Two-IMU FDI performance of the sequential probability ratio test during shuttle entry

NASA Technical Reports Server (NTRS)

Rich, T. M.

1976-01-01

Performance data for the sequential probability ratio test (SPRT) during shuttle entry are presented. Current modeling constants and failure thresholds are included for the full mission 3B from entry through landing trajectory. Minimum 100 percent detection/isolation failure levels and a discussion of the effects of failure direction are presented. Finally, a limited comparison of failures introduced at trajectory initiation shows that the SPRT algorithm performs slightly worse than the data tracking test.

Probabilistic modelling of overflow, surcharge and flooding in urban drainage using the first-order reliability method and parameterization of local rain series.

PubMed

Thorndahl, S; Willems, P

2008-01-01

Failure of urban drainage systems may occur due to surcharge or flooding at specific manholes in the system, or due to overflows from combined sewer systems to receiving waters. To quantify the probability or return period of failure, standard approaches make use of the simulation of design storms or long historical rainfall series in a hydrodynamic model of the urban drainage system. In this paper, an alternative probabilistic method is investigated: the first-order reliability method (FORM). To apply this method, a long rainfall time series was divided in rainstorms (rain events), and each rainstorm conceptualized to a synthetic rainfall hyetograph by a Gaussian shape with the parameters rainstorm depth, duration and peak intensity. Probability distributions were calibrated for these three parameters and used on the basis of the failure probability estimation, together with a hydrodynamic simulation model to determine the failure conditions for each set of parameters. The method takes into account the uncertainties involved in the rainstorm parameterization. Comparison is made between the failure probability results of the FORM method, the standard method using long-term simulations and alternative methods based on random sampling (Monte Carlo direct sampling and importance sampling). It is concluded that without crucial influence on the modelling accuracy, the FORM is very applicable as an alternative to traditional long-term simulations of urban drainage systems.

A risk assessment method for multi-site damage

NASA Astrophysics Data System (ADS)

Millwater, Harry Russell, Jr.

This research focused on developing probabilistic methods suitable for computing small probabilities of failure, e.g., 10sp{-6}, of structures subject to multi-site damage (MSD). MSD is defined as the simultaneous development of fatigue cracks at multiple sites in the same structural element such that the fatigue cracks may coalesce to form one large crack. MSD is modeled as an array of collinear cracks with random initial crack lengths with the centers of the initial cracks spaced uniformly apart. The data used was chosen to be representative of aluminum structures. The structure is considered failed whenever any two adjacent cracks link up. A fatigue computer model is developed that can accurately and efficiently grow a collinear array of arbitrary length cracks from initial size until failure. An algorithm is developed to compute the stress intensity factors of all cracks considering all interaction effects. The probability of failure of two to 100 cracks is studied. Lower bounds on the probability of failure are developed based upon the probability of the largest crack exceeding a critical crack size. The critical crack size is based on the initial crack size that will grow across the ligament when the neighboring crack has zero length. The probability is evaluated using extreme value theory. An upper bound is based on the probability of the maximum sum of initial cracks being greater than a critical crack size. A weakest link sampling approach is developed that can accurately and efficiently compute small probabilities of failure. This methodology is based on predicting the weakest link, i.e., the two cracks to link up first, for a realization of initial crack sizes, and computing the cycles-to-failure using these two cracks. Criteria to determine the weakest link are discussed. Probability results using the weakest link sampling method are compared to Monte Carlo-based benchmark results. The results indicate that very small probabilities can be computed accurately in a few minutes using a Hewlett-Packard workstation.

Estimation of submarine mass failure probability from a sequence of deposits with age dates

USGS Publications Warehouse

Geist, Eric L.; Chaytor, Jason D.; Parsons, Thomas E.; ten Brink, Uri S.

2013-01-01

The empirical probability of submarine mass failure is quantified from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the first and after the last event. The likelihood techniques are evaluated using Akaike’s Information Criterion (AIC) and Akaike’s Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio- and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasiperiodically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.

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.

Competing risk models in reliability systems, an exponential distribution model with Bayesian analysis approach

NASA Astrophysics Data System (ADS)

Iskandar, I.

2018-03-01

The exponential distribution is the most widely used reliability analysis. This distribution is very suitable for representing the lengths of life of many cases and is available in a simple statistical form. The characteristic of this distribution is a constant hazard rate. The exponential distribution is the lower rank of the Weibull distributions. In this paper our effort is to introduce the basic notions that constitute an exponential competing risks model in reliability analysis using Bayesian analysis approach and presenting their analytic methods. The cases are limited to the models with independent causes of failure. A non-informative prior distribution is used in our analysis. This model describes the likelihood function and follows with the description of the posterior function and the estimations of the point, interval, hazard function, and reliability. The net probability of failure if only one specific risk is present, crude probability of failure due to a specific risk in the presence of other causes, and partial crude probabilities are also included.

Reliability Analysis of Systems Subject to First-Passage Failure

NASA Technical Reports Server (NTRS)

Lutes, Loren D.; Sarkani, Shahram

2009-01-01

An obvious goal of reliability analysis is the avoidance of system failure. However, it is generally recognized that it is often not feasible to design a practical or useful system for which failure is impossible. Thus it is necessary to use techniques that estimate the likelihood of failure based on modeling the uncertainty about such items as the demands on and capacities of various elements in the system. This usually involves the use of probability theory, and a design is considered acceptable if it has a sufficiently small probability of failure. This report contains findings of analyses of systems subject to first-passage failure.

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.

Evolution of thermal stress and failure probability during reduction and re-oxidation of solid oxide fuel cell

NASA Astrophysics Data System (ADS)

Wang, Yu; Jiang, Wenchun; Luo, Yun; Zhang, Yucai; Tu, Shan-Tung

2017-12-01

The reduction and re-oxidation of anode have significant effects on the integrity of the solid oxide fuel cell (SOFC) sealed by the glass-ceramic (GC). The mechanical failure is mainly controlled by the stress distribution. Therefore, a three dimensional model of SOFC is established to investigate the stress evolution during the reduction and re-oxidation by finite element method (FEM) in this paper, and the failure probability is calculated using the Weibull method. The results demonstrate that the reduction of anode can decrease the thermal stresses and reduce the failure probability due to the volumetric contraction and porosity increasing. The re-oxidation can result in a remarkable increase of the thermal stresses, and the failure probabilities of anode, cathode, electrolyte and GC all increase to 1, which is mainly due to the large linear strain rather than the porosity decreasing. The cathode and electrolyte fail as soon as the linear strains are about 0.03% and 0.07%. Therefore, the re-oxidation should be controlled to ensure the integrity, and a lower re-oxidation temperature can decrease the stress and failure probability.

Game-Theoretic strategies for systems of components using product-form utilities

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

Rao, Nageswara S; Ma, Cheng-Yu; Hausken, K.

Many critical infrastructures are composed of multiple systems of components which are correlated so that disruptions to one may propagate to others. We consider such infrastructures with correlations characterized in two ways: (i) an aggregate failure correlation function specifies the conditional failure probability of the infrastructure given the failure of an individual system, and (ii) a pairwise correlation function between two systems specifies the failure probability of one system given the failure of the other. We formulate a game for ensuring the resilience of the infrastructure, wherein the utility functions of the provider and attacker are products of an infrastructuremore » survival probability term and a cost term, both expressed in terms of the numbers of system components attacked and reinforced. The survival probabilities of individual systems satisfy first-order differential conditions that lead to simple Nash Equilibrium conditions. We then derive sensitivity functions that highlight the dependence of infrastructure resilience on the cost terms, correlation functions, and individual system survival probabilities. We apply these results to simplified models of distributed cloud computing and energy grid infrastructures.« less

Re‐estimated effects of deep episodic slip on the occurrence and probability of great earthquakes in Cascadia

USGS Publications Warehouse

Beeler, Nicholas M.; Roeloffs, Evelyn A.; McCausland, Wendy

2013-01-01

Mazzotti and Adams (2004) estimated that rapid deep slip during typically two week long episodes beneath northern Washington and southern British Columbia increases the probability of a great Cascadia earthquake by 30–100 times relative to the probability during the ∼58 weeks between slip events. Because the corresponding absolute probability remains very low at ∼0.03% per week, their conclusion is that though it is more likely that a great earthquake will occur during a rapid slip event than during other times, a great earthquake is unlikely to occur during any particular rapid slip event. This previous estimate used a failure model in which great earthquakes initiate instantaneously at a stress threshold. We refine the estimate, assuming a delayed failure model that is based on laboratory‐observed earthquake initiation. Laboratory tests show that failure of intact rock in shear and the onset of rapid slip on pre‐existing faults do not occur at a threshold stress. Instead, slip onset is gradual and shows a damped response to stress and loading rate changes. The characteristic time of failure depends on loading rate and effective normal stress. Using this model, the probability enhancement during the period of rapid slip in Cascadia is negligible (<10%) for effective normal stresses of 10 MPa or more and only increases by 1.5 times for an effective normal stress of 1 MPa. We present arguments that the hypocentral effective normal stress exceeds 1 MPa. In addition, the probability enhancement due to rapid slip extends into the interevent period. With this delayed failure model for effective normal stresses greater than or equal to 50 kPa, it is more likely that a great earthquake will occur between the periods of rapid deep slip than during them. Our conclusion is that great earthquake occurrence is not significantly enhanced by episodic deep slip events.

A Framework for Final Drive Simultaneous Failure Diagnosis Based on Fuzzy Entropy and Sparse Bayesian Extreme Learning Machine

PubMed Central

Ye, Qing; Pan, Hao; Liu, Changhua

2015-01-01

This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F 1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach. PMID:25722717

Electromigration model for the prediction of lifetime based on the failure unit statistics in aluminum metallization

NASA Astrophysics Data System (ADS)

Park, Jong Ho; Ahn, Byung Tae

2003-01-01

A failure model for electromigration based on the "failure unit model" was presented for the prediction of lifetime in metal lines.The failure unit model, which consists of failure units in parallel and series, can predict both the median time to failure (MTTF) and the deviation in the time to failure (DTTF) in Al metal lines. The model can describe them only qualitatively. In our model, both the probability function of the failure unit in single grain segments and polygrain segments are considered instead of in polygrain segments alone. Based on our model, we calculated MTTF, DTTF, and activation energy for different median grain sizes, grain size distributions, linewidths, line lengths, current densities, and temperatures. Comparisons between our results and published experimental data showed good agreements and our model could explain the previously unexplained phenomena. Our advanced failure unit model might be further applied to other electromigration characteristics of metal lines.

Time-dependent landslide probability mapping

USGS Publications Warehouse

Campbell, Russell H.; Bernknopf, Richard L.; ,

1993-01-01

Case studies where time of failure is known for rainfall-triggered debris flows can be used to estimate the parameters of a hazard model in which the probability of failure is a function of time. As an example, a time-dependent function for the conditional probability of a soil slip is estimated from independent variables representing hillside morphology, approximations of material properties, and the duration and rate of rainfall. If probabilities are calculated in a GIS (geomorphic information system ) environment, the spatial distribution of the result for any given hour can be displayed on a map. Although the probability levels in this example are uncalibrated, the method offers a potential for evaluating different physical models and different earth-science variables by comparing the map distribution of predicted probabilities with inventory maps for different areas and different storms. If linked with spatial and temporal socio-economic variables, this method could be used for short-term risk assessment.

A physically-based earthquake recurrence model for estimation of long-term earthquake probabilities

USGS Publications Warehouse

Ellsworth, William L.; Matthews, Mark V.; Nadeau, Robert M.; Nishenko, Stuart P.; Reasenberg, Paul A.; Simpson, Robert W.

1999-01-01

A physically-motivated model for earthquake recurrence based on the Brownian relaxation oscillator is introduced. The renewal process defining this point process model can be described by the steady rise of a state variable from the ground state to failure threshold as modulated by Brownian motion. Failure times in this model follow the Brownian passage time (BPT) distribution, which is specified by the mean time to failure, μ, and the aperiodicity of the mean, α (equivalent to the familiar coefficient of variation). Analysis of 37 series of recurrent earthquakes, M -0.7 to 9.2, suggests a provisional generic value of α = 0.5. For this value of α, the hazard function (instantaneous failure rate of survivors) exceeds the mean rate for times > μ⁄2, and is ~ ~ 2 ⁄ μ for all times > μ. Application of this model to the next M 6 earthquake on the San Andreas fault at Parkfield, California suggests that the annual probability of the earthquake is between 1:10 and 1:13.

A methodology for estimating risks associated with landslides of contaminated soil into rivers.

PubMed

Göransson, Gunnel; Norrman, Jenny; Larson, Magnus; Alén, Claes; Rosén, Lars

2014-02-15

Urban areas adjacent to surface water are exposed to soil movements such as erosion and slope failures (landslides). A landslide is a potential mechanism for mobilisation and spreading of pollutants. This mechanism is in general not included in environmental risk assessments for contaminated sites, and the consequences associated with contamination in the soil are typically not considered in landslide risk assessments. This study suggests a methodology to estimate the environmental risks associated with landslides in contaminated sites adjacent to rivers. The methodology is probabilistic and allows for datasets with large uncertainties and the use of expert judgements, providing quantitative estimates of probabilities for defined failures. The approach is illustrated by a case study along the river Göta Älv, Sweden, where failures are defined and probabilities for those failures are estimated. Failures are defined from a pollution perspective and in terms of exceeding environmental quality standards (EQSs) and acceptable contaminant loads. Models are then suggested to estimate probabilities of these failures. A landslide analysis is carried out to assess landslide probabilities based on data from a recent landslide risk classification study along the river Göta Älv. The suggested methodology is meant to be a supplement to either landslide risk assessment (LRA) or environmental risk assessment (ERA), providing quantitative estimates of the risks associated with landslide in contaminated sites. The proposed methodology can also act as a basis for communication and discussion, thereby contributing to intersectoral management solutions. From the case study it was found that the defined failures are governed primarily by the probability of a landslide occurring. The overall probabilities for failure are low; however, if a landslide occurs the probabilities of exceeding EQS are high and the probability of having at least a 10% increase in the contamination load within one year is also high. Copyright © 2013 Elsevier B.V. All rights reserved.

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

Uncertainty Analysis via Failure Domain Characterization: Polynomial Requirement Functions

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Munoz, Cesar A.; Narkawicz, Anthony J.; Kenny, Sean P.; Giesy, Daniel P.

2011-01-01

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. A Bernstein expansion approach is used to size hyper-rectangular subsets while a sum of squares programming approach is used to size quasi-ellipsoidal subsets. These methods are applicable to requirement functions whose functional dependency on the uncertainty is a known polynomial. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the uncertainty model assumed (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

Uncertainty Analysis via Failure Domain Characterization: Unrestricted Requirement Functions

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2011-01-01

This paper proposes an uncertainty analysis framework based on the characterization of the uncertain parameter space. This characterization enables the identification of worst-case uncertainty combinations and the approximation of the failure and safe domains with a high level of accuracy. Because these approximations are comprised of subsets of readily computable probability, they enable the calculation of arbitrarily tight upper and lower bounds to the failure probability. The methods developed herein, which are based on nonlinear constrained optimization, are applicable to requirement functions whose functional dependency on the uncertainty is arbitrary and whose explicit form may even be unknown. Some of the most prominent features of the methodology are the substantial desensitization of the calculations from the assumed uncertainty model (i.e., the probability distribution describing the uncertainty) as well as the accommodation for changes in such a model with a practically insignificant amount of computational effort.

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 detection system risk reduction assessment

NASA Technical Reports Server (NTRS)

Aguilar, Robert B. (Inventor); Huang, Zhaofeng (Inventor)

2012-01-01

A process includes determining a probability of a failure mode of a system being analyzed reaching a failure limit as a function of time to failure limit, determining a probability of a mitigation of the failure mode as a function of a time to failure limit, and quantifying a risk reduction based on the probability of the failure mode reaching the failure limit and the probability of the mitigation.

Mechanistic Considerations Used in the Development of the PROFIT PCI Failure Model

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

Pankaskie, P. J.

A fuel Pellet-Zircaloy Cladding (thermo-mechanical-chemical) Interactions (PC!) failure model for estimating the probability of failure in !ransient increases in power (PROFIT) was developed. PROFIT is based on 1) standard statistical methods applied to available PC! fuel failure data and 2) a mechanistic analysis of the environmental and strain-rate-dependent stress versus strain characteristics of Zircaloy cladding. The statistical analysis of fuel failures attributable to PCI suggested that parameters in addition to power, transient increase in power, and burnup are needed to define PCI fuel failures in terms of probability estimates with known confidence limits. The PROFIT model, therefore, introduces an environmentalmore » and strain-rate dependent strain energy absorption to failure (SEAF) concept to account for the stress versus strain anomalies attributable to interstitial-disloction interaction effects in the Zircaloy cladding. Assuming that the power ramping rate is the operating corollary of strain-rate in the Zircaloy cladding, then the variables of first order importance in the PCI fuel failure phenomenon are postulated to be: 1. pre-transient fuel rod power, P{sub I}, 2. transient increase in fuel rod power, {Delta}P, 3. fuel burnup, Bu, and 4. the constitutive material property of the Zircaloy cladding, SEAF.« less

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.

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

Landslide Probability Assessment by the Derived Distributions Technique

NASA Astrophysics Data System (ADS)

Muñoz, E.; Ochoa, A.; Martínez, H.

2012-12-01

Landslides are potentially disastrous events that bring along human and economic losses; especially in cities where an accelerated and unorganized growth leads to settlements on steep and potentially unstable areas. Among the main causes of landslides are geological, geomorphological, geotechnical, climatological, hydrological conditions and anthropic intervention. This paper studies landslides detonated by rain, commonly known as "soil-slip", which characterize by having a superficial failure surface (Typically between 1 and 1.5 m deep) parallel to the slope face and being triggered by intense and/or sustained periods of rain. This type of landslides is caused by changes on the pore pressure produced by a decrease in the suction when a humid front enters, as a consequence of the infiltration initiated by rain and ruled by the hydraulic characteristics of the soil. Failure occurs when this front reaches a critical depth and the shear strength of the soil in not enough to guarantee the stability of the mass. Critical rainfall thresholds in combination with a slope stability model are widely used for assessing landslide probability. In this paper we present a model for the estimation of the occurrence of landslides based on the derived distributions technique. Since the works of Eagleson in the 1970s the derived distributions technique has been widely used in hydrology to estimate the probability of occurrence of extreme flows. The model estimates the probability density function (pdf) of the Factor of Safety (FOS) from the statistical behavior of the rainfall process and some slope parameters. The stochastic character of the rainfall is transformed by means of a deterministic failure model into FOS pdf. Exceedance probability and return period estimation is then straightforward. The rainfall process is modeled as a Rectangular Pulses Poisson Process (RPPP) with independent exponential pdf for mean intensity and duration of the storms. The Philip infiltration model is used along with the soil characteristic curve (suction vs. moisture) and the Mohr-Coulomb failure criteria in order to calculate the FOS of the slope. Data from two slopes located on steep tropical regions of the cities of Medellín (Colombia) and Rio de Janeiro (Brazil) where used to verify the model's performance. The results indicated significant differences between the obtained FOS values and the behavior observed on the field. The model shows relatively high values of FOS that do not reflect the instability of the analyzed slopes. For the two cases studied, the application of a more simple reliability concept (as the Probability of Failure - PR and Reliability Index - β), instead of a FOS could lead to more realistic results.

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.

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.

Importance Sampling in the Evaluation and Optimization of Buffered Failure Probability

DTIC Science & Technology

2015-07-01

12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12 Vancouver, Canada, July 12-15, 2015...Importance Sampling in the Evaluation and Optimization of Buffered Failure Probability Marwan M. Harajli Graduate Student, Dept. of Civil and Environ...criterion is usually the failure probability . In this paper, we examine the buffered failure probability as an attractive alternative to the failure

On defense strategies for system of systems using aggregated correlations

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

Rao, Nageswara S.; Imam, Neena; Ma, Chris Y. T.

2017-04-01

We consider a System of Systems (SoS) wherein each system Si, i = 1; 2; ... ;N, is composed of discrete cyber and physical components which can be attacked and reinforced. We characterize the disruptions using aggregate failure correlation functions given by the conditional failure probability of SoS given the failure of an individual system. We formulate the problem of ensuring the survival of SoS as a game between an attacker and a provider, each with a utility function composed of asurvival probability term and a cost term, both expressed in terms of the number of components attacked and reinforced.more » The survival probabilities of systems satisfy simple product-form, first-order differential conditions, which simplify the Nash Equilibrium (NE) conditions. We derive the sensitivity functions that highlight the dependence of SoS survival probability at NE on cost terms, correlation functions, and individual system survival probabilities.We apply these results to a simplified model of distributed cloud computing infrastructure.« less

Specifying design conservatism: Worst case versus probabilistic analysis

NASA Technical Reports Server (NTRS)

Miles, Ralph F., Jr.

1993-01-01

Design conservatism is the difference between specified and required performance, and is introduced when uncertainty is present. The classical approach of worst-case analysis for specifying design conservatism is presented, along with the modern approach of probabilistic analysis. The appropriate degree of design conservatism is a tradeoff between the required resources and the probability and consequences of a failure. A probabilistic analysis properly models this tradeoff, while a worst-case analysis reveals nothing about the probability of failure, and can significantly overstate the consequences of failure. Two aerospace examples will be presented that illustrate problems that can arise with a worst-case analysis.

A proportional hazards regression model for the subdistribution with right-censored and left-truncated competing risks data

PubMed Central

Zhang, Xu; Zhang, Mei-Jie; Fine, Jason

2012-01-01

With competing risks failure time data, one often needs to assess the covariate effects on the cumulative incidence probabilities. Fine and Gray proposed a proportional hazards regression model to directly model the subdistribution of a competing risk. They developed the estimating procedure for right-censored competing risks data, based on the inverse probability of censoring weighting. Right-censored and left-truncated competing risks data sometimes occur in biomedical researches. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with right-censored and left-truncated data. We adopt a new weighting technique to estimate the parameters in this model. We have derived the large sample properties of the proposed estimators. To illustrate the application of the new method, we analyze the failure time data for children with acute leukemia. In this example, the failure times for children who had bone marrow transplants were left truncated. PMID:21557288

A simplified fragility analysis of fan type cable stayed bridges

NASA Astrophysics Data System (ADS)

Khan, R. A.; Datta, T. K.; Ahmad, S.

2005-06-01

A simplified fragility analysis of fan type cable stayed bridges using Probabilistic Risk Analysis (PRA) procedure is presented for determining their failure probability under random ground motion. Seismic input to the bridge support is considered to be a risk consistent response spectrum which is obtained from a separate analysis. For the response analysis, the bridge deck is modeles as a beam supported on spring at different points. The stiffnesses of the springs are determined by a separate 2D static analysis of cable-tower-deck system. The analysis provides a coupled stiffness matrix for the spring system. A continuum method of analysis using dynamic stiffness is used to determine the dynamic properties of the bridges. The response of the bridge deck is obtained by the response spectrum method of analysis as applied to multidegree of freedom system which duly takes into account the quasi-static component of bridge deck vibration. The fragility analysis includes uncertainties arising due to the variation in ground motion, material property, modeling, method of analysis, ductility factor and damage concentration effect. Probability of failure of the bridge deck is determined by the First Order Second Moment (FOSM) method of reliability. A three span double plane symmetrical fan type cable stayed bridge of total span 689 m, is used as an illustrative example. The fragility curves for the bridge deck failure are obtained under a number of parametric variations. Some of the important conclusions of the study indicate that (i) not only vertical component but also the horizontal component of ground motion has considerable effect on the probability of failure; (ii) ground motion with no time lag between support excitations provides a smaller probability of failure as compared to ground motion with very large time lag between support excitation; and (iii) probability of failure may considerably increase soft soil condition.

A cost simulation for mammography examinations taking into account equipment failures and resource utilization characteristics.

PubMed

Coelli, Fernando C; Almeida, Renan M V R; Pereira, Wagner C A

2010-12-01

This work develops a cost analysis estimation for a mammography clinic, taking into account resource utilization and equipment failure rates. Two standard clinic models were simulated, the first with one mammography equipment, two technicians and one doctor, and the second (based on an actually functioning clinic) with two equipments, three technicians and one doctor. Cost data and model parameters were obtained by direct measurements, literature reviews and other hospital data. A discrete-event simulation model was developed, in order to estimate the unit cost (total costs/number of examinations in a defined period) of mammography examinations at those clinics. The cost analysis considered simulated changes in resource utilization rates and in examination failure probabilities (failures on the image acquisition system). In addition, a sensitivity analysis was performed, taking into account changes in the probabilities of equipment failure types. For the two clinic configurations, the estimated mammography unit costs were, respectively, US$ 41.31 and US$ 53.46 in the absence of examination failures. As the examination failures increased up to 10% of total examinations, unit costs approached US$ 54.53 and US$ 53.95, respectively. The sensitivity analysis showed that type 3 (the most serious) failure increases had a very large impact on the patient attendance, up to the point of actually making attendance unfeasible. Discrete-event simulation allowed for the definition of the more efficient clinic, contingent on the expected prevalence of resource utilization and equipment failures. © 2010 Blackwell Publishing Ltd.

A Brownian model for recurrent earthquakes

USGS Publications Warehouse

Matthews, M.V.; Ellsworth, W.L.; Reasenberg, P.A.

2002-01-01

We construct a probability model for rupture times on a recurrent earthquake source. Adding Brownian perturbations to steady tectonic loading produces a stochastic load-state process. Rupture is assumed to occur when this process reaches a critical-failure threshold. An earthquake relaxes the load state to a characteristic ground level and begins a new failure cycle. The load-state process is a Brownian relaxation oscillator. Intervals between events have a Brownian passage-time distribution that may serve as a temporal model for time-dependent, long-term seismic forecasting. This distribution has the following noteworthy properties: (1) the probability of immediate rerupture is zero; (2) the hazard rate increases steadily from zero at t = 0 to a finite maximum near the mean recurrence time and then decreases asymptotically to a quasi-stationary level, in which the conditional probability of an event becomes time independent; and (3) the quasi-stationary failure rate is greater than, equal to, or less than the mean failure rate because the coefficient of variation is less than, equal to, or greater than 1/???2 ??? 0.707. In addition, the model provides expressions for the hazard rate and probability of rupture on faults for which only a bound can be placed on the time of the last rupture. The Brownian relaxation oscillator provides a connection between observable event times and a formal state variable that reflects the macromechanics of stress and strain accumulation. Analysis of this process reveals that the quasi-stationary distance to failure has a gamma distribution, and residual life has a related exponential distribution. It also enables calculation of "interaction" effects due to external perturbations to the state, such as stress-transfer effects from earthquakes outside the target source. The influence of interaction effects on recurrence times is transient and strongly dependent on when in the loading cycle step pertubations occur. Transient effects may be much stronger than would be predicted by the "clock change" method and characteristically decay inversely with elapsed time after the perturbation.

An approximation formula for a class of fault-tolerant computers

NASA Technical Reports Server (NTRS)

White, A. L.

1986-01-01

An approximation formula is derived for the probability of failure for fault-tolerant process-control computers. These computers use redundancy and reconfiguration to achieve high reliability. Finite-state Markov models capture the dynamic behavior of component failure and system recovery, and the approximation formula permits an estimation of system reliability by an easy examination of the model.

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.

Estimation of the risk of failure for an endodontically treated maxillary premolar with MODP preparation and CAD/CAM ceramic restorations.

PubMed

Lin, Chun-Li; Chang, Yen-Hsiang; Pa, Che-An

2009-10-01

This study evaluated the risk of failure for an endodontically treated premolar with mesio occlusodistal palatal (MODP) preparation and 3 different computer-aided design/computer-aided manufacturing (CAD/CAM) ceramic restoration configurations. Three 3-dimensional finite element (FE) models designed with CAD/CAM ceramic onlay, endocrown, and conventional crown restorations were constructed to perform simulations. The Weibull function was incorporated with FE analysis to calculate the long-term failure probability relative to different load conditions. The results indicated that the stress values on the enamel, dentin, and luting cement for endocrown restoration were the lowest values relative to the other 2 restorations. Weibull analysis revealed that the individual failure probability in the endocrown enamel, dentin, and luting cement obviously diminished more than those for onlay and conventional crown restorations. The overall failure probabilities were 27.5%, 1%, and 1% for onlay, endocrown, and conventional crown restorations, respectively, in normal occlusal condition. This numeric investigation suggests that endocrown and conventional crown restorations for endodontically treated premolars with MODP preparation present similar longevity.

The assessment of low probability containment failure modes using dynamic PRA

NASA Astrophysics Data System (ADS)

Brunett, Acacia Joann

Although low probability containment failure modes in nuclear power plants may lead to large releases of radioactive material, these modes are typically crudely modeled in system level codes and have large associated uncertainties. Conventional risk assessment techniques (i.e. the fault-tree/event-tree methodology) are capable of accounting for these failure modes to some degree, however, they require the analyst to pre-specify the ordering of events, which can vary within the range of uncertainty of the phenomena. More recently, dynamic probabilistic risk assessment (DPRA) techniques have been developed which remove the dependency on the analyst. Through DPRA, it is now possible to perform a mechanistic and consistent analysis of low probability phenomena, with the timing of the possible events determined by the computational model simulating the reactor behavior. The purpose of this work is to utilize DPRA tools to assess low probability containment failure modes and the driving mechanisms. Particular focus is given to the risk-dominant containment failure modes considered in NUREG-1150, which has long been the standard for PRA techniques. More specifically, this work focuses on the low probability phenomena occurring during a station blackout (SBO) with late power recovery in the Zion Nuclear Power Plant, a Westinghouse pressurized water reactor (PWR). Subsequent to the major risk study performed in NUREG-1150, significant experimentation and modeling regarding the mechanisms driving containment failure modes have been performed. In light of this improved understanding, NUREG-1150 containment failure modes are reviewed in this work using the current state of knowledge. For some unresolved mechanisms, such as containment loading from high pressure melt ejection and combustion events, additional analyses are performed using the accident simulation tool MELCOR to explore the bounding containment loads for realistic scenarios. A dynamic treatment in the characterization of combustible gas ignition is also presented in this work. In most risk studies, combustion is treated simplistically in that it is assumed an ignition occurs if the gas mixture achieves a concentration favorable for ignition under the premise that an adequate ignition source is available. However, the criteria affecting ignition (such as the magnitude, location and frequency of the ignition sources) are complicated. This work demonstrates a technique for characterizing the properties of an ignition source to determine a probability of ignition. The ignition model developed in this work and implemented within a dynamic framework is utilized to analyze the implications and risk significance of late combustion events. This work also explores the feasibility of using dynamic event trees (DETs) with a deterministic sampling approach to analyze low probability phenomena. The flexibility of this approach is demonstrated through the rediscretization of containment fragility curves used in construction of the DET to show convergence to a true solution. Such a rediscretization also reduces the computational burden introduced through extremely fine fragility curve discretization by subsequent refinement of fragility curve regions of interest. Another advantage of the approach is the ability to perform sensitivity studies on the cumulative distribution functions (CDFs) used to determine branching probabilities without the need for rerunning the simulation code. Through review of the NUREG-1150 containment failure modes using the current state of knowledge, it is found that some failure modes, such as Alpha and rocket, can be excluded from further studies; other failure modes, such as failure to isolate, bypass, high pressure melt ejection (HPME), combustion-induced failure and overpressurization are still concerns to varying degrees. As part of this analysis, scoping studies performed in MELCOR show that HPME and the resulting direct containment heating (DCH) do not impose a significant threat to containment integrity. Additional scoping studies regarding the effect of recovery actions on in-vessel hydrogen generation show that reflooding a partially degraded core do not significantly affect hydrogen generation in-vessel, and the NUREG-1150 assumption that insufficient hydrogen is generated in-vessel to produce an energetic deflagration is confirmed. The DET analyses performed in this work show that very late power recovery produces the potential for very energetic combustion events which are capable of failing containment with a non-negligible probability, and that containment cooling systems have a significant impact on core concrete attack, and therefore combustible gas generation ex-vessel. Ultimately, the overall risk of combustion-induced containment failure is low, but its conditional likelihood can have a significant effect on accident mitigation strategies. It is also shown in this work that DETs are particularly well suited to examine low probability events because of their ability to rediscretize CDFs and observe solution convergence.

Performance of concatenated Reed-Solomon/Viterbi channel coding

NASA Technical Reports Server (NTRS)

Divsalar, D.; Yuen, J. H.

1982-01-01

The concatenated Reed-Solomon (RS)/Viterbi coding system is reviewed. The performance of the system is analyzed and results are derived with a new simple approach. A functional model for the input RS symbol error probability is presented. Based on this new functional model, we compute the performance of a concatenated system in terms of RS word error probability, output RS symbol error probability, bit error probability due to decoding failure, and bit error probability due to decoding error. Finally we analyze the effects of the noisy carrier reference and the slow fading on the system performance.

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

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

Controlling the self-organizing dynamics in a sandpile model on complex networks by failure tolerance

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

Qi, Junjian; Pfenninger, Stefan

In this paper, we propose a strategy to control the self-organizing dynamics of the Bak-Tang-Wiesenfeld (BTW) sandpile model on complex networks by allowing some degree of failure tolerance for the nodes and introducing additional active dissipation while taking the risk of possible node damage. We show that the probability for large cascades significantly increases or decreases respectively when the risk for node damage outweighs the active dissipation and when the active dissipation outweighs the risk for node damage. By considering the potential additional risk from node damage, a non-trivial optimal active dissipation control strategy which minimizes the total cost inmore » the system can be obtained. Under some conditions the introduced control strategy can decrease the total cost in the system compared to the uncontrolled model. Moreover, when the probability of damaging a node experiencing failure tolerance is greater than the critical value, then no matter how successful the active dissipation control is, the total cost of the system will have to increase. This critical damage probability can be used as an indicator of the robustness of a network or system. Copyright (C) EPLA, 2015« less

Impact of coverage on the reliability of a fault tolerant computer

NASA Technical Reports Server (NTRS)

Bavuso, S. J.

