Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

2016-01-01

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems.

Spatio-temporal propagation of cascading overload failures in spatially embedded networks

PubMed Central

Zhao, Jichang; Li, Daqing; Sanhedrai, Hillel; Cohen, Reuven; Havlin, Shlomo

2016-01-01

Different from the direct contact in epidemics spread, overload failures propagate through hidden functional dependencies. Many studies focused on the critical conditions and catastrophic consequences of cascading failures. However, to understand the network vulnerability and mitigate the cascading overload failures, the knowledge of how the failures propagate in time and space is essential but still missing. Here we study the spatio-temporal propagation behaviour of cascading overload failures analytically and numerically on spatially embedded networks. The cascading overload failures are found to spread radially from the centre of the initial failure with an approximately constant velocity. The propagation velocity decreases with increasing tolerance, and can be well predicted by our theoretical framework with one single correction for all the tolerance values. This propagation velocity is found similar in various model networks and real network structures. Our findings may help to predict the dynamics of cascading overload failures in realistic systems. PMID:26754065

Heterogeneity: The key to forecasting material failure?

NASA Astrophysics Data System (ADS)

Vasseur, J.; Wadsworth, F. B.; Lavallée, Y.; Dingwell, D. B.

2014-12-01

Empirical mechanistic models have been applied to the description of the stress and strain rate upon failure for heterogeneous materials. The behaviour of porous rocks and their analogous two-phase viscoelastic suspensions are particularly well-described by such models. Nevertheless, failure cannot yet be predicted forcing a reliance on other empirical prediction tools such as the Failure Forecast Method (FFM). Measurable, accelerating rates of physical signals (e.g., seismicity and deformation) preceding failure are often used as proxies for damage accumulation in the FFM. Previous studies have already statistically assessed the applicability and performance of the FFM, but none (to the best of our knowledge) has done so in terms of intrinsic material properties. Here we use a rheological standard glass, which has been powdered and then sintered for different times (up to 32 hours) at high temperature (675°C) in order to achieve a sample suite with porosities in the range of 0.10-0.45 gas volume fraction. This sample suite was then subjected to mechanical tests in a uniaxial press at a constant strain rate of 10-3 s-1 and a temperature in the region of the glass transition. A dual acoustic emission (AE) rig has been employed to test the success of the FFM in these materials of systematically varying porosity. The pore-emanating crack model describes well the peak stress at failure in the elastic regime for these materials. We show that the FFM predicts failure within 0-15% error at porosities >0.2. However, when porosities are <0.2, the forecast error associated with predicting the failure time increases to >100%. We interpret these results as a function of the low efficiency with which strain energy can be released in the scenario where there are few or no heterogeneities from which cracks can propagate. These observations shed light on questions surrounding the variable efficacy of the FFM applied to active volcanoes. In particular, they provide a systematic demonstration of the fact that a good understanding of the material properties is required. Thus, we wish to emphasize the need for a better coupling of empirical failure forecasting models with mechanical parameters, such as failure criteria for heterogeneous materials, and point to the implications of this for a broad range of material-based disciplines.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daniel, Isaac M.

To facilitate and accelerate the process of introducing, evaluating and adopting of new material systems, it is important to develop/establish comprehensive and effective procedures of characterization, modeling and failure prediction of structural laminates based on the properties of the constituent materials, e. g., fibers, matrix, and the single ply or lamina. A new failure theory, the Northwestern (NU-Daniel) theory, has been proposed for predicting lamina yielding and failure under multi-axial states of stress including strain rate effects. It is primarily applicable to matrix-dominated interfiber/interlaminar failures. It is based on micromechanical failure mechanisms but is expressed in terms of easily measuredmore » macroscopic lamina stiffness and strength properties. It is presented in the form of a master failure envelope incorporating strain rate effects. The theory was further adapted and extended to the prediction of in situ first ply yielding and failure (FPY and FPF) and progressive failure of multi-directional laminates under static and dynamic loadings. The significance of this theory is that it allows for rapid screening of new composite materials without very extensive testing and offers easily implemented design tools.« less

Simulations of the modified gap experiment

NASA Astrophysics Data System (ADS)

Sutherland, Gerrit T.; Benjamin, Richard; Kooker, Douglas

2017-01-01

Modified gap experiment (test) hydrocode simulations predict the trends seen in experimental excess free surface velocity versus input pressure curves for explosives with both large and modest failure diameters. Simulations were conducted for explosive "A", an explosive with a large failure diameter, and for cast TNT, which has a modest failure diameter. Using the best available reactive rate models, the simulations predicted sustained ignition thresholds similar to experiment. This is a threshold where detonation is likely given a long enough run distance. For input pressures greater than the sustained ignition threshold pressure, the simulations predicted too little velocity for explosive "A" and too much velocity for TNT. It was found that a better comparison of experiment and simulation requires additional experimental data for both explosives. It was observed that the choice of reactive rate model for cast TNT can lead to large differences in the predicted modified gap experiment result. The cause of the difference is that the same data was not used to parameterize both models; one set of data was more shock reactive than the other.

Accuracy of Seattle Heart Failure Model and HeartMate II Risk Score in Non-Inotrope-Dependent Advanced Heart Failure Patients: Insights From the ROADMAP Study (Risk Assessment and Comparative Effectiveness of Left Ventricular Assist Device and Medical Management in Ambulatory Heart Failure Patients).

PubMed

Lanfear, David E; Levy, Wayne C; Stehlik, Josef; Estep, Jerry D; Rogers, Joseph G; Shah, Keyur B; Boyle, Andrew J; Chuang, Joyce; Farrar, David J; Starling, Randall C

2017-05-01

Timing of left ventricular assist device (LVAD) implantation in advanced heart failure patients not on inotropes is unclear. Relevant prediction models exist (SHFM [Seattle Heart Failure Model] and HMRS [HeartMate II Risk Score]), but use in this group is not established. ROADMAP (Risk Assessment and Comparative Effectiveness of Left Ventricular Assist Device and Medical Management in Ambulatory Heart Failure Patients) is a prospective, multicenter, nonrandomized study of 200 advanced heart failure patients not on inotropes who met indications for LVAD implantation, comparing the effectiveness of HeartMate II support versus optimal medical management. We compared SHFM-predicted versus observed survival (overall survival and LVAD-free survival) in the optimal medical management arm (n=103) and HMRS-predicted versus observed survival in all LVAD patients (n=111) using Cox modeling, receiver-operator characteristic (ROC) curves, and calibration plots. In the optimal medical management cohort, the SHFM was a significant predictor of survival (hazard ratio=2.98; P <0.001; ROC area under the curve=0.71; P <0.001) but not LVAD-free survival (hazard ratio=1.41; P =0.097; ROC area under the curve=0.56; P =0.314). SHFM showed adequate calibration for survival but overestimated LVAD-free survival. In the LVAD cohort, the HMRS had marginal discrimination at 3 (Cox P =0.23; ROC area under the curve=0.71; P =0.026) and 12 months (Cox P =0.036; ROC area under the curve=0.62; P =0.122), but calibration was poor, underestimating survival across time and risk subgroups. In non-inotrope-dependent advanced heart failure patients receiving optimal medical management, the SHFM was predictive of overall survival but underestimated the risk of clinical worsening and LVAD implantation. Among LVAD patients, the HMRS had marginal discrimination and underestimated survival post-LVAD implantation. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01452802. © 2017 American Heart Association, Inc.

Handbook of Analytical Methods for Textile Composites

NASA Technical Reports Server (NTRS)

Cox, Brian N.; Flanagan, Gerry

1997-01-01

The purpose of this handbook is to introduce models and computer codes for predicting the properties of textile composites. The handbook includes several models for predicting the stress-strain response all the way to ultimate failure; methods for assessing work of fracture and notch sensitivity; and design rules for avoiding certain critical mechanisms of failure, such as delamination, by proper textile design. The following textiles received some treatment: 2D woven, braided, and knitted/stitched laminates and 3D interlock weaves, and braids.

A model for predicting high-temperature fatigue failure of a W/Cu composite

NASA Technical Reports Server (NTRS)

Verrilli, M. J.; Kim, Y.-S.; Gabb, T. P.

1991-01-01

The material studied, a tungsten-fiber-reinforced, copper-matrix composite, is a candidate material for rocket nozzle liner applications. It was shown that at high temperatures, fatigue cracks initiate and propagate inside the copper matrix through a process of initiation, growth, and coalescence of grain boundary cavities. The ductile tungsten fibers neck and rupture locally after the surrounding matrix fails, and complete failure of the composite then ensues. A simple fatigue life prediction model is presented for the tungsten/copper composite system.

N-terminal fraction of pro-B-type natriuretic peptide versus clinical risk scores for prognostic stratification in chronic systolic heart failure.

PubMed

Arzilli, Chiara; Aimo, Alberto; Vergaro, Giuseppe; Ripoli, Andrea; Senni, Michele; Emdin, Michele; Passino, Claudio

2018-05-01

Background The Seattle heart failure model or the cardiac and comorbid conditions (3C-HF) scores may help define patient risk in heart failure. Direct comparisons between them or versus N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP) have never been performed. Methods Data from consecutive patients with stable systolic heart failure and 3C-HF data were examined. A subgroup of patients had the Seattle heart failure model data available. The endpoints were one year all-cause or cardiovascular death. Results The population included 2023 patients, aged 68 ± 12 years, 75% were men. At the one year time-point, 198 deaths were recorded (10%), 124 of them (63%) from cardiovascular causes. While areas under the curve were not significantly different, NT-proBNP displayed better reclassification capability than the 3C-HF score for the prediction of one year all-cause and cardiovascular death. Adding NT-proBNP to the 3C-HF score resulted in a significant improvement in risk prediction. Among patients with Seattle heart failure model data available ( n = 798), the area under the curve values for all-cause and cardiovascular death were similar for the Seattle heart failure model score (0.790 and 0.820), NT-proBNP (0.783 and 0.803), and the 3C-HF score (0.770 and 0.800). The combination of the 3C-HF score and NT-proBNP displayed a similar prognostic performance to the Seattle heart failure model score for both endpoints. Adding NT-proBNP to the Seattle heart failure model score performed better than the Seattle heart failure model alone in terms of reclassification, but not discrimination. Conclusions Among systolic heart failure patients, NT-proBNP levels had better reclassification capability for all-cause and cardiovascular death than the 3C-HF score. The inclusion of NT-proBNP to the 3C-HF and Seattle heart failure model score resulted in significantly better risk stratification.

A Progressive Damage Methodology for Residual Strength Predictions of Center-Crack Tension Composite Panels

NASA Technical Reports Server (NTRS)

Coats, Timothy William

1996-01-01

An investigation of translaminate fracture and a progressive damage methodology was conducted to evaluate and develop a residual strength prediction capability for laminated composites with through penetration notches. This is relevant to the damage tolerance of an aircraft fuselage that might suffer an in-flight accident such as an uncontained engine failure. An experimental characterization of several composite materials systems revealed an R-curve type of behavior. Fractographic examinations led to the postulate that this crack growth resistance could be due to fiber bridging, defined here as fractured fibers of one ply bridged by intact fibers of an adjacent ply. The progressive damage methodology is currently capable of predicting the initiation and growth of matrix cracks and fiber fracture. Using two difference fiber failure criteria, residual strength was predicted for different size panel widths and notch lengths. A ply discount fiber failure criterion yielded extremely conservative results while an elastic-perfectly plastic fiber failure criterion showed that the fiber bridging concept is valid for predicting residual strength for tensile dominated failure loads. Furthermore, the R-curves predicted by the model using the elastic-perfectly plastic fiber criterion compared very well with the experimental R-curves.

An elastic failure model of indentation damage. [of brittle structural ceramics

NASA Technical Reports Server (NTRS)

Liaw, B. M.; Kobayashi, A. S.; Emery, A. F.

1984-01-01

A mechanistically consistent model for indentation damage based on elastic failure at tensile or shear overloads, is proposed. The model accommodates arbitrary crack orientation, stress relaxation, reduction and recovery of stiffness due to crack opening and closure, and interfacial friction due to backward sliding of closed cracks. This elastic failure model was implemented by an axisymmetric finite element program which was used to simulate progressive damage in a silicon nitride plate indented by a tungsten carbide sphere. The predicted damage patterns and the permanent impression matched those observed experimentally. The validation of this elastic failure model shows that the plastic deformation postulated by others is not necessary to replicate the indentation damage of brittle structural ceramics.

Dual Pathways from Reactive Aggression to Depressive Symptoms in Children: Further Examination of the Failure Model.

PubMed

Evans, Spencer C; Fite, Paula J

2018-04-13

The failure model posits that peer rejection and poor academic performance are dual pathways in the association between early aggressive behavior and subsequent depressive symptoms. We examined this model using an accelerated longitudinal design while also incorporating proactive and reactive aggression and gender moderation. Children in 1st, 3rd, and 5th grades (n = 912; ages 6-12; 48% female) were rated three times annually by their primary teachers on measures of proactive and reactive aggression, peer rejection, academic performance, and depressive symptoms. Using Bayesian cross-classified estimation to account for nested and planned-missing data, path models were estimated to examine whether early reactive aggression predicted subsequent peer rejection and academic performance, and whether these, in turn, predicted subsequent depressive symptoms. From 1st to 3rd grade, reactive aggression predicted peer rejection (not academic performance), proactive aggression predicted academic performance (not peer rejection), and academic performance and peer rejection both predicted depressive symptoms. From 3rd to 5th grade, however, neither peer rejection nor academic performance predicted subsequent depressive symptoms. Results were not moderated by gender. Overall, these findings provide mixed and limited support for the failure model among school-age children. Early reactive aggression may be a key risk factor for social problems, whereas proactive aggression may be linked to improved academic functioning. The "dual pathways" of peer rejection and academic performance may operate during early but not later elementary school. Limitations and implications are discussed.

Enhanced stability of steep channel beds to mass failure and debris flow initiation

NASA Astrophysics Data System (ADS)

Prancevic, J.; Lamb, M. P.; Ayoub, F.; Venditti, J. G.

2015-12-01

Debris flows dominate bedrock erosion and sediment transport in very steep mountain channels, and are often initiated from failure of channel-bed alluvium during storms. While several theoretical models exist to predict mass failures, few have been tested because observations of in-channel bed failures are extremely limited. To fill this gap in our understanding, we performed laboratory flume experiments to identify the conditions necessary to initiate bed failures in non-cohesive sediment of different sizes (D = 0.7 mm to 15 mm) on steep channel-bed slopes (S = 0.45 to 0.93) and in the presence of water flow. In beds composed of sand, failures occurred under sub-saturated conditions on steep bed slopes (S > 0.5) and under super-saturated conditions at lower slopes. In beds of gravel, however, failures occurred only under super-saturated conditions at all tested slopes, even those approaching the dry angle of repose. Consistent with theoretical models, mass failures under super-saturated conditions initiated along a failure plane approximately one grain-diameter below the bed surface, whereas the failure plane was located near the base of the bed under sub-saturated conditions. However, all experimental beds were more stable than predicted by 1-D infinite-slope stability models. In partially saturated sand, enhanced stability appears to result from suction stress. Enhanced stability in gravel may result from turbulent energy losses in pores or increased granular friction for failures that are shallow with respect to grain size. These grain-size dependent effects are not currently included in stability models for non-cohesive sediment, and they may help to explain better the timing and location of debris flow occurrence.

The Use of Probabilistic Methods to Evaluate the Systems Impact of Component Design Improvements on Large Turbofan Engines

NASA Technical Reports Server (NTRS)

Packard, Michael H.

2002-01-01

Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.

Individual prediction of heart failure among childhood cancer survivors.

PubMed

Chow, Eric J; Chen, Yan; Kremer, Leontien C; Breslow, Norman E; Hudson, Melissa M; Armstrong, Gregory T; Border, William L; Feijen, Elizabeth A M; Green, Daniel M; Meacham, Lillian R; Meeske, Kathleen A; Mulrooney, Daniel A; Ness, Kirsten K; Oeffinger, Kevin C; Sklar, Charles A; Stovall, Marilyn; van der Pal, Helena J; Weathers, Rita E; Robison, Leslie L; Yasui, Yutaka

2015-02-10

To create clinically useful models that incorporate readily available demographic and cancer treatment characteristics to predict individual risk of heart failure among 5-year survivors of childhood cancer. Survivors in the Childhood Cancer Survivor Study (CCSS) free of significant cardiovascular disease 5 years after cancer diagnosis (n = 13,060) were observed through age 40 years for the development of heart failure (ie, requiring medications or heart transplantation or leading to death). Siblings (n = 4,023) established the baseline population risk. An additional 3,421 survivors from Emma Children's Hospital (Amsterdam, the Netherlands), the National Wilms Tumor Study, and the St Jude Lifetime Cohort Study were used to validate the CCSS prediction models. Heart failure occurred in 285 CCSS participants. Risk scores based on selected exposures (sex, age at cancer diagnosis, and anthracycline and chest radiotherapy doses) achieved an area under the curve of 0.74 and concordance statistic of 0.76 at or through age 40 years. Validation cohort estimates ranged from 0.68 to 0.82. Risk scores were collapsed to form statistically distinct low-, moderate-, and high-risk groups, corresponding to cumulative incidences of heart failure at age 40 years of 0.5% (95% CI, 0.2% to 0.8%), 2.4% (95% CI, 1.8% to 3.0%), and 11.7% (95% CI, 8.8% to 14.5%), respectively. In comparison, siblings had a cumulative incidence of 0.3% (95% CI, 0.1% to 0.5%). Using information available to clinicians soon after completion of childhood cancer therapy, individual risk for subsequent heart failure can be predicted with reasonable accuracy and discrimination. These validated models provide a framework on which to base future screening strategies and interventions. © 2014 by American Society of Clinical Oncology.

Prediction of line failure fault based on weighted fuzzy dynamic clustering and improved relational analysis

NASA Astrophysics Data System (ADS)

Meng, Xiaocheng; Che, Renfei; Gao, Shi; He, Juntao

2018-04-01

With the advent of large data age, power system research has entered a new stage. At present, the main application of large data in the power system is the early warning analysis of the power equipment, that is, by collecting the relevant historical fault data information, the system security is improved by predicting the early warning and failure rate of different kinds of equipment under certain relational factors. In this paper, a method of line failure rate warning is proposed. Firstly, fuzzy dynamic clustering is carried out based on the collected historical information. Considering the imbalance between the attributes, the coefficient of variation is given to the corresponding weights. And then use the weighted fuzzy clustering to deal with the data more effectively. Then, by analyzing the basic idea and basic properties of the relational analysis model theory, the gray relational model is improved by combining the slope and the Deng model. And the incremental composition and composition of the two sequences are also considered to the gray relational model to obtain the gray relational degree between the various samples. The failure rate is predicted according to the principle of weighting. Finally, the concrete process is expounded by an example, and the validity and superiority of the proposed method are verified.

Progressive Damage Modeling of Durable Bonded Joint Technology

NASA Technical Reports Server (NTRS)

Leone, Frank A.; Davila, Carlos G.; Lin, Shih-Yung; Smeltzer, Stan; Girolamo, Donato; Ghose, Sayata; Guzman, Juan C.; McCarville, Duglas A.

2013-01-01

The development of durable bonded joint technology for assembling composite structures for launch vehicles is being pursued for the U.S. Space Launch System. The present work is related to the development and application of progressive damage modeling techniques to bonded joint technology applicable to a wide range of sandwich structures for a Heavy Lift Launch Vehicle. The joint designs studied in this work include a conventional composite splice joint and a NASA-patented Durable Redundant Joint. Both designs involve a honeycomb sandwich with carbon/epoxy facesheets joined with adhesively bonded doublers. Progressive damage modeling allows for the prediction of the initiation and evolution of damage. For structures that include multiple materials, the number of potential failure mechanisms that must be considered increases the complexity of the analyses. Potential failure mechanisms include fiber fracture, matrix cracking, delamination, core crushing, adhesive failure, and their interactions. The joints were modeled using Abaqus parametric finite element models, in which damage was modeled with user-written subroutines. Each ply was meshed discretely, and layers of cohesive elements were used to account for delaminations and to model the adhesive layers. Good correlation with experimental results was achieved both in terms of load-displacement history and predicted failure mechanisms.

Fatigue of notched fiber composite laminates. Part 1: Analytical model

NASA Technical Reports Server (NTRS)

Mclaughlin, P. V., Jr.; Kulkarni, S. V.; Huang, S. N.; Rosen, B. W.

1975-01-01

A description is given of a semi-empirical, deterministic analysis for prediction and correlation of fatigue crack growth, residual strength, and fatigue lifetime for fiber composite laminates containing notches (holes). The failure model used for the analysis is based upon composite heterogeneous behavior and experimentally observed failure modes under both static and fatigue loading. The analysis is consistent with the wearout philosophy. Axial cracking and transverse cracking failure modes are treated together in the analysis. Cracking off-axis is handled by making a modification to the axial cracking analysis. The analysis predicts notched laminate failure from unidirectional material fatique properties using constant strain laminate analysis techniques. For multidirectional laminates, it is necessary to know lamina fatique behavior under axial normal stress, transverse normal stress and axial shear stress. Examples of the analysis method are given.

Yield and failure criteria for composite materials under static and dynamic loading

DOE PAGES

Daniel, Isaac M.

2015-12-23

To facilitate and accelerate the process of introducing, evaluating and adopting of new material systems, it is important to develop/establish comprehensive and effective procedures of characterization, modeling and failure prediction of structural laminates based on the properties of the constituent materials, e. g., fibers, matrix, and the single ply or lamina. A new failure theory, the Northwestern (NU-Daniel) theory, has been proposed for predicting lamina yielding and failure under multi-axial states of stress including strain rate effects. It is primarily applicable to matrix-dominated interfiber/interlaminar failures. It is based on micromechanical failure mechanisms but is expressed in terms of easily measuredmore » macroscopic lamina stiffness and strength properties. It is presented in the form of a master failure envelope incorporating strain rate effects. The theory was further adapted and extended to the prediction of in situ first ply yielding and failure (FPY and FPF) and progressive failure of multi-directional laminates under static and dynamic loadings. The significance of this theory is that it allows for rapid screening of new composite materials without very extensive testing and offers easily implemented design tools.« less

Risk Prediction Models of Locoregional Failure After Radical Cystectomy for Urothelial Carcinoma: External Validation in a Cohort of Korean Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ku, Ja Hyeon; Kim, Myong; Jeong, Chang Wook

2014-08-01

Purpose: To evaluate the predictive accuracy and general applicability of the locoregional failure model in a different cohort of patients treated with radical cystectomy. Methods and Materials: A total of 398 patients were included in the analysis. Death and isolated distant metastasis were considered competing events, and patients without any events were censored at the time of last follow-up. The model included the 3 variables pT classification, the number of lymph nodes identified, and margin status, as follows: low risk (≤pT2), intermediate risk (≥pT3 with ≥10 nodes removed and negative margins), and high risk (≥pT3 with <10 nodes removed ormore » positive margins). Results: The bootstrap-corrected concordance index of the model 5 years after radical cystectomy was 66.2%. When the risk stratification was applied to the validation cohort, the 5-year locoregional failure estimates were 8.3%, 21.2%, and 46.3% for the low-risk, intermediate-risk, and high-risk groups, respectively. The risk of locoregional failure differed significantly between the low-risk and intermediate-risk groups (subhazard ratio [SHR], 2.63; 95% confidence interval [CI], 1.35-5.11; P<.001) and between the low-risk and high-risk groups (SHR, 4.28; 95% CI, 2.17-8.45; P<.001). Although decision curves were appropriately affected by the incidence of the competing risk, decisions about the value of the models are not likely to be affected because the model remains of value over a wide range of threshold probabilities. Conclusions: The model is not completely accurate, but it demonstrates a modest level of discrimination, adequate calibration, and meaningful net benefit gain for prediction of locoregional failure after radical cystectomy.« less

Predicting the mechanical behaviour of Kevlar/epoxy and carbon/epoxy filament-wound tubes

NASA Astrophysics Data System (ADS)

Cazeneuve, C.; Joguet, P.; Maile, J. C.; Oytana, C.

1992-11-01

The axial, hoop and shear moduli and failure conditions of carbon/epoxy and Kevlar/epoxy filament-wound tubes have been determined through respective applications of internal pressure, tension and torsion. The introduction in the laminated plate theory of a gradual reduction in individual moduli makes it possible to overcome the limitations of the theory and enables accurate predictions to be made of the linear and non-linear stress/strain curves of 90 deg +/- 0/90 deg tubes. The existence of a dominant layer in the failure of the multilayered tubes has been shown experimentally. When associated with a failure criterion applied to the dominant layer, the new model permits the prediction of tube failure. Agreement between calculated and experimental data is better than 5 percent.

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 1: Methodology and applications

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

Finite element based damage assessment of composite tidal turbine blades

NASA Astrophysics Data System (ADS)

Fagan, Edward M.; Leen, Sean B.; Kennedy, Ciaran R.; Goggins, Jamie

2015-07-01

With significant interest growing in the ocean renewables sector, horizontal axis tidal current turbines are in a position to dominate the marketplace. The test devices that have been placed in operation so far have suffered from premature failures, caused by difficulties with structural strength prediction. The goal of this work is to develop methods of predicting the damage level in tidal turbines under their maximum operating tidal velocity. The analysis was conducted using the finite element software package Abaqus; shell models of three representative tidal turbine blades are produced. Different construction methods will affect the damage level in the blade and for this study models were developed with varying hydrofoil profiles. In order to determine the risk of failure, a user material subroutine (UMAT) was created. The UMAT uses the failure criteria designed by Alfred Puck to calculate the risk of fibre and inter-fibre failure in the blades. The results show that degradation of the stiffness is predicted for the operating conditions, having an effect on the overall tip deflection. The failure criteria applied via the UMAT form a useful tool for analysis of high risk regions within the blade designs investigated.

DEPEND - A design environment for prediction and evaluation of system dependability

NASA Technical Reports Server (NTRS)

Goswami, Kumar K.; Iyer, Ravishankar K.

1990-01-01

The development of DEPEND, an integrated simulation environment for the design and dependability analysis of fault-tolerant systems, is described. DEPEND models both hardware and software components at a functional level, and allows automatic failure injection to assess system performance and reliability. It relieves the user of the work needed to inject failures, maintain statistics, and output reports. The automatic failure injection scheme is geared toward evaluating a system under high stress (workload) conditions. The failures that are injected can affect both hardware and software components. To illustrate the capability of the simulator, a distributed system which employs a prediction-based, dynamic load-balancing heuristic is evaluated. Experiments were conducted to determine the impact of failures on system performance and to identify the failures to which the system is especially susceptible.

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

NASA Astrophysics Data System (ADS)

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.

Analytical Modelling of Transverse Matrix Cracking of [plus or minus Theta/90(sub n)](sub s) Composite Laminates Under Multiaxial Loading

NASA Technical Reports Server (NTRS)

Mayugo, J A.; Camanho, P. P.; Maimi, P.; Davila, C. G.

2010-01-01

An analytical model based on the analysis of a cracked unit cell of a composite laminate subjected to multiaxial loads is proposed to predict the onset and accumulation of transverse matrix cracks in the 90(sub n) plies of uniformly stressed [plus or minus Theta/90(sub n)](sub s) laminates. The model predicts the effect of matrix cracks on the stiffness of the laminate, as well as the ultimate failure of the laminate, and it accounts for the effect of the ply thickness on the ply strength. Several examples describing the predictions of laminate response, from damage onset up to final failure under both uniaxial and multiaxial loads, are presented.

A probabilisitic based failure model for components fabricated from anisotropic graphite

NASA Astrophysics Data System (ADS)

Xiao, Chengfeng

The nuclear moderator for high temperature nuclear reactors are fabricated from graphite. During reactor operations graphite components are subjected to complex stress states arising from structural loads, thermal gradients, neutron irradiation damage, and seismic events. Graphite is a quasi-brittle material. Two aspects of nuclear grade graphite, i.e., material anisotropy and different behavior in tension and compression, are explicitly accounted for in this effort. Fracture mechanic methods are useful for metal alloys, but they are problematic for anisotropic materials with a microstructure that makes it difficult to identify a "critical" flaw. In fact cracking in a graphite core component does not necessarily result in the loss of integrity of a nuclear graphite core assembly. A phenomenological failure criterion that does not rely on flaw detection has been derived that accounts for the material behaviors mentioned. The probability of failure of components fabricated from graphite is governed by the scatter in strength. The design protocols being proposed by international code agencies recognize that design and analysis of reactor core components must be based upon probabilistic principles. The reliability models proposed herein for isotropic graphite and graphite that can be characterized as being transversely isotropic are another set of design tools for the next generation very high temperature reactors (VHTR) as well as molten salt reactors. The work begins with a review of phenomenologically based deterministic failure criteria. A number of this genre of failure models are compared with recent multiaxial nuclear grade failure data. Aspects in each are shown to be lacking. The basic behavior of different failure strengths in tension and compression is exhibited by failure models derived for concrete, but attempts to extend these concrete models to anisotropy were unsuccessful. The phenomenological models are directly dependent on stress invariants. A set of invariants, known as an integrity basis, was developed for a non-linear elastic constitutive model. This integrity basis allowed the non-linear constitutive model to exhibit different behavior in tension and compression and moreover, the integrity basis was amenable to being augmented and extended to anisotropic behavior. This integrity basis served as the starting point in developing both an isotropic reliability model and a reliability model for transversely isotropic materials. At the heart of the reliability models is a failure function very similar in nature to the yield functions found in classic plasticity theory. The failure function is derived and presented in the context of a multiaxial stress space. States of stress inside the failure envelope denote safe operating states. States of stress on or outside the failure envelope denote failure. The phenomenological strength parameters associated with the failure function are treated as random variables. There is a wealth of failure data in the literature that supports this notion. The mathematical integration of a joint probability density function that is dependent on the random strength variables over the safe operating domain defined by the failure function provides a way to compute the reliability of a state of stress in a graphite core component fabricated from graphite. The evaluation of the integral providing the reliability associated with an operational stress state can only be carried out using a numerical method. Monte Carlo simulation with importance sampling was selected to make these calculations. The derivation of the isotropic reliability model and the extension of the reliability model to anisotropy are provided in full detail. Model parameters are cast in terms of strength parameters that can (and have been) characterized by multiaxial failure tests. Comparisons of model predictions with failure data is made and a brief comparison is made to reliability predictions called for in the ASME Boiler and Pressure Vessel Code. Future work is identified that would provide further verification and augmentation of the numerical methods used to evaluate model predictions.

An Experimental Investigation into Failure and Localization Phenomena in the Extension to Shear Fracture Transition in Rock

NASA Astrophysics Data System (ADS)

Choens, R. C., II; Chester, F. M.; Bauer, S. J.; Flint, G. M.

2014-12-01

Fluid-pressure assisted fracturing can produce mesh and other large, interconnected and complex networks consisting of both extension and shear fractures in various metamorphic, magmatic and tectonic systems. Presently, rock failure criteria for tensile and low-mean compressive stress conditions is poorly defined, although there is accumulating evidence that the transition from extension to shear fracture with increasing mean stress is continuous. We report on the results of experiments designed to document failure criteria, fracture mode, and localization phenomena for several rock types (sandstone, limestone, chalk and marble). Experiments were conducted in triaxial extension using a necked (dogbone) geometry to achieve mixed tension and compression stress states with local component-strain measurements in the failure region. The failure envelope for all rock types is similar, but are poorly described using Griffith or modified Griffith (Coulomb or other) failure criteria. Notably, the mode of fracture changes systematically from pure extension to shear with increase in compressive mean stress and display a continuous change in fracture orientation with respect to principal stress axes. Differential stress and inelastic strain show a systematic increase with increasing mean stress, whereas the axial stress decreases before increasing with increasing mean stress. The stress and strain data are used to analyze elastic and plastic strains leading to failure and compare the experimental results to predictions for localization using constitutive models incorporating on bifurcation theory. Although models are able to describe the stability behavior and onset of localization qualitatively, the models are unable to predict fracture type or orientation. Constitutive models using single or multiple yield surfaces are unable to predict the experimental results, reflecting the difficulty in capturing the changing micromechanisms from extension to shear failure. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Deopartment of Energy's National Security Administration under contract DE-AC04-94AL85000. SAND2014-16578A

Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

NASA Astrophysics Data System (ADS)

Tavakoli, M. M.; Assadian, N.

2018-03-01

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.

Analysis of Machine Learning Techniques for Heart Failure Readmissions.

PubMed

Mortazavi, Bobak J; Downing, Nicholas S; Bucholz, Emily M; Dharmarajan, Kumar; Manhapra, Ajay; Li, Shu-Xia; Negahban, Sahand N; Krumholz, Harlan M

2016-11-01

The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates. © 2016 American Heart Association, Inc.

Modeling Progressive Damage Using Local Displacement Discontinuities Within the FEAMAC Multiscale Modeling Framework

NASA Technical Reports Server (NTRS)

Ranatunga, Vipul; Bednarcyk, Brett A.; Arnold, Steven M.

2010-01-01

A method for performing progressive damage modeling in composite materials and structures based on continuum level interfacial displacement discontinuities is presented. The proposed method enables the exponential evolution of the interfacial compliance, resulting in unloading of the tractions at the interface after delamination or failure occurs. In this paper, the proposed continuum displacement discontinuity model has been used to simulate failure within both isotropic and orthotropic materials efficiently and to explore the possibility of predicting the crack path, therein. Simulation results obtained from Mode-I and Mode-II fracture compare the proposed approach with the cohesive element approach and Virtual Crack Closure Techniques (VCCT) available within the ABAQUS (ABAQUS, Inc.) finite element software. Furthermore, an eccentrically loaded 3-point bend test has been simulated with the displacement discontinuity model, and the resulting crack path prediction has been compared with a prediction based on the extended finite element model (XFEM) approach.

Development of a calibrated software reliability model for flight and supporting ground software for avionic systems

NASA Technical Reports Server (NTRS)

Lawrence, Stella

1991-01-01

The object of this project was to develop and calibrate quantitative models for predicting the quality of software. Reliable flight and supporting ground software is a highly important factor in the successful operation of the space shuttle program. The models used in the present study consisted of SMERFS (Statistical Modeling and Estimation of Reliability Functions for Software). There are ten models in SMERFS. For a first run, the results obtained in modeling the cumulative number of failures versus execution time showed fairly good results for our data. Plots of cumulative software failures versus calendar weeks were made and the model results were compared with the historical data on the same graph. If the model agrees with actual historical behavior for a set of data then there is confidence in future predictions for this data. Considering the quality of the data, the models have given some significant results, even at this early stage. With better care in data collection, data analysis, recording of the fixing of failures and CPU execution times, the models should prove extremely helpful in making predictions regarding the future pattern of failures, including an estimate of the number of errors remaining in the software and the additional testing time required for the software quality to reach acceptable levels. It appears that there is no one 'best' model for all cases. It is for this reason that the aim of this project was to test several models. One of the recommendations resulting from this study is that great care must be taken in the collection of data. When using a model, the data should satisfy the model assumptions.

Progressive Damage Analysis of Bonded Composite Joints

NASA Technical Reports Server (NTRS)

Leone, Frank A., Jr.; Girolamo, Donato; Davila, Carlos G.

2012-01-01

The present work is related to the development and application of progressive damage modeling techniques to bonded joint technology. The joint designs studied in this work include a conventional composite splice joint and a NASA-patented durable redundant joint. Both designs involve honeycomb sandwich structures with carbon/epoxy facesheets joined using adhesively bonded doublers.Progressive damage modeling allows for the prediction of the initiation and evolution of damage within a structure. For structures that include multiple material systems, such as the joint designs under consideration, the number of potential failure mechanisms that must be accounted for drastically increases the complexity of the analyses. Potential failure mechanisms include fiber fracture, intraply matrix cracking, delamination, core crushing, adhesive failure, and their interactions. The bonded joints were modeled using highly parametric, explicitly solved finite element models, with damage modeling implemented via custom user-written subroutines. Each ply was discretely meshed using three-dimensional solid elements. Layers of cohesive elements were included between each ply to account for the possibility of delaminations and were used to model the adhesive layers forming the joint. Good correlation with experimental results was achieved both in terms of load-displacement history and the predicted failure mechanism(s).

In Search of Black Swans: Identifying Students at Risk of Failing Licensing Examinations.

PubMed

Barber, Cassandra; Hammond, Robert; Gula, Lorne; Tithecott, Gary; Chahine, Saad

2018-03-01

To determine which admissions variables and curricular outcomes are predictive of being at risk of failing the Medical Council of Canada Qualifying Examination Part 1 (MCCQE1), how quickly student risk of failure can be predicted, and to what extent predictive modeling is possible and accurate in estimating future student risk. Data from five graduating cohorts (2011-2015), Schulich School of Medicine & Dentistry, Western University, were collected and analyzed using hierarchical generalized linear models (HGLMs). Area under the receiver operating characteristic curve (AUC) was used to evaluate the accuracy of predictive models and determine whether they could be used to predict future risk, using the 2016 graduating cohort. Four predictive models were developed to predict student risk of failure at admissions, year 1, year 2, and pre-MCCQE1. The HGLM analyses identified gender, MCAT verbal reasoning score, two preclerkship course mean grades, and the year 4 summative objective structured clinical examination score as significant predictors of student risk. The predictive accuracy of the models varied. The pre-MCCQE1 model was the most accurate at predicting a student's risk of failing (AUC 0.66-0.93), while the admissions model was not predictive (AUC 0.25-0.47). Key variables predictive of students at risk were found. The predictive models developed suggest, while it is not possible to identify student risk at admission, we can begin to identify and monitor students within the first year. Using such models, programs may be able to identify and monitor students at risk quantitatively and develop tailored intervention strategies.

Development and validation of a 10-year-old child ligamentous cervical spine finite element model.

PubMed

Dong, Liqiang; Li, Guangyao; Mao, Haojie; Marek, Stanley; Yang, King H

2013-12-01

Although a number of finite element (FE) adult cervical spine models have been developed to understand the injury mechanisms of the neck in automotive related crash scenarios, there have been fewer efforts to develop a child neck model. In this study, a 10-year-old ligamentous cervical spine FE model was developed for application in the improvement of pediatric safety related to motor vehicle crashes. The model geometry was obtained from medical scans and meshed using a multi-block approach. Appropriate properties based on review of literature in conjunction with scaling were assigned to different parts of the model. Child tensile force-deformation data in three segments, Occipital-C2 (C0-C2), C4-C5 and C6-C7, were used to validate the cervical spine model and predict failure forces and displacements. Design of computer experiments was performed to determine failure properties for intervertebral discs and ligaments needed to set up the FE model. The model-predicted ultimate displacements and forces were within the experimental range. The cervical spine FE model was validated in flexion and extension against the child experimental data in three segments, C0-C2, C4-C5 and C6-C7. Other model predictions were found to be consistent with the experimental responses scaled from adult data. The whole cervical spine model was also validated in tension, flexion and extension against the child experimental data. This study provided methods for developing a child ligamentous cervical spine FE model and to predict soft tissue failures in tension.

Nonparametric method for failures diagnosis in the actuating subsystem of aircraft control system

NASA Astrophysics Data System (ADS)

Terentev, M. N.; Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures diagnosis in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on analytical nonparametric one-step-ahead state prediction approach. This makes it possible to predict the behavior of unidentified and failure dynamic systems, to weaken the requirements to control signals, and to reduce the diagnostic time and problem complexity.

Viscoelastic behavior and life-time predictions

NASA Technical Reports Server (NTRS)

Dillard, D. A.; Brinson, H. F.

1985-01-01

Fiber reinforced plastics were considered for many structural applications in automotive, aerospace and other industries. A major concern was and remains the failure modes associated with the polymer matrix which serves to bind the fibers together and transfer the load through connections, from fiber to fiber and ply to ply. An accelerated characterization procedure for prediction of delayed failures was developed. This method utilizes time-temperature-stress-moisture superposition principles in conjunction with laminated plate theory. Because failures are inherently nonlinear, the testing and analytic modeling for both moduli and strength is based upon nonlinear viscoelastic concepts.

The EST Model for Predicting Progressive Damage and Failure of Open Hole Bending Specimens

NASA Technical Reports Server (NTRS)

Joseph, Ashith P. K.; Waas, Anthony M.; Pineda, Evan J.

2016-01-01

Progressive damage and failure in open hole composite laminate coupons subjected to flexural loading is modeled using Enhanced Schapery Theory (EST). Previous studies have demonstrated that EST can accurately predict the strength of open hole coupons under remote tensile and compressive loading states. This homogenized modeling approach uses single composite shell elements to represent the entire laminate in the thickness direction and significantly reduces computational cost. Therefore, when delaminations are not of concern or are active in the post-peak regime, the version of EST presented here is a good engineering tool for predicting deformation response. Standard coupon level tests provides all the input data needed for the model and they are interpreted in conjunction with finite element (FE) based simulations. Open hole bending test results of three different IM7/8552 carbon fiber composite layups agree well with EST predictions. The model is able to accurately capture the curvature change and deformation localization in the specimen at and during the post catastrophic load drop event.

Failure analysis of thick composite cylinders under external pressure

NASA Technical Reports Server (NTRS)

Caiazzo, A.; Rosen, B. W.

1992-01-01

Failure of thick section composites due to local compression strength and overall structural instability is treated. Effects of material nonlinearity, imperfect fiber architecture, and structural imperfections upon anticipated failure stresses are determined. Comparisons with experimental data for a series of test cylinders are described. Predicting the failure strength of composite structures requires consideration of stability and material strength modes of failure using linear and nonlinear analysis techniques. Material strength prediction requires the accurate definition of the local multiaxial stress state in the material. An elasticity solution for the linear static analysis of thick anisotropic cylinders and rings is used herein to predict the axisymmetric stress state in the cylinders. Asymmetric nonlinear behavior due to initial cylinder out of roundness and the effects of end closure structure are treated using finite element methods. It is assumed that local fiber or ply waviness is an important factor in the initiation of material failure. An analytical model for the prediction of compression failure of fiber composites, which includes the effects of fiber misalignments, matrix inelasticity, and multiaxial applied stresses is used for material strength calculations. Analytical results are compared to experimental data for a series of glass and carbon fiber reinforced epoxy cylinders subjected to external pressure. Recommendations for pretest characterization and other experimental issues are presented. Implications for material and structural design are discussed.

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

NASA Technical Reports Server (NTRS)

Hatfield, Glen S.; Hark, Frank; Stott, James

2016-01-01

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Prediction of Composite Pressure Vessel Failure Location using Fiber Bragg Grating Sensors

NASA Technical Reports Server (NTRS)

Kreger, Steven T.; Taylor, F. Tad; Ortyl, Nicholas E.; Grant, Joseph

2006-01-01

Ten composite pressure vessels were instrumented with fiber Bragg grating sensors in order to assess the strain levels of the vessel under various loading conditions. This paper and presentation will discuss the testing methodology, the test results, compare the testing results to the analytical model, and present a possible methodology for predicting the failure location and strain level of composite pressure vessels.

Modelling Wind Turbine Failures based on Weather Conditions

NASA Astrophysics Data System (ADS)

Reder, Maik; Melero, Julio J.

2017-11-01

A large proportion of the overall costs of a wind farm is directly related to operation and maintenance (O&M) tasks. By applying predictive O&M strategies rather than corrective approaches these costs can be decreased significantly. Here, especially wind turbine (WT) failure models can help to understand the components’ degradation processes and enable the operators to anticipate upcoming failures. Usually, these models are based on the age of the systems or components. However, latest research shows that the on-site weather conditions also affect the turbine failure behaviour significantly. This study presents a novel approach to model WT failures based on the environmental conditions to which they are exposed to. The results focus on general WT failures, as well as on four main components: gearbox, generator, pitch and yaw system. A penalised likelihood estimation is used in order to avoid problems due to for example highly correlated input covariates. The relative importance of the model covariates is assessed in order to analyse the effect of each weather parameter on the model output.

Evaluation of critical nuclear power plant electrical cable response to severe thermal fire conditions

NASA Astrophysics Data System (ADS)

Taylor, Gabriel James

The failure of electrical cables exposed to severe thermal fire conditions are a safety concern for operating commercial nuclear power plants (NPPs). The Nuclear Regulatory Commission (NRC) has promoted the use of risk-informed and performance-based methods for fire protection which resulted in a need to develop realistic methods to quantify the risk of fire to NPP safety. Recent electrical cable testing has been conducted to provide empirical data on the failure modes and likelihood of fire-induced damage. This thesis evaluated numerous aspects of the data. Circuit characteristics affecting fire-induced electrical cable failure modes have been evaluated. In addition, thermal failure temperatures corresponding to cable functional failures have been evaluated to develop realistic single point thermal failure thresholds and probability distributions for specific cable insulation types. Finally, the data was used to evaluate the prediction capabilities of a one-dimension conductive heat transfer model used to predict cable failure.

Unit-Sphere Multiaxial Stochastic-Strength Model Applied to Anisotropic and Composite Materials

NASA Technical Reports Server (NTRS)

Nemeth, Noel, N.

2013-01-01

Models that predict the failure probability of brittle materials under multiaxial loading have been developed by authors such as Batdorf, Evans, and Matsuo. These "unit-sphere" models assume that the strength-controlling flaws are randomly oriented, noninteracting planar microcracks of specified geometry but of variable size. This methodology has been extended to predict the multiaxial strength response of transversely isotropic brittle materials, including polymer matrix composites (PMCs), by considering (1) flaw-orientation anisotropy, whereby a preexisting microcrack has a higher likelihood of being oriented in one direction over another direction, and (2) critical strength, or K (sub Ic) orientation anisotropy, whereby the level of critical strength or fracture toughness for mode I crack propagation, K (sub Ic), changes with regard to the orientation of the microstructure. In this report, results from finite element analysis of a fiber-reinforced-matrix unit cell were used with the unit-sphere model to predict the biaxial strength response of a unidirectional PMC previously reported from the World-Wide Failure Exercise. Results for nuclear-grade graphite materials under biaxial loading are also shown for comparison. This effort was successful in predicting the multiaxial strength response for the chosen problems. Findings regarding stress-state interactions and failure modes also are provided.

Experimental and Numerical Analysis of Triaxially Braided Composites Utilizing a Modified Subcell Modeling Approach

NASA Technical Reports Server (NTRS)

Cater, Christopher; Xiao, Xinran; Goldberg, Robert K.; Kohlman, Lee W.

2015-01-01

A combined experimental and analytical approach was performed for characterizing and modeling triaxially braided composites with a modified subcell modeling strategy. Tensile coupon tests were conducted on a [0deg/60deg/-60deg] braided composite at angles of 0deg, 30deg, 45deg, 60deg and 90deg relative to the axial tow of the braid. It was found that measured coupon strength varied significantly with the angle of the applied load and each coupon direction exhibited unique final failures. The subcell modeling approach implemented into the finite element software LS-DYNA was used to simulate the various tensile coupon test angles. The modeling approach was successful in predicting both the coupon strength and reported failure mode for the 0deg, 30deg and 60deg loading directions. The model over-predicted the strength in the 90deg direction; however, the experimental results show a strong influence of free edge effects on damage initiation and failure. In the absence of these local free edge effects, the subcell modeling approach showed promise as a viable and computationally efficient analysis tool for triaxially braided composite structures. Future work will focus on validation of the approach for predicting the impact response of the braided composite against flat panel impact tests.

Experimental and Numerical Analysis of Triaxially Braided Composites Utilizing a Modified Subcell Modeling Approach

NASA Technical Reports Server (NTRS)

Cater, Christopher; Xiao, Xinran; Goldberg, Robert K.; Kohlman, Lee W.

2015-01-01

A combined experimental and analytical approach was performed for characterizing and modeling triaxially braided composites with a modified subcell modeling strategy. Tensile coupon tests were conducted on a [0deg/60deg/-60deg] braided composite at angles [0deg, 30deg, 45deg, 60deg and 90deg] relative to the axial tow of the braid. It was found that measured coupon strength varied significantly with the angle of the applied load and each coupon direction exhibited unique final failures. The subcell modeling approach implemented into the finite element software LS-DYNA was used to simulate the various tensile coupon test angles. The modeling approach was successful in predicting both the coupon strength and reported failure mode for the 0deg, 30deg and 60deg loading directions. The model over-predicted the strength in the 90deg direction; however, the experimental results show a strong influence of free edge effects on damage initiation and failure. In the absence of these local free edge effects, the subcell modeling approach showed promise as a viable and computationally efficient analysis tool for triaxially braided composite structures. Future work will focus on validation of the approach for predicting the impact response of the braided composite against flat panel impact tests.

Thermal barrier coating life prediction model development

NASA Technical Reports Server (NTRS)

Demasi, J. T.

1986-01-01

A methodology is established to predict thermal barrier coating life in a environment similar to that experienced by gas turbine airfoils. Experiments were conducted to determine failure modes of the thermal barrier coating. Analytical studies were employed to derive a life prediction model. A review of experimental and flight service components as well as laboratory post evaluations indicates that the predominant mode of TBC failure involves thermomechanical spallation of the ceramic coating layer. This ceramic spallation involves the formation of a dominant crack in the ceramic coating parallel to and closely adjacent to the topologically complex metal ceramic interface. This mechanical failure mode clearly is influenced by thermal exposure effects as shown in experiments conducted to study thermal pre-exposure and thermal cycle-rate effects. The preliminary life prediction model developed focuses on the two major damage modes identified in the critical experiments tasks. The first of these involves a mechanical driving force, resulting from cyclic strains and stresses caused by thermally induced and externally imposed mechanical loads. The second is an environmental driving force based on experimental results, and is believed to be related to bond coat oxidation. It is also believed that the growth of this oxide scale influences the intensity of the mechanical driving force.

Scoring annual earthquake predictions in China

NASA Astrophysics Data System (ADS)

Zhuang, Jiancang; Jiang, Changsheng

2012-02-01

The Annual Consultation Meeting on Earthquake Tendency in China is held by the China Earthquake Administration (CEA) in order to provide one-year earthquake predictions over most China. In these predictions, regions of concern are denoted together with the corresponding magnitude range of the largest earthquake expected during the next year. Evaluating the performance of these earthquake predictions is rather difficult, especially for regions that are of no concern, because they are made on arbitrary regions with flexible magnitude ranges. In the present study, the gambling score is used to evaluate the performance of these earthquake predictions. Based on a reference model, this scoring method rewards successful predictions and penalizes failures according to the risk (probability of being failure) that the predictors have taken. Using the Poisson model, which is spatially inhomogeneous and temporally stationary, with the Gutenberg-Richter law for earthquake magnitudes as the reference model, we evaluate the CEA predictions based on 1) a partial score for evaluating whether issuing the alarmed regions is based on information that differs from the reference model (knowledge of average seismicity level) and 2) a complete score that evaluates whether the overall performance of the prediction is better than the reference model. The predictions made by the Annual Consultation Meetings on Earthquake Tendency from 1990 to 2003 are found to include significant precursory information, but the overall performance is close to that of the reference model.

Antithrombin III is associated with acute liver failure in patients with end-stage heart failure undergoing mechanical circulatory support.

PubMed

Hoefer, Judith; Ulmer, Hanno; Kilo, Juliane; Margreiter, Raimund; Grimm, Michael; Mair, Peter; Ruttmann, Elfriede

2017-06-01

There are few data on the role of liver dysfunction in patients with end-stage heart failure supported by mechanical circulatory support. The aim of our study was to investigate predictors for acute liver failure in patients with end-stage heart failure undergoing mechanical circulatory support. A consecutive 164 patients with heart failure with New York Heart Association class IV undergoing mechanical circulatory support were investigated for acute liver failure using the King's College criteria. Clinical characteristics of heart failure together with hemodynamic and laboratory values were analyzed by logistic regression. A total of 45 patients (27.4%) with heart failure developed subsequent acute liver failure with a hospital mortality of 88.9%. Duration of heart failure, cause, cardiopulmonary resuscitation, use of vasopressors, central venous pressure, pulmonary capillary wedge pressure, pulmonary pulsatility index, cardiac index, and transaminases were not significantly associated with acute liver failure. Repeated decompensation, atrial fibrillation (P < .001) and the use of inotropes (P = .007), mean arterial (P = .005) and pulmonary pressures (P = .042), cholinesterase, international normalized ratio, bilirubin, lactate, and pH (P < .001) were predictive of acute liver failure in univariate analysis only. In multivariable analysis, decreased antithrombin III was the strongest single measurement indicating acute liver failure (relative risk per %, 0.84; 95% confidence interval, 0.77-0.93; P = .001) and remained an independent predictor when adjustment for the Model for End-Stage Liver Disease score was performed (relative risk per %, 0.89; 95% confidence interval, 0.80-0.99; P = .031). Antithrombin III less than 59.5% was identified as a cutoff value to predict acute liver failure with a corresponding sensitivity of 81% and specificity of 87%. In addition to the Model for End-Stage Liver Disease score, decreased antithrombin III activity tends to be superior in predicting acute liver failure compared with traditionally thought predictors. Antithrombin III measurement may help to identify patients more precisely who are developing acute liver failure during mechanical circulatory support. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Detailed analysis and test correlation of a stiffened composite wing panel

NASA Technical Reports Server (NTRS)

Davis, D. Dale, Jr.

1991-01-01

Nonlinear finite element analysis techniques are evaluated by applying them to a realistic aircraft structural component. A wing panel from the V-22 tiltrotor aircraft is chosen because it is a typical modern aircraft structural component for which there is experimental data for comparison of results. From blueprints and drawings supplied by the Bell Helicopter Textron Corporation, a very detailed finite element model containing 2284 9-node Assumed Natural-Coordinate Strain (ANS) elements was generated. A novel solution strategy which accounts for geometric nonlinearity through the use of corotating element reference frames and nonlinear strain displacements relations is used to analyze this detailed model. Results from linear analyses using the same finite element model are presented in order to illustrate the advantages and costs of the nonlinear analysis as compared with the more traditional linear analysis. Strain predictions from both the linear and nonlinear stress analyses are shown to compare well with experimental data up through the Design Ultimate Load (DUL) of the panel. However, due to the extreme nonlinear response of the panel, the linear analysis was not accurate at loads above the DUL. The nonlinear analysis more accurately predicted the strain at high values of applied load, and even predicted complicated nonlinear response characteristics, such as load reversals, at the observed failure load of the test panel. In order to understand the failure mechanism of the panel, buckling and first ply failure analyses were performed. The buckling load was 17 percent above the observed failure load while first ply failure analyses indicated significant material damage at and below the observed failure load.

Echocardiography and risk prediction in advanced heart failure: incremental value over clinical markers.

PubMed

Agha, Syed A; Kalogeropoulos, Andreas P; Shih, Jeffrey; Georgiopoulou, Vasiliki V; Giamouzis, Grigorios; Anarado, Perry; Mangalat, Deepa; Hussain, Imad; Book, Wendy; Laskar, Sonjoy; Smith, Andrew L; Martin, Randolph; Butler, Javed

2009-09-01

Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established. We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P < .001 and P=.019, respectively). Reclassifying the SHFM-predicted risk with use of the echocardiography-added model resulted in improved prognostic separation. Addition of standard echocardiographic variables to the SHFM results in significant improvement in risk prediction for patients with advanced HF.

Nonlinear and progressive failure aspects of transport composite fuselage damage tolerance

NASA Technical Reports Server (NTRS)

Walker, Tom; Ilcewicz, L.; Murphy, Dan; Dopker, Bernhard

1993-01-01

The purpose is to provide an end-user's perspective on the state of the art in life prediction and failure analysis by focusing on subsonic transport fuselage issues being addressed in the NASA/Boeing Advanced Technology Composite Aircraft Structure (ATCAS) contract and a related task-order contract. First, some discrepancies between the ATCAS tension-fracture test database and classical prediction methods is discussed, followed by an overview of material modeling work aimed at explaining some of these discrepancies. Finally, analysis efforts associated with a pressure-box test fixture are addressed, as an illustration of modeling complexities required to model and interpret tests.

Implementation of a Tabulated Failure Model Into a Generalized Composite Material Model Suitable for Use in Impact Problems

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Hoffarth, Canio; Khaled, Bilal; Shyamsunder, Loukham; Rajan, Subramaniam; Blankenhorn, Gunther

2017-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased use in the aerospace and automotive communities. The aerospace community has identified several key capabilities which are currently lacking in the available material models in commercial transient dynamic finite element codes. To attempt to improve the predictive capability of composite impact simulations, a next generation material model is being developed for incorporation within the commercial transient dynamic finite element code LS-DYNA. The material model, which incorporates plasticity, damage and failure, utilizes experimentally based tabulated input to define the evolution of plasticity and damage and the initiation of failure as opposed to specifying discrete input parameters such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. For the damage model, a strain equivalent formulation is used to allow for the uncoupling of the deformation and damage analyses. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure. Failure surfaces can be defined with any arbitrary shape, unlike traditional failure models where the mathematical functions used to define the failure surface impose a specific shape on the failure surface. In the current paper, the complete development of the failure model is described and the generation of a tabulated failure surface for a representative composite material is discussed.

A maximum entropy fracture model for low and high strain-rate fracture in TinSilverCopper alloys

NASA Astrophysics Data System (ADS)

Chan, Dennis K.

SnAgCu solder alloys exhibit significant rate-dependent constitutive behavior. Solder joints made of these alloys exhibit failure modes that are also rate-dependent. Solder joints are an integral part of microelectronic packages and are subjected to a wide variety of loading conditions which range from thermo-mechanical fatigue to impact loading. Consequently, there is a need for non-empirical rate-dependent failure theory that is able to accurately predict fracture in these solder joints. In the present thesis, various failure models are first reviewed. But, these models are typically empirical or are not valid for solder joints due to limiting assumptions such as elastic behavior. Here, the development and validation of a maximum entropy fracture model (MEFM) valid for low strain-rate fracture in SnAgCu solders is presented. To this end, work on characterizing SnAgCu solder behavior at low strain-rates using a specially designed tester to estimate parameters for constitutive models is presented. Next, the maximum entropy fracture model is reviewed. This failure model uses a single damage accumulation parameter and relates the risk of fracture to accumulated inelastic dissipation. A methodology is presented to extract this model parameter through a custom-built microscale mechanical tester for Sn3.8Ag0.7Cu solder. This single parameter is used to numerically simulate fracture in two solder joints with entirely different geometries. The simulations are compared to experimentally observed fracture in these same packages. Following the simulations of fracture at low strain rate, the constitutive behavior of solder alloys across nine decades of strain rates through MTS compression tests and split-Hopkinson bar are presented. Preliminary work on using orthogonal machining as novel technique of material characterization at high strain rates is also presented. The resultant data from the MTS compression and split-Hopkinson bar tester is used to demonstrate the localization of stress to the interface of solder joints at high strain rates. The MEFM is further extended to predict failure in brittle materials. Such an extension allows for fracture prediction within intermetallic compounds (IMCs) in solder joints. It has been experimentally observed that the failure mode shifts from bulk solder to the IMC layer with increasing loading rates. The extension of the MEFM would allow for prediction of the fracture mode within the solder joint under different loading conditions. A fracture model capable of predicting failure modes at higher strain rates is necessary, as mobile electronics are becoming ubiquitous. Mobile devices are prone to being dropped which can induce loading rates within solder joints that are much larger than experienced under thermo-mechanical fatigue. A range of possible damage accumulation parameters for Cu6Sn 5 is determined for the MEFM. A value within the aforementioned range is used to demonstrate the increasing likelihood of IMC fracture in solder joints with larger loading rates. The thesis is concluded with remarks about ongoing work that include determining a more accurate damage accumulation parameter for Cu6Sn 5 IMC, and on using machining as a technique for extracting failure parameters for the MEFM.

Early Detection of Heart Failure Using Electronic Health Records: Practical Implications for Time Before Diagnosis, Data Diversity, Data Quantity, and Data Density.

PubMed

Ng, Kenney; Steinhubl, Steven R; deFilippi, Christopher; Dey, Sanjoy; Stewart, Walter F

2016-11-01

Using electronic health records data to predict events and onset of diseases is increasingly common. Relatively little is known, although, about the tradeoffs between data requirements and model utility. We examined the performance of machine learning models trained to detect prediagnostic heart failure in primary care patients using longitudinal electronic health records data. Model performance was assessed in relation to data requirements defined by the prediction window length (time before clinical diagnosis), the observation window length (duration of observation before prediction window), the number of different data domains (data diversity), the number of patient records in the training data set (data quantity), and the density of patient encounters (data density). A total of 1684 incident heart failure cases and 13 525 sex, age-category, and clinic matched controls were used for modeling. Model performance improved as (1) the prediction window length decreases, especially when <2 years; (2) the observation window length increases but then levels off after 2 years; (3) the training data set size increases but then levels off after 4000 patients; (4) more diverse data types are used, but, in order, the combination of diagnosis, medication order, and hospitalization data was most important; and (5) data were confined to patients who had ≥10 phone or face-to-face encounters in 2 years. These empirical findings suggest possible guidelines for the minimum amount and type of data needed to train effective disease onset predictive models using longitudinal electronic health records data. © 2016 American Heart Association, Inc.

Failed rib region prediction in a human body model during crash events with precrash braking.

PubMed

Guleyupoglu, B; Koya, B; Barnard, R; Gayzik, F S

2018-02-28

The objective of this study is 2-fold. We used a validated human body finite element model to study the predicted chest injury (focusing on rib fracture as a function of element strain) based on varying levels of simulated precrash braking. Furthermore, we compare deterministic and probabilistic methods of rib injury prediction in the computational model. The Global Human Body Models Consortium (GHBMC) M50-O model was gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and airbag. Twelve cases were investigated with permutations for failure, precrash braking system, and crash severity. The severities used were median (17 kph), severe (34 kph), and New Car Assessment Program (NCAP; 56.4 kph). Cases with failure enabled removed rib cortical bone elements once 1.8% effective plastic strain was exceeded. Alternatively, a probabilistic framework found in the literature was used to predict rib failure. Both the probabilistic and deterministic methods take into consideration location (anterior, lateral, and posterior). The deterministic method is based on a rubric that defines failed rib regions dependent on a threshold for contiguous failed elements. The probabilistic method depends on age-based strain and failure functions. Kinematics between both methods were similar (peak max deviation: ΔX head = 17 mm; ΔZ head = 4 mm; ΔX thorax = 5 mm; ΔZ thorax = 1 mm). Seat belt forces at the time of probabilistic failed region initiation were lower than those at deterministic failed region initiation. The probabilistic method for rib fracture predicted more failed regions in the rib (an analog for fracture) than the deterministic method in all but 1 case where they were equal. The failed region patterns between models are similar; however, there are differences that arise due to stress reduced from element elimination that cause probabilistic failed regions to continue to rise after no deterministic failed region would be predicted. Both the probabilistic and deterministic methods indicate similar trends with regards to the effect of precrash braking; however, there are tradeoffs. The deterministic failed region method is more spatially sensitive to failure and is more sensitive to belt loads. The probabilistic failed region method allows for increased capability in postprocessing with respect to age. The probabilistic failed region method predicted more failed regions than the deterministic failed region method due to force distribution differences.

Micromolecular modeling

NASA Technical Reports Server (NTRS)

Guillet, J. E.

1984-01-01

A reaction kinetics based model of the photodegradation process, which measures all important rate constants, and a computerized model capable of predicting the photodegradation rate and failure modes of a 30 year period, were developed. It is shown that the computerized photodegradation model for polyethylene correctly predicts failure of ELVAX 15 and cross linked ELVAX 150 on outdoor exposure. It is indicated that cross linking ethylene vinyl acetate (EVA) does not significantly change its degradation rate. It is shown that the effect of the stabilizer package is approximately equivalent on both polymers. The computerized model indicates that peroxide decomposers and UV absorbers are the most effective stabilizers. It is found that a combination of UV absorbers and a hindered amine light stabilizer (HALS) is the most effective stabilizer system.

A model of the human observer and decision maker

NASA Technical Reports Server (NTRS)

Wewerinke, P. H.

1981-01-01

The decision process is described in terms of classical sequential decision theory by considering the hypothesis that an abnormal condition has occurred by means of a generalized likelihood ratio test. For this, a sufficient statistic is provided by the innovation sequence which is the result of the perception an information processing submodel of the human observer. On the basis of only two model parameters, the model predicts the decision speed/accuracy trade-off and various attentional characteristics. A preliminary test of the model for single variable failure detection tasks resulted in a very good fit of the experimental data. In a formal validation program, a variety of multivariable failure detection tasks was investigated and the predictive capability of the model was demonstrated.

The Role of Three-Dimensional Boundary Stresses in Limiting the Occurrence and Size of Experimental Landslides

NASA Astrophysics Data System (ADS)

Prancevic, Jeffrey P.; Lamb, Michael P.; Palucis, Marisa C.; Venditti, Jeremy G.

2018-01-01

The occurrence of seepage-induced shallow landslides on hillslopes and steep channel beds is important for landscape evolution and natural hazards. Infinite-slope stability models have been applied for seven decades, but sediment beds generally require higher water saturation levels than predicted for failure, and controlled experiments are needed to test models. We initiated 90 landslides in a 5 m long laboratory flume with a range in sediment sizes (D = 0.7, 2, 5, and 15 mm) and hillslope angles (θ = 20° to 43°), resulting in subsurface flow that spanned the Darcian and turbulent regimes, and failures that occurred with subsaturated and supersaturated sediment beds. Near complete saturation was required for failure in most experiments, with water levels far greater than predicted by infinite-slope stability models. Although 3-D force balance models predict that larger landslides are less stable, observed downslope landslide lengths were typically only several decimeters, not the entire flume length. Boundary stresses associated with short landslides can explain the increased water levels required for failure, and we suggest that short failures are tied to heterogeneities in granular properties. Boundary stresses also limited landslide thicknesses, and landslides progressively thinned on lower gradient hillslopes until they were one grain diameter thick, corresponding to a change from near-saturated to supersaturated sediment beds. Thus, landslides are expected to be thick on steep hillslopes with large frictional stresses acting on the boundaries, whereas landslides should be thin on low-gradient hillslopes or in channel beds with a critical saturation level that is determined by sediment size.

VHSIC/VHSIC-Like Reliability Prediction Modeling

DTIC Science & Technology

1989-10-01

prediction would require ’ kowledge of event statistics as well as device robustness. Ii1 Additionally, although this is primarily a theoretical, bottom...Degradation in Section 5.3 P = Power PDIP = Plastic DIP P(f) = Probability of Failure due to EOS or ESD P(flc) = Probability of Failure given Contact from an...the results of those stresses: Device Stress Part Number Power Dissipation Manufacturer Test Type Part Description Junction Teniperatune Package Type

Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model

PubMed Central

Orini, Michele; Mincholé, Ana; Monasterio, Violeta; Cygankiewicz, Iwona; Bayés de Luna, Antonio; Martínez, Juan Pablo

2017-01-01

Background Sudden cardiac death (SCD) and pump failure death (PFD) are common endpoints in chronic heart failure (CHF) patients, but prevention strategies are different. Currently used tools to specifically predict these endpoints are limited. We developed risk models to specifically assess SCD and PFD risk in CHF by combining ECG markers and clinical variables. Methods The relation of clinical and ECG markers with SCD and PFD risk was assessed in 597 patients enrolled in the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study. ECG indices included: turbulence slope (TS), reflecting autonomic dysfunction; T-wave alternans (TWA), reflecting ventricular repolarization instability; and T-peak-to-end restitution (ΔαTpe) and T-wave morphology restitution (TMR), both reflecting changes in dispersion of repolarization due to heart rate changes. Standard clinical indices were also included. Results The indices with the greatest SCD prognostic impact were gender, New York Heart Association (NYHA) class, left ventricular ejection fraction, TWA, ΔαTpe and TMR. For PFD, the indices were diabetes, NYHA class, ΔαTpe and TS. Using a model with only clinical variables, the hazard ratios (HRs) for SCD and PFD for patients in the high-risk group (fifth quintile of risk score) with respect to patients in the low-risk group (first and second quintiles of risk score) were both greater than 4. HRs for SCD and PFD increased to 9 and 11 when using a model including only ECG markers, and to 14 and 13, when combining clinical and ECG markers. Conclusion The inclusion of ECG markers capturing complementary pro-arrhythmic and pump failure mechanisms into risk models based only on standard clinical variables substantially improves prediction of SCD and PFD in CHF patients. PMID:29020031

Advanced Fault Diagnosis Methods in Molecular Networks

PubMed Central

Habibi, Iman; Emamian, Effat S.; Abdi, Ali

2014-01-01

Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally. PMID:25290670

Failure mechanisms of additively manufactured porous biomaterials: Effects of porosity and type of unit cell.

PubMed

Kadkhodapour, J; Montazerian, H; Darabi, A Ch; Anaraki, A P; Ahmadi, S M; Zadpoor, A A; Schmauder, S

2015-10-01

Since the advent of additive manufacturing techniques, regular porous biomaterials have emerged as promising candidates for tissue engineering scaffolds owing to their controllable pore architecture and feasibility in producing scaffolds from a variety of biomaterials. The architecture of scaffolds could be designed to achieve similar mechanical properties as in the host bone tissue, thereby avoiding issues such as stress shielding in bone replacement procedure. In this paper, the deformation and failure mechanisms of porous titanium (Ti6Al4V) biomaterials manufactured by selective laser melting from two different types of repeating unit cells, namely cubic and diamond lattice structures, with four different porosities are studied. The mechanical behavior of the above-mentioned porous biomaterials was studied using finite element models. The computational results were compared with the experimental findings from a previous study of ours. The Johnson-Cook plasticity and damage model was implemented in the finite element models to simulate the failure of the additively manufactured scaffolds under compression. The computationally predicted stress-strain curves were compared with the experimental ones. The computational models incorporating the Johnson-Cook damage model could predict the plateau stress and maximum stress at the first peak with less than 18% error. Moreover, the computationally predicted deformation modes were in good agreement with the results of scaling law analysis. A layer-by-layer failure mechanism was found for the stretch-dominated structures, i.e. structures made from the cubic unit cell, while the failure of the bending-dominated structures, i.e. structures made from the diamond unit cells, was accompanied by the shearing bands of 45°. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sudden cardiac death and pump failure death prediction in chronic heart failure by combining ECG and clinical markers in an integrated risk model.

PubMed

Ramírez, Julia; Orini, Michele; Mincholé, Ana; Monasterio, Violeta; Cygankiewicz, Iwona; Bayés de Luna, Antonio; Martínez, Juan Pablo; Laguna, Pablo; Pueyo, Esther

2017-01-01

Sudden cardiac death (SCD) and pump failure death (PFD) are common endpoints in chronic heart failure (CHF) patients, but prevention strategies are different. Currently used tools to specifically predict these endpoints are limited. We developed risk models to specifically assess SCD and PFD risk in CHF by combining ECG markers and clinical variables. The relation of clinical and ECG markers with SCD and PFD risk was assessed in 597 patients enrolled in the MUSIC (MUerte Súbita en Insuficiencia Cardiaca) study. ECG indices included: turbulence slope (TS), reflecting autonomic dysfunction; T-wave alternans (TWA), reflecting ventricular repolarization instability; and T-peak-to-end restitution (ΔαTpe) and T-wave morphology restitution (TMR), both reflecting changes in dispersion of repolarization due to heart rate changes. Standard clinical indices were also included. The indices with the greatest SCD prognostic impact were gender, New York Heart Association (NYHA) class, left ventricular ejection fraction, TWA, ΔαTpe and TMR. For PFD, the indices were diabetes, NYHA class, ΔαTpe and TS. Using a model with only clinical variables, the hazard ratios (HRs) for SCD and PFD for patients in the high-risk group (fifth quintile of risk score) with respect to patients in the low-risk group (first and second quintiles of risk score) were both greater than 4. HRs for SCD and PFD increased to 9 and 11 when using a model including only ECG markers, and to 14 and 13, when combining clinical and ECG markers. The inclusion of ECG markers capturing complementary pro-arrhythmic and pump failure mechanisms into risk models based only on standard clinical variables substantially improves prediction of SCD and PFD in CHF patients.

A new yield and failure theory for composite materials under static and dynamic loading

DOE PAGES

Daniel, Isaac M.; Daniel, Sam M.; Fenner, Joel S.

2017-09-12

In order to facilitate and accelerate the process of introducing, evaluating and adopting new material systems, it is important to develop/establish comprehensive and effective procedures of characterization, modeling and failure prediction of composite structures based on the properties of the constituent materials, e. g., fibers, matrix, and the single ply or lamina. A new yield/failure theory is proposed for predicting lamina yielding and failure under multi-axial states of stress including strain rate effects. It is based on the equivalent stress concept derived from energy principles and is expressed in terms of a single criterion. It is presented in the formmore » of master yield and failure envelopes incorporating strain rate effects. The theory can be further adapted and extended to the prediction of in situ first ply yielding and failure (FPY and FPF) and progressive damage of multi-directional laminates under static and dynamic loadings. The significance of this theory is that it allows for rapid screening of new composite materials without extensive testing and offers easily implemented design tools.« less

A new yield and failure theory for composite materials under static and dynamic loading

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daniel, Isaac M.; Daniel, Sam M.; Fenner, Joel S.

In order to facilitate and accelerate the process of introducing, evaluating and adopting new material systems, it is important to develop/establish comprehensive and effective procedures of characterization, modeling and failure prediction of composite structures based on the properties of the constituent materials, e. g., fibers, matrix, and the single ply or lamina. A new yield/failure theory is proposed for predicting lamina yielding and failure under multi-axial states of stress including strain rate effects. It is based on the equivalent stress concept derived from energy principles and is expressed in terms of a single criterion. It is presented in the formmore » of master yield and failure envelopes incorporating strain rate effects. The theory can be further adapted and extended to the prediction of in situ first ply yielding and failure (FPY and FPF) and progressive damage of multi-directional laminates under static and dynamic loadings. The significance of this theory is that it allows for rapid screening of new composite materials without extensive testing and offers easily implemented design tools.« less

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

NASA Technical Reports Server (NTRS)

Hatfield, Glen S.; Hark, Frank; Stott, James

2016-01-01

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account system integration risks such as those attributable to manufacturing and assembly. These sources often dominate component level risk. While consequence of failure is often understood, using predicted values in a risk model to estimate the probability of occurrence may underestimate the actual risk. Managers and decision makers use the probability of occurrence to influence the determination whether to accept the risk or require a design modification. The actual risk threshold for acceptance may not be fully understood due to the absence of system level test data or operational data. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Numerical Analysis of AHSS Fracture in a Stretch-bending Test

NASA Astrophysics Data System (ADS)

Luo, Meng; Chen, Xiaoming; Shi, Ming F.; Shih, Hua-Chu

2010-06-01

Advanced High Strength Steels (AHSS) are increasingly used in the automotive industry due to their superior strength and substantial weight reduction advantage. However, their limited ductility gives rise to numerous manufacturing issues. One of them is the so-called `shear fracture' often observed on tight radii during stamping processes. Since traditional approaches, such as the Forming Limit Diagram (FLD), are unable to predict this type of fracture, efforts have been made to develop failure criteria that can predict shear fractures. In this paper, a recently developed Modified Mohr-Coulomb (MMC) ductile fracture criterion[1] is adopted to analyze the failure behavior of a Dual Phase (DP) steel sheet during stretch bending operations. The plasticity and ductile fracture of the present sheet are fully characterized by the Hill'48 orthotropic model and the MMC fracture model respectively. Finite Element models with three different element types (3D, shell and plane strain) were built for a Stretch Forming Simulator (SFS) test and numerical simulations with four different R/t ratios (die radius normalized by sheet thickness) were performed. It has been shown that the 3D and shell element models can accurately predict the failure location/mode, the upper die load-displacement responses as well as the wall stress and wrap angle at the onset of fracture for all R/t ratios. Furthermore, a series of parametric studies were conducted on the 3D element model, and the effects of tension level (clamping distance) and tooling friction on the failure modes/locations were investigated.

The Effect of Delamination on Damage Path and Failure Load Prediction for Notched Composite Laminates

NASA Technical Reports Server (NTRS)

Satyanarayana, Arunkumar; Bogert, Philip B.; Chunchu, Prasad B.

2007-01-01

The influence of delamination on the progressing damage path and initial failure load in composite laminates is investigated. Results are presented from a numerical and an experimental study of center-notched tensile-loaded coupons. The numerical study includes two approaches. The first approach considers only intralaminar (fiber breakage and matrix cracking) damage modes in calculating the progression of the damage path. In the second approach, the model is extended to consider the effect of interlaminar (delamination) damage modes in addition to the intralaminar damage modes. The intralaminar damage is modeled using progressive damage analysis (PDA) methodology implemented with the VUMAT subroutine in the ABAQUS finite element code. The interlaminar damage mode has been simulated using cohesive elements in ABAQUS. In the experimental study, 2-3 specimens each of two different stacking sequences of center-notched laminates are tensile loaded. The numerical results from the two different modeling approaches are compared with each other and the experimentally observed results for both laminate types. The comparisons reveal that the second modeling approach, where the delamination damage mode is included together with the intralaminar damage modes, better simulates the experimentally observed damage modes and damage paths, which were characterized by splitting failures perpendicular to the notch tips in one or more layers. Additionally, the inclusion of the delamination mode resulted in a better prediction of the loads at which the failure took place, which were higher than those predicted by the first modeling approach which did not include delaminations.

Bending and Shear Behavior of Pultruded Glass Fiber Reinforced Polymer Composite Beams With Closed and Open Sections

NASA Astrophysics Data System (ADS)

Estep, Daniel Douglas

Several advantages, such as high strength-to-weight ratio, high stiffness, superior corrosion resistance, and high fatigue and impact resistance, among others, make FRPs an attractive alternative to conventional construction materials for use in developing new structures as well as rehabilitating in-service infrastructure. As the number of infrastructure applications using FRPs grows, the need for the development of a uniform Load and Resistance Factor Design (LRFD) approach, including design procedures and examples, has become paramount. Step-by-step design procedures and easy-to-use design formulas are necessary to assure the quality and safety of FRP structural systems by reducing the possibility of design and construction errors. Since 2008, the American Society of Civil Engineers (ASCE), in coordination with the American Composites Manufacturers Association (ACMA), has overseen the development of the Pre-Standard for Load and Resistance Factor Design (LRFD) of Pultruded Fiber Reinforced Polymer (FRP) Structures using probability-based limit states design. The fifth chapter of the pre-standard focuses on the design of members in flexure and shear under different failure modes, where the current failure load prediction models proposed within have been shown to be highly inaccurate based on experimental data and evaluation performed by researchers at the West Virginia University Constructed Facilities Center. A new prediction model for determining the critical flexural load capacity of pultruded GFRP square and rectangular box beams is presented within. This model shows that the type of failure can be related to threshold values of the beam span-to-depth ratio (L/h) and total flange width-to-thickness ratio (bf /t), resulting in three governing modes of failure: local buckling failure in the compression flange (4 ≤ L/h < 6), combined strain failure at the web-flange junction (6 ≤ L/h ≤ 10), and bending failure in the tension flange (10 < L/h ≤ 42). Broadly, the proposed equations are predicting critical flexural load capacities within +/-22.3% of experimental data for all cases, with over 70% of all experimental data with within +/-10% error. A second prediction model was developed for predicting the critical lateral-torsional buckling (LTB) load for pultruded GFRP open sections, including wide flange (WF) sections and channels. Multiple LTB equations from several sources were considered and applied but yielded inaccurate results, leading to the development of this new critical buckling load prediction model based on the well-established elastic LTB strength equation for steel. By making a series of modifications to equations for calculating the weak axis moment of inertia, torsional warping constant, and torsion constant for open sections, as well as recognizing the influence of the shear lag phenomenon, the critical LTB load is predicted within +/-15.2% of experimental data for all channel and WF specimens tested and evaluated in the study.

Thermomechanical Modeling of Sintered Silver - A Fracture Mechanics-based Approach: Extended Abstract: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paret, Paul P; DeVoto, Douglas J; Narumanchi, Sreekant V

Sintered silver has proven to be a promising candidate for use as a die-attach and substrate-attach material in automotive power electronics components. It holds promise of greater reliability than lead-based and lead-free solders, especially at higher temperatures (less than 200 degrees Celcius). Accurate predictive lifetime models of sintered silver need to be developed and its failure mechanisms thoroughly characterized before it can be deployed as a die-attach or substrate-attach material in wide-bandgap device-based packages. We present a finite element method (FEM) modeling methodology that can offer greater accuracy in predicting the failure of sintered silver under accelerated thermal cycling. Amore » fracture mechanics-based approach is adopted in the FEM model, and J-integral/thermal cycle values are computed. In this paper, we outline the procedures for obtaining the J-integral/thermal cycle values in a computational model and report on the possible advantage of using these values as modeling parameters in a predictive lifetime model.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dobson, Ian; Hiskens, Ian; Linderoth, Jeffrey

Building on models of electrical power systems, and on powerful mathematical techniques including optimization, model predictive control, and simluation, this project investigated important issues related to the stable operation of power grids. A topic of particular focus was cascading failures of the power grid: simulation, quantification, mitigation, and control. We also analyzed the vulnerability of networks to component failures, and the design of networks that are responsive to and robust to such failures. Numerous other related topics were investigated, including energy hubs and cascading stall of induction machines

Thermal barrier coating life prediction model development

NASA Technical Reports Server (NTRS)

Sheffler, K. D.; Demasi, J. T.

1985-01-01

A methodology was established to predict thermal barrier coating life in an environment simulative of that experienced by gas turbine airfoils. Specifically, work is being conducted to determine failure modes of thermal barrier coatings in the aircraft engine environment. Analytical studies coupled with appropriate physical and mechanical property determinations are being employed to derive coating life prediction model(s) on the important failure mode(s). An initial review of experimental and flight service components indicates that the predominant mode of TBC failure involves thermomechanical spallation of the ceramic coating layer. This ceramic spallation involves the formation of a dominant crack in the ceramic coating parallel to and closely adjacent to the metal-ceramic interface. Initial results from a laboratory test program designed to study the influence of various driving forces such as temperature, thermal cycle frequency, environment, and coating thickness, on ceramic coating spalling life suggest that bond coat oxidation damage at the metal-ceramic interface contributes significantly to thermomechanical cracking in the ceramic layer. Low cycle rate furnace testing in air and in argon clearly shows a dramatic increase of spalling life in the non-oxidizing environments.

Numerical Modelling of Glass Fibre Reinforced Laminates Subjected to a Low Velocity Impact

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, J. Y.; Guana, Z. W.; Cantwell, W. J.

2010-05-21

This paper presents a series of numerical predictions of the perforation behaviour of glass fibre laminates subjected to quasi-static and low-velocity impact loading. Both shear and tensile failure criteria were used in the finite element models to simulate the post-failure processes via an automatic element removal procedure. The appropriate material properties, obtained through a series of uniaxial tension and bending tests on the composites, were used in the numerical models. Four, eight and sixteen ply glass fibre laminates panels were perforated at quasi-static rates and under low-velocity impact loading. Reasonably good correlation was obtained between the numerical simulations and themore » experimental results, both in terms of the failure modes and the load-deflection relationships before and during the penetration phase. The predicted impact energies of the GFRP panels were compared with the experimental data and reasonable agreement was observed.« less

Performance and Reliability of Bonded Interfaces for High-Temperature Packaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paret, Paul P

2017-08-02

Sintered silver has proven to be a promising candidate for use as a die-attach and substrate-attach material in automotive power electronics components. It holds promise of greater reliability than lead-based and lead-free solders, especially at higher temperatures (>200 degrees C). Accurate predictive lifetime models of sintered silver need to be developed and its failure mechanisms thoroughly characterized before it can be deployed as a die-attach or substrate-attach material in wide-bandgap device-based packages. Mechanical characterization tests that result in stress-strain curves and accelerated tests that produce cycles-to-failure result will be conducted. Also, we present a finite element method (FEM) modeling methodologymore » that can offer greater accuracy in predicting the failure of sintered silver under accelerated thermal cycling. A fracture mechanics-based approach is adopted in the FEM model, and J-integral/thermal cycle values are computed.« less

A Bayesian Approach Based Outage Prediction in Electric Utility Systems Using Radar Measurement Data

DOE PAGES

Yue, Meng; Toto, Tami; Jensen, Michael P.; ...

2017-05-18

Severe weather events such as strong thunderstorms are some of the most significant and frequent threats to the electrical grid infrastructure. Outages resulting from storms can be very costly. While some tools are available to utilities to predict storm occurrences and damage, they are typically very crude and provide little means of facilitating restoration efforts. This study developed a methodology to use historical high-resolution (both temporal and spatial) radar observations of storm characteristics and outage information to develop weather condition dependent failure rate models (FRMs) for different grid components. Such models can provide an estimation or prediction of the outagemore » numbers in small areas of a utility’s service territory once the real-time measurement or forecasted data of weather conditions become available as the input to the models. Considering the potential value provided by real-time outages reported, a Bayesian outage prediction (BOP) algorithm is proposed to account for both strength and uncertainties of the reported outages and failure rate models. The potential benefit of this outage prediction scheme is illustrated in this study.« less

A Bayesian Approach Based Outage Prediction in Electric Utility Systems Using Radar Measurement Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yue, Meng; Toto, Tami; Jensen, Michael P.

Severe weather events such as strong thunderstorms are some of the most significant and frequent threats to the electrical grid infrastructure. Outages resulting from storms can be very costly. While some tools are available to utilities to predict storm occurrences and damage, they are typically very crude and provide little means of facilitating restoration efforts. This study developed a methodology to use historical high-resolution (both temporal and spatial) radar observations of storm characteristics and outage information to develop weather condition dependent failure rate models (FRMs) for different grid components. Such models can provide an estimation or prediction of the outagemore » numbers in small areas of a utility’s service territory once the real-time measurement or forecasted data of weather conditions become available as the input to the models. Considering the potential value provided by real-time outages reported, a Bayesian outage prediction (BOP) algorithm is proposed to account for both strength and uncertainties of the reported outages and failure rate models. The potential benefit of this outage prediction scheme is illustrated in this study.« less

Biomarkers of Myocardial Stress and Fibrosis as Predictors of Mode of Death in Patients with Chronic Heart Failure

PubMed Central

Ahmad, Tariq; Fiuzat, Mona; Neely, Ben; Neely, Megan; Pencina, Michael J.; Kraus, William E.; Zannad, Faiez; Whellan, David J.; Donahue, Mark; Piña, Ileana L.; Adams, Kirkwood; Kitzman, Dalane W.; O’Connor, Christopher M.; Felker, G. Michael

2014-01-01

Objective To determine whether biomarkers of myocardial stress and fibrosis improve prediction of mode of death in patients with chronic heart failure. Background The two most common modes of death in patients with chronic heart failure are pump failure and sudden cardiac death. Prediction of mode of death may facilitate treatment decisions. The relationship between NT-proBNP, galectin-3, and ST2, biomarkers that reflect different pathogenic pathways in heart failure (myocardial stress and fibrosis), and mode of death is unknown. Methods HF-ACTION was a randomized controlled trial of exercise training vs. usual care in patients with chronic heart failure due to left ventricular systolic dysfunction (LVEF<35%). An independent clinical events committee prospectively adjudicated mode of death. NT-proBNP, galectin-3, and ST2 levels were assessed at baseline in 813 subjects. Associations between biomarkers and mode of death were assessed using cause-specific Cox-proportional hazards modeling, and interaction testing was used to measure differential association between biomarkers and pump failure versus sudden cardiac death. Discrimination and risk reclassification metrics were used to assess the added value of galectin-3 and ST2 in predicting mode of death risk beyond a clinical model that included NT-proBNP. Results After a median follow up of 2.5 years, there were 155 deaths: 49 from pump failure 42 from sudden cardiac death, and 64 from other causes. Elevations in all biomarkers were associated with increased risk of both pump failure and sudden cardiac death in both adjusted and unadjusted analyses. In each case, increases in the biomarker had a stronger association with pump failure than sudden cardiac death but this relationship was attenuated after adjustment for clinical risk factors. Clinical variables along with NT-proBNP levels were stronger predictors of pump failure (C statistic: 0.87) than sudden cardiac death (C statistic: 0.73). Addition of ST2 and galectin-3 led to improved net risk classification of 11% for sudden cardiac death, but not pump failure. Conclusions Clinical predictors along with NT-proBNP levels were strong predictors of pump failure risk, with insignificant incremental contributions of ST2 and galectin-3. Predictability of sudden cardiac death risk was less robust and enhanced by information provided by novel biomarkers. PMID:24952693

On the Formulation of Anisotropic-Polyaxial Failure Criteria: A Comparative Study

NASA Astrophysics Data System (ADS)

Parisio, Francesco; Laloui, Lyesse

2018-02-01

The correct representation of the failure of geomaterials that feature strength anisotropy and polyaxiality is crucial for many applications. In this contribution, we propose and evaluate through a comparative study a generalized framework that covers both features. Polyaxiality of strength is modeled with a modified Van Eekelen approach, while the anisotropy is modeled using a fabric tensor approach of the Pietruszczak and Mroz type. Both approaches share the same philosophy as they can be applied to simpler failure surfaces, allowing great flexibility in model formulation. The new failure surface is tested against experimental data and its performance compared against classical failure criteria commonly used in geomechanics. Our study finds that the global error between predictions and data is generally smaller for the proposed framework compared to other classical approaches.

The Effect of Scale Dependent Discretization on the Progressive Failure of Composite Materials Using Multiscale Analyses

NASA Technical Reports Server (NTRS)

Ricks, Trenton M.; Lacy, Thomas E., Jr.; Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.

2013-01-01

A multiscale modeling methodology, which incorporates a statistical distribution of fiber strengths into coupled micromechanics/ finite element analyses, is applied to unidirectional polymer matrix composites (PMCs) to analyze the effect of mesh discretization both at the micro- and macroscales on the predicted ultimate tensile (UTS) strength and failure behavior. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a PMC tensile specimen that initiates at the repeating unit cell (RUC) level. Three different finite element mesh densities were employed and each coupled with an appropriate RUC. Multiple simulations were performed in order to assess the effect of a statistical distribution of fiber strengths on the bulk composite failure and predicted strength. The coupled effects of both the micro- and macroscale discretizations were found to have a noticeable effect on the predicted UTS and computational efficiency of the simulations.

Static and fatigue testing of full-scale fuselage panels fabricated using a Therm-X(R) process

NASA Technical Reports Server (NTRS)

Dinicola, Albert J.; Kassapoglou, Christos; Chou, Jack C.

1992-01-01

Large, curved, integrally stiffened composite panels representative of an aircraft fuselage structure were fabricated using a Therm-X process, an alternative concept to conventional two-sided hard tooling and contour vacuum bagging. Panels subsequently were tested under pure shear loading in both static and fatigue regimes to assess the adequacy of the manufacturing process, the effectiveness of damage tolerant design features co-cured with the structure, and the accuracy of finite element and closed-form predictions of postbuckling capability and failure load. Test results indicated the process yielded panels of high quality and increased damage tolerance through suppression of common failure modes such as skin-stiffener separation and frame-stiffener corner failure. Finite element analyses generally produced good predictions of postbuckled shape, and a global-local modelling technique yielded failure load predictions that were within 7% of the experimental mean.

Cascading Failures in Bi-partite Graphs: Model for Systemic Risk Propagation

PubMed Central

Huang, Xuqing; Vodenska, Irena; Havlin, Shlomo; Stanley, H. Eugene

2013-01-01

As economic entities become increasingly interconnected, a shock in a financial network can provoke significant cascading failures throughout the system. To study the systemic risk of financial systems, we create a bi-partite banking network model composed of banks and bank assets and propose a cascading failure model to describe the risk propagation process during crises. We empirically test the model with 2007 US commercial banks balance sheet data and compare the model prediction of the failed banks with the real failed banks after 2007. We find that our model efficiently identifies a significant portion of the actual failed banks reported by Federal Deposit Insurance Corporation. The results suggest that this model could be useful for systemic risk stress testing for financial systems. The model also identifies that commercial rather than residential real estate assets are major culprits for the failure of over 350 US commercial banks during 2008–2011. PMID:23386974

Shuttle data book: SRM fragment velocity model. Presented to the SRB Fragment Model Review Panel

NASA Technical Reports Server (NTRS)

1989-01-01

This study was undertaken to determine the velocity of fragments generated by the range safety destruction (RSD) or random failure of a Space Transportation System (STS) Solid Rocket Motor (SRM). The specific requirement was to provide a fragment model for use in those Galileo and Ulysses RTG safety analyses concerned with possible fragment impact on the spacecraft radioisotope thermoelectric generators (RTGS). Good agreement was obtained between predictions and observations for fragment velocity, velocity distributions, azimuths, and rotation rates. Based on this agreement with the entire data base, the model was used to predict the probable fragment environments which would occur in the event of an STS-SRM RSD or randon failure at 10, 74, 84 and 110 seconds. The results of these predictions are the basis of the fragment environments presented in the Shuttle Data Book (NSTS-08116). The information presented here is in viewgraph form.

Predictability of Landslide Timing From Quasi-Periodic Precursory Earthquakes

NASA Astrophysics Data System (ADS)

Bell, Andrew F.

2018-02-01

Accelerating rates of geophysical signals are observed before a range of material failure phenomena. They provide insights into the physical processes controlling failure and the basis for failure forecasts. However, examples of accelerating seismicity before landslides are rare, and their behavior and forecasting potential are largely unknown. Here I use a Bayesian methodology to apply a novel gamma point process model to investigate a sequence of quasiperiodic repeating earthquakes preceding a large landslide at Nuugaatsiaq in Greenland in June 2017. The evolution in earthquake rate is best explained by an inverse power law increase with time toward failure, as predicted by material failure theory. However, the commonly accepted power law exponent value of 1.0 is inconsistent with the data. Instead, the mean posterior value of 0.71 indicates a particularly rapid acceleration toward failure and suggests that only relatively short warning times may be possible for similar landslides in future.

Prediction of L70 lumen maintenance and chromaticity for LEDs using extended Kalman filter models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-09-30

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 definedmore » 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 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.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 definedmore » 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 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.« less

Buckling Testing and Analysis of Space Shuttle Solid Rocket Motor Cylinders

NASA Technical Reports Server (NTRS)

Weidner, Thomas J.; Larsen, David V.; McCool, Alex (Technical Monitor)

2002-01-01

A series of full-scale buckling tests were performed on the space shuttle Reusable Solid Rocket Motor (RSRM) cylinders. The tests were performed to determine the buckling capability of the cylinders and to provide data for analytical comparison. A nonlinear ANSYS Finite Element Analysis (FEA) model was used to represent and evaluate the testing. Analytical results demonstrated excellent correlation to test results, predicting the failure load within 5%. The analytical value was on the conservative side, predicting a lower failure load than was applied to the test. The resulting study and analysis indicated the important parameters for FEA to accurately predict buckling failure. The resulting method was subsequently used to establish the pre-launch buckling capability of the space shuttle system.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes, These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

An Experimental Study of Incremental Surface Loading of an Elastic Plate: Application to Volcano Tectonics

NASA Technical Reports Server (NTRS)

Williams, K. K.; Zuber, M. T.

1995-01-01

Models of surface fractures due to volcanic loading an elastic plate are commonly used to constrain thickness of planetary lithospheres, but discrepancies exist in predictions of the style of initial failure and in the nature of subsequent fracture evolution. In this study, we perform an experiment to determine the mode of initial failure due to the incremental addition of a conical load to the surface of an elastic plate and compare the location of initial failure with that predicted by elastic theory. In all experiments, the mode of initial failure was tension cracking at the surface of the plate, with cracks oriented circumferential to the load. The cracks nucleated at a distance from load center that corresponds the maximum radial stress predicted by analytical solutions, so a tensile failure criterion is appropriate for predictions of initial failure. With continued loading of the plate, migration of tensional cracks was observed. In the same azimuthal direction as the initial crack, subsequent cracks formed at a smaller radial distance than the initial crack. When forming in a different azimuthal direction, the subsequent cracks formed at a distance greater than the radial distance of the initial crack. The observed fracture pattern may explain the distribution of extensional structures in annular bands around many large scale, circular volcanic features.

Is it possible to predict office hysteroscopy failure?

PubMed

Cobellis, Luigi; Castaldi, Maria Antonietta; Giordano, Valentino; De Franciscis, Pasquale; Signoriello, Giuseppe; Colacurci, Nicola

2014-10-01

The purpose of this study was to develop a clinical tool, the HFI (Hysteroscopy Failure Index), which gives criteria to predict hysteroscopic examination failure. This was a retrospective diagnostic test study, aimed to validate the HFI, set at the Department of Gynaecology, Obstetric and Reproductive Science of the Second University of Naples, Italy. The HFI was applied to our database of 995 consecutive women, who underwent office based to assess abnormal uterine bleeding (AUB), infertility, cervical polyps, and abnormal sonographic patterns (postmenopausal endometrial thickness of more than 5mm, endometrial hyperechogenic spots, irregular endometrial line, suspect of uterine septa). Demographic characteristics, previous surgery, recurrent infections, sonographic data, Estro-Progestins, IUD and menopausal status were collected. Receiver operating characteristic (ROC) curve analysis was used to assess the ability of the model to identify patients who were correctly identified (true positives) divided by the total number of failed hysteroscopies (true positives+false negatives). Positive and Negative Likelihood Ratios with 95%CI were calculated. The HFI score is able to predict office hysteroscopy failure in 76% of cases. Moreover, the Positive likelihood ratio was 11.37 (95% CI: 8.49-15.21), and the Negative likelihood ratio was 0.33 (95% CI: 0.27-0.41). Hysteroscopy failure index was able to retrospectively predict office hysteroscopy failure. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Applying artificial neural networks to predict communication risks in the emergency department.

PubMed

Bagnasco, Annamaria; Siri, Anna; Aleo, Giuseppe; Rocco, Gennaro; Sasso, Loredana

2015-10-01

To describe the utility of artificial neural networks in predicting communication risks. In health care, effective communication reduces the risk of error. Therefore, it is important to identify the predictive factors of effective communication. Non-technical skills are needed to achieve effective communication. This study explores how artificial neural networks can be applied to predict the risk of communication failures in emergency departments. A multicentre observational study. Data were collected between March-May 2011 by observing the communication interactions of 840 nurses with their patients during their routine activities in emergency departments. The tools used for our observation were a questionnaire to collect personal and descriptive data, level of training and experience and Guilbert's observation grid, applying the Situation-Background-Assessment-Recommendation technique to communication in emergency departments. A total of 840 observations were made on the nurses working in the emergency departments. Based on Guilbert's observation grid, the output variables is likely to influence the risk of communication failure were 'terminology'; 'listening'; 'attention' and 'clarity', whereas nurses' personal characteristics were used as input variables in the artificial neural network model. A model based on the multilayer perceptron topology was developed and trained. The receiver operator characteristic analysis confirmed that the artificial neural network model correctly predicted the performance of more than 80% of the communication failures. The application of the artificial neural network model could offer a valid tool to forecast and prevent harmful communication errors in the emergency department. © 2015 John Wiley & Sons Ltd.

Prediction of Hip Failure Load: In Vitro Study of 80 Femurs Using Three Imaging Methods and Finite Element Models-The European Fracture Study (EFFECT).

PubMed

Pottecher, Pierre; Engelke, Klaus; Duchemin, Laure; Museyko, Oleg; Moser, Thomas; Mitton, David; Vicaut, Eric; Adams, Judith; Skalli, Wafa; Laredo, Jean Denis; Bousson, Valérie

2016-09-01

Purpose To evaluate the performance of three imaging methods (radiography, dual-energy x-ray absorptiometry [DXA], and quantitative computed tomography [CT]) and that of a numerical analysis with finite element modeling (FEM) in the prediction of failure load of the proximal femur and to identify the best densitometric or geometric predictors of hip failure load. Materials and Methods Institutional review board approval was obtained. A total of 40 pairs of excised cadaver femurs (mean patient age at time of death, 82 years ± 12 [standard deviation]) were examined with (a) radiography to measure geometric parameters (lengths, angles, and cortical thicknesses), (b) DXA (reference standard) to determine areal bone mineral densities (BMDs), and (c) quantitative CT with dedicated three-dimensional analysis software to determine volumetric BMDs and geometric parameters (neck axis length, cortical thicknesses, volumes, and moments of inertia), and (d) quantitative CT-based FEM to calculate a numerical value of failure load. The 80 femurs were fractured via mechanical testing, with random assignment of one femur from each pair to the single-limb stance configuration (hereafter, stance configuration) and assignment of the paired femur to the sideways fall configuration (hereafter, side configuration). Descriptive statistics, univariate correlations, and stepwise regression models were obtained for each imaging method and for FEM to enable us to predict failure load in both configurations. Results Statistics reported are for stance and side configurations, respectively. For radiography, the strongest correlation with mechanical failure load was obtained by using a geometric parameter combined with a cortical thickness (r(2) = 0.66, P < .001; r(2) = 0.65, P < .001). For DXA, the strongest correlation with mechanical failure load was obtained by using total BMD (r(2) = 0.73, P < .001) and trochanteric BMD (r(2) = 0.80, P < .001). For quantitative CT, in both configurations, the best model combined volumetric BMD and a moment of inertia (r(2) = 0.78, P < .001; r(2) = 0.85, P < .001). FEM explained 87% (P < .001) and 83% (P < .001) of bone strength, respectively. By combining (a) radiography and DXA and (b) quantitative CT and DXA, correlations with mechanical failure load increased to 0.82 (P < .001) and 0.84 (P < .001), respectively, for radiography and DXA and to 0.80 (P < .001) and 0.86 (P < .001) , respectively, for quantitative CT and DXA. Conclusion Quantitative CT-based FEM was the best method with which to predict the experimental failure load; however, combining quantitative CT and DXA yielded a performance as good as that attained with FEM. The quantitative CT DXA combination may be easier to use in fracture prediction, provided standardized software is developed. These findings also highlight the major influence on femoral failure load, particularly in the trochanteric region, of a densitometric parameter combined with a geometric parameter. (©) RSNA, 2016 Online supplemental material is available for this article.

Conduit Stability and Collapse in Explosive Volcanic Eruptions: Coupling Conduit Flow and Failure Models

NASA Astrophysics Data System (ADS)

Mullet, B.; Segall, P.

2017-12-01

Explosive volcanic eruptions can exhibit abrupt changes in physical behavior. In the most extreme cases, high rates of mass discharge are interspaced by dramatic drops in activity and periods of quiescence. Simple models predict exponential decay in magma chamber pressure, leading to a gradual tapering of eruptive flux. Abrupt changes in eruptive flux therefore indicate that relief of chamber pressure cannot be the only control of the evolution of such eruptions. We present a simplified physics-based model of conduit flow during an explosive volcanic eruption that attempts to predict stress-induced conduit collapse linked to co-eruptive pressure loss. The model couples a simple two phase (gas-melt) 1-D conduit solution of the continuity and momentum equations with a Mohr-Coulomb failure condition for the conduit wall rock. First order models of volatile exsolution (i.e. phase mass transfer) and fragmentation are incorporated. The interphase interaction force changes dramatically between flow regimes, so smoothing of this force is critical for realistic results. Reductions in the interphase force lead to significant relative phase velocities, highlighting the deficiency of homogenous flow models. Lateral gas loss through conduit walls is incorporated using a membrane-diffusion model with depth dependent wall rock permeability. Rapid eruptive flux results in a decrease of chamber and conduit pressure, which leads to a critical deviatoric stress condition at the conduit wall. Analogous stress distributions have been analyzed for wellbores, where much work has been directed at determining conditions that lead to wellbore failure using Mohr-Coulomb failure theory. We extend this framework to cylindrical volcanic conduits, where large deviatoric stresses can develop co-eruptively leading to multiple distinct failure regimes depending on principal stress orientations. These failure regimes are categorized and possible implications for conduit flow are discussed, including cessation of eruption.

Fatigue life prediction of liquid rocket engine combustor with subscale test verification

NASA Astrophysics Data System (ADS)

Sung, In-Kyung

Reusable rocket systems such as the Space Shuttle introduced a new era in propulsion system design for economic feasibility. Practical reusable systems require an order of magnitude increase in life. To achieve this improved methods are needed to assess failure mechanisms and to predict life cycles of rocket combustor. A general goal of the research was to demonstrate the use of subscale rocket combustor prototype in a cost-effective test program. Life limiting factors and metal behaviors under repeated loads were surveyed and reviewed. The life prediction theories are presented, with an emphasis on studies that used subscale test hardware for model validation. From this review, low cycle fatigue (LCF) and creep-fatigue interaction (ratcheting) were identified as the main life limiting factors of the combustor. Several life prediction methods such as conventional and advanced viscoplastic models were used to predict life cycle due to low cycle thermal stress, transient effects, and creep rupture damage. Creep-fatigue interaction and cyclic hardening were also investigated. A prediction method based on 2D beam theory was modified using 3D plate deformation theory to provide an extended prediction method. For experimental validation two small scale annular plug nozzle thrusters were designed, built and tested. The test article was composed of a water-cooled liner, plug annular nozzle and 200 psia precombustor that used decomposed hydrogen peroxide as the oxidizer and JP-8 as the fuel. The first combustor was tested cyclically at the Advanced Propellants and Combustion Laboratory at Purdue University. Testing was stopped after 140 cycles due to an unpredicted failure mechanism due to an increasing hot spot in the location where failure was predicted. A second combustor was designed to avoid the previous failure, however, it was over pressurized and deformed beyond repair during cold-flow test. The test results are discussed and compared to the analytical and numerical predictions. A detailed comparison was not performed, however, due to the lack of test data resulting from a failure of the test article. Some theoretical and experimental aspects such as fin effect and round corner were found to reduce the discrepancy between prediction and test results.

Final Report: System Reliability Model for Solid-State Lighting (SSL) Luminaires

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, J. Lynn

2017-05-31

The primary objectives of this project was to develop and validate reliability models and accelerated stress testing (AST) methodologies for predicting the lifetime of integrated SSL luminaires. This study examined the likely failure modes for SSL luminaires including abrupt failure, excessive lumen depreciation, unacceptable color shifts, and increased power consumption. Data on the relative distribution of these failure modes were acquired through extensive accelerated stress tests and combined with industry data and other source of information on LED lighting. This data was compiled and utilized to build models of the aging behavior of key luminaire optical and electrical components.

Predictors of Success and Failure for ADN Students on the NCLEX-RN

ERIC Educational Resources Information Center

Benefiel, Diane

2011-01-01

The purpose of this study was to: 1) analyze the relationship of preprogram and nursing program variables on National Council Licensure Examination for Registered Nurses (NCLEX-RN) success and failure, and 2) develop a model to predict success and failure on the NCLEX-RN. The convenience sample was comprised of 245 spring, summer, and fall midterm…

Determination of fiber-matrix interface failure parameters from off-axis tests

NASA Technical Reports Server (NTRS)

Naik, Rajiv A.; Crews, John H., Jr.

1993-01-01

Critical fiber-matrix (FM) interface strength parameters were determined using a micromechanics-based approach together with failure data from off-axis tension (OAT) tests. The ply stresses at failure for a range of off-axis angles were used as input to a micromechanics analysis that was performed using the personal computer-based MICSTRAN code. FM interface stresses at the failure loads were calculated for both the square and the diamond array models. A simple procedure was developed to determine which array had the more severe FM interface stresses and the location of these critical stresses on the interface. For the cases analyzed, critical FM interface stresses were found to occur with the square array model and were located at a point where adjacent fibers were closest together. The critical FM interface stresses were used together with the Tsai-Wu failure theory to determine a failure criterion for the FM interface. This criterion was then used to predict the onset of ply cracking in angle-ply laminates for a range of laminate angles. Predictions for the onset of ply cracking in angle-ply laminates agreed with the test data trends.

Developing a Model for Identifying Students at Risk of Failure in a First Year Accounting Unit

ERIC Educational Resources Information Center

Smith, Malcolm; Therry, Len; Whale, Jacqui

2012-01-01

This paper reports on the process involved in attempting to build a predictive model capable of identifying students at risk of failure in a first year accounting unit in an Australian university. Identifying attributes that contribute to students being at risk can lead to the development of appropriate intervention strategies and support…

Using automated texture features to determine the probability for masking of a tumor on mammography, but not ultrasound.