1975-01-01

A mathematical reliability model is established for a reconfigurable fault tolerant avionic computer system utilizing state-of-the-art computers. System reliability is studied in light of the coverage probabilities associated with the first and second independent hardware failures. Coverage models are presented as a function of detection, isolation, and recovery probabilities. Upper and lower bonds are established for the coverage probabilities and the method for computing values for the coverage probabilities is investigated. Further, an architectural variation is proposed which is shown to enhance coverage.

Cyber-Physical Correlations for Infrastructure Resilience: A Game-Theoretic Approach

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

Rao, Nageswara S; He, Fei; Ma, Chris Y. T.

In several critical infrastructures, the cyber and physical parts are correlated so that disruptions to one affect the other and hence the whole system. These correlations may be exploited to strategically launch components attacks, and hence must be accounted for ensuring the infrastructure resilience, specified by its survival probability. We characterize the cyber-physical interactions at two levels: (i) the failure correlation function specifies the conditional survival probability of cyber sub-infrastructure given the physical sub-infrastructure as a function of their marginal probabilities, and (ii) the individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions. We formulate a resiliencemore » problem for infrastructures composed of discrete components as a game between the provider and attacker, wherein their utility functions consist of an infrastructure survival probability term and a cost term expressed in terms of the number of components attacked and reinforced. We derive Nash Equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure resilience on the cost term, correlation function and sub-infrastructure survival probabilities. These results generalize earlier ones based on linear failure correlation functions and independent component failures. We apply the results to models of cloud computing infrastructures and energy grids.« less

Defense strategies for asymmetric networked systems under composite utilities

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

Rao, Nageswara S.; Ma, Chris Y. T.; Hausken, Kjell

We consider an infrastructure of networked systems with discrete components that can be reinforced at certain costs to guard against attacks. The communications network plays a critical, asymmetric role of providing the vital connectivity between the systems. We characterize the correlations within this infrastructure at two levels using (a) aggregate failure correlation function that specifies the infrastructure failure probability giventhe failure of an individual system or network, and (b) first order differential conditions on system survival probabilities that characterize component-level correlations. We formulate an infrastructure survival game between an attacker and a provider, who attacks and reinforces individual components, respectively.more » They use the composite utility functions composed of a survival probability term and a cost term, and the previously studiedsum-form and product-form utility functions are their special cases. At Nash Equilibrium, we derive expressions for individual system survival probabilities and the expected total number of operational components. We apply and discuss these estimates for a simplified model of distributed cloud computing infrastructure« less

A method for producing digital probabilistic seismic landslide hazard maps

USGS Publications Warehouse

Jibson, R.W.; Harp, E.L.; Michael, J.A.

2000-01-01

The 1994 Northridge, California, earthquake is the first earthquake for which we have all of the data sets needed to conduct a rigorous regional analysis of seismic slope instability. These data sets include: (1) a comprehensive inventory of triggered landslides, (2) about 200 strong-motion records of the mainshock, (3) 1:24 000-scale geologic mapping of the region, (4) extensive data on engineering properties of geologic units, and (5) high-resolution digital elevation models of the topography. All of these data sets have been digitized and rasterized at 10 m grid spacing using ARC/INFO GIS software on a UNIX computer. Combining these data sets in a dynamic model based on Newmark's permanent-deformation (sliding-block) analysis yields estimates of coseismic landslide displacement in each grid cell from the Northridge earthquake. The modeled displacements are then compared with the digital inventory of landslides triggered by the Northridge earthquake to construct a probability curve relating predicted displacement to probability of failure. This probability function can be applied to predict and map the spatial variability in failure probability in any ground-shaking conditions of interest. We anticipate that this mapping procedure will be used to construct seismic landslide hazard maps that will assist in emergency preparedness planning and in making rational decisions regarding development and construction in areas susceptible to seismic slope failure. ?? 2000 Elsevier Science B.V. All rights reserved.

A method for producing digital probabilistic seismic landslide hazard maps; an example from the Los Angeles, California, area

USGS Publications Warehouse

Jibson, Randall W.; Harp, Edwin L.; Michael, John A.

1998-01-01

The 1994 Northridge, California, earthquake is the first earthquake for which we have all of the data sets needed to conduct a rigorous regional analysis of seismic slope instability. These data sets include (1) a comprehensive inventory of triggered landslides, (2) about 200 strong-motion records of the mainshock, (3) 1:24,000-scale geologic mapping of the region, (4) extensive data on engineering properties of geologic units, and (5) high-resolution digital elevation models of the topography. All of these data sets have been digitized and rasterized at 10-m grid spacing in the ARC/INFO GIS platform. Combining these data sets in a dynamic model based on Newmark's permanent-deformation (sliding-block) analysis yields estimates of coseismic landslide displacement in each grid cell from the Northridge earthquake. The modeled displacements are then compared with the digital inventory of landslides triggered by the Northridge earthquake to construct a probability curve relating predicted displacement to probability of failure. This probability function can be applied to predict and map the spatial variability in failure probability in any ground-shaking conditions of interest. We anticipate that this mapping procedure will be used to construct seismic landslide hazard maps that will assist in emergency preparedness planning and in making rational decisions regarding development and construction in areas susceptible to seismic slope failure.

The GRASP 3: Graphical Reliability Analysis Simulation Program. Version 3: A users' manual and modelling guide

NASA Technical Reports Server (NTRS)

Phillips, D. T.; Manseur, B.; Foster, J. W.

1982-01-01

Alternate definitions of system failure create complex analysis for which analytic solutions are available only for simple, special cases. The GRASP methodology is a computer simulation approach for solving all classes of problems in which both failure and repair events are modeled according to the probability laws of the individual components of the system.

Failure probability under parameter uncertainty.

PubMed

Gerrard, R; Tsanakas, A

2011-05-01

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.

Unit-Sphere Anisotropic Multiaxial Stochastic-Strength Model Probability Density Distribution for the Orientation of Critical Flaws

NASA Technical Reports Server (NTRS)

Nemeth, Noel

2013-01-01

Models that predict the failure probability of monolithic glass and ceramic components under multiaxial loading have been developed by authors such as Batdorf, Evans, and Matsuo. These "unit-sphere" failure models assume that the strength-controlling flaws are randomly oriented, noninteracting planar microcracks of specified geometry but of variable size. This report develops a formulation to describe the probability density distribution of the orientation of critical strength-controlling flaws that results from an applied load. This distribution is a function of the multiaxial stress state, the shear sensitivity of the flaws, the Weibull modulus, and the strength anisotropy. Examples are provided showing the predicted response on the unit sphere for various stress states for isotropic and transversely isotropic (anisotropic) materials--including the most probable orientation of critical flaws for offset uniaxial loads with strength anisotropy. The author anticipates that this information could be used to determine anisotropic stiffness degradation or anisotropic damage evolution for individual brittle (or quasi-brittle) composite material constituents within finite element or micromechanics-based software

Fishnet model for failure probability tail of nacre-like imbricated lamellar materials

NASA Astrophysics Data System (ADS)

Luo, Wen; Bažant, Zdeněk P.

2017-12-01

Nacre, the iridescent material of the shells of pearl oysters and abalone, consists mostly of aragonite (a form of CaCO3), a brittle constituent of relatively low strength (≈10 MPa). Yet it has astonishing mean tensile strength (≈150 MPa) and fracture energy (≈350 to 1,240 J/m2). The reasons have recently become well understood: (i) the nanoscale thickness (≈300 nm) of nacre's building blocks, the aragonite lamellae (or platelets), and (ii) the imbricated, or staggered, arrangement of these lamellea, bound by biopolymer layers only ≈25 nm thick, occupying <5% of volume. These properties inspire manmade biomimetic materials. For engineering applications, however, the failure probability of ≤10-6 is generally required. To guarantee it, the type of probability density function (pdf) of strength, including its tail, must be determined. This objective, not pursued previously, is hardly achievable by experiments alone, since >10^8 tests of specimens would be needed. Here we outline a statistical model of strength that resembles a fishnet pulled diagonally, captures the tail of pdf of strength and, importantly, allows analytical safety assessments of nacreous materials. The analysis shows that, in terms of safety, the imbricated lamellar structure provides a major additional advantage—˜10% strength increase at tail failure probability 10^-6 and a 1 to 2 orders of magnitude tail probability decrease at fixed stress. Another advantage is that a high scatter of microstructure properties diminishes the strength difference between the mean and the probability tail, compared with the weakest link model. These advantages of nacre-like materials are here justified analytically and supported by millions of Monte Carlo simulations.

Disparity between online and offline tests in accelerated aging tests of LED lamps under electric stress.

PubMed

Wang, Yao; Jing, Lei; Ke, Hong-Liang; Hao, Jian; Gao, Qun; Wang, Xiao-Xun; Sun, Qiang; Xu, Zhi-Jun

2016-09-20

The accelerated aging tests under electric stress for one type of LED lamp are conducted, and the differences between online and offline tests of the degradation of luminous flux are studied in this paper. The transformation of the two test modes is achieved with an adjustable AC voltage stabilized power source. Experimental results show that the exponential fitting of the luminous flux degradation in online tests possesses a higher fitting degree for most lamps, and the degradation rate of the luminous flux by online tests is always lower than that by offline tests. Bayes estimation and Weibull distribution are used to calculate the failure probabilities under the accelerated voltages, and then the reliability of the lamps under rated voltage of 220 V is estimated by use of the inverse power law model. Results show that the relative error of the lifetime estimation by offline tests increases as the failure probability decreases, and it cannot be neglected when the failure probability is less than 1%. The relative errors of lifetime estimation are 7.9%, 5.8%, 4.2%, and 3.5%, at the failure probabilities of 0.1%, 1%, 5%, and 10%, respectively.

Cycles till failure of silver-zinc cells with competing failure modes - Preliminary data analysis

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Leibecki, H. F.; Bozek, J. M.

1980-01-01

The data analysis of cycles to failure of silver-zinc electrochemical cells with competing failure modes is presented. The test ran 129 cells through charge-discharge cycles until failure; preliminary data analysis consisted of response surface estimate of life. Batteries fail through low voltage condition and an internal shorting condition; a competing failure modes analysis was made using maximum likelihood estimation for the extreme value life distribution. Extensive residual plotting and probability plotting were used to verify data quality and selection of model.

Approximation of Failure Probability Using Conditional Sampling

NASA Technical Reports Server (NTRS)

Giesy. Daniel P.; Crespo, Luis G.; Kenney, Sean P.

2008-01-01

In analyzing systems which depend on uncertain parameters, one technique is to partition the uncertain parameter domain into a failure set and its complement, and judge the quality of the system by estimating the probability of failure. If this is done by a sampling technique such as Monte Carlo and the probability of failure is small, accurate approximation can require so many sample points that the computational expense is prohibitive. Previous work of the authors has shown how to bound the failure event by sets of such simple geometry that their probabilities can be calculated analytically. In this paper, it is shown how to make use of these failure bounding sets and conditional sampling within them to substantially reduce the computational burden of approximating failure probability. It is also shown how the use of these sampling techniques improves the confidence intervals for the failure probability estimate for a given number of sample points and how they reduce the number of sample point analyses needed to achieve a given level of confidence.

Gaussian process surrogates for failure detection: A Bayesian experimental design approach

NASA Astrophysics Data System (ADS)

Wang, Hongqiao; Lin, Guang; Li, Jinglai

2016-05-01

An important task of uncertainty quantification is to identify the probability of undesired events, in particular, system failures, caused by various sources of uncertainties. In this work we consider the construction of Gaussian process surrogates for failure detection and failure probability estimation. In particular, we consider the situation that the underlying computer models are extremely expensive, and in this setting, determining the sampling points in the state space is of essential importance. We formulate the problem as an optimal experimental design for Bayesian inferences of the limit state (i.e., the failure boundary) and propose an efficient numerical scheme to solve the resulting optimization problem. In particular, the proposed limit-state inference method is capable of determining multiple sampling points at a time, and thus it is well suited for problems where multiple computer simulations can be performed in parallel. The accuracy and performance of the proposed method is demonstrated by both academic and practical examples.

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.

Dam failure analysis for the Lago El Guineo Dam, Orocovis, Puerto Rico

USGS Publications Warehouse

Gómez-Fragoso, Julieta; Heriberto Torres-Sierra,

2016-08-09

The U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, completed hydrologic and hydraulic analyses to assess the potential hazard to human life and property associated with the hypothetical failure of the Lago El Guineo Dam. The Lago El Guineo Dam is within the headwaters of the Río Grande de Manatí and impounds a drainage area of about 4.25 square kilometers.The hydrologic assessment was designed to determine the outflow hydrographs and peak discharges for Lago El Guineo and other subbasins in the Río Grande de Manatí hydrographic basin for three extreme rainfall events: (1) a 6-hour probable maximum precipitation event, (2) a 24-hour probable maximum precipitation event, and (3) a 24-hour, 100-year recurrence rainfall event. The hydraulic study simulated a dam failure of Lago El Guineo Dam using flood hydrographs generated from the hydrologic study. The simulated dam failure generated a hydrograph that was routed downstream from Lago El Guineo Dam through the lower reaches of the Río Toro Negro and the Río Grande de Manatí to determine water-surface profiles developed from the event-based hydrologic scenarios and “sunny day” conditions. The Hydrologic Engineering Center’s Hydrologic Modeling System (HEC–HMS) and Hydrologic Engineering Center’s River Analysis System (HEC–RAS) computer programs, developed by the U.S. Army Corps of Engineers, were used for the hydrologic and hydraulic modeling, respectively. The flow routing in the hydraulic analyses was completed using the unsteady flow module available in the HEC–RAS model.Above the Lago El Guineo Dam, the simulated inflow peak discharges from HEC–HMS resulted in about 550 and 414 cubic meters per second for the 6- and 24-hour probable maximum precipitation events, respectively. The 24-hour, 100-year recurrence storm simulation resulted in a peak discharge of about 216 cubic meters per second. For the hydrologic analysis, no dam failure conditions are considered within the model. The results of the hydrologic simulations indicated that for all hydrologic conditions scenarios, the Lago El Guineo Dam would not experience overtopping. For the dam breach hydraulic analysis, failure by piping was the selected hypothetical failure mode for the Lago El Guineo Dam.Results from the simulated dam failure of the Lago El Guineo Dam using the HEC–RAS model for the 6- and 24-hour probable maximum precipitation events indicated peak discharges below the dam of 1,342.43 and 1,434.69 cubic meters per second, respectively. Dam failure during the 24-hour, 100-year recurrence rainfall event resulted in a peak discharge directly downstream from Lago El Guineo Dam of 1,183.12 cubic meters per second. Dam failure during sunny-day conditions (no precipitation) produced a peak discharge at Lago El Guineo Dam of 1,015.31 cubic meters per second assuming the initial water-surface elevation was at the morning-glory spillway invert elevation.The results of the hydraulic analysis indicate that the flood would extend to many inhabited areas along the stream banks from the Lago El Guineo Dam to the mouth of the Río Grande as a result of the simulated failure of the Lago El Guineo Dam. Low-lying regions in the vicinity of Ciales, Manatí, and Barceloneta, Puerto Rico, are among the regions that would be most affected by failure of the Lago El Guineo Dam. Effects of the flood control (levee) structure constructed in 2000 to provide protection to the low-lying populated areas of Barceloneta, Puerto Rico, were considered in the hydraulic analysis of dam failure. The results indicate that overtopping can be expected in the aforementioned levee during 6- and 24-hour probable maximum precipitation events. The levee was not overtopped during dam failure scenarios under the 24-hour, 100-year recurrence rainfall event or sunny-day conditions.

Cascading failures in ac electricity grids.

PubMed

Rohden, Martin; Jung, Daniel; Tamrakar, Samyak; Kettemann, Stefan

2016-09-01

Sudden failure of a single transmission element in a power grid can induce a domino effect of cascading failures, which can lead to the isolation of a large number of consumers or even to the failure of the entire grid. Here we present results of the simulation of cascading failures in power grids, using an alternating current (AC) model. We first apply this model to a regular square grid topology. For a random placement of consumers and generators on the grid, the probability to find more than a certain number of unsupplied consumers decays as a power law and obeys a scaling law with respect to system size. Varying the transmitted power threshold above which a transmission line fails does not seem to change the power-law exponent q≈1.6. Furthermore, we study the influence of the placement of generators and consumers on the number of affected consumers and demonstrate that large clusters of generators and consumers are especially vulnerable to cascading failures. As a real-world topology, we consider the German high-voltage transmission grid. Applying the dynamic AC model and considering a random placement of consumers, we find that the probability to disconnect more than a certain number of consumers depends strongly on the threshold. For large thresholds the decay is clearly exponential, while for small ones the decay is slow, indicating a power-law decay.

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.

Failure probability analysis of optical grid

NASA Astrophysics Data System (ADS)

Zhong, Yaoquan; Guo, Wei; Sun, Weiqiang; Jin, Yaohui; Hu, Weisheng

2008-11-01

Optical grid, the integrated computing environment based on optical network, is expected to be an efficient infrastructure to support advanced data-intensive grid applications. In optical grid, the faults of both computational and network resources are inevitable due to the large scale and high complexity of the system. With the optical network based distributed computing systems extensive applied in the processing of data, the requirement of the application failure probability have been an important indicator of the quality of application and an important aspect the operators consider. This paper will present a task-based analysis method of the application failure probability in optical grid. Then the failure probability of the entire application can be quantified, and the performance of reducing application failure probability in different backup strategies can be compared, so that the different requirements of different clients can be satisfied according to the application failure probability respectively. In optical grid, when the application based DAG (directed acyclic graph) is executed in different backup strategies, the application failure probability and the application complete time is different. This paper will propose new multi-objective differentiated services algorithm (MDSA). New application scheduling algorithm can guarantee the requirement of the failure probability and improve the network resource utilization, realize a compromise between the network operator and the application submission. Then differentiated services can be achieved in optical grid.

POF-Darts: Geometric adaptive sampling for probability of failure

DOE PAGES

Ebeida, Mohamed S.; Mitchell, Scott A.; Swiler, Laura P.; ...

2016-06-18

We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink,more » improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.« 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 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.

Scalable Failure Masking for Stencil Computations using Ghost Region Expansion and Cell to Rank Remapping

DOE PAGES

Gamell, Marc; Teranishi, Keita; Kolla, Hemanth; ...

2017-10-26

In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments.more » In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.« less

Scalable Failure Masking for Stencil Computations using Ghost Region Expansion and Cell to Rank Remapping

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

Gamell, Marc; Teranishi, Keita; Kolla, Hemanth

In order to achieve exascale systems, application resilience needs to be addressed. Some programming models, such as task-DAG (directed acyclic graphs) architectures, currently embed resilience features whereas traditional SPMD (single program, multiple data) and message-passing models do not. Since a large part of the community's code base follows the latter models, it is still required to take advantage of application characteristics to minimize the overheads of fault tolerance. To that end, this paper explores how recovering from hard process/node failures in a local manner is a natural approach for certain applications to obtain resilience at lower costs in faulty environments.more » In particular, this paper targets enabling online, semitransparent local recovery for stencil computations on current leadership-class systems as well as presents programming support and scalable runtime mechanisms. Also described and demonstrated in this paper is the effect of failure masking, which allows the effective reduction of impact on total time to solution due to multiple failures. Furthermore, we discuss, implement, and evaluate ghost region expansion and cell-to-rank remapping to increase the probability of failure masking. To conclude, this paper shows the integration of all aforementioned mechanisms with the S3D combustion simulation through an experimental demonstration (using the Titan system) of the ability to tolerate high failure rates (i.e., node failures every five seconds) with low overhead while sustaining performance at large scales. In addition, this demonstration also displays the failure masking probability increase resulting from the combination of both ghost region expansion and cell-to-rank remapping.« less

Model analysis of the link between interest rates and crashes

NASA Astrophysics Data System (ADS)

Broga, Kristijonas M.; Viegas, Eduardo; Jensen, Henrik Jeldtoft

2016-09-01

We analyse the effect of distinct levels of interest rates on the stability of the financial network under our modelling framework. We demonstrate that banking failures are likely to emerge early on under sustained high interest rates, and at much later stage-with higher probability-under a sustained low interest rate scenario. Moreover, we demonstrate that those bank failures are of a different nature: high interest rates tend to result in significantly more bankruptcies associated to credit losses whereas lack of liquidity tends to be the primary cause of failures under lower rates.

Evaluation of the probability of arrester failure in a high-voltage transmission line using a Q learning artificial neural network model

NASA Astrophysics Data System (ADS)

Ekonomou, L.; Karampelas, P.; Vita, V.; Chatzarakis, G. E.

2011-04-01

One of the most popular methods of protecting high voltage transmission lines against lightning strikes and internal overvoltages is the use of arresters. The installation of arresters in high voltage transmission lines can prevent or even reduce the lines' failure rate. Several studies based on simulation tools have been presented in order to estimate the critical currents that exceed the arresters' rated energy stress and to specify the arresters' installation interval. In this work artificial intelligence, and more specifically a Q-learning artificial neural network (ANN) model, is addressed for evaluating the arresters' failure probability. The aims of the paper are to describe in detail the developed Q-learning ANN model and to compare the results obtained by its application in operating 150 kV Greek transmission lines with those produced using a simulation tool. The satisfactory and accurate results of the proposed ANN model can make it a valuable tool for designers of electrical power systems seeking more effective lightning protection, reducing operational costs and better continuity of service.

Model-Based Method for Sensor Validation

NASA Technical Reports Server (NTRS)

Vatan, Farrokh

2012-01-01

Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

Game-theoretic strategies for asymmetric networked systems

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

Rao, Nageswara S.; Ma, Chris Y. T.; Hausken, Kjell

Abstract—We consider an infrastructure consisting of a network of systems each composed of discrete components that can be reinforced at a certain cost to guard against attacks. The network provides the vital connectivity between systems, and hence plays a critical, asymmetric role in the infrastructure operations. We characterize the system-level correlations using the aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual system or network. The survival probabilities of systems and network satisfy first-order differential conditions that capture the component-level correlations. We formulate the problem of ensuring the infrastructure survival as a gamemore » between anattacker and a provider, using the sum-form and product-form utility functions, each composed of a survival probability term and a cost term. We derive Nash Equilibrium conditions which provide expressions for individual system survival probabilities, and also the expected capacity specified by the total number of operational components. These expressions differ only in a single term for the sum-form and product-form utilities, despite their significant differences.We apply these results to simplified models of distributed cloud computing infrastructures.« 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.

Probability elicitation to inform early health economic evaluations of new medical technologies: a case study in heart failure disease management.

PubMed

Cao, Qi; Postmus, Douwe; Hillege, Hans L; Buskens, Erik

2013-06-01

Early estimates of the commercial headroom available to a new medical device can assist producers of health technology in making appropriate product investment decisions. The purpose of this study was to illustrate how this quantity can be captured probabilistically by combining probability elicitation with early health economic modeling. The technology considered was a novel point-of-care testing device in heart failure disease management. First, we developed a continuous-time Markov model to represent the patients' disease progression under the current care setting. Next, we identified the model parameters that are likely to change after the introduction of the new device and interviewed three cardiologists to capture the probability distributions of these parameters. Finally, we obtained the probability distribution of the commercial headroom available per measurement by propagating the uncertainty in the model inputs to uncertainty in modeled outcomes. For a willingness-to-pay value of €10,000 per life-year, the median headroom available per measurement was €1.64 (interquartile range €0.05-€3.16) when the measurement frequency was assumed to be daily. In the subsequently conducted sensitivity analysis, this median value increased to a maximum of €57.70 for different combinations of the willingness-to-pay threshold and the measurement frequency. Probability elicitation can successfully be combined with early health economic modeling to obtain the probability distribution of the headroom available to a new medical technology. Subsequently feeding this distribution into a product investment evaluation method enables stakeholders to make more informed decisions regarding to which markets a currently available product prototype should be targeted. Copyright © 2013. Published by Elsevier Inc.

Probabilistic seismic hazard in the San Francisco Bay area based on a simplified viscoelastic cycle model of fault interactions

USGS Publications Warehouse

Pollitz, F.F.; Schwartz, D.P.

2008-01-01

We construct a viscoelastic cycle model of plate boundary deformation that includes the effect of time-dependent interseismic strain accumulation, coseismic strain release, and viscoelastic relaxation of the substrate beneath the seismogenic crust. For a given fault system, time-averaged stress changes at any point (not on a fault) are constrained to zero; that is, kinematic consistency is enforced for the fault system. The dates of last rupture, mean recurrence times, and the slip distributions of the (assumed) repeating ruptures are key inputs into the viscoelastic cycle model. This simple formulation allows construction of stress evolution at all points in the plate boundary zone for purposes of probabilistic seismic hazard analysis (PSHA). Stress evolution is combined with a Coulomb failure stress threshold at representative points on the fault segments to estimate the times of their respective future ruptures. In our PSHA we consider uncertainties in a four-dimensional parameter space: the rupture peridocities, slip distributions, time of last earthquake (for prehistoric ruptures) and Coulomb failure stress thresholds. We apply this methodology to the San Francisco Bay region using a recently determined fault chronology of area faults. Assuming single-segment rupture scenarios, we find that fature rupture probabilities of area faults in the coming decades are the highest for the southern Hayward, Rodgers Creek, and northern Calaveras faults. This conclusion is qualitatively similar to that of Working Group on California Earthquake Probabilities, but the probabilities derived here are significantly higher. Given that fault rupture probabilities are highly model-dependent, no single model should be used to assess to time-dependent rupture probabilities. We suggest that several models, including the present one, be used in a comprehensive PSHA methodology, as was done by Working Group on California Earthquake Probabilities.

Treatment carryover impacts on effectiveness of intraocular pressure lowering agents, estimated by a discrete event simulation model.

PubMed

Denis, P; Le Pen, C; Umuhire, D; Berdeaux, G

2008-01-01

To compare the effectiveness of two treatment sequences, latanoprost-latanoprost timolol fixed combination (L-LT) versus travoprost-travoprost timolol fixed combination (T-TT), in the treatment of open-angle glaucoma (OAG) or ocular hypertension (OHT). A discrete event simulation (DES) model was constructed. Patients with either OAG or OHT were treated first-line with a prostaglandin, either latanoprost or travoprost. In case of treatment failure, patients were switched to the specific prostaglandin-timolol sequence LT or TT. Failure was defined as intraocular pressure higher than or equal to 18 mmHg at two visits. Time to failure was estimated from two randomized clinical trials. Log-rank tests were computed. Linear functions after log-log transformation were used to model time to failure. The time horizon of the model was 60 months. Outcomes included treatment failure and disease progression. Sensitivity analyses were performed. Latanoprost treatment resulted in more treatment failures than travoprost (p<0.01), and LT more than TT (p<0.01). At 60 months, the probability of starting a third treatment line was 39.2% with L-LT versus 29.9% with T-TT. On average, L-LT patients developed 0.55 new visual field defects versus 0.48 for T-TT patients. The probability of no disease progression at 60 months was 61.4% with L-LT and 65.5% with T-TT. Based on randomized clinical trial results and using a DES model, the T-TT sequence was more effective at avoiding starting a third line treatment than the L-LT sequence. T-TT treated patients developed less glaucoma progression.

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...

Risk assessment of turbine rotor failure using probabilistic ultrasonic non-destructive evaluations

NASA Astrophysics Data System (ADS)

Guan, Xuefei; Zhang, Jingdan; Zhou, S. Kevin; Rasselkorde, El Mahjoub; Abbasi, Waheed A.

2014-02-01

The study presents a method and application of risk assessment methodology for turbine rotor fatigue failure using probabilistic ultrasonic nondestructive evaluations. A rigorous probabilistic modeling for ultrasonic flaw sizing is developed by incorporating the model-assisted probability of detection, and the probability density function (PDF) of the actual flaw size is derived. Two general scenarios, namely the ultrasonic inspection with an identified flaw indication and the ultrasonic inspection without flaw indication, are considered in the derivation. To perform estimations for fatigue reliability and remaining useful life, uncertainties from ultrasonic flaw sizing and fatigue model parameters are systematically included and quantified. The model parameter PDF is estimated using Bayesian parameter estimation and actual fatigue testing data. The overall method is demonstrated using a realistic application of steam turbine rotor, and the risk analysis under given safety criteria is provided to support maintenance planning.

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.

The influence of microstructure on the probability of early failure in aluminum-based interconnects

NASA Astrophysics Data System (ADS)

Dwyer, V. M.

2004-09-01

For electromigration in short aluminum interconnects terminated by tungsten vias, the well known "short-line" effect applies. In a similar manner, for longer lines, early failure is determined by a critical value Lcrit for the length of polygranular clusters. Any cluster shorter than Lcrit is "immortal" on the time scale of early failure where the figure of merit is not the standard t50 value (the time to 50% failures), but rather the total probability of early failure, Pcf. Pcf is a complex function of current density, linewidth, line length, and material properties (the median grain size d50 and grain size shape factor σd). It is calculated here using a model based around the theory of runs, which has proved itself to be a useful tool for assessing the probability of extreme events. Our analysis shows that Pcf is strongly dependent on σd, and a change in σd from 0.27 to 0.5 can cause an order of magnitude increase in Pcf under typical test conditions. This has implications for the web-based two-dimensional grain-growth simulator MIT/EmSim, which generates grain patterns with σd=0.27, while typical as-patterned structures are better represented by a σd in the range 0.4 - 0.6. The simulator will consequently overestimate interconnect reliability due to this particular electromigration failure mode.

Economic Statistical Design of Integrated X-bar-S Control Chart with Preventive Maintenance and General Failure Distribution

PubMed Central

Caballero Morales, Santiago Omar

2013-01-01

The application of Preventive Maintenance (PM) and Statistical Process Control (SPC) are important practices to achieve high product quality, small frequency of failures, and cost reduction in a production process. However there are some points that have not been explored in depth about its joint application. First, most SPC is performed with the X-bar control chart which does not fully consider the variability of the production process. Second, many studies of design of control charts consider just the economic aspect while statistical restrictions must be considered to achieve charts with low probabilities of false detection of failures. Third, the effect of PM on processes with different failure probability distributions has not been studied. Hence, this paper covers these points, presenting the Economic Statistical Design (ESD) of joint X-bar-S control charts with a cost model that integrates PM with general failure distribution. Experiments showed statistically significant reductions in costs when PM is performed on processes with high failure rates and reductions in the sampling frequency of units for testing under SPC. PMID:23527082

Failure analysis and modeling of a VAXcluster system

NASA Technical Reports Server (NTRS)

Tang, Dong; Iyer, Ravishankar K.; Subramani, Sujatha S.

1990-01-01

This paper discusses the results of a measurement-based analysis of real error data collected from a DEC VAXcluster multicomputer system. In addition to evaluating basic system dependability characteristics such as error and failure distributions and hazard rates for both individual machines and for the VAXcluster, reward models were developed to analyze the impact of failures on the system as a whole. The results show that more than 46 percent of all failures were due to errors in shared resources. This is despite the fact that these errors have a recovery probability greater than 0.99. The hazard rate calculations show that not only errors, but also failures occur in bursts. Approximately 40 percent of all failures occur in bursts and involved multiple machines. This result indicates that correlated failures are significant. Analysis of rewards shows that software errors have the lowest reward (0.05 vs 0.74 for disk errors). The expected reward rate (reliability measure) of the VAXcluster drops to 0.5 in 18 hours for the 7-out-of-7 model and in 80 days for the 3-out-of-7 model.

Failure analysis of storage tank component in LNG regasification unit using fault tree analysis method (FTA)

NASA Astrophysics Data System (ADS)

Mulyana, Cukup; Muhammad, Fajar; Saad, Aswad H.; Mariah, Riveli, Nowo

2017-03-01

Storage tank component is the most critical component in LNG regasification terminal. It has the risk of failure and accident which impacts to human health and environment. Risk assessment is conducted to detect and reduce the risk of failure in storage tank. The aim of this research is determining and calculating the probability of failure in regasification unit of LNG. In this case, the failure is caused by Boiling Liquid Expanding Vapor Explosion (BLEVE) and jet fire in LNG storage tank component. The failure probability can be determined by using Fault Tree Analysis (FTA). Besides that, the impact of heat radiation which is generated is calculated. Fault tree for BLEVE and jet fire on storage tank component has been determined and obtained with the value of failure probability for BLEVE of 5.63 × 10-19 and for jet fire of 9.57 × 10-3. The value of failure probability for jet fire is high enough and need to be reduced by customizing PID scheme of regasification LNG unit in pipeline number 1312 and unit 1. The value of failure probability after customization has been obtained of 4.22 × 10-6.

Cycles till failure of silver-zinc cells with completing failures modes: Preliminary data analysis

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Leibecki, H. F.; Bozek, J. M.

1980-01-01

One hundred and twenty nine cells were run through charge-discharge cycles until failure. The experiment design was a variant of a central composite factorial in five factors. Preliminary data analysis consisted of response surface estimation of life. Batteries fail under two basic modes; a low voltage condition and an internal shorting condition. A competing failure modes analysis using maximum likelihood estimation for the extreme value life distribution was performed. Extensive diagnostics such as residual plotting and probability plotting were employed to verify data quality and choice of model.

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.