PubMed

Häberle, Lothar; Hack, Carolin C; Heusinger, Katharina; Wagner, Florian; Jud, Sebastian M; Uder, Michael; Beckmann, Matthias W; Schulz-Wendtland, Rüdiger; Wittenberg, Thomas; Fasching, Peter A

2017-08-30

Tumors in radiologically dense breast were overlooked on mammograms more often than tumors in low-density breasts. A fast reproducible and automated method of assessing percentage mammographic density (PMD) would be desirable to support decisions whether ultrasonography should be provided for women in addition to mammography in diagnostic mammography units. PMD assessment has still not been included in clinical routine work, as there are issues of interobserver variability and the procedure is quite time consuming. This study investigated whether fully automatically generated texture features of mammograms can replace time-consuming semi-automatic PMD assessment to predict a patient's risk of having an invasive breast tumor that is visible on ultrasound but masked on mammography (mammography failure). This observational study included 1334 women with invasive breast cancer treated at a hospital-based diagnostic mammography unit. Ultrasound was available for the entire cohort as part of routine diagnosis. Computer-based threshold PMD assessments ("observed PMD") were carried out and 363 texture features were obtained from each mammogram. Several variable selection and regression techniques (univariate selection, lasso, boosting, random forest) were applied to predict PMD from the texture features. The predicted PMD values were each used as new predictor for masking in logistic regression models together with clinical predictors. These four logistic regression models with predicted PMD were compared among themselves and with a logistic regression model with observed PMD. The most accurate masking prediction was determined by cross-validation. About 120 of the 363 texture features were selected for predicting PMD. Density predictions with boosting were the best substitute for observed PMD to predict masking. Overall, the corresponding logistic regression model performed better (cross-validated AUC, 0.747) than one without mammographic density (0.734), but less well than the one with the observed PMD (0.753). However, in patients with an assigned mammography failure risk >10%, covering about half of all masked tumors, the boosting-based model performed at least as accurately as the original PMD model. Automatically generated texture features can replace semi-automatically determined PMD in a prediction model for mammography failure, such that more than 50% of masked tumors could be discovered.

DOES GARP REALLY FAIL MISERABLY? A RESPONSE TO STOCKMAN ET AL. (2006)

EPA Science Inventory

Stockman et al. (2006) found that ecological niche models built using DesktopGARP 'failed miserably' to predict trapdoor spider (genus Promyrmekiaphila) distributions in California. This apparent failure of GARP (Genetic Algorithm for Rule-Set Production) was actually a failure ...

A Thermal Runaway Failure Model for Low-Voltage BME Ceramic Capacitors with Defects

NASA Technical Reports Server (NTRS)

Teverovsky, Alexander

2017-01-01

Reliability of base metal electrode (BME) multilayer ceramic capacitors (MLCCs) that until recently were used mostly in commercial applications, have been improved substantially by using new materials and processes. Currently, the inception of intrinsic wear-out failures in high quality capacitors became much greater than the mission duration in most high-reliability applications. However, in capacitors with defects degradation processes might accelerate substantially and cause infant mortality failures. In this work, a physical model that relates the presence of defects to reduction of breakdown voltages and decreasing times to failure has been suggested. The effect of the defect size has been analyzed using a thermal runaway model of failures. Adequacy of highly accelerated life testing (HALT) to predict reliability at normal operating conditions and limitations of voltage acceleration are considered. The applicability of the model to BME capacitors with cracks is discussed and validated experimentally.

Numerical Predictions of Damage and Failure in Carbon Fiber Reinforced Laminates Using a Thermodynamically-Based Work Potential Theory

NASA Technical Reports Server (NTRS)

Pineda, Evan Jorge; Waas, Anthony M.

2013-01-01

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, referred to as enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Consistent characteristic lengths are introduced into the formulation to govern the evolution of the failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs are derived. The theory is implemented into a commercial finite element code. The model is verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared against the experimental results.

A Computational Comparison of High Strain Rate Strength and Failure Models for Glass

DTIC Science & Technology

2012-11-05

many researchers, however accuracy across a broad range of impact conditions is still not always achievable. Glasses , including soda - lime - silica ...plug/cone failure appearance when testing soda - lime - silica glass (see Fig. 5 from Ref. [7]). He notes that at 60 µs, the plug begins to break up and...material model. Although the JH-2 model has been adapated to provide reasonably accurate predictions for soda - lime glass , the Holmquist-Johnson model

Applying the Seattle Heart Failure Model in the Office Setting in the Era of Electronic Medical Records.

PubMed

Williams, Brent A; Agarwal, Shikhar

2018-02-23

Prediction models such as the Seattle Heart Failure Model (SHFM) can help guide management of heart failure (HF) patients, but the SHFM has not been validated in the office environment. This retrospective cohort study assessed the predictive performance of the SHFM among patients with new or pre-existing HF in the context of an office visit.Methods and Results:SHFM elements were ascertained through electronic medical records at an office visit. The primary outcome was all-cause mortality. A "warranty period" for the baseline SHFM risk estimate was sought by examining predictive performance over time through a series of landmark analyses. Discrimination and calibration were estimated according to the proposed warranty period. Low- and high-risk thresholds were proposed based on the distribution of SHFM estimates. Among 26,851 HF patients, 14,380 (54%) died over a mean 4.7-year follow-up period. The SHFM lost predictive performance over time, with C=0.69 and C<0.65 within 3 and beyond 12 months from baseline respectively. The diminishing predictive value was attributed to modifiable SHFM elements. Discrimination (C=0.66) and calibration for 12-month mortality were acceptable. A low-risk threshold of ∼5% mortality risk within 12 months reflects the 10% of HF patients in the office setting with the lowest risk. The SHFM has utility in the office environment.

Progressive Failure Analysis of Composite Stiffened Panels

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Yarrington, Phillip W.; Collier, Craig S.; Arnold, Steven M.

2006-01-01

A new progressive failure analysis capability for stiffened composite panels has been developed based on the combination of the HyperSizer stiffened panel design/analysis/optimization software with the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). MAC/GMC discretizes a composite material s microstructure into a number of subvolumes and solves for the stress and strain state in each while providing the homogenized composite properties as well. As a result, local failure criteria may be employed to predict local subvolume failure and the effects of these local failures on the overall composite response. When combined with HyperSizer, MAC/GMC is employed to represent the ply level composite material response within the laminates that constitute a stiffened panel. The effects of local subvolume failures can then be tracked as loading on the stiffened panel progresses. Sample progressive failure results are presented at both the composite laminate and the composite stiffened panel levels. Deformation and failure model predictions are compared with experimental data from the World Wide Failure Exercise for AS4/3501-6 graphite/epoxy laminates.

Some effects of thermal-cycle-induced deformation in rocket thrust chambers

NASA Technical Reports Server (NTRS)

Hannum, N. P.; Price, R. G., Jr.

1981-01-01

The deformation process observed in the hot gas side wall of rocket combustion chambers was investigaged for three different liner materials. Five thrust chambers were cycled to failure by using hydrogen and oxygen as propellants at a chamber pressure of 4.14 MN/cu m. The deformation was observed nondestructively at midlife points and destructively after failure occurred. The cyclic life results are presented with an accompanying discussion about the problems of life prediction associated with the types of failures encountered in the present work. Data indicating the deformation of the thrust chamber liner as cycles are accumulated are presented for each of the test thrust chambers. From these deformation data and observation of the failure sites it is evident that modeling the failure process as classic low cycle thermal fatigue is inadequate as a life prediction method.

The prehospital intravenous access assessment: a prospective study on intravenous access failure and access delay in prehospital emergency medicine.

PubMed

Prottengeier, Johannes; Albermann, Matthias; Heinrich, Sebastian; Birkholz, Torsten; Gall, Christine; Schmidt, Joachim

2016-12-01

Intravenous access in prehospital emergency care allows for early administration of medication and extended measures such as anaesthesia. Cannulation may, however, be difficult, and failure and resulting delay in treatment and transport may have negative effects on the patient. Therefore, our study aims to perform a concise assessment of the difficulties of prehospital venous cannulation. We analysed 23 candidate predictor variables on peripheral venous cannulations in terms of cannulation failure and exceedance of a 2 min time threshold. Multivariate logistic regression models were fitted for variables of predictive value (P<0.25) and evaluated by the area under the curve (AUC>0.6) of their respective receiver operating characteristic curve. A total of 762 intravenous cannulations were enroled. In all, 22% of punctures failed on the first attempt and 13% of punctures exceeded 2 min. Model selection yielded a three-factor model (vein visibility without tourniquet, vein palpability with tourniquet and insufficient ambient lighting) of fair accuracy for the prediction of puncture failure (AUC=0.76) and a structurally congruent model of four factors (failure model factors plus vein visibility with tourniquet) for the exceedance of the 2 min threshold (AUC=0.80). Our study offers a simple assessment to identify cases of difficult intravenous access in prehospital emergency care. Of the numerous factors subjectively perceived as possibly exerting influences on cannulation, only the universal - not exclusive to emergency care - factors of lighting, vein visibility and palpability proved to be valid predictors of cannulation failure and exceedance of a 2 min threshold.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 ismore » 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 been compared with the TM-21 model predictions and experimental data.« less

Implementing Lumberjacks and Black Swans Into Model-Based Tools to Support Human-Automation Interaction.

PubMed

Sebok, Angelia; Wickens, Christopher D

2017-03-01

The objectives were to (a) implement theoretical perspectives regarding human-automation interaction (HAI) into model-based tools to assist designers in developing systems that support effective performance and (b) conduct validations to assess the ability of the models to predict operator performance. Two key concepts in HAI, the lumberjack analogy and black swan events, have been studied extensively. The lumberjack analogy describes the effects of imperfect automation on operator performance. In routine operations, an increased degree of automation supports performance, but in failure conditions, increased automation results in more significantly impaired performance. Black swans are the rare and unexpected failures of imperfect automation. The lumberjack analogy and black swan concepts have been implemented into three model-based tools that predict operator performance in different systems. These tools include a flight management system, a remotely controlled robotic arm, and an environmental process control system. Each modeling effort included a corresponding validation. In one validation, the software tool was used to compare three flight management system designs, which were ranked in the same order as predicted by subject matter experts. The second validation compared model-predicted operator complacency with empirical performance in the same conditions. The third validation compared model-predicted and empirically determined time to detect and repair faults in four automation conditions. The three model-based tools offer useful ways to predict operator performance in complex systems. The three tools offer ways to predict the effects of different automation designs on operator performance.

Predicting No-Shows in Radiology Using Regression Modeling of Data Available in the Electronic Medical Record.

PubMed

Harvey, H Benjamin; Liu, Catherine; Ai, Jing; Jaworsky, Cristina; Guerrier, Claude Emmanuel; Flores, Efren; Pianykh, Oleg

2017-10-01

To test whether data elements available in the electronic medical record (EMR) can be effectively leveraged to predict failure to attend a scheduled radiology examination. Using data from a large academic medical center, we identified all patients with a diagnostic imaging examination scheduled from January 1, 2016, to April 1, 2016, and determined whether the patient successfully attended the examination. Demographic, clinical, and health services utilization variables available in the EMR potentially relevant to examination attendance were recorded for each patient. We used descriptive statistics and logistic regression models to test whether these data elements could predict failure to attend a scheduled radiology examination. The predictive accuracy of the regression models were determined by calculating the area under the receiver operator curve. Among the 54,652 patient appointments with radiology examinations scheduled during the study period, 6.5% were no-shows. No-show rates were highest for the modalities of mammography and CT and lowest for PET and MRI. Logistic regression indicated that 16 of the 27 demographic, clinical, and health services utilization factors were significantly associated with failure to attend a scheduled radiology examination (P ≤ .05). Stepwise logistic regression analysis demonstrated that previous no-shows, days between scheduling and appointments, modality type, and insurance type were most strongly predictive of no-show. A model considering all 16 data elements had good ability to predict radiology no-shows (area under the receiver operator curve = 0.753). The predictive ability was similar or improved when these models were analyzed by modality. Patient and examination information readily available in the EMR can be successfully used to predict radiology no-shows. Moving forward, this information can be proactively leveraged to identify patients who might benefit from additional patient engagement through appointment reminders or other targeted interventions to avoid no-shows. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Modeling of damage driven fracture failure of fiber post-restored teeth.

PubMed

Xu, Binting; Wang, Yining; Li, Qing

2015-09-01

Mechanical failure of biomaterials, which can be initiated by either violent force, or progressive stress fatigue, is a serious issue. Great efforts have been made to improve the mechanical performances of dental restorations. Virtual simulation is a promising approach for biomechanical investigations, which presents significant advantages in improving efficiency than traditional in vivo/in vitro studies. Over the past few decades, a number of virtual studies have been conducted to investigate the biomechanical issues concerning dental biomaterials, but only with limited incorporation of brittle failure phenomena. Motivated by the contradictory findings between several finite element analyses and common clinical observations on the fracture resistance of post-restored teeth, this study aimed to provide an approach using numerical simulations for investigating the fracture failure process through a non-linear fracture mechanics model. The ability of this approach to predict fracture initiation and propagation in a complex biomechanical status based on the intrinsic material properties was investigated. Results of the virtual simulations matched the findings of experimental tests, in terms of the ultimate fracture failure strengths and predictive areas under risk of clinical failure. This study revealed that the failure of dental post-restored restorations is a typical damage-driven continuum-to-discrete process. This approach is anticipated to have ramifications not only for modeling fracture events, but also for the design and optimization of the mechanical properties of biomaterials for specific clinically determined requirements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting short-term mortality in advanced decompensated heart failure - role of the updated acute decompensated heart failure/N-terminal pro-B-type natriuretic Peptide risk score.

PubMed

Scrutinio, Domenico; Ammirati, Enrico; Passantino, Andrea; Guida, Pietro; D'Angelo, Luciana; Oliva, Fabrizio; Ciccone, Marco Matteo; Iacoviello, Massimo; Dentamaro, Ilaria; Santoro, Daniela; Lagioia, Rocco; Sarzi Braga, Simona; Guzzetti, Daniela; Frigerio, Maria

2015-01-01

The first few months after admission are the most vulnerable period in patients with acute decompensated heart failure (ADHF). We assessed the association of the updated ADHF/N-terminal pro-B-type natriuretic peptide (NT-proBNP) risk score with 90-day and in-hospital mortality in 701 patients admitted with advanced ADHF, defined as severe symptoms of worsening HF, severely depressed left ventricular ejection fraction, and the need for i.v. diuretic and/or inotropic drugs. A total of 15.7% of the patients died within 90 days of admission and 5.2% underwent ventricular assist device (VAD) implantation or urgent heart transplantation (UHT). The C-statistic of the ADHF/NT-proBNP risk score for 90-day mortality was 0.810 (95% CI: 0.769-0.852). Predicted and observed mortality rates were in close agreement. When the composite outcome of death/VAD/UHT at 90 days was considered, the C-statistic decreased to 0.741. During hospitalization, 7.6% of the patients died. The C-statistic for in-hospital mortality was 0.815 (95% CI: 0.761-0.868) and Hosmer-Lemeshow χ(2)=3.71 (P=0.716). The updated ADHF/NT-proBNP risk score outperformed the Acute Decompensated Heart Failure National Registry, the Organized Program to Initiate Lifesaving Treatment in Patients Hospitalized for Heart Failure, and the American Heart Association Get with the Guidelines Program predictive models. Updated ADHF/NT-proBNP risk score is a valuable tool for predicting short-term mortality in severe ADHF, outperforming existing inpatient predictive models.

Isolating the Role of Psychological Dysfunction in Smoking Cessation Failure: Relations of Personality and Psychopathology to Attaining Smoking Cessation Milestones

PubMed Central

Leventhal, Adam M.; Japuntich, Sandra J.; Piper, Megan E.; Jorenby, Douglas E.; Schlam, Tanya R.; Baker, Timothy B.

2012-01-01

Research exploring psychological dysfunction as a predictor of smoking cessation success may be limited by nonoptimal predictor variables (i.e., categorical psychodiagnostic measures vs. continuous personality-based manifestations of dysfunction) and imprecise outcomes (i.e., summative point prevalence abstinence vs. constituent cessation milestone measures). Accordingly, this study evaluated the unique and overlapping relations of broad-spectrum personality traits (positive emotionality, negative emotionality, and constraint) and past-year psychopathology (anxiety, mood, and substance use disorder) to point prevalence abstinence and three smoking cessation milestones: (1) initiating abstinence; (2) first lapse; and (3) transition from lapse to relapse. Participants were daily smokers (N=1365) enrolled in a smoking cessation treatment study. In single predictor regression models, each manifestation of internalizing dysfunction (lower positive emotionality, higher negative emotionality, and anxiety and mood disorder) predicted failure at one or more cessation milestone. In simultaneous predictor models, lower positive and higher negative emotionality significantly predicted failure to achieve milestones after controlling for psychopathology. Psychopathology did not predict any outcome when controlling for personality. Negative emotionality showed the most robust and consistent effects, significantly predicting failure to initiate abstinence, earlier lapse, and lower point prevalence abstinence rates. Substance use disorder and constraint did not predict cessation outcomes, and no single variable predicted lapse-to-relapse transition. These findings suggest that personality-related manifestations of internalizing dysfunction are more accurate markers of affective sources of relapse risk than mood and anxiety disorders. Further, individuals with high trait negative emotionality may require intensive intervention to promote the initiation and early maintenance of abstinence. PMID:22642858

Advanced composites structural concepts and materials technologies for primary aircraft structures: Structural response and failure analysis

NASA Technical Reports Server (NTRS)

Dorris, William J.; Hairr, John W.; Huang, Jui-Tien; Ingram, J. Edward; Shah, Bharat M.

1992-01-01

Non-linear analysis methods were adapted and incorporated in a finite element based DIAL code. These methods are necessary to evaluate the global response of a stiffened structure under combined in-plane and out-of-plane loading. These methods include the Arc Length method and target point analysis procedure. A new interface material model was implemented that can model elastic-plastic behavior of the bond adhesive. Direct application of this method is in skin/stiffener interface failure assessment. Addition of the AML (angle minus longitudinal or load) failure procedure and Hasin's failure criteria provides added capability in the failure predictions. Interactive Stiffened Panel Analysis modules were developed as interactive pre-and post-processors. Each module provides the means of performing self-initiated finite elements based analysis of primary structures such as a flat or curved stiffened panel; a corrugated flat sandwich panel; and a curved geodesic fuselage panel. This module brings finite element analysis into the design of composite structures without the requirement for the user to know much about the techniques and procedures needed to actually perform a finite element analysis from scratch. An interactive finite element code was developed to predict bolted joint strength considering material and geometrical non-linearity. The developed method conducts an ultimate strength failure analysis using a set of material degradation models.

Influence of yield surface curvature on the macroscopic yielding and ductile failure of isotropic porous plastic materials

NASA Astrophysics Data System (ADS)

Dæhli, Lars Edvard Bryhni; Morin, David; Børvik, Tore; Hopperstad, Odd Sture

2017-10-01

Numerical unit cell models of an approximative representative volume element for a porous ductile solid are utilized to investigate differences in the mechanical response between a quadratic and a non-quadratic matrix yield surface. A Hershey equivalent stress measure with two distinct values of the yield surface exponent is employed as the matrix description. Results from the unit cell calculations are further used to calibrate a heuristic extension of the Gurson model which incorporates effects of the third deviatoric stress invariant. An assessment of the porous plasticity model reveals its ability to describe the unit cell response to some extent, however underestimating the effect of the Lode parameter for the lower triaxiality ratios imposed in this study when compared to unit cell simulations. Ductile failure predictions by means of finite element simulations using a unit cell model that resembles an imperfection band are then conducted to examine how the non-quadratic matrix yield surface influences the failure strain as compared to the quadratic matrix yield surface. Further, strain localization predictions based on bifurcation analyses and imperfection band analyses are undertaken using the calibrated porous plasticity model. These simulations are then compared to the unit cell calculations in order to elucidate the differences between the various modelling strategies. The current study reveals that strain localization analyses using an imperfection band model and a spatially discretized unit cell are in reasonable agreement, while the bifurcation analyses predict higher strain levels at localization. Imperfection band analyses are finally used to calculate failure loci for the quadratic and the non-quadratic matrix yield surface under a wide range of loading conditions. The underlying matrix yield surface is demonstrated to have a pronounced influence on the onset of strain localization.

Peer Review of Launch Environments

NASA Technical Reports Server (NTRS)

Wilson, Timmy R.

2011-01-01

Catastrophic failures of launch vehicles during launch and ascent are currently modeled using equivalent trinitrotoluene (TNT) estimates. This approach tends to over-predict the blast effect with subsequent impact to launch vehicle and crew escape requirements. Bangham Engineering, located in Huntsville, Alabama, assembled a less-conservative model based on historical failure and test data coupled with physical models and estimates. This white paper summarizes NESC's peer review of the Bangham analytical work completed to date.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2018-06-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

Color Shift Failure Prediction for Phosphor-Converted White LEDs by Modeling Features of Spectral Power Distribution with a Nonlinear Filter Approach

PubMed Central

Mohamed, Moumouni Guero; Fan, Xuejun; Zhang, Guoqi; Pecht, Michael

2017-01-01

With the expanding application of light-emitting diodes (LEDs), the color quality of white LEDs has attracted much attention in several color-sensitive application fields, such as museum lighting, healthcare lighting and displays. Reliability concerns for white LEDs are changing from the luminous efficiency to color quality. However, most of the current available research on the reliability of LEDs is still focused on luminous flux depreciation rather than color shift failure. The spectral power distribution (SPD), defined as the radiant power distribution emitted by a light source at a range of visible wavelength, contains the most fundamental luminescence mechanisms of a light source. SPD is used as the quantitative inference of an LED’s optical characteristics, including color coordinates that are widely used to represent the color shift process. Thus, to model the color shift failure of white LEDs during aging, this paper first extracts the features of an SPD, representing the characteristics of blue LED chips and phosphors, by multi-peak curve-fitting and modeling them with statistical functions. Then, because the shift processes of extracted features in aged LEDs are always nonlinear, a nonlinear state-space model is then developed to predict the color shift failure time within a self-adaptive particle filter framework. The results show that: (1) the failure mechanisms of LEDs can be identified by analyzing the extracted features of SPD with statistical curve-fitting and (2) the developed method can dynamically and accurately predict the color coordinates, correlated color temperatures (CCTs), and color rendering indexes (CRIs) of phosphor-converted (pc)-white LEDs, and also can estimate the residual color life. PMID:28773176

Color Shift Failure Prediction for Phosphor-Converted White LEDs by Modeling Features of Spectral Power Distribution with a Nonlinear Filter Approach.

PubMed

Fan, Jiajie; Mohamed, Moumouni Guero; Qian, Cheng; Fan, Xuejun; Zhang, Guoqi; Pecht, Michael

2017-07-18

With the expanding application of light-emitting diodes (LEDs), the color quality of white LEDs has attracted much attention in several color-sensitive application fields, such as museum lighting, healthcare lighting and displays. Reliability concerns for white LEDs are changing from the luminous efficiency to color quality. However, most of the current available research on the reliability of LEDs is still focused on luminous flux depreciation rather than color shift failure. The spectral power distribution (SPD), defined as the radiant power distribution emitted by a light source at a range of visible wavelength, contains the most fundamental luminescence mechanisms of a light source. SPD is used as the quantitative inference of an LED's optical characteristics, including color coordinates that are widely used to represent the color shift process. Thus, to model the color shift failure of white LEDs during aging, this paper first extracts the features of an SPD, representing the characteristics of blue LED chips and phosphors, by multi-peak curve-fitting and modeling them with statistical functions. Then, because the shift processes of extracted features in aged LEDs are always nonlinear, a nonlinear state-space model is then developed to predict the color shift failure time within a self-adaptive particle filter framework. The results show that: (1) the failure mechanisms of LEDs can be identified by analyzing the extracted features of SPD with statistical curve-fitting and (2) the developed method can dynamically and accurately predict the color coordinates, correlated color temperatures (CCTs), and color rendering indexes (CRIs) of phosphor-converted (pc)-white LEDs, and also can estimate the residual color life.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2017-09-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

Multiscale Static Analysis of Notched and Unnotched Laminates Using the Generalized Method of Cells

NASA Technical Reports Server (NTRS)

Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.; Stier, Bertram; Hansen, Lucas; Bednarcyk, Brett A.; Waas, Anthony M.

2016-01-01

The generalized method of cells (GMC) is demonstrated to be a viable micromechanics tool for predicting the deformation and failure response of laminated composites, with and without notches, subjected to tensile and compressive static loading. Given the axial [0], transverse [90], and shear [+45/-45] response of a carbon/epoxy (IM7/977-3) system, the unnotched and notched behavior of three multidirectional layups (Layup 1: [0,45,90,-45](sub 2S), Layup 2: [0,60,0](sub 3S), and Layup 3: [30,60,90,-30, -60](sub 2S)) are predicted under both tensile and compressive static loading. Matrix nonlinearity is modeled in two ways. The first assumes all nonlinearity is due to anisotropic progressive damage of the matrix only, which is modeled, using the multiaxial mixed-mode continuum damage model (MMCDM) within GMC. The second utilizes matrix plasticity coupled with brittle final failure based on the maximum principle strain criteria to account for matrix nonlinearity and failure within the Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software multiscale framework. Both MMCDM and plasticity models incorporate brittle strain- and stress-based failure criteria for the fiber. Upon satisfaction of these criteria, the fiber properties are immediately reduced to a nominal value. The constitutive response for each constituent (fiber and matrix) is characterized using a combination of vendor data and the axial, transverse, and shear responses of unnotched laminates. Then, the capability of the multiscale methodology is assessed by performing blind predictions of the mentioned notched and unnotched composite laminates response under tensile and compressive loading. Tabulated data along with the detailed results (i.e., stress-strain curves as well as damage evolution states at various ratios of strain to failure) for all laminates are presented.

Degradation modeling of mid-power white-light LEDs by using Wiener process.

PubMed

Huang, Jianlin; Golubović, Dušan S; Koh, Sau; Yang, Daoguo; Li, Xiupeng; Fan, Xuejun; Zhang, G Q

2015-07-27

The IES standard TM-21-11 provides a guideline for lifetime prediction of LED devices. As it uses average normalized lumen maintenance data and performs non-linear regression for lifetime modeling, it cannot capture dynamic and random variation of the degradation process of LED devices. In addition, this method cannot capture the failure distribution, although it is much more relevant in reliability analysis. Furthermore, the TM-21-11 only considers lumen maintenance for lifetime prediction. Color shift, as another important performance characteristic of LED devices, may also render significant degradation during service life, even though the lumen maintenance has not reached the critical threshold. In this study, a modified Wiener process has been employed for the modeling of the degradation of LED devices. By using this method, dynamic and random variations, as well as the non-linear degradation behavior of LED devices, can be easily accounted for. With a mild assumption, the parameter estimation accuracy has been improved by including more information into the likelihood function while neglecting the dependency between the random variables. As a consequence, the mean time to failure (MTTF) has been obtained and shows comparable result with IES TM-21-11 predictions, indicating the feasibility of the proposed method. Finally, the cumulative failure distribution was presented corresponding to different combinations of lumen maintenance and color shift. The results demonstrate that a joint failure distribution of LED devices could be modeled by simply considering their lumen maintenance and color shift as two independent variables.

Predicting outcome on admission and post-admission for acetaminophen-induced acute liver failure using classification and regression tree models.

PubMed

Speiser, Jaime Lynn; Lee, William M; Karvellas, Constantine J

2015-01-01

Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients often presents significant challenges. King's College (KCC) has been validated on hospital admission, but little has been published on later phases of illness. We aimed to improve determinations of prognosis both at the time of and following admission for APAP-ALF using Classification and Regression Tree (CART) models. CART models were applied to US ALFSG registry data to predict 21-day death or liver transplant early (on admission) and post-admission (days 3-7) for 803 APAP-ALF patients enrolled 01/1998-09/2013. Accuracy in prediction of outcome (AC), sensitivity (SN), specificity (SP), and area under receiver-operating curve (AUROC) were compared between 3 models: KCC (INR, creatinine, coma grade, pH), CART analysis using only KCC variables (KCC-CART) and a CART model using new variables (NEW-CART). Traditional KCC yielded 69% AC, 90% SP, 27% SN, and 0.58 AUROC on admission, with similar performance post-admission. KCC-CART at admission offered predictive 66% AC, 65% SP, 67% SN, and 0.74 AUROC. Post-admission, KCC-CART had predictive 82% AC, 86% SP, 46% SN and 0.81 AUROC. NEW-CART models using MELD (Model for end stage liver disease), lactate and mechanical ventilation on admission yielded predictive 72% AC, 71% SP, 77% SN and AUROC 0.79. For later stages, NEW-CART (MELD, lactate, coma grade) offered predictive AC 86%, SP 91%, SN 46%, AUROC 0.73. CARTs offer simple prognostic models for APAP-ALF patients, which have higher AUROC and SN than KCC, with similar AC and negligibly worse SP. Admission and post-admission predictions were developed. • Prognostication in acetaminophen-induced acute liver failure (APAP-ALF) is challenging beyond admission • Little has been published regarding the use of King's College Criteria (KCC) beyond admission and KCC has shown limited sensitivity in subsequent studies • Classification and Regression Tree (CART) methodology allows the development of predictive models using binary splits and offers an intuitive method for predicting outcome, using processes familiar to clinicians • Data from the ALFSG registry suggested that CART prognosis models for the APAP population offer improved sensitivity and model performance over traditional regression-based KCC, while maintaining similar accuracy and negligibly worse specificity • KCC-CART models offered modest improvement over traditional KCC, with NEW-CART models performing better than KCC-CART particularly at late time points.

Predicting the velocity and azimuth of fragments generated by the range destruction or random failure of rocket casings and tankage

NASA Astrophysics Data System (ADS)

Eck, M.; Mukunda, M.

The proliferation of space vehicle launch sites and the projected utilization of these facilities portends an increase in the number of on-pad, ascent, and on-orbit solid-rocket motor (SRM) casings and liquid-rocket tanks which will randomly fail or will fail from range destruct actions. Beyond the obvious safety implications, these failures may have serious resource implications for mission system and facility planners. SRM-casing failures and liquid-rocket tankage failures result in the generation of large, high velocity fragments which may be serious threats to the safety of launch support personnel if proper bunkers and exclusion areas are not provided. In addition, these fragments may be indirect threats to the general public's safety if they encounter hazardous spacecraft payloads which have not been designed to withstand shrapnel of this caliber. They may also become threats to other spacecraft if, by failing on-orbit, they add to the ever increasing space-junk collision cross-section. Most prior attempts to assess the velocity of fragments from failed SRM casings have simply assigned the available chamber impulse to available casing and fuel mass and solved the resulting momentum balance for velocity. This method may predict a fragment velocity which is high or low by a factor of two depending on the ratio of fuel to casing mass extant at the time of failure. Recognizing the limitations of existing methods, the authors devised an analytical approach which properly partitions the available impulse to each major system-mass component. This approach uses the Physics International developed PISCES code to couple the forces generated by an Eulerian modeled gas flow field to a Lagrangian modeled fuel and casing system. The details of a predictive analytical modeling process as well as the development of normalized relations for momentum partition as a function of SRM burn time and initial geometry are discussed in this paper. Methods for applying similar modeling techniques to liquid-tankage-over-pressure failures are also discussed. These methods have been calibrated against observed SRM ascent failures and on-orbit tankage failures. Casing-quadrant sized fragments with velocities exceeding 100 m/s resulted from Titan 34D-SRM range destruct actions at 10 s mission elapsed time (MET). Casing-quadrant sized fragments with velocities of approx. 200 m/s resulted from STS-SRM range destruct actions at 110 s MET. Similar sized fragments for Ariane third stage and Delta second stage tankage were predicted to have maximum velocities of 260 and 480 m/s respectively. Good agreement was found between the predictions and observations for five specific events and it was concluded that the methods developed have good potential for use in predicting the fragmentation process of a number of generically similar casing and tankage systems.

Effect and clinical prediction of worsening renal function in acute decompensated heart failure.

PubMed

Breidthardt, Tobias; Socrates, Thenral; Noveanu, Markus; Klima, Theresia; Heinisch, Corinna; Reichlin, Tobias; Potocki, Mihael; Nowak, Albina; Tschung, Christopher; Arenja, Nisha; Bingisser, Roland; Mueller, Christian

2011-03-01

We aimed to establish the prevalence and effect of worsening renal function (WRF) on survival among patients with acute decompensated heart failure. Furthermore, we sought to establish a risk score for the prediction of WRF and externally validate the previously established Forman risk score. A total of 657 consecutive patients with acute decompensated heart failure presenting to the emergency department and undergoing serial creatinine measurements were enrolled. The potential of the clinical parameters at admission to predict WRF was assessed as the primary end point. The secondary end point was all-cause mortality at 360 days. Of the 657 patients, 136 (21%) developed WRF, and 220 patients had died during the first year. WRF was more common in the nonsurvivors (30% vs 41%, p = 0.03). Multivariate regression analysis found WRF to independently predict mortality (hazard ratio 1.92, p <0.01). In a single parameter model, previously diagnosed chronic kidney disease was the only independent predictor of WRF and achieved an area under the receiver operating characteristic curve of 0.60. After the inclusion of the blood gas analysis parameters into the model history of chronic kidney disease (hazard ratio 2.13, p = 0.03), outpatient diuretics (hazard ratio 5.75, p <0.01), and bicarbonate (hazard ratio 0.91, p <0.01) were all predictive of WRF. A risk score was developed using these predictors. On receiver operating characteristic curve analysis, the Forman and Basel prediction rules achieved an area under the curve of 0.65 and 0.71, respectively. In conclusion, WRF was common in patients with acute decompensated heart failure and was linked to significantly worse outcomes. However, the clinical parameters failed to adequately predict its occurrence, making a tailored therapy approach impossible. Copyright © 2011 Elsevier Inc. All rights reserved.

Prognostics using Engineering and Environmental Parameters as Applied to State of Health (SOH) Radionuclide Aerosol Sampler Analyzer (RASA) Real-Time Monitoring

NASA Astrophysics Data System (ADS)

Hutchenson, K. D.; Hartley-McBride, S.; Saults, T.; Schmidt, D. P.

2006-05-01

The International Monitoring System (IMS) is composed in part of radionuclide particulate and gas monitoring systems. Monitoring the operational status of these systems is an important aspect of nuclear weapon test monitoring. Quality data, process control techniques, and predictive models are necessary to detect and predict system component failures. Predicting failures in advance provides time to mitigate these failures, thus minimizing operational downtime. The Provisional Technical Secretariat (PTS) requires IMS radionuclide systems be operational 95 percent of the time. The United States National Data Center (US NDC) offers contributing components to the IMS. This effort focuses on the initial research and process development using prognostics for monitoring and predicting failures of the RASA two (2) days into the future. The predictions, using time series methods, are input to an expert decision system, called SHADES (State of Health Airflow and Detection Expert System). The results enable personnel to make informed judgments about the health of the RASA system. Data are read from a relational database, processed, and displayed to the user in a GIS as a prototype GUI. This procedure mimics the real time application process that could be implemented as an operational system, This initial proof-of-concept effort developed predictive models focused on RASA components for a single site (USP79). Future work shall include the incorporation of other RASA systems, as well as their environmental conditions that play a significant role in performance. Similarly, SHADES currently accommodates specific component behaviors at this one site. Future work shall also include important environmental variables that play an important part of the prediction algorithms.

Identification of failure type in corroded pipelines: a bayesian probabilistic approach.

PubMed

Breton, T; Sanchez-Gheno, J C; Alamilla, J L; Alvarez-Ramirez, J

2010-07-15

Spillover of hazardous materials from transport pipelines can lead to catastrophic events with serious and dangerous environmental impact, potential fire events and human fatalities. The problem is more serious for large pipelines when the construction material is under environmental corrosion conditions, as in the petroleum and gas industries. In this way, predictive models can provide a suitable framework for risk evaluation, maintenance policies and substitution procedure design that should be oriented to reduce increased hazards. This work proposes a bayesian probabilistic approach to identify and predict the type of failure (leakage or rupture) for steel pipelines under realistic corroding conditions. In the first step of the modeling process, the mechanical performance of the pipe is considered for establishing conditions under which either leakage or rupture failure can occur. In the second step, experimental burst tests are used to introduce a mean probabilistic boundary defining a region where the type of failure is uncertain. In the boundary vicinity, the failure discrimination is carried out with a probabilistic model where the events are considered as random variables. In turn, the model parameters are estimated with available experimental data and contrasted with a real catastrophic event, showing good discrimination capacity. The results are discussed in terms of policies oriented to inspection and maintenance of large-size pipelines in the oil and gas industry. 2010 Elsevier B.V. All rights reserved.

Predictive modeling for corrective maintenance of imaging devices from machine logs.

PubMed

Patil, Ravindra B; Patil, Meru A; Ravi, Vidya; Naik, Sarif

2017-07-01

In the cost sensitive healthcare industry, an unplanned downtime of diagnostic and therapy imaging devices can be a burden on the financials of both the hospitals as well as the original equipment manufacturers (OEMs). In the current era of connectivity, it is easier to get these devices connected to a standard monitoring station. Once the system is connected, OEMs can monitor the health of these devices remotely and take corrective actions by providing preventive maintenance thereby avoiding major unplanned downtime. In this article, we present an overall methodology of predicting failure of these devices well before customer experiences it. We use data-driven approach based on machine learning to predict failures in turn resulting in reduced machine downtime, improved customer satisfaction and cost savings for the OEMs. One of the use-case of predicting component failure of PHILIPS iXR system is explained in this article.

Pitfalls in Prediction Modeling for Normal Tissue Toxicity in Radiation Therapy: An Illustration With the Individual Radiation Sensitivity and Mammary Carcinoma Risk Factor Investigation Cohorts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mbah, Chamberlain, E-mail: chamberlain.mbah@ugent.be; Department of Mathematical Modeling, Statistics, and Bioinformatics, Faculty of Bioscience Engineering, Ghent University, Ghent; Thierens, Hubert

Purpose: To identify the main causes underlying the failure of prediction models for radiation therapy toxicity to replicate. Methods and Materials: Data were used from two German cohorts, Individual Radiation Sensitivity (ISE) (n=418) and Mammary Carcinoma Risk Factor Investigation (MARIE) (n=409), of breast cancer patients with similar characteristics and radiation therapy treatments. The toxicity endpoint chosen was telangiectasia. The LASSO (least absolute shrinkage and selection operator) logistic regression method was used to build a predictive model for a dichotomized endpoint (Radiation Therapy Oncology Group/European Organization for the Research and Treatment of Cancer score 0, 1, or ≥2). Internal areas undermore » the receiver operating characteristic curve (inAUCs) were calculated by a naïve approach whereby the training data (ISE) were also used for calculating the AUC. Cross-validation was also applied to calculate the AUC within the same cohort, a second type of inAUC. Internal AUCs from cross-validation were calculated within ISE and MARIE separately. Models trained on one dataset (ISE) were applied to a test dataset (MARIE) and AUCs calculated (exAUCs). Results: Internal AUCs from the naïve approach were generally larger than inAUCs from cross-validation owing to overfitting the training data. Internal AUCs from cross-validation were also generally larger than the exAUCs, reflecting heterogeneity in the predictors between cohorts. The best models with largest inAUCs from cross-validation within both cohorts had a number of common predictors: hypertension, normalized total boost, and presence of estrogen receptors. Surprisingly, the effect (coefficient in the prediction model) of hypertension on telangiectasia incidence was positive in ISE and negative in MARIE. Other predictors were also not common between the 2 cohorts, illustrating that overcoming overfitting does not solve the problem of replication failure of prediction models completely. Conclusions: Overfitting and cohort heterogeneity are the 2 main causes of replication failure of prediction models across cohorts. Cross-validation and similar techniques (eg, bootstrapping) cope with overfitting, but the development of validated predictive models for radiation therapy toxicity requires strategies that deal with cohort heterogeneity.« less

Biomarkers of myocardial stress and fibrosis as predictors of mode of death in patients with chronic heart failure.

PubMed

Ahmad, Tariq; Fiuzat, Mona; Neely, Benjamin; Neely, Megan L; Pencina, Michael J; Kraus, William E; Zannad, Faiez; Whellan, David J; Donahue, Mark P; Piña, Ileana L; Adams, Kirkwood F; Kitzman, Dalane W; O'Connor, Christopher M; Felker, G Michael

2014-06-01

The aim of this study was to determine whether biomarkers of myocardial stress and fibrosis improve prediction of the mode of death in patients with chronic heart failure. The 2 most common modes of death in patients with chronic heart failure are pump failure and sudden cardiac death. Prediction of the mode of death may facilitate treatment decisions. The relationship between amino-terminal pro-brain natriuretic peptide (NT-proBNP), galectin-3, and ST2, biomarkers that reflect different pathogenic pathways in heart failure (myocardial stress and fibrosis), and mode of death is unknown. HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) was a randomized controlled trial of exercise training versus usual care in patients with chronic heart failure due to left ventricular systolic dysfunction (left ventricular ejection fraction ≤35%). An independent clinical events committee prospectively adjudicated mode of death. NT-proBNP, galectin-3, and ST2 levels were assessed at baseline in 813 subjects. Associations between biomarkers and mode of death were assessed using cause-specific Cox proportional hazards modeling, and interaction testing was used to measure differential associations between biomarkers and pump failure versus sudden cardiac death. Discrimination and risk reclassification metrics were used to assess the added value of galectin-3 and ST2 in predicting mode of death risk beyond a clinical model that included NT-proBNP. After a median follow-up period of 2.5 years, there were 155 deaths: 49 from pump failure, 42 from sudden cardiac death, and 64 from other causes. Elevations in all biomarkers were associated with increased risk for both pump failure and sudden cardiac death in both adjusted and unadjusted analyses. In each case, increases in the biomarker had a stronger association with pump failure than sudden cardiac death, but this relationship was attenuated after adjustment for clinical risk factors. Clinical variables along with NT-proBNP levels were stronger predictors of pump failure (C statistic: 0.87) than sudden cardiac death (C statistic: 0.73). Addition of ST2 and galectin-3 led to improved net risk classification of 11% for sudden cardiac death, but not pump failure. Clinical predictors along with NT-proBNP levels were strong predictors of pump failure risk, with insignificant incremental contributions of ST2 and galectin-3. Predictability of sudden cardiac death risk was less robust and enhanced by information provided by novel biomarkers. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Evaluating the risk of water distribution system failure: A shared frailty model

NASA Astrophysics Data System (ADS)

Clark, Robert M.; Thurnau, Robert C.

2011-12-01

Condition assessment (CA) Modeling is drawing increasing interest as a technique that can assist in managing drinking water infrastructure. This paper develops a model based on the application of a Cox proportional hazard (PH)/shared frailty model and applies it to evaluating the risk of failure in drinking water networks using data from the Laramie Water Utility (located in Laramie, Wyoming, USA). Using the risk model a cost/ benefit analysis incorporating the inspection value method (IVM), is used to assist in making improved repair, replacement and rehabilitation decisions for selected drinking water distribution system pipes. A separate model is developed to predict failures in prestressed concrete cylinder pipe (PCCP). Various currently available inspection technologies are presented and discussed.

A Nonlinear Viscoelastic Model for Ceramics at High Temperatures

NASA Technical Reports Server (NTRS)

Powers, Lynn M.; Panoskaltsis, Vassilis P.; Gasparini, Dario A.; Choi, Sung R.

2002-01-01

High-temperature creep behavior of ceramics is characterized by nonlinear time-dependent responses, asymmetric behavior in tension and compression, and nucleation and coalescence of voids leading to creep rupture. Moreover, creep rupture experiments show considerable scatter or randomness in fatigue lives of nominally equal specimens. To capture the nonlinear, asymmetric time-dependent behavior, the standard linear viscoelastic solid model is modified. Nonlinearity and asymmetry are introduced in the volumetric components by using a nonlinear function similar to a hyperbolic sine function but modified to model asymmetry. The nonlinear viscoelastic model is implemented in an ABAQUS user material subroutine. To model the random formation and coalescence of voids, each element is assigned a failure strain sampled from a lognormal distribution. An element is deleted when its volumetric strain exceeds its failure strain. Element deletion has been implemented within ABAQUS. Temporal increases in strains produce a sequential loss of elements (a model for void nucleation and growth), which in turn leads to failure. Nonlinear viscoelastic model parameters are determined from uniaxial tensile and compressive creep experiments on silicon nitride. The model is then used to predict the deformation of four-point bending and ball-on-ring specimens. Simulation is used to predict statistical moments of creep rupture lives. Numerical simulation results compare well with results of experiments of four-point bending specimens. The analytical model is intended to be used to predict the creep rupture lives of ceramic parts in arbitrary stress conditions.

Creep failure of a reactor pressure vessel lower head under severe accident conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pilch, M.M.; Ludwigsen, J.S.; Chu, T.Y.

A severe accident in a nuclear power plant could result in the relocation of large quantities of molten core material onto the lower head of he reactor pressure vessel (RPV). In the absence of inherent cooling mechanisms, failure of the RPV ultimately becomes possible under the combined effects of system pressure and the thermal heat-up of the lower head. Sandia National Laboratories has performed seven experiments at 1:5th scale simulating creep failure of a RPV lower head. This paper describes a modeling program that complements the experimental program. Analyses have been performed using the general-purpose finite-element code ABAQUS-5.6. In ordermore » to make ABAQUS solve the specific problem at hand, a material constitutive model that utilizes temperature dependent properties has been developed and attached to ABAQUS-executable through its UMAT utility. Analyses of the LHF-1 experiment predict instability-type failure. Predicted strains are delayed relative to the observed strain histories. Parametric variations on either the yield stress, creep rate, or both (within the range of material property data) can bring predictions into agreement with experiment. The analysis indicates that it is necessary to conduct material property tests on the actual material used in the experimental program. The constitutive model employed in the present analyses is the subject of a separate publication.« less

A Generalized Orthotropic Elasto-Plastic Material Model for Impact Analysis

NASA Astrophysics Data System (ADS)

Hoffarth, Canio

Composite materials are now beginning to provide uses hitherto reserved for metals in structural systems such as airframes and engine containment systems, wraps for repair and rehabilitation, and ballistic/blast mitigation systems. These structural systems are often subjected to impact loads and there is a pressing need for accurate prediction of deformation, damage and failure. There are numerous material models that have been developed to analyze the dynamic impact response of polymer matrix composites. However, there are key features that are missing in those models that prevent them from providing accurate predictive capabilities. In this dissertation, a general purpose orthotropic elasto-plastic computational constitutive material model has been developed to predict the response of composites subjected to high velocity impacts. The constitutive model is divided into three components - deformation model, damage model and failure model, with failure to be added at a later date. The deformation model generalizes the Tsai-Wu failure criteria and extends it using a strain-hardening-based orthotropic yield function with a non-associative flow rule. A strain equivalent formulation is utilized in the damage model that permits plastic and damage calculations to be uncoupled and capture the nonlinear unloading and local softening of the stress-strain response. A diagonal damage tensor is defined to account for the directionally dependent variation of damage. However, in composites it has been found that loading in one direction can lead to damage in multiple coordinate directions. To account for this phenomena, the terms in the damage matrix are semi-coupled such that the damage in a particular coordinate direction is a function of the stresses and plastic strains in all of the coordinate directions. The overall framework is driven by experimental tabulated temperature and rate-dependent stress-strain data as well as data that characterizes the damage matrix and failure. The developed theory has been implemented in a commercial explicit finite element analysis code, LS-DYNARTM, as MAT213. Several verification and validation tests using a commonly available carbon-fiber composite, Toyobo's T800/F3900, have been carried and the results show that the theory and implementation are efficient, robust and accurate.

The failure of earthquake failure models

USGS Publications Warehouse

Gomberg, J.

2001-01-01

In this study I show that simple heuristic models and numerical calculations suggest that an entire class of commonly invoked models of earthquake failure processes cannot explain triggering of seismicity by transient or "dynamic" stress changes, such as stress changes associated with passing seismic waves. The models of this class have the common feature that the physical property characterizing failure increases at an accelerating rate when a fault is loaded (stressed) at a constant rate. Examples include models that invoke rate state friction or subcritical crack growth, in which the properties characterizing failure are slip or crack length, respectively. Failure occurs when the rate at which these grow accelerates to values exceeding some critical threshold. These accelerating failure models do not predict the finite durations of dynamically triggered earthquake sequences (e.g., at aftershock or remote distances). Some of the failure models belonging to this class have been used to explain static stress triggering of aftershocks. This may imply that the physical processes underlying dynamic triggering differs or that currently applied models of static triggering require modification. If the former is the case, we might appeal to physical mechanisms relying on oscillatory deformations such as compaction of saturated fault gouge leading to pore pressure increase, or cyclic fatigue. However, if dynamic and static triggering mechanisms differ, one still needs to ask why static triggering models that neglect these dynamic mechanisms appear to explain many observations. If the static and dynamic triggering mechanisms are the same, perhaps assumptions about accelerating failure and/or that triggering advances the failure times of a population of inevitable earthquakes are incorrect.

Prediction of hospital failure: a post-PPS analysis.

PubMed

Gardiner, L R; Oswald, S L; Jahera, J S

1996-01-01

This study investigates the ability of discriminant analysis to provide accurate predictions of hospital failure. Using data from the period following the introduction of the Prospective Payment System, we developed discriminant functions for each of two hospital ownership categories: not-for-profit and proprietary. The resulting discriminant models contain six and seven variables, respectively. For each ownership category, the variables represent four major aspects of financial health (liquidity, leverage, profitability, and efficiency) plus county marketshare and length of stay. The proportion of closed hospitals misclassified as open one year before closure does not exceed 0.05 for either ownership type. Our results show that discriminant functions based on a small set of financial and nonfinancial variables provide the capability to predict hospital failure reliably for both not-for-profit and proprietary hospitals.

Basic failure mechanisms in advanced composites

NASA Technical Reports Server (NTRS)

Mullin, J. V.; Mazzio, V. F.; Mehan, R. L.

1972-01-01

Failure mechanisms in carbon-epoxy composites are identified as a basis for more reliable prediction of the performance of these materials. The approach involves both the study of local fracture events in model specimens containing small groups of filaments and fractographic examination of high fiber content engineering composites. Emphasis is placed on the correlation of model specimen observations with gross fracture modes. The effects of fiber surface treatment, resin modification and fiber content are studied and acoustic emission methods are applied. Some effort is devoted to analysis of the failure process in composite/metal specimens.

Survival Predictions of Ceramic Crowns Using Statistical Fracture Mechanics

PubMed Central

Nasrin, S.; Katsube, N.; Seghi, R.R.; Rokhlin, S.I.

2017-01-01

This work establishes a survival probability methodology for interface-initiated fatigue failures of monolithic ceramic crowns under simulated masticatory loading. A complete 3-dimensional (3D) finite element analysis model of a minimally reduced molar crown was developed using commercially available hardware and software. Estimates of material surface flaw distributions and fatigue parameters for 3 reinforced glass-ceramics (fluormica [FM], leucite [LR], and lithium disilicate [LD]) and a dense sintered yttrium-stabilized zirconia (YZ) were obtained from the literature and incorporated into the model. Utilizing the proposed fracture mechanics–based model, crown survival probability as a function of loading cycles was obtained from simulations performed on the 4 ceramic materials utilizing identical crown geometries and loading conditions. The weaker ceramic materials (FM and LR) resulted in lower survival rates than the more recently developed higher-strength ceramic materials (LD and YZ). The simulated 10-y survival rate of crowns fabricated from YZ was only slightly better than those fabricated from LD. In addition, 2 of the model crown systems (FM and LD) were expanded to determine regional-dependent failure probabilities. This analysis predicted that the LD-based crowns were more likely to fail from fractures initiating from margin areas, whereas the FM-based crowns showed a slightly higher probability of failure from fractures initiating from the occlusal table below the contact areas. These 2 predicted fracture initiation locations have some agreement with reported fractographic analyses of failed crowns. In this model, we considered the maximum tensile stress tangential to the interfacial surface, as opposed to the more universally reported maximum principal stress, because it more directly impacts crack propagation. While the accuracy of these predictions needs to be experimentally verified, the model can provide a fundamental understanding of the importance that pre-existing flaws at the intaglio surface have on fatigue failures. PMID:28107637

Test and Analysis Correlation for a Y-Joint Specimen for a Composite Cryotank

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Sleight, David W.; Grenoble, Ray

2015-01-01

The Composite Cryotank Technology Demonstration (CCTD) project under NASA's Game Changing Development Program (GCDP) developed space technologies using advanced composite materials. Under CCTD, NASA funded the Boeing Company to design and test a number of element-level joint specimens as a precursor to a 2.4-m diameter composite cryotank. Preliminary analyses indicated that the y-joint in the cryotank had low margins of safety; hence the y-joint was considered to be a critical design region. The y-joint design includes a softening strip wedge to reduce localized shear stresses at the skirt/dome interface. In this paper, NASA-developed analytical models will be correlated with the experimental results of a series of positive-peel y-joint specimens from Boeing tests. Initial analytical models over-predicted the experimental strain gage readings in the far-field region by approximately 10%. The over-prediction was attributed to uncertainty in the elastic properties of the laminate and a mismatch between the thermal expansion of the strain gages and the laminate. The elastic properties of the analytical model were adjusted to account for the strain gage differences. The experimental strain gages also indicated a large non-linear effect in the softening strip region that was not predicted by the analytical model. This non-linear effect was attributed to delamination initiating in the softening strip region at below 20% of the failure load for the specimen. Because the specimen was contained in a thermally insulated box during cryogenic testing to failure, delamination initiation and progression was not visualized during the test. Several possible failure initiation locations were investigated, and a most likely failure scenario was determined that correlated well with the experimental data. The most likely failure scenario corresponded to damage initiating in the softening strip and delamination extending to the grips at final failure.

Assessment of compressive failure process of cortical bone materials using damage-based model.