Statistical modeling of SRAM yield performance and circuit variability

NASA Astrophysics Data System (ADS)

Cheng, Qi; Chen, Yijian

2015-03-01

In this paper, we develop statistical models to investigate SRAM yield performance and circuit variability in the presence of self-aligned multiple patterning (SAMP) process. It is assumed that SRAM fins are fabricated by a positivetone (spacer is line) self-aligned sextuple patterning (SASP) process which accommodates two types of spacers, while gates are fabricated by a more pitch-relaxed self-aligned quadruple patterning (SAQP) process which only allows one type of spacer. A number of possible inverter and SRAM structures are identified and the related circuit multi-modality is studied using the developed failure-probability and yield models. It is shown that SRAM circuit yield is significantly impacted by the multi-modality of fins' spatial variations in a SRAM cell. The sensitivity of 6-transistor SRAM read/write failure probability to SASP process variations is calculated and the specific circuit type with the highest probability to fail in the reading/writing operation is identified. Our study suggests that the 6-transistor SRAM configuration may not be scalable to 7-nm half pitch and more robust SRAM circuit design needs to be researched.

Probabilistic Analysis of a Composite Crew Module

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Krishnamurthy, Thiagarajan

2011-01-01

An approach for conducting reliability-based analysis (RBA) of a Composite Crew Module (CCM) is presented. The goal is to identify and quantify the benefits of probabilistic design methods for the CCM and future space vehicles. The coarse finite element model from a previous NASA Engineering and Safety Center (NESC) project is used as the baseline deterministic analysis model to evaluate the performance of the CCM using a strength-based failure index. The first step in the probabilistic analysis process is the determination of the uncertainty distributions for key parameters in the model. Analytical data from water landing simulations are used to develop an uncertainty distribution, but such data were unavailable for other load cases. The uncertainty distributions for the other load scale factors and the strength allowables are generated based on assumed coefficients of variation. Probability of first-ply failure is estimated using three methods: the first order reliability method (FORM), Monte Carlo simulation, and conditional sampling. Results for the three methods were consistent. The reliability is shown to be driven by first ply failure in one region of the CCM at the high altitude abort load set. The final predicted probability of failure is on the order of 10-11 due to the conservative nature of the factors of safety on the deterministic loads.

An experimental evaluation of software redundancy as a strategy for improving reliability

NASA Technical Reports Server (NTRS)

Eckhardt, Dave E., Jr.; Caglayan, Alper K.; Knight, John C.; Lee, Larry D.; Mcallister, David F.; Vouk, Mladen A.; Kelly, John P. J.

1990-01-01

The strategy of using multiple versions of independently developed software as a means to tolerate residual software design faults is suggested by the success of hardware redundancy for tolerating hardware failures. Although, as generally accepted, the independence of hardware failures resulting from physical wearout can lead to substantial increases in reliability for redundant hardware structures, a similar conclusion is not immediate for software. The degree to which design faults are manifested as independent failures determines the effectiveness of redundancy as a method for improving software reliability. Interest in multi-version software centers on whether it provides an adequate measure of increased reliability to warrant its use in critical applications. The effectiveness of multi-version software is studied by comparing estimates of the failure probabilities of these systems with the failure probabilities of single versions. The estimates are obtained under a model of dependent failures and compared with estimates obtained when failures are assumed to be independent. The experimental results are based on twenty versions of an aerospace application developed and certified by sixty programmers from four universities. Descriptions of the application, development and certification processes, and operational evaluation are given together with an analysis of the twenty versions.

Probability of Loss of Assured Safety in Systems with Multiple Time-Dependent Failure Modes: Incorporation of Delayed Link Failure in the Presence of Aleatory Uncertainty.

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

Helton, Jon C.; Brooks, Dusty Marie; Sallaberry, Cedric Jean-Marie.

Probability of loss of assured safety (PLOAS) is modeled for weak link (WL)/strong link (SL) systems in which one or more WLs or SLs could potentially degrade into a precursor condition to link failure that will be followed by an actual failure after some amount of elapsed time. The following topics are considered: (i) Definition of precursor occurrence time cumulative distribution functions (CDFs) for individual WLs and SLs, (ii) Formal representation of PLOAS with constant delay times, (iii) Approximation and illustration of PLOAS with constant delay times, (iv) Formal representation of PLOAS with aleatory uncertainty in delay times, (v) Approximationmore » and illustration of PLOAS with aleatory uncertainty in delay times, (vi) Formal representation of PLOAS with delay times defined by functions of link properties at occurrence times for failure precursors, (vii) Approximation and illustration of PLOAS with delay times defined by functions of link properties at occurrence times for failure precursors, and (viii) Procedures for the verification of PLOAS calculations for the three indicated definitions of delayed link failure.« less

Adjusting survival estimates for premature transmitter failure: A case study from the Sacramento-San Joaquin Delta

USGS Publications Warehouse

Holbrook, Christopher M.; Perry, Russell W.; Brandes, Patricia L.; Adams, Noah S.

2013-01-01

In telemetry studies, premature tag failure causes negative bias in fish survival estimates because tag failure is interpreted as fish mortality. We used mark-recapture modeling to adjust estimates of fish survival for a previous study where premature tag failure was documented. High rates of tag failure occurred during the Vernalis Adaptive Management Plan’s (VAMP) 2008 study to estimate survival of fall-run Chinook salmon (Oncorhynchus tshawytscha) during migration through the San Joaquin River and Sacramento-San Joaquin Delta, California. Due to a high rate of tag failure, the observed travel time distribution was likely negatively biased, resulting in an underestimate of tag survival probability in this study. Consequently, the bias-adjustment method resulted in only a small increase in estimated fish survival when the observed travel time distribution was used to estimate the probability of tag survival. Since the bias-adjustment failed to remove bias, we used historical travel time data and conducted a sensitivity analysis to examine how fish survival might have varied across a range of tag survival probabilities. Our analysis suggested that fish survival estimates were low (95% confidence bounds range from 0.052 to 0.227) over a wide range of plausible tag survival probabilities (0.48–1.00), and this finding is consistent with other studies in this system. When tags fail at a high rate, available methods to adjust for the bias may perform poorly. Our example highlights the importance of evaluating the tag life assumption during survival studies, and presents a simple framework for evaluating adjusted survival estimates when auxiliary travel time data are available.

Development of STS/Centaur failure probabilities liftoff to Centaur separation

NASA Technical Reports Server (NTRS)

Hudson, J. M.

1982-01-01

The results of an analysis to determine STS/Centaur catastrophic vehicle response probabilities for the phases of vehicle flight from STS liftoff to Centaur separation from the Orbiter are presented. The analysis considers only category one component failure modes as contributors to the vehicle response mode probabilities. The relevant component failure modes are grouped into one of fourteen categories of potential vehicle behavior. By assigning failure rates to each component, for each of its failure modes, the STS/Centaur vehicle response probabilities in each phase of flight can be calculated. The results of this study will be used in a DOE analysis to ascertain the hazard from carrying a nuclear payload on the STS.

Improved Correction of Misclassification Bias With Bootstrap Imputation.

PubMed

van Walraven, Carl

2018-07-01

Diagnostic codes used in administrative database research can create bias due to misclassification. Quantitative bias analysis (QBA) can correct for this bias, requires only code sensitivity and specificity, but may return invalid results. Bootstrap imputation (BI) can also address misclassification bias but traditionally requires multivariate models to accurately estimate disease probability. This study compared misclassification bias correction using QBA and BI. Serum creatinine measures were used to determine severe renal failure status in 100,000 hospitalized patients. Prevalence of severe renal failure in 86 patient strata and its association with 43 covariates was determined and compared with results in which renal failure status was determined using diagnostic codes (sensitivity 71.3%, specificity 96.2%). Differences in results (misclassification bias) were then corrected with QBA or BI (using progressively more complex methods to estimate disease probability). In total, 7.4% of patients had severe renal failure. Imputing disease status with diagnostic codes exaggerated prevalence estimates [median relative change (range), 16.6% (0.8%-74.5%)] and its association with covariates [median (range) exponentiated absolute parameter estimate difference, 1.16 (1.01-2.04)]. QBA produced invalid results 9.3% of the time and increased bias in estimates of both disease prevalence and covariate associations. BI decreased misclassification bias with increasingly accurate disease probability estimates. QBA can produce invalid results and increase misclassification bias. BI avoids invalid results and can importantly decrease misclassification bias when accurate disease probability estimates are used.

Automatic Monitoring System Design and Failure Probability Analysis for River Dikes on Steep Channel

NASA Astrophysics Data System (ADS)

Chang, Yin-Lung; Lin, Yi-Jun; Tung, Yeou-Koung

2017-04-01

The purposes of this study includes: (1) design an automatic monitoring system for river dike; and (2) develop a framework which enables the determination of dike failure probabilities for various failure modes during a rainstorm. The historical dike failure data collected in this study indicate that most dikes in Taiwan collapsed under the 20-years return period discharge, which means the probability of dike failure is much higher than that of overtopping. We installed the dike monitoring system on the Chiu-She Dike which located on the middle stream of Dajia River, Taiwan. The system includes: (1) vertical distributed pore water pressure sensors in front of and behind the dike; (2) Time Domain Reflectometry (TDR) to measure the displacement of dike; (3) wireless floating device to measure the scouring depth at the toe of dike; and (4) water level gauge. The monitoring system recorded the variation of pore pressure inside the Chiu-She Dike and the scouring depth during Typhoon Megi. The recorded data showed that the highest groundwater level insides the dike occurred 15 hours after the peak discharge. We developed a framework which accounts for the uncertainties from return period discharge, Manning's n, scouring depth, soil cohesion, and friction angle and enables the determination of dike failure probabilities for various failure modes such as overtopping, surface erosion, mass failure, toe sliding and overturning. The framework was applied to Chiu-She, Feng-Chou, and Ke-Chuang Dikes on Dajia River. The results indicate that the toe sliding or overturning has the highest probability than other failure modes. Furthermore, the overall failure probability (integrate different failure modes) reaches 50% under 10-years return period flood which agrees with the historical failure data for the study reaches.

Probability of loss of assured safety in temperature dependent systems with multiple weak and strong links.

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

Johnson, Jay Dean; Oberkampf, William Louis; Helton, Jon Craig

2004-12-01

Relationships to determine the probability that a weak link (WL)/strong link (SL) safety system will fail to function as intended in a fire environment are investigated. In the systems under study, failure of the WL system before failure of the SL system is intended to render the overall system inoperational and thus prevent the possible occurrence of accidents with potentially serious consequences. Formal developments of the probability that the WL system fails to deactivate the overall system before failure of the SL system (i.e., the probability of loss of assured safety, PLOAS) are presented for several WWSL configurations: (i) onemore » WL, one SL, (ii) multiple WLs, multiple SLs with failure of any SL before any WL constituting failure of the safety system, (iii) multiple WLs, multiple SLs with failure of all SLs before any WL constituting failure of the safety system, and (iv) multiple WLs, multiple SLs and multiple sublinks in each SL with failure of any sublink constituting failure of the associated SL and failure of all SLs before failure of any WL constituting failure of the safety system. The indicated probabilities derive from time-dependent temperatures in the WL/SL system and variability (i.e., aleatory uncertainty) in the temperatures at which the individual components of this system fail and are formally defined as multidimensional integrals. Numerical procedures based on quadrature (i.e., trapezoidal rule, Simpson's rule) and also on Monte Carlo techniques (i.e., simple random sampling, importance sampling) are described and illustrated for the evaluation of these integrals. Example uncertainty and sensitivity analyses for PLOAS involving the representation of uncertainty (i.e., epistemic uncertainty) with probability theory and also with evidence theory are presented.« less

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.

Effects of footwear and stride length on metatarsal strains and failure in running.

PubMed

Firminger, Colin R; Fung, Anita; Loundagin, Lindsay L; Edwards, W Brent

2017-11-01

The metatarsal bones of the foot are particularly susceptible to stress fracture owing to the high strains they experience during the stance phase of running. Shoe cushioning and stride length reduction represent two potential interventions to decrease metatarsal strain and thus stress fracture risk. Fourteen male recreational runners ran overground at a 5-km pace while motion capture and plantar pressure data were collected during four experimental conditions: traditional shoe at preferred and 90% preferred stride length, and minimalist shoe at preferred and 90% preferred stride length. Combined musculoskeletal - finite element modeling based on motion analysis and computed tomography data were used to quantify metatarsal strains and the probability of failure was determined using stress-life predictions. No significant interactions between footwear and stride length were observed. Running in minimalist shoes increased strains for all metatarsals by 28.7% (SD 6.4%; p<0.001) and probability of failure for metatarsals 2-4 by 17.3% (SD 14.3%; p≤0.005). Running at 90% preferred stride length decreased strains for metatarsal 4 by 4.2% (SD 2.0%; p≤0.007), and no differences in probability of failure were observed. Significant increases in metatarsal strains and the probability of failure were observed for recreational runners acutely transitioning to minimalist shoes. Running with a 10% reduction in stride length did not appear to be a beneficial technique for reducing the risk of metatarsal stress fracture, however the increased number of loading cycles for a given distance was not detrimental either. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effect of Endocrown Restorations with Different CAD/CAM Materials: 3D Finite Element and Weibull Analyses

PubMed Central

Ulusoy, Nuran

2017-01-01

The aim of this study was to evaluate the effects of two endocrown designs and computer aided design/manufacturing (CAD/CAM) materials on stress distribution and failure probability of restorations applied to severely damaged endodontically treated maxillary first premolar tooth (MFP). Two types of designs without and with 3 mm intraradicular extensions, endocrown (E) and modified endocrown (ME), were modeled on a 3D Finite element (FE) model of the MFP. Vitablocks Mark II (VMII), Vita Enamic (VE), and Lava Ultimate (LU) CAD/CAM materials were used for each type of design. von Mises and maximum principle values were evaluated and the Weibull function was incorporated with FE analysis to calculate the long term failure probability. Regarding the stresses that occurred in enamel, for each group of material, ME restoration design transmitted less stress than endocrown. During normal occlusal function, the overall failure probability was minimum for ME with VMII. ME restoration design with VE was the best restorative option for premolar teeth with extensive loss of coronal structure under high occlusal loads. Therefore, ME design could be a favorable treatment option for MFPs with missing palatal cusp. Among the CAD/CAM materials tested, VMII and VE were found to be more tooth-friendly than LU. PMID:29119108

Diagnostic reasoning techniques for selective monitoring

NASA Technical Reports Server (NTRS)

Homem-De-mello, L. S.; Doyle, R. J.

1991-01-01

An architecture for using diagnostic reasoning techniques in selective monitoring is presented. Given the sensor readings and a model of the physical system, a number of assertions are generated and expressed as Boolean equations. The resulting system of Boolean equations is solved symbolically. Using a priori probabilities of component failure and Bayes' rule, revised probabilities of failure can be computed. These will indicate what components have failed or are the most likely to have failed. This approach is suitable for systems that are well understood and for which the correctness of the assertions can be guaranteed. Also, the system must be such that changes are slow enough to allow the computation.

A Methodology for Modeling Nuclear Power Plant Passive Component Aging in Probabilistic Risk Assessment under the Impact of Operating Conditions, Surveillance and Maintenance Activities

NASA Astrophysics Data System (ADS)

Guler Yigitoglu, Askin

In the context of long operation of nuclear power plants (NPPs) (i.e., 60-80 years, and beyond), investigation of the aging of passive systems, structures and components (SSCs) is important to assess safety margins and to decide on reactor life extension as indicated within the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. In the traditional probabilistic risk assessment (PRA) methodology, evaluating the potential significance of aging of passive SSCs on plant risk is challenging. Although passive SSC failure rates can be added as initiating event frequencies or basic event failure rates in the traditional event-tree/fault-tree methodology, these failure rates are generally based on generic plant failure data which means that the true state of a specific plant is not reflected in a realistic manner on aging effects. Dynamic PRA methodologies have gained attention recently due to their capability to account for the plant state and thus address the difficulties in the traditional PRA modeling of aging effects of passive components using physics-based models (and also in the modeling of digital instrumentation and control systems). Physics-based models can capture the impact of complex aging processes (e.g., fatigue, stress corrosion cracking, flow-accelerated corrosion, etc.) on SSCs and can be utilized to estimate passive SSC failure rates using realistic NPP data from reactor simulation, as well as considering effects of surveillance and maintenance activities. The objectives of this dissertation are twofold: The development of a methodology for the incorporation of aging modeling of passive SSC into a reactor simulation environment to provide a framework for evaluation of their risk contribution in both the dynamic and traditional PRA; and the demonstration of the methodology through its application to pressurizer surge line pipe weld and steam generator tubes in commercial nuclear power plants. In the proposed methodology, a multi-state physics based model is selected to represent the aging process. The model is modified via sojourn time approach to reflect the operational and maintenance history dependence of the transition rates. Thermal-hydraulic parameters of the model are calculated via the reactor simulation environment and uncertainties associated with both parameters and the models are assessed via a two-loop Monte Carlo approach (Latin hypercube sampling) to propagate input probability distributions through the physical model. The effort documented in this thesis towards this overall objective consists of : i) defining a process for selecting critical passive components and related aging mechanisms, ii) aging model selection, iii) calculating the probability that aging would cause the component to fail, iv) uncertainty/sensitivity analyses, v) procedure development for modifying an existing PRA to accommodate consideration of passive component failures, and, vi) including the calculated failure probability in the modified PRA. The proposed methodology is applied to pressurizer surge line pipe weld aging and steam generator tube degradation in pressurized water reactors.

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.

Probabilistic confidence for decisions based on uncertain reliability estimates

NASA Astrophysics Data System (ADS)

Reid, Stuart G.

2013-05-01

Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.

Probabilistic risk assessment of the Space Shuttle. Phase 3: A study of the potential of losing the vehicle during nominal operation. Volume 2: Integrated loss of vehicle model

NASA Technical Reports Server (NTRS)

Fragola, Joseph R.; Maggio, Gaspare; Frank, Michael V.; Gerez, Luis; Mcfadden, Richard H.; Collins, Erin P.; Ballesio, Jorge; Appignani, Peter L.; Karns, James J.

1995-01-01

The application of the probabilistic risk assessment methodology to a Space Shuttle environment, particularly to the potential of losing the Shuttle during nominal operation is addressed. The different related concerns are identified and combined to determine overall program risks. A fault tree model is used to allocate system probabilities to the subsystem level. The loss of the vehicle due to failure to contain energetic gas and debris, to maintain proper propulsion and configuration is analyzed, along with the loss due to Orbiter, external tank failure, and landing failure or error.

An evidential reasoning extension to quantitative model-based failure diagnosis

NASA Technical Reports Server (NTRS)

Gertler, Janos J.; Anderson, Kenneth C.

1992-01-01

The detection and diagnosis of failures in physical systems characterized by continuous-time operation are studied. A quantitative diagnostic methodology has been developed that utilizes the mathematical model of the physical system. On the basis of the latter, diagnostic models are derived each of which comprises a set of orthogonal parity equations. To improve the robustness of the algorithm, several models may be used in parallel, providing potentially incomplete and/or conflicting inferences. Dempster's rule of combination is used to integrate evidence from the different models. The basic probability measures are assigned utilizing quantitative information extracted from the mathematical model and from online computation performed therewith.

Modeling and Simulating Multiple Failure Masking enabled by Local Recovery for Stencil-based Applications at Extreme Scales

DOE PAGES

Gamell, Marc; Teranishi, Keita; Mayo, Jackson; ...

2017-04-24

By obtaining multi-process hard failure resilience at the application level is a key challenge that must be overcome before the promise of exascale can be fully realized. Some previous work has shown that online global recovery can dramatically reduce the overhead of failures when compared to the more traditional approach of terminating the job and restarting it from the last stored checkpoint. If online recovery is performed in a local manner further scalability is enabled, not only due to the intrinsic lower costs of recovering locally, but also due to derived effects when using some application types. In this papermore » we model one such effect, namely multiple failure masking, that manifests when running Stencil parallel computations on an environment when failures are recovered locally. First, the delay propagation shape of one or multiple failures recovered locally is modeled to enable several analyses of the probability of different levels of failure masking under certain Stencil application behaviors. These results indicate that failure masking is an extremely desirable effect at scale which manifestation is more evident and beneficial as the machine size or the failure rate increase.« less

Modeling and Simulating Multiple Failure Masking enabled by Local Recovery for Stencil-based Applications at Extreme Scales

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

Gamell, Marc; Teranishi, Keita; Mayo, Jackson

By obtaining multi-process hard failure resilience at the application level is a key challenge that must be overcome before the promise of exascale can be fully realized. Some previous work has shown that online global recovery can dramatically reduce the overhead of failures when compared to the more traditional approach of terminating the job and restarting it from the last stored checkpoint. If online recovery is performed in a local manner further scalability is enabled, not only due to the intrinsic lower costs of recovering locally, but also due to derived effects when using some application types. In this papermore » we model one such effect, namely multiple failure masking, that manifests when running Stencil parallel computations on an environment when failures are recovered locally. First, the delay propagation shape of one or multiple failures recovered locally is modeled to enable several analyses of the probability of different levels of failure masking under certain Stencil application behaviors. These results indicate that failure masking is an extremely desirable effect at scale which manifestation is more evident and beneficial as the machine size or the failure rate increase.« less

The usefulness of administrative databases for identifying disease cohorts is increased with a multivariate model.

PubMed

van Walraven, Carl; Austin, Peter C; Manuel, Douglas; Knoll, Greg; Jennings, Allison; Forster, Alan J

2010-12-01

Administrative databases commonly use codes to indicate diagnoses. These codes alone are often inadequate to accurately identify patients with particular conditions. In this study, we determined whether we could quantify the probability that a person has a particular disease-in this case renal failure-using other routinely collected information available in an administrative data set. This would allow the accurate identification of a disease cohort in an administrative database. We determined whether patients in a randomly selected 100,000 hospitalizations had kidney disease (defined as two or more sequential serum creatinines or the single admission creatinine indicating a calculated glomerular filtration rate less than 60 mL/min/1.73 m²). The independent association of patient- and hospitalization-level variables with renal failure was measured using a multivariate logistic regression model in a random 50% sample of the patients. The model was validated in the remaining patients. Twenty thousand seven hundred thirteen patients had kidney disease (20.7%). A diagnostic code of kidney disease was strongly associated with kidney disease (relative risk: 34.4), but the accuracy of the code was poor (sensitivity: 37.9%; specificity: 98.9%). Twenty-nine patient- and hospitalization-level variables entered the kidney disease model. This model had excellent discrimination (c-statistic: 90.1%) and accurately predicted the probability of true renal failure. The probability threshold that maximized sensitivity and specificity for the identification of true kidney disease was 21.3% (sensitivity: 80.0%; specificity: 82.2%). Multiple variables available in administrative databases can be combined to quantify the probability that a person has a particular disease. This process permits accurate identification of a disease cohort in an administrative database. These methods may be extended to other diagnoses or procedures and could both facilitate and clarify the use of administrative databases for research and quality improvement. Copyright © 2010 Elsevier Inc. All rights reserved.

Estimation of reliability and dynamic property for polymeric material at high strain rate using SHPB technique and probability theory

NASA Astrophysics Data System (ADS)

Kim, Dong Hyeok; Lee, Ouk Sub; Kim, Hong Min; Choi, Hye Bin

2008-11-01

A modified Split Hopkinson Pressure Bar technique with aluminum pressure bars and a pulse shaper technique to achieve a closer impedance match between the pressure bars and the specimen materials such as hot temperature degraded POM (Poly Oxy Methylene) and PP (Poly Propylene). The more distinguishable experimental signals were obtained to evaluate the more accurate dynamic deformation behavior of materials under a high strain rate loading condition. A pulse shaping technique is introduced to reduce the non-equilibrium on the dynamic material response by modulation of the incident wave during a short period of test. This increases the rise time of the incident pulse in the SHPB experiment. For the dynamic stress strain curve obtained from SHPB experiment, the Johnson-Cook model is applied as a constitutive equation. The applicability of this constitutive equation is verified by using the probabilistic reliability estimation method. Two reliability methodologies such as the FORM and the SORM have been proposed. The limit state function(LSF) includes the Johnson-Cook model and applied stresses. The LSF in this study allows more statistical flexibility on the yield stress than a paper published before. It is found that the failure probability estimated by using the SORM is more reliable than those of the FORM/ It is also noted that the failure probability increases with increase of the applied stress. Moreover, it is also found that the parameters of Johnson-Cook model such as A and n, and the applied stress are found to affect the failure probability more severely than the other random variables according to the sensitivity analysis.

Risk management.

PubMed

Chambers, David W

2010-01-01

Every plan contains risk. To proceed without planning some means of managing that risk is to court failure. The basic logic of risk is explained. It consists in identifying a threshold where some corrective action is necessary, the probability of exceeding that threshold, and the attendant cost should the undesired outcome occur. This is the probable cost of failure. Various risk categories in dentistry are identified, including lack of liquidity; poor quality; equipment or procedure failures; employee slips; competitive environments; new regulations; unreliable suppliers, partners, and patients; and threats to one's reputation. It is prudent to make investments in risk management to the extent that the cost of managing the risk is less than the probable loss due to risk failure and when risk management strategies can be matched to type of risk. Four risk management strategies are discussed: insurance, reducing the probability of failure, reducing the costs of failure, and learning. A risk management accounting of the financial meltdown of October 2008 is provided.

Probabilistic safety analysis of earth retaining structures during earthquakes

NASA Astrophysics Data System (ADS)

Grivas, D. A.; Souflis, C.

1982-07-01

A procedure is presented for determining the probability of failure of Earth retaining structures under static or seismic conditions. Four possible modes of failure (overturning, base sliding, bearing capacity, and overall sliding) are examined and their combined effect is evaluated with the aid of combinatorial analysis. The probability of failure is shown to be a more adequate measure of safety than the customary factor of safety. As Earth retaining structures may fail in four distinct modes, a system analysis can provide a single estimate for the possibility of failure. A Bayesian formulation of the safety retaining walls is found to provide an improved measure for the predicted probability of failure under seismic loading. The presented Bayesian analysis can account for the damage incurred to a retaining wall during an earthquake to provide an improved estimate for its probability of failure during future seismic events.

Improving online risk assessment with equipment prognostics and health monitoring

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

Coble, Jamie B.; Liu, Xiaotong; Briere, Chris

The current approach to evaluating the risk of nuclear power plant (NPP) operation relies on static probabilities of component failure, which are based on industry experience with the existing fleet of nominally similar light water reactors (LWRs). As the nuclear industry looks to advanced reactor designs that feature non-light water coolants (e.g., liquid metal, high temperature gas, molten salt), this operating history is not available. Many advanced reactor designs use advanced components, such as electromagnetic pumps, that have not been used in the US commercial nuclear fleet. Given the lack of rich operating experience, we cannot accurately estimate the evolvingmore » probability of failure for basic components to populate the fault trees and event trees that typically comprise probabilistic risk assessment (PRA) models. Online equipment prognostics and health management (PHM) technologies can bridge this gap to estimate the failure probabilities for components under operation. The enhanced risk monitor (ERM) incorporates equipment condition assessment into the existing PRA and risk monitor framework to provide accurate and timely estimates of operational risk.« less

Bounding the Failure Probability Range of Polynomial Systems Subject to P-box Uncertainties

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2012-01-01

This paper proposes a reliability analysis framework for systems subject to multiple design requirements that depend polynomially on the uncertainty. Uncertainty is prescribed by probability boxes, also known as p-boxes, whose distribution functions have free or fixed functional forms. An approach based on the Bernstein expansion of polynomials and optimization is proposed. In particular, we search for the elements of a multi-dimensional p-box that minimize (i.e., the best-case) and maximize (i.e., the worst-case) the probability of inner and outer bounding sets of the failure domain. This technique yields intervals that bound the range of failure probabilities. The offset between this bounding interval and the actual failure probability range can be made arbitrarily tight with additional computational effort.

Modelling of Safety Instrumented Systems by using Bernoulli trials: towards the notion of odds on for SIS failures analysis

NASA Astrophysics Data System (ADS)

Cauffriez, Laurent

2017-01-01

This paper deals with the modeling of a random failures process of a Safety Instrumented System (SIS). It aims to identify the expected number of failures for a SIS during its lifecycle. Indeed, the fact that the SIS is a system being tested periodically gives the idea to apply Bernoulli trials to characterize the random failure process of a SIS and thus to verify if the PFD (Probability of Failing Dangerously) experimentally obtained agrees with the theoretical one. Moreover, the notion of "odds on" found in Bernoulli theory allows engineers and scientists determining easily the ratio between “outcomes with success: failure of SIS” and “outcomes with unsuccess: no failure of SIS” and to confirm that SIS failures occur sporadically. A Stochastic P-temporised Petri net is proposed and serves as a reference model for describing the failure process of a 1oo1 SIS architecture. Simulations of this stochastic Petri net demonstrate that, during its lifecycle, the SIS is rarely in a state in which it cannot perform its mission. Experimental results are compared to Bernoulli trials in order to validate the powerfulness of Bernoulli trials for the modeling of the failures process of a SIS. The determination of the expected number of failures for a SIS during its lifecycle opens interesting research perspectives for engineers and scientists by completing the notion of PFD.

Parameter estimation in Cox models with missing failure indicators and the OPPERA study.

PubMed

Brownstein, Naomi C; Cai, Jianwen; Slade, Gary D; Bair, Eric

2015-12-30

In a prospective cohort study, examining all participants for incidence of the condition of interest may be prohibitively expensive. For example, the "gold standard" for diagnosing temporomandibular disorder (TMD) is a physical examination by a trained clinician. In large studies, examining all participants in this manner is infeasible. Instead, it is common to use questionnaires to screen for incidence of TMD and perform the "gold standard" examination only on participants who screen positively. Unfortunately, some participants may leave the study before receiving the "gold standard" examination. Within the framework of survival analysis, this results in missing failure indicators. Motivated by the Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA) study, a large cohort study of TMD, we propose a method for parameter estimation in survival models with missing failure indicators. We estimate the probability of being an incident case for those lacking a "gold standard" examination using logistic regression. These estimated probabilities are used to generate multiple imputations of case status for each missing examination that are combined with observed data in appropriate regression models. The variance introduced by the procedure is estimated using multiple imputation. The method can be used to estimate both regression coefficients in Cox proportional hazard models as well as incidence rates using Poisson regression. We simulate data with missing failure indicators and show that our method performs as well as or better than competing methods. Finally, we apply the proposed method to data from the OPPERA study. Copyright © 2015 John Wiley & Sons, Ltd.

Failure Time Analysis of Office System Use.

ERIC Educational Resources Information Center

Cooper, Michael D.

1991-01-01

Develops mathematical models to characterize the probability of continued use of an integrated office automation system and tests these models on longitudinal data collected from 210 individuals using the IBM Professional Office System (PROFS) at the University of California at Berkeley. Analyses using survival functions and proportional hazard…

An integrated approach coupling physically based models and probabilistic method to assess quantitatively landslide susceptibility at different scale: application to different geomorphological environments

NASA Astrophysics Data System (ADS)

Vandromme, Rosalie; Thiéry, Yannick; Sedan, Olivier; Bernardie, Séverine

2016-04-01

Landslide hazard assessment is the estimation of a target area where landslides of a particular type, volume, runout and intensity may occur within a given period. The first step to analyze landslide hazard consists in assessing the spatial and temporal failure probability (when the information is available, i.e. susceptibility assessment). Two types of approach are generally recommended to achieve this goal: (i) qualitative approach (i.e. inventory based methods and knowledge data driven methods) and (ii) quantitative approach (i.e. data-driven methods or deterministic physically based methods). Among quantitative approaches, deterministic physically based methods (PBM) are generally used at local and/or site-specific scales (1:5,000-1:25,000 and >1:5,000, respectively). The main advantage of these methods is the calculation of probability of failure (safety factor) following some specific environmental conditions. For some models it is possible to integrate the land-uses and climatic change. At the opposite, major drawbacks are the large amounts of reliable and detailed data (especially materials type, their thickness and the geotechnical parameters heterogeneity over a large area) and the fact that only shallow landslides are taking into account. This is why they are often used at site-specific scales (> 1:5,000). Thus, to take into account (i) materials' heterogeneity , (ii) spatial variation of physical parameters, (iii) different landslide types, the French Geological Survey (i.e. BRGM) has developed a physically based model (PBM) implemented in a GIS environment. This PBM couples a global hydrological model (GARDENIA®) including a transient unsaturated/saturated hydrological component with a physically based model computing the stability of slopes (ALICE®, Assessment of Landslides Induced by Climatic Events) based on the Morgenstern-Price method for any slip surface. The variability of mechanical parameters is handled by Monte Carlo approach. The probability to obtain a safety factor below 1 represents the probability of occurrence of a landslide for a given triggering event. The dispersion of the distribution gives the uncertainty of the result. Finally, a map is created, displaying a probability of occurrence for each computing cell of the studied area. In order to take into account the land-uses change, a complementary module integrating the vegetation effects on soil properties has been recently developed. Last years, the model has been applied at different scales for different geomorphological environments: (i) at regional scale (1:50,000-1:25,000) in French West Indies and French Polynesian islands (ii) at local scale (i.e.1:10,000) for two complex mountainous areas; (iii) at the site-specific scale (1:2,000) for one landslide. For each study the 3D geotechnical model has been adapted. The different studies have allowed : (i) to discuss the different factors included in the model especially the initial 3D geotechnical models; (ii) to precise the location of probable failure following different hydrological scenarii; (iii) to test the effects of climatic change and land-use on slopes for two cases. In that way, future changes in temperature, precipitation and vegetation cover can be analyzed, permitting to address the impacts of global change on landslides. Finally, results show that it is possible to obtain reliable information about future slope failures at different scale of work for different scenarii with an integrated approach. The final information about landslide susceptibility (i.e. probability of failure) can be integrated in landslide hazard assessment and could be an essential information source for future land planning. As it has been performed in the ANR Project SAMCO (Society Adaptation for coping with Mountain risks in a global change COntext), this analysis constitutes a first step in the chain for risk assessment for different climate and economical development scenarios, to evaluate the resilience of mountainous areas.