PubMed

Ng, Theng Pin; R Koloor, S S; Djuansjah, J R P; Abdul Kadir, M R

2017-02-01

The main failure factors of cortical bone are aging or osteoporosis, accident and high energy trauma or physiological activities. However, the mechanism of damage evolution coupled with yield criterion is considered as one of the unclear subjects in failure analysis of cortical bone materials. Therefore, this study attempts to assess the structural response and progressive failure process of cortical bone using a brittle damaged plasticity model. For this reason, several compressive tests are performed on cortical bone specimens made of bovine femur, in order to obtain the structural response and mechanical properties of the material. Complementary finite element (FE) model of the sample and test is prepared to simulate the elastic-to-damage behavior of the cortical bone using the brittle damaged plasticity model. The FE model is validated in a comparative method using the predicted and measured structural response as load-compressive displacement through simulation and experiment. FE results indicated that the compressive damage initiated and propagated at central region where maximum equivalent plastic strain is computed, which coincided with the degradation of structural compressive stiffness followed by a vast amount of strain energy dissipation. The parameter of compressive damage rate, which is a function dependent on damage parameter and the plastic strain is examined for different rates. Results show that considering a similar rate to the initial slope of the damage parameter in the experiment would give a better sense for prediction of compressive failure. Copyright © 2016 Elsevier Ltd. All rights reserved.

High-Fidelity Multi-Rotor Unmanned Aircraft System Simulation Development for Trajectory Prediction Under Off-Nominal Flight Dynamics

NASA Technical Reports Server (NTRS)

Foster, John V.; Hartman, David C.

2017-01-01

The NASA Unmanned Aircraft System (UAS) Traffic Management (UTM) project is conducting research to enable civilian low-altitude airspace and UAS operations. A goal of this project is to develop probabilistic methods to quantify risk during failures and off nominal flight conditions. An important part of this effort is the reliable prediction of feasible trajectories during off-nominal events such as control failure, atmospheric upsets, or navigation anomalies that can cause large deviations from the intended flight path or extreme vehicle upsets beyond the normal flight envelope. Few examples of high-fidelity modeling and prediction of off-nominal behavior for small UAS (sUAS) vehicles exist, and modeling requirements for accurately predicting flight dynamics for out-of-envelope or failure conditions are essentially undefined. In addition, the broad range of sUAS aircraft configurations already being fielded presents a significant modeling challenge, as these vehicles are often very different from one another and are likely to possess dramatically different flight dynamics and resultant trajectories and may require different modeling approaches to capture off-nominal behavior. NASA has undertaken an extensive research effort to define sUAS flight dynamics modeling requirements and develop preliminary high fidelity six degree-of-freedom (6-DOF) simulations capable of more closely predicting off-nominal flight dynamics and trajectories. This research has included a literature review of existing sUAS modeling and simulation work as well as development of experimental testing methods to measure and model key components of propulsion, airframe and control characteristics. The ultimate objective of these efforts is to develop tools to support UTM risk analyses and for the real-time prediction of off-nominal trajectories for use in the UTM Risk Assessment Framework (URAF). This paper focuses on modeling and simulation efforts for a generic quad-rotor configuration typical of many commercial vehicles in use today. An overview of relevant off-nominal multi-rotor behaviors will be presented to define modeling goals and to identify the prediction capability lacking in simplified models of multi-rotor performance. A description of recent NASA wind tunnel testing of multi-rotor propulsion and airframe components will be presented illustrating important experimental and data acquisition methods, and a description of preliminary propulsion and airframe models will be presented. Lastly, examples of predicted off-nominal flight dynamics and trajectories from the simulation will be presented.

Hybrid neural intelligent system to predict business failure in small-to-medium-size enterprises.

PubMed

Borrajo, M Lourdes; Baruque, Bruno; Corchado, Emilio; Bajo, Javier; Corchado, Juan M

2011-08-01

During the last years there has been a growing need of developing innovative tools that can help small to medium sized enterprises to predict business failure as well as financial crisis. In this study we present a novel hybrid intelligent system aimed at monitoring the modus operandi of the companies and predicting possible failures. This system is implemented by means of a neural-based multi-agent system that models the different actors of the companies as agents. The core of the multi-agent system is a type of agent that incorporates a case-based reasoning system and automates the business control process and failure prediction. The stages of the case-based reasoning system are implemented by means of web services: the retrieval stage uses an innovative weighted voting summarization of self-organizing maps ensembles-based method and the reuse stage is implemented by means of a radial basis function neural network. An initial prototype was developed and the results obtained related to small and medium enterprises in a real scenario are presented.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 3: Structure and listing of programs

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Personality traits and achievement motives: theoretical and empirical relations between the NEO Personality Inventory-Revised and the Achievement Motives Scale.

PubMed

Diseth, Age; Martinsen, Øyvind

2009-04-01

Theoretical and empirical relations between personality traits and motive dispositions were investigated by comparing scores of 315 undergraduate psychology students on the NEO Personality Inventory-Revised and the Achievement Motives Scale. Analyses showed all NEO Personality Inventory-Revised factors except agreeableness were significantly correlated with the motive for success and the motive to avoid failure. A structural equation model showed that motive for success was predicted by Extraversion, Openness, Conscientiousness, and Neuroticism (negative relation), and motive to avoid failure was predicted by Neuroticism and Openness (negative relation). Although both achievement motives were predicted by several personality factors, motive for success was most strongly predicted by Openness, and motive to avoid failure was most strongly predicted by neuroticism. These findings extended previous research on the relations of personality traits and achievement motives and provided a basis for the discussion of motive dispositions in personality. The results also added to the construct validity of the Achievement Motives Scale.

Prediction of Muscle Performance During Dynamic Repetitive Exercise

NASA Technical Reports Server (NTRS)

Byerly, D. L.; Byerly, K. A.; Sognier, M. A.; Squires, W. G.

2002-01-01

A method for predicting human muscle performance was developed. Eight test subjects performed a repetitive dynamic exercise to failure using a Lordex spinal machine. Electromyography (EMG) data was collected from the erector spinae. Evaluation of the EMG data using a 5th order Autoregressive (AR) model and statistical regression analysis revealed that an AR parameter, the mean average magnitude of AR poles, can predict performance to failure as early as the second repetition of the exercise. Potential applications to the space program include evaluating on-orbit countermeasure effectiveness, maximizing post-flight recovery, and future real-time monitoring capability during Extravehicular Activity.

AGR-5/6/7 Irradiation Test Predictions using PARFUME

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skerjanc, William F.

PARFUME, (PARticle FUel ModEl) a fuel performance modeling code used for high temperature gas-cooled reactors (HTGRs), was used to model the Advanced Gas Reactor (AGR)-5/6/7 irradiation test using predicted physics and thermal hydraulics data. The AGR-5/6/7 test consists of the combined fifth, sixth, and seventh planned irradiations of the AGR Fuel Development and Qualification Program. The AGR-5/6/7 test train is a multi-capsule, instrumented experiment that is designed for irradiation in the 133.4-mm diameter north east flux trap (NEFT) position of Advanced Test Reactor (ATR). Each capsule contains compacts filled with uranium oxycarbide (UCO) unaltered fuel particles. This report documents themore » calculations performed to predict the failure probability of tristructural isotropic (TRISO)-coated fuel particles during the AGR-5/6/7 experiment. In addition, this report documents the calculated source term from the driver fuel. The calculations include modeling of the AGR-5/6/7 irradiation that is scheduled to occur from October 2017 to April 2021 over a total of 13 ATR cycles, including nine normal cycles and four Power Axial Locator Mechanism (PALM) cycle for a total between 500 – 550 effective full power days (EFPD). The irradiation conditions and material properties of the AGR-5/6/7 test predicted zero fuel particle failures in Capsules 1, 2, and 4. Fuel particle failures were predicted in Capsule 3 due to internal particle pressure. These failures were predicted in the highest temperature compacts. Capsule 5 fuel particle failures were due to inner pyrolytic carbon (IPyC) cracking causing localized stresses concentrations in the SiC layer. This capsule predicted the highest particle failures due to the lower irradiation temperature. In addition, shrinkage of the buffer and IPyC layer during irradiation resulted in formation of a buffer-IPyC gap. The two capsules at the two ends of the test train, Capsules 1 and 5 experienced the smallest buffer-IPyC gap formation due to the lower irradiation fluences and temperatures. Capsule 3 experienced the largest buffer-IPyC gap formation of just under 24 µm. The release fraction of fission products Ag, Cs, and Sr silver (Ag), cesium (Cs), and strontium (Sr) vary depending on capsule location and irradiation temperature. The maximum release fraction of Ag occurs in Capsule 3, reaching up to 84.8% for the TRISO fuel particles. The release fraction of the other two fission products, Cs and Sr are much smaller and, in most cases, less than 1%. The notable exception is again in Capsule 3, where the release fraction for Cs and Sr reach up to 9.7% and 19.1%, respectively.« less

Predicting effects of structural stress in a genome-reduced model bacterial metabolism

NASA Astrophysics Data System (ADS)

Güell, Oriol; Sagués, Francesc; Serrano, M. Ángeles

2012-08-01

Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

A Probabilistic Model for Predicting Attenuation of Viruses During Percolation in Unsaturated Natural Barriers

NASA Astrophysics Data System (ADS)

Faulkner, B. R.; Lyon, W. G.

2001-12-01

We present a probabilistic model for predicting virus attenuation. The solution employs the assumption of complete mixing. Monte Carlo methods are used to generate ensemble simulations of virus attenuation due to physical, biological, and chemical factors. The model generates a probability of failure to achieve 4-log attenuation. We tabulated data from related studies to develop probability density functions for input parameters, and utilized a database of soil hydraulic parameters based on the 12 USDA soil categories. Regulators can use the model based on limited information such as boring logs, climate data, and soil survey reports for a particular site of interest. Plackett-Burman sensitivity analysis indicated the most important main effects on probability of failure to achieve 4-log attenuation in our model were mean logarithm of saturated hydraulic conductivity (+0.396), mean water content (+0.203), mean solid-water mass transfer coefficient (-0.147), and the mean solid-water equilibrium partitioning coefficient (-0.144). Using the model, we predicted the probability of failure of a one-meter thick proposed hydrogeologic barrier and a water content of 0.3. With the currently available data and the associated uncertainty, we predicted soils classified as sand would fail (p=0.999), silt loams would also fail (p=0.292), but soils classified as clays would provide the required 4-log attenuation (p=0.001). The model is extendible in the sense that probability density functions of parameters can be modified as future studies refine the uncertainty, and the lightweight object-oriented design of the computer model (implemented in Java) will facilitate reuse with modified classes. This is an abstract of a proposed presentation and does not necessarily reflect EPA policy.

3D Microstructures for Materials and Damage Models

DOE PAGES

Livescu, Veronica; Bronkhorst, Curt Allan; Vander Wiel, Scott Alan

2017-02-01

Many challenges exist with regard to understanding and representing complex physical processes involved with ductile damage and failure in polycrystalline metallic materials. Currently, the ability to accurately predict the macroscale ductile damage and failure response of metallic materials is lacking. Research at Los Alamos National Laboratory (LANL) is aimed at building a coupled experimental and computational methodology that supports the development of predictive damage capabilities by: capturing real distributions of microstructural features from real material and implementing them as digitally generated microstructures in damage model development; and, distilling structure-property information to link microstructural details to damage evolution under a multitudemore » of loading states.« less

Failure analysis of single-bolted joint for lightweight composite laminates and metal plate

NASA Astrophysics Data System (ADS)

Li, Linjie; Qu, Junli; Liu, Xiangdong

2018-01-01

A three-dimensional progressive damage model was developed in ANSYS to predict the damage accumulation of single bolted joint in composite laminates under in-plane tensile loading. First, we describe the formulation and algorithm of this model. Second, we calculate the failure loads of the joint in fibre reinforced epoxy laminated composite plates and compare it with the experiment results, which validates that our model can appropriately simulate the ultimate tensile strength of the joints and the whole process of failure of structure. Finally, this model is applied to study the failure process of the light-weight composite material (USN125). The study also has a great potential to provide a strong basis for bolted joints design in composite Laminates as well as a simple tool for comparing different laminate geometries and bolt arrangements.

Psychological distress and in vitro fertilization outcome

PubMed Central

Pasch, Lauri A.; Gregorich, Steven E.; Katz, Patricia K.; Millstein, Susan G.; Nachtigall, Robert D.; Bleil, Maria E.; Adler, Nancy E.

2016-01-01

Objective To examine whether psychological distress predicts IVF treatment outcome as well as whether IVF treatment outcome predicts subsequent psychological distress. Design Prospective cohort study over an 18-month period. Setting Five community and academic fertility practices. Patients Two hundred and two women who initiated their first IVF cycle. Interventions Women completed interviews and questionnaires at baseline and at 4, 10, and 18 months follow-up. Main Outcome Measures IVF cycle outcome and psychological distress. Results Using a binary logistic model including covariates (woman’s age, ethnicity, income, education, parity, duration of infertility, and time interval), pre-treatment depression and anxiety were not significant predictors of the outcome of the first IVF cycle. Using linear regression models including covariates (woman’s age, income, education, parity, duration of infertility, assessment point, time since last treatment cycle, and pre-IVF depression or anxiety), experiencing failed IVF was associated with higher post-IVF depression and anxiety. Conclusions IVF failure predicts subsequent psychological distress, but pre-IVF psychological distress does not predict IVF failure. Instead of focusing efforts on psychological interventions specifically aimed at improving the chance of pregnancy, these findings suggest that attention be paid to helping patients prepare for and cope with treatment and treatment failure. PMID:22698636

Psychological distress and in vitro fertilization outcome.

PubMed

Pasch, Lauri A; Gregorich, Steven E; Katz, Patricia K; Millstein, Susan G; Nachtigall, Robert D; Bleil, Maria E; Adler, Nancy E

2012-08-01

To examine whether psychological distress predicts IVF treatment outcome as well as whether IVF treatment outcome predicts subsequent psychological distress. Prospective cohort study over an 18-month period. Five community and academic fertility practices. Two hundred two women who initiated their first IVF cycle. Women completed interviews and questionnaires at baseline and at 4, 10, and 18 months' follow-up. IVF cycle outcome and psychological distress. In a binary logistic model including covariates (woman's age, ethnicity, income, education, parity, duration of infertility, and time interval), pretreatment depression and anxiety were not significant predictors of the outcome of the first IVF cycle. In linear regression models including covariates (woman's age, income, education, parity, duration of infertility, assessment point, time since last treatment cycle, and pre-IVF depression or anxiety), experiencing failed IVF was associated with higher post-IVF depression and anxiety. IVF failure predicts subsequent psychological distress, but pre-IVF psychological distress does not predict IVF failure. Instead of focusing efforts on psychological interventions specifically aimed at improving the chance of pregnancy, these findings suggest that attention be paid to helping patients prepare for and cope with treatment and treatment failure. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Fatigue of graphite/epoxy /0/90/45/-45/s laminates under dual stress levels

NASA Technical Reports Server (NTRS)

Yang, J. N.; Jones, D. L.

1982-01-01

A model for the prediction of loading sequence effects on the statistical distribution of fatigue life and residual strength in composite materials is generalized and applied to (0/90/45/-45)s graphite/epoxy laminates. Load sequence effects are found to be caused by both the difference in residual strength when failure occurs (boundary effect) and the effect of previously applied loads (memory effect). The model allows the isolation of these two effects, and the estimation of memory effect magnitudes under dual fatigue loading levels. It is shown that the material memory effect is insignificant, and that correlations between predictions of the number of early failures agree with the verification tests, as do predictions of fatigue life and residual strength degradation under dual stress levels.

Current indications for transplantation: stratification of severe heart failure and shared decision-making

PubMed Central

Vucicevic, Darko; Honoris, Lily; Raia, Federica

2018-01-01

Heart failure (HF) is a complex clinical syndrome that results from structural or functional cardiovascular disorders causing a mismatch between demand and supply of oxygenated blood and consecutive failure of the body’s organs. For those patients with stage D HF, advanced therapies, such as mechanical circulatory support (MCS) or heart transplantation (HTx), are potentially life-saving options. The role of risk stratification of patients with stage D HF in a value-based healthcare framework is to predict which subset might benefit from advanced HF (AdHF) therapies, to improve outcomes related to the individual patient including mortality, morbidity and patient experience as well as to optimize health care delivery system outcomes such as cost-effectiveness. Risk stratification and subsequent outcome prediction as well as therapeutic recommendation-making need to be based on the comparative survival benefit rationale. A robust model needs to (I) have the power to discriminate (i.e., to correctly risk stratify patients); (II) calibrate (i.e., to show agreement between the predicted and observed risk); (III) to be applicable to the general population; and (IV) provide good external validation. The Seattle Heart Failure Model (SHFM) and the Heart Failure Survival Score (HFSS) are two of the most widely utilized scores. However, outcomes for patients with HF are highly variable which make clinical predictions challenging. Despite our clinical expertise and current prediction tools, the best short- and long-term survival for the individual patient, particularly the sickest patient, is not easy to identify because among the most severely ill, elderly and frail patients, most preoperative prediction tools have the tendency to be imprecise in estimating risk. They should be used as a guide in a clinical encounter grounded in a culture of shared decision-making, with the expert healthcare professional team as consultants and the patient as an empowered decision-maker in a trustful safe therapeutic relationship. PMID:29492383

Current indications for transplantation: stratification of severe heart failure and shared decision-making.

PubMed

Vucicevic, Darko; Honoris, Lily; Raia, Federica; Deng, Mario

2018-01-01

Heart failure (HF) is a complex clinical syndrome that results from structural or functional cardiovascular disorders causing a mismatch between demand and supply of oxygenated blood and consecutive failure of the body's organs. For those patients with stage D HF, advanced therapies, such as mechanical circulatory support (MCS) or heart transplantation (HTx), are potentially life-saving options. The role of risk stratification of patients with stage D HF in a value-based healthcare framework is to predict which subset might benefit from advanced HF (AdHF) therapies, to improve outcomes related to the individual patient including mortality, morbidity and patient experience as well as to optimize health care delivery system outcomes such as cost-effectiveness. Risk stratification and subsequent outcome prediction as well as therapeutic recommendation-making need to be based on the comparative survival benefit rationale. A robust model needs to (I) have the power to discriminate (i.e., to correctly risk stratify patients); (II) calibrate (i.e., to show agreement between the predicted and observed risk); (III) to be applicable to the general population; and (IV) provide good external validation. The Seattle Heart Failure Model (SHFM) and the Heart Failure Survival Score (HFSS) are two of the most widely utilized scores. However, outcomes for patients with HF are highly variable which make clinical predictions challenging. Despite our clinical expertise and current prediction tools, the best short- and long-term survival for the individual patient, particularly the sickest patient, is not easy to identify because among the most severely ill, elderly and frail patients, most preoperative prediction tools have the tendency to be imprecise in estimating risk. They should be used as a guide in a clinical encounter grounded in a culture of shared decision-making, with the expert healthcare professional team as consultants and the patient as an empowered decision-maker in a trustful safe therapeutic relationship.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burnham, A K; Weese, R K; Adrzejewski, W J

Accelerated aging tests play an important role in assessing the lifetime of manufactured products. There are two basic approaches to lifetime qualification. One tests a product to failure over range of accelerated conditions to calibrate a model, which is then used to calculate the failure time for conditions of use. A second approach is to test a component to a lifetime-equivalent dose (thermal or radiation) to see if it still functions to specification. Both methods have their advantages and limitations. A disadvantage of the 2nd method is that one does not know how close one is to incipient failure. Thismore » limitation can be mitigated by testing to some higher level of dose as a safety margin, but having a predictive model of failure via the 1st approach provides an additional measure of confidence. Even so, proper calibration of a failure model is non-trivial, and the extrapolated failure predictions are only as good as the model and the quality of the calibration. This paper outlines results for predicting the potential failure point of a system involving a mixture of two energetic materials, HMX (nitramine octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and CP (2-(5-cyanotetrazalato) pentaammine cobalt (III) perchlorate). Global chemical kinetic models for the two materials individually and as a mixture are developed and calibrated from a variety of experiments. These include traditional thermal analysis experiments run on time scales from hours to a couple days, detonator aging experiments with exposures up to 50 months, and sealed-tube aging experiments for up to 5 years. Decomposition kinetics are determined for HMX (nitramine octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) and CP (2-(5-cyanotetrazalato) pentaammine cobalt (III) perchlorate) separately and together. For high levels of thermal stress, the two materials decompose faster as a mixture than individually. This effect is observed both in high-temperature thermal analysis experiments and in long-term thermal aging experiments. An Arrhenius plot of the 10% level of HMX decomposition by itself from a diverse set of experiments is linear from 120 to 260 C, with an apparent activation energy of 165 kJ/mol. Similar but less extensive thermal analysis data for the mixture suggests a slightly lower activation energy for the mixture, and an analogous extrapolation is consistent with the amount of gas observed in the long-term detonator aging experiments, which is about 30 times greater than expected from HMX by itself for 50 months at 100 C. Even with this acceleration, however, it would take {approx}10,000 years to achieve 10% decomposition at {approx}30 C. Correspondingly, negligible decomposition is predicted by this kinetic model for a few decades aging at temperatures slightly above ambient. This prediction is consistent with additional sealed-tube aging experiments at 100-120 C, which are estimated to have an effective thermal dose greater than that from decades of exposure to temperatures slightly above ambient.« less

Analysis of whisker-toughened CMC structural components using an interactive reliability model

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Palko, Joseph L.

1992-01-01

Realizing wider utilization of ceramic matrix composites (CMC) requires the development of advanced structural analysis technologies. This article focuses on the use of interactive reliability models to predict component probability of failure. The deterministic William-Warnke failure criterion serves as theoretical basis for the reliability model presented here. The model has been implemented into a test-bed software program. This computer program has been coupled to a general-purpose finite element program. A simple structural problem is presented to illustrate the reliability model and the computer algorithm.

Yield modeling of acoustic charge transport transversal filters

NASA Technical Reports Server (NTRS)

Kenney, J. S.; May, G. S.; Hunt, W. D.

1995-01-01

This paper presents a yield model for acoustic charge transport transversal filters. This model differs from previous IC yield models in that it does not assume that individual failures of the nondestructive sensing taps necessarily cause a device failure. A redundancy in the number of taps included in the design is explained. Poisson statistics are used to describe the tap failures, weighted over a uniform defect density distribution. A representative design example is presented. The minimum number of taps needed to realize the filter is calculated, and tap weights for various numbers of redundant taps are calculated. The critical area for device failure is calculated for each level of redundancy. Yield is predicted for a range of defect densities and redundancies. To verify the model, a Monte Carlo simulation is performed on an equivalent circuit model of the device. The results of the yield model are then compared to the Monte Carlo simulation. Better than 95% agreement was obtained for the Poisson model with redundant taps ranging from 30% to 150% over the minimum.

Micromechanical investigation of ductile failure in Al 5083-H116 via 3D unit cell modeling

NASA Astrophysics Data System (ADS)

Bomarito, G. F.; Warner, D. H.

2015-01-01

Ductile failure is governed by the evolution of micro-voids within a material. The micro-voids, which commonly initiate at second phase particles within metal alloys, grow and interact with each other until failure occurs. The evolution of the micro-voids, and therefore ductile failure, depends on many parameters (e.g., stress state, temperature, strain rate, void and particle volume fraction, etc.). In this study, the stress state dependence of the ductile failure of Al 5083-H116 is investigated by means of 3-D Finite Element (FE) periodic cell models. The cell models require only two pieces of information as inputs: (1) the initial particle volume fraction of the alloy and (2) the constitutive behavior of the matrix material. Based on this information, cell models are subjected to a given stress state, defined by the stress triaxiality and the Lode parameter. For each stress state, the cells are loaded in many loading orientations until failure. Material failure is assumed to occur in the weakest orientation, and so the orientation in which failure occurs first is considered as the critical orientation. The result is a description of material failure that is derived from basic principles and requires no fitting parameters. Subsequently, the results of the simulations are used to construct a homogenized material model, which is used in a component-scale FE model. The component-scale FE model is compared to experiments and is shown to over predict ductility. By excluding smaller nucleation events and load path non-proportionality, it is concluded that accuracy could be gained by including more information about the true microstructure in the model; emphasizing that its incorporation into micromechanical models is critical to developing quantitatively accurate physics-based ductile failure models.

Sequential experimental design based generalised ANOVA

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2016-07-01

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover, generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.

Sequential experimental design based generalised ANOVA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakraborty, Souvik, E-mail: csouvik41@gmail.com; Chowdhury, Rajib, E-mail: rajibfce@iitr.ac.in

Over the last decade, surrogate modelling technique has gained wide popularity in the field of uncertainty quantification, optimization, model exploration and sensitivity analysis. This approach relies on experimental design to generate training points and regression/interpolation for generating the surrogate. In this work, it is argued that conventional experimental design may render a surrogate model inefficient. In order to address this issue, this paper presents a novel distribution adaptive sequential experimental design (DA-SED). The proposed DA-SED has been coupled with a variant of generalised analysis of variance (G-ANOVA), developed by representing the component function using the generalised polynomial chaos expansion. Moreover,more » generalised analytical expressions for calculating the first two statistical moments of the response, which are utilized in predicting the probability of failure, have also been developed. The proposed approach has been utilized in predicting probability of failure of three structural mechanics problems. It is observed that the proposed approach yields accurate and computationally efficient estimate of the failure probability.« less

A two-scale Weibull approach to the failure of porous ceramic structures made by robocasting: possibilities and limits

PubMed Central

Genet, Martin; Houmard, Manuel; Eslava, Salvador; Saiz, Eduardo; Tomsia, Antoni P.

2012-01-01

This paper introduces our approach to modeling the mechanical behavior of cellular ceramics, through the example of calcium phosphate scaffolds made by robocasting for bone-tissue engineering. The Weibull theory is used to deal with the scaffolds’ constitutive rods statistical failure, and the Sanchez-Palencia theory of periodic homogenization is used to link the rod- and scaffold-scales. Uniaxial compression of scaffolds and three-point bending of rods were performed to calibrate and validate the model. If calibration based on rod-scale data leads to over-conservative predictions of scaffold’s properties (as rods’ successive failures are not taken into account), we show that, for a given rod diameter, calibration based on scaffold-scale data leads to very satisfactory predictions for a wide range of rod spacing, i.e. of scaffold porosity, as well as for different loading conditions. This work establishes the proposed model as a reliable tool for understanding and optimizing cellular ceramics’ mechanical properties. PMID:23439936

Reliability Prediction Models for Discrete Semiconductor Devices

DTIC Science & Technology

1988-07-01

influence failure rate were device construction, semiconductor material, junction temperature, electrical stress, circuit application., a plication...found to influence failure rate were device construction, semiconductor material, junction temperature, electrical stress, circuit application...MFA Airbreathlng 14issile, Flight MFF Missile, Free Flight ML Missile, Launch MMIC Monolithic Microwave Integrated Circuits MOS Metal-Oxide

Polymer damage mitigation---predictive lifetime models of polymer insulation degradation and biorenewable thermosets through cationic polymerization for self-healing applications

NASA Astrophysics Data System (ADS)

Hondred, Peter Raymond

Over the past 50 years, the industrial development and applications for polymers and polymer composites has become expansive. However, as with any young technology, the techniques for predicting material damage and resolving material failure are in need of continued development and refinement. This thesis work takes two approaches to polymer damage mitigation---material lifetime prediction and spontaneous damage repair through self-healing while incorporating bio-renewable feedstock. First, material lifetime prediction offers the benefit of identifying and isolating material failures before the effects of damage results in catastrophic failure. Second, self-healing provides a systematic approach to repairing damaged polymer composites, specifically in applications where a hands-on approach or removing the part from service are not feasible. With regard to lifetime prediction, we investigated three specific polymeric materials---polytetrafluoroethylene (PTFE), poly(ethylene-alt-tetrafluoroethylene) (ETFE), and Kapton. All three have been utilized extensively in the aerospace field as a wire insulation coating. Because of the vast amount of electrical wiring used in aerospace constructions and the potential for electrical and thermal failure, this work develops mathematical models for both the thermal degradation kinetics as well as a lifetime prediction model for electrothermal breakdown. Isoconversional kinetic methods, which plot activation energy as a function of the extent of degradation, present insight into the development each kinetic model. The models for PTFE, ETFE, and Kapton are one step, consecutive three-step, and competitive and consecutive five-step respectively. Statistical analysis shows that an nth order autocatalytic reaction best defined the reaction kinetics for each polymer's degradation. Self-healing polymers arrest crack propagation through the use of an imbedded adhesive that reacts when cracks form. This form of damage mitigation focuses on repairing damage before the damage causes a failure in the polymer's function. In this work, the healing agent (adhesive) is developed using bio-renewable oils instead of solely relying on petroleum based feedstocks. Several bio-renewable thermosetting polymers were successfully prepared from tung oil through cationic polymerization for the use as the healing agent in self-healing microencapsulated applications. Modifications to both the monomers in the resin and the catalyst for polymerization were made and the subsequent changes to mechanical, thermal, and structural properties were identified. Furthermore, compressive lap shear testing was used to confirm that the adhesive properties would be beneficial for self-healing applications. Finally, scanning electron microscopy of the crack plane was used to study the fracture mechanism of the crack.

Puncture mechanics of soft elastomeric membrane with large deformation by rigid cylindrical indenter

NASA Astrophysics Data System (ADS)

Liu, Junjie; Chen, Zhe; Liang, Xueya; Huang, Xiaoqiang; Mao, Guoyong; Hong, Wei; Yu, Honghui; Qu, Shaoxing

2018-03-01

Soft elastomeric membrane structures are widely used and commonly found in engineering and biological applications. Puncture is one of the primary failure modes of soft elastomeric membrane at large deformation when indented by rigid objects. In order to investigate the puncture failure mechanism of soft elastomeric membrane with large deformation, we study the deformation and puncture failure of silicone rubber membrane that results from the continuous axisymmetric indentation by cylindrical steel indenters experimentally and analytically. In the experiment, effects of indenter size and the friction between the indenter and the membrane on the deformation and puncture failure of the membrane are investigated. In the analytical study, a model within the framework of nonlinear field theory is developed to describe the large local deformation around the punctured area, as well as to predict the puncture failure of the membrane. The deformed membrane is divided into three parts and the friction contact between the membrane and indenter is modeled by Coulomb friction law. The first invariant of the right Cauchy-Green deformation tensor I1 is adopted to predict the puncture failure of the membrane. The experimental and analytical results agree well. This work provides a guideline in designing reliable soft devices featured with membrane structures, which are present in a wide variety of applications.

Postglacial rebound and fault instability in Fennoscandia

NASA Astrophysics Data System (ADS)

Wu, Patrick; Johnston, Paul; Lambeck, Kurt

1999-12-01

The best available rebound model is used to investigate the role that postglacial rebound plays in triggering seismicity in Fennoscandia. The salient features of the model include tectonic stress due to spreading at the North Atlantic Ridge, overburden pressure, gravitationally self-consistent ocean loading, and the realistic deglaciation history and compressible earth model which best fits the sea-level and ice data in Fennoscandia. The model predicts the spatio-temporal evolution of the state of stress, the magnitude of fault instability, the timing of the onset of this instability, and the mode of failure of lateglacial and postglacial seismicity. The consistency of the predictions with the observations suggests that postglacial rebound is probably the cause of the large postglacial thrust faults observed in Fennoscandia. The model also predicts a uniform stress field and instability in central Fennoscandia for the present, with thrust faulting as the predicted mode of failure. However, the lack of spatial correlation of the present seismicity with the region of uplift, and the existence of strike-slip and normal modes of current seismicity are inconsistent with this model. Further unmodelled factors such as the presence of high-angle faults in the central region of uplift along the Baltic coast would be required in order to explain the pattern of seismicity today in terms of postglacial rebound stress. The sensitivity of the model predictions to the effects of compressibility, tectonic stress, viscosity and ice model is also investigated. For sites outside the ice margin, it is found that the mode of failure is sensitive to the presence of tectonic stress and that the onset timing is also dependent on compressibility. For sites within the ice margin, the effect of Earth rheology is shown to be small. However, ice load history is shown to have larger effects on the onset time of earthquakes and the magnitude of fault instability.

Finite Element Creep-Fatigue Analysis of a Welded Furnace Roll for Identifying Failure Root Cause

NASA Astrophysics Data System (ADS)

Yang, Y. P.; Mohr, W. C.

2015-11-01

Creep-fatigue induced failures are often observed in engineering components operating under high temperature and cyclic loading. Understanding the creep-fatigue damage process and identifying failure root cause are very important for preventing such failures and improving the lifetime of engineering components. Finite element analyses including a heat transfer analysis and a creep-fatigue analysis were conducted to model the cyclic thermal and mechanical process of a furnace roll in a continuous hot-dip coating line. Typically, the roll has a short life, <1 year, which has been a problem for a long time. The failure occurred in the weld joining an end bell to a roll shell and resulted in the complete 360° separation of the end bell from the roll shell. The heat transfer analysis was conducted to predict the temperature history of the roll by modeling heat convection from hot air inside the furnace. The creep-fatigue analysis was performed by inputting the predicted temperature history and applying mechanical loads. The analysis results showed that the failure was resulted from a creep-fatigue mechanism rather than a creep mechanism. The difference of material properties between the filler metal and the base metal is the root cause for the roll failure, which induces higher creep strain and stress in the interface between the weld and the HAZ.

Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random Attacks.

PubMed

Podobnik, Boris; Lipic, Tomislav; Horvatic, Davor; Majdandzic, Antonio; Bishop, Steven R; Eugene Stanley, H

2015-09-21

Estimating the critical points at which complex systems abruptly flip from one state to another is one of the remaining challenges in network science. Due to lack of knowledge about the underlying stochastic processes controlling critical transitions, it is widely considered difficult to determine the location of critical points for real-world networks, and it is even more difficult to predict the time at which these potentially catastrophic failures occur. We analyse a class of decaying dynamic networks experiencing persistent failures in which the magnitude of the overall failure is quantified by the probability that a potentially permanent internal failure will occur. When the fraction of active neighbours is reduced to a critical threshold, cascading failures can trigger a total network failure. For this class of network we find that the time to network failure, which is equivalent to network lifetime, is inversely dependent upon the magnitude of the failure and logarithmically dependent on the threshold. We analyse how permanent failures affect network robustness using network lifetime as a measure. These findings provide new methodological insight into system dynamics and, in particular, of the dynamic processes of networks. We illustrate the network model by selected examples from biology, and social science.

Prediction of damage formation in hip arthroplasties by finite element analysis using computed tomography images.

PubMed

Abdullah, Abdul Halim; Todo, Mitsugu; Nakashima, Yasuharu

2017-06-01

Femoral bone fracture is one of the main causes for the failure of hip arthroplasties (HA). Being subjected to abrupt and high impact forces in daily activities may lead to complex loading configuration such as bending and sideway falls. The objective of this study is to predict the risk of femoral bone fractures in total hip arthroplasty (THA) and resurfacing hip arthroplasty (RHA). A computed tomography (CT) based on finite element analysis was conducted to demonstrate damage formation in a three dimensional model of HAs. The inhomogeneous model of femoral bone was constructed from a 79 year old female patient with hip osteoarthritis complication. Two different femoral components were modeled with titanium alloy and cobalt chromium and inserted into the femoral bones to present THA and RHA models respectively. The analysis included six configurations, which exhibited various loading and boundary conditions, including axial compression, torsion, lateral bending, stance and two types of falling configurations. The applied hip loadings were normalized to body weight (BW) and accumulated from 1 BW to 3 BW. Predictions of damage formation in the femoral models were discussed as the resulting tensile failure as well as the compressive yielding and failure elements. The results indicate that loading directions can forecast the pattern and location of fractures at varying magnitudes of loading. Lateral bending configuration experienced the highest damage formation in both THA and RHA models. Femoral neck and trochanteric regions were in a common location in the RHA model in most configurations, while the predicted fracture locations in THA differed as per the Vancouver classification. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Multi-Dimensional Shallow Landslide Stability Analysis Suitable for Application at the Watershed Scale

NASA Astrophysics Data System (ADS)

Milledge, David; Bellugi, Dino; McKean, Jim; Dietrich, William E.

2013-04-01

Current practice in regional-scale shallow landslide hazard assessment is to adopt a one-dimensional slope stability representation. Such a representation cannot produce discrete landslides and thus cannot make predictions on landslide size. Furthermore, one-dimensional approaches cannot include lateral effects, which are known to be important in defining instability. Here we derive an alternative model that accounts for lateral resistance by representing the forces acting on each margin of an unstable block of soil. We model boundary frictional resistances using 'at rest' earth pressure on the lateral sides, and 'active' and 'passive' pressure, using the log-spiral method, on the upslope and downslope margins. We represent root reinforcement on each margin assuming that root cohesion declines exponentially with soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are relatively well constrained and find that our model predicts failure at the observed location and predicts that larger or smaller failures conformal to the observed shape are indeed more stable. We use a sensitivity analysis of the model to show that lateral reinforcement sets a minimum landslide size, and that the additional strength at the downslope boundary results in optimal shapes that are longer in the downslope direction. However, reinforcement effects alone cannot fully explain the size or shape distributions of observed landslides, highlighting the importance of the spatial pattern of key parameters (e.g. pore water pressure and soil depth) at the watershed scale. The application of the model at this scale requires an efficient method to find unstable shapes among an exponential number of candidates. In this context, the model allows a more extensive examination of the controls on landslide size, shape and location.

Prediction of Mass Wasting, Erosion, and Sediment Transport With the Distributed Hydrology-Soil-Vegetation Model

NASA Astrophysics Data System (ADS)

Doten, C. O.; Lanini, J. S.; Bowling, L. C.; Lettenmaier, D. P.

2004-12-01

Erosion and sediment transport in a temperate forested watershed are predicted with a new sediment module linked to the Distributed Hydrology-Soil-Vegetation Model (DHSVM). The DHSVM sediment module represents the main sources of sediment generation in forested environments: mass wasting, hillslope erosion and road surface erosion. It produces failures based on a factor-of-safety analysis with the infinite slope model through use of stochastically generated soil and vegetation parameters. Failed material is routed downslope with a rule-based scheme that determines sediment delivery to streams. Sediment from hillslopes and road surfaces is also transported to the channel network. Basin sediment yield is predicted with a simple channel sediment routing scheme. The model was applied to the Rainy Creek catchment, a tributary of the Wenatchee River which drains the east slopes of the Cascade Mountains, and Hard and Ware Creeks on the west slopes of the Cascades. In these initial applications, the model produced plausible sediment yield and ratios of landsliding and surface erosion , when compared to published rates for similar catchments in the Pacific Northwest. We have also used the model to examine the implications of fires and logging road removal on sediment generation in the Rainy Creek catchment. Generally, in absolute value, the predicted changes (increased sediment generation) following fires, which are primarily associated with increased slope failures, are much larger than the modest changes (reductions in sediment yield) associated with road obliteration, although the small sensitivity to forest road obliteration may be due in part to the relatively low road density in the Rainy Creek catchment, and to mechanisms, such as culvert failure, that are not represented in the model.

Earthquake and failure forecasting in real-time: A Forecasting Model Testing Centre

NASA Astrophysics Data System (ADS)

Filgueira, Rosa; Atkinson, Malcolm; Bell, Andrew; Main, Ian; Boon, Steven; Meredith, Philip

2013-04-01

Across Europe there are a large number of rock deformation laboratories, each of which runs many experiments. Similarly there are a large number of theoretical rock physicists who develop constitutive and computational models both for rock deformation and changes in geophysical properties. Here we consider how to open up opportunities for sharing experimental data in a way that is integrated with multiple hypothesis testing. We present a prototype for a new forecasting model testing centre based on e-infrastructures for capturing and sharing data and models to accelerate the Rock Physicist (RP) research. This proposal is triggered by our work on data assimilation in the NERC EFFORT (Earthquake and Failure Forecasting in Real Time) project, using data provided by the NERC CREEP 2 experimental project as a test case. EFFORT is a multi-disciplinary collaboration between Geoscientists, Rock Physicists and Computer Scientist. Brittle failure of the crust is likely to play a key role in controlling the timing of a range of geophysical hazards, such as volcanic eruptions, yet the predictability of brittle failure is unknown. Our aim is to provide a facility for developing and testing models to forecast brittle failure in experimental and natural data. Model testing is performed in real-time, verifiably prospective mode, in order to avoid selection biases that are possible in retrospective analyses. The project will ultimately quantify the predictability of brittle failure, and how this predictability scales from simple, controlled laboratory conditions to the complex, uncontrolled real world. Experimental data are collected from controlled laboratory experiments which includes data from the UCL Laboratory and from Creep2 project which will undertake experiments in a deep-sea laboratory. We illustrate the properties of the prototype testing centre by streaming and analysing realistically noisy synthetic data, as an aid to generating and improving testing methodologies in imperfect conditions. The forecasting model testing centre uses a repository to hold all the data and models and a catalogue to hold all the corresponding metadata. It allows to: Data transfer: Upload experimental data: We have developed FAST (Flexible Automated Streaming Transfer) tool to upload data from RP laboratories to the repository. FAST sets up data transfer requirements and selects automatically the transfer protocol. Metadata are automatically created and stored. Web data access: Create synthetic data: Users can choose a generator and supply parameters. Synthetic data are automatically stored with corresponding metadata. Select data and models: Search the metadata using criteria design for RP. The metadata of each data (synthetic or from laboratory) and models are well-described through their respective catalogues accessible by the web portal. Upload models: Upload and store a model with associated metadata. This provide an opportunity to share models. The web portal solicits and creates metadata describing each model. Run model and visualise results: Selected data and a model to be submitted to a High Performance Computational resource hiding technical details. Results are displayed in accelerated time and stored allowing retrieval, inspection and aggregation. The forecasting model testing centre proposed could be integrated into EPOS. Its expected benefits are: Improved the understanding of brittle failure prediction and its scalability to natural phenomena. Accelerated and extensive testing and rapid sharing of insights. Increased impact and visibility of RP and GeoScience research. Resources for education and training. A key challenge is to agree the framework for sharing RP data and models. Our work is provocative first step.

A Mathematical Model to Predict Endothelial Cell Density Following Penetrating Keratoplasty With Selective Dropout From Graft Failure

PubMed Central

Riddlesworth, Tonya D.; Kollman, Craig; Lass, Jonathan H.; Patel, Sanjay V.; Stulting, R. Doyle; Benetz, Beth Ann; Gal, Robin L.; Beck, Roy W.

2014-01-01

Purpose. We constructed several mathematical models that predict endothelial cell density (ECD) for patients after penetrating keratoplasty (PK) for a moderate-risk condition (principally Fuchs' dystrophy or pseudophakic/aphakic corneal edema). Methods. In a subset (n = 591) of Cornea Donor Study participants, postoperative ECD was determined by a central reading center. Various statistical models were considered to estimate the ECD trend longitudinally over 10 years of follow-up. A biexponential model with and without a logarithm transformation was fit using the Gauss-Newton nonlinear least squares algorithm. To account for correlated data, a log-polynomial model was fit using the restricted maximum likelihood method. A sensitivity analysis for the potential bias due to selective dropout was performed using Bayesian analysis techniques. Results. The three models using a logarithm transformation yield similar trends, whereas the model without the transform predicts higher ECD values. The adjustment for selective dropout turns out to be negligible. However, this is possibly due to the relatively low rate of graft failure in this cohort (19% at 10 years). Fuchs' dystrophy and pseudophakic/aphakic corneal edema (PACE) patients had similar ECD decay curves, with the PACE group having slightly higher cell densities by 10 years. Conclusions. Endothelial cell loss after PK can be modeled via a log-polynomial model, which accounts for the correlated data from repeated measures on the same subject. This model is not significantly affected by the selective dropout due to graft failure. Our findings warrant further study on how this may extend to ECD following endothelial keratoplasty. PMID:25425307

DOE Office of Scientific and Technical Information (OSTI.GOV)

English, Shawn A.; Briggs, Timothy M.; Nelson, Stacy M.

Simulations of low velocity impact with a flat cylindrical indenter upon a carbon fiber fabric reinforced polymer laminate are rigorously validated. Comparison of the impact energy absorption between the model and experiment is used as the validation metric. Additionally, non-destructive evaluation, including ultrasonic scans and three-dimensional computed tomography, provide qualitative validation of the models. The simulations include delamination, matrix cracks and fiber breaks. An orthotropic damage and failure constitutive model, capable of predicting progressive damage and failure, is developed in conjunction and described. An ensemble of simulations incorporating model parameter uncertainties is used to predict a response distribution which ismore » then compared to experimental output using appropriate statistical methods. Lastly, the model form errors are exposed and corrected for use in an additional blind validation analysis. The result is a quantifiable confidence in material characterization and model physics when simulating low velocity impact in structures of interest.« less

Quantitative validation of carbon-fiber laminate low velocity impact simulations

DOE PAGES

English, Shawn A.; Briggs, Timothy M.; Nelson, Stacy M.

2015-09-26

Simulations of low velocity impact with a flat cylindrical indenter upon a carbon fiber fabric reinforced polymer laminate are rigorously validated. Comparison of the impact energy absorption between the model and experiment is used as the validation metric. Additionally, non-destructive evaluation, including ultrasonic scans and three-dimensional computed tomography, provide qualitative validation of the models. The simulations include delamination, matrix cracks and fiber breaks. An orthotropic damage and failure constitutive model, capable of predicting progressive damage and failure, is developed in conjunction and described. An ensemble of simulations incorporating model parameter uncertainties is used to predict a response distribution which ismore » then compared to experimental output using appropriate statistical methods. Lastly, the model form errors are exposed and corrected for use in an additional blind validation analysis. The result is a quantifiable confidence in material characterization and model physics when simulating low velocity impact in structures of interest.« less

Prediction of Fatigue Crack Growth in Rail Steels.

DOT National Transportation Integrated Search

1981-10-01

Measures to prevent derailments due to fatigue failures of rails require adequate knowledge of the rate of propagation of fatigue cracks under service loading. The report presents a computational model for the prediction of crack growth in rails. The...

Analysis of temporal dynamics in imagery during acute limb ischemia and reperfusion

NASA Astrophysics Data System (ADS)

Irvine, John M.; Regan, John; Spain, Tammy A.; Caruso, Joseph D.; Rodriquez, Maricela; Luthra, Rajiv; Forsberg, Jonathon; Crane, Nicole J.; Elster, Eric

2014-03-01

Ischemia and reperfusion injuries present major challenges for both military and civilian medicine. Improved methods for assessing the effects and predicting outcome could guide treatment decisions. Specific issues related to ischemia and reperfusion injury can include complications arising from tourniquet use, such as microvascular leakage in the limb, loss of muscle strength and systemic failures leading to hypotension and cardiac failure. Better methods for assessing the viability of limbs/tissues during ischemia and reducing complications arising from reperfusion are critical to improving clinical outcomes for at-risk patients. The purpose of this research is to develop and assess possible prediction models of outcome for acute limb ischemia using a pre-clinical model. Our model relies only on non-invasive imaging data acquired from an animal study. Outcome is measured by pathology and functional scores. We explore color, texture, and temporal features derived from both color and thermal motion imagery acquired during ischemia and reperfusion. The imagery features form the explanatory variables in a model for predicting outcome. Comparing model performance to outcome prediction based on direct observation of blood chemistry, blood gas, urinalysis, and physiological measurements provides a reference standard. Initial results show excellent performance for the imagery-base model, compared to predictions based direct measurements. This paper will present the models and supporting analysis, followed by recommendations for future investigations.

Ductile Tearing of Thin Aluminum Plates Under Blast Loading. Predictions with Fully Coupled Models and Biaxial Material Response Characterization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corona, Edmundo; Gullerud, Arne S.; Haulenbeek, Kimberly K.

2015-06-01

The work presented in this report concerns the response and failure of thin 2024- T3 aluminum alloy circular plates to a blast load produced by the detonation of a nearby spherical charge. The plates were fully clamped around the circumference and the explosive charge was located centrally with respect to the plate. The principal objective was to conduct a numerical model validation study by comparing the results of predictions to experimental measurements of plate deformation and failure for charges with masses in the vicinity of the threshold between no tearing and tearing of the plates. Stereo digital image correlation datamore » was acquired for all tests to measure the deflection and strains in the plates. The size of the virtual strain gage in the measurements, however, was relatively large, so the strain measurements have to be interpreted accordingly as lower bounds of the actual strains in the plate and of the severity of the strain gradients. A fully coupled interaction model between the blast and the deflection of the structure was considered. The results of the validation exercise indicated that the model predicted the deflection of the plates reasonably accurately as well as the distribution of strain on the plate. The estimation of the threshold charge based on a critical value of equivalent plastic strain measured in a bulge test, however, was not accurate. This in spite of efforts to determine the failure strain of the aluminum sheet under biaxial stress conditions. Further work is needed to be able to predict plate tearing with some degree of confidence. Given the current technology, at least one test under the actual blast conditions where the plate tears is needed to calibrate the value of equivalent plastic strain when failure occurs in the numerical model. Once that has been determined, the question of the explosive mass value at the threshold could be addressed with more confidence.« less

Predictors and Patterns of Local, Regional, and Distant Failure in Squamous Cell Carcinoma of the Vulva.

PubMed

Bogani, Giorgio; Cromi, Antonella; Serati, Maurizio; Uccella, Stefano; Donato, Violante Di; Casarin, Jvan; Naro, Edoardo Di; Ghezzi, Fabio

2017-06-01

To identify factors predicting for recurrence in vulvar cancer patients undergoing surgical treatment. We retrospectively evaluated data of consecutive patients with squamous cell vulvar cancer treated between January 1, 1990 and December 31, 2013. Basic descriptive statistics and multivariable analysis were used to design predicting models influencing outcomes. Five-year disease-free survival (DFS) and overall survival (OS) were analyzed using the Cox model. The study included 101 patients affected by vulvar cancer: 64 (63%) stage I, 12 (12%) stage II, 20 (20%) stage III, and 5 (5%) stage IV. After a mean (SD) follow-up of 37.6 (22.1) months, 21 (21%) recurrences occurred. Local, regional, and distant failures were recorded in 14 (14%), 6 (6%), and 3 (3%) patients, respectively. Five-year DFS and OS were 77% and 82%, respectively. At multivariate analysis only stromal invasion >2 mm (hazard ratio: 4.9 [95% confidence interval, 1.17-21.1]; P=0.04) and extracapsular lymph node involvement (hazard ratio: 9.0 (95% confidence interval, 1.17-69.5); P=0.03) correlated with worse DFS, although no factor independently correlated with OS. Looking at factors influencing local and regional failure, we observed that stromal invasion >2 mm was the only factor predicting for local recurrence, whereas lymph node extracapsular involvement predicted for regional recurrence. Stromal invasion >2 mm and lymph node extracapsular spread are the most important factors predicting for local and regional failure, respectively. Studies evaluating the effectiveness of adjuvant treatment in high-risk patients are warranted.

Effort test failure: toward a predictive model.

PubMed

Webb, James W; Batchelor, Jennifer; Meares, Susanne; Taylor, Alan; Marsh, Nigel V

2012-01-01

Predictors of effort test failure were examined in an archival sample of 555 traumatically brain-injured (TBI) adults. Logistic regression models were used to examine whether compensation-seeking, injury-related, psychological, demographic, and cultural factors predicted effort test failure (ETF). ETF was significantly associated with compensation-seeking (OR = 3.51, 95% CI [1.25, 9.79]), low education (OR:. 83 [.74, . 94]), self-reported mood disorder (OR: 5.53 [3.10, 9.85]), exaggerated displays of behavior (OR: 5.84 [2.15, 15.84]), psychotic illness (OR: 12.86 [3.21, 51.44]), being foreign-born (OR: 5.10 [2.35, 11.06]), having sustained a workplace accident (OR: 4.60 [2.40, 8.81]), and mild traumatic brain injury severity compared with very severe traumatic brain injury severity (OR: 0.37 [0.13, 0.995]). ETF was associated with a broader range of statistical predictors than has previously been identified and the relative importance of psychological and behavioral predictors of ETF was evident in the logistic regression model. Variables that might potentially extend the model of ETF are identified for future research efforts.

Failure prediction for the optimization of stretch forming aluminium-polymer laminate foils used for pharmaceutical packaging

NASA Astrophysics Data System (ADS)

Müller, Simon; Weygand, Sabine M.

2018-05-01

Axisymmetric stretch forming processes of aluminium-polymer laminate foils (e.g. consisting of PA-Al-PVC layers) are analyzed numerically by finite element modeling of the multi-layer material as well as experimentally in order to identify a suitable damage initiation criterion. A simple ductile fracture criterion is proposed to predict the forming limits. The corresponding material constants are determined from tensile tests and then applied in forming simulations with different punch geometries. A comparison between the simulations and the experimental results shows that the determined failure constants are not applicable. Therefore, one forming experiment was selected and in the corresponding simulation the failure constant was fitted to its measured maximum stretch. With this approach it is possible to predict the forming limit of the laminate foil with satisfying accuracy for different punch geometries.

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

Compression failure of angle-ply laminates

NASA Technical Reports Server (NTRS)

Peel, L. D.; Hyer, M. W.; Shuart, M. J.

1992-01-01

Test results from the compression loading of (+ or - Theta/ - or + Theta)(sub 6s) angle-ply IM7-8551-7a specimens, 0 less than or = Theta less than or = 90 degs, are presented. The observed failure strengths and modes are discussed, and typical stress-strain relations shown. Using classical lamination theory and the maximum stress criterion, an attempt is made to predict failure stress as a function of Theta. This attempt results in poor correlation with test results and thus a more advanced model is used. The model, which is based on a geometrically nonlinear theory, and which was taken from previous work, includes the influence of observed layer waviness. The waviness is described by the wave length and the wave amplitude. The theory is briefly described and results from the theory are correlated with test results. It is shown that by using levels of waviness observed in the specimens, the correlation between predictions and observations is good.

Quasi-Static 3-Point Reinforced Carbon-Carbon Bend Test and Analysis for Shuttle Orbiter Wing Leading Edge Impact Damage Thresholds

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Sotiris, Kellas

2006-01-01

Static 3-point bend tests of Reinforced Carbon-Carbon (RCC) were conducted to failure to provide data for additional validation of an LS-DYNA RCC model suitable for predicting the threshold of impact damage to shuttle orbiter wing leading edges. LS-DYNA predictions correlated well with the average RCC failure load, and were good in matching the load vs. deflection. However, correlating the detectable damage using NDE methods with the cumulative damage parameter in LS-DYNA material model 58 was not readily achievable. The difficulty of finding internal RCC damage with NDE and the high sensitivity of the mat58 damage parameter to the load near failure made the task very challenging. In addition, damage mechanisms for RCC due to dynamic impact of debris such as foam and ice and damage mechanisms due to a static loading were, as expected, not equivalent.