The Failure Models of Lead Free Sn-3.0Ag-0.5Cu Solder Joint Reliability Under Low-G and High-G Drop Impact

NASA Astrophysics Data System (ADS)

Gu, Jian; Lei, YongPing; Lin, Jian; Fu, HanGuang; Wu, Zhongwei

2017-02-01

The reliability of Sn-3.0Ag-0.5Cu (SAC 305) solder joint under a broad level of drop impacts was studied. The failure performance of solder joint, failure probability and failure position were analyzed under two shock test conditions, i.e., 1000 g for 1 ms and 300 g for 2 ms. The stress distribution on the solder joint was calculated by ABAQUS. The results revealed that the dominant reason was the tension due to the difference in stiffness between the print circuit board and ball grid array, and the maximum tension of 121.1 MPa and 31.1 MPa, respectively, under both 1000 g or 300 g drop impact, was focused on the corner of the solder joint which was located in the outmost corner of the solder ball row. The failure modes were summarized into the following four modes: initiation and propagation through the (1) intermetallic compound layer, (2) Ni layer, (3) Cu pad, or (4) Sn-matrix. The outmost corner of the solder ball row had a high failure probability under both 1000 g and 300 g drop impact. The number of failures of solder ball under the 300 g drop impact was higher than that under the 1000 g drop impact. The characteristic drop values for failure were 41 and 15,199, respectively, following the statistics.

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.

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

Tom Elicson; Bentley Harwood; Jim Bouchard

Over a 12 month period, a fire PRA was developed for a DOE facility using the NUREG/CR-6850 EPRI/NRC fire PRA methodology. The fire PRA modeling included calculation of fire severity factors (SFs) and fire non-suppression probabilities (PNS) for each safe shutdown (SSD) component considered in the fire PRA model. The SFs were developed by performing detailed fire modeling through a combination of CFAST fire zone model calculations and Latin Hypercube Sampling (LHS). Component damage times and automatic fire suppression system actuation times calculated in the CFAST LHS analyses were then input to a time-dependent model of fire non-suppression probability. Themore » fire non-suppression probability model is based on the modeling approach outlined in NUREG/CR-6850 and is supplemented with plant specific data. This paper presents the methodology used in the DOE facility fire PRA for modeling fire-induced SSD component failures and includes discussions of modeling techniques for: • Development of time-dependent fire heat release rate profiles (required as input to CFAST), • Calculation of fire severity factors based on CFAST detailed fire modeling, and • Calculation of fire non-suppression probabilities.« less

Modeling of a bubble-memory organization with self-checking translators to achieve high reliability.

NASA Technical Reports Server (NTRS)

Bouricius, W. G.; Carter, W. C.; Hsieh, E. P.; Wadia, A. B.; Jessep, D. C., Jr.

1973-01-01

Study of the design and modeling of a highly reliable bubble-memory system that has the capabilities of: (1) correcting a single 16-adjacent bit-group error resulting from failures in a single basic storage module (BSM), and (2) detecting with a probability greater than 0.99 any double errors resulting from failures in BSM's. The results of the study justify the design philosophy adopted of employing memory data encoding and a translator to correct single group errors and detect double group errors to enhance the overall system reliability.

The influence of protection system failures and preventive maintenance on protection systems in distribution systems

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

Meeuwsen, J.J.; Kling, W.L.; Ploem, W.A.G.A.

1997-01-01

Protection systems in power systems can fail either by not responding when they should (failure to operate) or by operating when they should not (false tripping). The former type of failure is particularly serious since it may result in the isolation of large sections of the network. However, the probability of a failure to operate can be reduced by carrying out preventive maintenance on protection systems. This paper describes an approach to determine the impact of preventive maintenance on protection systems on the reliability of the power supply to customers. The proposed approach is based on Markov models.

Methods to assess performance of models estimating risk of death in intensive care patients: a review.

PubMed

Cook, D A

2006-04-01

Models that estimate the probability of death of intensive care unit patients can be used to stratify patients according to the severity of their condition and to control for casemix and severity of illness. These models have been used for risk adjustment in quality monitoring, administration, management and research and as an aid to clinical decision making. Models such as the Mortality Prediction Model family, SAPS II, APACHE II, APACHE III and the organ system failure models provide estimates of the probability of in-hospital death of ICU patients. This review examines methods to assess the performance of these models. The key attributes of a model are discrimination (the accuracy of the ranking in order of probability of death) and calibration (the extent to which the model's prediction of probability of death reflects the true risk of death). These attributes should be assessed in existing models that predict the probability of patient mortality, and in any subsequent model that is developed for the purposes of estimating these probabilities. The literature contains a range of approaches for assessment which are reviewed and a survey of the methodologies used in studies of intensive care mortality models is presented. The systematic approach used by Standards for Reporting Diagnostic Accuracy provides a framework to incorporate these theoretical considerations of model assessment and recommendations are made for evaluation and presentation of the performance of models that estimate the probability of death of intensive care patients.

The effect of delayed graft function on graft and patient survival in kidney transplantation: an approach using competing events analysis.

PubMed

Fonseca, Isabel; Teixeira, Laetitia; Malheiro, Jorge; Martins, La Salete; Dias, Leonídio; Castro Henriques, António; Mendonça, Denisa

2015-06-01

In kidney transplantation, the impact of delayed graft function (DGF) on long-term graft and patient survival is controversial. We examined the impact of DGF on graft and recipient survival by accounting for the possibility that death with graft function may act as a competing risk for allograft failure. We used data from 1281 adult primary deceased-donor kidney recipients whose allografts functioned at least 1 year. The probability of graft loss occurrence is overestimated using the complement of Kaplan-Meier estimates (1-KM). Both the cause-specific Cox proportional hazard regression model (standard Cox) and the subdistribution hazard regression model proposed by Fine and Gray showed that DGF was associated with shorter time to graft failure (csHR = 2.0, P = 0.002; sHR = 1.57, P = 0.009), independent of acute rejection (AR) and after adjusting for traditional factors associated with graft failure. Regarding patient survival, DGF was a predictor of patient death using the cause-specific Cox model (csHR = 1.57, P = 0.029) but not using the subdistribution model. The probability of graft loss from competing end points should not be reported with the 1-KM. Application of a regression model for subdistribution hazard showed that, independent of AR, DGF has a detrimental effect on long-term graft survival, but not on patient survival. © 2015 Steunstichting ESOT.

Assessing changes in failure probability of dams in a changing climate

NASA Astrophysics Data System (ADS)

Mallakpour, I.; AghaKouchak, A.; Moftakhari, H.; Ragno, E.

2017-12-01

Dams are crucial infrastructures and provide resilience against hydrometeorological extremes (e.g., droughts and floods). In 2017, California experienced series of flooding events terminating a 5-year drought, and leading to incidents such as structural failure of Oroville Dam's spillway. Because of large socioeconomic repercussions of such incidents, it is of paramount importance to evaluate dam failure risks associated with projected shifts in the streamflow regime. This becomes even more important as the current procedures for design of hydraulic structures (e.g., dams, bridges, spillways) are based on the so-called stationary assumption. Yet, changes in climate are anticipated to result in changes in statistics of river flow (e.g., more extreme floods) and possibly increasing the failure probability of already aging dams. Here, we examine changes in discharge under two representative concentration pathways (RCPs): RCP4.5 and RCP8.5. In this study, we used routed daily streamflow data from ten global climate models (GCMs) in order to investigate possible climate-induced changes in streamflow in northern California. Our results show that while the average flow does not show a significant change, extreme floods are projected to increase in the future. Using the extreme value theory, we estimate changes in the return periods of 50-year and 100-year floods in the current and future climates. Finally, we use the historical and future return periods to quantify changes in failure probability of dams in a warming climate.

Performance evaluation of the croissant production line with reparable machines

NASA Astrophysics Data System (ADS)

Tsarouhas, Panagiotis H.

2015-03-01

In this study, the analytical probability models for an automated serial production system, bufferless that consists of n-machines in series with common transfer mechanism and control system was developed. Both time to failure and time to repair a failure are assumed to follow exponential distribution. Applying those models, the effect of system parameters on system performance in actual croissant production line was studied. The production line consists of six workstations with different numbers of reparable machines in series. Mathematical models of the croissant production line have been developed using Markov process. The strength of this study is in the classification of the whole system in states, representing failures of different machines. Failure and repair data from the actual production environment have been used to estimate reliability and maintainability for each machine, workstation, and the entire line is based on analytical models. The analysis provides a useful insight into the system's behaviour, helps to find design inherent faults and suggests optimal modifications to upgrade the system and improve its performance.

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.

Estimating distributions with increasing failure rate in an imperfect repair model.

PubMed

Kvam, Paul H; Singh, Harshinder; Whitaker, Lyn R

2002-03-01

A failed system is repaired minimally if after failure, it is restored to the working condition of an identical system of the same age. We extend the nonparametric maximum likelihood estimator (MLE) of a system's lifetime distribution function to test units that are known to have an increasing failure rate. Such items comprise a significant portion of working components in industry. The order-restricted MLE is shown to be consistent. Similar results hold for the Brown-Proschan imperfect repair model, which dictates that a failed component is repaired perfectly with some unknown probability, and is otherwise repaired minimally. The estimators derived are motivated and illustrated by failure data in the nuclear industry. Failure times for groups of emergency diesel generators and motor-driven pumps are analyzed using the order-restricted methods. The order-restricted estimators are consistent and show distinct differences from the ordinary MLEs. Simulation results suggest significant improvement in reliability estimation is available in many cases when component failure data exhibit the IFR property.

Systems Biology and Biomechanical Model of Heart Failure

PubMed Central

Louridas, George E; Lourida, Katerina G

2012-01-01

Heart failure is seen as a complex disease caused by a combination of a mechanical disorder, cardiac remodeling and neurohormonal activation. To define heart failure the systems biology approach integrates genes and molecules, interprets the relationship of the molecular networks with modular functional units, and explains the interaction between mechanical dysfunction and cardiac remodeling. The biomechanical model of heart failure explains satisfactorily the progression of myocardial dysfunction and the development of clinical phenotypes. The earliest mechanical changes and stresses applied in myocardial cells and/or myocardial loss or dysfunction activate left ventricular cavity remodeling and other neurohormonal regulatory mechanisms such as early release of natriuretic peptides followed by SAS and RAAS mobilization. Eventually the neurohormonal activation and the left ventricular remodeling process are leading to clinical deterioration of heart failure towards a multi-organic damage. It is hypothesized that approaching heart failure with the methodology of systems biology we promote the elucidation of its complex pathophysiology and most probably we can invent new therapeutic strategies. PMID:22935019

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Fault tolerant system with imperfect coverage, reboot and server vacation

NASA Astrophysics Data System (ADS)

Jain, Madhu; Meena, Rakesh Kumar

2017-06-01

This study is concerned with the performance modeling of a fault tolerant system consisting of operating units supported by a combination of warm and cold spares. The on-line as well as warm standby units are subject to failures and are send for the repair to a repair facility having single repairman which is prone to failure. If the failed unit is not detected, the system enters into an unsafe state from which it is cleared by the reboot and recovery action. The server is allowed to go for vacation if there is no failed unit present in the system. Markov model is developed to obtain the transient probabilities associated with the system states. Runge-Kutta method is used to evaluate the system state probabilities and queueing measures. To explore the sensitivity and cost associated with the system, numerical simulation is conducted.

Transient queue-size distribution in a finite-capacity queueing system with server breakdowns and Bernoulli feedback

NASA Astrophysics Data System (ADS)

Kempa, Wojciech M.

2017-12-01

A finite-capacity queueing system with server breakdowns is investigated, in which successive exponentially distributed failure-free times are followed by repair periods. After the processing a customer may either rejoin the queue (feedback) with probability q, or definitely leave the system with probability 1 - q. The system of integral equations for transient queue-size distribution, conditioned by the initial level of buffer saturation, is build. The solution of the corresponding system written for Laplace transforms is found using the linear algebraic approach. The considered queueing system can be successfully used in modelling production lines with machine failures, in which the parameter q may be considered as a typical fraction of items demanding corrections. Morever, this queueing model can be applied in the analysis of real TCP/IP performance, where q stands for the fraction of packets requiring retransmission.

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

Ebeida, Mohamed S.; Mitchell, Scott A.; Swiler, Laura P.

We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink,more » improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.« less

Contraceptive failure in the United States

PubMed Central

Trussell, James

2013-01-01

This review provides an update of previous estimates of first-year probabilities of contraceptive failure for all methods of contraception available in the United States. Estimates are provided of probabilities of failure during typical use (which includes both incorrect and inconsistent use) and during perfect use (correct and consistent use). The difference between these two probabilities reveals the consequences of imperfect use; it depends both on how unforgiving of imperfect use a method is and on how hard it is to use that method perfectly. These revisions reflect new research on contraceptive failure both during perfect use and during typical use. PMID:21477680

Estimation of the lower and upper bounds on the probability of failure using subset simulation and random set theory

NASA Astrophysics Data System (ADS)

Alvarez, Diego A.; Uribe, Felipe; Hurtado, Jorge E.

2018-02-01

Random set theory is a general framework which comprises uncertainty in the form of probability boxes, possibility distributions, cumulative distribution functions, Dempster-Shafer structures or intervals; in addition, the dependence between the input variables can be expressed using copulas. In this paper, the lower and upper bounds on the probability of failure are calculated by means of random set theory. In order to accelerate the calculation, a well-known and efficient probability-based reliability method known as subset simulation is employed. This method is especially useful for finding small failure probabilities in both low- and high-dimensional spaces, disjoint failure domains and nonlinear limit state functions. The proposed methodology represents a drastic reduction of the computational labor implied by plain Monte Carlo simulation for problems defined with a mixture of representations for the input variables, while delivering similar results. Numerical examples illustrate the efficiency of the proposed approach.

Advances on the Failure Analysis of the Dam-Foundation Interface of Concrete Dams.

PubMed

Altarejos-García, Luis; Escuder-Bueno, Ignacio; Morales-Torres, Adrián

2015-12-02

Failure analysis of the dam-foundation interface in concrete dams is characterized by complexity, uncertainties on models and parameters, and a strong non-linear softening behavior. In practice, these uncertainties are dealt with a well-structured mixture of experience, best practices and prudent, conservative design approaches based on the safety factor concept. Yet, a sound, deep knowledge of some aspects of this failure mode remain unveiled, as they have been offset in practical applications by the use of this conservative approach. In this paper we show a strategy to analyse this failure mode under a reliability-based approach. The proposed methodology of analysis integrates epistemic uncertainty on spatial variability of strength parameters and data from dam monitoring. The purpose is to produce meaningful and useful information regarding the probability of occurrence of this failure mode that can be incorporated in risk-informed dam safety reviews. In addition, relationships between probability of failure and factors of safety are obtained. This research is supported by a more than a decade of intensive professional practice on real world cases and its final purpose is to bring some clarity, guidance and to contribute to the improvement of current knowledge and best practices on such an important dam safety concern.

Advances on the Failure Analysis of the Dam—Foundation Interface of Concrete Dams

PubMed Central

Altarejos-García, Luis; Escuder-Bueno, Ignacio; Morales-Torres, Adrián

2015-01-01

Failure analysis of the dam-foundation interface in concrete dams is characterized by complexity, uncertainties on models and parameters, and a strong non-linear softening behavior. In practice, these uncertainties are dealt with a well-structured mixture of experience, best practices and prudent, conservative design approaches based on the safety factor concept. Yet, a sound, deep knowledge of some aspects of this failure mode remain unveiled, as they have been offset in practical applications by the use of this conservative approach. In this paper we show a strategy to analyse this failure mode under a reliability-based approach. The proposed methodology of analysis integrates epistemic uncertainty on spatial variability of strength parameters and data from dam monitoring. The purpose is to produce meaningful and useful information regarding the probability of occurrence of this failure mode that can be incorporated in risk-informed dam safety reviews. In addition, relationships between probability of failure and factors of safety are obtained. This research is supported by a more than a decade of intensive professional practice on real world cases and its final purpose is to bring some clarity, guidance and to contribute to the improvement of current knowledge and best practices on such an important dam safety concern. PMID:28793709

Analysis of Emergency Diesel Generators Failure Incidents in Nuclear Power Plants

NASA Astrophysics Data System (ADS)

Hunt, Ronderio LaDavis

In early years of operation, emergency diesel generators have had a minimal rate of demand failures. Emergency diesel generators are designed to operate as a backup when the main source of electricity has been disrupted. As of late, EDGs (emergency diesel generators) have been failing at NPPs (nuclear power plants) around the United States causing either station blackouts or loss of onsite and offsite power. These failures occurred from a specific type called demand failures. This thesis evaluated the current problem that raised concern in the nuclear industry which was averaging 1 EDG demand failure/year in 1997 to having an excessive event of 4 EDG demand failure year which occurred in 2011. To determine the next occurrence of the extreme event and possible cause to an event of such happening, two analyses were conducted, the statistical and root cause analysis. Considering the statistical analysis in which an extreme event probability approach was applied to determine the next occurrence year of an excessive event as well as, the probability of that excessive event occurring. Using the root cause analysis in which the potential causes of the excessive event occurred by evaluating, the EDG manufacturers, aging, policy changes/ maintenance practices and failure components. The root cause analysis investigated the correlation between demand failure data and historical data. Final results from the statistical analysis showed expectations of an excessive event occurring in a fixed range of probability and a wider range of probability from the extreme event probability approach. The root-cause analysis of the demand failure data followed historical statistics for the EDG manufacturer, aging and policy changes/ maintenance practices but, indicated a possible cause regarding the excessive event with the failure components. Conclusions showed the next excessive demand failure year, prediction of the probability and the next occurrence year of such failures, with an acceptable confidence level, was difficult but, it was likely that this type of failure will not be a 100 year event. It was noticeable to see that the majority of the EDG demand failures occurred within the main components as of 2005. The overall analysis of this study provided from percentages, indicated that it would be appropriate to make the statement that the excessive event was caused by the overall age (wear and tear) of the Emergency Diesel Generators in Nuclear Power Plants. Future Work will be to better determine the return period of the excessive event once the occurrence has happened for a second time by implementing the extreme event probability approach.

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.

Comprehensive, Quantitative Risk Assessment of CO{sub 2} Geologic Sequestration

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

Lepinski, James

2013-09-30

A Quantitative Failure Modes and Effects Analysis (QFMEA) was developed to conduct comprehensive, quantitative risk assessments on CO{sub 2} capture, transportation, and sequestration or use in deep saline aquifers, enhanced oil recovery operations, or enhanced coal bed methane operations. The model identifies and characterizes potential risks; identifies the likely failure modes, causes, effects and methods of detection; lists possible risk prevention and risk mitigation steps; estimates potential damage recovery costs, mitigation costs and costs savings resulting from mitigation; and ranks (prioritizes) risks according to the probability of failure, the severity of failure, the difficulty of early failure detection and themore » potential for fatalities. The QFMEA model generates the necessary information needed for effective project risk management. Diverse project information can be integrated into a concise, common format that allows comprehensive, quantitative analysis, by a cross-functional team of experts, to determine: What can possibly go wrong? How much will damage recovery cost? How can it be prevented or mitigated? What is the cost savings or benefit of prevention or mitigation? Which risks should be given highest priority for resolution? The QFMEA model can be tailored to specific projects and is applicable to new projects as well as mature projects. The model can be revised and updated as new information comes available. It accepts input from multiple sources, such as literature searches, site characterization, field data, computer simulations, analogues, process influence diagrams, probability density functions, financial analysis models, cost factors, and heuristic best practices manuals, and converts the information into a standardized format in an Excel spreadsheet. Process influence diagrams, geologic models, financial models, cost factors and an insurance schedule were developed to support the QFMEA model. Comprehensive, quantitative risk assessments were conducted on three (3) sites using the QFMEA model: (1) SACROC Northern Platform CO{sub 2}-EOR Site in the Permian Basin, Scurry County, TX, (2) Pump Canyon CO{sub 2}-ECBM Site in the San Juan Basin, San Juan County, NM, and (3) Farnsworth Unit CO{sub 2}-EOR Site in the Anadarko Basin, Ochiltree County, TX. The sites were sufficiently different from each other to test the robustness of the QFMEA model.« less

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.

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.

A stochastic model for soft tissue failure using acoustic emission data.

PubMed

Sánchez-Molina, D; Martínez-González, E; Velázquez-Ameijide, J; Llumà, J; Rebollo Soria, M C; Arregui-Dalmases, C

2015-11-01

The strength of soft tissues is due mainly to collagen fibers. In most collagenous tissues, the arrangement of the fibers is random, but has preferred directions. The random arrangement makes it difficult to make deterministic predictions about the starting process of fiber breaking under tension. When subjected to tensile stress the fibers are progressively straighten out and then start to be stretched. At the beginning of fiber breaking, some of the fibers reach their maximum tensile strength and break down while some others remain unstressed (this latter fibers will assume then bigger stress until they eventually arrive to their failure point). In this study, a sample of human esophagi was subjected to a tensile breaking of fibers, up to the complete failure of the specimen. An experimental setup using Acoustic Emission to detect the elastic energy released is used during the test to detect the location of the emissions and the number of micro-failures per time unit. The data were statistically analyzed in order to be compared to a stochastic model which relates the level of stress in the tissue and the probability of breaking given the number of previously broken fibers (i.e. the deterioration in the tissue). The probability of a fiber breaking as the stretch increases in the tissue can be represented by a non-homogeneous Markov process which is the basis of the stochastic model proposed. This paper shows that a two-parameter model can account for the fiber breaking and the expected distribution for ultimate stress is a Fréchet distribution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Probabilistic structural analysis of aerospace components using NESSUS

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Nagpal, Vinod K.; Chamis, Christos C.

1988-01-01

Probabilistic structural analysis of a Space Shuttle main engine turbopump blade is conducted using the computer code NESSUS (numerical evaluation of stochastic structures under stress). The goal of the analysis is to derive probabilistic characteristics of blade response given probabilistic descriptions of uncertainties in blade geometry, material properties, and temperature and pressure distributions. Probability densities are derived for critical blade responses. Risk assessment and failure life analysis is conducted assuming different failure models.

Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

NASA Technical Reports Server (NTRS)

Iverson, David L.; George, Laurence L.; Patterson-Hine, F. A.; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.

Fishnet statistics for probabilistic strength and scaling of nacreous imbricated lamellar materials

NASA Astrophysics Data System (ADS)

Luo, Wen; Bažant, Zdeněk P.

2017-12-01

Similar to nacre (or brick masonry), imbricated (or staggered) lamellar structures are widely found in nature and man-made materials, and are of interest for biomimetics. They can achieve high defect insensitivity and fracture toughness, as demonstrated in previous studies. But the probability distribution with a realistic far-left tail is apparently unknown. Here, strictly for statistical purposes, the microstructure of nacre is approximated by a diagonally pulled fishnet with quasibrittle links representing the shear bonds between parallel lamellae (or platelets). The probability distribution of fishnet strength is calculated as a sum of a rapidly convergent series of the failure probabilities after the rupture of one, two, three, etc., links. Each of them represents a combination of joint probabilities and of additive probabilities of disjoint events, modified near the zone of failed links by the stress redistributions caused by previously failed links. Based on previous nano- and multi-scale studies at Northwestern, the strength distribution of each link, characterizing the interlamellar shear bond, is assumed to be a Gauss-Weibull graft, but with a deeper Weibull tail than in Type 1 failure of non-imbricated quasibrittle materials. The autocorrelation length is considered equal to the link length. The size of the zone of failed links at maximum load increases with the coefficient of variation (CoV) of link strength, and also with fishnet size. With an increasing width-to-length aspect ratio, a rectangular fishnet gradually transits from the weakest-link chain to the fiber bundle, as the limit cases. The fishnet strength at failure probability 10-6 grows with the width-to-length ratio. For a square fishnet boundary, the strength at 10-6 failure probability is about 11% higher, while at fixed load the failure probability is about 25-times higher than it is for the non-imbricated case. This is a major safety advantage of the fishnet architecture over particulate or fiber reinforced materials. There is also a strong size effect, partly similar to that of Type 1 while the curves of log-strength versus log-size for different sizes could cross each other. The predicted behavior is verified by about a million Monte Carlo simulations for each of many fishnet geometries, sizes and CoVs of link strength. In addition to the weakest-link or fiber bundle, the fishnet becomes the third analytically tractable statistical model of structural strength, and has the former two as limit cases.

Defense Strategies for Asymmetric Networked Systems with Discrete Components.

PubMed

Rao, Nageswara S V; Ma, Chris Y T; Hausken, Kjell; He, Fei; Yau, David K Y; Zhuang, Jun

2018-05-03

We consider infrastructures consisting of a network of systems, each composed of discrete components. The network provides the vital connectivity between the systems and hence plays a critical, asymmetric role in the infrastructure operations. The individual components of the systems can be attacked by cyber and physical means and can be appropriately reinforced to withstand these attacks. We formulate the problem of ensuring the infrastructure performance as a game between an attacker and a provider, who choose the numbers of the components of the systems and network to attack and reinforce, respectively. The costs and benefits of attacks and reinforcements are characterized using the sum-form, product-form and composite utility functions, each composed of a survival probability term and a component cost term. We present a two-level characterization of the correlations within the infrastructure: (i) the aggregate failure correlation function specifies the infrastructure failure probability given the failure of an individual system or network, and (ii) the survival probabilities of the systems and network satisfy first-order differential conditions that capture the component-level correlations using multiplier functions. We derive Nash equilibrium conditions that provide expressions for individual system survival probabilities and also the expected infrastructure capacity specified by the total number of operational components. We apply these results to derive and analyze defense strategies for distributed cloud computing infrastructures using cyber-physical models.

Defense Strategies for Asymmetric Networked Systems with Discrete Components

PubMed Central

Rao, Nageswara S. V.; Ma, Chris Y. T.; Hausken, Kjell; He, Fei; Yau, David K. Y.

2018-01-01

We consider infrastructures consisting of a network of systems, each composed of discrete components. The network provides the vital connectivity between the systems and hence plays a critical, asymmetric role in the infrastructure operations. The individual components of the systems can be attacked by cyber and physical means and can be appropriately reinforced to withstand these attacks. We formulate the problem of ensuring the infrastructure performance as a game between an attacker and a provider, who choose the numbers of the components of the systems and network to attack and reinforce, respectively. The costs and benefits of attacks and reinforcements are characterized using the sum-form, product-form and composite utility functions, each composed of a survival probability term and a component cost term. We present a two-level characterization of the correlations within the infrastructure: (i) the aggregate failure correlation function specifies the infrastructure failure probability given the failure of an individual system or network, and (ii) the survival probabilities of the systems and network satisfy first-order differential conditions that capture the component-level correlations using multiplier functions. We derive Nash equilibrium conditions that provide expressions for individual system survival probabilities and also the expected infrastructure capacity specified by the total number of operational components. We apply these results to derive and analyze defense strategies for distributed cloud computing infrastructures using cyber-physical models. PMID:29751588

Allocating risk capital for a brownfields redevelopment project under hydrogeological and financial uncertainty.

PubMed

Yu, Soonyoung; Unger, Andre J A; Parker, Beth; Kim, Taehee

2012-06-15

In this study, we defined risk capital as the contingency fee or insurance premium that a brownfields redeveloper needs to set aside from the sale of each house in case they need to repurchase it at a later date because the indoor air has been detrimentally affected by subsurface contamination. The likelihood that indoor air concentrations will exceed a regulatory level subject to subsurface heterogeneity and source zone location uncertainty is simulated by a physics-based hydrogeological model using Monte Carlo realizations, yielding the probability of failure. The cost of failure is the future value of the house indexed to the stochastic US National Housing index. The risk capital is essentially the probability of failure times the cost of failure with a surcharge to compensate the developer against hydrogeological and financial uncertainty, with the surcharge acting as safety loading reflecting the developers' level of risk aversion. We review five methodologies taken from the actuarial and financial literature to price the risk capital for a highly stylized brownfield redevelopment project, with each method specifically adapted to accommodate our notion of the probability of failure. The objective of this paper is to develop an actuarially consistent approach for combining the hydrogeological and financial uncertainty into a contingency fee that the brownfields developer should reserve (i.e. the risk capital) in order to hedge their risk exposure during the project. Results indicate that the price of the risk capital is much more sensitive to hydrogeological rather than financial uncertainty. We use the Capital Asset Pricing Model to estimate the risk-adjusted discount rate to depreciate all costs to present value for the brownfield redevelopment project. A key outcome of this work is that the presentation of our risk capital valuation methodology is sufficiently generalized for application to a wide variety of engineering projects. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Comments on the use of the "life-table method" in orthopedics].

PubMed

Hassenpflug, J; Hahne, H J; Hedderich, J

1992-01-01

In the description of long term results, e.g. of joint replacements, survivorship analysis is used increasingly in orthopaedic surgery. The survivorship analysis is more useful to describe the frequency of failure rather than global statements in percentage. The relative probability of failure for fixed intervals is drawn from the number of controlled patients and the frequency of failure. The complementary probabilities of success are linked in their temporal sequence thus representing the probability of survival at a fixed endpoint. Necessary condition for the use of this procedure is the exact definition of moment and manner of failure. It is described how to establish survivorship tables.

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).

AGR-3/4 Irradiation Test Predictions using PARFUME

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

Skerjanc, William Frances; Collin, Blaise Paul

2016-03-01

PARFUME, a fuel performance modeling code used for high temperature gas reactors, was used to model the AGR-3/4 irradiation test using as-run physics and thermal hydraulics data. The AGR-3/4 test is the combined third and fourth planned irradiations of the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program. The AGR-3/4 test train consists of twelve separate and independently controlled and monitored capsules. Each capsule contains four compacts filled with both uranium oxycarbide (UCO) unaltered “driver” fuel particles and UCO designed-to-fail (DTF) fuel particles. The DTF fraction was specified to be 1×10-2. This report documents the calculations performed to predictmore » failure probability of TRISO-coated fuel particles during the AGR-3/4 experiment. In addition, this report documents the calculated source term from both the driver fuel and DTF particles. The calculations include the modeling of the AGR-3/4 irradiation that occurred from December 2011 to April 2014 in the Advanced Test Reactor (ATR) over a total of ten ATR cycles including seven normal cycles, one low power cycle, one unplanned outage cycle, and one Power Axial Locator Mechanism cycle. Results show that failure probabilities are predicted to be low, resulting in zero fuel particle failures per capsule. The primary fuel particle failure mechanism occurred as a result of localized stresses induced by the calculated IPyC cracking. Assuming 1,872 driver fuel particles per compact, failure probability calculated by PARFUME leads to no predicted particle failure in the AGR-3/4 driver fuel. In addition, the release fraction of fission products Ag, Cs, and Sr were calculated to vary depending on capsule location and irradiation temperature. The maximum release fraction of Ag occurs in Capsule 7 reaching up to 56% for the driver fuel and 100% for the DTF fuel. The release fraction of the other two fission products, Cs and Sr, are much smaller and in most cases less than 1% for the driver fuel. The notable exception occurs in Capsule 7 where the release fraction for Cs and Sr reach up to 0.73% and 2.4%, respectively, for the driver fuel. For the DTF fuel in Capsule 7, the release fraction for Cs and Sr are estimated to be 100% and 5%, respectively.« less

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.

Reliability growth modeling analysis of the space shuttle main engines based upon the Weibull process

NASA Technical Reports Server (NTRS)

Wheeler, J. T.

1990-01-01

The Weibull process, identified as the inhomogeneous Poisson process with the Weibull intensity function, is used to model the reliability growth assessment of the space shuttle main engine test and flight failure data. Additional tables of percentage-point probabilities for several different values of the confidence coefficient have been generated for setting (1-alpha)100-percent two sided confidence interval estimates on the mean time between failures. The tabled data pertain to two cases: (1) time-terminated testing, and (2) failure-terminated testing. The critical values of the three test statistics, namely Cramer-von Mises, Kolmogorov-Smirnov, and chi-square, were calculated and tabled for use in the goodness of fit tests for the engine reliability data. Numerical results are presented for five different groupings of the engine data that reflect the actual response to the failures.

Differential subsidence and its effect on subsurface infrastructure: predicting probability of pipeline failure (STOOP project)

NASA Astrophysics Data System (ADS)

de Bruijn, Renée; Dabekaussen, Willem; Hijma, Marc; Wiersma, Ane; Abspoel-Bukman, Linda; Boeije, Remco; Courage, Wim; van der Geest, Johan; Hamburg, Marc; Harmsma, Edwin; Helmholt, Kristian; van den Heuvel, Frank; Kruse, Henk; Langius, Erik; Lazovik, Elena

2017-04-01

Due to heterogeneity of the subsurface in the delta environment of the Netherlands, differential subsidence over short distances results in tension and subsequent wear of subsurface infrastructure, such as water and gas pipelines. Due to uncertainties in the build-up of the subsurface, however, it is unknown where this problem is the most prominent. This is a problem for asset managers deciding when a pipeline needs replacement: damaged pipelines endanger security of supply and pose a significant threat to safety, yet premature replacement raises needless expenses. In both cases, costs - financial or other - are high. Therefore, an interdisciplinary research team of geotechnicians, geologists and Big Data engineers from research institutes TNO, Deltares and SkyGeo developed a stochastic model to predict differential subsidence and the probability of consequent pipeline failure on a (sub-)street level. In this project pipeline data from company databases is combined with a stochastic geological model and information on (historical) groundwater levels and overburden material. Probability of pipeline failure is modelled by a coupling with a subsidence model and two separate models on pipeline behaviour under stress, using a probabilistic approach. The total length of pipelines (approx. 200.000 km operational in the Netherlands) and the complexity of the model chain that is needed to calculate a chance of failure, results in large computational challenges, as it requires massive evaluation of possible scenarios to reach the required level of confidence. To cope with this, a scalable computational infrastructure has been developed, composing a model workflow in which components have a heterogeneous technological basis. Three pilot areas covering an urban, a rural and a mixed environment, characterised by different groundwater-management strategies and different overburden histories, are used to evaluate the differences in subsidence and uncertainties that come with different types of land use. Furthermore, the model provides results with a measure of reliability, and determines what is the limiting input factor causing most uncertainty. The model results can be validated and further improved using inSAR data for these pilot areas, by iteratively revising model parameters. The design of the model is such, that it can be applied to the whole of the Netherlands. By assessing differential subsidence and its effect on pipelines over time, the model helps to establish when and where maintenance is due, by indicating what areas are particularly vulnerable, thereby increasing safety and lowering maintenance costs.

Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks

PubMed Central

Nasir, Hina; Javaid, Nadeem; Sher, Muhammad; Qasim, Umar; Khan, Zahoor Ali; Alrajeh, Nabil; Niaz, Iftikhar Azim

2016-01-01

This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs); performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three step procedure is carried out; a system model is presented, the number of available relays are determined, and based on cooperative incremental retransmission methodology, closed-form expressions for outage and error probability are derived. Subject to the second contribution, Adaptive Cooperation in Energy (ACE) efficient depth based routing and Enhanced-ACE (E-ACE) are presented. In the proposed model, feedback mechanism indicates success or failure of data transmission. If direct transmission is successful, there is no need for relaying by cooperative relay nodes. In case of failure, all the available relays retransmit the data one by one till the desired signal quality is achieved at destination. Simulation results show that the ACE and E-ACE significantly improves network performance, i.e., throughput, when compared with other incremental relaying protocols like Cooperative Automatic Repeat reQuest (CARQ). E-ACE and ACE achieve 69% and 63% more throughput respectively as compared to CARQ in hard underwater environment. PMID:27420061

Accident hazard evaluation and control decisions on forested recreation sites

Treesearch

Lee A. Paine

1971-01-01

Accident hazard associated with trees on recreation sites is inherently concerned with probabilities. The major factors include the probabilities of mechanical failure and of target impact if failure occurs, the damage potential of the failure, and the target value. Hazard may be evaluated as the product of these factors; i.e., expected loss during the current...

Estimating earthquake-induced failure probability and downtime of critical facilities.

PubMed

Porter, Keith; Ramer, Kyle

2012-01-01

Fault trees have long been used to estimate failure risk in earthquakes, especially for nuclear power plants (NPPs). One interesting application is that one can assess and manage the probability that two facilities - a primary and backup - would be simultaneously rendered inoperative in a single earthquake. Another is that one can calculate the probabilistic time required to restore a facility to functionality, and the probability that, during any given planning period, the facility would be rendered inoperative for any specified duration. A large new peer-reviewed library of component damageability and repair-time data for the first time enables fault trees to be used to calculate the seismic risk of operational failure and downtime for a wide variety of buildings other than NPPs. With the new library, seismic risk of both the failure probability and probabilistic downtime can be assessed and managed, considering the facility's unique combination of structural and non-structural components, their seismic installation conditions, and the other systems on which the facility relies. An example is offered of real computer data centres operated by a California utility. The fault trees were created and tested in collaboration with utility operators, and the failure probability and downtime results validated in several ways.

A double hit model for the distribution of time to AIDS onset

NASA Astrophysics Data System (ADS)

Chillale, Nagaraja Rao

2013-09-01

Incubation time is a key epidemiologic descriptor of an infectious disease. In the case of HIV infection this is a random variable and is probably the longest one. The probability distribution of incubation time is the major determinant of the relation between the incidences of HIV infection and its manifestation to Aids. This is also one of the key factors used for accurate estimation of AIDS incidence in a region. The present article i) briefly reviews the work done, points out uncertainties in estimation of AIDS onset time and stresses the need for its precise estimation, ii) highlights some of the modelling features of onset distribution including immune failure mechanism, and iii) proposes a 'Double Hit' model for the distribution of time to AIDS onset in the cases of (a) independent and (b) dependent time variables of the two markers and examined the applicability of a few standard probability models.

Fracture strength and probability of survival of narrow and extra-narrow dental implants after fatigue testing: In vitro and in silico analysis.

PubMed

Bordin, Dimorvan; Bergamo, Edmara T P; Fardin, Vinicius P; Coelho, Paulo G; Bonfante, Estevam A

2017-07-01

To assess the probability of survival (reliability) and failure modes of narrow implants with different diameters. For fatigue testing, 42 implants with the same macrogeometry and internal conical connection were divided, according to diameter, as follows: narrow (Ø3.3×10mm) and extra-narrow (Ø2.9×10mm) (21 per group). Identical abutments were torqued to the implants and standardized maxillary incisor crowns were cemented and subjected to step-stress accelerated life testing (SSALT) in water. The use-level probability Weibull curves, and reliability for a mission of 50,000 and 100,000 cycles at 50N, 100, 150 and 180N were calculated. For the finite element analysis (FEA), two virtual models, simulating the samples tested in fatigue, were constructed. Loading at 50N and 100N were applied 30° off-axis at the crown. The von-Mises stress was calculated for implant and abutment. The beta (β) values were: 0.67 for narrow and 1.32 for extra-narrow implants, indicating that failure rates did not increase with fatigue in the former, but more likely were associated with damage accumulation and wear-out failures in the latter. Both groups showed high reliability (up to 97.5%) at 50 and 100N. A decreased reliability was observed for both groups at 150 and 180N (ranging from 0 to 82.3%), but no significant difference was observed between groups. Failure predominantly involved abutment fracture for both groups. FEA at 50N-load, Ø3.3mm showed higher von-Mises stress for abutment (7.75%) and implant (2%) when compared to the Ø2.9mm. There was no significant difference between narrow and extra-narrow implants regarding probability of survival. The failure mode was similar for both groups, restricted to abutment fracture. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Using software metrics and software reliability models to attain acceptable quality software for flight and ground support software for avionic systems

NASA Technical Reports Server (NTRS)

Lawrence, Stella

1992-01-01

This paper is concerned with methods of measuring and developing quality software. Reliable flight and ground support software is a highly important factor in the successful operation of the space shuttle program. Reliability is probably the most important of the characteristics inherent in the concept of 'software quality'. It is the probability of failure free operation of a computer program for a specified time and environment.

RELAV - RELIABILITY/AVAILABILITY ANALYSIS PROGRAM

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

RELAV (Reliability/Availability Analysis Program) is a comprehensive analytical tool to determine the reliability or availability of any general system which can be modeled as embedded k-out-of-n groups of items (components) and/or subgroups. Both ground and flight systems at NASA's Jet Propulsion Laboratory have utilized this program. RELAV can assess current system performance during the later testing phases of a system design, as well as model candidate designs/architectures or validate and form predictions during the early phases of a design. Systems are commonly modeled as System Block Diagrams (SBDs). RELAV calculates the success probability of each group of items and/or subgroups within the system assuming k-out-of-n operating rules apply for each group. The program operates on a folding basis; i.e. it works its way towards the system level from the most embedded level by folding related groups into single components. The entire folding process involves probabilities; therefore, availability problems are performed in terms of the probability of success, and reliability problems are performed for specific mission lengths. An enhanced cumulative binomial algorithm is used for groups where all probabilities are equal, while a fast algorithm based upon "Computing k-out-of-n System Reliability", Barlow & Heidtmann, IEEE TRANSACTIONS ON RELIABILITY, October 1984, is used for groups with unequal probabilities. Inputs to the program include a description of the system and any one of the following: 1) availabilities of the items, 2) mean time between failures and mean time to repairs for the items from which availabilities are calculated, 3) mean time between failures and mission length(s) from which reliabilities are calculated, or 4) failure rates and mission length(s) from which reliabilities are calculated. The results are probabilities of success of each group and the system in the given configuration. RELAV assumes exponential failure distributions for reliability calculations and infinite repair resources for availability calculations. No more than 967 items or groups can be modeled by RELAV. If larger problems can be broken into subsystems of 967 items or less, the subsystem results can be used as item inputs to a system problem. The calculated availabilities are steady-state values. Group results are presented in the order in which they were calculated (from the most embedded level out to the system level). This provides a good mechanism to perform trade studies. Starting from the system result and working backwards, the granularity gets finer; therefore, system elements that contribute most to system degradation are detected quickly. RELAV is a C-language program originally developed under the UNIX operating system on a MASSCOMP MC500 computer. It has been modified, as necessary, and ported to an IBM PC compatible with a math coprocessor. The current version of the program runs in the DOS environment and requires a Turbo C vers. 2.0 compiler. RELAV has a memory requirement of 103 KB and was developed in 1989. RELAV is a copyrighted work with all copyright vested in NASA.

Dynamic behavior of the interaction between epidemics and cascades on heterogeneous networks

NASA Astrophysics Data System (ADS)

Jiang, Lurong; Jin, Xinyu; Xia, Yongxiang; Ouyang, Bo; Wu, Duanpo

2014-12-01

Epidemic spreading and cascading failure are two important dynamical processes on complex networks. They have been investigated separately for a long time. But in the real world, these two dynamics sometimes may interact with each other. In this paper, we explore a model combined with the SIR epidemic spreading model and a local load sharing cascading failure model. There exists a critical value of the tolerance parameter for which the epidemic with high infection probability can spread out and infect a fraction of the network in this model. When the tolerance parameter is smaller than the critical value, the cascading failure cuts off the abundance of paths and blocks the spreading of the epidemic locally. While the tolerance parameter is larger than the critical value, the epidemic spreads out and infects a fraction of the network. A method for estimating the critical value is proposed. In simulations, we verify the effectiveness of this method in the uncorrelated configuration model (UCM) scale-free networks.

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

Quantum error-correction failure distributions: Comparison of coherent and stochastic error models

NASA Astrophysics Data System (ADS)

Barnes, Jeff P.; Trout, Colin J.; Lucarelli, Dennis; Clader, B. D.

2017-06-01

We compare failure distributions of quantum error correction circuits for stochastic errors and coherent errors. We utilize a fully coherent simulation of a fault-tolerant quantum error correcting circuit for a d =3 Steane and surface code. We find that the output distributions are markedly different for the two error models, showing that no simple mapping between the two error models exists. Coherent errors create very broad and heavy-tailed failure distributions. This suggests that they are susceptible to outlier events and that mean statistics, such as pseudothreshold estimates, may not provide the key figure of merit. This provides further statistical insight into why coherent errors can be so harmful for quantum error correction. These output probability distributions may also provide a useful metric that can be utilized when optimizing quantum error correcting codes and decoding procedures for purely coherent errors.

Fault tree analysis of failure cause of crushing plant and mixing bed hall at Khoy cement factory in Iran☆

PubMed Central

Nouri.Gharahasanlou, Ali; Mokhtarei, Ashkan; Khodayarei, Aliasqar; Ataei, Mohammad

2014-01-01

Evaluating and analyzing the risk in the mining industry is a new approach for improving the machinery performance. Reliability, safety, and maintenance management based on the risk analysis can enhance the overall availability and utilization of the mining technological systems. This study investigates the failure occurrence probability of the crushing and mixing bed hall department at Azarabadegan Khoy cement plant by using fault tree analysis (FTA) method. The results of the analysis in 200 h operating interval show that the probability of failure occurrence for crushing, conveyor systems, crushing and mixing bed hall department is 73, 64, and 95 percent respectively and the conveyor belt subsystem found as the most probable system for failure. Finally, maintenance as a method of control and prevent the occurrence of failure is proposed. PMID:26779433

Fault tree analysis of failure cause of crushing plant and mixing bed hall at Khoy cement factory in Iran.

PubMed

Nouri Gharahasanlou, Ali; Mokhtarei, Ashkan; Khodayarei, Aliasqar; Ataei, Mohammad

2014-04-01

Evaluating and analyzing the risk in the mining industry is a new approach for improving the machinery performance. Reliability, safety, and maintenance management based on the risk analysis can enhance the overall availability and utilization of the mining technological systems. This study investigates the failure occurrence probability of the crushing and mixing bed hall department at Azarabadegan Khoy cement plant by using fault tree analysis (FTA) method. The results of the analysis in 200 h operating interval show that the probability of failure occurrence for crushing, conveyor systems, crushing and mixing bed hall department is 73, 64, and 95 percent respectively and the conveyor belt subsystem found as the most probable system for failure. Finally, maintenance as a method of control and prevent the occurrence of failure is proposed.

Risk-based maintenance of ethylene oxide production facilities.

PubMed

Khan, Faisal I; Haddara, Mahmoud R

2004-05-20

This paper discusses a methodology for the design of an optimum inspection and maintenance program. The methodology, called risk-based maintenance (RBM) is based on integrating a reliability approach and a risk assessment strategy to obtain an optimum maintenance schedule. First, the likely equipment failure scenarios are formulated. Out of many likely failure scenarios, the ones, which are most probable, are subjected to a detailed study. Detailed consequence analysis is done for the selected scenarios. Subsequently, these failure scenarios are subjected to a fault tree analysis to determine their probabilities. Finally, risk is computed by combining the results of the consequence and the probability analyses. The calculated risk is compared against known acceptable criteria. The frequencies of the maintenance tasks are obtained by minimizing the estimated risk. A case study involving an ethylene oxide production facility is presented. Out of the five most hazardous units considered, the pipeline used for the transportation of the ethylene is found to have the highest risk. Using available failure data and a lognormal reliability distribution function human health risk factors are calculated. Both societal risk factors and individual risk factors exceeded the acceptable risk criteria. To determine an optimal maintenance interval, a reverse fault tree analysis was used. The maintenance interval was determined such that the original high risk is brought down to an acceptable level. A sensitivity analysis is also undertaken to study the impact of changing the distribution of the reliability model as well as the error in the distribution parameters on the maintenance interval.

Sensor failure and multivariable control for airbreathing propulsion systems. Ph.D. Thesis - Dec. 1979 Final Report

NASA Technical Reports Server (NTRS)

Behbehani, K.

1980-01-01

A new sensor/actuator failure analysis technique for turbofan jet engines was developed. Three phases of failure analysis, namely detection, isolation, and accommodation are considered. Failure detection and isolation techniques are developed by utilizing the concept of Generalized Likelihood Ratio (GLR) tests. These techniques are applicable to both time varying and time invariant systems. Three GLR detectors are developed for: (1) hard-over sensor failure; (2) hard-over actuator failure; and (3) brief disturbances in the actuators. The probability distribution of the GLR detectors and the detectability of sensor/actuator failures are established. Failure type is determined by the maximum of the GLR detectors. Failure accommodation is accomplished by extending the Multivariable Nyquest Array (MNA) control design techniques to nonsquare system designs. The performance and effectiveness of the failure analysis technique are studied by applying the technique to a turbofan jet engine, namely the Quiet Clean Short Haul Experimental Engine (QCSEE). Single and multiple sensor/actuator failures in the QCSEE are simulated and analyzed and the effects of model degradation are studied.

Model-OA wind turbine generator - Failure modes and effects analysis

NASA Technical Reports Server (NTRS)

Klein, William E.; Lali, Vincent R.

1990-01-01

The results failure modes and effects analysis (FMEA) conducted for wind-turbine generators are presented. The FMEA was performed for the functional modes of each system, subsystem, or component. The single-point failures were eliminated for most of the systems. The blade system was the only exception. The qualitative probability of a blade separating was estimated at level D-remote. Many changes were made to the hardware as a result of this analysis. The most significant change was the addition of the safety system. Operational experience and need to improve machine availability have resulted in subsequent changes to the various systems, which are also reflected in this FMEA.

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

Dana L. Kelly

Typical engineering systems in applications with high failure consequences such as nuclear reactor plants often employ redundancy and diversity of equipment in an effort to lower the probability of failure and therefore risk. However, it has long been recognized that dependencies exist in these redundant and diverse systems. Some dependencies, such as common sources of electrical power, are typically captured in the logic structure of the risk model. Others, usually referred to as intercomponent dependencies, are treated implicitly by introducing one or more statistical parameters into the model. Such common-cause failure models have limitations in a simulation environment. In addition,more » substantial subjectivity is associated with parameter estimation for these models. This paper describes an approach in which system performance is simulated by drawing samples from the joint distributions of dependent variables. The approach relies on the notion of a copula distribution, a notion which has been employed by the actuarial community for ten years or more, but which has seen only limited application in technological risk assessment. The paper also illustrates how equipment failure data can be used in a Bayesian framework to estimate the parameter values in the copula model. This approach avoids much of the subjectivity required to estimate parameters in traditional common-cause failure models. Simulation examples are presented for failures in time. The open-source software package R is used to perform the simulations. The open-source software package WinBUGS is used to perform the Bayesian inference via Markov chain Monte Carlo sampling.« less

Defense strategies for cloud computing multi-site server infrastructures

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

Rao, Nageswara S.; Ma, Chris Y. T.; He, Fei

We consider cloud computing server infrastructures for big data applications, which consist of multiple server sites connected over a wide-area network. The sites house a number of servers, network elements and local-area connections, and the wide-area network plays a critical, asymmetric role of providing vital connectivity between them. We model this infrastructure as a system of systems, wherein the sites and wide-area network are represented by their cyber and physical components. These components can be disabled by cyber and physical attacks, and also can be protected against them using component reinforcements. The effects of attacks propagate within the systems, andmore » also beyond them via the wide-area network.We characterize these effects using correlations at two levels using: (a) aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual site or network, and (b) first-order differential conditions on system survival probabilities that characterize the component-level correlations within individual systems. We formulate a game between an attacker and a provider using utility functions composed of survival probability and cost terms. At Nash Equilibrium, we derive expressions for the expected capacity of the infrastructure given by the number of operational servers connected to the network for sum-form, product-form and composite utility functions.« less

Influences of Availability on Parameter Estimates from Site Occupancy Models with Application to Submersed Aquatic Vegetation

USGS Publications Warehouse

Gray, Brian R.; Holland, Mark D.; Yi, Feng; Starcevich, Leigh Ann Harrod

2013-01-01

Site occupancy models are commonly used by ecologists to estimate the probabilities of species site occupancy and of species detection. This study addresses the influence on site occupancy and detection estimates of variation in species availability among surveys within sites. Such variation in availability may result from temporary emigration, nonavailability of the species for detection, and sampling sites spatially when species presence is not uniform within sites. We demonstrate, using Monte Carlo simulations and aquatic vegetation data, that variation in availability and heterogeneity in the probability of availability may yield biases in the expected values of the site occupancy and detection estimates that have traditionally been associated with low-detection probabilities and heterogeneity in those probabilities. These findings confirm that the effects of availability may be important for ecologists and managers, and that where such effects are expected, modification of sampling designs and/or analytical methods should be considered. Failure to limit the effects of availability may preclude reliable estimation of the probability of site occupancy.

SURE reliability analysis: Program and mathematics

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; White, Allan L.

1988-01-01

The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The computational methods on which the program is based provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

Probabilistic Based Modeling and Simulation Assessment

DTIC Science & Technology

2010-06-01

different crash and blast scenarios. With the integration of the high fidelity neck and head model, a methodology to calculate the probability of injury...variability, correlation, and multiple (often competing) failure metrics. Important scenarios include vehicular collisions, blast /fragment impact, and...first area of focus is to develop a methodology to integrate probabilistic analysis into finite element analysis of vehicle collisions and blast . The

Software Supportability Risk Assessment in OT&E (Operational Test and Evaluation): Literature Review, Current Research Review, and Data Base Assemblage.

DTIC Science & Technology

1984-09-28

variables before simula- tion of model - Search for reality checks a, - Express uncertainty as a probability density distribution. a. H2 a, H-22 TWIF... probability that the software con- tains errors. This prior is updated as test failure data are accumulated. Only a p of 1 (software known to contain...discusssed; both parametric and nonparametric versions are presented. It is shown by the author that the bootstrap underlies the jackknife method and

Factors influencing territorial occupancy and reproductive success in a Eurasian Eagle-owl (Bubo bubo) population.

PubMed

León-Ortega, Mario; Jiménez-Franco, María V; Martínez, José E; Calvo, José F

2017-01-01

Modelling territorial occupancy and reproductive success is a key issue for better understanding the population dynamics of territorial species. This study aimed to investigate these ecological processes in a Eurasian Eagle-owl (Bubo bubo) population in south-eastern Spain during a seven-year period. A multi-season, multi-state modelling approach was followed to estimate the probabilities of occupancy and reproductive success in relation to previous state, time and habitat covariates, and accounting for imperfect detection. The best estimated models showed past breeding success in the territories to be the most important factor determining a high probability of reoccupation and reproductive success in the following year. In addition, alternative occupancy models suggested the positive influence of crops on the probability of territory occupation. By contrast, the best reproductive model revealed strong interannual variations in the rates of breeding success, which may be related to changes in the abundance of the European Rabbit, the main prey of the Eurasian Eagle-owl. Our models also estimated the probabilities of detecting the presence of owls in a given territory and the probability of detecting evidence of successful reproduction. Estimated detection probabilities were high throughout the breeding season, decreasing in time for unsuccessful breeders but increasing for successful breeders. The probability of detecting reproductive success increased with time, being close to one in the last survey. These results suggest that reproduction failure in the early stages of the breeding season is a determinant factor in the probability of detecting occupancy and reproductive success.

Factors influencing territorial occupancy and reproductive success in a Eurasian Eagle-owl (Bubo bubo) population

PubMed Central

León-Ortega, Mario; Jiménez-Franco, María V.; Martínez, José E.

2017-01-01

Modelling territorial occupancy and reproductive success is a key issue for better understanding the population dynamics of territorial species. This study aimed to investigate these ecological processes in a Eurasian Eagle-owl (Bubo bubo) population in south-eastern Spain during a seven-year period. A multi-season, multi-state modelling approach was followed to estimate the probabilities of occupancy and reproductive success in relation to previous state, time and habitat covariates, and accounting for imperfect detection. The best estimated models showed past breeding success in the territories to be the most important factor determining a high probability of reoccupation and reproductive success in the following year. In addition, alternative occupancy models suggested the positive influence of crops on the probability of territory occupation. By contrast, the best reproductive model revealed strong interannual variations in the rates of breeding success, which may be related to changes in the abundance of the European Rabbit, the main prey of the Eurasian Eagle-owl. Our models also estimated the probabilities of detecting the presence of owls in a given territory and the probability of detecting evidence of successful reproduction. Estimated detection probabilities were high throughout the breeding season, decreasing in time for unsuccessful breeders but increasing for successful breeders. The probability of detecting reproductive success increased with time, being close to one in the last survey. These results suggest that reproduction failure in the early stages of the breeding season is a determinant factor in the probability of detecting occupancy and reproductive success. PMID:28399175

Machine health prognostics using the Bayesian-inference-based probabilistic indication and high-order particle filtering framework

NASA Astrophysics Data System (ADS)

Yu, Jianbo

2015-12-01

Prognostics is much efficient to achieve zero-downtime performance, maximum productivity and proactive maintenance of machines. Prognostics intends to assess and predict the time evolution of machine health degradation so that machine failures can be predicted and prevented. A novel prognostics system is developed based on the data-model-fusion scheme using the Bayesian inference-based self-organizing map (SOM) and an integration of logistic regression (LR) and high-order particle filtering (HOPF). In this prognostics system, a baseline SOM is constructed to model the data distribution space of healthy machine under an assumption that predictable fault patterns are not available. Bayesian inference-based probability (BIP) derived from the baseline SOM is developed as a quantification indication of machine health degradation. BIP is capable of offering failure probability for the monitored machine, which has intuitionist explanation related to health degradation state. Based on those historic BIPs, the constructed LR and its modeling noise constitute a high-order Markov process (HOMP) to describe machine health propagation. HOPF is used to solve the HOMP estimation to predict the evolution of the machine health in the form of a probability density function (PDF). An on-line model update scheme is developed to adapt the Markov process changes to machine health dynamics quickly. The experimental results on a bearing test-bed illustrate the potential applications of the proposed system as an effective and simple tool for machine health prognostics.

Branch-and-Bound algorithm applied to uncertainty quantification of a Boiling Water Reactor Station Blackout

DOE PAGES

Nielsen, Joseph; Tokuhiro, Akira; Hiromoto, Robert; ...

2015-11-13

Evaluation of the impacts of uncertainty and sensitivity in modeling presents a significant set of challenges in particular to high fidelity modeling. Computational costs and validation of models creates a need for cost effective decision making with regards to experiment design. Experiments designed to validate computation models can be used to reduce uncertainty in the physical model. In some cases, large uncertainty in a particular aspect of the model may or may not have a large impact on the final results. For example, modeling of a relief valve may result in large uncertainty, however, the actual effects on final peakmore » clad temperature in a reactor transient may be small and the large uncertainty with respect to valve modeling may be considered acceptable. Additionally, the ability to determine the adequacy of a model and the validation supporting it should be considered within a risk informed framework. Low fidelity modeling with large uncertainty may be considered adequate if the uncertainty is considered acceptable with respect to risk. In other words, models that are used to evaluate the probability of failure should be evaluated more rigorously with the intent of increasing safety margin. Probabilistic risk assessment (PRA) techniques have traditionally been used to identify accident conditions and transients. Traditional classical event tree methods utilize analysts’ knowledge and experience to identify the important timing of events in coordination with thermal-hydraulic modeling. These methods lack the capability to evaluate complex dynamic systems. In these systems, time and energy scales associated with transient events may vary as a function of transition times and energies to arrive at a different physical state. Dynamic PRA (DPRA) methods provide a more rigorous analysis of complex dynamic systems. Unfortunately DPRA methods introduce issues associated with combinatorial explosion of states. This study presents a methodology to address combinatorial explosion using a Branch-and-Bound algorithm applied to Dynamic Event Trees (DET), which utilize LENDIT (L – Length, E – Energy, N – Number, D – Distribution, I – Information, and T – Time) as well as a set theory to describe system, state, resource, and response (S2R2) sets to create bounding functions for the DET. The optimization of the DET in identifying high probability failure branches is extended to create a Phenomenological Identification and Ranking Table (PIRT) methodology to evaluate modeling parameters important to safety of those failure branches that have a high probability of failure. The PIRT can then be used as a tool to identify and evaluate the need for experimental validation of models that have the potential to reduce risk. Finally, in order to demonstrate this methodology, a Boiling Water Reactor (BWR) Station Blackout (SBO) case study is presented.« less

Effectiveness of back-to-back testing

NASA Technical Reports Server (NTRS)

Vouk, Mladen A.; Mcallister, David F.; Eckhardt, David E.; Caglayan, Alper; Kelly, John P. J.

1987-01-01

Three models of back-to-back testing processes are described. Two models treat the case where there is no intercomponent failure dependence. The third model describes the more realistic case where there is correlation among the failure probabilities of the functionally equivalent components. The theory indicates that back-to-back testing can, under the right conditions, provide a considerable gain in software reliability. The models are used to analyze the data obtained in a fault-tolerant software experiment. It is shown that the expected gain is indeed achieved, and exceeded, provided the intercomponent failure dependence is sufficiently small. However, even with the relatively high correlation the use of several functionally equivalent components coupled with back-to-back testing may provide a considerable reliability gain. Implications of this finding are that the multiversion software development is a feasible and cost effective approach to providing highly reliable software components intended for fault-tolerant software systems, on condition that special attention is directed at early detection and elimination of correlated faults.

Improving default risk prediction using Bayesian model uncertainty techniques.

PubMed

Kazemi, Reza; Mosleh, Ali

2012-11-01

Credit risk is the potential exposure of a creditor to an obligor's failure or refusal to repay the debt in principal or interest. The potential of exposure is measured in terms of probability of default. Many models have been developed to estimate credit risk, with rating agencies dating back to the 19th century. They provide their assessment of probability of default and transition probabilities of various firms in their annual reports. Regulatory capital requirements for credit risk outlined by the Basel Committee on Banking Supervision have made it essential for banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with higher accuracy. The Bayesian framework proposed in this article uses the techniques developed in physical sciences and engineering for dealing with model uncertainty and expert accuracy to obtain improved estimates of credit risk and associated uncertainties. The approach uses estimates from one or more rating agencies and incorporates their historical accuracy (past performance data) in estimating future default risk and transition probabilities. Several examples demonstrate that the proposed methodology can assess default probability with accuracy exceeding the estimations of all the individual models. Moreover, the methodology accounts for potentially significant departures from "nominal predictions" due to "upsetting events" such as the 2008 global banking crisis. © 2012 Society for Risk Analysis.

Stochastic methods for analysis of power flow in electric networks

NASA Astrophysics Data System (ADS)

1982-09-01

The modeling and effects of probabilistic behavior on steady state power system operation were analyzed. A solution to the steady state network flow equations which adhere both to Kirchoff's Laws and probabilistic laws, using either combinatorial or functional approximation techniques was obtained. The development of sound techniques for producing meaningful data to serve as input is examined. Electric demand modeling, equipment failure analysis, and algorithm development are investigated. Two major development areas are described: a decomposition of stochastic processes which gives stationarity, ergodicity, and even normality; and a powerful surrogate probability approach using proportions of time which allows the calculation of joint events from one dimensional probability spaces.

Analysis of flood hazard under consideration of dike breaches

NASA Astrophysics Data System (ADS)

Vorogushyn, S.; Apel, H.; Lindenschmidt, K.-E.; Merz, B.

2009-04-01

The study focuses on the development and application of a new modelling system which allows a comprehensive flood hazard assessment along diked river reaches under consideration of dike failures. The proposed Inundation Hazard Assessment Model (IHAM) represents a hybrid probabilistic-deterministic model. It comprises three models interactively coupled at runtime. These are: (1) 1D unsteady hydrodynamic model of river channel and floodplain flow between dikes, (2) probabilistic dike breach model which determines possible dike breach locations, breach widths and breach outflow discharges, and (3) 2D raster-based diffusion wave storage cell model of the hinterland areas behind the dikes. Due to the unsteady nature of the 1D and 2D coupled models, the dependence between hydraulic load at various locations along the reach is explicitly considered. The probabilistic dike breach model describes dike failures due to three failure mechanisms: overtopping, piping and slope instability caused by the seepage flow through the dike core (micro-instability). Dike failures for each mechanism are simulated based on fragility functions. The probability of breach is conditioned by the uncertainty in geometrical and geotechnical dike parameters. The 2D storage cell model driven by the breach outflow boundary conditions computes an extended spectrum of flood intensity indicators such as water depth, flow velocity, impulse, inundation duration and rate of water rise. IHAM is embedded in a Monte Carlo simulation in order to account for the natural variability of the flood generation processes reflected in the form of input hydrographs and for the randomness of dike failures given by breach locations, times and widths. The scenario calculations for the developed synthetic input hydrographs for the main river and tributary were carried out for floods with return periods of T = 100; 200; 500; 1000 a. Based on the modelling results, probabilistic dike hazard maps could be generated that indicate the failure probability of each discretised dike section for every scenario magnitude. Besides the binary inundation patterns that indicate the probability of raster cells being inundated, IHAM generates probabilistic flood hazard maps. These maps display spatial patterns of the considered flood intensity indicators and their associated return periods. The probabilistic nature of IHAM allows for the generation of percentile flood hazard maps that indicate the median and uncertainty bounds of the flood intensity indicators. The uncertainty results from the natural variability of the flow hydrographs and randomness of dike breach processes. The same uncertainty sources determine the uncertainty in the flow hydrographs along the study reach. The simulations showed that the dike breach stochasticity has an increasing impact on hydrograph uncertainty in downstream direction. Whereas in the upstream part of the reach the hydrograph uncertainty is mainly stipulated by the variability of the flood wave form, the dike failures strongly shape the uncertainty boundaries in the downstream part of the reach. Finally, scenarios of polder deployment for the extreme floods with T = 200; 500; 1000 a were simulated with IHAM. The results indicate a rather weak reduction of the mean and median flow hydrographs in the river channel. However, the capping of the flow peaks resulted in a considerable reduction of the overtopping failures downstream of the polder with a simultaneous slight increase of the piping and slope micro-instability frequencies explained by a more durable average impoundment. The developed IHAM simulation system represents a new scientific tool for studying fluvial inundation dynamics under extreme conditions incorporating effects of technical flood protection measures. With its major outputs in form of novel probabilistic inundation and dike hazard maps, the IHAM system has a high practical value for decision support in flood management.

A Physically-Based and Distributed Tool for Modeling the Hydrological and Mechanical Processes of Shallow Landslides

NASA Astrophysics Data System (ADS)

Arnone, E.; Noto, L. V.; Dialynas, Y. G.; Caracciolo, D.; Bras, R. L.

2015-12-01

This work presents the capabilities of a model, i.e. the tRIBS-VEGGIE-Landslide, in two different versions, i.e. developed within a probabilistic framework and coupled with a root cohesion module. The probabilistic model treats geotechnical and soil retention curve parameters as random variables across the basin and estimates theoretical probability distributions of slope stability and the associated "factor of safety" commonly used to describe the occurrence of shallow landslides. The derived distributions are used to obtain the spatio-temporal dynamics of probability of failure, conditioned on soil moisture dynamics at each watershed location. The framework has been tested in the Luquillo Experimental Forest (Puerto Rico) where shallow landslides are common. In particular, the methodology was used to evaluate how the spatial and temporal patterns of precipitation, whose variability is significant over the basin, affect the distribution of probability of failure. Another version of the model accounts for the additional cohesion exerted by vegetation roots. The approach is to use the Fiber Bundle Model (FBM) framework that allows for the evaluation of the root strength as a function of the stress-strain relationships of bundles of fibers. The model requires the knowledge of the root architecture to evaluate the additional reinforcement from each root diameter class. The root architecture is represented with a branching topology model based on Leonardo's rule. The methodology has been tested on a simple case study to explore the role of both hydrological and mechanical root effects. Results demonstrate that the effects of root water uptake can at times be more significant than the mechanical reinforcement; and that the additional resistance provided by roots depends heavily on the vegetation root structure and length.