High-sensitivity cardiac troponin I and risk of heart failure in patients with suspected acute coronary syndrome: a cohort study.

PubMed

Stelzle, Dominik; Shah, Anoop S V; Anand, Atul; Strachan, Fiona E; Chapman, Andrew R; Denvir, Martin A; Mills, Nicholas L; McAllister, David A

2018-01-01

Heart failure may occur following acute myocardial infarction, but with the use of high-sensitivity cardiac troponin assays we increasingly diagnose patients with minor myocardial injury. Whether troponin concentrations remain a useful predictor of heart failure in patients with acute coronary syndrome is uncertain. We identified all consecutive patients (n = 4748) with suspected acute coronary syndrome (61 ± 16 years, 57% male) presenting to three secondary and tertiary care hospitals. Cox-regression models were used to evaluate the association between high-sensitivity cardiac troponin I concentration and subsequent heart failure hospitalization. C-statistics were estimated to evaluate the predictive value of troponin for heart failure hospitalization. Over 2071 years of follow-up there were 83 heart failure hospitalizations. Patients with troponin concentrations above the upper reference limit (URL) were more likely to be hospitalized with heart failure than patients below the URL (118/1000 vs. 17/1000 person years, adjusted hazard ratio: 7.0). Among patients with troponin concentrations

Machine learning for the New York City power grid.

PubMed

Rudin, Cynthia; Waltz, David; Anderson, Roger N; Boulanger, Albert; Salleb-Aouissi, Ansaf; Chow, Maggie; Dutta, Haimonti; Gross, Philip N; Huang, Bert; Ierome, Steve; Isaac, Delfina F; Kressner, Arthur; Passonneau, Rebecca J; Radeva, Axinia; Wu, Leon

2012-02-01

Power companies can benefit from the use of knowledge discovery methods and statistical machine learning for preventive maintenance. We introduce a general process for transforming historical electrical grid data into models that aim to predict the risk of failures for components and systems. These models can be used directly by power companies to assist with prioritization of maintenance and repair work. Specialized versions of this process are used to produce 1) feeder failure rankings, 2) cable, joint, terminator, and transformer rankings, 3) feeder Mean Time Between Failure (MTBF) estimates, and 4) manhole events vulnerability rankings. The process in its most general form can handle diverse, noisy, sources that are historical (static), semi-real-time, or realtime, incorporates state-of-the-art machine learning algorithms for prioritization (supervised ranking or MTBF), and includes an evaluation of results via cross-validation and blind test. Above and beyond the ranked lists and MTBF estimates are business management interfaces that allow the prediction capability to be integrated directly into corporate planning and decision support; such interfaces rely on several important properties of our general modeling approach: that machine learning features are meaningful to domain experts, that the processing of data is transparent, and that prediction results are accurate enough to support sound decision making. We discuss the challenges in working with historical electrical grid data that were not designed for predictive purposes. The “rawness” of these data contrasts with the accuracy of the statistical models that can be obtained from the process; these models are sufficiently accurate to assist in maintaining New York City’s electrical grid.

Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

USGS Publications Warehouse

Montgomery, D.R.; Schmidt, K.M.; Dietrich, W.E.; McKean, J.

2009-01-01

The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium. Postfailure observations of the bedrock surface exposed in the debris flow scar reveal a strong spatial correspondence between elevated piezometric response and water discharging from bedrock fractures. Measurements of apparent root cohesion on the basal (Cb) and lateral (Cl) scarp demonstrate substantial local variability, with areally weighted values of Cb = 0.1 and Cl = 4.6 kPa. Using measured soil properties and basal root strength, the widely used infinite slope model, employed assuming slope parallel groundwater flow, provides a poor prediction of hydrologie conditions at failure. In contrast, a model including lateral root strength (but neglecting lateral frictional strength) gave a predicted critical value of relative soil saturation that fell within the range defined by the arithmetic and geometric mean values at the time of failure. The 3-D slope stability model CLARA-W, used with locally observed pore water pressure, predicted small areas with lower factors of safety within the overall slide mass at sites consistent with field observations of where the failure initiated. This highly variable and localized nature of small areas of high pore pressure that can trigger slope failure means, however, that substantial uncertainty appears inevitable for estimating hydrologie conditions within incipient debris flows under natural conditions. Copyright 2009 by the American Geophysical Union.

Prediction of progressive damage and strength of plain weave composites using the finite element method

NASA Astrophysics Data System (ADS)

Srirengan, Kanthikannan

The overall objective of this research was to develop the finite element code required to efficiently predict the strength of plain weave composite structures. Towards which, three-dimensional conventional progressive damage analysis was implemented to predict the strength of plain weave composites subjected to periodic boundary conditions. Also, modal technique for three-dimensional global/local stress analysis was developed to predict the failure initiation in plain weave composite structures. The progressive damage analysis was used to study the effect of quadrature order, mesh refinement and degradation models on the predicted damage and strength of plain weave composites subjected to uniaxial tension in the warp tow direction. A 1/32sp{nd} part of the representative volume element of a symmetrically stacked configuration was analyzed. The tow geometry was assumed to be sinusoidal. Graphite/Epoxy system was used. Maximum stress criteria and combined stress criteria were used to predict failure in the tows and maximum principal stress criterion was used to predict failure in the matrix. Degradation models based on logical reasoning, micromechanics idealization and experimental comparisons were used to calculate the effective material properties with of damage. Modified Newton-Raphson method was used to determine the incremental solution for each applied strain level. Using a refined mesh and the discount method based on experimental comparisons, the progressive damage and the strength of plain weave composites of waviness ratios 1/3 and 1/6 subjected to uniaxial tension in the warp direction have been characterized. Plain weave composites exhibit a brittle response in uniaxial tension. The strength decreases significantly with the increase in waviness ratio. Damage initiation and collapse were caused dominantly due to intra-tow cracking and inter-tow debonding respectively. The predicted strength of plain weave composites of racetrack geometry and waviness ratio 1/25.7 was compared with analytical predictions and experimental findings and was found to match well. To evaluate the performance of the modal technique, failure initiation in a short woven composite cantilevered plate subjected to end moment and transverse end load was predicted. The global/local predictions were found to reasonably match well with the conventional finite element predictions.

Detailed investigation of causes of avionics field failures

NASA Astrophysics Data System (ADS)

Kallis, J. M.; Buechler, D. W.; Richardson, Z. C.; Backes, P. G.; Lopez, S. B.; Erickson, J. J.; van Westerhuyzen, D. H.

A detailed analysis of digital and analog modules from the F-15 AN/APG-63 Radar was performed to identify the kinds, types, and number of life models based on observed failure modes, mechanisms, locations, and characteristics needed to perform a Failure Free Operating Period prediction for these items. It is found that a significant fraction of the failures of the analog module and a small fraction of those of the digital module resulted from the exacerbation of latent defects by environmental stresses. It is also found that the fraction of failures resulting from thermal cycling and vibration is small.

Reliability analysis and fault-tolerant system development for a redundant strapdown inertial measurement unit. [inertial platforms

NASA Technical Reports Server (NTRS)

Motyka, P.

1983-01-01

A methodology is developed and applied for quantitatively analyzing the reliability of a dual, fail-operational redundant strapdown inertial measurement unit (RSDIMU). A Markov evaluation model is defined in terms of the operational states of the RSDIMU to predict system reliability. A 27 state model is defined based upon a candidate redundancy management system which can detect and isolate a spectrum of failure magnitudes. The results of parametric studies are presented which show the effect on reliability of the gyro failure rate, both the gyro and accelerometer failure rates together, false alarms, probability of failure detection, probability of failure isolation, and probability of damage effects and mission time. A technique is developed and evaluated for generating dynamic thresholds for detecting and isolating failures of the dual, separated IMU. Special emphasis is given to the detection of multiple, nonconcurrent failures. Digital simulation time histories are presented which show the thresholds obtained and their effectiveness in detecting and isolating sensor failures.

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

PubMed

Yu, Zheng-Yong; Zhu, Shun-Peng; Liu, Qiang; Liu, Yunhan

2017-05-08

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.

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

PubMed Central

Yu, Zheng-Yong; Zhu, Shun-Peng; Liu, Qiang; Liu, Yunhan

2017-01-01

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. PMID:28772873

Disturbed State constitutive modeling of two Pleistocene tills

NASA Astrophysics Data System (ADS)

Sane, S. M.; Desai, C. S.; Jenson, J. W.; Contractor, D. N.; Carlson, A. E.; Clark, P. U.

2008-02-01

The Disturbed State Concept (DSC) provides a general approach for constitutive modeling of deforming materials. Here, we briefly explain the DSC and present the results of laboratory tests on two regionally significant North American tills, along with the results of a numerical simulation to predict the behavior of one of the tills in an idealized physical system. Laboratory shear tests showed that plastic strain starts almost from the beginning of loading, and that failure and resulting motion begin at a critical disturbance, when about 85% of the mass has reached the fully adjusted or critical state. Specimens of both tills exhibited distributed strain, deforming into barrel shapes without visible shear planes. DSC parameters obtained from shear and creep tests were validated by comparing model predictions against test data used to find the parameters, as well as against data from independent tests. The DSC parameters from one of the tills were applied in a finite-element simulation to predict gravity-induced motion for a 5000-m long, 100-m thick slab of ice coupled to an underlying 1.5-m thick layer of till set on a 4° incline, with pore-water pressure in the till at 90% of the load. The simulation predicted that in the middle segment of the till layer (i.e., from x=2000 to 3000 m) the induced (computed) shear stress, strain, and disturbance increase gradually with the applied shear stress. Induced shear stress peaks at ˜60 kPa. The critical disturbance, at which failure occurs, is observed after the peak shear stress, at an induced shear stress of ˜23 kPa and shear strain of ˜0.75 in the till. Calculated horizontal displacement over the height of the entire till section at the applied shear stress of 65 kPa is ˜4.5 m. We note that the numerical prediction of critical disturbance, when the displacement shows a sharp change in rate, compares very well with the occurrence of critical disturbance observed in the laboratory triaxial tests, when a sharp change in the rate of strain occurs. This implies that the failure and concomitant initiation of motion occur near the residual state, at large strains. In contrast to the Mohr-Coulomb model, which predicts failure and motion at very small (elastic) strain, the DSC thus predicts failure and initiation of motion after the till has undergone considerable (plastic) strain. These results suggest that subglacial till may be able to sustain stress in the vicinity of 20 kPa even after the motion begins. They also demonstrate the potential of the DSC to model not only local behavior, including potential "sticky spot" mechanisms, but also global behavior for soft-bedded ice.

Predicting failure of hematopoietic stem cell mobilization before it starts: the predicted poor mobilizer (pPM) score.

PubMed

Olivieri, Jacopo; Attolico, Immacolata; Nuccorini, Roberta; Pascale, Sara Pasquina; Chiarucci, Martina; Poiani, Monica; Corradini, Paolo; Farina, Lucia; Gaidano, Gianluca; Nassi, Luca; Sica, Simona; Piccirillo, Nicola; Pioltelli, Pietro Enrico; Martino, Massimo; Moscato, Tiziana; Pini, Massimo; Zallio, Francesco; Ciceri, Fabio; Marktel, Sarah; Mengarelli, Andrea; Musto, Pellegrino; Capria, Saveria; Merli, Francesco; Codeluppi, Katia; Mele, Giuseppe; Lanza, Francesco; Specchia, Giorgina; Pastore, Domenico; Milone, Giuseppe; Saraceni, Francesco; Di Nardo, Elvira; Perseghin, Paolo; Olivieri, Attilio

2018-04-01

Predicting mobilization failure before it starts may enable patient-tailored strategies. Although consensus criteria for predicted PM (pPM) are available, their predictive performance has never been measured on real data. We retrospectively collected and analyzed 1318 mobilization procedures performed for MM and lymphoma patients in the plerixafor era. In our sample, 180/1318 (13.7%) were PM. The score resulting from published pPM criteria had sufficient performance for predicting PM, as measured by AUC (0.67, 95%CI: 0.63-0.72). We developed a new prediction model from multivariate analysis whose score (pPM-score) resulted in better AUC (0.80, 95%CI: 0.76-0.84, p < 0001). pPM-score included as risk factors: increasing age, diagnosis of NHL, positive bone marrow biopsy or cytopenias before mobilization, previous mobilization failure, priming strategy with G-CSF alone, or without upfront plerixafor. A simplified version of pPM-score was categorized using a cut-off to maximize positive likelihood ratio (15.7, 95%CI: 9.9-24.8); specificity was 98% (95%CI: 97-98.7%), sensitivity 31.7% (95%CI: 24.9-39%); positive predictive value in our sample was 71.3% (95%CI: 60-80.8%). Simplified pPM-score can "rule in" patients at very high risk for PM before starting mobilization, allowing changes in clinical management, such as choice of alternative priming strategies, to avoid highly likely mobilization failure.

Bayesian transformation cure frailty models with multivariate failure time data.

PubMed

Yin, Guosheng

2008-12-10

We propose a class of transformation cure frailty models to accommodate a survival fraction in multivariate failure time data. Established through a general power transformation, this family of cure frailty models includes the proportional hazards and the proportional odds modeling structures as two special cases. Within the Bayesian paradigm, we obtain the joint posterior distribution and the corresponding full conditional distributions of the model parameters for the implementation of Gibbs sampling. Model selection is based on the conditional predictive ordinate statistic and deviance information criterion. As an illustration, we apply the proposed method to a real data set from dentistry.

Earthquake triggering by transient and static deformations

USGS Publications Warehouse

Gomberg, J.; Beeler, N.M.; Blanpied, M.L.; Bodin, P.

1998-01-01

Observational evidence for both static and transient near-field and far-field triggered seismicity are explained in terms of a frictional instability model, based on a single degree of freedom spring-slider system and rate- and state-dependent frictional constitutive equations. In this study a triggered earthquake is one whose failure time has been advanced by ??t (clock advance) due to a stress perturbation. Triggering stress perturbations considered include square-wave transients and step functions, analogous to seismic waves and coseismic static stress changes, respectively. Perturbations are superimposed on a constant background stressing rate which represents the tectonic stressing rate. The normal stress is assumed to be constant. Approximate, closed-form solutions of the rate-and-state equations are derived for these triggering and background loads, building on the work of Dieterich [1992, 1994]. These solutions can be used to simulate the effects of static and transient stresses as a function of amplitude, onset time t0, and in the case of square waves, duration. The accuracies of the approximate closed-form solutions are also evaluated with respect to the full numerical solution and t0. The approximate solutions underpredict the full solutions, although the difference decreases as t0, approaches the end of the earthquake cycle. The relationship between ??t and t0 differs for transient and static loads: a static stress step imposed late in the cycle causes less clock advance than an equal step imposed earlier, whereas a later applied transient causes greater clock advance than an equal one imposed earlier. For equal ??t, transient amplitudes must be greater than static loads by factors of several tens to hundreds depending on t0. We show that the rate-and-state model requires that the total slip at failure is a constant, regardless of the loading history. Thus a static load applied early in the cycle, or a transient applied at any time, reduces the stress at the initiation of failure, whereas static loads that are applied sufficiently late raise it. Rate-and-state friction predictions differ markedly from those based on Coulomb failure stress changes (??CFS) in which ??t equals the amplitude of the static stress change divided by the background stressing rate. The ??CFS model assumes a stress failure threshold, while the rate-and-state equations require a slip failure threshold. The complete rale-and-state equations predict larger ??t than the ??CFS model does for static stress steps at small t0, and smaller ??t than the ??CFS model for stress steps at large t0. The ??CFS model predicts nonzero ??t only for transient loads that raise the stress to failure stress levels during the transient. In contrast, the rate-and-state model predicts nonzero ??t for smaller loads, and triggered failure may occur well after the transient is finished. We consider heuristically the effects of triggering on a population of faults, as these effects might be evident in seismicity data. Triggering is manifest as an initial increase in seismicity rate that may be followed by a quiescence or by a return to the background rate. Available seismicity data are insufficient to discriminate whether triggered earthquakes are "new" or clock advanced. However, if triggering indeed results from advancing the failure time of inevitable earthquakes, then our modeling suggests that a quiescence always follows transient triggering and that the duration of increased seismicity also cannot exceed the duration of a triggering transient load. Quiescence follows static triggering only if the population of available faults is finite.

A Field Synopsis of Sex in Clinical Prediction Models for Cardiovascular Disease

PubMed Central

Paulus, Jessica K.; Wessler, Benjamin S.; Lundquist, Christine; Lai, Lana L.Y.; Raman, Gowri; Lutz, Jennifer S.; Kent, David M.

2017-01-01

Background Several widely-used risk scores for cardiovascular disease (CVD) incorporate sex effects, yet there has been no systematic summary of the role of sex in clinical prediction models (CPMs). To better understand the potential of these models to support sex-specific care, we conducted a field synopsis of sex effects in CPMs for CVD. Methods and Results We identified CPMs in the Tufts Predictive Analytics and Comparative Effectiveness (PACE) CPM Registry, a comprehensive database of CVD CPMs published from 1/1990–5/2012. We report the proportion of models including sex effects on CVD incidence or prognosis, summarize the directionality of the predictive effects of sex, and explore factors influencing the inclusion of sex. Of 592 CVD-related CPMs, 193 (33%) included sex as a predictor or presented sex-stratified models. Sex effects were included in 78% (53/68) of models predicting incidence of CVD in a general population, versus only 35% (59/171), 21% (12/58) and 17% (12/72) of models predicting outcomes in patients with coronary artery disease (CAD), stroke, and heart failure, respectively. Among sex-including CPMs, women with heart failure were at lower mortality risk in 8/8 models; women undergoing revascularization for CAD were at higher mortality risk in 10/12 models. Factors associated with the inclusion of sex effects included the number of outcome events and using cohorts at-risk for CVD (rather than with established CVD). Conclusions While CPMs hold promise for supporting sex-specific decision making in CVD clinical care, sex effects are included in only one third of published CPMs. PMID:26908865

Reliability analysis and initial requirements for FC systems and stacks

NASA Astrophysics Data System (ADS)

Åström, K.; Fontell, E.; Virtanen, S.

In the year 2000 Wärtsilä Corporation started an R&D program to develop SOFC systems for CHP applications. The program aims to bring to the market highly efficient, clean and cost competitive fuel cell systems with rated power output in the range of 50-250 kW for distributed generation and marine applications. In the program Wärtsilä focuses on system integration and development. System reliability and availability are key issues determining the competitiveness of the SOFC technology. In Wärtsilä, methods have been implemented for analysing the system in respect to reliability and safety as well as for defining reliability requirements for system components. A fault tree representation is used as the basis for reliability prediction analysis. A dynamic simulation technique has been developed to allow for non-static properties in the fault tree logic modelling. Special emphasis has been placed on reliability analysis of the fuel cell stacks in the system. A method for assessing reliability and critical failure predictability requirements for fuel cell stacks in a system consisting of several stacks has been developed. The method is based on a qualitative model of the stack configuration where each stack can be in a functional, partially failed or critically failed state, each of the states having different failure rates and effects on the system behaviour. The main purpose of the method is to understand the effect of stack reliability, critical failure predictability and operating strategy on the system reliability and availability. An example configuration, consisting of 5 × 5 stacks (series of 5 sets of 5 parallel stacks) is analysed in respect to stack reliability requirements as a function of predictability of critical failures and Weibull shape factor of failure rate distributions.

A Competing Risk Model of First Failure Site after Definitive Chemoradiation Therapy for Locally Advanced Non-Small Cell Lung Cancer.

PubMed

Nygård, Lotte; Vogelius, Ivan R; Fischer, Barbara M; Kjær, Andreas; Langer, Seppo W; Aznar, Marianne C; Persson, Gitte F; Bentzen, Søren M

2018-04-01

The aim of the study was to build a model of first failure site- and lesion-specific failure probability after definitive chemoradiotherapy for inoperable NSCLC. We retrospectively analyzed 251 patients receiving definitive chemoradiotherapy for NSCLC at a single institution between 2009 and 2015. All patients were scanned by fludeoxyglucose positron emission tomography/computed tomography for radiotherapy planning. Clinical patient data and fludeoxyglucose positron emission tomography standardized uptake values from primary tumor and nodal lesions were analyzed by using multivariate cause-specific Cox regression. In patients experiencing locoregional failure, multivariable logistic regression was applied to assess risk of each lesion being the first site of failure. The two models were used in combination to predict probability of lesion failure accounting for competing events. Adenocarcinoma had a lower hazard ratio (HR) of locoregional failure than squamous cell carcinoma (HR = 0.45, 95% confidence interval [CI]: 0.26-0.76, p = 0.003). Distant failures were more common in the adenocarcinoma group (HR = 2.21, 95% CI: 1.41-3.48, p < 0.001). Multivariable logistic regression of individual lesions at the time of first failure showed that primary tumors were more likely to fail than lymph nodes (OR = 12.8, 95% CI: 5.10-32.17, p < 0.001). Increasing peak standardized uptake value was significantly associated with lesion failure (OR = 1.26 per unit increase, 95% CI: 1.12-1.40, p < 0.001). The electronic model is available at http://bit.ly/LungModelFDG. We developed a failure site-specific competing risk model based on patient- and lesion-level characteristics. Failure patterns differed between adenocarcinoma and squamous cell carcinoma, illustrating the limitation of aggregating them into NSCLC. Failure site-specific models add complementary information to conventional prognostic models. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Failure to Rescue Rates After Coronary Artery Bypass Grafting: An Analysis From The Society of Thoracic Surgeons Adult Cardiac Surgery Database.

PubMed

Edwards, Fred H; Ferraris, Victor A; Kurlansky, Paul A; Lobdell, Kevin W; He, Xia; O'Brien, Sean M; Furnary, Anthony P; Rankin, J Scott; Vassileva, Christina M; Fazzalari, Frank L; Magee, Mitchell J; Badhwar, Vinay; Xian, Ying; Jacobs, Jeffrey P; Wyler von Ballmoos, Moritz C; Shahian, David M

2016-08-01

Failure to rescue (FTR) is increasingly recognized as an important quality indicator in surgery. The Society of Thoracic Surgeons National Database was used to develop FTR metrics and a predictive FTR model for coronary artery bypass grafting (CABG). The study included 604,154 patients undergoing isolated CABG at 1,105 centers from January 2010 to January 2014. FTR was defined as death after four complications: stroke, renal failure, reoperation, and prolonged ventilation. FTR was determined for each complication and a composite of the four complications. A statistical model to predict FTR was developed. FTR rates were 22.3% for renal failure, 16.4% for stroke, 12.4% for reoperation, 12.1% for prolonged ventilation, and 10.5% for the composite. Mortality increased with multiple complications and with specific combinations of complications. The multivariate risk model for prediction of FTR demonstrated a C index of 0.792 and was well calibrated, with a 1.0% average difference between observed/expected (O/E) FTR rates. With centers grouped into mortality terciles, complication rates increased modestly (11.4% to 15.7%), but FTR rates more than doubled (6.8% to 13.9%) from the lowest to highest terciles. Centers in the lowest complication rate tercile had an FTR O/E of 1.14, whereas centers in the highest complication rate tercile had an FTR O/E of 0.91. CABG mortality rates vary directly with FTR, but complication rates have little relation to death. FTR rates derived from The Society of Thoracic Surgeons data can serve as national benchmarks. Predicted FTR rates may facilitate patient counseling, and FTR O/E ratios have promise as valuable quality metrics. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Analysis of Factors Affecting the Performance of RLV Thrust Cell Liners

NASA Technical Reports Server (NTRS)

Arnold, Steven M. (Technical Monitor); Butler, Daniel T., Jr.; Pinders, Marek-Jerzy

2004-01-01

The reusable launch vehicle (RLV) thrust cell liner, or thrust chamber, is a critical component of the Space Shuttle Main Engine (SSME). It is designed to operate in some of the most severe conditions seen in engineering practice. This requirement, in conjunction with experimentally observed 'dog-house' failure modes characterized by bulging and thinning of the cooling channel wall, provides the motivation to study the factors that influence RLV thrust cell liner performance. Factors or parameters believed to be directly related to the observed characteristic deformation modes leading to failure under in-service loading conditions are identified, and subsequently investigated using the cylindrical version of the higher-order theory for functionally graded materials in conjunction with the Robinson's unified viscoplasticity theory and the power-law creep model for modeling the response of the liner s constituents. Configurations are analyzed in which specific modifications in cooling channel wall thickness or constituent materials are made to determine the influence of these parameters on the deformations resulting in the observed failure modes in the outer walls of the cooling channel. The application of thermal barrier coatings and functional grading are also investigated within this context. Comparison of the higher-order theory results based on the Robinson and power-law creep model predictions has demonstrated that, using the available material parameters, the power-law creep model predicts more precisely the experimentally observed deformation leading to the 'dog-house' failure mode for multiple short cycles, while also providing much improved computational efficiency. However, for a single long cycle, both models predict virtually identical deformations. Increasing the power-law creep model coefficients produces appreciable deformations after just one long cycle that would normally be obtained after multiple cycles, thereby enhancing the efficiency of the analysis. This provides a basis for the development of an accelerated modeling procedure to further characterize dog-house deformation modes in RLV thrust cell liners. Additionally, the results presented herein have demonstrated that the mechanism responsible for deformation leading to 'dog-house' failure modes is driven by pressure, creep/relaxation and geometric effects.

Development of an engineering analysis of progressive damage in composites during low velocity impact

NASA Technical Reports Server (NTRS)

Humphreys, E. A.

1981-01-01

A computerized, analytical methodology was developed to study damage accumulation during low velocity lateral impact of layered composite plates. The impact event was modeled as perfectly plastic with complete momentum transfer to the plate structure. A transient dynamic finite element approach was selected to predict the displacement time response of the plate structure. Composite ply and interlaminar stresses were computed at selected time intervals and subsequently evaluated to predict layer and interlaminar damage. The effects of damage on elemental stiffness were then incorporated back into the analysis for subsequent time steps. Damage predicted included fiber failure, matrix ply failure and interlaminar delamination.

A life prediction methodology for encapsulated solar cells

NASA Technical Reports Server (NTRS)

Coulbert, C. D.

1978-01-01

This paper presents an approach to the development of a life prediction methodology for encapsulated solar cells which are intended to operate for twenty years or more in a terrestrial environment. Such a methodology, or solar cell life prediction model, requires the development of quantitative intermediate relationships between local environmental stress parameters and the basic chemical mechanisms of encapsulant aging leading to solar cell failures. The use of accelerated/abbreviated testing to develop these intermediate relationships and in revealing failure modes is discussed. Current field and demonstration tests of solar cell arrays and the present laboratory tests to qualify solar module designs provide very little data applicable to predicting the long-term performance of encapsulated solar cells. An approach to enhancing the value of such field tests to provide data for life prediction is described.

Theoretical model of impact damage in structural ceramics

NASA Technical Reports Server (NTRS)

Liaw, B. M.; Kobayashi, A. S.; Emery, A. G.

1984-01-01

This paper presents a mechanistically consistent model of impact damage based on elastic failures due to tensile and shear overloading. An elastic axisymmetric finite element model is used to determine the dynamic stresses generated by a single particle impact. Local failures in a finite element are assumed to occur when the primary/secondary principal stresses or the maximum shear stress reach critical tensile or shear stresses, respectively. The succession of failed elements thus models macrocrack growth. Sliding motions of cracks, which closed during unloading, are resisted by friction and the unrecovered deformation represents the 'plastic deformation' reported in the literature. The predicted ring cracks on the contact surface, as well as the cone cracks, median cracks, radial cracks, lateral cracks, and damage-induced porous zones in the interior of hot-pressed silicon nitride plates, matched those observed experimentally. The finite element model also predicted the uplifting of the free surface surrounding the impact site.

An evaluation of the Johnson-Cook model to simulate puncture of 7075 aluminum plates.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corona, Edmundo; Orient, George Edgar

The objective of this project was to evaluate the use of the Johnson-Cook strength and failure models in an adiabatic finite element model to simulate the puncture of 7075- T651 aluminum plates that were studied as part of an ASC L2 milestone by Corona et al (2012). The Johnson-Cook model parameters were determined from material test data. The results show a marked improvement, in particular in the calculated threshold velocity between no puncture and puncture, over those obtained in 2012. The threshold velocity calculated using a baseline model is just 4% higher than the mean value determined from experiment, inmore » contrast to 60% in the 2012 predictions. Sensitivity studies showed that the threshold velocity predictions were improved by calibrating the relations between the equivalent plastic strain at failure and stress triaxiality, strain rate and temperature, as well as by the inclusion of adiabatic heating.« less

Tensile Strength of Carbon Nanotubes Under Realistic Temperature and Strain Rate

NASA Technical Reports Server (NTRS)

Wei, Chen-Yu; Cho, Kyeong-Jae; Srivastava, Deepak; Biegel, Bryan (Technical Monitor)

2002-01-01

Strain rate and temperature dependence of the tensile strength of single-wall carbon nanotubes has been investigated with molecular dynamics simulations. The tensile failure or yield strain is found to be strongly dependent on the temperature and strain rate. A transition state theory based predictive model is developed for the tensile failure of nanotubes. Based on the parameters fitted from high-strain rate and temperature dependent molecular dynamics simulations, the model predicts that a defect free micrometer long single-wall nanotube at 300 K, stretched with a strain rate of 1%/hour, fails at about 9 plus or minus 1% tensile strain. This is in good agreement with recent experimental findings.

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

NASA Technical Reports Server (NTRS)

Drake, R. L.; Duvoisin, P. F.; Asthana, A.; Mather, T. W.

1971-01-01

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Incorporation of Failure Into an Orthotropic Three-Dimensional Model with Tabulated Input Suitable for Use in Composite Impact Problems

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Carney, Kelly S.; Dubois, Paul; Hoffarth, Canio; Khaled, Bilal; Shyamsunder, Loukham; Rajan, Subramaniam; Blankenhorn, Gunther

2017-01-01

The need for accurate material models to simulate the deformation, damage and failure of polymer matrix composites under impact conditions is becoming critical as these materials are gaining increased use in the aerospace and automotive communities. The aerospace community has identified several key capabilities which are currently lacking in the available material models in commercial transient dynamic finite element codes. To attempt to improve the predictive capability of composite impact simulations, a next generation material model is being developed for incorporation within the commercial transient dynamic finite element code LS-DYNA. The material model, which incorporates plasticity, damage and failure, utilizes experimentally based tabulated input to define the evolution of plasticity and damage and the initiation of failure as opposed to specifying discrete input parameters such as modulus and strength. The plasticity portion of the orthotropic, three-dimensional, macroscopic composite constitutive model is based on an extension of the Tsai-Wu composite failure model into a generalized yield function with a non-associative flow rule. For the damage model, a strain equivalent formulation is used to allow for the uncoupling of the deformation and damage analyses. In the damage model, a semi-coupled approach is employed where the overall damage in a particular coordinate direction is assumed to be a multiplicative combination of the damage in that direction resulting from the applied loads in various coordinate directions. For the failure model, a tabulated approach is utilized in which a stress or strain based invariant is defined as a function of the location of the current stress state in stress space to define the initiation of failure. Failure surfaces can be defined with any arbitrary shape, unlike traditional failure models where the mathematical functions used to define the failure surface impose a specific shape on the failure surface. In the current paper, the complete development of the failure model is described and the generation of a tabulated failure surface for a representative composite material is discussed.

A New Approach to Fibrous Composite Laminate Strength Prediction

NASA Technical Reports Server (NTRS)

Hart-Smith, L. J.

1990-01-01

A method of predicting the strength of cross-plied fibrous composite laminates is based on expressing the classical maximum-shear-stress failure criterion for ductile metals in terms of strains. Starting with such a formulation for classical isotropic materials, the derivation is extended to orthotropic materials having a longitudinal axis of symmetry, to represent the fibers in a unidirectional composite lamina. The only modification needed to represent those same fibers with properties normalized to the lamina rather than fiber is a change in axial modulus. A mirror image is added to the strain-based lamina failure criterion for fiber-dominated failures to reflect the cutoffs due to the presence of orthogonal fibers. It is found that the combined failure envelope is now identical with the well-known maximum-strain failure model in the tension-tension and compression-compression quadrants but is truncated in the shear quadrants. The successive application of this simple failure model for fibers in the 0/90 degree and +/- 45 degree orientations, in turn, is shown to be the necessary and sufficient characterization of the fiber-dominated failures of laminates made from fibers having the same tensile and compressive strengths. When one such strength is greater than the other, the failure envelope is appropriately truncated for the lesser direct strain. The shear-failure cutoffs are now based on the higher axial strain to failure since they occur at lower strains than and are usually not affected by such mechanisms as microbuckling. Premature matrix failures can also be covered by appropriately truncating the fiber failure envelope. Matrix failures are excluded from consideration for conventional fiber/polymer composites but the additional features needed for a more rigorous analysis of exotic materials are covered. The new failure envelope is compared with published biaxial test data. The theory is developed for unnotched laminates but is easily shrunk to incorporate reductions to allow for bolt holes, cutouts, reduced compressive strength after impact, and the like.

Transient simulation of groundwater levels within a sandbar of the Colorado River, Marble Canyon, Arizona, 2004

USGS Publications Warehouse

Sabol, Thomas A.; Springer, Abraham E.

2013-01-01

Seepage erosion and mass failure of emergent sandy deposits along the Colorado River in Grand Canyon National Park, Arizona, are a function of the elevation of groundwater in the sandbar, fluctuations in river stage, the exfiltration of water from the bar face, and the slope of the bar face. In this study, a generalized three-dimensional numerical model was developed to predict the time-varying groundwater level, within the bar face region of a freshly deposited eddy sandbar, as a function of river stage. Model verification from two transient simulations demonstrates the ability of the model to predict groundwater levels within the onshore portion of the sandbar face across a range of conditions. Use of this generalized model is applicable across a range of typical eddy sandbar deposits in diverse settings. The ability to predict the groundwater level at the onshore end of the sandbar face is essential for both physical and numerical modeling efforts focusing on the erosion and mass failure of eddy sandbars downstream of Glen Canyon Dam along the Colorado River.

Macrodamage Accumulation Model for a Human Femur

PubMed Central

2017-01-01

The objective of this study was to more fully understand the mechanical behavior of bone tissue that is important to find an alternative material to be used as an implant and to develop an accurate model to predict the fracture of the bone. Predicting and preventing bone failure is an important area in orthopaedics. In this paper, the macrodamage accumulation models in the bone tissue have been investigated. Phenomenological models for bone damage have been discussed in detail. In addition, 3D finite element model of the femur prepared from imaging data with both cortical and trabecular structures is delineated using MIMICS and ANSYS® and simulated as a composite structure. The damage accumulation occurring during cyclic loading was analyzed for fatigue scenario. We found that the damage accumulates sooner in the multiaxial than in the uniaxial loading condition for the same number of cycles, and the failure starts in the cortical bone. The damage accumulation behavior seems to follow a three-stage growth: a primary phase, a secondary phase of damage growth marked by linear damage growth, and a tertiary phase that leads to failure. Finally, the stiffness of the composite bone comprising the cortical and trabecular bone was significantly different as expected. PMID:28951659

Life prediction technologies for aeronautical propulsion systems

NASA Technical Reports Server (NTRS)

Mcgaw, Michael A.

1987-01-01

Fatigue and fracture problems continue to occur in aeronautical gas turbine engines. Components whose useful life is limited by these failure modes include turbine hot-section blades, vanes and disks. Safety considerations dictate that catastrophic failures be avoided, while economic considerations dictate that noncatastrophic failures occur as infrequently as possible. The design decision is therefore in making the tradeoff between engine performance and durability. The NASA Lewis Research Center has contributed to the aeropropulsion industry in the areas of life prediction technology for 30 years, developing creep and fatigue life prediction methodologies for hot-section materials. Emphasis is placed on the development of methods capable of handling both thermal and mechanical fatigue under severe environments. Recent accomplishments include the development of more accurate creep-fatigue life prediction methods such as the total strain version of Lewis' Strainrange Partitioning (SRP) and the HOST-developed Cyclic Damage Accumulation (CDA) model. Other examples include the Double Damage Curve Approach (DDCA), which provides greatly improved accuracy for cumulative fatigue design rules.

Shell feature: a new radiomics descriptor for predicting distant failure after radiotherapy in non-small cell lung cancer and cervix cancer

NASA Astrophysics Data System (ADS)

Hao, Hongxia; Zhou, Zhiguo; Li, Shulong; Maquilan, Genevieve; Folkert, Michael R.; Iyengar, Puneeth; Westover, Kenneth D.; Albuquerque, Kevin; Liu, Fang; Choy, Hak; Timmerman, Robert; Yang, Lin; Wang, Jing

2018-05-01

Distant failure is the main cause of human cancer-related mortalities. To develop a model for predicting distant failure in non-small cell lung cancer (NSCLC) and cervix cancer (CC) patients, a shell feature, consisting of outer voxels around the tumor boundary, was constructed using pre-treatment positron emission tomography (PET) images from 48 NSCLC patients received stereotactic body radiation therapy and 52 CC patients underwent external beam radiation therapy and concurrent chemotherapy followed with high-dose-rate intracavitary brachytherapy. The hypothesis behind this feature is that non-invasive and invasive tumors may have different morphologic patterns in the tumor periphery, in turn reflecting the differences in radiological presentations in the PET images. The utility of the shell was evaluated by the support vector machine classifier in comparison with intensity, geometry, gray level co-occurrence matrix-based texture, neighborhood gray tone difference matrix-based texture, and a combination of these four features. The results were assessed in terms of accuracy, sensitivity, specificity, and AUC. Collectively, the shell feature showed better predictive performance than all the other features for distant failure prediction in both NSCLC and CC cohorts.

Damage Simulation in Non-Crimp Fabric Composite Plates Subjected to Impact Loads

NASA Technical Reports Server (NTRS)

Satyanarayana, Arunkumar; Bogert, Philip B.; Aitharaju, Venkat; Aashat, Satvir; Kia, Hamid

2014-01-01

Progressive failure analysis (PFA) of non-crimp fabric (NCF) composite laminates subjected to low velocity impact loads was performed using the COmplete STress Reduction (COSTR) damage model implemented through VUMAT and UMAT41 user subroutines in the frame works of the commercial finite element programs ABAQUS/Explicit and LS-DYNA, respectively. To validate the model, low velocity experiments were conducted and detailed correlations between the predictions and measurements for both intra-laminar and inter-laminar failures were made. The developed material and damage model predicts the peak impact load and duration very close with the experimental results. Also, the simulation results of delamination damage between the ply interfaces, in-plane matrix damages and fiber damages were all in good agreement with the measurements from the non-destructive evaluation data.

A model for predicting embankment slope failures in clay-rich soils; A Louisiana example

NASA Astrophysics Data System (ADS)

Burns, S. F.

2015-12-01

A model for predicting embankment slope failures in clay-rich soils; A Louisiana example It is well known that smectite-rich soils significantly reduce the stability of slopes. The question is how much smectite in the soil causes slope failures. A study of over 100 sites in north and south Louisiana, USA, compared slopes that failed during a major El Nino winter (heavy rainfall) in 1982-1983 to similar slopes that did not fail. Soils in the slopes were tested for per cent clay, liquid limits, plasticity indices and semi-quantitative clay mineralogy. Slopes with the High Risk for failure (85-90% chance of failure in 8-15 years after construction) contained soils with a liquid limit > 54%, a plasticity index over 29%, and clay contents > 47%. Slopes with an Intermediate Risk (55-50% chance of failure in 8-15 years) contained soils with a liquid limit between 36-54%, plasticity index between 16-19%, and clay content between 32-47%. Slopes with a Low Risk chance of failure (< 5% chance of failure in 8-15 years after construction) contained soils with a liquid limit < 36%, a plasticity index < 16%, and a clay content < 32%. These data show that if one is constructing embankments and one wants to prevent slope failure of the 3:1 slopes, check the above soil characteristics before construction. If the soils fall into the Low Risk classification, construct the embankment normally. If the soils fall into the High Risk classification, one will need to use lime stabilization or heat treatments to prevent failures. Soils in the Intermediate Risk class will have to be evaluated on a case by case basis.

Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model: A Web-based program designed to evaluate the cost-effectiveness of disease management programs in heart failure.

PubMed

Reed, Shelby D; Neilson, Matthew P; Gardner, Matthew; Li, Yanhong; Briggs, Andrew H; Polsky, Daniel E; Graham, Felicia L; Bowers, Margaret T; Paul, Sara C; Granger, Bradi B; Schulman, Kevin A; Whellan, David J; Riegel, Barbara; Levy, Wayne C

2015-11-01

Heart failure disease management programs can influence medical resource use and quality-adjusted survival. Because projecting long-term costs and survival is challenging, a consistent and valid approach to extrapolating short-term outcomes would be valuable. We developed the Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model, a Web-based simulation tool designed to integrate data on demographic, clinical, and laboratory characteristics; use of evidence-based medications; and costs to generate predicted outcomes. Survival projections are based on a modified Seattle Heart Failure Model. Projections of resource use and quality of life are modeled using relationships with time-varying Seattle Heart Failure Model scores. The model can be used to evaluate parallel-group and single-cohort study designs and hypothetical programs. Simulations consist of 10,000 pairs of virtual cohorts used to generate estimates of resource use, costs, survival, and incremental cost-effectiveness ratios from user inputs. The model demonstrated acceptable internal and external validity in replicating resource use, costs, and survival estimates from 3 clinical trials. Simulations to evaluate the cost-effectiveness of heart failure disease management programs across 3 scenarios demonstrate how the model can be used to design a program in which short-term improvements in functioning and use of evidence-based treatments are sufficient to demonstrate good long-term value to the health care system. The Tools for Economic Analysis of Patient Management Interventions in Heart Failure Cost-Effectiveness Model provides researchers and providers with a tool for conducting long-term cost-effectiveness analyses of disease management programs in heart failure. Copyright © 2015 Elsevier Inc. All rights reserved.

Factors Predicting Meniscal Allograft Transplantation Failure

PubMed Central

Parkinson, Ben; Smith, Nicholas; Asplin, Laura; Thompson, Peter; Spalding, Tim

2016-01-01

Background: Meniscal allograft transplantation (MAT) is performed to improve symptoms and function in patients with a meniscal-deficient compartment of the knee. Numerous studies have shown a consistent improvement in patient-reported outcomes, but high failure rates have been reported by some studies. The typical patients undergoing MAT often have multiple other pathologies that require treatment at the time of surgery. The factors that predict failure of a meniscal allograft within this complex patient group are not clearly defined. Purpose: To determine predictors of MAT failure in a large series to refine the indications for surgery and better inform future patients. Study Design: Cohort study; Level of evidence, 3. Methods: All patients undergoing MAT at a single institution between May 2005 and May 2014 with a minimum of 1-year follow-up were prospectively evaluated and included in this study. Failure was defined as removal of the allograft, revision transplantation, or conversion to a joint replacement. Patients were grouped according to the articular cartilage status at the time of the index surgery: group 1, intact or partial-thickness chondral loss; group 2, full-thickness chondral loss 1 condyle; and group 3, full-thickness chondral loss both condyles. The Cox proportional hazards model was used to determine significant predictors of failure, independently of other factors. Kaplan-Meier survival curves were produced for overall survival and significant predictors of failure in the Cox proportional hazards model. Results: There were 125 consecutive MATs performed, with 1 patient lost to follow-up. The median follow-up was 3 years (range, 1-10 years). The 5-year graft survival for the entire cohort was 82% (group 1, 97%; group 2, 82%; group 3, 62%). The probability of failure in group 1 was 85% lower (95% CI, 13%-97%) than in group 3 at any time. The probability of failure with lateral allografts was 76% lower (95% CI, 16%-89%) than medial allografts at any time. Conclusion: This study showed that the presence of severe cartilage damage at the time of MAT and medial allografts were significantly predictive of failure. Surgeons and patients should use this information when considering the risks and benefits of surgery. PMID:27583257

Failure-probability driven dose painting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vogelius, Ivan R.; Håkansson, Katrin; Due, Anne K.

Purpose: To demonstrate a data-driven dose-painting strategy based on the spatial distribution of recurrences in previously treated patients. The result is a quantitative way to define a dose prescription function, optimizing the predicted local control at constant treatment intensity. A dose planning study using the optimized dose prescription in 20 patients is performed.Methods: Patients treated at our center have five tumor subvolumes from the center of the tumor (PET positive volume) and out delineated. The spatial distribution of 48 failures in patients with complete clinical response after (chemo)radiation is used to derive a model for tumor control probability (TCP). Themore » total TCP is fixed to the clinically observed 70% actuarial TCP at five years. Additionally, the authors match the distribution of failures between the five subvolumes to the observed distribution. The steepness of the dose–response is extracted from the literature and the authors assume 30% and 20% risk of subclinical involvement in the elective volumes. The result is a five-compartment dose response model matching the observed distribution of failures. The model is used to optimize the distribution of dose in individual patients, while keeping the treatment intensity constant and the maximum prescribed dose below 85 Gy.Results: The vast majority of failures occur centrally despite the small volumes of the central regions. Thus, optimizing the dose prescription yields higher doses to the central target volumes and lower doses to the elective volumes. The dose planning study shows that the modified prescription is clinically feasible. The optimized TCP is 89% (range: 82%–91%) as compared to the observed TCP of 70%.Conclusions: The observed distribution of locoregional failures was used to derive an objective, data-driven dose prescription function. The optimized dose is predicted to result in a substantial increase in local control without increasing the predicted risk of toxicity.« less

Predicting treatment failure, death and drug resistance using a computed risk score among newly diagnosed TB patients in Tamaulipas, Mexico.

PubMed

Abdelbary, B E; Garcia-Viveros, M; Ramirez-Oropesa, H; Rahbar, M H; Restrepo, B I

2017-10-01

The purpose of this study was to develop a method for identifying newly diagnosed tuberculosis (TB) patients at risk for TB adverse events in Tamaulipas, Mexico. Surveillance data between 2006 and 2013 (8431 subjects) was used to develop risk scores based on predictive modelling. The final models revealed that TB patients failing their treatment regimen were more likely to have at most a primary school education, multi-drug resistance (MDR)-TB, and few to moderate bacilli on acid-fast bacilli smear. TB patients who died were more likely to be older males with MDR-TB, HIV, malnutrition, and reporting excessive alcohol use. Modified risk scores were developed with strong predictability for treatment failure and death (c-statistic 0·65 and 0·70, respectively), and moderate predictability for drug resistance (c-statistic 0·57). Among TB patients with diabetes, risk scores showed moderate predictability for death (c-statistic 0·68). Our findings suggest that in the clinical setting, the use of our risk scores for TB treatment failure or death will help identify these individuals for tailored management to prevent these adverse events. In contrast, the available variables in the TB surveillance dataset are not robust predictors of drug resistance, indicating the need for prompt testing at time of diagnosis.

Method for Predicting Thermal Buckling in Rails

DOT National Transportation Integrated Search

2018-01-01

A method is proposed herein for predicting the onset of thermal buckling in rails in such a way as to provide a means of avoiding this type of potentially devastating failure. The method consists of the development of a thermomechanical model of rail...

Friction of hard surfaces and its application in earthquakes and rock slope stability

NASA Astrophysics Data System (ADS)

Sinha, Nitish; Singh, Arun K.; Singh, Trilok N.

2018-05-01

In this article, we discuss the friction models for hard surfaces and their applications in earth sciences. The rate and state friction (RSF) model, which is basically modified form of the classical Amontons-Coulomb friction laws, is widely used for explaining the crustal earthquakes and the rock slope failures. Yet the RSF model has further been modified by considering the role of temperature at the sliding interface known as the rate, state and temperature friction (RSTF) model. Further, if the pore pressure is also taken into account then it is stated as the rate, state, temperature and pore pressure friction (RSTPF) model. All the RSF models predict a critical stiffness as well as a critical velocity at which sliding behavior becomes stable/unstable. The friction models are also used for predicting time of failure of the rock mass on an inclined plane. Finally, the limitation and possibilities of the proposed friction models are also highlighted.

Percutaneous Coronary Revascularization for Chronic Total Occlusions: A Novel Predictive Score of Technical Failure Using Advanced Technologies.

PubMed

Galassi, Alfredo R; Boukhris, Marouane; Azzarelli, Salvatore; Castaing, Marine; Marzà, Francesco; Tomasello, Salvatore D

2016-05-09

The aims of this study were to describe the 10-year experience of a single operator dedicated to chronic total occlusion (CTO) and to establish a model for predicting technical failure. During the last decade, the interest in percutaneous coronary interventions (PCIs) of chronic total occlusions (CTOs) has increased, allowing the improvement of success rate. One thousand nineteen patients with CTO underwent 1,073 CTO procedures performed by a single CTO-dedicated operator. The study population was subdivided into 2 groups by time period: period 1 (January 2005 to December 2009, n = 378) and period 2 (January 2010 to December 2014, n = 641). Observations were randomly assigned to a derivation set and a validation set (in a 2:1 ratio). A prediction score was established by assigning points for each independent predictor of technical failure in the derivation set according to the beta coefficient and summing all points accrued. Lesions attempted in period 2 were more complex in comparison with those in period 1. Compared with period 1, both technical and clinical success rates significantly improved (from 87.8% to 94.4% [p = 0.001] and from 77.6% to 89.9% [p < 0.001], respectively). A prediction score for technical failure including age ≥75 years (1 point), ostial location (1 point), and collateral filling Rentrop grade <2 (2 points) was established, stratifying procedures into 4 difficulty groups: easy (0), intermediate (1), difficult (2), and very difficult (3 or 4), with decreasing technical success rates. In derivation and validation sets, areas under the curve were comparable (0.728 and 0.772, respectively). With growing expertise, the success rate has increased despite increasing complexity of attempted lesions. The established model predicted the probability of technical failure and thus might be applied to grading the difficulty of CTO procedures. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-01-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Astrophysics Data System (ADS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-03-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

A New Local Failure Model with Application to the Longitudinal Tensile Behavior of Continuously Reinforced Titanium Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2000-01-01

A new model for local fiber failures in composite materials loaded longitudinally is presented. In developing the model, the goal was to account for the effects of fiber breakage on the global response of a composite in a relatively simple and efficient manner. Towards this end, the model includes the important feature of local stress unloading, even as global loading of the composite continues. The model has been incorporated into NASA Glenn's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) and was employed to simulate the longitudinal tensile deformation and failure behavior of several silicon carbide fiber/titanium matrix (SiC/Ti) composites. The model is shown to be quite realistic and capable of accurate predictions for various temperatures, fiber volume fractions, and fiber diameters. Further- more, the new model compares favorably to Curtin's (1993) effective fiber breakage model, which has also been incorporated into MAC/GMC.

Empirical and semi-analytical models for predicting peak outflows caused by embankment dam failures

NASA Astrophysics Data System (ADS)

Wang, Bo; Chen, Yunliang; Wu, Chao; Peng, Yong; Song, Jiajun; Liu, Wenjun; Liu, Xin

2018-07-01

Prediction of peak discharge of floods has attracted great attention for researchers and engineers. In present study, nine typical nonlinear mathematical models are established based on database of 40 historical dam failures. The first eight models that were developed with a series of regression analyses are purely empirical, while the last one is a semi-analytical approach that was derived from an analytical solution of dam-break floods in a trapezoidal channel. Water depth above breach invert (Hw), volume of water stored above breach invert (Vw), embankment length (El), and average embankment width (Ew) are used as independent variables to develop empirical formulas of estimating the peak outflow from breached embankment dams. It is indicated from the multiple regression analysis that a function using the former two variables (i.e., Hw and Vw) produce considerably more accurate results than that using latter two variables (i.e., El and Ew). It is shown that the semi-analytical approach works best in terms of both prediction accuracy and uncertainty, and the established empirical models produce considerably reasonable results except the model only using El. Moreover, present models have been compared with other models available in literature for estimating peak discharge.

Progressive failure methodologies for predicting residual strength and life of laminated composites

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Allen, David H.; Obrien, T. Kevin

1991-01-01

Two progressive failure methodologies currently under development by the Mechanics of Materials Branch at NASA Langley Research Center are discussed. The damage tolerance/fail safety methodology developed by O'Brien is an engineering approach to ensuring adequate durability and damage tolerance by treating only delamination onset and the subsequent delamination accumulation through the laminate thickness. The continuum damage model developed by Allen and Harris employs continuum damage laws to predict laminate strength and life. The philosophy, mechanics framework, and current implementation status of each methodology are presented.

Failure prediction of thin beryllium sheets used in spacecraft structures

NASA Technical Reports Server (NTRS)

Roschke, Paul N.; Mascorro, Edward; Papados, Photios; Serna, Oscar R.

1991-01-01

The primary objective of this study is to develop a method for prediction of failure of thin beryllium sheets that undergo complex states of stress. Major components of the research include experimental evaluation of strength parameters for cross-rolled beryllium sheet, application of the Tsai-Wu failure criterion to plate bending problems, development of a high order failure criterion, application of the new criterion to a variety of structures, and incorporation of both failure criteria into a finite element code. A Tsai-Wu failure model for SR-200 sheet material is developed from available tensile data, experiments carried out by NASA on two circular plates, and compression and off-axis experiments performed in this study. The failure surface obtained from the resulting criterion forms an ellipsoid. By supplementing experimental data used in the the two-dimensional criterion and modifying previously suggested failure criteria, a multi-dimensional failure surface is proposed for thin beryllium structures. The new criterion for orthotropic material is represented by a failure surface in six-dimensional stress space. In order to determine coefficients of the governing equation, a number of uniaxial, biaxial, and triaxial experiments are required. Details of these experiments and a complementary ultrasonic investigation are described in detail. Finally, validity of the criterion and newly determined mechanical properties is established through experiments on structures composed of SR200 sheet material. These experiments include a plate-plug arrangement under a complex state of stress and a series of plates with an out-of-plane central point load. Both criteria have been incorporated into a general purpose finite element analysis code. Numerical simulation incrementally applied loads to a structural component that is being designed and checks each nodal point in the model for exceedance of a failure criterion. If stresses at all locations do not exceed the failure criterion, the load is increased and the process is repeated. Failure results for the plate-plug and clamped plate tests are accurate to within 2 percent.