Size distribution of submarine landslides along the U.S. Atlantic margin

USGS Publications Warehouse

Chaytor, J.D.; ten Brink, Uri S.; Solow, A.R.; Andrews, B.D.

2009-01-01

Assessment of the probability for destructive landslide-generated tsunamis depends on the knowledge of the number, size, and frequency of large submarine landslides. This paper investigates the size distribution of submarine landslides along the U.S. Atlantic continental slope and rise using the size of the landslide source regions (landslide failure scars). Landslide scars along the margin identified in a detailed bathymetric Digital Elevation Model (DEM) have areas that range between 0.89??km2 and 2410??km2 and volumes between 0.002??km3 and 179??km3. The area to volume relationship of these failure scars is almost linear (inverse power-law exponent close to 1), suggesting a fairly uniform failure thickness of a few 10s of meters in each event, with only rare, deep excavating landslides. The cumulative volume distribution of the failure scars is very well described by a log-normal distribution rather than by an inverse power-law, the most commonly used distribution for both subaerial and submarine landslides. A log-normal distribution centered on a volume of 0.86??km3 may indicate that landslides preferentially mobilize a moderate amount of material (on the order of 1??km3), rather than large landslides or very small ones. Alternatively, the log-normal distribution may reflect an inverse power law distribution modified by a size-dependent probability of observing landslide scars in the bathymetry data. If the latter is the case, an inverse power-law distribution with an exponent of 1.3 ?? 0.3, modified by a size-dependent conditional probability of identifying more failure scars with increasing landslide size, fits the observed size distribution. This exponent value is similar to the predicted exponent of 1.2 ?? 0.3 for subaerial landslides in unconsolidated material. Both the log-normal and modified inverse power-law distributions of the observed failure scar volumes suggest that large landslides, which have the greatest potential to generate damaging tsunamis, occur infrequently along the margin. ?? 2008 Elsevier B.V.

Estimation of the failure risk of a maxillary premolar with different crack depths with endodontic treatment by computer-aided design/computer-aided manufacturing ceramic restorations.

PubMed

Lin, Chun-Li; Chang, Yen-Hsiang; Hsieh, Shih-Kai; Chang, Wen-Jen

2013-03-01

This study evaluated the risk of failure for an endodontically treated premolar with different crack depths, which was shearing toward the pulp chamber and was restored by using 3 different computer-aided design/computer-aided manufacturing ceramic restoration configurations. Three 3-dimensional finite element models designed with computer-aided design/computer-aided manufacturing ceramic onlay, endocrown, and conventional crown restorations were constructed to perform simulations. The Weibull function was incorporated with finite element analysis to calculate the long-term failure probability relative to different load conditions. The results indicated that the stress values on the enamel, dentin, and luting cement for endocrown restorations exhibited the lowest values relative to the other 2 restoration methods. Weibull analysis revealed that the overall failure probabilities in a shallow cracked premolar were 27%, 2%, and 1% for the onlay, endocrown, and conventional crown restorations, respectively, in the normal occlusal condition. The corresponding values were 70%, 10%, and 2% for the depth cracked premolar. This numeric investigation suggests that the endocrown provides sufficient fracture resistance only in a shallow cracked premolar with endodontic treatment. The conventional crown treatment can immobilize the premolar for different cracked depths with lower failure risk. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Quality Issues in Propulsion

NASA Technical Reports Server (NTRS)

McCarty, John P.; Lyles, Garry M.

1997-01-01

Propulsion system quality is defined in this paper as having high reliability, that is, quality is a high probability of within-tolerance performance or operation. Since failures are out-of-tolerance performance, the probability of failures and their occurrence is the difference between high and low quality systems. Failures can be described at 3 levels: the system failure (which is the detectable end of a failure), the failure mode (which is the failure process), and the failure cause (which is the start). Failure causes can be evaluated & classified by type. The results of typing flight history failures shows that most failures are in unrecognized modes and result from human error or noise, i.e. failures are when engineers learn how things really work. Although the study based on US launch vehicles, a sampling of failures from other countries indicates the finding has broad application. The parameters of the design of a propulsion system are not single valued, but have dispersions associated with the manufacturing of parts. Many tests are needed to find failures, if the dispersions are large relative to tolerances, which could contribute to the large number of failures in unrecognized modes.

Cost-effectiveness of early compared to late inhaled nitric oxide therapy in near-term infants.

PubMed

Armstrong, Edward P; Dhanda, Rahul

2010-12-01

The purpose of this study was to determine the cost-effectiveness of early versus late inhaled nitric oxide (INO) therapy in neonates with hypoxic respiratory failure initially managed on conventional mechanical ventilation. A decision analytic model was created to compare the use of early INO compared to delayed INO for neonates receiving mechanical ventilation due to hypoxic respiratory failure. The perspective of the model was that of a hospital. Patients who did not respond to either early or delayed INO were assumed to have been treated with extracorporeal membrane oxygenation (ECMO). The effectiveness measure was defined as a neonate discharged alive without requiring ECMO therapy. A Monte Carlo simulation of 10,000 cases was conducted using first and second order probabilistic analysis. Direct medical costs that differed between early versus delayed INO treatment were estimated until time to hospital discharge. The proportion of successfully treated patients and costs were determined from the probabilistic sensitivity analysis. The mean (± SD) effectiveness rate for early INO was 0.75 (± 0.08) and 0.61 (± 0.09) for delayed INO. The mean hospital cost for early INO was $21,462 (± $2695) and $27,226 (± $3532) for delayed INO. In 87% of scenarios, early INO dominated delayed INO by being both more effective and less costly. The acceptability curve between products demonstrated that early INO had over a 90% probability of being the most cost-effective treatment across a wide range of willingness to pay values. This analysis indicated that early INO therapy was cost-effective in neonates with hypoxic respiratory failure requiring mechanical ventilation compared to delayed INO by reducing the probability of developing severe hypoxic respiratory failure. There was a 90% or higher probability that early INO was more cost-effective than delayed INO across a wide range of willingness to pay values in this analysis.

Sensory redundancy management: The development of a design methodology for determining threshold values through a statistical analysis of sensor output data

NASA Technical Reports Server (NTRS)

Scalzo, F.

1983-01-01

Sensor redundancy management (SRM) requires a system which will detect failures and reconstruct avionics accordingly. A probability density function to determine false alarm rates, using an algorithmic approach was generated. Microcomputer software was developed which will print out tables of values for the cummulative probability of being in the domain of failure; system reliability; and false alarm probability, given a signal is in the domain of failure. The microcomputer software was applied to the sensor output data for various AFT1 F-16 flights and sensor parameters. Practical recommendations for further research were made.

A statistical-based material and process guidelines for design of carbon nanotube field-effect transistors in gigascale integrated circuits.

PubMed

Ghavami, Behnam; Raji, Mohsen; Pedram, Hossein

2011-08-26

Carbon nanotube field-effect transistors (CNFETs) show great promise as building blocks of future integrated circuits. However, synthesizing single-walled carbon nanotubes (CNTs) with accurate chirality and exact positioning control has been widely acknowledged as an exceedingly complex task. Indeed, density and chirality variations in CNT growth can compromise the reliability of CNFET-based circuits. In this paper, we present a novel statistical compact model to estimate the failure probability of CNFETs to provide some material and process guidelines for the design of CNFETs in gigascale integrated circuits. We use measured CNT spacing distributions within the framework of detailed failure analysis to demonstrate that both the CNT density and the ratio of metallic to semiconducting CNTs play dominant roles in defining the failure probability of CNFETs. Besides, it is argued that the large-scale integration of these devices within an integrated circuit will be feasible only if a specific range of CNT density with an acceptable ratio of semiconducting to metallic CNTs can be adjusted in a typical synthesis process.

Data Applicability of Heritage and New Hardware For Launch Vehicle Reliability Models

NASA Technical Reports Server (NTRS)

Al Hassan, Mohammad; Novack, Steven

2015-01-01

Bayesian reliability requires the development of a prior distribution to represent degree of belief about the value of a parameter (such as a component's failure rate) before system specific data become available from testing or operations. Generic failure data are often provided in reliability databases as point estimates (mean or median). A component's failure rate is considered a random variable where all possible values are represented by a probability distribution. The applicability of the generic data source is a significant source of uncertainty that affects the spread of the distribution. This presentation discusses heuristic guidelines for quantifying uncertainty due to generic data applicability when developing prior distributions mainly from reliability predictions.

Probability of failure prediction for step-stress fatigue under sine or random stress

NASA Technical Reports Server (NTRS)

Lambert, R. G.

1979-01-01

A previously proposed cumulative fatigue damage law is extended to predict the probability of failure or fatigue life for structural materials with S-N fatigue curves represented as a scatterband of failure points. The proposed law applies to structures subjected to sinusoidal or random stresses and includes the effect of initial crack (i.e., flaw) sizes. The corrected cycle ratio damage function is shown to have physical significance.

Detection of faults and software reliability analysis

NASA Technical Reports Server (NTRS)

Knight, J. C.

1986-01-01

Multiversion or N-version programming was proposed as a method of providing fault tolerance in software. The approach requires the separate, independent preparation of multiple versions of a piece of software for some application. Specific topics addressed are: failure probabilities in N-version systems, consistent comparison in N-version systems, descriptions of the faults found in the Knight and Leveson experiment, analytic models of comparison testing, characteristics of the input regions that trigger faults, fault tolerance through data diversity, and the relationship between failures caused by automatically seeded faults.

Probabilistic analysis on the failure of reactivity control for the PWR

NASA Astrophysics Data System (ADS)

Sony Tjahyani, D. T.; Deswandri; Sunaryo, G. R.

2018-02-01

The fundamental safety function of the power reactor is to control reactivity, to remove heat from the reactor, and to confine radioactive material. The safety analysis is used to ensure that each parameter is fulfilled during the design and is done by deterministic and probabilistic method. The analysis of reactivity control is important to be done because it will affect the other of fundamental safety functions. The purpose of this research is to determine the failure probability of the reactivity control and its failure contribution on a PWR design. The analysis is carried out by determining intermediate events, which cause the failure of reactivity control. Furthermore, the basic event is determined by deductive method using the fault tree analysis. The AP1000 is used as the object of research. The probability data of component failure or human error, which is used in the analysis, is collected from IAEA, Westinghouse, NRC and other published documents. The results show that there are six intermediate events, which can cause the failure of the reactivity control. These intermediate events are uncontrolled rod bank withdrawal at low power or full power, malfunction of boron dilution, misalignment of control rod withdrawal, malfunction of improper position of fuel assembly and ejection of control rod. The failure probability of reactivity control is 1.49E-03 per year. The causes of failures which are affected by human factor are boron dilution, misalignment of control rod withdrawal and malfunction of improper position for fuel assembly. Based on the assessment, it is concluded that the failure probability of reactivity control on the PWR is still within the IAEA criteria.

Quantifying Safety Margin Using the Risk-Informed Safety Margin Characterization (RISMC)

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

Grabaskas, David; Bucknor, Matthew; Brunett, Acacia

2015-04-26

The Risk-Informed Safety Margin Characterization (RISMC), developed by Idaho National Laboratory as part of the Light-Water Reactor Sustainability Project, utilizes a probabilistic safety margin comparison between a load and capacity distribution, rather than a deterministic comparison between two values, as is usually done in best-estimate plus uncertainty analyses. The goal is to determine the failure probability, or in other words, the probability of the system load equaling or exceeding the system capacity. While this method has been used in pilot studies, there has been little work conducted investigating the statistical significance of the resulting failure probability. In particular, it ismore » difficult to determine how many simulations are necessary to properly characterize the failure probability. This work uses classical (frequentist) statistics and confidence intervals to examine the impact in statistical accuracy when the number of simulations is varied. Two methods are proposed to establish confidence intervals related to the failure probability established using a RISMC analysis. The confidence interval provides information about the statistical accuracy of the method utilized to explore the uncertainty space, and offers a quantitative method to gauge the increase in statistical accuracy due to performing additional simulations.« less

The SURE reliability analysis program

NASA Technical Reports Server (NTRS)

Butler, R. W.

1986-01-01

The SURE program is a new reliability tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

The SURE Reliability Analysis Program

NASA Technical Reports Server (NTRS)

Butler, R. W.

1986-01-01

The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

A Markov chain model for reliability growth and decay

NASA Technical Reports Server (NTRS)

Siegrist, K.

1982-01-01

A mathematical model is developed to describe a complex system undergoing a sequence of trials in which there is interaction between the internal states of the system and the outcomes of the trials. For example, the model might describe a system undergoing testing that is redesigned after each failure. The basic assumptions for the model are that the state of the system after a trial depends probabilistically only on the state before the trial and on the outcome of the trial and that the outcome of a trial depends probabilistically only on the state of the system before the trial. It is shown that under these basic assumptions, the successive states form a Markov chain and the successive states and outcomes jointly form a Markov chain. General results are obtained for the transition probabilities, steady-state distributions, etc. A special case studied in detail describes a system that has two possible state ('repaired' and 'unrepaired') undergoing trials that have three possible outcomes ('inherent failure', 'assignable-cause' 'failure' and 'success'). For this model, the reliability function is computed explicitly and an optimal repair policy is obtained.

14 CFR 417.224 - Probability of failure analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 4 2013-01-01 2013-01-01 false Probability of failure analysis. 417.224 Section 417.224 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... phase of normal flight or when any anomalous condition exhibits the potential for a stage or its debris...

14 CFR 417.224 - Probability of failure analysis.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Probability of failure analysis. 417.224 Section 417.224 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... phase of normal flight or when any anomalous condition exhibits the potential for a stage or its debris...

14 CFR 417.224 - Probability of failure analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 4 2012-01-01 2012-01-01 false Probability of failure analysis. 417.224 Section 417.224 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... phase of normal flight or when any anomalous condition exhibits the potential for a stage or its debris...

14 CFR 417.224 - Probability of failure analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 4 2011-01-01 2011-01-01 false Probability of failure analysis. 417.224 Section 417.224 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... phase of normal flight or when any anomalous condition exhibits the potential for a stage or its debris...

14 CFR 417.224 - Probability of failure analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 4 2014-01-01 2014-01-01 false Probability of failure analysis. 417.224 Section 417.224 Aeronautics and Space COMMERCIAL SPACE TRANSPORTATION, FEDERAL AVIATION ADMINISTRATION... phase of normal flight or when any anomalous condition exhibits the potential for a stage or its debris...

Mechanics-based statistics of failure risk of quasibrittle structures and size effect on safety factors.

PubMed

Bazant, Zdenĕk P; Pang, Sze-Dai

2006-06-20

In mechanical design as well as protection from various natural hazards, one must ensure an extremely low failure probability such as 10(-6). How to achieve that goal is adequately understood only for the limiting cases of brittle or ductile structures. Here we present a theory to do that for the transitional class of quasibrittle structures, having brittle constituents and characterized by nonnegligible size of material inhomogeneities. We show that the probability distribution of strength of the representative volume element of material is governed by the Maxwell-Boltzmann distribution of atomic energies and the stress dependence of activation energy barriers; that it is statistically modeled by a hierarchy of series and parallel couplings; and that it consists of a broad Gaussian core having a grafted far-left power-law tail with zero threshold and amplitude depending on temperature and load duration. With increasing structure size, the Gaussian core shrinks and Weibull tail expands according to the weakest-link model for a finite chain of representative volume elements. The model captures experimentally observed deviations of the strength distribution from Weibull distribution and of the mean strength scaling law from a power law. These deviations can be exploited for verification and calibration. The proposed theory will increase the safety of concrete structures, composite parts of aircraft or ships, microelectronic components, microelectromechanical systems, prosthetic devices, etc. It also will improve protection against hazards such as landslides, avalanches, ice breaks, and rock or soil failures.

Regional Earthquake Likelihood Models: A realm on shaky grounds?

NASA Astrophysics Data System (ADS)

Kossobokov, V.

2005-12-01

Seismology is juvenile and its appropriate statistical tools to-date may have a "medievil flavor" for those who hurry up to apply a fuzzy language of a highly developed probability theory. To become "quantitatively probabilistic" earthquake forecasts/predictions must be defined with a scientific accuracy. Following the most popular objectivists' viewpoint on probability, we cannot claim "probabilities" adequate without a long series of "yes/no" forecast/prediction outcomes. Without "antiquated binary language" of "yes/no" certainty we cannot judge an outcome ("success/failure"), and, therefore, quantify objectively a forecast/prediction method performance. Likelihood scoring is one of the delicate tools of Statistics, which could be worthless or even misleading when inappropriate probability models are used. This is a basic loophole for a misuse of likelihood as well as other statistical methods on practice. The flaw could be avoided by an accurate verification of generic probability models on the empirical data. It is not an easy task in the frames of the Regional Earthquake Likelihood Models (RELM) methodology, which neither defines the forecast precision nor allows a means to judge the ultimate success or failure in specific cases. Hopefully, the RELM group realizes the problem and its members do their best to close the hole with an adequate, data supported choice. Regretfully, this is not the case with the erroneous choice of Gerstenberger et al., who started the public web site with forecasts of expected ground shaking for `tomorrow' (Nature 435, 19 May 2005). Gerstenberger et al. have inverted the critical evidence of their study, i.e., the 15 years of recent seismic record accumulated just in one figure, which suggests rejecting with confidence above 97% "the generic California clustering model" used in automatic calculations. As a result, since the date of publication in Nature the United States Geological Survey website delivers to the public, emergency planners and the media, a forecast product, which is based on wrong assumptions that violate the best-documented earthquake statistics in California, which accuracy was not investigated, and which forecasts were not tested in a rigorous way.

Individual versus systemic risk and the Regulator's Dilemma.

PubMed

Beale, Nicholas; Rand, David G; Battey, Heather; Croxson, Karen; May, Robert M; Nowak, Martin A

2011-08-02

The global financial crisis of 2007-2009 exposed critical weaknesses in the financial system. Many proposals for financial reform address the need for systemic regulation--that is, regulation focused on the soundness of the whole financial system and not just that of individual institutions. In this paper, we study one particular problem faced by a systemic regulator: the tension between the distribution of assets that individual banks would like to hold and the distribution across banks that best supports system stability if greater weight is given to avoiding multiple bank failures. By diversifying its risks, a bank lowers its own probability of failure. However, if many banks diversify their risks in similar ways, then the probability of multiple failures can increase. As more banks fail simultaneously, the economic disruption tends to increase disproportionately. We show that, in model systems, the expected systemic cost of multiple failures can be largely explained by two global parameters of risk exposure and diversity, which can be assessed in terms of the risk exposures of individual actors. This observation hints at the possibility of regulatory intervention to promote systemic stability by incentivizing a more diverse diversification among banks. Such intervention offers the prospect of an additional lever in the armory of regulators, potentially allowing some combination of improved system stability and reduced need for additional capital.

Vulnerability of bridges to scour: insights from an international expert elicitation workshop

NASA Astrophysics Data System (ADS)

Lamb, Rob; Aspinall, Willy; Odbert, Henry; Wagener, Thorsten

2017-08-01

Scour (localised erosion) during flood events is one of the most significant threats to bridges over rivers and estuaries, and has been the cause of numerous bridge failures, with damaging consequences. Mitigation of the risk of bridges being damaged by scour is therefore important to many infrastructure owners, and is supported by industry guidance. Even after mitigation, some residual risk remains, though its extent is difficult to quantify because of the uncertainties inherent in the prediction of scour and the assessment of the scour risk. This paper summarises findings from an international expert workshop on bridge scour risk assessment that explores uncertainties about the vulnerability of bridges to scour. Two specialised structured elicitation methods were applied to explore the factors that experts in the field consider important when assessing scour risk and to derive pooled expert judgements of bridge failure probabilities that are conditional on a range of assumed scenarios describing flood event severity, bridge and watercourse types and risk mitigation protocols. The experts' judgements broadly align with industry good practice, but indicate significant uncertainty about quantitative estimates of bridge failure probabilities, reflecting the difficulty in assessing the residual risk of failure. The data and findings presented here could provide a useful context for the development of generic scour fragility models and their associated uncertainties.

Probability of survival of implant-supported metal ceramic and CAD/CAM resin nanoceramic crowns.

PubMed

Bonfante, Estevam A; Suzuki, Marcelo; Lorenzoni, Fábio C; Sena, Lídia A; Hirata, Ronaldo; Bonfante, Gerson; Coelho, Paulo G

2015-08-01

To evaluate the probability of survival and failure modes of implant-supported resin nanoceramic relative to metal-ceramic crowns. Resin nanoceramic molar crowns (LU) (Lava Ultimate, 3M ESPE, USA) were milled and metal-ceramic (MC) (Co-Cr alloy, Wirobond C+, Bego, USA) with identical anatomy were fabricated (n=21). The metal coping and a burnout-resin veneer were created by CAD/CAM, using an abutment (Stealth-abutment, Bicon LLC, USA) and a milled crown from the LU group as models for porcelain hot-pressing (GC-Initial IQ-Press, GC, USA). Crowns were cemented, the implants (n=42, Bicon) embedded in acrylic-resin for mechanical testing, and subjected to single-load to fracture (SLF, n=3 each) for determination of step-stress profiles for accelerated-life testing in water (n=18 each). Weibull curves (50,000 cycles at 200N, 90% CI) were plotted. Weibull modulus (m) and characteristic strength (η) were calculated and a contour plot used (m versus η) for determining differences between groups. Fractography was performed in SEM and polarized-light microscopy. SLF mean values were 1871N (±54.03) for MC and 1748N (±50.71) for LU. Beta values were 0.11 for MC and 0.49 for LU. Weibull modulus was 9.56 and η=1038.8N for LU, and m=4.57 and η=945.42N for MC (p>0.10). Probability of survival (50,000 and 100,000 cycles at 200 and 300N) was 100% for LU and 99% for MC. Failures were cohesive within LU. In MC crowns, porcelain veneer fractures frequently extended to the supporting metal coping. Probability of survival was not different between crown materials, but failure modes differed. In load bearing regions, similar reliability should be expected for metal ceramics, known as the gold standard, and resin nanoceramic crowns over implants. Failure modes involving porcelain veneer fracture and delamination in MC crowns are less likely to be successfully repaired compared to cohesive failures in resin nanoceramic material. Copyright © 2015 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Initial high anti-emetic efficacy of granisetron with dexamethasone is not maintained over repeated cycles.

PubMed Central

de Wit, R.; van den Berg, H.; Burghouts, J.; Nortier, J.; Slee, P.; Rodenburg, C.; Keizer, J.; Fonteyn, M.; Verweij, J.; Wils, J.

1998-01-01

We have reported previously that the anti-emetic efficacy of single agent 5HT3 antagonists is not maintained when analysed with the measurement of cumulative probabilities. Presently, the most effective anti-emetic regimen is a combination of a 5HT3 antagonist plus dexamethasone. We, therefore, assessed the sustainment of efficacy of such a combination in 125 patients, scheduled to receive cisplatin > or = 70 mg m(-2) either alone or in combination with other cytotoxic drugs. Anti-emetic therapy was initiated with 10 mg of dexamethasone and 3 mg of granisetron intravenously, before cisplatin. On days 1-6, patients received 8 mg of dexamethasone and 1 mg of granisetron twice daily by oral administration. Protection was assessed during all cycles and calculated based on cumulative probability analyses using the method of Kaplan-Meier and a model for transitional probabilities. Irrespective of the type of analysis used, the anti-emetic efficacy of granisetron/dexamethasone decreased over cycles. The initial complete acute emesis protection rate of 66% decreased to 30% according to the method of Kaplan-Meier and to 39% using the model for transitional probabilities. For delayed emesis, the initial complete protection rate of 52% decreased to 21% (Kaplan-Meier) and to 43% (transitional probabilities). In addition, we observed that protection failure in the delayed emesis period adversely influenced the acute emesis protection in the next cycle. We conclude that the anti-emetic efficacy of a 5HT3 antagonist plus dexamethasone is not maintained over multiple cycles of highly emetogenic chemotherapy, and that the acute emesis protection is adversely influenced by protection failure in the delayed emesis phase. PMID:9652766

A new statistical methodology predicting chip failure probability considering electromigration

NASA Astrophysics Data System (ADS)

Sun, Ted

In this research thesis, we present a new approach to analyze chip reliability subject to electromigration (EM) whose fundamental causes and EM phenomenon happened in different materials are presented in this thesis. This new approach utilizes the statistical nature of EM failure in order to assess overall EM risk. It includes within-die temperature variations from the chip's temperature map extracted by an Electronic Design Automation (EDA) tool to estimate the failure probability of a design. Both the power estimation and thermal analysis are performed in the EDA flow. We first used the traditional EM approach to analyze the design with a single temperature across the entire chip that involves 6 metal and 5 via layers. Next, we used the same traditional approach but with a realistic temperature map. The traditional EM analysis approach and that coupled with a temperature map and the comparison between the results of considering and not considering temperature map are presented in in this research. A comparison between these two results confirms that using a temperature map yields a less pessimistic estimation of the chip's EM risk. Finally, we employed the statistical methodology we developed considering a temperature map and different use-condition voltages and frequencies to estimate the overall failure probability of the chip. The statistical model established considers the scaling work with the usage of traditional Black equation and four major conditions. The statistical result comparisons are within our expectations. The results of this statistical analysis confirm that the chip level failure probability is higher i) at higher use-condition frequencies for all use-condition voltages, and ii) when a single temperature instead of a temperature map across the chip is considered. In this thesis, I start with an overall review on current design types, common flows, and necessary verifications and reliability checking steps used in this IC design industry. Furthermore, the important concepts about "Scripting Automation" which is used in all the integration of using diversified EDA tools in this research work are also described in detail with several examples and my completed coding works are also put in the appendix for your reference. Hopefully, this construction of my thesis will give readers a thorough understanding about my research work from the automation of EDA tools to the statistical data generation, from the nature of EM to the statistical model construction, and the comparisons among the traditional EM analysis and the statistical EM analysis approaches.

Contraceptive Failure in the United States: Estimates from the 2006-2010 National Survey of Family Growth.

PubMed

Sundaram, Aparna; Vaughan, Barbara; Kost, Kathryn; Bankole, Akinrinola; Finer, Lawrence; Singh, Susheela; Trussell, James

2017-03-01

Contraceptive failure rates measure a woman's probability of becoming pregnant while using a contraceptive. Information about these rates enables couples to make informed contraceptive choices. Failure rates were last estimated for 2002, and social and economic changes that have occurred since then necessitate a reestimation. To estimate failure rates for the most commonly used reversible methods in the United States, data from the 2006-2010 National Survey of Family Growth were used; some 15,728 contraceptive use intervals, contributed by 6,683 women, were analyzed. Data from the Guttmacher Institute's 2008 Abortion Patient Survey were used to adjust for abortion underreporting. Kaplan-Meier methods were used to estimate the associated single-decrement probability of failure by duration of use. Failure rates were compared with those from 1995 and 2002. Long-acting reversible contraceptives (the IUD and the implant) had the lowest failure rates of all methods (1%), while condoms and withdrawal carried the highest probabilities of failure (13% and 20%, respectively). However, the failure rate for the condom had declined significantly since 1995 (from 18%), as had the failure rate for all hormonal methods combined (from 8% to 6%). The failure rate for all reversible methods combined declined from 12% in 2002 to 10% in 2006-2010. These broad-based declines in failure rates reverse a long-term pattern of minimal change. Future research should explore what lies behind these trends, as well as possibilities for further improvements. © 2017 The Authors. Perspectives on Sexual and Reproductive Health published by Wiley Periodicals, Inc., on behalf of the Guttmacher Institute.

Inclusion of Radiation Environment Variability in Total Dose Hardness Assurance Methodology

NASA Technical Reports Server (NTRS)

Xapsos, M. A.; Stauffer, C.; Phan, A.; McClure, S. S.; Ladbury, R. L.; Pellish, J. A.; Campola, M. J.; LaBel, K. A.

2015-01-01

Variability of the space radiation environment is investigated with regard to parts categorization for total dose hardness assurance methods. It is shown that it can have a significant impact. A modified approach is developed that uses current environment models more consistently and replaces the design margin concept with one of failure probability.

Mechanical failure probability of glasses in Earth orbit

NASA Technical Reports Server (NTRS)

Kinser, Donald L.; Wiedlocher, David E.

1992-01-01

Results of five years of earth-orbital exposure on mechanical properties of glasses indicate that radiation effects on mechanical properties of glasses, for the glasses examined, are less than the probable error of measurement. During the 5 year exposure, seven micrometeorite or space debris impacts occurred on the samples examined. These impacts were located in locations which were not subjected to effective mechanical testing, hence limited information on their influence upon mechanical strength was obtained. Combination of these results with micrometeorite and space debris impact frequency obtained by other experiments permits estimates of the failure probability of glasses exposed to mechanical loading under earth-orbit conditions. This probabilistic failure prediction is described and illustrated with examples.

Probabilistic Plan Management

DTIC Science & Technology

2009-11-17

set of chains , the step adds scheduled methods that have an a priori likelihood of a failure outcome (Lines 3-5). It identifies the max eul value of the...activity meeting its objective, as well as its expected contribution to the schedule. By explicitly calculating these values , PADS is able to summarize the...variables. One of the main difficulties of this model is convolving the probability density functions and value functions while solving the model; this

[Survival analysis with competing risks: estimating failure probability].

PubMed

Llorca, Javier; Delgado-Rodríguez, Miguel

2004-01-01

To show the impact of competing risks of death on survival analysis. We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model. The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks. Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.

A new algorithm for finding survival coefficients employed in reliability equations

NASA Technical Reports Server (NTRS)

Bouricius, W. G.; Flehinger, B. J.

1973-01-01

Product reliabilities are predicted from past failure rates and reasonable estimate of future failure rates. Algorithm is used to calculate probability that product will function correctly. Algorithm sums the probabilities of each survival pattern and number of permutations for that pattern, over all possible ways in which product can survive.

A chi-square goodness-of-fit test for non-identically distributed random variables: with application to empirical Bayes

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

Conover, W.J.; Cox, D.D.; Martz, H.F.

1997-12-01

When using parametric empirical Bayes estimation methods for estimating the binomial or Poisson parameter, the validity of the assumed beta or gamma conjugate prior distribution is an important diagnostic consideration. Chi-square goodness-of-fit tests of the beta or gamma prior hypothesis are developed for use when the binomial sample sizes or Poisson exposure times vary. Nine examples illustrate the application of the methods, using real data from such diverse applications as the loss of feedwater flow rates in nuclear power plants, the probability of failure to run on demand and the failure rates of the high pressure coolant injection systems atmore » US commercial boiling water reactors, the probability of failure to run on demand of emergency diesel generators in US commercial nuclear power plants, the rate of failure of aircraft air conditioners, baseball batting averages, the probability of testing positive for toxoplasmosis, and the probability of tumors in rats. The tests are easily applied in practice by means of corresponding Mathematica{reg_sign} computer programs which are provided.« less

A two-stage model of fracture of rocks

USGS Publications Warehouse

Kuksenko, V.; Tomilin, N.; Damaskinskaya, E.; Lockner, D.

1996-01-01

In this paper we propose a two-stage model of rock fracture. In the first stage, cracks or local regions of failure are uncorrelated occur randomly throughout the rock in response to loading of pre-existing flaws. As damage accumulates in the rock, there is a gradual increase in the probability that large clusters of closely spaced cracks or local failure sites will develop. Based on statistical arguments, a critical density of damage will occur where clusters of flaws become large enough to lead to larger-scale failure of the rock (stage two). While crack interaction and cooperative failure is expected to occur within clusters of closely spaced cracks, the initial development of clusters is predicted based on the random variation in pre-existing Saw populations. Thus the onset of the unstable second stage in the model can be computed from the generation of random, uncorrelated damage. The proposed model incorporates notions of the kinetic (and therefore time-dependent) nature of the strength of solids as well as the discrete hierarchic structure of rocks and the flaw populations that lead to damage accumulation. The advantage offered by this model is that its salient features are valid for fracture processes occurring over a wide range of scales including earthquake processes. A notion of the rank of fracture (fracture size) is introduced, and criteria are presented for both fracture nucleation and the transition of the failure process from one scale to another.

Design solutions for the solar cell interconnect fatigue fracture problem

NASA Technical Reports Server (NTRS)

Mon, G. R.; Ross, R. G., Jr.

1982-01-01

Mechanical fatigue of solar cell interconnects is a major failure mechanism in photovoltaic arrays. A comprehensive approach to the reliability design of interconnects, together with extensive design data for the fatigue properties of copper interconnects, has been published. This paper extends the previous work, developing failure prediction (fatigue) data for additional interconnect material choices, including aluminum and a variety of copper-Invar and copper-steel claddings. An improved global fatigue function is used to model the probability-of-failure statistics of each material as a function of level and number of cycles of applied strain. Life-cycle economic analyses are used to evaluate the relative merits of each material choce. The copper-Invar clad composites demonstrate superior performance over pure copper. Aluminum results are disappointing.

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.