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear finite element program MSC.Dytran was used to predict the impact pulse for (he drop test of an energy absorbing cellular structure. This pre-test simulation was performed to aid in the design of an energy absorbing concept for a highly reliable passive Earth Entry Vehicle (EEV) that will directly impact the Earth without a parachute. In addition, a goal of the simulation was to bound the acceleration pulse produced and delivered to the simulated space cargo container. EEV's are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the enter of the EEV's cellular structure. The material models and failure criteria were varied to determine their effect on the resulting acceleration pulse. Pre-test analytical predictions using MSC.Dytran were compared with the test results obtained from impact test #4 using bungee accelerator located at the NASA Langley Research Center Impact Dynamics Research Facility. The material model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAMI model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for drop test #4.

Influence of enamel preservation on failure rates of porcelain laminate veneers.

PubMed

Gurel, Galip; Sesma, Newton; Calamita, Marcelo A; Coachman, Christian; Morimoto, Susana

2013-01-01

The purpose of this study was to evaluate the failure rates of porcelain laminate veneers (PLVs) and the influence of clinical parameters on these rates in a retrospective survey of up to 12 years. Five hundred eighty laminate veneers were bonded in 66 patients. The following parameters were analyzed: type of preparation (depth and margin), crown lengthening, presence of restoration, diastema, crowding, discoloration, abrasion, and attrition. Survival was analyzed using the Kaplan-Meier method. Cox regression modeling was used to determine which factors would predict PLV failure. Forty-two veneers (7.2%) failed in 23 patients, and an overall cumulative survival rate of 86% was observed. A statistically significant association was noted between failure and the limits of the prepared tooth surface (margin and depth). The most frequent failure type was fracture (n = 20). The results revealed no significant influence of crown lengthening apically, presence of restoration, diastema, discoloration, abrasion, or attrition on failure rates. Multivariable analysis (Cox regression model) also showed that PLVs bonded to dentin and teeth with preparation margins in dentin were approximately 10 times more likely to fail than PLVs bonded to enamel. Moreover, coronal crown lengthening increased the risk of PLV failure by 2.3 times. A survival rate of 99% was observed for veneers with preparations confined to enamel and 94% for veneers with enamel only at the margins. Laminate veneers have high survival rates when bonded to enamel and provide a safe and predictable treatment option that preserves tooth structure.

Combining Early Coagulation and Inflammatory Status Improves Prediction of Mortality in Burned and Nonburned Trauma Patients

DTIC Science & Technology

2008-02-01

clinician to distinguish between the effects of treatment and the effects of disease. Several different prediction models for multiple or- gan failure...treat- ment protocols and allow a clinician to distinguish the effect of treatment from effect of disease. In this study, our model predicted in...TNF produces a decrease in protein C activation by down regulating the expression of endothelial cell protein C receptor and thrombomodulin, both of

An assessment of models that predict soil reinforcement by plant roots

NASA Astrophysics Data System (ADS)

Hallett, P. D.; Loades, K. W.; Mickovski, S.; Bengough, A. G.; Bransby, M. F.; Davies, M. C. R.; Sonnenberg, R.

2009-04-01

Predicting soil reinforcement by plant roots is fraught with uncertainty because of spatio-temporal variability, the mechanical complexity of roots and soil, and the limitations of existing models. In this study, the validity of root-reinforcement models was tested with data from numerous controlled laboratory tests of both fibrous and woody root systems. By using pot experiments packed with homogeneous soil, each planted with one plant species and grown in glasshouses with controlled water and temperature regimes, spatio-temporal variability was reduced. After direct shear testing to compare the mechanical behaviour of planted versus unplanted samples, the size distribution of roots crossing the failure surface was measured accurately. Separate tensile tests on a wide range of root sizes for each test series provided information on the scaling of root strength and stiffness, which was fitted using power-law relationships. These data were used to assess four root-reinforcement models: (1) Wu et al.'s (1979) root-reinforcement model, (2) Rip-Root fibre bundle model (FBM) proposed by Pollen & Simon (2005), (3) a stress-based FBM and (4) a strain-based FBM. For both fibrous (barley) and woody (willow) root systems, all of the FBMs provided a better prediction of reinforcement than Wu's root-reinforcement model. As FBMs simulate progressive failure of roots, they reflect reality better than the Wu model which assumes all roots break (and contribute to increased shear strength) simultaneously. However, all of the FBMs contain assumptions about the distribution of the applied load within the bundle of roots and the failure criterion. The stress-based FBM assumes the same stiffness for different sized roots, resulting in progressive failure from the largest to smallest roots. This is not observed in testing where the smallest roots fail first. The Rip-Root FBM predicts failure from smallest to largest roots, but the distribution of load between different sized roots is based on unverified scaling rules (stiffness is inversely proportional to diameter). In the strain-based FBM, both stiffness and strength data are used to evaluate root breakage. As roots stretch across the shear surface, the stress mobilised in individual roots depends on both their individual stiffness and strain. Small roots being stiffer, mobilise more stress for the same strain (or shear displacement) and therefore fail first. The strain based FBM offers promise as a starting point to predict the reinforcement of soil by plant roots using sound mechanical principles. Compared to other models, it provided the best prediction of root reinforcement. Further developments are required to account particularly for the stochastic variability of the mechanical behaviour and spatial distribution of roots and this will be achieved by adapting advanced fibre bundle methods. Pollen, N., and A. Simon. 2005. Estimating the mechanical effects of riparian vegetation on stream bank stability using a fiber bundle model. Water Resour. Res. 41: W07025. Wu T. H., W. P. McKinnell, and D. N. Swanston. 1979. Strength of tree roots and landslides on Prince of Wales Island, Alaska. Can. Geotech. J. 16: 19-33.

Methods, apparatus and system for notification of predictable memory failure

DOEpatents

Cher, Chen-Yong; Andrade Costa, Carlos H.; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

2017-01-03

A method for providing notification of a predictable memory failure includes the steps of: obtaining information regarding at least one condition associated with a memory; calculating a memory failure probability as a function of the obtained information; calculating a failure probability threshold; and generating a signal when the memory failure probability exceeds the failure probability threshold, the signal being indicative of a predicted future memory failure.

Finite Element Model for Failure Study of Two-Dimensional Triaxially Braided Composite

NASA Technical Reports Server (NTRS)

Li, Xuetao; Binienda, Wieslaw K.; Goldberg, Robert K.

2010-01-01

A new three-dimensional finite element model of two-dimensional triaxially braided composites is presented in this paper. This meso-scale modeling technique is used to examine and predict the deformation and damage observed in tests of straight sided specimens. A unit cell based approach is used to take into account the braiding architecture as well as the mechanical properties of the fiber tows, the matrix and the fiber tow-matrix interface. A 0 deg / plus or minus 60 deg. braiding configuration has been investigated by conducting static finite element analyses. Failure initiation and progressive degradation has been simulated in the fiber tows by use of the Hashin failure criteria and a damage evolution law. The fiber tow-matrix interface was modeled by using a cohesive zone approach to capture any fiber-matrix debonding. By comparing the analytical results to those obtained experimentally, the applicability of the developed model was assessed and the failure process was investigated.

Statistical analysis of lithium iron sulfide status cell cycle life and failure mode

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gay, E.C.; Battles, J.E.; Miller, W.E.

1983-08-01

A statistical model was developed for life cycle testing of electrochemical cell life cycle trials and verified experimentally. The Weibull distribution was selected to predict the end of life for a cell, based on a 20 percent loss of initial stabilized capacity or a decrease to less than 95 percent coulombic efficiency. Groups of 12 or more Li-alloy/FeS cells were cycled to determine the mean time to failure (MTTF) and also to identify the failure modes. The cells were all full size electric vehicle batteries with 150-350 A-hr capacity. The Weibull shape factors were determined and verified in prediction ofmore » the number of cell failures in two 10 cell modules. The short circuit failure in the cells with BN-felt and MgO powder separators were found to be caused by the formation of Li-Al protrusions that penetrated the BN-felt separators, and the extrusion of active material at the edge of the electrodes.« less

Developing EHR-driven heart failure risk prediction models using CPXR(Log) with the probabilistic loss function.

PubMed

Taslimitehrani, Vahid; Dong, Guozhu; Pereira, Naveen L; Panahiazar, Maryam; Pathak, Jyotishman

2016-04-01

Computerized survival prediction in healthcare identifying the risk of disease mortality, helps healthcare providers to effectively manage their patients by providing appropriate treatment options. In this study, we propose to apply a classification algorithm, Contrast Pattern Aided Logistic Regression (CPXR(Log)) with the probabilistic loss function, to develop and validate prognostic risk models to predict 1, 2, and 5year survival in heart failure (HF) using data from electronic health records (EHRs) at Mayo Clinic. The CPXR(Log) constructs a pattern aided logistic regression model defined by several patterns and corresponding local logistic regression models. One of the models generated by CPXR(Log) achieved an AUC and accuracy of 0.94 and 0.91, respectively, and significantly outperformed prognostic models reported in prior studies. Data extracted from EHRs allowed incorporation of patient co-morbidities into our models which helped improve the performance of the CPXR(Log) models (15.9% AUC improvement), although did not improve the accuracy of the models built by other classifiers. We also propose a probabilistic loss function to determine the large error and small error instances. The new loss function used in the algorithm outperforms other functions used in the previous studies by 1% improvement in the AUC. This study revealed that using EHR data to build prediction models can be very challenging using existing classification methods due to the high dimensionality and complexity of EHR data. The risk models developed by CPXR(Log) also reveal that HF is a highly heterogeneous disease, i.e., different subgroups of HF patients require different types of considerations with their diagnosis and treatment. Our risk models provided two valuable insights for application of predictive modeling techniques in biomedicine: Logistic risk models often make systematic prediction errors, and it is prudent to use subgroup based prediction models such as those given by CPXR(Log) when investigating heterogeneous diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

Method of Testing and Predicting Failures of Electronic Mechanical Systems

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, Frances A.

1996-01-01

A method employing a knowledge base of human expertise comprising a reliability model analysis implemented for diagnostic routines is disclosed. The reliability analysis comprises digraph models that determine target events created by hardware failures human actions, and other factors affecting the system operation. The reliability analysis contains a wealth of human expertise information that is used to build automatic diagnostic routines and which provides a knowledge base that can be used to solve other artificial intelligence problems.

Internal Progressive Failure in Deep-Seated Landslides

NASA Astrophysics Data System (ADS)

Yerro, Alba; Pinyol, Núria M.; Alonso, Eduardo E.

2016-06-01

Except for simple sliding motions, the stability of a slope does not depend only on the resistance of the basal failure surface. It is affected by the internal distortion of the moving mass, which plays an important role on the stability and post-failure behaviour of a landslide. The paper examines the stability conditions and the post-failure behaviour of a compound landslide whose geometry is inspired by one of the representative cross-sections of Vajont landslide. The brittleness of the mobilized rock mass was described by a strain-softening Mohr-Coulomb model, whose parameters were derived from previous contributions. The analysis was performed by means of a MPM computer code, which is capable of modelling the whole instability procedure in a unified calculation. The gravity action has been applied to initialize the stress state. This step mobilizes part of the strength along a shearing band located just above the kink of the basal surface, leading to the formation a kinematically admissible mechanism. The overall instability is triggered by an increase of water level. The increase of pore water pressures reduces the effective stresses within the slope and it leads to a progressive failure mechanism developing along an internal shearing band which controls the stability of the compound slope. The effect of the basal shearing resistance has been analysed during the post-failure stage. If no shearing strength is considered (as predicted by a thermal pressurization analysis), the model predicts a response similar to actual observations, namely a maximum sliding velocity of 25 m/s and a run-out close to 500 m.

Depression and Delinquency Covariation in an Accelerated Longitudinal Sample of Adolescents

PubMed Central

Kofler, Michael J.; McCart, Michael R.; Zajac, Kristyn; Ruggiero, Kenneth J.; Saunders, Benjamin E.; Kilpatrick, Dean G.

2015-01-01

Objectives The current study tested opposing predictions stemming from the failure and acting out theories of depression-delinquency covariation. Methods Participants included a nationwide longitudinal sample of adolescents (N = 3,604) ages 12 to 17. Competing models were tested using cohort-sequential latent growth curve modeling to determine whether depressive symptoms at age 12 (baseline) predicted concurrent and age-related changes in delinquent behavior, whether the opposite pattern was apparent (delinquency predicting depression), and whether initial levels of depression predict changes in delinquency significantly better than vice versa. Results Early depressive symptoms predicted age-related changes in delinquent behavior significantly better than early delinquency predicted changes in depressive symptoms. In addition, the impact of gender on age-related changes in delinquent symptoms was mediated by gender differences in depressive symptom changes, indicating that depressive symptoms are a particularly salient risk factor for delinquent behavior in girls. Conclusion Early depressive symptoms represent a significant risk factor for later delinquent behavior – especially for girls – and appear to be a better predictor of later delinquency than early delinquency is of later depression. These findings provide support for the acting out theory and contradict failure theory predictions. PMID:21787049

Predicting the dynamic fracture of steel via a non-local strain-energy density failure criterion.

DOT National Transportation Integrated Search

2014-06-01

Predicting the onset of fracture in a material subjected to dynamic loading conditions has typically been heavily mesh-dependent, and often must be specifically calibrated for each geometric design. This can lead to costly models and even : costlier ...

An accelerating precursor to predict "time-to-failure" in creep and volcanic eruptions

NASA Astrophysics Data System (ADS)

Hao, Shengwang; Yang, Hang; Elsworth, Derek

2017-09-01

Real-time prediction by monitoring of the evolution of response variables is a central goal in predicting rock failure. A linear relation Ω˙Ω¨-1 = C(tf - t) has been developed to describe the time to failure, where Ω represents a response quantity, C is a constant and tf represents the failure time. Observations from laboratory creep failure experiments and precursors to volcanic eruptions are used to test the validity of the approach. Both cumulative and simple moving window techniques are developed to perform predictions and to illustrate the effects of data selection on the results. Laboratory creep failure experiments on granites show that the linear relation works well during the final approach to failure. For blind prediction, the simple moving window technique is preferred because it always uses the most recent data and excludes effects of early data deviating significantly from the predicted trend. When the predicted results show only small fluctuations, failure is imminent.

Evaluating a slope-stability model for shallow rain-induced landslides using gage and satellite data

USGS Publications Warehouse

Yatheendradas, S.; Kirschbaum, D.; Baum, Rex L.; Godt, Jonathan W.

2014-01-01

Improving prediction of landslide early warning systems requires accurate estimation of the conditions that trigger slope failures. This study tested a slope-stability model for shallow rainfall-induced landslides by utilizing rainfall information from gauge and satellite records. We used the TRIGRS model (Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis) for simulating the evolution of the factor of safety due to rainfall infiltration. Using a spatial subset of a well-characterized digital landscape from an earlier study, we considered shallow failure on a slope adjoining an urban transportation roadway near the Seattle area in Washington, USA.We ran the TRIGRS model using high-quality rain gage and satellite-based rainfall data from the Tropical Rainfall Measuring Mission (TRMM). Preliminary results with parameterized soil depth values suggest that the steeper slope values in this spatial domain have factor of safety values that are extremely close to the failure limit within an extremely narrow range of values, providing multiple false alarms. When the soil depths were constrained using a back analysis procedure to ensure that slopes were stable under initial condtions, the model accurately predicted the timing and location of the landslide observation without false alarms over time for gage rain data. The TRMM satellite rainfall data did not show adequately retreived rainfall peak magnitudes and accumulation over the study period, and as a result failed to predict the landslide event. These preliminary results indicate that more accurate and higher-resolution rain data (e.g., the upcoming Global Precipitation Measurement (GPM) mission) are required to provide accurate and reliable landslide predictions in ungaged basins.

Proposal for a New Predictive Model of Short-Term Mortality After Living Donor Liver Transplantation due to Acute Liver Failure.

PubMed

Chung, Hyun Sik; Lee, Yu Jung; Jo, Yun Sung

2017-02-21

BACKGROUND Acute liver failure (ALF) is known to be a rapidly progressive and fatal disease. Various models which could help to estimate the post-transplant outcome for ALF have been developed; however, none of them have been proved to be the definitive predictive model of accuracy. We suggest a new predictive model, and investigated which model has the highest predictive accuracy for the short-term outcome in patients who underwent living donor liver transplantation (LDLT) due to ALF. MATERIAL AND METHODS Data from a total 88 patients were collected retrospectively. King's College Hospital criteria (KCH), Child-Turcotte-Pugh (CTP) classification, and model for end-stage liver disease (MELD) score were calculated. Univariate analysis was performed, and then multivariate statistical adjustment for preoperative variables of ALF prognosis was performed. A new predictive model was developed, called the MELD conjugated serum phosphorus model (MELD-p). The individual diagnostic accuracy and cut-off value of models in predicting 3-month post-transplant mortality were evaluated using the area under the receiver operating characteristic curve (AUC). The difference in AUC between MELD-p and the other models was analyzed. The diagnostic improvement in MELD-p was assessed using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS The MELD-p and MELD scores had high predictive accuracy (AUC >0.9). KCH and serum phosphorus had an acceptable predictive ability (AUC >0.7). The CTP classification failed to show discriminative accuracy in predicting 3-month post-transplant mortality. The difference in AUC between MELD-p and the other models had statistically significant associations with CTP and KCH. The cut-off value of MELD-p was 3.98 for predicting 3-month post-transplant mortality. The NRI was 9.9% and the IDI was 2.9%. CONCLUSIONS MELD-p score can predict 3-month post-transplant mortality better than other scoring systems after LDLT due to ALF. The recommended cut-off value of MELD-p is 3.98.

A Multiscale Progressive Failure Modeling Methodology for Composites that Includes Fiber Strength Stochastics

NASA Technical Reports Server (NTRS)

Ricks, Trenton M.; Lacy, Thomas E., Jr.; Bednarcyk, Brett A.; Arnold, Steven M.; Hutchins, John W.

2014-01-01

A multiscale modeling methodology was developed for continuous fiber composites that incorporates a statistical distribution of fiber strengths into coupled multiscale micromechanics/finite element (FE) analyses. A modified two-parameter Weibull cumulative distribution function, which accounts for the effect of fiber length on the probability of failure, was used to characterize the statistical distribution of fiber strengths. A parametric study using the NASA Micromechanics Analysis Code with the Generalized Method of Cells (MAC/GMC) was performed to assess the effect of variable fiber strengths on local composite failure within a repeating unit cell (RUC) and subsequent global failure. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a unidirectional SCS-6/TIMETAL 21S metal matrix composite tensile dogbone specimen at 650 degC. Multiscale progressive failure analyses were performed to quantify the effect of spatially varying fiber strengths on the RUC-averaged and global stress-strain responses and failure. The ultimate composite strengths and distribution of failure locations (predominately within the gage section) reasonably matched the experimentally observed failure behavior. The predicted composite failure behavior suggests that use of macroscale models that exploit global geometric symmetries are inappropriate for cases where the actual distribution of local fiber strengths displays no such symmetries. This issue has not received much attention in the literature. Moreover, the model discretization at a specific length scale can have a profound effect on the computational costs associated with multiscale simulations.models that yield accurate yet tractable results.

Virulo

EPA Science Inventory

Virulo is a probabilistic model for predicting virus attenuation. Monte Carlo methods are used to generate ensemble simulations of virus attenuation due to physical, biological, and chemical factors. The model generates a probability of failure to achieve a chosen degree o...

Evaluation of strength and failure of brittle rock containing initial cracks under lithospheric conditions

NASA Astrophysics Data System (ADS)

Li, Xiaozhao; Qi, Chengzhi; Shao, Zhushan; Ma, Chao

2018-02-01

Natural brittle rock contains numerous randomly distributed microcracks. Crack initiation, growth, and coalescence play a predominant role in evaluation for the strength and failure of brittle rocks. A new analytical method is proposed to predict the strength and failure of brittle rocks containing initial microcracks. The formulation of this method is based on an improved wing crack model and a suggested micro-macro relation. In this improved wing crack model, the parameter of crack angle is especially introduced as a variable, and the analytical stress-crack relation considering crack angle effect is obtained. Coupling the proposed stress-crack relation and the suggested micro-macro relation describing the relation between crack growth and axial strain, the stress-strain constitutive relation is obtained to predict the rock strength and failure. Considering different initial microcrack sizes, friction coefficients and confining pressures, effects of crack angle on tensile wedge force acting on initial crack interface are studied, and effects of crack angle on stress-strain constitutive relation of rocks are also analyzed. The strength and crack initiation stress under different crack angles are discussed, and the value of most disadvantaged angle triggering crack initiation and rock failure is founded. The analytical results are similar to the published study results. Rationality of this proposed analytical method is verified.

Interfacial characterization of flexible hybrid electronics

NASA Astrophysics Data System (ADS)

Najafian, Sara; Amirkhizi, Alireza V.; Stapleton, Scott

2018-03-01

Flexible Hybrid Electronics (FHEs) are the new generation of electronics combining flexible plastic film substrates with electronic devices. Besides the electrical features, design improvements of FHEs depend on the prediction of their mechanical and failure behavior. Debonding of electronic components from the flexible substrate is one of the most common and critical failures of these devices, therefore, the experimental determination of material and interface properties is of great importance in the prediction of failure mechanisms. Traditional interface characterization involves isolated shear and normal mode tests such as the double cantilever beam (DCB) and end notch flexure (ENF) tests. However, due to the thin, flexible nature of the materials and manufacturing restrictions, tests mirroring traditional interface characterization experiments may not always be possible. The ideal goal of this research is to design experiments such that each mode of fracture is isolated. However, due to the complex nonlinear nature of the response and small geometries of FHEs, design of the proper tests to characterize the interface properties can be significantly time and cost consuming. Hence numerical modeling has been implemented to design these novel characterization experiments. This research involves loading case and specimen geometry parametric studies using numerical modeling to design future experiments where either shear or normal fracture modes are dominant. These virtual experiments will provide a foundation for designing similar tests for many different types of flexible electronics and predicting the failure mechanism independent of the specific FHE materials.

Aberrant GSTP1 promoter methylation predicts short-term prognosis in acute-on-chronic hepatitis B liver failure.

PubMed

Gao, S; Sun, F-K; Fan, Y-C; Shi, C-H; Zhang, Z-H; Wang, L-Y; Wang, K

2015-08-01

Glutathione-S-transferase P1 (GSTP1) methylation has been demonstrated to be associated with oxidative stress induced liver damage in acute-on-chronic hepatitis B liver failure (ACHBLF). To evaluate the methylation level of GSTP1 promoter in acute-on-chronic hepatitis B liver failure and determine its predictive value for prognosis. One hundred and five patients with acute-on-chronic hepatitis B liver failure, 86 with chronic hepatitis B (CHB) and 30 healthy controls (HC) were retrospectively enrolled. GSTP1 methylation level in peripheral mononuclear cells (PBMC) was detected by MethyLight. Clinical and laboratory parameters were obtained. GSTP1 methylation levels were significantly higher in patients with acute-on-chronic hepatitis B liver failure (median 16.84%, interquartile range 1.83-59.05%) than those with CHB (median 1.25%, interquartile range 0.48-2.47%; P < 0.01) and HC (median 0.80%, interquartile range 0.67-1.27%; P < 0.01). In acute-on-chronic hepatitis B liver failure group, nonsurvivors showed significantly higher GSTP1 methylation levels (P < 0.05) than survivors. GSTP1 methylation level was significantly correlated with total bilirubin (r = 0.29, P < 0.01), prothrombin time activity (r = -0.24, P = 0.01) and model for end-stage liver disease (MELD) score (r = 0.26, P = 0.01). When used to predict 1- or 2-month mortality of acute-on-chronic hepatitis B liver failure, GSTP1 methylation showed significantly better predictive value than MELD score [area under the receiver operating characteristic curve (AUC) 0.89 vs. 0.72, P < 0.01; AUC 0.83 vs. 0.70, P < 0.05 respectively]. Meanwhile, patients with GSTP1 methylation levels above the cut-off points showed significantly poorer survival than those below (P < 0.05). Aberrant GSTP1 promoter methylation exists in acute-on-chronic hepatitis B liver failure and shows high predictive value for short-term mortality. It might serve as a potential prognostic marker for acute-on-chronic hepatitis B liver failure. © 2015 John Wiley & Sons Ltd.

Design study of the geometry of the blanking tool to predict the burr formation of Zircaloy-4 sheet

NASA Astrophysics Data System (ADS)

Ha, Jisun; Lee, Hyungyil; Kim, Dongchul; Kim, Naksoo

2013-12-01

In this work, we investigated factors that influence burr formation for zircaloy-4 sheet used for spacer grids of nuclear fuel roads. Factors we considered are geometric factors of punch. We changed clearance and velocity in order to consider the failure parameters, and we changed shearing angle and corner radius of L-shaped punch in order to consider geometric factors of punch. First, we carried out blanking test with failure parameter of GTN model using L-shaped punch. The tendency of failure parameters and geometric factors that affect burr formation by analyzing sheared edges is investigated. Consequently, geometric factor's influencing on the burr formation is also high as failure parameters. Then, the sheared edges and burr formation with failure parameters and geometric factors is investigated using FE analysis model. As a result of analyzing sheared edges with the variables, we checked geometric factors more affect burr formation than failure parameters. To check the reliability of the FE model, the blanking force and the sheared edges obtained from experiments are compared with the computations considering heat transfer.

Transient Finite Element Analyses Developed to Model Fan Containment Impact Events

NASA Technical Reports Server (NTRS)

Pereira, J. Michael

1997-01-01

Research is underway to establish an increased level of confidence in existing numerical techniques for predicting transient behavior when the fan of a jet engine is released and impacts the fan containment system. To evaluate the predictive accuracy that can currently be obtained, researchers at the NASA Lewis Research Center used the DYNA 3D computer code to simulate large-scale subcomponent impact tests that were conducted at the University of Dayton Research Institute (UDRI) Impact Physics Lab. In these tests, 20- by 40-in. flat metal panels, contoured to the shape of a typical fan case, were impacted by the root section of a fan blade. The panels were oriented at an angle to the path of the projectile that would simulate the conditions in an actual blade-out event. The metal panels were modeled in DYNA 3D using a kinematic hardening model with the strain rate dependence of the yield stress governed by the Cowper-Simons rule. Failure was governed by the effective plastic strain criterion. The model of the fan blade and case just after impact is shown. By varying the maximum effective plastic strain, we obtained good qualitative agreement between the model and the experiments. Both the velocity required to penetrate the case and the deflection during impact compared well. This indicates that the failure criterion and constitutive model may be appropriate, but for DYNA 3D to be useful as a predictive tool, methods to determine accurate model parameters must be established. Simple methods for measuring model parameters are currently being developed. In addition, alternative constitutive models and failure criteria are being investigated.

SEVENTH INTERIM STATUS REPORT: MODEL 9975 PCV O-RING FIXTURE LONG-TERM LEAK PERFORMANCE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daugherty, W.

2012-08-30

A series of experiments to monitor the aging performance of Viton® GLT O-rings used in the Model 9975 package has been ongoing since 2004 at the Savannah River National Laboratory. Seventy tests using mock-ups of 9975 Primary Containment Vessels (PCVs) were assembled and heated to temperatures ranging from 200 to 450 ºF. They were leak-tested initially and have been tested periodically to determine if they meet the criterion of leak-tightness defined in ANSI standard N14.5-97. Fourteen additional tests were initiated in 2008 with GLT-S O-rings heated to temperatures ranging from 200 to 400 ºF. High temperature aging continues for 23more » GLT O-ring fixtures at 200 – 270 ºF. Room temperature leak test failures have been experienced in all of the GLT O-ring fixtures aging at 350 ºF and higher temperatures, and in 8 fixtures aging at 300 ºF. The remaining GLT O-ring fixtures aging at 300 ºF have been retired from testing following more than 5 years at temperature without failure. No failures have yet been observed in GLT O-ring fixtures aging at 200 ºF for 54-72 months, which is still bounding to O-ring temperatures during storage in K-Area Complex (KAC). Based on expectations that the fixtures aging at 200 ºF will remain leak-tight for a significant period yet to come, 2 additional fixtures began aging in 2011 at an intermediate temperature of 270 ºF, with hopes that they may reach a failure condition before the 200 ºF fixtures. High temperature aging continues for 6 GLT-S O-ring fixtures at 200 – 300 ºF. Room temperature leak test failures have been experienced in all 8 of the GLT-S O-ring fixtures aging at 350 and 400 ºF. No failures have yet been observed in GLT-S O-ring fixtures aging at 200 - 300 ºF for 30 - 36 months. For O-ring fixtures that have failed the room temperature leak test and been disassembled, the O-rings displayed a compression set ranging from 51 – 96%. This is greater than seen to date for any packages inspected during KAC field surveillance (24% average). For GLT O-rings, separate service life estimates have been made based on the O-ring fixture leak test data and based on compression stress relaxation (CSR) data. These two predictive models show reasonable agreement at higher temperatures (350 – 400 ºF). However, at 300 ºF, the room temperature leak test failures to date experienced longer aging times than predicted by the CSRbased model. This suggests that extrapolations of the CSR model predictions to temperatures below 300 ºF will provide a conservative prediction of service life relative to the leak rate criterion. Leak test failure data at lower temperatures are needed to verify this apparent trend. Insufficient failure data exist currently to perform a similar comparison for GLT-S O-rings. Aging and periodic leak testing will continue for the remaining PCV O-ring fixtures.« less

Combined mechanical loading of composite tubes

NASA Technical Reports Server (NTRS)

Derstine, Mark S.; Pindera, Marek-Jerzy; Bowles, David E.

1988-01-01

An analytical/experimental investigation was performed to study the effect of material nonlinearities on the response of composite tubes subjected to combined axial and torsional loading. The effect of residual stresses on subsequent mechanical response was included in the investigation. Experiments were performed on P75/934 graphite-epoxy tubes with a stacking sequence of (15/0/ + or - 10/0/ -15), using pure torsion and combined axial/torsional loading. In the presence of residual stresses, the analytical model predicted a reduction in the initial shear modulus. Experimentally, coupling between axial loading and shear strain was observed in laminated tubes under combined loading. The phenomenon was predicted by the nonlinear analytical model. The experimentally observed linear limit of the global shear response was found to correspond to the analytically predicted first ply failure. Further, the failure of the tubes was found to be path dependent above a critical load level.

Modelling of Rainfall Induced Landslides in Puerto Rico

NASA Astrophysics Data System (ADS)

Lepore, C.; Arnone, E.; Sivandran, G.; Noto, L. V.; Bras, R. L.

2010-12-01

We performed an island-wide determination of static landslide susceptibility and hazard assessment as well as dynamic modeling of rainfall-induced shallow landslides in a particular hydrologic basin. Based on statistical analysis of past landslides, we determined that reliable prediction of the susceptibility to landslides is strongly dependent on the resolution of the digital elevation model (DEM) employed and the reliability of the rainfall data. A distributed hydrology model, Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator with VEGetation Generator for Interactive Evolution (tRIBS-VEGGIE), tRIBS-VEGGIE, has been implemented for the first time in a humid tropical environment like Puerto Rico and validated against in-situ measurements. A slope-failure module has been added to tRIBS-VEGGIE’s framework, after analyzing several failure criterions to identify the most suitable for our application; the module is used to predict the location and timing of landsliding events. The Mameyes basin, located in the Luquillo Experimental Forest in Puerto Rico, was selected for modeling based on the availability of soil, vegetation, topographical, meteorological and historic landslide data. Application of the model yields a temporal and spatial distribution of predicted rainfall-induced landslides.

Numerical simulation of damage and progressive failures in composite laminates using the layerwise plate theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reddy, Y.S.

1992-01-01

The failure behavior of composite laminates is modeled numerically using the Generalized Layerwise Plate Theory (GLPT) of Reddy and a progressive failure algorithm. The Layerwise Theory of Reddy assumes a piecewise continuous displacement field through the thickness of the laminate and therefore has the ability to capture the interlaminar stress fields near the free edges and cut outs more accurately. The progressive failure algorithm is based on the assumption that the material behaves like a stable progressively fracturing solid. A three-dimensional stiffness reduction scheme is developed and implemented to study progressive failures in composite laminates. The effect of various parametersmore » such as out-of-plane material properties, boundary conditions, and stiffness reduction methods on the failure stresses and strains of a quasi-isotropic composite laminate with free edges subjected to tensile loading is studied. The ultimate stresses and strains predicted by the Generalized Layerwise Plate Theory (GLPT) and the more widely used First Order Shear Deformation Theory (FSDT) are compared with experimental results. The predictions of the GLPT are found to be in good agreement with the experimental results both qualitatively and quantitatively, while the predictions of FSDT are found to be different from experimental results both qualitatively and quantitatively. The predictive ability of various phenomenological failure criteria is evaluated with reference to the experimental results available in the literature. The effect of geometry of the test specimen and the displacement boundary conditions at the grips on the ultimate stresses and strains of a composite laminate under compressive loading is studied. The ultimate stresses and strains are found to be quite sensitive to the geometry of the test specimen and the displacement boundary conditions at the grips. The degree of sensitivity is observed to depend strongly on the lamination sequence.« less

Management of heart failure in the new era: the role of scores.

PubMed

Mantegazza, Valentina; Badagliacca, Roberto; Nodari, Savina; Parati, Gianfranco; Lombardi, Carolina; Di Somma, Salvatore; Carluccio, Erberto; Dini, Frank Lloyd; Correale, Michele; Magrì, Damiano; Agostoni, Piergiuseppe

2016-08-01

Heart failure is a widespread syndrome involving several organs, still characterized by high mortality and morbidity, and whose clinical course is heterogeneous and hardly predictable.In this scenario, the assessment of heart failure prognosis represents a fundamental step in clinical practice. A single parameter is always unable to provide a very precise prognosis. Therefore, risk scores based on multiple parameters have been introduced, but their clinical utility is still modest. In this review, we evaluated several prognostic models for acute, right, chronic, and end-stage heart failure based on multiple parameters. In particular, for chronic heart failure we considered risk scores essentially based on clinical evaluation, comorbidities analysis, baroreflex sensitivity, heart rate variability, sleep disorders, laboratory tests, echocardiographic imaging, and cardiopulmonary exercise test parameters. What is at present established is that a single parameter is not sufficient for an accurate prediction of prognosis in heart failure because of the complex nature of the disease. However, none of the scoring systems available is widely used, being in some cases complex, not user-friendly, or based on expensive or not easily available parameters. We believe that multiparametric scores for risk assessment in heart failure are promising but their widespread use needs to be experienced.

The failure analysis and lifetime prediction for the solder joint of the magnetic head

NASA Astrophysics Data System (ADS)

Xiao, Xianghui; Peng, Minfang; Cardoso, Jaime S.; Tang, Rongjun; Zhou, YingLiang

2015-02-01

Micro-solder joint (MSJ) lifetime prediction methodology and failure analysis (FA) are to assess reliability by fatigue model with a series of theoretical calculations, numerical simulation and experimental method. Due to shortened time of solder joints on high-temperature, high-frequency sampling error that is not allowed in productions may exist in various models, including round-off error. Combining intermetallic compound (IMC) growth theory and the FA technology for the magnetic head in actual production, this thesis puts forward a new growth model to predict life expectancy for solder joint of the magnetic head. And the impact of IMC, generating from interface reaction between slider (magnetic head, usually be called slider) and bonding pad, on mechanical performance during aging process is analyzed in it. By further researching on FA of solder ball bonding, thesis chooses AuSn4 growth model that affects least to solder joint mechanical property to indicate that the IMC methodology is suitable to forecast the solder lifetime. And the diffusion constant under work condition 60 °C is 0.015354; the solder lifetime t is 14.46 years.

Fracture mechanisms and fracture control in composite structures

NASA Astrophysics Data System (ADS)

Kim, Wone-Chul

Four basic failure modes--delamination, delamination buckling of composite sandwich panels, first-ply failure in cross-ply laminates, and compression failure--are analyzed using linear elastic fracture mechanics (LEFM) and the J-integral method. Structural failures, including those at the micromechanical level, are investigated with the aid of the models developed, and the critical strains for crack propagation for each mode are obtained. In the structural fracture analyses area, the fracture control schemes for delamination in a composite rib stiffener and delamination buckling in composite sandwich panels subjected to in-plane compression are determined. The critical fracture strains were predicted with the aid of LEFM for delamination and the J-integral method for delamination buckling. The use of toughened matrix systems has been recommended for improved damage tolerant design for delamination crack propagation. An experimental study was conducted to determine the onset of delamination buckling in composite sandwich panel containing flaws. The critical fracture loads computed using the proposed theoretical model and a numerical computational scheme closely followed the experimental measurements made on sandwich panel specimens of graphite/epoxy faceskins and aluminum honeycomb core with varying faceskin thicknesses and core sizes. Micromechanical models of fracture in composites are explored to predict transverse cracking of cross-ply laminates and compression fracture of unidirectional composites. A modified shear lag model which takes into account the important role of interlaminar shear zones between the 0 degree and 90 degree piles in cross-ply laminate is proposed and criteria for transverse cracking have been developed. For compressive failure of unidirectional composites, pre-existing defects play an important role. Using anisotropic elasticity, the stress state around a defect under a remotely applied compressive load is obtained. The experimentally observed complex compressive failure modes, such as shear crippling and pure compressive fiber failure of fibers are explained by the predicted stress distributions calculated in this work. These fracture analyses can be damage tolerant design methodology for composite structures. The proposed fracture criteria and the corresponding critical fracture strains provide the designer with quantitative guidelines for safe-life design. These have been incorporated into a fracture control plan for composite structures, which is also described. Currently, fracture control plans do not exist for composite structures; the proposed plan is a first step towards establishing fracture control and damage tolerant design methodology for this important class of materials.

Modeling the attenuation and failure of action potentials in the dendrites of hippocampal neurons.

PubMed Central

Migliore, M

1996-01-01

We modeled two different mechanisms, a shunting conductance and a slow sodium inactivation, to test whether they could modulate the active propagation of a train of action potentials in a dendritic tree. Computer simulations, using a compartmental model of a pyramidal neuron, suggest that each of these two mechanisms could account for the activity-dependent attenuation and failure of the action potentials in the dendrites during the train. Each mechanism is shown to be in good qualitative agreement with experimental findings on somatic or dendritic stimulation and on the effects of hyperpolarization. The conditions under which branch point failures can be observed, and a few experimentally testable predictions, are presented and discussed. PMID:8913580

Cigarette smoking in a student sample: neurocognitive and clinical correlates.

PubMed

Dinn, Wayne M; Aycicegi, Ayse; Harris, Catherine L

2004-01-01

Why do adolescents begin to smoke in the face of profound health risks and aggressive antismoking campaigns? The present study tested predictions based on two theoretical models of tobacco use in young adults: (1) the self-medication model; and (2) the orbitofrontal/disinhibition model. Investigators speculated that a significant number of smokers were self-medicating since nicotine possesses mood-elevating and hedonic properties. The self-medication model predicts that smokers will demonstrate increased rates of psychopathology relative to nonsmokers. Similarly, researchers have suggested that individuals with attention-deficit/hyperactivity disorder (ADHD) employ nicotine to enhance cognitive function. The ADHD/self-medication model predicts that smokers will perform poorly on tests of executive function and report a greater number of ADHD symptoms. A considerable body of research indicates that tobacco use is associated with several related personality traits including extraversion, impulsivity, risk taking, sensation seeking, novelty seeking, and antisocial personality features. Antisocial behavior and related personality traits as well as tobacco use may reflect, in part, a failure to effectively employ reward and punishment cues to guide behavior. This failure may reflect orbitofrontal dysfunction. The orbitofrontal/disinhibition model predicts that smokers will perform poorly on neurocognitive tasks considered sensitive to orbitofrontal dysfunction and will obtain significantly higher scores on measures of behavioral disinhibition and antisocial personality relative to nonsmokers. To test these predictions, we administered a battery of neuropsychological tests, clinical scales, and personality questionnaires to university student smokers and nonsmokers. Results did not support the self-medication model or the ADHD/self-medication model; however, findings were consistent with the orbitofrontal/disinhibition model.

Analysis and Test Correlation of Proof of Concept Box for Blended Wing Body-Low Speed Vehicle

NASA Technical Reports Server (NTRS)

Spellman, Regina L.

2003-01-01

The Low Speed Vehicle (LSV) is a 14.2% scale remotely piloted vehicle of the revolutionary Blended Wing Body concept. The design of the LSV includes an all composite airframe. Due to internal manufacturing capability restrictions, room temperature layups were necessary. An extensive materials testing and manufacturing process development effort was underwent to establish a process that would achieve the high modulus/low weight properties required to meet the design requirements. The analysis process involved a loads development effort that incorporated aero loads to determine internal forces that could be applied to a traditional FEM of the vehicle and to conduct detailed component analyses. A new tool, Hypersizer, was added to the design process to address various composite failure modes and to optimize the skin panel thickness of the upper and lower skins for the vehicle. The analysis required an iterative approach as material properties were continually changing. As a part of the material characterization effort, test articles, including a proof of concept wing box and a full-scale wing, were fabricated. The proof of concept box was fabricated based on very preliminary material studies and tested in bending, torsion, and shear. The box was then tested to failure under shear. The proof of concept box was also analyzed using Nastran and Hypersizer. The results of both analyses were scaled to determine the predicted failure load. The test results were compared to both the Nastran and Hypersizer analytical predictions. The actual failure occurred at 899 lbs. The failure was predicted at 1167 lbs based on the Nastran analysis. The Hypersizer analysis predicted a lower failure load of 960 lbs. The Nastran analysis alone was not sufficient to predict the failure load because it does not identify local composite failure modes. This analysis has traditionally been done using closed form solutions. Although Hypersizer is typically used as an optimizer for the design process, the failure prediction was used to help gain acceptance and confidence in this new tool. The correlated models and process were to be used to analyze the full BWB-LSV airframe design. The analysis and correlation with test results of the proof of concept box is presented here, including the comparison of the Nastran and Hypersizer results.

Simulating Fatigue Crack Growth in Spiral Bevel Pinion

NASA Technical Reports Server (NTRS)

Ural, Ani; Wawrzynek, Paul A.; Ingraffe, Anthony R.

2003-01-01

This project investigates computational modeling of fatigue crack growth in spiral bevel gears. Current work is a continuation of the previous efforts made to use the Boundary Element Method (BEM) to simulate tooth-bending fatigue failure in spiral bevel gears. This report summarizes new results predicting crack trajectory and fatigue life for a spiral bevel pinion using the Finite Element Method (FEM). Predicting crack trajectories is important in determining the failure mode of a gear. Cracks propagating through the rim may result in catastrophic failure, whereas the gear may remain intact if one tooth fails and this may allow for early detection of failure. Being able to predict crack trajectories is insightful for the designer. However, predicting growth of three-dimensional arbitrary cracks is complicated due to the difficulty of creating three-dimensional models, the computing power required, and absence of closed- form solutions of the problem. Another focus of this project was performing three-dimensional contact analysis of a spiral bevel gear set incorporating cracks. These analyses were significant in determining the influence of change of tooth flexibility due to crack growth on the magnitude and location of contact loads. This is an important concern since change in contact loads might lead to differences in SIFs and therefore result in alteration of the crack trajectory. Contact analyses performed in this report showed the expected trend of decreasing tooth loads carried by the cracked tooth with increasing crack length. Decrease in tooth loads lead to differences between SIFs extracted from finite element contact analysis and finite element analysis with Hertz contact loads. This effect became more pronounced as the crack grew.

Testing the prospective evaluation of a new healthcare system

PubMed Central

Planitz, Birgit; Sanderson, Penelope; Freeman, Clinton; Xiao, Tania; Botea, Adi; Orihuela, Cristina Beltran

2012-01-01

Research into health ICT adoption suggests that the failure to understand the clinical workplace has been a major contributing factor to the failure of many computer-based clinical systems. We suggest that clinicians and administrators need methods for envisioning future use when adopting new ICT. This paper presents and evaluates a six-stage “prospective evaluation” model that clinicians can use when assessing the impact of a new electronic patient information system on a Specialist Outpatients Department (SOPD). The prospective evaluation model encompasses normative, descriptive, formative and projective approaches. We show that this combination helped health informaticians to make reasonably accurate predictions for technology adoption at the SOPD. We suggest some refinements, however, to improve the scope and accuracy of predictions. PMID:23304347

Predicting seasonal diet in the yellow-bellied marmot: success and failure for the linear programming model.

PubMed

Edwards, G P

1997-10-01

Seasonal diet selection in the yellow-bellied marmot (Marmota flaviventris) was studied at two sites in Montana during 1991 and 1992. A linear programming model of optimal diet selection successfully predicted the composition of observed diets (monocot versus dicot) in eight out of ten cases early in the active season (April-June). During this period, adult, yearling and juvenile marmots selected diets consistent with the predicted goal of energy maximisation. However, late in the active season (July-August), the model predicted the diet composition in only one out of six cases. In all six late-season determinations, the model underestimated the amount of monocot in the diet. Possible reasons why the model failed to reliably predict diet composition late in the active season are discussed.

Solid-state lighting life prediction using extended Kalman filter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lall, Pradeep; Wei, Junchao; Davis, Lynn

2013-07-16

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. The U.S. Department of Energy has made a long term commitment to advance the efficiency, understandingmore » and development of solid-state lighting (SSL) and is making a strong push for the acceptance and use of SSL products to reduce overall energy consumption attributable to lighting. 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 SSL Luminaires from LM-80 test data. The TM-21 model uses an Arrhenius Equation with an Activation Energy, Pre-decay factor and Decay Rates. Several failure mechanisms may be active in a luminaire at a single time causing lumen depreciation. The underlying TM-21 Arrhenius 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, a Kalman Filter and Extended Kalman Filters have been used to develop a 70% Lumen Maintenance Life Prediction Model for a LEDs used in SSL luminaires. This model can be used to calculate acceleration factors, evaluate failure-probability and identify ALT methodologies for reducing test time. Ten-thousand hour LM-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.« less

Fully Coupled Micro/Macro Deformation, Damage, and Failure Prediction for SiC/Ti-15-3 Laminates

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.; Lerch, Brad A.

2001-01-01

The deformation, failure, and low cycle fatigue life of SCS-6/Ti-15-3 composites are predicted using a coupled deformation and damage approach in the context of the analytical generalized method of cells (GMC) micromechanics model. The local effects of inelastic deformation, fiber breakage, fiber-matrix interfacial debonding, and fatigue damage are included as sub-models that operate on the micro scale for the individual composite phases. For the laminate analysis, lamination theory is employed as the global or structural scale model, while GMC is embedded to operate on the meso scale to simulate the behavior of the composite material within each laminate layer. While the analysis approach is quite complex and multifaceted, it is shown, through comparison with experimental data, to be quite accurate and realistic while remaining extremely efficient.

A Compatible Hardware/Software Reliability Prediction Model.

DTIC Science & Technology

1981-07-22

machines. In particular, he was interested in the following problem: assu me that one has a collection of connected elements computing and transmitting...software reliability prediction model is desirable, the findings about the Weibull distribution are intriguing. After collecting failure data from several...capacitor, some of the added charge carriers are collected by the capacitor. If the added charge is sufficiently large, the information stored is changed

Development of High Level Electrical Stress Failure Threshold and Prediction Model for Small Scale Junction Integrated Circuits

DTIC Science & Technology

1978-09-01

AWACS EMP Guidelines presents two different models to predict the damage pcwer of the dev-ce and the circuit damage EMP voltage ( VEMP ). Neither of...calculated as K P~ I V BD 6. The damage EMP voltage ( VEMP ) is calculated KZ EMP +IZ =D +BD VBD1F 7. The damage EMP voltage is calculated for collector

Anchorage strength models for end-debonding predictions in RC beams strengthened with FRP composites

NASA Astrophysics Data System (ADS)

Nardini, V.; Guadagnini, M.; Valluzzi, M. R.

2008-05-01

The increase in the flexural capacity of RC beams obtained by externally bonding FRP composites to their tension side is often limited by the premature and brittle debonding of the external reinforcement. An in-depth understanding of this complex failure mechanism, however, has not yet been achieved. With specific regard to end-debonding failure modes, extensive experimental observations reported in the literature highlight the important distinction, often neglected in strength models proposed by researchers, between the peel-off and rip-off end-debonding types of failure. The peel-off failure is generally characterized by a failure plane located within the first few millimetres of the concrete cover, whilst the rip-off failure penetrates deeper into the concrete cover and propagates along the tensile steel reinforcement. A new rip-off strength model is described in this paper. The model proposed is based on the Chen and Teng peel-off model and relies upon additional theoretical considerations. The influence of the amount of the internal tensile steel reinforcement and the effective anchorage length of FRP are considered and discussed. The validity of the new model is analyzed further through comparisons with test results, findings of a numerical investigation, and a parametric study. The new rip-off strength model is assessed against a database comprising results from 62 beams tested by various researchers and is shown to yield less conservative results.

Continuous fiber ceramic matrix composites for heat engine components

NASA Technical Reports Server (NTRS)

Tripp, David E.

1988-01-01

High strength at elevated temperatures, low density, resistance to wear, and abundance of nonstrategic raw materials make structural ceramics attractive for advanced heat engine applications. Unfortunately, ceramics have a low fracture toughness and fail catastrophically because of overload, impact, and contact stresses. Ceramic matrix composites provide the means to achieve improved fracture toughness while retaining desirable characteristics, such as high strength and low density. Materials scientists and engineers are trying to develop the ideal fibers and matrices to achieve the optimum ceramic matrix composite properties. A need exists for the development of failure models for the design of ceramic matrix composite heat engine components. Phenomenological failure models are currently the most frequently used in industry, but they are deterministic and do not adequately describe ceramic matrix composite behavior. Semi-empirical models were proposed, which relate the failure of notched composite laminates to the stress a characteristic distance away from the notch. Shear lag models describe composite failure modes at the micromechanics level. The enhanced matrix cracking stress occurs at the same applied stress level predicted by the two models of steady state cracking. Finally, statistical models take into consideration the distribution in composite failure strength. The intent is to develop these models into computer algorithms for the failure analysis of ceramic matrix composites under monotonically increasing loads. The algorithms will be included in a postprocessor to general purpose finite element programs.

Pile group program for full material modeling and progressive failure.

DOT National Transportation Integrated Search

2008-12-01

Strain wedge (SW) model formulation has been used, in previous work, to evaluate the response of a single pile or a group of piles (including its : pile cap) in layered soils to lateral loading. The SW model approach provides appropriate prediction f...

Software reliability models for fault-tolerant avionics computers and related topics

NASA Technical Reports Server (NTRS)

Miller, Douglas R.

1987-01-01

Software reliability research is briefly described. General research topics are reliability growth models, quality of software reliability prediction, the complete monotonicity property of reliability growth, conceptual modelling of software failure behavior, assurance of ultrahigh reliability, and analysis techniques for fault-tolerant systems.

Multi-Scale Impact and Compression-After-Impact Modeling of Reinforced Benzoxazine/Epoxy Composites using Micromechanics Approach

NASA Astrophysics Data System (ADS)

Montero, Marc Villa; Barjasteh, Ehsan; Baid, Harsh K.; Godines, Cody; Abdi, Frank; Nikbin, Kamran

A multi-scale micromechanics approach along with finite element (FE) model predictive tool is developed to analyze low-energy-impact damage footprint and compression-after-impact (CAI) of composite laminates which is also tested and verified with experimental data. Effective fiber and matrix properties were reverse-engineered from lamina properties using an optimization algorithm and used to assess damage at the micro-level during impact and post-impact FE simulations. Progressive failure dynamic analysis (PFDA) was performed for a two step-process simulation. Damage mechanisms at the micro-level were continuously evaluated during the analyses. Contribution of each failure mode was tracked during the simulations and damage and delamination footprint size and shape were predicted to understand when, where and why failure occurred during both impact and CAI events. The composite laminate was manufactured by the vacuum infusion of the aero-grade toughened Benzoxazine system into the fabric preform. Delamination footprint was measured using C-scan data from the impacted panels and compared with the predicated values obtained from proposed multi-scale micromechanics coupled with FE analysis. Furthermore, the residual strength was predicted from the load-displacement curve and compared with the experimental values as well.

Launch Vehicle Debris Models and Crew Vehicle Ascent Abort Risk

NASA Technical Reports Server (NTRS)

Gee, Ken; Lawrence, Scott

2013-01-01

For manned space launch systems, a reliable abort system is required to reduce the risks associated with a launch vehicle failure during ascent. Understanding the risks associated with failure environments can be achieved through the use of physics-based models of these environments. Debris fields due to destruction of the launch vehicle is one such environment. To better analyze the risk posed by debris, a physics-based model for generating launch vehicle debris catalogs has been developed. The model predicts the mass distribution of the debris field based on formulae developed from analysis of explosions. Imparted velocity distributions are computed using a shock-physics code to model the explosions within the launch vehicle. A comparison of the debris catalog with an existing catalog for the Shuttle external tank show good comparison in the debris characteristics and the predicted debris strike probability. The model is used to analyze the effects of number of debris pieces and velocity distributions on the strike probability and risk.

Characterization of acute-on-chronic liver failure and prediction of mortality in Asian patients with active alcoholism.

PubMed

Kim, Hwi Young; Chang, Young; Park, Jae Yong; Ahn, Hongkeun; Cho, Hyeki; Han, Seung Jun; Oh, Sohee; Kim, Donghee; Jung, Yong Jin; Kim, Byeong Gwan; Lee, Kook Lae; Kim, Won

2016-02-01

Alcoholic liver diseases often evolve to acute-on-chronic liver failure (ACLF), which increases the risk of (multi-)organ failure and death. We investigated the development and characteristics of alcohol-related ACLF and evaluated prognostic scores for prediction of mortality in Asian patients with active alcoholism. A total of 205 patients who were hospitalized with severe alcoholic liver disease were included in this retrospective cohort study, after excluding those with serious cardiovascular diseases, malignancy, or co-existing viral hepatitis. The Chronic Liver Failure (CLIF) Consortium Organ Failure score was used in the diagnosis and grading of ACLF, and the CLIF Consortium ACLF score (CLIF-C ACLFs) was used to predict mortality. Patients with ACLF had higher Maddrey discriminant function, model for end-stage liver disease (MELD), and MELD-sodium scores than those without ACLF. Infections were more frequently documented in patients with ACLF (33.3% vs 53.0%; P = 0.004). Predictive factors for ACLF development were systemic inflammatory response syndrome (odds ratio [OR], 2.239; P < 0.001), serum sodium level (OR, 0.939; P = 0.029), and neutrophil count (OR, 1.000; P = 0.021). For prediction of mortality at predefined time points (28-day and 90-day) in patients with ACLF, areas under the receiver-operating characteristic were significantly greater for the CLIF-C ACLFs than for Child-Pugh, MELD, and MELD-sodium scores. Infection and systemic inflammatory response syndrome play an important role in the development of alcohol-related ACLF in Asian patients with active alcoholism. The CLIF-C ACLFs may be more useful for predicting mortality in ACLF cases than liver-specific scoring systems. © 2015 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Can baseline ultrasound results help to predict failure to achieve DAS28 remission after 1 year of tight control treatment in early RA patients?

PubMed

Ten Cate, D F; Jacobs, J W G; Swen, W A A; Hazes, J M W; de Jager, M H; Basoski, N M; Haagsma, C J; Luime, J J; Gerards, A H

2018-01-30

At present, there are no prognostic parameters unequivocally predicting treatment failure in early rheumatoid arthritis (RA) patients. We investigated whether baseline ultrasonography (US) findings of joints, when added to baseline clinical, laboratory, and radiographical data, could improve prediction of failure to achieve Disease Activity Score assessing 28 joints (DAS28) remission (<2.6) at 1 year in newly diagnosed RA patients. A multicentre cohort of newly diagnosed RA patients was followed prospectively for 1 year. US of the hands, wrists, and feet was performed at baseline. Clinical, laboratory, and radiographical parameters were recorded. Primary analysis was the prediction by logistic regression of the absence of DAS28 remission 12 months after diagnosis and start of therapy. Of 194 patients included, 174 were used for the analysis, with complete data available for 159. In a multivariate model with baseline DAS28 (odds ratio (OR) 1.6, 95% confidence interval (CI) 1.2-2.2), the presence of rheumatoid factor (OR 2.3, 95% CI 1.1-5.1), and type of monitoring strategy (OR 0.2, 95% CI 0.05-0.85), the addition of baseline US results for joints (OR 0.96, 95% CI 0.89-1.04) did not significantly improve the prediction of failure to achieve DAS28 remission (likelihood ratio test, 1.04; p = 0.31). In an early RA population, adding baseline ultrasonography of the hands, wrists, and feet to commonly available baseline characteristics did not improve prediction of failure to achieve DAS28 remission at 12 months. Clinicaltrials.gov, NCT01752309 . Registered on 19 December 2012.

A Monte Carlo Risk Analysis of Life Cycle Cost Prediction.

DTIC Science & Technology

1975-09-01

process which occurs with each FLU failure. With this in mind there is no alternative other than the binomial distribution. 24 GOR/SM/75D-6 With all of...Weibull distribution of failures as selected by user. For each failure of the ith FLU, the model then samples from the binomial distribution to deter- mine...which is sampled from the binomial . Neither of the two conditions for normality are met, i.e., that RTS Ie close to .5 and the number of samples close

A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

NASA Technical Reports Server (NTRS)

Freed, Michael; Remington, Roger; Null, Cynthia H. (Technical Monitor)

1998-01-01

We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

Prediction failure of a wolf landscape model

USGS Publications Warehouse

Mech, L.D.

2006-01-01

I compared 101 wolf (Canis lupus) pack territories formed in Wisconsin during 1993-2004 to the logistic regression predictive model of Mladenoff et al. (1995, 1997, 1999). Of these, 60% were located in putative habitat suitabilities 50% remained unoccupied by known packs after 24 years of recolonization. This model was a poor predictor of wolf re-colonizing locations in Wisconsin, apparently because it failed to consider the adaptability of wolves. Such models should be used cautiously in wolf-management or restoration plans.

Accelerated Aging System for Prognostics of Power Semiconductor Devices

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Vashchenko, Vladislav; Wysocki, Philip; Saha, Sankalita

2010-01-01

Prognostics is an engineering discipline that focuses on estimation of the health state of a component and the prediction of its remaining useful life (RUL) before failure. Health state estimation is based on actual conditions and it is fundamental for the prediction of RUL under anticipated future usage. Failure of electronic devices is of great concern as future aircraft will see an increase of electronics to drive and control safety-critical equipment throughout the aircraft. Therefore, development of prognostics solutions for electronics is of key importance. This paper presents an accelerated aging system for gate-controlled power transistors. This system allows for the understanding of the effects of failure mechanisms, and the identification of leading indicators of failure which are essential in the development of physics-based degradation models and RUL prediction. In particular, this system isolates electrical overstress from thermal overstress. Also, this system allows for a precise control of internal temperatures, enabling the exploration of intrinsic failure mechanisms not related to the device packaging. By controlling the temperature within safe operation levels of the device, accelerated aging is induced by electrical overstress only, avoiding the generation of thermal cycles. The temperature is controlled by active thermal-electric units. Several electrical and thermal signals are measured in-situ and recorded for further analysis in the identification of leading indicators of failures. This system, therefore, provides a unique capability in the exploration of different failure mechanisms and the identification of precursors of failure that can be used to provide a health management solution for electronic devices.

SU-E-T-630: Predictive Modeling of Mortality, Tumor Control, and Normal Tissue Complications After Stereotactic Body Radiotherapy for Stage I Non-Small Cell Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindsay, WD; Oncora Medical, LLC, Philadelphia, PA; Berlind, CG

Purpose: While rates of local control have been well characterized after stereotactic body radiotherapy (SBRT) for stage I non-small cell lung cancer (NSCLC), less data are available characterizing survival and normal tissue toxicities, and no validated models exist assessing these parameters after SBRT. We evaluate the reliability of various machine learning techniques when applied to radiation oncology datasets to create predictive models of mortality, tumor control, and normal tissue complications. Methods: A dataset of 204 consecutive patients with stage I non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT) at the University of Pennsylvania between 2009 and 2013more » was used to create predictive models of tumor control, normal tissue complications, and mortality in this IRB-approved study. Nearly 200 data fields of detailed patient- and tumor-specific information, radiotherapy dosimetric measurements, and clinical outcomes data were collected. Predictive models were created for local tumor control, 1- and 3-year overall survival, and nodal failure using 60% of the data (leaving the remainder as a test set). After applying feature selection and dimensionality reduction, nonlinear support vector classification was applied to the resulting features. Models were evaluated for accuracy and area under ROC curve on the 81-patient test set. Results: Models for common events in the dataset (such as mortality at one year) had the highest predictive power (AUC = .67, p < 0.05). For rare occurrences such as radiation pneumonitis and local failure (each occurring in less than 10% of patients), too few events were present to create reliable models. Conclusion: Although this study demonstrates the validity of predictive analytics using information extracted from patient medical records and can most reliably predict for survival after SBRT, larger sample sizes are needed to develop predictive models for normal tissue toxicities and more advanced machine learning methodologies need be consider in the future.« less

Validation of prediction models: examining temporal and geographic stability of baseline risk and estimated covariate effects

PubMed Central

Austin, Peter C.; van Klaveren, David; Vergouwe, Yvonne; Nieboer, Daan; Lee, Douglas S.; Steyerberg, Ewout W.

2018-01-01

Background Stability in baseline risk and estimated predictor effects both geographically and temporally is a desirable property of clinical prediction models. However, this issue has received little attention in the methodological literature. Our objective was to examine methods for assessing temporal and geographic heterogeneity in baseline risk and predictor effects in prediction models. Methods We studied 14,857 patients hospitalized with heart failure at 90 hospitals in Ontario, Canada, in two time periods. We focussed on geographic and temporal variation in baseline risk (intercept) and predictor effects (regression coefficients) of the EFFECT-HF mortality model for predicting 1-year mortality in patients hospitalized for heart failure. We used random effects logistic regression models for the 14,857 patients. Results The baseline risk of mortality displayed moderate geographic variation, with the hospital-specific probability of 1-year mortality for a reference patient lying between 0.168 and 0.290 for 95% of hospitals. Furthermore, the odds of death were 11% lower in the second period than in the first period. However, we found minimal geographic or temporal variation in predictor effects. Among 11 tests of differences in time for predictor variables, only one had a modestly significant P value (0.03). Conclusions This study illustrates how temporal and geographic heterogeneity of prediction models can be assessed in settings with a large sample of patients from a large number of centers at different time periods. PMID:29350215

Dynamically induced cascading failures in power grids.

PubMed

Schäfer, Benjamin; Witthaut, Dirk; Timme, Marc; Latora, Vito

2018-05-17

Reliable functioning of infrastructure networks is essential for our modern society. Cascading failures are the cause of most large-scale network outages. Although cascading failures often exhibit dynamical transients, the modeling of cascades has so far mainly focused on the analysis of sequences of steady states. In this article, we focus on electrical transmission networks and introduce a framework that takes into account both the event-based nature of cascades and the essentials of the network dynamics. We find that transients of the order of seconds in the flows of a power grid play a crucial role in the emergence of collective behaviors. We finally propose a forecasting method to identify critical lines and components in advance or during operation. Overall, our work highlights the relevance of dynamically induced failures on the synchronization dynamics of national power grids of different European countries and provides methods to predict and model cascading failures.

New Approach For Prediction Groundwater Depletion

NASA Astrophysics Data System (ADS)

Moustafa, Mahmoud

2017-01-01

Current approaches to quantify groundwater depletion involve water balance and satellite gravity. However, the water balance technique includes uncertain estimation of parameters such as evapotranspiration and runoff. The satellite method consumes time and effort. The work reported in this paper proposes using failure theory in a novel way to predict groundwater saturated thickness depletion. An important issue in the failure theory proposed is to determine the failure point (depletion case). The proposed technique uses depth of water as the net result of recharge/discharge processes in the aquifer to calculate remaining saturated thickness resulting from the applied pumping rates in an area to evaluate the groundwater depletion. Two parameters, the Weibull function and Bayes analysis were used to model and analyze collected data from 1962 to 2009. The proposed methodology was tested in a nonrenewable aquifer, with no recharge. Consequently, the continuous decline in water depth has been the main criterion used to estimate the depletion. The value of the proposed approach is to predict the probable effect of the current applied pumping rates on the saturated thickness based on the remaining saturated thickness data. The limitation of the suggested approach is that it assumes the applied management practices are constant during the prediction period. The study predicted that after 300 years there would be an 80% probability of the saturated aquifer which would be expected to be depleted. Lifetime or failure theory can give a simple alternative way to predict the remaining saturated thickness depletion with no time-consuming processes such as the sophisticated software required.

Bipolar Transistor and Diode Failure to Electrical Transients-Predictive Failure Modeling versus Experimental Damage Testing. 1 Junction Capacitance Damage Model

DTIC Science & Technology

1981-06-01

into the Wunsch-Bell equation) are P = A R , 1t-0 5 1.2 PD) = A26B2t-.5 (3) JAJ where A,*, A, B1, and B2 are experimentally determined constants and TJ...ATTN CODE 7240, S. N. LICHT’NAN PATRICK AID, FL 32J25 DIV COIMAND SAN DIEGO, CA 92152 ATTN D]PN-ATC AF WEAPONS LABORATORY, AFSC ATTN DRCFN- TDS -DSI

Local-global analysis of crack growth in continuously reinfoced ceramic matrix composites

NASA Technical Reports Server (NTRS)

Ballarini, Roberto; Ahmed, Shamim

1989-01-01

This paper describes the development of a mathematical model for predicting the strength and micromechanical failure characteristics of continuously reinforced ceramic matrix composites. The local-global analysis models the vicinity of a propagating crack tip as a local heterogeneous region (LHR) consisting of spring-like representation of the matrix, fibers and interfaces. Parametric studies are conducted to investigate the effects of LHR size, component properties, and interface conditions on the strength and sequence of the failure processes in the unidirectional composite system.

Discharge clinical characteristics and 60-day readmission in patients hospitalized with heart failure.

PubMed

Anderson, Kelley M

2014-01-01

Heart failure is a clinical syndrome that incurs a high prevalence, mortality, morbidity, and economic burden in our society. Patients with heart failure may experience hospitalization because of an acute exacerbation of their condition. Recurrent hospitalizations soon after discharge are an unfortunate occurrence in this patient population. The purpose of this study was to explore the clinical and diagnostic characteristics of individuals hospitalized with a primary diagnosis of heart failure at the time of discharge and to compare the association of these indicators in individuals who did and did not experience a heart failure hospitalization within 60 days of the index stay. The study is a descriptive, correlational, quantitative study using a retrospective review of 134 individuals discharged with a primary diagnosis of heart failure. Records were reviewed for sociodemographic characteristics, health histories, clinical assessment findings, and diagnostic information. Significant predictors of 60-day heart failure readmissions were dyspnea (β = 0.579), crackles (β = 1.688), and assistance with activities of daily living (β = 2.328), independent of age, gender, and multiple other factors. By using hierarchical logistical regression, a model was derived that demonstrated the ability to correctly classify 77.4% of the cohort, 78.2% of those who did have a readmission (sensitivity of the prediction), and 76.7% of the subjects in whom the predicted event, readmission, did not occur (specificity of the prediction). Hospitalizations for heart failure are markers of clinical instability. Future events after hospitalization are common in this patient population, and this study provides a novel understanding of clinical characteristics at the time of discharge that are associated with future outcomes, specifically 60-day heart failure readmissions. A consideration of these characteristics provides an additional perspective to guide clinical decision making and the evaluation of discharge readiness.

Prediction of Size Effects in Notched Laminates Using Continuum Damage Mechanics

NASA Technical Reports Server (NTRS)

Camanho, D. P.; Maimi, P.; Davila, C. G.

2007-01-01

This paper examines the use of a continuum damage model to predict strength and size effects in notched carbon-epoxy laminates. The effects of size and the development of a fracture process zone before final failure are identified in an experimental program. The continuum damage model is described and the resulting predictions of size effects are compared with alternative approaches: the point stress and the inherent flaw models, the Linear-Elastic Fracture Mechanics approach, and the strength of materials approach. The results indicate that the continuum damage model is the most accurate technique to predict size effects in composites. Furthermore, the continuum damage model does not require any calibration and it is applicable to general geometries and boundary conditions.

Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

PubMed

Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

2015-07-01

Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

Probabilistic Design Analysis (PDA) Approach to Determine the Probability of Cross-System Failures for a Space Launch Vehicle

NASA Technical Reports Server (NTRS)

Shih, Ann T.; Lo, Yunnhon; Ward, Natalie C.

2010-01-01

Quantifying the probability of significant launch vehicle failure scenarios for a given design, while still in the design process, is critical to mission success and to the safety of the astronauts. Probabilistic risk assessment (PRA) is chosen from many system safety and reliability tools to verify the loss of mission (LOM) and loss of crew (LOC) requirements set by the NASA Program Office. To support the integrated vehicle PRA, probabilistic design analysis (PDA) models are developed by using vehicle design and operation data to better quantify failure probabilities and to better understand the characteristics of a failure and its outcome. This PDA approach uses a physics-based model to describe the system behavior and response for a given failure scenario. Each driving parameter in the model is treated as a random variable with a distribution function. Monte Carlo simulation is used to perform probabilistic calculations to statistically obtain the failure probability. Sensitivity analyses are performed to show how input parameters affect the predicted failure probability, providing insight for potential design improvements to mitigate the risk. The paper discusses the application of the PDA approach in determining the probability of failure for two scenarios from the NASA Ares I project

A computer model of the pediatric circulatory system for testing pediatric assist devices.

PubMed

Giridharan, Guruprasad A; Koenig, Steven C; Mitchell, Michael; Gartner, Mark; Pantalos, George M

2007-01-01

Lumped parameter computer models of the pediatric circulatory systems for 1- and 4-year-olds were developed to predict hemodynamic responses to mechanical circulatory support devices. Model parameters, including resistance, compliance and volume, were adjusted to match hemodynamic pressure and flow waveforms, pressure-volume loops, percent systole, and heart rate of pediatric patients (n = 6) with normal ventricles. Left ventricular failure was modeled by adjusting the time-varying compliance curve of the left heart to produce aortic pressures and cardiac outputs consistent with those observed clinically. Models of pediatric continuous flow (CF) and pulsatile flow (PF) ventricular assist devices (VAD) and intraaortic balloon pump (IABP) were developed and integrated into the heart failure pediatric circulatory system models. Computer simulations were conducted to predict acute hemodynamic responses to PF and CF VAD operating at 50%, 75% and 100% support and 2.5 and 5 ml IABP operating at 1:1 and 1:2 support modes. The computer model of the pediatric circulation matched the human pediatric hemodynamic waveform morphology to within 90% and cardiac function parameters with 95% accuracy. The computer model predicted PF VAD and IABP restore aortic pressure pulsatility and variation in end-systolic and end-diastolic volume, but diminish with increasing CF VAD support.

The Impact of Worsening Heart Failure in the United States

PubMed Central

Cooper, Lauren B.; DeVore, Adam D.; Felker, G. Michael

2015-01-01

Synopsis In-hospital worsening heart failure represents a clinical scenario in which a patient hospitalized for treatment of acute heart failure experiences a worsening of their condition while in the hospital, requiring escalation of therapy. In-hospital worsening heart failure is associated with worse in-hospital and post-discharge outcomes. In-hospital worsening heart failure is increasingly being used as an endpoint, or as part of a combined endpoint, in many clinical trials in acute heart failure. This endpoint has advantages over other endpoints commonly used in acute and chronic heart failure trials, such as dyspnea relief and mortality or rehospitalization. Despite the extensive study of this condition, no treatment strategies have been approved for the prevention of this condition. However, several prediction models have been developed to identify worsening heart failure. Continued study in this area is warranted. PMID:26462100

26th International Symposium on Ballistics

DTIC Science & Technology

2011-09-16

judicious use of analytical predictions correlated with ballistic testing and post - test failure morphology investigations. •Our approach...ballistic predictions. The numerical predictions correlate well with the damage pattern. Post - Test Morphology Simulation Imbedded Steel Plate Removed Post ... Test •Numerical simulation of damage to embedded steel plate compares well with the post - test plate morphology •Multi-strike modeling in work

Analyzing Log Files to Predict Students' Problem Solving Performance in a Computer-Based Physics Tutor

ERIC Educational Resources Information Center

Lee, Young-Jin

2015-01-01

This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…

Reevaluating the two-representation model of numerical magnitude processing.

PubMed

Jiang, Ting; Zhang, Wenfeng; Wen, Wen; Zhu, Haiting; Du, Han; Zhu, Xiangru; Gao, Xuefei; Zhang, Hongchuan; Dong, Qi; Chen, Chuansheng

2016-01-01

One debate in mathematical cognition centers on the single-representation model versus the two-representation model. Using an improved number Stroop paradigm (i.e., systematically manipulating physical size distance), in the present study we tested the predictions of the two models for number magnitude processing. The results supported the single-representation model and, more importantly, explained how a design problem (failure to manipulate physical size distance) and an analytical problem (failure to consider the interaction between congruity and task-irrelevant numerical distance) might have contributed to the evidence used to support the two-representation model. This study, therefore, can help settle the debate between the single-representation and two-representation models.

Forecasting volcanic eruptions and other material failure phenomena: An evaluation of the failure forecast method

NASA Astrophysics Data System (ADS)

Bell, Andrew F.; Naylor, Mark; Heap, Michael J.; Main, Ian G.

2011-08-01

Power-law accelerations in the mean rate of strain, earthquakes and other precursors have been widely reported prior to material failure phenomena, including volcanic eruptions, landslides and laboratory deformation experiments, as predicted by several theoretical models. The Failure Forecast Method (FFM), which linearizes the power-law trend, has been routinely used to forecast the failure time in retrospective analyses; however, its performance has never been formally evaluated. Here we use synthetic and real data, recorded in laboratory brittle creep experiments and at volcanoes, to show that the assumptions of the FFM are inconsistent with the error structure of the data, leading to biased and imprecise forecasts. We show that a Generalized Linear Model method provides higher-quality forecasts that converge more accurately to the eventual failure time, accounting for the appropriate error distributions. This approach should be employed in place of the FFM to provide reliable quantitative forecasts and estimate their associated uncertainties.

Measurement-based reliability prediction methodology. M.S. Thesis

NASA Technical Reports Server (NTRS)

Linn, Linda Shen

1991-01-01

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Simple Elasticity Modeling and Failure Prediction for Composite Flexbeams

NASA Technical Reports Server (NTRS)

Makeev, Andrew; Armanios, Erian; OBrien, T. Kevin (Technical Monitor)

2001-01-01

A simple 2D boundary element analysis, suitable for developing cost effective models for tapered composite laminates, is presented. Constant stress and displacement elements are used. Closed-form fundamental solutions are derived. Numerical results are provided for several configurations to illustrate the accuracy of the model.

Day-to-day measurement of patient-reported outcomes in exacerbations of chronic obstructive pulmonary disease

PubMed Central

Kocks, Jan Willem H; van den Berg, Jan Willem K; Kerstjens, Huib AM; Uil, Steven M; Vonk, Judith M; de Jong, Ynze P; Tsiligianni, Ioanna G; van der Molen, Thys

2013-01-01

Background Exacerbations of chronic obstructive pulmonary disease (COPD) are a major burden to patients and to society. Little is known about the possible role of day-to-day patient-reported outcomes during an exacerbation. This study aims to describe the day-to-day course of patient-reported health status during exacerbations of COPD and to assess its value in predicting clinical outcomes. Methods Data from two randomized controlled COPD exacerbation trials (n = 210 and n = 45 patients) were used to describe both the feasibility of daily collection of and the day-to-day course of patient-reported outcomes during outpatient treatment or admission to hospital. In addition to clinical parameters, the BORG dyspnea score, the Clinical COPD Questionnaire (CCQ), and the St George’s Respiratory Questionnaire were used in Cox regression models to predict treatment failure, time to next exacerbation, and mortality in the hospital study. Results All patient-reported outcomes showed a distinct pattern of improvement. In the multivariate models, absence of improvement in CCQ symptom score and impaired lung function were independent predictors of treatment failure. Health status and gender predicted time to next exacerbation. Five-year mortality was predicted by age, forced expiratory flow in one second % predicted, smoking status, and CCQ score. In outpatient management of exacerbations, health status was found to be less impaired than in hospitalized patients, while the rate and pattern of recovery was remarkably similar. Conclusion Daily health status measurements were found to predict treatment failure, which could help decision-making for patients hospitalized due to an exacerbation of COPD. PMID:23766644

Failure Predictions for VHTR Core Components using a Probabilistic Contiuum Damage Mechanics Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fok, Alex

2013-10-30

The proposed work addresses the key research need for the development of constitutive models and overall failure models for graphite and high temperature structural materials, with the long-term goal being to maximize the design life of the Next Generation Nuclear Plant (NGNP). To this end, the capability of a Continuum Damage Mechanics (CDM) model, which has been used successfully for modeling fracture of virgin graphite, will be extended as a predictive and design tool for the core components of the very high- temperature reactor (VHTR). Specifically, irradiation and environmental effects pertinent to the VHTR will be incorporated into the modelmore » to allow fracture of graphite and ceramic components under in-reactor conditions to be modeled explicitly using the finite element method. The model uses a combined stress-based and fracture mechanics-based failure criterion, so it can simulate both the initiation and propagation of cracks. Modern imaging techniques, such as x-ray computed tomography and digital image correlation, will be used during material testing to help define the baseline material damage parameters. Monte Carlo analysis will be performed to address inherent variations in material properties, the aim being to reduce the arbitrariness and uncertainties associated with the current statistical approach. The results can potentially contribute to the current development of American Society of Mechanical Engineers (ASME) codes for the design and construction of VHTR core components.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Livescu, Veronica; Bronkhorst, Curt Allan; Vander Wiel, Scott Alan

Many challenges exist with regard to understanding and representing complex physical processes involved with ductile damage and failure in polycrystalline metallic materials. Currently, the ability to accurately predict the macroscale ductile damage and failure response of metallic materials is lacking. Research at Los Alamos National Laboratory (LANL) is aimed at building a coupled experimental and computational methodology that supports the development of predictive damage capabilities by: capturing real distributions of microstructural features from real material and implementing them as digitally generated microstructures in damage model development; and, distilling structure-property information to link microstructural details to damage evolution under a multitudemore » of loading states.« less

Predicting distant failure in early stage NSCLC treated with SBRT using clinical parameters.

PubMed

Zhou, Zhiguo; Folkert, Michael; Cannon, Nathan; Iyengar, Puneeth; Westover, Kenneth; Zhang, Yuanyuan; Choy, Hak; Timmerman, Robert; Yan, Jingsheng; Xie, Xian-J; Jiang, Steve; Wang, Jing

2016-06-01

The aim of this study is to predict early distant failure in early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT) using clinical parameters by machine learning algorithms. The dataset used in this work includes 81 early stage NSCLC patients with at least 6months of follow-up who underwent SBRT between 2006 and 2012 at a single institution. The clinical parameters (n=18) for each patient include demographic parameters, tumor characteristics, treatment fraction schemes, and pretreatment medications. Three predictive models were constructed based on different machine learning algorithms: (1) artificial neural network (ANN), (2) logistic regression (LR) and (3) support vector machine (SVM). Furthermore, to select an optimal clinical parameter set for the model construction, three strategies were adopted: (1) clonal selection algorithm (CSA) based selection strategy; (2) sequential forward selection (SFS) method; and (3) statistical analysis (SA) based strategy. 5-cross-validation is used to validate the performance of each predictive model. The accuracy was assessed by area under the receiver operating characteristic (ROC) curve (AUC), sensitivity and specificity of the system was also evaluated. The AUCs for ANN, LR and SVM were 0.75, 0.73, and 0.80, respectively. The sensitivity values for ANN, LR and SVM were 71.2%, 72.9% and 83.1%, while the specificity values for ANN, LR and SVM were 59.1%, 63.6% and 63.6%, respectively. Meanwhile, the CSA based strategy outperformed SFS and SA in terms of AUC, sensitivity and specificity. Based on clinical parameters, the SVM with the CSA optimal parameter set selection strategy achieves better performance than other strategies for predicting distant failure in lung SBRT patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A comparison of three organ dysfunction scores: MODS, SOFA and LOD for predicting ICU mortality in critically ill patients.

PubMed

Khwannimit, Bodin

2007-06-01

To compare the validity of the Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), and Logistic Organ Dysfunction Score (LOD) for predicting ICU mortality of Thai critically ill patients. A retrospective study was made of prospective data collected between the 1st July 2004 and 31st March 2006 at Songklanagarind Hospital. One thousand seven hundred and eighty two patients were enrolled in the present study. Two hundred and ninety three (16.4%) deaths were recorded in the ICU. The areas under the Receiver Operating Curves (A UC) for the prediction of ICU mortality the results were 0.861 for MODS, 0.879 for SOFA and 0.880 for LOD. The AUC of SOFA and LOD showed a statistical significance higher than the MODS score (p = 0.014 and p = 0.042, respectively). Of all the models, the neurological failure score showed the best correlation with ICU mortality. All three organ dysfunction scores satisfactorily predicted ICU mortality. The LOD and neurological failure had the best correlation with ICU outcome.

Can the Seattle heart failure model be used to risk-stratify heart failure patients for potential left ventricular assist device therapy?

PubMed

Levy, Wayne C; Mozaffarian, Dariush; Linker, David T; Farrar, David J; Miller, Leslie W

2009-03-01

According to results of the REMATCH trial, left ventricular assist device therapy in patients with severe heart failure has resulted in a 48% reduction in mortality. A decision tool will be necessary to aid in the selection of patients for destination left ventricular assist devices (LVADs) as the technology progresses for implantation in ambulatory Stage D heart failure patients. The purpose of this analysis was to determine whether the Seattle Heart Failure Model (SHFM) can be used to risk-stratify heart failure patients for potential LVAD therapy. The SHFM was applied to REMATCH patients with the prospective addition of inotropic agents and intra-aortic balloon pump (IABP) +/- ventilator. The SHFM was highly predictive of survival (p = 0.0004). One-year SHFM-predicted survival was similar to actual survival for both the REMATCH medical (30% vs 28%) and LVAD (49% vs 52%) groups. The estimated 1-year survival with medical therapy for patients in REMATCH was 30 +/- 21%, but with a range of 0% to 74%. The 1- and 2-year estimated survival was

A Predictive Safety Management System Software Package Based on the Continuous Hazard Tracking and Failure Prediction Methodology

NASA Technical Reports Server (NTRS)

Quintana, Rolando

2003-01-01

The goal of this research was to integrate a previously validated and reliable safety model, called Continuous Hazard Tracking and Failure Prediction Methodology (CHTFPM), into a software application. This led to the development of a safety management information system (PSMIS). This means that the theory or principles of the CHTFPM were incorporated in a software package; hence, the PSMIS is referred to as CHTFPM management information system (CHTFPM MIS). The purpose of the PSMIS is to reduce the time and manpower required to perform predictive studies as well as to facilitate the handling of enormous quantities of information in this type of studies. The CHTFPM theory encompasses the philosophy of looking at the concept of safety engineering from a new perspective: from a proactive, than a reactive, viewpoint. That is, corrective measures are taken before a problem instead of after it happened. That is why the CHTFPM is a predictive safety because it foresees or anticipates accidents, system failures and unacceptable risks; therefore, corrective action can be taken in order to prevent all these unwanted issues. Consequently, safety and reliability of systems or processes can be further improved by taking proactive and timely corrective actions.

Tailor-made heart simulation predicts the effect of cardiac resynchronization therapy in a canine model of heart failure.

PubMed

Panthee, Nirmal; Okada, Jun-ichi; Washio, Takumi; Mochizuki, Youhei; Suzuki, Ryohei; Koyama, Hidekazu; Ono, Minoru; Hisada, Toshiaki; Sugiura, Seiryo

2016-07-01

Despite extensive studies on clinical indices for the selection of patient candidates for cardiac resynchronization therapy (CRT), approximately 30% of selected patients do not respond to this therapy. Herein, we examined whether CRT simulations based on individualized realistic three-dimensional heart models can predict the therapeutic effect of CRT in a canine model of heart failure with left bundle branch block. In four canine models of failing heart with dyssynchrony, individualized three-dimensional heart models reproducing the electromechanical activity of each animal were created based on the computer tomographic images. CRT simulations were performed for 25 patterns of three ventricular pacing lead positions. Lead positions producing the best and the worst therapeutic effects were selected in each model. The validity of predictions was tested in acute experiments in which hearts were paced from the sites identified by simulations. We found significant correlations between the experimentally observed improvement in ejection fraction (EF) and the predicted improvements in ejection fraction (P<0.01) or the maximum value of the derivative of left ventricular pressure (P<0.01). The optimal lead positions produced better outcomes compared with the worst positioning in all dogs studied, although there were significant variations in responses. Variations in ventricular wall thickness among the dogs may have contributed to these responses. Thus CRT simulations using the individualized three-dimensional heart models can predict acute hemodynamic improvement, and help determine the optimal positions of the pacing lead. Copyright © 2016 Elsevier B.V. All rights reserved.

Reliability-based management of buried pipelines considering external corrosion defects

NASA Astrophysics Data System (ADS)

Miran, Seyedeh Azadeh

Corrosion is one of the main deteriorating mechanisms that degrade the energy pipeline integrity, due to transferring corrosive fluid or gas and interacting with corrosive environment. Corrosion defects are usually detected by periodical inspections using in-line inspection (ILI) methods. In order to ensure pipeline safety, this study develops a cost-effective maintenance strategy that consists of three aspects: corrosion growth model development using ILI data, time-dependent performance evaluation, and optimal inspection interval determination. In particular, the proposed study is applied to a cathodic protected buried steel pipeline located in Mexico. First, time-dependent power-law formulation is adopted to probabilistically characterize growth of the maximum depth and length of the external corrosion defects. Dependency between defect depth and length are considered in the model development and generation of the corrosion defects over time is characterized by the homogenous Poisson process. The growth models unknown parameters are evaluated based on the ILI data through the Bayesian updating method with Markov Chain Monte Carlo (MCMC) simulation technique. The proposed corrosion growth models can be used when either matched or non-matched defects are available, and have ability to consider newly generated defects since last inspection. Results of this part of study show that both depth and length growth models can predict damage quantities reasonably well and a strong correlation between defect depth and length is found. Next, time-dependent system failure probabilities are evaluated using developed corrosion growth models considering prevailing uncertainties where three failure modes, namely small leak, large leak and rupture are considered. Performance of the pipeline is evaluated through failure probability per km (or called a sub-system) where each subsystem is considered as a series system of detected and newly generated defects within that sub-system. Sensitivity analysis is also performed to determine to which incorporated parameter(s) in the growth models reliability of the studied pipeline is most sensitive. The reliability analysis results suggest that newly generated defects should be considered in calculating failure probability, especially for prediction of long-term performance of the pipeline and also, impact of the statistical uncertainty in the model parameters is significant that should be considered in the reliability analysis. Finally, with the evaluated time-dependent failure probabilities, a life cycle-cost analysis is conducted to determine optimal inspection interval of studied pipeline. The expected total life-cycle costs consists construction cost and expected costs of inspections, repair, and failure. The repair is conducted when failure probability from any described failure mode exceeds pre-defined probability threshold after each inspection. Moreover, this study also investigates impact of repair threshold values and unit costs of inspection and failure on the expected total life-cycle cost and optimal inspection interval through a parametric study. The analysis suggests that a smaller inspection interval leads to higher inspection costs, but can lower failure cost and also repair cost is less significant compared to inspection and failure costs.

SIXTH INTERIM STATUS REPORT: MODEL 9975 PCV O-RING FIXTURE LONG-TERM LEAK PERFORMANCE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daugherty, W.

2011-08-31

A series of experiments to monitor the aging performance of Viton{reg_sign} GLT O-rings used in the Model 9975 package has been ongoing for seven years at the Savannah River National Laboratory. Seventy tests using mock-ups of 9975 Primary Containment Vessels (PCVs) were assembled and heated to temperatures ranging from 200 to 450 F. They were leak-tested initially and have been tested periodically to determine if they meet the criterion of leak-tightness defined in ANSI standard N14.5-97. Fourteen additional tests were initiated in 2008 with GLT-S O-rings heated to temperatures ranging from 200 to 400 F. High temperature aging continues formore » 33 GLT O-ring fixtures at 200-300 F. Room temperature leak test failures have been experienced in all of the GLT O-ring fixtures aging at 350 F and higher temperatures, and in 7 fixtures aging at 300 F. No failures have yet been observed in GLT O-ring fixtures aging at 200 F for 41-60 months, which is still bounding to O-ring temperatures during storage in K-Area Complex (KAC). Based on expectations that the fixtures aging at 200 F will remain leak-tight for a significant period yet to come, 2 additional fixtures began aging within the past year at an intermediate temperature of 270 F, with hopes that they may leak before the 200 F fixtures. High temperature aging continues for 6 GLT-S O-ring fixtures at 200-300 F. Room temperature leak test failures have been experienced in all 8 of the GLT-S O-ring fixtures aging at 350 and 400 F. No failures have yet been observed in GLT-S O-ring fixtures aging at 200-300 F for up to 26 months. For O-ring fixtures that have failed the room temperature leak test and been disassembled, the Orings displayed a compression set ranging from 51-96%. This is greater than seen to date for packages inspected during KAC field surveillance (24% average). For GLT O-rings, separate service life estimates have been made based on the O-ring fixture leak test data and based on compression stress relaxation (CSR) data. These two predictive models show reasonable agreement at higher temperatures (350-400 F). However, at 300 F, the room temperature leak test failures to date experienced longer aging times than predicted by the CSR-based model. This suggests that extrapolations of the CSR model predictions to temperatures below 300 F will provide a conservative prediction of service life relative to the leak rate criterion. Leak test failure data at lower temperatures are needed to verify this apparent trend. Insufficient failure data exist currently to perform a similar comparison for GLT-S O-rings. Aging and periodic leak testing will continue for the remaining fixtures.« less

Effective Simulation of Delamination in Aeronautical Structures Using Shells and Cohesive Elements

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Camanho, Pedro P.; Turon, Albert

2007-01-01

A cohesive element for shell analysis is presented. The element can be used to simulate the initiation and growth of delaminations between stacked, non-coincident layers of shell elements. The procedure to construct the element accounts for the thickness offset by applying the kinematic relations of shell deformation to transform the stiffness and internal force of a zero-thickness cohesive element such that interfacial continuity between the layers is enforced. The procedure is demonstrated by simulating the response and failure of the Mixed Mode Bending test and a skin-stiffener debond specimen. In addition, it is shown that stacks of shell elements can be used to create effective models to predict the inplane and delamination failure modes of thick components. The results indicate that simple shell models can retain many of the necessary predictive attributes of much more complex 3D models while providing the computational efficiency that is necessary for design.

Cohesive Elements for Shells

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Camanho, Pedro P.; Turon, Albert

2007-01-01

A cohesive element for shell analysis is presented. The element can be used to simulate the initiation and growth of delaminations between stacked, non-coincident layers of shell elements. The procedure to construct the element accounts for the thickness offset by applying the kinematic relations of shell deformation to transform the stiffness and internal force of a zero-thickness cohesive element such that interfacial continuity between the layers is enforced. The procedure is demonstrated by simulating the response and failure of the Mixed Mode Bending test and a skin-stiffener debond specimen. In addition, it is shown that stacks of shell elements can be used to create effective models to predict the inplane and delamination failure modes of thick components. The results indicate that simple shell models can retain many of the necessary predictive attributes of much more complex 3D models while providing the computational efficiency that is necessary for design.

Testing an idealized dynamic cascade model of the development of serious violence in adolescence.

PubMed

Dodge, Kenneth A; Greenberg, Mark T; Malone, Patrick S

2008-01-01

A dynamic cascade model of development of serious adolescent violence was proposed and tested through prospective inquiry with 754 children (50% male; 43% African American) from 27 schools at 4 geographic sites followed annually from kindergarten through Grade 11 (ages 5-18). Self, parent, teacher, peer, observer, and administrative reports provided data. Partial least squares analyses revealed a cascade of prediction and mediation: An early social context of disadvantage predicts harsh-inconsistent parenting, which predicts social and cognitive deficits, which predicts conduct problem behavior, which predicts elementary school social and academic failure, which predicts parental withdrawal from supervision and monitoring, which predicts deviant peer associations, which ultimately predicts adolescent violence. Findings suggest targets for in-depth inquiry and preventive intervention.

Reliability Analysis of Uniaxially Ground Brittle Materials

NASA Technical Reports Server (NTRS)

Salem, Jonathan A.; Nemeth, Noel N.; Powers, Lynn M.; Choi, Sung R.

1995-01-01

The fast fracture strength distribution of uniaxially ground, alpha silicon carbide was investigated as a function of grinding angle relative to the principal stress direction in flexure. Both as-ground and ground/annealed surfaces were investigated. The resulting flexural strength distributions were used to verify reliability models and predict the strength distribution of larger plate specimens tested in biaxial flexure. Complete fractography was done on the specimens. Failures occurred from agglomerates, machining cracks, or hybrid flaws that consisted of a machining crack located at a processing agglomerate. Annealing eliminated failures due to machining damage. Reliability analyses were performed using two and three parameter Weibull and Batdorf methodologies. The Weibull size effect was demonstrated for machining flaws. Mixed mode reliability models reasonably predicted the strength distributions of uniaxial flexure and biaxial plate specimens.

Role of B-Type Natriuretic Peptide and N-Terminal Prohormone BNP as Predictors of Cardiovascular Morbidity and Mortality in Patients With a Recent Coronary Event and Type 2 Diabetes Mellitus.

PubMed

Wolsk, Emil; Claggett, Brian; Pfeffer, Marc A; Diaz, Rafael; Dickstein, Kenneth; Gerstein, Hertzel C; Lawson, Francesca C; Lewis, Eldrin F; Maggioni, Aldo P; McMurray, John J V; Probstfield, Jeffrey L; Riddle, Matthew C; Solomon, Scott D; Tardif, Jean-Claude; Køber, Lars

2017-05-29

Natriuretic peptides are recognized as important predictors of cardiovascular events in patients with heart failure, but less is known about their prognostic importance in patients with acute coronary syndrome. We sought to determine whether B-type natriuretic peptide (BNP) and N-terminal prohormone B-type natriuretic peptide (NT-proBNP) could enhance risk prediction of a broad range of cardiovascular outcomes in patients with acute coronary syndrome and type 2 diabetes mellitus. Patients with a recent acute coronary syndrome and type 2 diabetes mellitus were prospectively enrolled in the ELIXA trial (n=5525, follow-up time 26 months). Best risk models were constructed from relevant baseline variables with and without BNP/NT-proBNP. C statistics, Net Reclassification Index, and Integrated Discrimination Index were analyzed to estimate the value of adding BNP or NT-proBNP to best risk models. Overall, BNP and NT-proBNP were the most important predictors of all outcomes examined, irrespective of history of heart failure or any prior cardiovascular disease. BNP significantly improved C statistics when added to risk models for each outcome examined, the strongest increments being in death (0.77-0.82, P <0.001), cardiovascular death (0.77-0.83, P <0.001), and heart failure (0.84-0.87, P <0.001). BNP or NT-proBNP alone predicted death as well as all other variables combined (0.77 versus 0.77). In patients with a recent acute coronary syndrome and type 2 diabetes mellitus, BNP and NT-proBNP were powerful predictors of cardiovascular outcomes beyond heart failure and death, ie, were also predictive of MI and stroke. Natriuretic peptides added as much predictive information about death as all other conventional variables combined. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01147250. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

A model for the space shuttle main engine high pressure oxidizer turbopump shaft seal system

NASA Technical Reports Server (NTRS)

Paxson, Daniel E.

1990-01-01

A simple static model is presented which solves for the flow properties of pressure, temperature, and mass flow in the Space Shuttle Main Engine pressure Oxidizer Turbopump Shaft Seal Systems. This system includes the primary and secondary turbine seals, the primary and secondary turbine drains, the helium purge seals and feed line, the primary oxygen drain, and the slinger/labyrinth oxygen seal pair. The model predicts the changes in flow variables that occur during and after failures of the various seals. Such information would be particularly useful in a post flight situation where processing of sensor information using this model could identify a particular seal that had experienced excessive wear. Most of the seals in the system are modeled using simple one dimensional equations which can be applied to almost any seal provided that the fluid is gaseous. A failure is modeled as an increase in the clearance between the shaft and the seal. Thus, the model does not attempt to predict how the failure process actually occurs (e.g., wear, seal crack initiation). The results presented were obtained using a FORTRAN implementation of the model running on a VAX computer. Solution for the seal system properties is obtained iteratively; however, a further simplified implementation (which does not include the slinger/labyrinth combination) was also developed which provides fast and reasonable results for most engine operating conditions. Results from the model compare favorably with the limited redline data available.

Damage Instability and Transition From Quasi-Static to Dynamic Fracture

NASA Technical Reports Server (NTRS)

Davila, Carlos G.

2015-01-01

In a typical mechanical test, the loading phase is intended to be a quasi-static process, while the failure and collapse is usually a dynamic event. The structural strength and modes of damage can seldom be predicted without accounting for these two aspects of the response. For a proper prediction, it is therefore essential to use tools and methodologies that are capable of addressing both aspects of responses. In some cases, implicit quasi-static models have been shown to be able to predict the entire response of a structure, including the unstable path that leads to fracture. However, is it acceptable to ignore the effect of inertial forces in the formation of damage? In this presentation we examine aspects of the damage processes that must be simulated for an accurate prediction of structural strength and modes of failure.

Using Modeling and Simulation to Predict Operator Performance and Automation-Induced Complacency With Robotic Automation: A Case Study and Empirical Validation.

PubMed

Wickens, Christopher D; Sebok, Angelia; Li, Huiyang; Sarter, Nadine; Gacy, Andrew M

2015-09-01

The aim of this study was to develop and validate a computational model of the automation complacency effect, as operators work on a robotic arm task, supported by three different degrees of automation. Some computational models of complacency in human-automation interaction exist, but those are formed and validated within the context of fairly simplified monitoring failures. This research extends model validation to a much more complex task, so that system designers can establish, without need for human-in-the-loop (HITL) experimentation, merits and shortcomings of different automation degrees. We developed a realistic simulation of a space-based robotic arm task that could be carried out with three different levels of trajectory visualization and execution automation support. Using this simulation, we performed HITL testing. Complacency was induced via several trials of correctly performing automation and then was assessed on trials when automation failed. Following a cognitive task analysis of the robotic arm operation, we developed a multicomponent model of the robotic operator and his or her reliance on automation, based in part on visual scanning. The comparison of model predictions with empirical results revealed that the model accurately predicted routine performance and predicted the responses to these failures after complacency developed. However, the scanning models do not account for the entire attention allocation effects of complacency. Complacency modeling can provide a useful tool for predicting the effects of different types of imperfect automation. The results from this research suggest that focus should be given to supporting situation awareness in automation development. © 2015, Human Factors and Ergonomics Society.

A Predictive Model of Weight Loss After Roux-en-Y Gastric Bypass up to 5 Years After Surgery: a Useful Tool to Select and Manage Candidates to Bariatric Surgery.

PubMed

Seyssel, Kevin; Suter, Michel; Pattou, François; Caiazzo, Robert; Verkindt, Helene; Raverdy, Violeta; Jolivet, Mathieu; Disse, Emmanuel; Robert, Maud; Giusti, Vittorio

2018-06-19

Different factors, such as age, gender, preoperative weight but also the patient's motivation, are known to impact outcomes after Roux-en-Y gastric bypass (RYGBP). Weight loss prediction is helpful to define realistic expectations and maintain motivation during follow-up, but also to select good candidates for surgery and limit failures. Therefore, developing a realistic predictive tool appears interesting. A Swiss cohort (n = 444), who underwent RYGBP, was used, with multiple linear regression models, to predict weight loss up to 60 months after surgery considering age, height, gender and weight at baseline. We then applied our model on two French cohorts and compared predicted weight to the one finally reached. Accuracy of our model was controlled using root mean square error (RMSE). Mean weight loss was 43.6 ± 13.0 and 40.8 ± 15.4 kg at 12 and 60 months respectively. The model was reliable to predict weight loss (0.37 < R 2  < 0.48) and RMSE between 5.0 and 12.2 kg. High preoperative weight and young age were positively correlated to weight loss, as well as male gender. Correlations between predicted weight and real weight were highly significant in both validation cohorts (R ≥ 0.7 and P < 0.01) and RMSE increased throughout follow-up between 6.2 and 15.4 kg. Our statistical model to predict weight loss outcomes after RYGBP seems accurate. It could be a valuable tool to define realistic weight loss expectations and to improve patient selection and outcomes during follow-up. Further research is needed to demonstrate the interest of this model in improving patients' motivation and results and limit the failures.

Accuracy of circulating histones in predicting persistent organ failure and mortality in patients with acute pancreatitis.

PubMed

Liu, T; Huang, W; Szatmary, P; Abrams, S T; Alhamdi, Y; Lin, Z; Greenhalf, W; Wang, G; Sutton, R; Toh, C H

2017-08-01

Early prediction of acute pancreatitis severity remains a challenge. Circulating levels of histones are raised early in mouse models and correlate with disease severity. It was hypothesized that circulating histones predict persistent organ failure in patients with acute pancreatitis. Consecutive patients with acute pancreatitis fulfilling inclusion criteria admitted to Royal Liverpool University Hospital were enrolled prospectively between June 2010 and March 2014. Blood samples were obtained within 48 h of abdominal pain onset and relevant clinical data during the hospital stay were collected. Healthy volunteers were enrolled as controls. The primary endpoint was occurrence of persistent organ failure. The predictive values of circulating histones, clinical scores and other biomarkers were determined. Among 236 patients with acute pancreatitis, there were 156 (66·1 per cent), 57 (24·2 per cent) and 23 (9·7 per cent) with mild, moderate and severe disease respectively, according to the revised Atlanta classification. Forty-seven healthy volunteers were included. The area under the receiver operating characteristic (ROC) curve (AUC) for circulating histones in predicting persistent organ failure and mortality was 0·92 (95 per cent c.i. 0·85 to 0·99) and 0·96 (0·92 to 1·00) respectively; histones were at least as accurate as clinical scores or biochemical markers. For infected pancreatic necrosis and/or sepsis, the AUC was 0·78 (0·62 to 0·94). Histones did not predict or correlate with local pancreatic complications, but correlated negatively with leucocyte cell viability (r = -0·511, P = 0·001). Quantitative assessment of circulating histones in plasma within 48 h of abdominal pain onset can predict persistent organ failure and mortality in patients with acute pancreatitis. Early death of immune cells may contribute to raised circulating histone levels in acute pancreatitis. © 2017 The Authors. BJS published by John Wiley & Sons Ltd on behalf of BJS Society Ltd.

Nanowire failure: long = brittle and short = ductile.

PubMed

Wu, Zhaoxuan; Zhang, Yong-Wei; Jhon, Mark H; Gao, Huajian; Srolovitz, David J

2012-02-08

Experimental studies of the tensile behavior of metallic nanowires show a wide range of failure modes, ranging from ductile necking to brittle/localized shear failure-often in the same diameter wires. We performed large-scale molecular dynamics simulations of copper nanowires with a range of nanowire lengths and provide unequivocal evidence for a transition in nanowire failure mode with change in nanowire length. Short nanowires fail via a ductile mode with serrated stress-strain curves, while long wires exhibit extreme shear localization and abrupt failure. We developed a simple model for predicting the critical nanowire length for this failure mode transition and showed that it is in excellent agreement with both the simulation results and the extant experimental data. The present results provide a new paradigm for the design of nanoscale mechanical systems that demarcates graceful and catastrophic failure. © 2012 American Chemical Society

The Use of Various Failure Criteria as Applied to High Speed Wear

DTIC Science & Technology

2011-12-01

This research has been aimed at developing methods to predict mechanical wear of sliding bodies at high velocities. Specifically, wear of test sled...Several failure criteria were evaluated as possible methods to estimate damaged material from the sliding body . The Johnson and Cook constitutive...Data [11] . . . . . . . . . . . . . 12 1.11. Finite Element Model Used by Burton [11] . . . . . . . . . . . 12 1.12. HHSTT Third Stage Velocity

Neonatal Hypoxia, Hippocampal Atrophy, and Memory Impairment: Evidence of a Causal Sequence

PubMed Central

Cooper, Janine M.; Gadian, David G.; Jentschke, Sebastian; Goldman, Allan; Munoz, Monica; Pitts, Georgia; Banks, Tina; Chong, W. Kling; Hoskote, Aparna; Deanfield, John; Baldeweg, Torsten; de Haan, Michelle; Mishkin, Mortimer; Vargha-Khadem, Faraneh

2015-01-01

Neonates treated for acute respiratory failure experience episodes of hypoxia. The hippocampus, a structure essential for memory, is particularly vulnerable to such insults. Hence, some neonates undergoing treatment for acute respiratory failure might sustain bilateral hippocampal pathology early in life and memory problems later in childhood. We investigated this possibility in a cohort of 40 children who had been treated neonatally for acute respiratory failure but were free of overt neurological impairment. The cohort had mean hippocampal volumes (HVs) significantly below normal control values, memory scores significantly below the standard population means, and memory quotients significantly below those predicted by their full scale IQs. Brain white matter volume also fell below the volume of the controls, but brain gray matter volumes and scores on nonmnemonic neuropsychological tests were within the normal range. Stepwise linear regression models revealed that the cohort's HVs were predictive of degree of memory impairment, and gestational age at treatment was predictive of HVs: the younger the age, the greater the atrophy. We conclude that many neonates treated for acute respiratory failure sustain significant hippocampal atrophy as a result of the associated hypoxia and, consequently, show deficient memory later in life. PMID:24343890

Prognostics for Microgrid Components

NASA Technical Reports Server (NTRS)

Saxena, Abhinav

2012-01-01

Prognostics is the science of predicting future performance and potential failures based on targeted condition monitoring. Moving away from the traditional reliability centric view, prognostics aims at detecting and quantifying the time to impending failures. This advance warning provides the opportunity to take actions that can preserve uptime, reduce cost of damage, or extend the life of the component. The talk will focus on the concepts and basics of prognostics from the viewpoint of condition-based systems health management. Differences with other techniques used in systems health management and philosophies of prognostics used in other domains will be shown. Examples relevant to micro grid systems and subsystems will be used to illustrate various types of prediction scenarios and the resources it take to set up a desired prognostic system. Specifically, the implementation results for power storage and power semiconductor components will demonstrate specific solution approaches of prognostics. The role of constituent elements of prognostics, such as model, prediction algorithms, failure threshold, run-to-failure data, requirements and specifications, and post-prognostic reasoning will be explained. A discussion on performance evaluation and performance metrics will conclude the technical discussion followed by general comments on open research problems and challenges in prognostics.

Neonatal hypoxia, hippocampal atrophy, and memory impairment: evidence of a causal sequence.

PubMed

Cooper, Janine M; Gadian, David G; Jentschke, Sebastian; Goldman, Allan; Munoz, Monica; Pitts, Georgia; Banks, Tina; Chong, W Kling; Hoskote, Aparna; Deanfield, John; Baldeweg, Torsten; de Haan, Michelle; Mishkin, Mortimer; Vargha-Khadem, Faraneh

2015-06-01

Neonates treated for acute respiratory failure experience episodes of hypoxia. The hippocampus, a structure essential for memory, is particularly vulnerable to such insults. Hence, some neonates undergoing treatment for acute respiratory failure might sustain bilateral hippocampal pathology early in life and memory problems later in childhood. We investigated this possibility in a cohort of 40 children who had been treated neonatally for acute respiratory failure but were free of overt neurological impairment. The cohort had mean hippocampal volumes (HVs) significantly below normal control values, memory scores significantly below the standard population means, and memory quotients significantly below those predicted by their full scale IQs. Brain white matter volume also fell below the volume of the controls, but brain gray matter volumes and scores on nonmnemonic neuropsychological tests were within the normal range. Stepwise linear regression models revealed that the cohort's HVs were predictive of degree of memory impairment, and gestational age at treatment was predictive of HVs: the younger the age, the greater the atrophy. We conclude that many neonates treated for acute respiratory failure sustain significant hippocampal atrophy as a result of the associated hypoxia and, consequently, show deficient memory later in life. © The Author 2013. Published by Oxford University Press.

Evolution of an interfacial crack on the concrete-embankment boundary

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glascoe, Lee; Antoun, Tarabay; Kanarska, Yuliya

2013-07-10

Failure of a dam can have subtle beginnings. A small crack or dislocation at the interface of the concrete dam and the surrounding embankment soil initiated by, for example, a seismic or an explosive event can lead to a catastrophic failure of the dam. The dam may ‘self-rehabilitate’ if a properly designed granular filter is engineered around the embankment. Currently, the design criteria for such filters have only been based on experimental studies. We demonstrate the numerical prediction of filter effectiveness at the soil grain scale. This joint LLNL-ERDC basic research project, funded by the Department of Homeland Security’s Sciencemore » and Technology Directorate (DHS S&T), consists of validating advanced high performance computer simulations of soil erosion and transport of grain- and dam-scale models to detailed centrifuge and soil erosion tests. Validated computer predictions highlight that a resilient filter is consistent with the current design specifications for dam filters. These predictive simulations, unlike the design specifications, can be used to assess filter success or failure under different soil or loading conditions and can lead to meaningful estimates of the timing and nature of full-scale dam failure.« less

Predicting Vulnerability of the Integrity and Connectivity Associated with Culverts in Low Order Streams of Northern Michigan

NASA Astrophysics Data System (ADS)

King, C. H.; Wagenbrenner, J.; Fedora, M.; Watkins, D.; Watkins, M. K.; Huckins, C.

2017-12-01

The Great Lakes Region of North America has experienced more frequent extreme precipitation events in recent decades, resulting in a large number of stream crossing failures. While there are accepted methods for designing stream crossings to accommodate peak storm discharges, less attention has been paid to assessing the risk of failure. To evaluate failure risk and potential impacts, coarse-resolution stream crossing surveys were completed on 51 stream crossings and dams in the North Branch Paint River watershed in Michigan's Upper Peninsula. These inventories determined stream crossing dimensions along with stream and watershed characteristics. Eleven culverts were selected from the coarse surveys for high resolution hydraulic analysis to estimate discharge conditions expected at crossing failure. Watershed attributes upstream of the crossing, including area, slope, and storage, were acquired. Sediment discharge and the economic impact associated with a failure event were also estimated for each stream crossing. Impacts to stream connectivity and fish passability were assessed from the coarse-level surveys. Using information from both the coarse and high-resolution surveys, we also developed indicators to predict failure risk without the need for complex hydraulic modeling. These passability scores and failure risk indicators will help to prioritize infrastructure replacement and improve the overall connectivity of river systems throughout the upper Great Lakes Region.

Cascading Failures as Continuous Phase-Space Transitions

DOE PAGES

Yang, Yang; Motter, Adilson E.

2017-12-14

In network systems, a local perturbation can amplify as it propagates, potentially leading to a large-scale cascading failure. We derive a continuous model to advance our understanding of cascading failures in power-grid networks. The model accounts for both the failure of transmission lines and the desynchronization of power generators and incorporates the transient dynamics between successive steps of the cascade. In this framework, we show that a cascade event is a phase-space transition from an equilibrium state with high energy to an equilibrium state with lower energy, which can be suitably described in a closed form using a global Hamiltonian-likemore » function. From this function, we show that a perturbed system cannot always reach the equilibrium state predicted by quasi-steady-state cascade models, which would correspond to a reduced number of failures, and may instead undergo a larger cascade. We also show that, in the presence of two or more perturbations, the outcome depends strongly on the order and timing of the individual perturbations. These results offer new insights into the current understanding of cascading dynamics, with potential implications for control interventions.« less

Cascading Failures as Continuous Phase-Space Transitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Yang; Motter, Adilson E.

In network systems, a local perturbation can amplify as it propagates, potentially leading to a large-scale cascading failure. We derive a continuous model to advance our understanding of cascading failures in power-grid networks. The model accounts for both the failure of transmission lines and the desynchronization of power generators and incorporates the transient dynamics between successive steps of the cascade. In this framework, we show that a cascade event is a phase-space transition from an equilibrium state with high energy to an equilibrium state with lower energy, which can be suitably described in a closed form using a global Hamiltonian-likemore » function. From this function, we show that a perturbed system cannot always reach the equilibrium state predicted by quasi-steady-state cascade models, which would correspond to a reduced number of failures, and may instead undergo a larger cascade. We also show that, in the presence of two or more perturbations, the outcome depends strongly on the order and timing of the individual perturbations. These results offer new insights into the current understanding of cascading dynamics, with potential implications for control interventions.« less

The dynamic failure behavior of tungsten heavy alloys subjected to transverse loads

NASA Astrophysics Data System (ADS)

Tarcza, Kenneth Robert

Tungsten heavy alloys (WHA), a category of particulate composites used in defense applications as kinetic energy penetrators, have been studied for many years. Even so, their dynamic failure behavior is not fully understood and cannot be predicted by numerical models presently in use. In this experimental investigation, a comprehensive understanding of the high-rate transverse-loading fracture behavior of WHA has been developed. Dynamic fracture events spanning a range of strain rates and loading conditions were created via mechanical testing and used to determine the influence of surface condition and microstructure on damage initiation, accumulation, and sample failure under different loading conditions. Using standard scanning electron microscopy metallographic and fractographic techniques, sample surface condition is shown to be extremely influential to the manner in which WHA fails, causing a fundamental change from externally to internally nucleated failures as surface condition is improved. Surface condition is characterized using electron microscopy and surface profilometry. Fracture surface analysis is conducted using electron microscopy, and linear elastic fracture mechanics is used to understand the influence of surface condition, specifically initial flaw size, on sample failure behavior. Loading conditions leading to failure are deduced from numerical modeling and experimental observation. The results highlight parameters and considerations critical to the understanding of dynamic WHA fracture and the development of dynamic WHA failure models.

Prediction of moment-rotation characteristic of top- and seat-angle bolted connection incorporating prying action

NASA Astrophysics Data System (ADS)

Ahmed, Ali

2017-03-01

Finite element (FE) analyses were performed to explore the prying influence on moment-rotation behaviour and to locate yielding zones of top- and seat-angle connections in author's past research studies. The results of those FE analyses with experimental failure strategies of the connections were used to develop failure mechanisms of top- and seat-angle connections in the present study. Then a formulation was developed based on three simple failure mechanisms considering bending and shear deformations, effects of prying action on the top angle and stiffness of the tension bolts to estimate rationally the ultimate moment M u of the connection, which is a vital parameter of the proposed four-parameter power model. Applicability of the proposed formulation is assessed by comparing moment-rotation ( M- θ r ) curves and ultimate moment capacities with those measured by experiments and estimated by FE analyses and three-parameter power model. This study shows that proposed formulation and Kishi-Chen's method both achieved close approximation driving M- θ r curves of all given connections except a few cases of Kishi-Chen model, and M u estimated by the proposed formulation is more rational than that predicted by Kishi-Chen's method.

Falling Off Track: How Teacher-Student Relationships Predict Early High School Failure Rates.

ERIC Educational Resources Information Center

Miller, Shazia Rafiullah

This paper examines the relationship between the climate of teacher-student relations within a school and individual student's likelihood of freshman year success. Using administrative data from the Chicago Public Schools and survey data, researchers used hierarchical linear modeling to determine whether teacher-student climate predicts students'…

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear, transient dynamic finite element code, MSC.Dytran, was used to simulate an impact test of an energy absorbing Earth Entry Vehicle (EEV) that will impact without a parachute. EEVOs are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the center of the EEVOs cellular structure. Pre-test analytical predictions were compared with the test results from a bungee accelerator. The model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAM1 model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for cellular impact.

Wind Turbine Failures - Tackling current Problems in Failure Data Analysis

NASA Astrophysics Data System (ADS)

Reder, M. D.; Gonzalez, E.; Melero, J. J.

2016-09-01

The wind industry has been growing significantly over the past decades, resulting in a remarkable increase in installed wind power capacity. Turbine technologies are rapidly evolving in terms of complexity and size, and there is an urgent need for cost effective operation and maintenance (O&M) strategies. Especially unplanned downtime represents one of the main cost drivers of a modern wind farm. Here, reliability and failure prediction models can enable operators to apply preventive O&M strategies rather than corrective actions. In order to develop these models, the failure rates and downtimes of wind turbine (WT) components have to be understood profoundly. This paper is focused on tackling three of the main issues related to WT failure analyses. These are, the non-uniform data treatment, the scarcity of available failure analyses, and the lack of investigation on alternative data sources. For this, a modernised form of an existing WT taxonomy is introduced. Additionally, an extensive analysis of historical failure and downtime data of more than 4300 turbines is presented. Finally, the possibilities to encounter the lack of available failure data by complementing historical databases with Supervisory Control and Data Acquisition (SCADA) alarms are evaluated.

Accurate Prediction of Motor Failures by Application of Multi CBM Tools: A Case Study

NASA Astrophysics Data System (ADS)

Dutta, Rana; Singh, Veerendra Pratap; Dwivedi, Jai Prakash

2018-02-01

Motor failures are very difficult to predict accurately with a single condition-monitoring tool as both electrical and the mechanical systems are closely related. Electrical problem, like phase unbalance, stator winding insulation failures can, at times, lead to vibration problem and at the same time mechanical failures like bearing failure, leads to rotor eccentricity. In this case study of a 550 kW blower motor it has been shown that a rotor bar crack was detected by current signature analysis and vibration monitoring confirmed the same. In later months in a similar motor vibration monitoring predicted bearing failure and current signature analysis confirmed the same. In both the cases, after dismantling the motor, the predictions were found to be accurate. In this paper we will be discussing the accurate predictions of motor failures through use of multi condition monitoring tools with two case studies.

A Micromechanics-Based Damage Model for [+/- Theta/90n]s Composite Laminates

NASA Technical Reports Server (NTRS)

Mayugo, Joan-Andreu; Camanho, Pedro P.; Maimi, Pere; Davila, Carlos G.

2006-01-01

A new damage model based on a micromechanical analysis of cracked [+/- Theta/90n]s laminates subjected to multiaxial loads is proposed. The model predicts the onset and accumulation of transverse matrix cracks in uniformly stressed laminates, the effect of matrix cracks on the stiffness of the laminate, as well as the ultimate failure of the laminate. The model also accounts for the effect of the ply thickness on the ply strength. Predictions relating the elastic properties of several laminates and multiaxial loads are presented.

Thermomechanical Controls on the Success and Failure of Continental Rift Systems

NASA Astrophysics Data System (ADS)

Brune, S.

2017-12-01

Studies of long-term continental rift evolution are often biased towards rifts that succeed in breaking the continent like the North Atlantic, South China Sea, or South Atlantic rifts. However there are many prominent rift systems on Earth where activity stopped before the formation of a new ocean basin such as the North Sea, the West and Central African Rifts, or the West Antarctic Rift System. The factors controlling the success and failure of rifts can be divided in two groups: (1) Intrinsic processes - for instance frictional weakening, lithospheric thinning, shear heating or the strain-dependent growth of rift strength by replacing weak crust with strong mantle. (2) External processes - such as a change of plate divergence rate, the waning of a far-field driving force, or the arrival of a mantle plume. Here I use numerical and analytical modeling to investigate the role of these processes for the success and failure of rift systems. These models show that a change of plate divergence rate under constant force extension is controlled by the non-linearity of lithospheric materials. For successful rifts, a strong increase in divergence velocity can be expected to take place within few million years, a prediction that agrees with independent plate tectonic reconstructions of major Mesozoic and Cenozoic ocean-forming rift systems. Another model prediction is that oblique rifting is mechanically favored over orthogonal rifting, which means that simultaneous deformation within neighboring rift systems of different obliquity and otherwise identical properties will lead to success and failure of the more and less oblique rift, respectively. This can be exemplified by the Cretaceous activity within the Equatorial Atlantic and the West African Rifts that lead to the formation of a highly oblique oceanic spreading center and the failure of the West African Rift System. While in nature the circumstances of rift success or failure may be manifold, simplified numerical and analytical models allow the isolated analysis of various contributing factors and to define a characteristic time scale for each process.

Model Verification and Validation Concepts for a Probabilistic Fracture Assessment Model to Predict Cracking of Knife Edge Seals in the Space Shuttle Main Engine High Pressure Oxidizer

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Riha, David S.

2013-01-01

Physics-based models are routinely used to predict the performance of engineered systems to make decisions such as when to retire system components, how to extend the life of an aging system, or if a new design will be safe or available. Model verification and validation (V&V) is a process to establish credibility in model predictions. Ideally, carefully controlled validation experiments will be designed and performed to validate models or submodels. In reality, time and cost constraints limit experiments and even model development. This paper describes elements of model V&V during the development and application of a probabilistic fracture assessment model to predict cracking in space shuttle main engine high-pressure oxidizer turbopump knife-edge seals. The objective of this effort was to assess the probability of initiating and growing a crack to a specified failure length in specific flight units for different usage and inspection scenarios. The probabilistic fracture assessment model developed in this investigation combined a series of submodels describing the usage, temperature history, flutter tendencies, tooth stresses and numbers of cycles, fatigue cracking, nondestructive inspection, and finally the probability of failure. The analysis accounted for unit-to-unit variations in temperature, flutter limit state, flutter stress magnitude, and fatigue life properties. The investigation focused on the calculation of relative risk rather than absolute risk between the usage scenarios. Verification predictions were first performed for three units with known usage and cracking histories to establish credibility in the model predictions. Then, numerous predictions were performed for an assortment of operating units that had flown recently or that were projected for future flights. Calculations were performed using two NASA-developed software tools: NESSUS(Registered Trademark) for the probabilistic analysis, and NASGRO(Registered Trademark) for the fracture mechanics analysis. The goal of these predictions was to provide additional information to guide decisions on the potential of reusing existing and installed units prior to the new design certification.

Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

PubMed

Lau, Lawrence; Kankanige, Yamuna; Rubinstein, Benjamin; Jones, Robert; Christophi, Christopher; Muralidharan, Vijayaragavan; Bailey, James

2017-04-01

The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritized. An index that is derived to predict graft failure using donor and recipient factors, based on local data sets, will be more beneficial in the Australian context. Liver transplant data from the Austin Hospital, Melbourne, Australia, from 2010 to 2013 has been included in the study. The top 15 donor, recipient, and transplant factors influencing the outcome of graft failure within 30 days were selected using a machine learning methodology. An algorithm predicting the outcome of interest was developed using those factors. Donor Risk Index predicts the outcome with an area under the receiver operating characteristic curve (AUC-ROC) value of 0.680 (95% confidence interval [CI], 0.669-0.690). The combination of the factors used in Donor Risk Index with the model for end-stage liver disease score yields an AUC-ROC of 0.764 (95% CI, 0.756-0.771), whereas survival outcomes after liver transplantation score obtains an AUC-ROC of 0.638 (95% CI, 0.632-0.645). The top 15 donor and recipient characteristics within random forests results in an AUC-ROC of 0.818 (95% CI, 0.812-0.824). Using donor, transplant, and recipient characteristics known at the decision time of a transplant, high accuracy in matching donors and recipients can be achieved, potentially providing assistance with clinical decision making.

Ganymede's Stresses Past and Present: How Evolving Eccentricity Effects Tidally-Driven Coulomb Failure

NASA Astrophysics Data System (ADS)

Cameron, M. E.; Smith-Konter, B. R.; Burkhard, L. M.; Patthoff, D. A.; Pappalardo, R. T.; Collins, G. C.

2017-12-01

Laplace-like resonances among Ganymede, Europa, and Io may have once led Ganymede to have an eccentricity as high as 0.07 (presently e = 0.0013). While diurnal stresses at Ganymede today are small (<10 kPa), a previous period of high eccentricity may have produced significant diurnal tidal stresses that influenced faulting during a past period of active tectonism. We investigate the role of tidal stresses on faulting by using the numerical model SatStress to calculate both diurnal and non-synchronous rotation (NSR) tidal stresses at Ganymede's surface. We assume an NSR rate of 105 years, and steady-state rotation of a viscoelastic ice shell of viscosity 1019 Pa s, yielding stresses on the order of MPa. We adopt two end-member models: (1) present-day Ganymede, and (2) Ganymede in the past (e = 0.05). For the present-day model, we assume a spherical ice shell of thickness 150 km (upper 10 km is cold, stiff ice), underlain by a 40 km deep global subsurface ocean. For the warmer past model, we assume a 100 km ice shell (upper 2 km is cold, stiff ice), and a 140 km ocean. We resolve normal and shear stress components onto discrete fault segments of specified orientation and assess Coulomb failure stress criteria along three previously inferred shear zones: Dardanus Sulcus, Tiamat Sulcus, and Nun Sulci. Models of stress contributions from only the diurnal tidal cycle are strongly dependent on eccentricity, while combined diurnal and NSR stress models are largely insensitive due to large (MPa) NSR stresses. For the diurnal only model, failure is not expected for the present eccentricity along any of the three shear zones. For the past, high eccentricity case, failure is predicted in isolated diurnal slip windows and limited to very shallow depths (< 250 m). This model predicts a dominant right-lateral slip window for both Dardanus and Tiamat Sulcus and significant right- and left-lateral slip windows are predicted along both north and south branches of Nun Sulci. Likewise, the sense of inferred shear from imagery and structural mapping efforts is right-lateral for Dardanus and Tiamat Sulcus, and left-lateral for Nun Sulci. Moreover, a low coefficient of friction (μf = 0.2) Coulomb failure model of right- and left- lateral slip episodes over a diurnal cycle could indicate a plausible case for tidal walking in Ganymede's high-eccentricity past.

Predicting the Probability of Failure of Cementitious Sewer Pipes Using Stochastic Finite Element Method

PubMed Central

Alani, Amir M.; Faramarzi, Asaad

2015-01-01

In this paper, a stochastic finite element method (SFEM) is employed to investigate the probability of failure of cementitious buried sewer pipes subjected to combined effect of corrosion and stresses. A non-linear time-dependant model is used to determine the extent of concrete corrosion. Using the SFEM, the effects of different random variables, including loads, pipe material, and corrosion on the remaining safe life of the cementitious sewer pipes are explored. A numerical example is presented to demonstrate the merit of the proposed SFEM in evaluating the effects of the contributing parameters upon the probability of failure of cementitious sewer pipes. The developed SFEM offers many advantages over traditional probabilistic techniques since it does not use any empirical equations in order to determine failure of pipes. The results of the SFEM can help the concerning industry (e.g., water companies) to better plan their resources by providing accurate prediction for the remaining safe life of cementitious sewer pipes. PMID:26068092

Predictions of High Strain Rate Failure Modes in Layered Aluminum Composites

NASA Astrophysics Data System (ADS)

Khanikar, Prasenjit; Zikry, M. A.

2014-01-01

A dislocation density-based crystalline plasticity formulation, specialized finite-element techniques, and rational crystallographic orientation relations were used to predict and characterize the failure modes associated with the high strain rate behavior of aluminum layered composites. Two alloy layers, a high strength alloy, aluminum 2195, and an aluminum alloy 2139, with high toughness, were modeled with representative microstructures that included precipitates, dispersed particles, and different grain boundary distributions. Different layer arrangements were investigated for high strain rate applications and the optimal arrangement was with the high toughness 2139 layer on the bottom, which provided extensive shear strain localization, and the high strength 2195 layer on the top for high strength resistance The layer thickness of the bottom high toughness layer also affected the bending behavior of the roll-bonded interface and the potential delamination of the layers. Shear strain localization, dynamic cracking, and delamination are the mutually competing failure mechanisms for the layered metallic composite, and control of these failure modes can be used to optimize behavior for high strain rate applications.

Predicting laser weld reliability with stochastic reduced-order models. Predicting laser weld reliability

DOE PAGES

Emery, John M.; Field, Richard V.; Foulk, James W.; ...

2015-05-26

Laser welds are prevalent in complex engineering systems and they frequently govern failure. The weld process often results in partial penetration of the base metals, leaving sharp crack-like features with a high degree of variability in the geometry and material properties of the welded structure. Furthermore, accurate finite element predictions of the structural reliability of components containing laser welds requires the analysis of a large number of finite element meshes with very fine spatial resolution, where each mesh has different geometry and/or material properties in the welded region to address variability. We found that traditional modeling approaches could not bemore » efficiently employed. Consequently, a method is presented for constructing a surrogate model, based on stochastic reduced-order models, and is proposed to represent the laser welds within the component. Here, the uncertainty in weld microstructure and geometry is captured by calibrating plasticity parameters to experimental observations of necking as, because of the ductility of the welds, necking – and thus peak load – plays the pivotal role in structural failure. The proposed method is exercised for a simplified verification problem and compared with the traditional Monte Carlo simulation with rather remarkable results.« less

Orthotropic elasto-plastic behavior of AS4/APC-2 thermoplastic composite in compression

NASA Technical Reports Server (NTRS)

Sun, C. T.; Rui, Y.

1989-01-01

Uniaxial compression tests were performed on off-axis coupon specimens of unidirectional AS4/APC-2 thermoplastic composite at various temperatures. The elasto-plastic and strength properties of AS4/APC-2 composite were characterized with respect to temperature variation by using a one-parameter orthotropic plasticity model and a one-parameter failure criterion. Experimental results show that the orthotropic plastic behavior can be characterized quite well using the plasticity model, and the matrix-dominant compressive strengths can be predicted very accurately by the one-parameter failure criterion.

Progressive Damage Analyses of Skin/Stringer Debonding

NASA Technical Reports Server (NTRS)

Daville, Carlos G.; Camanho, Pedro P.; deMoura, Marcelo F.

2004-01-01

The debonding of skin/stringer constructions is analyzed using a step-by-step simulation of material degradation based on strain softening decohesion elements and a ply degradation procedure. Decohesion elements with mixed-mode capability are placed at the interface between the skin and the flange to simulate the initiation and propagation of the delamination. In addition, the initiation and accumulation of fiber failure and matrix damage is modeled using Hashin-type failure criteria and their corresponding material degradation schedules. The debonding predictions using simplified three-dimensional models correlate well with test results.

A numerical approach to model and predict the energy absorption and crush mechanics within a long-fiber composite crush tube

NASA Astrophysics Data System (ADS)

Pickett, Leon, Jr.

Past research has conclusively shown that long fiber structural composites possess superior specific energy absorption characteristics as compared to steel and aluminum structures. However, destructive physical testing of composites is very costly and time consuming. As a result, numerical solutions are desirable as an alternative to experimental testing. Up until this point, very little numerical work has been successful in predicting the energy absorption of composite crush structures. This research investigates the ability to use commercially available numerical modeling tools to approximate the energy absorption capability of long-fiber composite crush tubes. This study is significant because it provides a preliminary analysis of the suitability of LS-DYNA to numerically characterize the crushing behavior of a dynamic axial impact crushing event. Composite crushing theory suggests that there are several crushing mechanisms occurring during a composite crush event. This research evaluates the capability and suitability of employing, LS-DYNA, to simulate the dynamic crush event of an E-glass/epoxy cylindrical tube. The model employed is the composite "progressive failure model", a much more limited failure model when compared to the experimental failure events which naturally occur. This numerical model employs (1) matrix cracking, (2) compression, and (3) fiber breakage failure modes only. The motivation for the work comes from the need to reduce the significant cost associated with experimental trials. This research chronicles some preliminary efforts to better understand the mechanics essential in pursuit of this goal. The immediate goal is to begin to provide deeper understanding of a composite crush event and ultimately create a viable alternative to destructive testing of composite crush tubes.

Real-time forecasting and predictability of catastrophic failure events: from rock failure to volcanoes and earthquakes

NASA Astrophysics Data System (ADS)

Main, I. G.; Bell, A. F.; Naylor, M.; Atkinson, M.; Filguera, R.; Meredith, P. G.; Brantut, N.

2012-12-01

Accurate prediction of catastrophic brittle failure in rocks and in the Earth presents a significant challenge on theoretical and practical grounds. The governing equations are not known precisely, but are known to produce highly non-linear behavior similar to those of near-critical dynamical systems, with a large and irreducible stochastic component due to material heterogeneity. In a laboratory setting mechanical, hydraulic and rock physical properties are known to change in systematic ways prior to catastrophic failure, often with significant non-Gaussian fluctuations about the mean signal at a given time, for example in the rate of remotely-sensed acoustic emissions. The effectiveness of such signals in real-time forecasting has never been tested before in a controlled laboratory setting, and previous work has often been qualitative in nature, and subject to retrospective selection bias, though it has often been invoked as a basis in forecasting natural hazard events such as volcanoes and earthquakes. Here we describe a collaborative experiment in real-time data assimilation to explore the limits of predictability of rock failure in a best-case scenario. Data are streamed from a remote rock deformation laboratory to a user-friendly portal, where several proposed physical/stochastic models can be analysed in parallel in real time, using a variety of statistical fitting techniques, including least squares regression, maximum likelihood fitting, Markov-chain Monte-Carlo and Bayesian analysis. The results are posted and regularly updated on the web site prior to catastrophic failure, to ensure a true and and verifiable prospective test of forecasting power. Preliminary tests on synthetic data with known non-Gaussian statistics shows how forecasting power is likely to evolve in the live experiments. In general the predicted failure time does converge on the real failure time, illustrating the bias associated with the 'benefit of hindsight' in retrospective analyses. Inference techniques that account explicitly for non-Gaussian statistics significantly reduce the bias, and increase the reliability and accuracy, of the forecast failure time in prospective mode.

Micromechanical models for textile structural composites

NASA Technical Reports Server (NTRS)

Marrey, Ramesh V.; Sankar, Bhavani V.

1995-01-01

The objective is to develop micromechanical models for predicting the stiffness and strength properties of textile composite materials. Two models are presented to predict the homogeneous elastic constants and coefficients of thermal expansion of a textile composite. The first model is based on rigorous finite element analysis of the textile composite unit-cell. Periodic boundary conditions are enforced between opposite faces of the unit-cell to simulate deformations accurately. The second model implements the selective averaging method (SAM), which is based on a judicious combination of stiffness and compliance averaging. For thin textile composites, both models can predict the plate stiffness coefficients and plate thermal coefficients. The finite element procedure is extended to compute the thermal residual microstresses, and to estimate the initial failure envelope for textile composites.

Fatigue of concrete subjected to biaxial loading in the tension region

NASA Astrophysics Data System (ADS)

Subramaniam, Kolluru V. L.

Rigid airport pavement structures are subjected to repeated high-amplitude loads resulting from passing aircraft. The resulting stress-state in the concrete is a biaxial combination of compression and tension. It is of interest to model the response of plain concrete to such loading conditions and develop accurate fatigue-based material models for implementation in mechanistic pavement design procedures. The objective of this work is to characterize the quasi-static and low-cycle fatigue response of concrete subjected to biaxial stresses in the tensile-compression-tension (t-C-T) region, where the principal tensile stress is larger in magnitude than the principal compressive stress. An experimental investigation of material behavior in the biaxial t-C-T region is conducted. The experimental setup consists of the following test configurations: (a) notched concrete beams tested in three-point bend configuration, and (b) hollow concrete cylinders subjected to torsion with or without superimposed axial tensile force. The damage imparted to the material is examined using mechanical measurements and an independent nondestructive evaluation (NDE) technique based on vibration measurements. The failure of concrete in t-C-T region is shown to be a local phenomenon under quasi-static and fatigue loading, wherein the specimen fails owing to a single crack. The crack propagation is studied using the principles of fracture mechanics. It is shown that the crack propagation resulting from the t-C-T loading can be predicted using mode I fracture parameters. It is observed that crack growth in constant amplitude fatigue loading is a two-phase process: a deceleration phase followed by an acceleration stage. The quasi-static load envelope is shown to predict the crack length at fatigue failure. A fracture-based fatigue failure criterion is proposed, wherein the fatigue failure can be predicted using the critical mode I stress intensity factor. A material model for the damage evolution during fatigue loading of concrete in terms of crack propagation is proposed. The crack growth acceleration stage is shown to follow Paris law. The model parameters obtained from uniaxial fatigue tests are shown to be sufficient for predicting the considered biaxial fatigue response.

Spatial regression methods capture prediction uncertainty in species distribution model projections through time

Treesearch

Alan K. Swanson; Solomon Z. Dobrowski; Andrew O. Finley; James H. Thorne; Michael K. Schwartz

2013-01-01

The uncertainty associated with species distribution model (SDM) projections is poorly characterized, despite its potential value to decision makers. Error estimates from most modelling techniques have been shown to be biased due to their failure to account for spatial autocorrelation (SAC) of residual error. Generalized linear mixed models (GLMM) have the ability to...

Everyday cognitive failure and depressive symptoms predict fatigue in sarcoidosis: A prospective follow-up study.

PubMed

Hendriks, Celine; Drent, Marjolein; De Kleijn, Willemien; Elfferich, Marjon; Wijnen, Petal; De Vries, Jolanda

2018-05-01

Fatigue is a major and disabling problem in sarcoidosis. Knowledge concerning correlates of the development of fatigue and possible interrelationships is lacking. A conceptual model of fatigue was developed and tested. Sarcoidosis outpatients (n = 292) of Maastricht University Medical Center completed questionnaires regarding trait anxiety, depressive symptoms, cognitive failure, dyspnea, social support, and small fiber neuropathy (SFN) at baseline. Fatigue was assessed at 6 and 12 months. Sex, age, and time since diagnosis were taken from medical records. Pathways were estimated by means of path analyses in AMOS. Everyday cognitive failure, depressive symptoms, symptoms suggestive of SFN, and dyspnea were positive predictors of fatigue. Fit indices of the model were good. The model validly explains variation in fatigue. Everyday cognitive failure and depressive symptoms were the most important predictors of fatigue. In addition to physical functioning, cognitive and psychological aspects should be included in the management of sarcoidosis patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

PCI fuel failure analysis: a report on a cooperative program undertaken by Pacific Northwest Laboratory and Chalk River Nuclear Laboratories.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohr, C.L.; Pankaskie, P.J.; Heasler, P.G.

Reactor fuel failure data sets in the form of initial power (P/sub i/), final power (P/sub f/), transient increase in power (..delta..P), and burnup (Bu) were obtained for pressurized heavy water reactors (PHWRs), boiling water reactors (BWRs), and pressurized water reactors (PWRs). These data sets were evaluated and used as the basis for developing two predictive fuel failure models, a graphical concept called the PCI-OGRAM, and a nonlinear regression based model called PROFIT. The PCI-OGRAM is an extension of the FUELOGRAM developed by AECL. It is based on a critical threshold concept for stress dependent stress corrosion cracking. The PROFITmore » model, developed at Pacific Northwest Laboratory, is the result of applying standard statistical regression methods to the available PCI fuel failure data and an analysis of the environmental and strain rate dependent stress-strain properties of the Zircaloy cladding.« less

A hybrid feature selection and health indicator construction scheme for delay-time-based degradation modelling of rolling element bearings

NASA Astrophysics Data System (ADS)

Zhang, Bin; Deng, Congying; Zhang, Yi

2018-03-01

Rolling element bearings are mechanical components used frequently in most rotating machinery and they are also vulnerable links representing the main source of failures in such systems. Thus, health condition monitoring and fault diagnosis of rolling element bearings have long been studied to improve operational reliability and maintenance efficiency of rotatory machines. Over the past decade, prognosis that enables forewarning of failure and estimation of residual life attracted increasing attention. To accurately and efficiently predict failure of the rolling element bearing, the degradation requires to be well represented and modelled. For this purpose, degradation of the rolling element bearing is analysed with the delay-time-based model in this paper. Also, a hybrid feature selection and health indicator construction scheme is proposed for extraction of the bearing health relevant information from condition monitoring sensor data. Effectiveness of the presented approach is validated through case studies on rolling element bearing run-to-failure experiments.

Both high and low HbA1c predict incident heart failure in type 2 diabetes mellitus.

PubMed

Parry, Helen M; Deshmukh, Harshal; Levin, Daniel; Van Zuydam, Natalie; Elder, Douglas H J; Morris, Andrew D; Struthers, Allan D; Palmer, Colin N A; Doney, Alex S F; Lang, Chim C

2015-03-01

Type 2 diabetes mellitus is an independent risk factor for heart failure development, but the relationship between incident heart failure and antecedent glycemia has not been evaluated. The Genetics of Diabetes Audit and Research in Tayside Study study holds data for 8683 individuals with type 2 diabetes mellitus. Dispensed prescribing, hospital admission data, and echocardiography reports were linked to extract incident heart failure cases from December 1998 to August 2011. All available HbA1c measures until heart failure development or end of study were used to model HbA1c time-dependently. Individuals were observed from study enrolment until heart failure development or end of study. Proportional hazard regression calculated heart failure development risk associated with specific HbA1c ranges accounting for comorbidities associated with heart failure, including blood pressure, body mass index, and coronary artery disease. Seven hundred and one individuals with type 2 diabetes mellitus (8%) developed heart failure during follow up (mean 5.5 years, ±2.8 years). Time-updated analysis with longitudinal HbA1c showed that both HbA1c <6% (hazard ratio =1.60; 95% confidence interval, 1.38-1.86; P value <0.0001) and HbA1c >10% (hazard ratio =1.80; 95% confidence interval, 1.60-2.16; P value <0.0001) were independently associated with the risk of heart failure. Both high and low HbA1c predicted heart failure development in our cohort, forming a U-shaped relationship. © 2015 American Heart Association, Inc.

Capturing strain localization behind a geosynthetic-reinforced soil wall

NASA Astrophysics Data System (ADS)

Lai, Timothy Y.; Borja, Ronaldo I.; Duvernay, Blaise G.; Meehan, Richard L.

2003-04-01

This paper presents the results of finite element (FE) analyses of shear strain localization that occurred in cohesionless soils supported by a geosynthetic-reinforced retaining wall. The innovative aspects of the analyses include capturing of the localized deformation and the accompanying collapse mechanism using a recently developed embedded strong discontinuity model. The case study analysed, reported in previous publications, consists of a 3.5-m tall, full-scale reinforced wall model deforming in plane strain and loaded by surcharge at the surface to failure. Results of the analysis suggest strain localization developing from the toe of the wall and propagating upward to the ground surface, forming a curved failure surface. This is in agreement with a well-documented failure mechanism experienced by the physical wall model showing internal failure surfaces developing behind the wall as a result of the surface loading. Important features of the analyses include mesh sensitivity studies and a comparison of the localization properties predicted by different pre-localization constitutive models, including a family of three-invariant elastoplastic constitutive models appropriate for frictional/dilatant materials. Results of the analysis demonstrate the potential of the enhanced FE method for capturing a collapse mechanism characterized by the presence of a failure, or slip, surface through earthen materials.

Does improvement in self-management skills predict improvement in quality of life and depressive symptoms? A prospective study in patients with heart failure up to one year after self-management education.

PubMed

Musekamp, Gunda; Schuler, Michael; Seekatz, Bettina; Bengel, Jürgen; Faller, Hermann; Meng, Karin

2017-02-15

Heart failure (HF) patient education aims to foster patients' self-management skills. These are assumed to bring about, in turn, improvements in distal outcomes such as quality of life. The purpose of this study was to test the hypothesis that change in self-reported self-management skills observed after participation in self-management education predicts changes in physical and mental quality of life and depressive symptoms up to one year thereafter. The sample comprised 342 patients with chronic heart failure, treated in inpatient rehabilitation clinics, who received a heart failure self-management education program. Latent change modelling was used to analyze relationships between both short-term (during inpatient rehabilitation) and intermediate-term (after six months) changes in self-reported self-management skills and both intermediate-term and long-term (after twelve months) changes in physical and mental quality of life and depressive symptoms. Short-term changes in self-reported self-management skills predicted intermediate-term changes in mental quality of life and long-term changes in physical quality of life. Intermediate-term changes in self-reported self-management skills predicted long-term changes in all outcomes. These findings support the assumption that improvements in self-management skills may foster improvements in distal outcomes.

A Thermodynamically-Based Mesh Objective Work Potential Theory for Predicting Intralaminar Progressive Damage and Failure in Fiber-Reinforced Laminates

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Waas, Anthony M.

2012-01-01

A thermodynamically-based work potential theory for modeling progressive damage and failure in fiber-reinforced laminates is presented. The current, multiple-internal state variable (ISV) formulation, enhanced Schapery theory (EST), utilizes separate ISVs for modeling the effects of damage and failure. Damage is considered to be the effect of any structural changes in a material that manifest as pre-peak non-linearity in the stress versus strain response. Conversely, failure is taken to be the effect of the evolution of any mechanisms that results in post-peak strain softening. It is assumed that matrix microdamage is the dominant damage mechanism in continuous fiber-reinforced polymer matrix laminates, and its evolution is controlled with a single ISV. Three additional ISVs are introduced to account for failure due to mode I transverse cracking, mode II transverse cracking, and mode I axial failure. Typically, failure evolution (i.e., post-peak strain softening) results in pathologically mesh dependent solutions within a finite element method (FEM) setting. Therefore, consistent character element lengths are introduced into the formulation of the evolution of the three failure ISVs. Using the stationarity of the total work potential with respect to each ISV, a set of thermodynamically consistent evolution equations for the ISVs is derived. The theory is implemented into commercial FEM software. Objectivity of total energy dissipated during the failure process, with regards to refinements in the FEM mesh, is demonstrated. The model is also verified against experimental results from two laminated, T800/3900-2 panels containing a central notch and different fiber-orientation stacking sequences. Global load versus displacement, global load versus local strain gage data, and macroscopic failure paths obtained from the models are compared to the experiments.

Micromechanical constitutive model for low-temperature constant strain rate deformation of limestones in the brittle and semi-brittle regime

NASA Astrophysics Data System (ADS)

Nicolas, A.; Fortin, J.; Guéguen, Y.

2017-10-01

Deformation and failure of rocks are important for a better understanding of many crustal geological phenomena such as faulting and compaction. In carbonate rocks among others, low-temperature deformation can either occur with dilatancy or compaction, having implications for porosity changes, failure and petrophysical properties. Hence, a thorough understanding of all the micromechanisms responsible for deformation is of great interest. In this study, a constitutive model for the low-temperature deformation of low-porosity (<20 per cent) carbonate rocks is derived from the micromechanisms identified in previous studies. The micromechanical model is based on (1) brittle crack propagation, (2) a plasticity law (interpreted in terms of dislocation glide without possibility to climb) for porous media with hardening and (3) crack nucleation due to dislocation pile-ups. The model predicts stress-strain relations and the evolution of damage during deformation. The model adequately predicts brittle behaviour at low confining pressures, which switches to a semi-brittle behaviour characterized by inelastic compaction followed by dilatancy at higher confining pressures. Model predictions are compared to experimental results from previous studies and are found to be in close agreement with experimental results. This suggests that microphysical phenomena responsible for the deformation are sufficiently well captured by the model although twinning, recovery and cataclasis are not considered. The porosity range of applicability and limits of the model are discussed.

Fatigue Life Prediction of Fiber-Reinforced Ceramic-Matrix Composites with Different Fiber Preforms at Room and Elevated Temperatures

PubMed Central

Li, Longbiao

2016-01-01

In this paper, the fatigue life of fiber-reinforced ceramic-matrix composites (CMCs) with different fiber preforms, i.e., unidirectional, cross-ply, 2D (two dimensional), 2.5D and 3D CMCs at room and elevated temperatures in air and oxidative environments, has been predicted using the micromechanics approach. An effective coefficient of the fiber volume fraction along the loading direction (ECFL) was introduced to describe the fiber architecture of preforms. The statistical matrix multicracking model and fracture mechanics interface debonding criterion were used to determine the matrix crack spacing and interface debonded length. Under cyclic fatigue loading, the fiber broken fraction was determined by combining the interface wear model and fiber statistical failure model at room temperature, and interface/fiber oxidation model, interface wear model and fiber statistical failure model at elevated temperatures, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfies the Global Load Sharing (GLS) criterion. When the broken fiber fraction approaches the critical value, the composites fatigue fracture. PMID:28773332

Hydraulic limits preceding mortality in a piñon-juniper woodland under experimental drought.

PubMed

Plaut, Jennifer A; Yepez, Enrico A; Hill, Judson; Pangle, Robert; Sperry, John S; Pockman, William T; McDowell, Nate G

2012-09-01

Drought-related tree mortality occurs globally and may increase in the future, but we lack sufficient mechanistic understanding to accurately predict it. Here we present the first field assessment of the physiological mechanisms leading to mortality in an ecosystem-scale rainfall manipulation of a piñon-juniper (Pinus edulis-Juniperus monosperma) woodland. We measured transpiration (E) and modelled the transpiration rate initiating hydraulic failure (E(crit) ). We predicted that isohydric piñon would experience mortality after prolonged periods of severely limited gas exchange as required to avoid hydraulic failure; anisohydric juniper would also avoid hydraulic failure, but sustain gas exchange due to its greater cavitation resistance. After 1 year of treatment, 67% of droughted mature piñon died with concomitant infestation by bark beetles (Ips confusus) and bluestain fungus (Ophiostoma spp.); no mortality occurred in juniper or in control piñon. As predicted, both species avoided hydraulic failure, but safety margins from E(crit) were much smaller in piñon, especially droughted piñon, which also experienced chronically low hydraulic conductance. The defining characteristic of trees that died was a 7 month period of near-zero gas exchange, versus 2 months for surviving piñon. Hydraulic limits to gas exchange, not hydraulic failure per se, promoted drought-related mortality in piñon pine. © 2012 Blackwell Publishing Ltd.

Fatigue lifetime prediction of a reduced-diameter dental implant system: Numerical and experimental study.

PubMed

Duan, Yuanyuan; Gonzalez, Jorge A; Kulkarni, Pratim A; Nagy, William W; Griggs, Jason A

2018-06-16

To validate the fatigue lifetime of a reduced-diameter dental implant system predicted by three-dimensional finite element analysis (FEA) by testing physical implant specimens using an accelerated lifetime testing (ALT) strategy with the apparatus specified by ISO 14801. A commercially-available reduced-diameter titanium dental implant system (Straumann Standard Plus NN) was digitized using a micro-CT scanner. Axial slices were processed using an interactive medical image processing software (Mimics) to create 3D models. FEA analysis was performed in ABAQUS, and fatigue lifetime was predicted using fe-safe ® software. The same implant specimens (n=15) were tested at a frequency of 2Hz on load frames using apparatus specified by ISO 14801 and ALT. Multiple step-stress load profiles with various aggressiveness were used to improve testing efficiency. Fatigue lifetime statistics of physical specimens were estimated in a reliability analysis software (ALTA PRO). Fractured specimens were examined using SEM with fractographic technique to determine the failure mode. FEA predicted lifetime was within the 95% confidence interval of lifetime estimated by experimental results, which suggested that FEA prediction was accurate for this implant system. The highest probability of failure was located at the root of the implant body screw thread adjacent to the simulated bone level, which also agreed with the failure origin in physical specimens. Fatigue lifetime predictions based on finite element modeling could yield similar results in lieu of physical testing, allowing the use of virtual testing in the early stages of future research projects on implant fatigue. Copyright © 2018 The Academy of Dental Materials. Published by Elsevier Inc. All rights reserved.

Plasma Neutrophil Gelatinase-Associated Lipocalin and Predicting Clinically Relevant Worsening Renal Function in Acute Heart Failure

PubMed Central

Damman, Kevin; A.E. Valente, Mattia; J. van Veldhuisen, Dirk; G.F. Cleland, John; M. O’Connor, Christopher; Metra, Marco; Ponikowski, Piotr; Cotter, Gad; Davison, Beth; M. Givertz, Michael; M. Bloomfield, Daniel; L. Hillege, Hans; A. Voors, Adriaan

2017-01-01

The aim of this study was to evaluate the ability of Neutrophil Gelatinase-Associated Lipocalin (NGAL) to predict clinically relevant worsening renal function (WRF) in acute heart failure (AHF). Plasma NGAL and serum creatinine changes during the first 4 days of admission were investigated in 1447 patients hospitalized for AHF and enrolled in the Placebo-Controlled Randomized Study of the Selective A1Adenosine Receptor Antagonist Rolofylline for Patients Hospitalized with Acute Decompensated Heart Failure and Volume Overload to Assess Treatment Effect on Congestion and Renal Function (PROTECT) study. WRF was defined as serum creatinine rise ≥ 0.3 mg/dL through day 4. Biomarker patterns were described using linear mixed models. WRF developed in 325 patients (22%). Plasma NGAL did not rise earlier than creatinine in patients with WRF. After multivariable adjustment, baseline plasma NGAL, but not creatinine, predicted WRF. AUCs for WRF prediction were modest (<0.60) for all models. NGAL did not independently predict death or rehospitalization (p = n.s.). Patients with WRF and high baseline plasma NGAL had a greater risk of death, and renal or cardiovascular rehospitalization by 60 days than patients with WRF and a low baseline plasma NGAL (p for interaction = 0.024). A rise in plasma NGAL after baseline was associated with a worse outcome in patients with WRF, but not in patients without WRF (p = 0.007). On the basis of these results, plasma NGAL does not provide additional, clinically relevant information about the occurrence of WRF in patients with AHF. PMID:28698481

Plasma Neutrophil Gelatinase-Associated Lipocalin and Predicting Clinically Relevant Worsening Renal Function in Acute Heart Failure.

PubMed

Damman, Kevin; Valente, Mattia A E; van Veldhuisen, Dirk J; Cleland, John G F; O'Connor, Christopher M; Metra, Marco; Ponikowski, Piotr; Cotter, Gad; Davison, Beth; Givertz, Michael M; Bloomfield, Daniel M; Hillege, Hans L; Voors, Adriaan A

2017-07-08

The aim of this study was to evaluate the ability of Neutrophil Gelatinase-Associated Lipocalin (NGAL) to predict clinically relevant worsening renal function (WRF) in acute heart failure (AHF). Plasma NGAL and serum creatinine changes during the first 4 days of admission were investigated in 1447 patients hospitalized for AHF and enrolled in the Placebo-Controlled Randomized Study of the Selective A₁Adenosine Receptor Antagonist Rolofylline for Patients Hospitalized with Acute Decompensated Heart Failure and Volume Overload to Assess Treatment Effect on Congestion and Renal Function (PROTECT) study. WRF was defined as serum creatinine rise ≥ 0.3 mg/dL through day 4. Biomarker patterns were described using linear mixed models. WRF developed in 325 patients (22%). Plasma NGAL did not rise earlier than creatinine in patients with WRF. After multivariable adjustment, baseline plasma NGAL, but not creatinine, predicted WRF. AUCs for WRF prediction were modest (<0.60) for all models. NGAL did not independently predict death or rehospitalization ( p = n.s.). Patients with WRF and high baseline plasma NGAL had a greater risk of death, and renal or cardiovascular rehospitalization by 60 days than patients with WRF and a low baseline plasma NGAL (p for interaction = 0.024). A rise in plasma NGAL after baseline was associated with a worse outcome in patients with WRF, but not in patients without WRF ( p = 0.007). On the basis of these results, plasma NGAL does not provide additional, clinically relevant information about the occurrence of WRF in patients with AHF.

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

NASA Astrophysics Data System (ADS)

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.

TEAM-HF Cost-Effectiveness Model: A Web-Based Program Designed to Evaluate the Cost-Effectiveness of Disease Management Programs in Heart Failure

PubMed Central

Reed, Shelby D.; Neilson, Matthew P.; Gardner, Matthew; Li, Yanhong; Briggs, Andrew H.; Polsky, Daniel E.; Graham, Felicia L.; Bowers, Margaret T.; Paul, Sara C.; Granger, Bradi B.; Schulman, Kevin A.; Whellan, David J.; Riegel, Barbara; Levy, Wayne C.

2015-01-01

Background Heart failure disease management programs can influence medical resource use and quality-adjusted survival. Because projecting long-term costs and survival is challenging, a consistent and valid approach to extrapolating short-term outcomes would be valuable. Methods We developed the Tools for Economic Analysis of Patient Management Interventions in Heart Failure (TEAM-HF) Cost-Effectiveness Model, a Web-based simulation tool designed to integrate data on demographic, clinical, and laboratory characteristics, use of evidence-based medications, and costs to generate predicted outcomes. Survival projections are based on a modified Seattle Heart Failure Model (SHFM). Projections of resource use and quality of life are modeled using relationships with time-varying SHFM scores. The model can be used to evaluate parallel-group and single-cohort designs and hypothetical programs. Simulations consist of 10,000 pairs of virtual cohorts used to generate estimates of resource use, costs, survival, and incremental cost-effectiveness ratios from user inputs. Results The model demonstrated acceptable internal and external validity in replicating resource use, costs, and survival estimates from 3 clinical trials. Simulations to evaluate the cost-effectiveness of heart failure disease management programs across 3 scenarios demonstrate how the model can be used to design a program in which short-term improvements in functioning and use of evidence-based treatments are sufficient to demonstrate good long-term value to the health care system. Conclusion The TEAM-HF Cost-Effectiveness Model provides researchers and providers with a tool for conducting long-term cost-effectiveness analyses of disease management programs in heart failure. PMID:26542504

Multiscale modeling of ductile failure in metallic alloys

NASA Astrophysics Data System (ADS)

Pardoen, Thomas; Scheyvaerts, Florence; Simar, Aude; Tekoğlu, Cihan; Onck, Patrick R.

2010-04-01

Micromechanical models for ductile failure have been developed in the 1970s and 1980s essentially to address cracking in structural applications and complement the fracture mechanics approach. Later, this approach has become attractive for physical metallurgists interested by the prediction of failure during forming operations and as a guide for the design of more ductile and/or high-toughness microstructures. Nowadays, a realistic treatment of damage evolution in complex metallic microstructures is becoming feasible when sufficiently sophisticated constitutive laws are used within the context of a multilevel modelling strategy. The current understanding and the state of the art models for the nucleation, growth and coalescence of voids are reviewed with a focus on the underlying physics. Considerations are made about the introduction of the different length scales associated with the microstructure and damage process. Two applications of the methodology are then described to illustrate the potential of the current models. The first application concerns the competition between intergranular and transgranular ductile fracture in aluminum alloys involving soft precipitate free zones along the grain boundaries. The second application concerns the modeling of ductile failure in friction stir welded joints, a problem which also involves soft and hard zones, albeit at a larger scale.

A mathematical model for predicting the life of polymer electrolyte fuel cell membranes subjected to hydration cycling

NASA Astrophysics Data System (ADS)

Burlatsky, S. F.; Gummalla, M.; O'Neill, J.; Atrazhev, V. V.; Varyukhin, A. N.; Dmitriev, D. V.; Erikhman, N. S.

2012-10-01

Under typical Polymer Electrolyte Membrane Fuel Cell (PEMFC) fuel cell operating conditions, part of the membrane electrode assembly is subjected to humidity cycling due to variation of inlet gas RH and/or flow rate. Cyclic membrane hydration/dehydration would cause cyclic swelling/shrinking of the unconstrained membrane. In a constrained membrane, it causes cyclic stress resulting in mechanical failure in the area adjacent to the gas inlet. A mathematical modeling framework for prediction of the lifetime of a PEMFC membrane subjected to hydration cycling is developed in this paper. The model predicts membrane lifetime as a function of RH cycling amplitude and membrane mechanical properties. The modeling framework consists of three model components: a fuel cell RH distribution model, a hydration/dehydration induced stress model that predicts stress distribution in the membrane, and a damage accrual model that predicts membrane lifetime. Short descriptions of the model components along with overall framework are presented in the paper. The model was used for lifetime prediction of a GORE-SELECT membrane.

Space Shuttle Main Engine structural analysis and data reduction/evaluation. Volume 1: Aft Skirt analysis

NASA Technical Reports Server (NTRS)

Berry, David M.; Stansberry, Mark

1989-01-01

Using the ANSYS finite element program, a global model of the aft skirt and a detailed nonlinear model of the failure region was made. The analysis confirmed the area of failure in both STA-2B and STA-3 tests as the forging heat affected zone (HAZ) at the aft ring centerline. The highest hoop strain in the HAZ occurs in this area. However, the analysis does not predict failure as defined by ultimate elongation of the material equal to 3.5 percent total strain. The analysis correlates well with the strain gage data from both the Wyle influence test of the original design aft sjirt and the STA-3 test of the redesigned aft skirt. it is suggested that the sensitivity of the failure area material strength and stress/strain state to material properties and therefore to small manufacturing or processing variables is the most likely cause of failure below the expected material ultimate properties.

Critical analysis of 3-D organoid in vitro cell culture models for high-throughput drug candidate toxicity assessments.

PubMed

Astashkina, Anna; Grainger, David W

2014-04-01

Drug failure due to toxicity indicators remains among the primary reasons for staggering drug attrition rates during clinical studies and post-marketing surveillance. Broader validation and use of next-generation 3-D improved cell culture models are expected to improve predictive power and effectiveness of drug toxicological predictions. However, after decades of promising research significant gaps remain in our collective ability to extract quality human toxicity information from in vitro data using 3-D cell and tissue models. Issues, challenges and future directions for the field to improve drug assay predictive power and reliability of 3-D models are reviewed. Copyright © 2014 Elsevier B.V. All rights reserved.

Progressive Failure Analysis Methodology for Laminated Composite Structures

NASA Technical Reports Server (NTRS)

Sleight, David W.

1999-01-01

A progressive failure analysis method has been developed for predicting the failure of laminated composite structures under geometrically nonlinear deformations. The progressive failure analysis uses C(exp 1) shell elements based on classical lamination theory to calculate the in-plane stresses. Several failure criteria, including the maximum strain criterion, Hashin's criterion, and Christensen's criterion, are used to predict the failure mechanisms and several options are available to degrade the material properties after failures. The progressive failure analysis method is implemented in the COMET finite element analysis code and can predict the damage and response of laminated composite structures from initial loading to final failure. The different failure criteria and material degradation methods are compared and assessed by performing analyses of several laminated composite structures. Results from the progressive failure method indicate good correlation with the existing test data except in structural applications where interlaminar stresses are important which may cause failure mechanisms such as debonding or delaminations.