Monte Carlo Simulation of Markov, Semi-Markov, and Generalized Semi- Markov Processes in Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

English, Thomas

2005-01-01

A standard tool of reliability analysis used at NASA-JSC is the event tree. An event tree is simply a probability tree, with the probabilities determining the next step through the tree specified at each node. The nodal probabilities are determined by a reliability study of the physical system at work for a particular node. The reliability study performed at a node is typically referred to as a fault tree analysis, with the potential of a fault tree existing.for each node on the event tree. When examining an event tree it is obvious why the event tree/fault tree approach has been adopted. Typical event trees are quite complex in nature, and the event tree/fault tree approach provides a systematic and organized approach to reliability analysis. The purpose of this study was two fold. Firstly, we wanted to explore the possibility that a semi-Markov process can create dependencies between sojourn times (the times it takes to transition from one state to the next) that can decrease the uncertainty when estimating time to failures. Using a generalized semi-Markov model, we studied a four element reliability model and were able to demonstrate such sojourn time dependencies. Secondly, we wanted to study the use of semi-Markov processes to introduce a time variable into the event tree diagrams that are commonly developed in PRA (Probabilistic Risk Assessment) analyses. Event tree end states which change with time are more representative of failure scenarios than are the usual static probability-derived end states.

Methodology for Collision Risk Assessment of an Airspace Flow Corridor Concept

NASA Astrophysics Data System (ADS)

Zhang, Yimin

This dissertation presents a methodology to estimate the collision risk associated with a future air-transportation concept called the flow corridor. The flow corridor is a Next Generation Air Transportation System (NextGen) concept to reduce congestion and increase throughput in en-route airspace. The flow corridor has the potential to increase throughput by reducing the controller workload required to manage aircraft outside the corridor and by reducing separation of aircraft within corridor. The analysis in this dissertation is a starting point for the safety analysis required by the Federal Aviation Administration (FAA) to eventually approve and implement the corridor concept. This dissertation develops a hybrid risk analysis methodology that combines Monte Carlo simulation with dynamic event tree analysis. The analysis captures the unique characteristics of the flow corridor concept, including self-separation within the corridor, lane change maneuvers, speed adjustments, and the automated separation assurance system. Monte Carlo simulation is used to model the movement of aircraft in the flow corridor and to identify precursor events that might lead to a collision. Since these precursor events are not rare, standard Monte Carlo simulation can be used to estimate these occurrence rates. Dynamic event trees are then used to model the subsequent series of events that may lead to collision. When two aircraft are on course for a near-mid-air collision (NMAC), the on-board automated separation assurance system provides a series of safety layers to prevent the impending NNAC or collision. Dynamic event trees are used to evaluate the potential failures of these layers in order to estimate the rare-event collision probabilities. The results show that the throughput can be increased by reducing separation to 2 nautical miles while maintaining the current level of safety. A sensitivity analysis shows that the most critical parameters in the model related to the overall collision probability are the minimum separation, the probability that both flights fail to respond to traffic collision avoidance system, the probability that an NMAC results in a collision, the failure probability of the automatic dependent surveillance broadcast in receiver, and the conflict detection probability.

Local linear estimation of concordance probability with application to covariate effects models on association for bivariate failure-time data.

PubMed

Ding, Aidong Adam; Hsieh, Jin-Jian; Wang, Weijing

2015-01-01

Bivariate survival analysis has wide applications. In the presence of covariates, most literature focuses on studying their effects on the marginal distributions. However covariates can also affect the association between the two variables. In this article we consider the latter issue by proposing a nonstandard local linear estimator for the concordance probability as a function of covariates. Under the Clayton copula, the conditional concordance probability has a simple one-to-one correspondence with the copula parameter for different data structures including those subject to independent or dependent censoring and dependent truncation. The proposed method can be used to study how covariates affect the Clayton association parameter without specifying marginal regression models. Asymptotic properties of the proposed estimators are derived and their finite-sample performances are examined via simulations. Finally, for illustration, we apply the proposed method to analyze a bone marrow transplant data set.

SPACE PROPULSION SYSTEM PHASED-MISSION PROBABILITY ANALYSIS USING CONVENTIONAL PRA METHODS

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

Curtis Smith; James Knudsen

As part of a series of papers on the topic of advance probabilistic methods, a benchmark phased-mission problem has been suggested. This problem consists of modeling a space mission using an ion propulsion system, where the mission consists of seven mission phases. The mission requires that the propulsion operate for several phases, where the configuration changes as a function of phase. The ion propulsion system itself consists of five thruster assemblies and a single propellant supply, where each thruster assembly has one propulsion power unit and two ion engines. In this paper, we evaluate the probability of mission failure usingmore » the conventional methodology of event tree/fault tree analysis. The event tree and fault trees are developed and analyzed using Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE). While the benchmark problem is nominally a "dynamic" problem, in our analysis the mission phases are modeled in a single event tree to show the progression from one phase to the next. The propulsion system is modeled in fault trees to account for the operation; or in this case, the failure of the system. Specifically, the propulsion system is decomposed into each of the five thruster assemblies and fed into the appropriate N-out-of-M gate to evaluate mission failure. A separate fault tree for the propulsion system is developed to account for the different success criteria of each mission phase. Common-cause failure modeling is treated using traditional (i.e., parametrically) methods. As part of this paper, we discuss the overall results in addition to the positive and negative aspects of modeling dynamic situations with non-dynamic modeling techniques. One insight from the use of this conventional method for analyzing the benchmark problem is that it requires significant manual manipulation to the fault trees and how they are linked into the event tree. The conventional method also requires editing the resultant cut sets to obtain the correct results. While conventional methods may be used to evaluate a dynamic system like that in the benchmark, the level of effort required may preclude its use on real-world problems.« less

Enhancing the Possibility of Success by Measuring the Probability of Failure in an Educational Program.

ERIC Educational Resources Information Center

Brookhart, Susan M.; And Others

1997-01-01

Process Analysis is described as a method for identifying and measuring the probability of events that could cause the failure of a program, resulting in a cause-and-effect tree structure of events. The method is illustrated through the evaluation of a pilot instructional program at an elementary school. (SLD)

The Influence of Improper Sets of Information on Judgment: How Irrelevant Information Can Bias Judged Probability

ERIC Educational Resources Information Center

Dougherty, Michael R.; Sprenger, Amber

2006-01-01

This article introduces 2 new sources of bias in probability judgment, discrimination failure and inhibition failure, which are conceptualized as arising from an interaction between error prone memory processes and a support theory like comparison process. Both sources of bias stem from the influence of irrelevant information on participants'…

A detailed description of the sequential probability ratio test for 2-IMU FDI

NASA Technical Reports Server (NTRS)

Rich, T. M.

1976-01-01

The sequential probability ratio test (SPRT) for 2-IMU FDI (inertial measuring unit failure detection/isolation) is described. The SPRT is a statistical technique for detecting and isolating soft IMU failures originally developed for the strapdown inertial reference unit. The flowchart of a subroutine incorporating the 2-IMU SPRT is included.

Optimized Vertex Method and Hybrid Reliability

NASA Technical Reports Server (NTRS)

Smith, Steven A.; Krishnamurthy, T.; Mason, B. H.

2002-01-01

A method of calculating the fuzzy response of a system is presented. This method, called the Optimized Vertex Method (OVM), is based upon the vertex method but requires considerably fewer function evaluations. The method is demonstrated by calculating the response membership function of strain-energy release rate for a bonded joint with a crack. The possibility of failure of the bonded joint was determined over a range of loads. After completing the possibilistic analysis, the possibilistic (fuzzy) membership functions were transformed to probability density functions and the probability of failure of the bonded joint was calculated. This approach is called a possibility-based hybrid reliability assessment. The possibility and probability of failure are presented and compared to a Monte Carlo Simulation (MCS) of the bonded joint.

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

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

Dickson, T.L.; Simonen, F.A.

1992-05-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

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

Dickson, T.L.; Simonen, F.A.

1992-01-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

Probabilistic evaluation of seismic isolation effect with respect to siting of a fusion reactor facility

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

Takeda, Masatoshi; Komura, Toshiyuki; Hirotani, Tsutomu

1995-12-01

Annual failure probabilities of buildings and equipment were roughly evaluated for two fusion-reactor-like buildings, with and without seismic base isolation, in order to examine the effectiveness of the base isolation system regarding siting issues. The probabilities are calculated considering nonlinearity and rupture of isolators. While the probability of building failure for both buildings on the same site was almost equal, the function failures for equipment showed that the base-isolated building had higher reliability than the non-isolated building. Even if the base-isolated building alone is located on a higher seismic hazard area, it could compete favorably with the ordinary one inmore » reliability of equipment.« less

Challenges for pharmaceutical industry: new partnerships for sustainable human health.

PubMed

Hunter, Jackie

2011-05-13

The healthcare burden is increasing in both the developed and the developing world and there is widespread acceptance that the historical pharmaceutical business model is not sustainable. In order to meet the healthcare challenge, companies and academia need to develop new business models to increase the probability of success and decrease the cost of failure. New partnerships have already emerged in the area of neglected diseases and other models for diseases of the developed world are emerging. © 2011 Royal Society

Data Analysis

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

Powell, Danny H; Elwood Jr, Robert H

2011-01-01

Analysis of the material protection, control, and accountability (MPC&A) system is necessary to understand the limits and vulnerabilities of the system to internal threats. A self-appraisal helps the facility be prepared to respond to internal threats and reduce the risk of theft or diversion of nuclear material. The material control and accountability (MC&A) system effectiveness tool (MSET) fault tree was developed to depict the failure of the MPC&A system as a result of poor practices and random failures in the MC&A system. It can also be employed as a basis for assessing deliberate threats against a facility. MSET uses faultmore » tree analysis, which is a top-down approach to examining system failure. The analysis starts with identifying a potential undesirable event called a 'top event' and then determining the ways it can occur (e.g., 'Fail To Maintain Nuclear Materials Under The Purview Of The MC&A System'). The analysis proceeds by determining how the top event can be caused by individual or combined lower level faults or failures. These faults, which are the causes of the top event, are 'connected' through logic gates. The MSET model uses AND-gates and OR-gates and propagates the effect of event failure using Boolean algebra. To enable the fault tree analysis calculations, the basic events in the fault tree are populated with probability risk values derived by conversion of questionnaire data to numeric values. The basic events are treated as independent variables. This assumption affects the Boolean algebraic calculations used to calculate results. All the necessary calculations are built into the fault tree codes, but it is often useful to estimate the probabilities manually as a check on code functioning. The probability of failure of a given basic event is the probability that the basic event primary question fails to meet the performance metric for that question. The failure probability is related to how well the facility performs the task identified in that basic event over time (not just one performance or exercise). Fault tree calculations provide a failure probability for the top event in the fault tree. The basic fault tree calculations establish a baseline relative risk value for the system. This probability depicts relative risk, not absolute risk. Subsequent calculations are made to evaluate the change in relative risk that would occur if system performance is improved or degraded. During the development effort of MSET, the fault tree analysis program used was SAPHIRE. SAPHIRE is an acronym for 'Systems Analysis Programs for Hands-on Integrated Reliability Evaluations.' Version 1 of the SAPHIRE code was sponsored by the Nuclear Regulatory Commission in 1987 as an innovative way to draw, edit, and analyze graphical fault trees primarily for safe operation of nuclear power reactors. When the fault tree calculations are performed, the fault tree analysis program will produce several reports that can be used to analyze the MPC&A system. SAPHIRE produces reports showing risk importance factors for all basic events in the operational MC&A system. The risk importance information is used to examine the potential impacts when performance of certain basic events increases or decreases. The initial results produced by the SAPHIRE program are considered relative risk values. None of the results can be interpreted as absolute risk values since the basic event probability values represent estimates of risk associated with the performance of MPC&A tasks throughout the material balance area (MBA). The RRR for a basic event represents the decrease in total system risk that would result from improvement of that one event to a perfect performance level. Improvement of the basic event with the greatest RRR value produces a greater decrease in total system risk than improvement of any other basic event. Basic events with the greatest potential for system risk reduction are assigned performance improvement values, and new fault tree calculations show the improvement in total system risk. The operational impact or cost-effectiveness from implementing the performance improvements can then be evaluated. The improvements being evaluated can be system performance improvements, or they can be potential, or actual, upgrades to the system. The RIR for a basic event represents the increase in total system risk that would result from failure of that one event. Failure of the basic event with the greatest RIR value produces a greater increase in total system risk than failure of any other basic event. Basic events with the greatest potential for system risk increase are assigned failure performance values, and new fault tree calculations show the increase in total system risk. This evaluation shows the importance of preventing performance degradation of the basic events. SAPHIRE identifies combinations of basic events where concurrent failure of the events results in failure of the top event.« less

Lognormal Approximations of Fault Tree Uncertainty Distributions.

PubMed

El-Shanawany, Ashraf Ben; Ardron, Keith H; Walker, Simon P

2018-01-26

Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed-form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling-based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed-form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks's method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models. © 2018 Society for Risk Analysis.

Robustness of assembly supply chain networks by considering risk propagation and cascading failure

NASA Astrophysics Data System (ADS)

Tang, Liang; Jing, Ke; He, Jie; Stanley, H. Eugene

2016-10-01

An assembly supply chain network (ASCN) is composed of manufacturers located in different geographical regions. To analyze the robustness of this ASCN when it suffers from catastrophe disruption events, we construct a cascading failure model of risk propagation. In our model, different disruption scenarios s are considered and the probability equation of all disruption scenarios is developed. Using production capability loss as the robustness index (RI) of an ASCN, we conduct a numerical simulation to assess its robustness. Through simulation, we compare the network robustness at different values of linking intensity and node threshold and find that weak linking intensity or high node threshold increases the robustness of the ASCN. We also compare network robustness levels under different disruption scenarios.

Inclusion of Radiation Environment Variability in Total Dose Hardness Assurance Methodology

NASA Technical Reports Server (NTRS)

Xapsos, M. A.; Stauffer, C.; Phan, A.; McClure, S. S.; Ladbury, R. L.; Pellish, J. A.; Campola, M. J.; LaBel, K. A.

2016-01-01

Variability of the space radiation environment is investigated with regard to parts categorization for total dose hardness assurance methods. It is shown that it can have a significant impact. A modified approach is developed that uses current environment models more consistently and replaces the radiation design margin concept with one of failure probability during a mission.

Conceptual modeling of coincident failures in multiversion software

NASA Technical Reports Server (NTRS)

Littlewood, Bev; Miller, Douglas R.

1989-01-01

Recent work by Eckhardt and Lee (1985) shows that independently developed program versions fail dependently (specifically, simultaneous failure of several is greater than would be the case under true independence). The present authors show there is a precise duality between input choice and program choice in this model and consider a generalization in which different versions can be developed using diverse methodologies. The use of diverse methodologies is shown to decrease the probability of the simultaneous failure of several versions. Indeed, it is theoretically possible to obtain versions which exhibit better than independent failure behavior. The authors try to formalize the notion of methodological diversity by considering the sequence of decision outcomes that constitute a methodology. They show that diversity of decision implies likely diversity of behavior for the different verions developed under such forced diversity. For certain one-out-of-n systems the authors obtain an optimal method for allocating diversity between versions. For two-out-of-three systems there seem to be no simple optimality results which do not depend on constraints which cannot be verified in practice.

Risk analysis of gravity dam instability using credibility theory Monte Carlo simulation model.

PubMed

Xin, Cao; Chongshi, Gu

2016-01-01

Risk analysis of gravity dam stability involves complicated uncertainty in many design parameters and measured data. Stability failure risk ratio described jointly by probability and possibility has deficiency in characterization of influence of fuzzy factors and representation of the likelihood of risk occurrence in practical engineering. In this article, credibility theory is applied into stability failure risk analysis of gravity dam. Stability of gravity dam is viewed as a hybrid event considering both fuzziness and randomness of failure criterion, design parameters and measured data. Credibility distribution function is conducted as a novel way to represent uncertainty of influence factors of gravity dam stability. And combining with Monte Carlo simulation, corresponding calculation method and procedure are proposed. Based on a dam section, a detailed application of the modeling approach on risk calculation of both dam foundation and double sliding surfaces is provided. The results show that, the present method is feasible to be applied on analysis of stability failure risk for gravity dams. The risk assessment obtained can reflect influence of both sorts of uncertainty, and is suitable as an index value.

Evaluation of design parameters for TRISO-coated fuel particles to establish manufacturing critical limits using PARFUME

DOE PAGES

Skerjanc, William F.; Maki, John T.; Collin, Blaise P.; ...

2015-12-02

The success of modular high temperature gas-cooled reactors is highly dependent on the performance of the tristructural-isotopic (TRISO) coated fuel particle and the quality to which it can be manufactured. During irradiation, TRISO-coated fuel particles act as a pressure vessel to contain fission gas and mitigate the diffusion of fission products to the coolant boundary. The fuel specifications place limits on key attributes to minimize fuel particle failure under irradiation and postulated accident conditions. PARFUME (an integrated mechanistic coated particle fuel performance code developed at the Idaho National Laboratory) was used to calculate fuel particle failure probabilities. By systematically varyingmore » key TRISO-coated particle attributes, failure probability functions were developed to understand how each attribute contributes to fuel particle failure. Critical manufacturing limits were calculated for the key attributes of a low enriched TRISO-coated nuclear fuel particle with a kernel diameter of 425 μm. As a result, these critical manufacturing limits identify ranges beyond where an increase in fuel particle failure probability is expected to occur.« less

Structural Reliability Analysis and Optimization: Use of Approximations

NASA Technical Reports Server (NTRS)

Grandhi, Ramana V.; Wang, Liping

1999-01-01

This report is intended for the demonstration of function approximation concepts and their applicability in reliability analysis and design. Particularly, approximations in the calculation of the safety index, failure probability and structural optimization (modification of design variables) are developed. With this scope in mind, extensive details on probability theory are avoided. Definitions relevant to the stated objectives have been taken from standard text books. The idea of function approximations is to minimize the repetitive use of computationally intensive calculations by replacing them with simpler closed-form equations, which could be nonlinear. Typically, the approximations provide good accuracy around the points where they are constructed, and they need to be periodically updated to extend their utility. There are approximations in calculating the failure probability of a limit state function. The first one, which is most commonly discussed, is how the limit state is approximated at the design point. Most of the time this could be a first-order Taylor series expansion, also known as the First Order Reliability Method (FORM), or a second-order Taylor series expansion (paraboloid), also known as the Second Order Reliability Method (SORM). From the computational procedure point of view, this step comes after the design point identification; however, the order of approximation for the probability of failure calculation is discussed first, and it is denoted by either FORM or SORM. The other approximation of interest is how the design point, or the most probable failure point (MPP), is identified. For iteratively finding this point, again the limit state is approximated. The accuracy and efficiency of the approximations make the search process quite practical for analysis intensive approaches such as the finite element methods; therefore, the crux of this research is to develop excellent approximations for MPP identification and also different approximations including the higher-order reliability methods (HORM) for representing the failure surface. This report is divided into several parts to emphasize different segments of the structural reliability analysis and design. Broadly, it consists of mathematical foundations, methods and applications. Chapter I discusses the fundamental definitions of the probability theory, which are mostly available in standard text books. Probability density function descriptions relevant to this work are addressed. In Chapter 2, the concept and utility of function approximation are discussed for a general application in engineering analysis. Various forms of function representations and the latest developments in nonlinear adaptive approximations are presented with comparison studies. Research work accomplished in reliability analysis is presented in Chapter 3. First, the definition of safety index and most probable point of failure are introduced. Efficient ways of computing the safety index with a fewer number of iterations is emphasized. In chapter 4, the probability of failure prediction is presented using first-order, second-order and higher-order methods. System reliability methods are discussed in chapter 5. Chapter 6 presents optimization techniques for the modification and redistribution of structural sizes for improving the structural reliability. The report also contains several appendices on probability parameters.

Response analysis of curved bridge with unseating failure control system under near-fault ground motions

NASA Astrophysics Data System (ADS)

Zuo, Ye; Sun, Guangjun; Li, Hongjing

2018-01-01

Under the action of near-fault ground motions, curved bridges are prone to pounding, local damage of bridge components and even unseating. A multi-scale fine finite element model of a typical three-span curved bridge is established by considering the elastic-plastic behavior of piers and pounding effect of adjacent girders. The nonlinear time-history method is used to study the seismic response of the curved bridge equipped with unseating failure control system under the action of near-fault ground motion. An in-depth analysis is carried to evaluate the control effect of the proposed unseating failure control system. The research results indicate that under the near-fault ground motion, the seismic response of the curved bridge is strong. The unseating failure control system perform effectively to reduce the pounding force of the adjacent girders and the probability of deck unseating.

Nodal failure index approach to groundwater remediation design

USGS Publications Warehouse

Lee, J.; Reeves, H.W.; Dowding, C.H.

2008-01-01

Computer simulations often are used to design and to optimize groundwater remediation systems. We present a new computationally efficient approach that calculates the reliability of remedial design at every location in a model domain with a single simulation. The estimated reliability and other model information are used to select a best remedial option for given site conditions, conceptual model, and available data. To evaluate design performance, we introduce the nodal failure index (NFI) to determine the number of nodal locations at which the probability of success is below the design requirement. The strength of the NFI approach is that selected areas of interest can be specified for analysis and the best remedial design determined for this target region. An example application of the NFI approach using a hypothetical model shows how the spatial distribution of reliability can be used for a decision support system in groundwater remediation design. ?? 2008 ASCE.

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.

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.

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

PubMed

Pérez, M A

2012-12-01

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

Estimation in a semi-Markov transformation model

PubMed Central

Dabrowska, Dorota M.

2012-01-01

Multi-state models provide a common tool for analysis of longitudinal failure time data. In biomedical applications, models of this kind are often used to describe evolution of a disease and assume that patient may move among a finite number of states representing different phases in the disease progression. Several authors developed extensions of the proportional hazard model for analysis of multi-state models in the presence of covariates. In this paper, we consider a general class of censored semi-Markov and modulated renewal processes and propose the use of transformation models for their analysis. Special cases include modulated renewal processes with interarrival times specified using transformation models, and semi-Markov processes with with one-step transition probabilities defined using copula-transformation models. We discuss estimation of finite and infinite dimensional parameters of the model, and develop an extension of the Gaussian multiplier method for setting confidence bands for transition probabilities. A transplant outcome data set from the Center for International Blood and Marrow Transplant Research is used for illustrative purposes. PMID:22740583

Analysis of risk factors for cluster behavior of dental implant failures.

PubMed

Chrcanovic, Bruno Ramos; Kisch, Jenö; Albrektsson, Tomas; Wennerberg, Ann

2017-08-01

Some studies indicated that implant failures are commonly concentrated in few patients. To identify and analyze cluster behavior of dental implant failures among subjects of a retrospective study. This retrospective study included patients receiving at least three implants only. Patients presenting at least three implant failures were classified as presenting a cluster behavior. Univariate and multivariate logistic regression models and generalized estimating equations analysis evaluated the effect of explanatory variables on the cluster behavior. There were 1406 patients with three or more implants (8337 implants, 592 failures). Sixty-seven (4.77%) patients presented cluster behavior, with 56.8% of all implant failures. The intake of antidepressants and bruxism were identified as potential negative factors exerting a statistically significant influence on a cluster behavior at the patient-level. The negative factors at the implant-level were turned implants, short implants, poor bone quality, age of the patient, the intake of medicaments to reduce the acid gastric production, smoking, and bruxism. A cluster pattern among patients with implant failure is highly probable. Factors of interest as predictors for implant failures could be a number of systemic and local factors, although a direct causal relationship cannot be ascertained. © 2017 Wiley Periodicals, Inc.

Individual versus systemic risk and the Regulator's Dilemma

PubMed Central

Beale, Nicholas; Rand, David G.; Battey, Heather; Croxson, Karen; May, Robert M.; Nowak, Martin A.

2011-01-01

The global financial crisis of 2007–2009 exposed critical weaknesses in the financial system. Many proposals for financial reform address the need for systemic regulation—that is, regulation focused on the soundness of the whole financial system and not just that of individual institutions. In this paper, we study one particular problem faced by a systemic regulator: the tension between the distribution of assets that individual banks would like to hold and the distribution across banks that best supports system stability if greater weight is given to avoiding multiple bank failures. By diversifying its risks, a bank lowers its own probability of failure. However, if many banks diversify their risks in similar ways, then the probability of multiple failures can increase. As more banks fail simultaneously, the economic disruption tends to increase disproportionately. We show that, in model systems, the expected systemic cost of multiple failures can be largely explained by two global parameters of risk exposure and diversity, which can be assessed in terms of the risk exposures of individual actors. This observation hints at the possibility of regulatory intervention to promote systemic stability by incentivizing a more diverse diversification among banks. Such intervention offers the prospect of an additional lever in the armory of regulators, potentially allowing some combination of improved system stability and reduced need for additional capital. PMID:21768387

Uncertainty Quantification of the FUN3D-Predicted NASA CRM Flutter Boundary

NASA Technical Reports Server (NTRS)

Stanford, Bret K.; Massey, Steven J.

2017-01-01

A nonintrusive point collocation method is used to propagate parametric uncertainties of the flexible Common Research Model, a generic transport configuration, through the unsteady aeroelastic CFD solver FUN3D. A range of random input variables are considered, including atmospheric flow variables, structural variables, and inertial (lumped mass) variables. UQ results are explored for a range of output metrics (with a focus on dynamic flutter stability), for both subsonic and transonic Mach numbers, for two different CFD mesh refinements. A particular focus is placed on computing failure probabilities: the probability that the wing will flutter within the flight envelope.

Differential reliability : probabilistic engineering applied to wood members in bending-tension

Treesearch

Stanley K. Suddarth; Frank E. Woeste; William L. Galligan

1978-01-01

Reliability analysis is a mathematical technique for appraising the design and materials of engineered structures to provide a quantitative estimate of probability of failure. Two or more cases which are similar in all respects but one may be analyzed by this method; the contrast between the probabilities of failure for these cases allows strong analytical focus on the...

Fuzzy Bayesian Network-Bow-Tie Analysis of Gas Leakage during Biomass Gasification

PubMed Central

Yan, Fang; Xu, Kaili; Yao, Xiwen; Li, Yang

2016-01-01

Biomass gasification technology has been rapidly developed recently. But fire and poisoning accidents caused by gas leakage restrict the development and promotion of biomass gasification. Therefore, probabilistic safety assessment (PSA) is necessary for biomass gasification system. Subsequently, Bayesian network-bow-tie (BN-bow-tie) analysis was proposed by mapping bow-tie analysis into Bayesian network (BN). Causes of gas leakage and the accidents triggered by gas leakage can be obtained by bow-tie analysis, and BN was used to confirm the critical nodes of accidents by introducing corresponding three importance measures. Meanwhile, certain occurrence probability of failure was needed in PSA. In view of the insufficient failure data of biomass gasification, the occurrence probability of failure which cannot be obtained from standard reliability data sources was confirmed by fuzzy methods based on expert judgment. An improved approach considered expert weighting to aggregate fuzzy numbers included triangular and trapezoidal numbers was proposed, and the occurrence probability of failure was obtained. Finally, safety measures were indicated based on the obtained critical nodes. The theoretical occurrence probabilities in one year of gas leakage and the accidents caused by it were reduced to 1/10.3 of the original values by these safety measures. PMID:27463975

On the probability of exceeding allowable leak rates through degraded steam generator tubes

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

Cizelj, L.; Sorsek, I.; Riesch-Oppermann, H.

1997-02-01

This paper discusses some possible ways of predicting the behavior of the total leak rate through the damaged steam generator tubes. This failure mode is of special concern in cases where most through-wall defects may remain In operation. A particular example is the application of alternate (bobbin coil voltage) plugging criterion to Outside Diameter Stress Corrosion Cracking at the tube support plate intersections. It is the authors aim to discuss some possible modeling options that could be applied to solve the problem formulated as: Estimate the probability that the sum of all individual leak rates through degraded tubes exceeds themore » predefined acceptable value. The probabilistic approach is of course aiming at reliable and computationaly bearable estimate of the failure probability. A closed form solution is given for a special case of exponentially distributed individual leak rates. Also, some possibilities for the use of computationaly efficient First and Second Order Reliability Methods (FORM and SORM) are discussed. The first numerical example compares the results of approximate methods with closed form results. SORM in particular shows acceptable agreement. The second numerical example considers a realistic case of NPP in Krsko, Slovenia.« less

Tiger in the fault tree jungle

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

Rubel, P.

1976-01-01

There is yet little evidence of serious efforts to apply formal reliability analysis methods to evaluate, or even to identify, potential common-mode failures (CMF) of reactor safeguard systems. The prospects for event logic modeling in this regard are examined by the primitive device of reviewing actual CMF experience in terms of what the analyst might have perceived a priori. Further insights of the probability and risks aspects of CMFs are sought through consideration of three key likelihood factors: (1) prior probability of cause ever existing, (2) opportunities for removing cause, and (3) probability that a CMF cause will be activatedmore » by conditions associated with a real system challenge. It was concluded that the principal needs for formal logical discipline in the endeavor to decrease CMF-related risks are to discover and to account for strong ''energetic'' dependency couplings that could arise in the major accidents usually classed as ''hypothetical.'' This application would help focus research, design and quality assurance efforts to cope with major CMF causes. But without extraordinary challenges to the reactor safeguard systems, there must continue to be virtually no statistical evidence pertinent to that class of failure dependencies.« less

Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

NASA Astrophysics Data System (ADS)

Li, Zhiqiang; Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

2018-04-01

This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit.

Evaluation of the safety performance of highway alignments based on fault tree analysis and safety boundaries.

PubMed

Chen, Yikai; Wang, Kai; Xu, Chengcheng; Shi, Qin; He, Jie; Li, Peiqing; Shi, Ting

2018-05-19

To overcome the limitations of previous highway alignment safety evaluation methods, this article presents a highway alignment safety evaluation method based on fault tree analysis (FTA) and the characteristics of vehicle safety boundaries, within the framework of dynamic modeling of the driver-vehicle-road system. Approaches for categorizing the vehicle failure modes while driving on highways and the corresponding safety boundaries were comprehensively investigated based on vehicle system dynamics theory. Then, an overall crash probability model was formulated based on FTA considering the risks of 3 failure modes: losing steering capability, losing track-holding capability, and rear-end collision. The proposed method was implemented on a highway segment between Bengbu and Nanjing in China. A driver-vehicle-road multibody dynamics model was developed based on the 3D alignments of the Bengbu to Nanjing section of Ning-Luo expressway using Carsim, and the dynamics indices, such as sideslip angle and, yaw rate were obtained. Then, the average crash probability of each road section was calculated with a fixed-length method. Finally, the average crash probability was validated against the crash frequency per kilometer to demonstrate the accuracy of the proposed method. The results of the regression analysis and correlation analysis indicated good consistency between the results of the safety evaluation and the crash data and that it outperformed the safety evaluation methods used in previous studies. The proposed method has the potential to be used in practical engineering applications to identify crash-prone locations and alignment deficiencies on highways in the planning and design phases, as well as those in service.

A theoretical basis for the analysis of redundant software subject to coincident errors

NASA Technical Reports Server (NTRS)

Eckhardt, D. E., Jr.; Lee, L. D.

1985-01-01

Fundamental to the development of redundant software techniques fault-tolerant software, is an understanding of the impact of multiple-joint occurrences of coincident errors. A theoretical basis for the study of redundant software is developed which provides a probabilistic framework for empirically evaluating the effectiveness of the general (N-Version) strategy when component versions are subject to coincident errors, and permits an analytical study of the effects of these errors. The basic assumptions of the model are: (1) independently designed software components are chosen in a random sample; and (2) in the user environment, the system is required to execute on a stationary input series. The intensity of coincident errors, has a central role in the model. This function describes the propensity to introduce design faults in such a way that software components fail together when executing in the user environment. The model is used to give conditions under which an N-Version system is a better strategy for reducing system failure probability than relying on a single version of software. A condition which limits the effectiveness of a fault-tolerant strategy is studied, and it is posted whether system failure probability varies monotonically with increasing N or whether an optimal choice of N exists.

Effect of non-linear fluid pressure diffusion on modeling induced seismicity during reservoir stimulation

NASA Astrophysics Data System (ADS)

Gischig, V.; Goertz-Allmann, B. P.; Bachmann, C. E.; Wiemer, S.

2012-04-01

Success of future enhanced geothermal systems relies on an appropriate pre-estimate of seismic risk associated with fluid injection at high pressure. A forward-model based on a semi-stochastic approach was created, which is able to compute synthetic earthquake catalogues. It proved to be able to reproduce characteristics of the seismic cloud detected during the geothermal project in Basel (Switzerland), such as radial dependence of stress drop and b-values as well as higher probability of large magnitude earthquakes (M>3) after shut-in. The modeling strategy relies on a simplistic fluid pressure model used to trigger failure points (so-called seeds) that are randomly distributed around an injection well. The seed points are assigned principal stress magnitudes drawn from Gaussian distributions representative of the ambient stress field. Once the effective stress state at a seed point meets a pre-defined Mohr-Coulomb failure criterion due to a fluid pressure increase a seismic event is induced. We assume a negative linear relationship between b-values and differential stress. Thus, for each event a magnitude can be drawn from a Gutenberg-Richter distribution with a b-value corresponding to differential stress at failure. The result is a seismic cloud evolving in time and space. Triggering of seismic events depends on appropriately calculating the transient fluid pressure field. Hence an effective continuum reservoir model able to reasonably reproduce the hydraulic behavior of the reservoir during stimulation is required. While analytical solutions for pressure diffusion are computationally efficient, they rely on linear pressure diffusion with constant hydraulic parameters, and only consider well head pressure while neglecting fluid injection rate. They cannot be considered appropriate in a stimulation experiment where permeability irreversibly increases by orders of magnitude during injection. We here suggest a numerical continuum model of non-linear pressure diffusion. Permeability increases both reversibly and, if a certain pressure threshold is reached, irreversibly in the form of a smoothed step-function. The models are able to reproduce realistic well head pressure magnitudes for injection rates common during reservoir stimulation. We connect this numerical model with the semi-stochastic seismicity model, and demonstrate the role of non-linear pressure diffusion on earthquakes probability estimates. We further use the model to explore various injection histories to assess the dependence of seismicity on injection strategy. It allows to qualitatively explore the probability of larger magnitude earthquakes (M>3) for different injection volumes, injection times, as well as injection build-up and shut-in strategies.

Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes’ Areas of Concern

USGS Publications Warehouse

Custer, Christine M.; Custer, Thomas W.; Etterson, Matthew A.; Dummer, Paul; Goldberg, Diana R.; Franson, J. Christian

2018-01-01

During 2010-2014, tree swallow (Tachycineta bicolor) reproductive success was monitored at 68 sites across all 5 Great Lakes, including 58 sites located within Great Lakes Areas of Concern (AOCs) and 10 non-AOCs. Sample eggs were collected from tree swallow clutches and analyzed for contaminants including polychlorinated biphenyls (PCBs), dioxins and furans, polybrominated diphenyl ethers, and 34 other organic compounds. Contaminant data were available for 360 of the clutches monitored. Markov chain multistate modeling was used to assess the importance of 5 ecological variables and 11 of the dominant contaminants in explaining the pattern of egg and nestling failure rates. Four of 5 ecological variables (Female Age, Date within season, Year, and Site) were important explanatory variables. Of the 11 contaminants, only total dioxin and furan toxic equivalents (TEQs) explained a significant amount of the egg failure probabilities. Neither total PCBs nor PCB TEQs explained the variation in egg failure rates. In a separate analysis, polycyclic aromatic hydrocarbon exposure in nestling diet, used as a proxy for female diet during egg laying, was significantly correlated with the daily probability of egg failure. The 8 sites within AOCs which had poorer reproduction when compared to 10 non-AOC sites, the measure of impaired reproduction as defined by the Great Lakes Restoration Initiative, were associated with exposure to dioxins and furan TEQs, PAHs, or depredation. Only 2 sites had poorer reproduction than the poorest performing non-AOC. Using a classic (non-modeling) approach to estimating reproductive success, 82% of nests hatched at least 1 egg, and 75% of eggs laid, excluding those collected for contaminant analyses, hatched.

Reproductive success and contaminant associations in tree swallows (Tachycineta bicolor) used to assess a Beneficial Use Impairment in U.S. and Binational Great Lakes' Areas of Concern.

PubMed

Custer, Christine M; Custer, Thomas W; Etterson, Matthew A; Dummer, Paul M; Goldberg, Diana; Franson, J Christian

2018-05-01

During 2010-2014, tree swallow (Tachycineta bicolor) reproductive success was monitored at 68 sites across all 5 Great Lakes, including 58 sites located within Great Lakes Areas of Concern (AOCs) and 10 non-AOCs. Sample eggs were collected from tree swallow clutches and analyzed for contaminants including polychlorinated biphenyls (PCBs), dioxins and furans, polybrominated diphenyl ethers, and 34 other organic compounds. Contaminant data were available for 360 of the clutches monitored. Markov chain multistate modeling was used to assess the importance of 5 ecological variables and 11 of the dominant contaminants in explaining the pattern of egg and nestling failure rates. Four of 5 ecological variables (Female Age, Date within season, Year, and Site) were important explanatory variables. Of the 11 contaminants, only total dioxin and furan toxic equivalents (TEQs) explained a significant amount of the egg failure probabilities. Neither total PCBs nor PCB TEQs explained the variation in egg failure rates. In a separate analysis, polycyclic aromatic hydrocarbon exposure in nestling diet, used as a proxy for female diet during egg laying, was significantly correlated with the daily probability of egg failure. The 8 sites within AOCs which had poorer reproduction when compared to 10 non-AOC sites, the measure of impaired reproduction as defined by the Great Lakes Restoration Initiative, were associated with exposure to dioxins and furan TEQs, PAHs, or depredation. Only 2 sites had poorer reproduction than the poorest performing non-AOC. Using a classic (non-modeling) approach to estimating reproductive success, 82% of nests hatched at least 1 egg, and 75% of eggs laid, excluding those collected for contaminant analyses, hatched.

Fault tree analysis for integrated and probabilistic risk analysis of drinking water systems.

PubMed

Lindhe, Andreas; Rosén, Lars; Norberg, Tommy; Bergstedt, Olof

2009-04-01

Drinking water systems are vulnerable and subject to a wide range of risks. To avoid sub-optimisation of risk-reduction options, risk analyses need to include the entire drinking water system, from source to tap. Such an integrated approach demands tools that are able to model interactions between different events. Fault tree analysis is a risk estimation tool with the ability to model interactions between events. Using fault tree analysis on an integrated level, a probabilistic risk analysis of a large drinking water system in Sweden was carried out. The primary aims of the study were: (1) to develop a method for integrated and probabilistic risk analysis of entire drinking water systems; and (2) to evaluate the applicability of Customer Minutes Lost (CML) as a measure of risk. The analysis included situations where no water is delivered to the consumer (quantity failure) and situations where water is delivered but does not comply with water quality standards (quality failure). Hard data as well as expert judgements were used to estimate probabilities of events and uncertainties in the estimates. The calculations were performed using Monte Carlo simulations. CML is shown to be a useful measure of risks associated with drinking water systems. The method presented provides information on risk levels, probabilities of failure, failure rates and downtimes of the system. This information is available for the entire system as well as its different sub-systems. Furthermore, the method enables comparison of the results with performance targets and acceptable levels of risk. The method thus facilitates integrated risk analysis and consequently helps decision-makers to minimise sub-optimisation of risk-reduction options.

A quantum-like model of homeopathy clinical trials: importance of in situ randomization and unblinding.

PubMed

Beauvais, Francis

2013-04-01

The randomized controlled trial (RCT) is the 'gold standard' of modern clinical pharmacology. However, for many practitioners of homeopathy, blind RCTs are an inadequate research tool for testing complex therapies such as homeopathy. Classical probabilities used in biological sciences and in medicine are only a special case of the generalized theory of probability used in quantum physics. I describe homeopathy trials using a quantum-like statistical model, a model inspired by quantum physics and taking into consideration superposition of states, non-commuting observables, probability interferences, contextuality, etc. The negative effect of blinding on success of homeopathy trials and the 'smearing effect' ('specific' effects of homeopathy medicine occurring in the placebo group) are described by quantum-like probabilities without supplementary ad hoc hypotheses. The difference of positive outcome rates between placebo and homeopathy groups frequently vanish in centralized blind trials. The model proposed here suggests a way to circumvent such problems in masked homeopathy trials by incorporating in situ randomization/unblinding. In this quantum-like model of homeopathy clinical trials, success in open-label setting and failure with centralized blind RCTs emerge logically from the formalism. This model suggests that significant differences between placebo and homeopathy in blind RCTs would be found more frequently if in situ randomization/unblinding was used. Copyright © 2013. Published by Elsevier Ltd.

Injury pattern as an indication of seat belt failure in ejected vehicle occupants.

PubMed

Freeman, Michael D; Eriksson, Anders; Leith, Wendy

2014-09-01

Prior authors have suggested that when occupant ejection occurs in association with a seat belt failure, entanglement of the outboard upper extremity (OUE) with the retracting shoulder belt will invariably occur, leaving injury pattern evidence of belt use. In the present investigation, the authors assessed this theory using data accessed from the NASS-CDS for ejected front seat occupants of passenger vehicles. Logistic regression models were used to assess the associations between seat belt failure status and injuries. Injury types associated with seat belt failure were significant OUE and head injuries (OR = 3.87, [95% CI 1.2, 13.0] and 3.1, [95% CI 1.0, 9.7], respectively). The two injury types were found to be a predictor of seat belt use and subsequent failure only if combined with a high (≥0.8) precrash probability of belt use. The injury pattern associated with a seat belt failure-related ejection has limited use in the forensic investigation of crash-related ejections. © 2014 American Academy of Forensic Sciences.

The additive value of N-terminal pro-B-type natriuretic peptide testing at the emergency department in patients with acute dyspnoea.

PubMed

van der Burg-de Graauw, N; Cobbaert, C M; Middelhoff, C J F M; Bantje, T A; van Guldener, C

2009-05-01

B-type natriuretic peptide (BNP) and its inactive counterpart NT-proBNP can help to identify or rule out heart failure in patients presenting with acute dyspnoea. It is not well known whether measurement of these peptides can be omitted in certain patient groups. We conducted a prospective observational study of 221 patients presenting with acute dyspnoea at the emergency department. The attending physicians estimated the probability of heart failure by clinical judgement. NT-proBNP was measured, but not reported. An independent panel made a final diagnosis of all available data including NT-proBNP level and judged whether and how NT-proBNP would have altered patient management. NT-proBNP levels were highest in patients with heart failure, alone or in combination with pulmonary failure. Additive value of NT-proBNP was present in 40 of 221 (18%) of the patients, and it mostly indicated that a more intensive treatment for heart failure would have been needed. Clinical judgement was an independent predictor of additive value of NT-proBNP with a maximum at a clinical probability of heart failure of 36%. NT-proBNP measurement has additive value in a substantial number of patients presenting with acute dyspnoea, but can possibly be omitted in patients with a clinical probability of heart failure of >70%.

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

Effects of Stress Ratio and Microstructure on Fatigue Failure Behavior of Polycrystalline Nickel Superalloy

NASA Astrophysics Data System (ADS)

Zhang, H.; Guan, Z. W.; Wang, Q. Y.; Liu, Y. J.; Li, J. K.

2018-05-01

The effects of microstructure and stress ratio on high cycle fatigue of nickel superalloy Nimonic 80A were investigated. The stress ratios of 0.1, 0.5 and 0.8 were chosen to perform fatigue tests in a frequency of 110 Hz. Cleavage failure was observed, and three competing failure crack initiation modes were discovered by a scanning electron microscope, which were classified as surface without facets, surface with facets and subsurface with facets. With increasing the stress ratio from 0.1 to 0.8, the occurrence probability of surface and subsurface with facets also increased and reached the maximum value at R = 0.5, meanwhile the probability of surface initiation without facets decreased. The effect of microstructure on the fatigue fracture behavior at different stress ratios was also observed and discussed. Based on the Goodman diagram, it was concluded that the fatigue strength of 50% probability of failure at R = 0.1, 0.5 and 0.8 is lower than the modified Goodman line.

Deviation from Power Law Behavior in Landslide Phenomenon

NASA Astrophysics Data System (ADS)

Li, L.; Lan, H.; Wu, Y.

2013-12-01

Power law distribution of magnitude is widely observed in many natural hazards (e.g., earthquake, floods, tornadoes, and forest fires). Landslide is unique as the size distribution of landslide is characterized by a power law decrease with a rollover in the small size end. Yet, the emergence of the rollover, i.e., the deviation from power law behavior for small size landslides, remains a mystery. In this contribution, we grouped the forces applied on landslide bodies into two categories: 1) the forces proportional to the volume of failure mass (gravity and friction), and 2) the forces proportional to the area of failure surface (cohesion). Failure occurs when the forces proportional to volume exceed the forces proportional to surface area. As such, given a certain mechanical configuration, the failure volume to failure surface area ratio must exceed a corresponding threshold to guarantee a failure. Assuming all landslides share a uniform shape, which means the volume to surface area ratio of landslide regularly increase with the landslide volume, a cutoff of landslide volume distribution in the small size end can be defined. However, in realistic landslide phenomena, where heterogeneities of landslide shape and mechanical configuration are existent, a simple cutoff of landslide volume distribution does not exist. The stochasticity of landslide shape introduce a probability distribution of the volume to surface area ratio with regard to landslide volume, with which the probability that the volume to surface ratio exceed the threshold can be estimated regarding values of landslide volume. An experiment based on empirical data showed that this probability can induce the power law distribution of landslide volume roll down in the small size end. We therefore proposed that the constraints on the failure volume to failure surface area ratio together with the heterogeneity of landslide geometry and mechanical configuration attribute for the deviation from power law behavior in landslide phenomenon. Figure shows that a rollover of landslide size distribution in the small size end is produced as the probability for V/S (the failure volume to failure surface ratio of landslide) exceeding the mechanical threshold applied to the power law distribution of landslide volume.

Tsunamis caused by submarine slope failures along western Great Bahama Bank

PubMed Central

Schnyder, Jara S.D.; Eberli, Gregor P.; Kirby, James T.; Shi, Fengyan; Tehranirad, Babak; Mulder, Thierry; Ducassou, Emmanuelle; Hebbeln, Dierk; Wintersteller, Paul

2016-01-01

Submarine slope failures are a likely cause for tsunami generation along the East Coast of the United States. Among potential source areas for such tsunamis are submarine landslides and margin collapses of Bahamian platforms. Numerical models of past events, which have been identified using high-resolution multibeam bathymetric data, reveal possible tsunami impact on Bimini, the Florida Keys, and northern Cuba. Tsunamis caused by slope failures with terminal landslide velocity of 20 ms−1 will either dissipate while traveling through the Straits of Florida, or generate a maximum wave of 1.5 m at the Florida coast. Modeling a worst-case scenario with a calculated terminal landslide velocity generates a wave of 4.5 m height. The modeled margin collapse in southwestern Great Bahama Bank potentially has a high impact on northern Cuba, with wave heights between 3.3 to 9.5 m depending on the collapse velocity. The short distance and travel time from the source areas to densely populated coastal areas would make the Florida Keys and Miami vulnerable to such low-probability but high-impact events. PMID:27811961

Tsunamis caused by submarine slope failures along western Great Bahama Bank

NASA Astrophysics Data System (ADS)

Schnyder, Jara S. D.; Eberli, Gregor P.; Kirby, James T.; Shi, Fengyan; Tehranirad, Babak; Mulder, Thierry; Ducassou, Emmanuelle; Hebbeln, Dierk; Wintersteller, Paul

2016-11-01

Submarine slope failures are a likely cause for tsunami generation along the East Coast of the United States. Among potential source areas for such tsunamis are submarine landslides and margin collapses of Bahamian platforms. Numerical models of past events, which have been identified using high-resolution multibeam bathymetric data, reveal possible tsunami impact on Bimini, the Florida Keys, and northern Cuba. Tsunamis caused by slope failures with terminal landslide velocity of 20 ms-1 will either dissipate while traveling through the Straits of Florida, or generate a maximum wave of 1.5 m at the Florida coast. Modeling a worst-case scenario with a calculated terminal landslide velocity generates a wave of 4.5 m height. The modeled margin collapse in southwestern Great Bahama Bank potentially has a high impact on northern Cuba, with wave heights between 3.3 to 9.5 m depending on the collapse velocity. The short distance and travel time from the source areas to densely populated coastal areas would make the Florida Keys and Miami vulnerable to such low-probability but high-impact events.

Tsunamis caused by submarine slope failures along western Great Bahama Bank.

PubMed

Schnyder, Jara S D; Eberli, Gregor P; Kirby, James T; Shi, Fengyan; Tehranirad, Babak; Mulder, Thierry; Ducassou, Emmanuelle; Hebbeln, Dierk; Wintersteller, Paul

2016-11-04

Submarine slope failures are a likely cause for tsunami generation along the East Coast of the United States. Among potential source areas for such tsunamis are submarine landslides and margin collapses of Bahamian platforms. Numerical models of past events, which have been identified using high-resolution multibeam bathymetric data, reveal possible tsunami impact on Bimini, the Florida Keys, and northern Cuba. Tsunamis caused by slope failures with terminal landslide velocity of 20 ms -1 will either dissipate while traveling through the Straits of Florida, or generate a maximum wave of 1.5 m at the Florida coast. Modeling a worst-case scenario with a calculated terminal landslide velocity generates a wave of 4.5 m height. The modeled margin collapse in southwestern Great Bahama Bank potentially has a high impact on northern Cuba, with wave heights between 3.3 to 9.5 m depending on the collapse velocity. The short distance and travel time from the source areas to densely populated coastal areas would make the Florida Keys and Miami vulnerable to such low-probability but high-impact events.

Diverse Redundant Systems for Reliable Space Life Support

NASA Technical Reports Server (NTRS)

Jones, Harry W.

2015-01-01

Reliable life support systems are required for deep space missions. The probability of a fatal life support failure should be less than one in a thousand in a multi-year mission. It is far too expensive to develop a single system with such high reliability. Using three redundant units would require only that each have a failure probability of one in ten over the mission. Since the system development cost is inverse to the failure probability, this would cut cost by a factor of one hundred. Using replaceable subsystems instead of full systems would further cut cost. Using full sets of replaceable components improves reliability more than using complete systems as spares, since a set of components could repair many different failures instead of just one. Replaceable components would require more tools, space, and planning than full systems or replaceable subsystems. However, identical system redundancy cannot be relied on in practice. Common cause failures can disable all the identical redundant systems. Typical levels of common cause failures will defeat redundancy greater than two. Diverse redundant systems are required for reliable space life support. Three, four, or five diverse redundant systems could be needed for sufficient reliability. One system with lower level repair could be substituted for two diverse systems to save cost.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1995-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Hidden Markov models for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic J. (Inventor)

1993-01-01

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) perpendicular to x), 1 less than or equal to i is less than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Inclusion of Radiation Environment Variability in Total Dose Hardness Assurance Methodology

PubMed Central

Xapsos, M.A.; Stauffer, C.; Phan, A.; McClure, S.S.; Ladbury, R.L.; Pellish, J.A.; Campola, M.J.; LaBel, K.A.

2017-01-01

Variability of the space radiation environment is investigated with regard to parts categorization for total dose hardness assurance methods. It is shown that it can have a significant impact. A modified approach is developed that uses current environment models more consistently and replaces the radiation design margin concept with one of failure probability during a mission. PMID:28804156

Probabilistic Prediction of Lifetimes of Ceramic Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Gyekenyesi, John P.; Jadaan, Osama M.; Palfi, Tamas; Powers, Lynn; Reh, Stefan; Baker, Eric H.

2006-01-01

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

Survival analysis of heart failure patients: A case study.

PubMed

Ahmad, Tanvir; Munir, Assia; Bhatti, Sajjad Haider; Aftab, Muhammad; Raza, Muhammad Ali

2017-01-01

This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015). All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.

Extreme Threshold Failures Within a Heterogeneous Elastic Thin Sheet and the Spatial-Temporal Development of Induced Seismicity Within the Groningen Gas Field

NASA Astrophysics Data System (ADS)

Bourne, S. J.; Oates, S. J.

2017-12-01

Measurements of the strains and earthquakes induced by fluid extraction from a subsurface reservoir reveal a transient, exponential-like increase in seismicity relative to the volume of fluids extracted. If the frictional strength of these reactivating faults is heterogeneously and randomly distributed, then progressive failures of the weakest fault patches account in a general manner for this initial exponential-like trend. Allowing for the observable elastic and geometric heterogeneity of the reservoir, the spatiotemporal evolution of induced seismicity over 5 years is predictable without significant bias using a statistical physics model of poroelastic reservoir deformations inducing extreme threshold frictional failures of previously inactive faults. This model is used to forecast the temporal and spatial probability density of earthquakes within the Groningen natural gas reservoir, conditional on future gas production plans. Probabilistic seismic hazard and risk assessments based on these forecasts inform the current gas production policy and building strengthening plans.

Reliability analysis based on the losses from failures.

PubMed

Todinov, M T

2006-04-01

The conventional reliability analysis is based on the premise that increasing the reliability of a system will decrease the losses from failures. On the basis of counterexamples, it is demonstrated that this is valid only if all failures are associated with the same losses. In case of failures associated with different losses, a system with larger reliability is not necessarily characterized by smaller losses from failures. Consequently, a theoretical framework and models are proposed for a reliability analysis, linking reliability and the losses from failures. Equations related to the distributions of the potential losses from failure have been derived. It is argued that the classical risk equation only estimates the average value of the potential losses from failure and does not provide insight into the variability associated with the potential losses. Equations have also been derived for determining the potential and the expected losses from failures for nonrepairable and repairable systems with components arranged in series, with arbitrary life distributions. The equations are also valid for systems/components with multiple mutually exclusive failure modes. The expected losses given failure is a linear combination of the expected losses from failure associated with the separate failure modes scaled by the conditional probabilities with which the failure modes initiate failure. On this basis, an efficient method for simplifying complex reliability block diagrams has been developed. Branches of components arranged in series whose failures are mutually exclusive can be reduced to single components with equivalent hazard rate, downtime, and expected costs associated with intervention and repair. A model for estimating the expected losses from early-life failures has also been developed. For a specified time interval, the expected losses from early-life failures are a sum of the products of the expected number of failures in the specified time intervals covering the early-life failures region and the expected losses given failure characterizing the corresponding time intervals. For complex systems whose components are not logically arranged in series, discrete simulation algorithms and software have been created for determining the losses from failures in terms of expected lost production time, cost of intervention, and cost of replacement. Different system topologies are assessed to determine the effect of modifications of the system topology on the expected losses from failures. It is argued that the reliability allocation in a production system should be done to maximize the profit/value associated with the system. Consequently, a method for setting reliability requirements and reliability allocation maximizing the profit by minimizing the total cost has been developed. Reliability allocation that maximizes the profit in case of a system consisting of blocks arranged in series is achieved by determining for each block individually the reliabilities of the components in the block that minimize the sum of the capital, operation costs, and the expected losses from failures. A Monte Carlo simulation based net present value (NPV) cash-flow model has also been proposed, which has significant advantages to cash-flow models based on the expected value of the losses from failures per time interval. Unlike these models, the proposed model has the capability to reveal the variation of the NPV due to different number of failures occurring during a specified time interval (e.g., during one year). The model also permits tracking the impact of the distribution pattern of failure occurrences and the time dependence of the losses from failures.

Identification of Modeling Approaches To Support Common-Cause Failure Analysis

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

Korsah, Kofi; Wood, Richard Thomas

2015-06-01

Experience with applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The impact of CCF vulnerability is to inhibit I&C modernization and, thereby, challenge the long-term sustainability of existing plants. For new plants and advanced reactor concepts, the issue of CCF vulnerability for highly integrated digital I&C systems imposes a design burden resulting in higher costs and increased complexity. The regulatory uncertainty regarding which mitigation strategies are acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adoptmore » complicated, costly solutions devised for existing plants. The conditions that constrain the transition to digital I&C technology by the U.S. nuclear industry require crosscutting research to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for usage in Nuclear Power Plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is conducting an investigation into mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive technical basis for establishing the qualification of digital technology for nuclear power applications. This report documents the investigation of modeling approaches for representing failure of I&C systems. Failure models are used when there is a need to analyze how the probability of success (or failure) of a system depends on the success (or failure) of individual elements. If these failure models are extensible to represent CCF, then they can be employed to support analysis of CCF vulnerabilities and mitigation strategies. Specifically, the research findings documented in this report identify modeling approaches that can be adapted to contribute to the basis for developing systematic methods, quantifiable measures, and objective criteria for evaluating CCF vulnerabilities and mitigation strategies.« less

A probabilistic approach for shallow rainfall-triggered landslide modeling at basin scale. A case study in the Luquillo Forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Dialynas, Y. G.; Arnone, E.; Noto, L. V.; Bras, R. L.

2013-12-01

Slope stability depends on geotechnical and hydrological factors that exhibit wide natural spatial variability, yet sufficient measurements of the related parameters are rarely available over entire study areas. The uncertainty associated with the inability to fully characterize hydrologic behavior has an impact on any attempt to model landslide hazards. This work suggests a way to systematically account for this uncertainty in coupled distributed hydrological-stability models for shallow landslide hazard assessment. A probabilistic approach for the prediction of rainfall-triggered landslide occurrence at basin scale was implemented in an existing distributed eco-hydrological and landslide model, tRIBS-VEGGIE -landslide (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator - VEGetation Generator for Interactive Evolution). More precisely, we upgraded tRIBS-VEGGIE- landslide to assess the likelihood of shallow landslides by accounting for uncertainty related to geotechnical and hydrological factors that directly affect slope stability. Natural variability of geotechnical soil characteristics was considered by randomizing soil cohesion and friction angle. Hydrological uncertainty related to the estimation of matric suction was taken into account by considering soil retention parameters as correlated random variables. The probability of failure is estimated through an assumed theoretical Factor of Safety (FS) distribution, conditioned on soil moisture content. At each cell, the temporally variant FS statistics are approximated by the First Order Second Moment (FOSM) method, as a function of parameters statistical properties. The model was applied on the Rio Mameyes Basin, located in the Luquillo Experimental Forest in Puerto Rico, where previous landslide analyses have been carried out. At each time step, model outputs include the probability of landslide occurrence across the basin, and the most probable depth of failure at each soil column. The use of the proposed probabilistic approach for shallow landslide prediction is able to reveal and quantify landslide risk at slopes assessed as stable by simpler deterministic methods.

Demonstrating the Safety and Reliability of a New System or Spacecraft: Incorporating Analyses and Reviews of the Design and Processing in Determining the Number of Tests to be Conducted

NASA Technical Reports Server (NTRS)

Vesely, William E.; Colon, Alfredo E.

2010-01-01

Design Safety/Reliability is associated with the probability of no failure-causing faults existing in a design. Confidence in the non-existence of failure-causing faults is increased by performing tests with no failure. Reliability-Growth testing requirements are based on initial assurance and fault detection probability. Using binomial tables generally gives too many required tests compared to reliability-growth requirements. Reliability-Growth testing requirements are based on reliability principles and factors and should be used.

Deterministic and reliability based optimization of integrated thermal protection system composite panel using adaptive sampling techniques

NASA Astrophysics Data System (ADS)

Ravishankar, Bharani

Conventional space vehicles have thermal protection systems (TPS) that provide protection to an underlying structure that carries the flight loads. In an attempt to save weight, there is interest in an integrated TPS (ITPS) that combines the structural function and the TPS function. This has weight saving potential, but complicates the design of the ITPS that now has both thermal and structural failure modes. The main objectives of this dissertation was to optimally design the ITPS subjected to thermal and mechanical loads through deterministic and reliability based optimization. The optimization of the ITPS structure requires computationally expensive finite element analyses of 3D ITPS (solid) model. To reduce the computational expenses involved in the structural analysis, finite element based homogenization method was employed, homogenizing the 3D ITPS model to a 2D orthotropic plate. However it was found that homogenization was applicable only for panels that are much larger than the characteristic dimensions of the repeating unit cell in the ITPS panel. Hence a single unit cell was used for the optimization process to reduce the computational cost. Deterministic and probabilistic optimization of the ITPS panel required evaluation of failure constraints at various design points. This further demands computationally expensive finite element analyses which was replaced by efficient, low fidelity surrogate models. In an optimization process, it is important to represent the constraints accurately to find the optimum design. Instead of building global surrogate models using large number of designs, the computational resources were directed towards target regions near constraint boundaries for accurate representation of constraints using adaptive sampling strategies. Efficient Global Reliability Analyses (EGRA) facilitates sequentially sampling of design points around the region of interest in the design space. EGRA was applied to the response surface construction of the failure constraints in the deterministic and reliability based optimization of the ITPS panel. It was shown that using adaptive sampling, the number of designs required to find the optimum were reduced drastically, while improving the accuracy. System reliability of ITPS was estimated using Monte Carlo Simulation (MCS) based method. Separable Monte Carlo method was employed that allowed separable sampling of the random variables to predict the probability of failure accurately. The reliability analysis considered uncertainties in the geometry, material properties, loading conditions of the panel and error in finite element modeling. These uncertainties further increased the computational cost of MCS techniques which was also reduced by employing surrogate models. In order to estimate the error in the probability of failure estimate, bootstrapping method was applied. This research work thus demonstrates optimization of the ITPS composite panel with multiple failure modes and large number of uncertainties using adaptive sampling techniques.

Model 0A wind turbine generator FMEA

NASA Technical Reports Server (NTRS)

Klein, William E.; Lalli, Vincent R.

1989-01-01

The results of Failure Modes and Effects Analysis (FMEA) conducted for the Wind Turbine Generators are presented. The FMEA was performed for the functional modes of each system, subsystem, or component. The single-point failures were eliminated for most of the systems. The blade system was the only exception. The qualitative probability of a blade separating was estimated at level D-remote. Many changes were made to the hardware as a result of this analysis. The most significant change was the addition of the safety system. Operational experience and need to improve machine availability have resulted in subsequent changes to the various systems which are also reflected in this FMEA.

Statistically qualified neuro-analytic failure detection method and system

DOEpatents

Vilim, Richard B.; Garcia, Humberto E.; Chen, Frederick W.

2002-03-02

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

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

Simonen, E.P.; Johnson, K.I.; Simonen, F.A.

The Vessel Integrity Simulation Analysis (VISA-II) code was developed to allow calculations of the failure probability of a reactor pressure vessel subject to defined pressure/temperature transients. A version of the code, revised by Pacific Northwest Laboratory for the US Nuclear Regulatory Commission, was used to evaluate the sensitivities of calculated through-wall flaw probability to material, flaw and calculational assumptions. Probabilities were more sensitive to flaw assumptions than to material or calculational assumptions. Alternative flaw assumptions changed the probabilities by one to two orders of magnitude, whereas alternative material assumptions typically changed the probabilities by a factor of two or less.more » Flaw shape, flaw through-wall position and flaw inspection were sensitivities examined. Material property sensitivities included the assumed distributions in copper content and fracture toughness. Methods of modeling flaw propagation that were evaluated included arrest/reinitiation toughness correlations, multiple toughness values along the length of a flaw, flaw jump distance for each computer simulation and added error in estimating irradiated properties caused by the trend curve correlation error.« less

Probabilistic Design of a Wind Tunnel Model to Match the Response of a Full-Scale Aircraft

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Stroud, W. Jefferson; Krishnamurthy, T.; Spain, Charles V.; Naser, Ahmad S.

2005-01-01

approach is presented for carrying out the reliability-based design of a plate-like wing that is part of a wind tunnel model. The goal is to design the wind tunnel model to match the stiffness characteristics of the wing box of a flight vehicle while satisfying strength-based risk/reliability requirements that prevents damage to the wind tunnel model and fixtures. The flight vehicle is a modified F/A-18 aircraft. The design problem is solved using reliability-based optimization techniques. The objective function to be minimized is the difference between the displacements of the wind tunnel model and the corresponding displacements of the flight vehicle. The design variables control the thickness distribution of the wind tunnel model. Displacements of the wind tunnel model change with the thickness distribution, while displacements of the flight vehicle are a set of fixed data. The only constraint imposed is that the probability of failure is less than a specified value. Failure is assumed to occur if the stress caused by aerodynamic pressure loading is greater than the specified strength allowable. Two uncertain quantities are considered: the allowable stress and the thickness distribution of the wind tunnel model. Reliability is calculated using Monte Carlo simulation with response surfaces that provide approximate values of stresses. The response surface equations are, in turn, computed from finite element analyses of the wind tunnel model at specified design points. Because the response surface approximations were fit over a small region centered about the current design, the response surfaces were refit periodically as the design variables changed. Coarse-grained parallelism was used to simultaneously perform multiple finite element analyses. Studies carried out in this paper demonstrate that this scheme of using moving response surfaces and coarse-grained computational parallelism reduce the execution time of the Monte Carlo simulation enough to make the design problem tractable. The results of the reliability-based designs performed in this paper show that large decreases in the probability of stress-based failure can be realized with only small sacrifices in the ability of the wind tunnel model to represent the displacements of the full-scale vehicle.

Probability techniques for reliability analysis of composite materials

NASA Technical Reports Server (NTRS)

Wetherhold, Robert C.; Ucci, Anthony M.

1994-01-01

Traditional design approaches for composite materials have employed deterministic criteria for failure analysis. New approaches are required to predict the reliability of composite structures since strengths and stresses may be random variables. This report will examine and compare methods used to evaluate the reliability of composite laminae. The two types of methods that will be evaluated are fast probability integration (FPI) methods and Monte Carlo methods. In these methods, reliability is formulated as the probability that an explicit function of random variables is less than a given constant. Using failure criteria developed for composite materials, a function of design variables can be generated which defines a 'failure surface' in probability space. A number of methods are available to evaluate the integration over the probability space bounded by this surface; this integration delivers the required reliability. The methods which will be evaluated are: the first order, second moment FPI methods; second order, second moment FPI methods; the simple Monte Carlo; and an advanced Monte Carlo technique which utilizes importance sampling. The methods are compared for accuracy, efficiency, and for the conservativism of the reliability estimation. The methodology involved in determining the sensitivity of the reliability estimate to the design variables (strength distributions) and importance factors is also presented.

The Simulation Heuristic.

DTIC Science & Technology

1981-05-15

Crane. is capable of imagining unicorns -- and we expect he is -- why does he find it relatively difficult to imagine himself avoiding a 30 minute...probability that the plan will succeed and to evaluate the risk of various causes of failure . We have suggested that the construction of scenarios is...expect that events will unfold as planned. However, the cumulative probability of at least one fatal failure could be overwhelmingly high even when

USAREC’S (United States Army Recruiting Command) Image to the Officer Corps Good, Bad, or Irrelevant? A Prescription for Change.

DTIC Science & Technology

1986-04-07

34 Blackhol -" * Success/failure is too clear cut * The probability of failure is greater than the probability of success The Job Itsellf (59) • Does not...indecd, it is not -- or as one officer in the survey co-ented "a blackhole ." USAHEC is a viable career oppor- tunity; it is career enhancing; and

Predictive Modelling for Fisheries Management in the Colombian Amazon

NASA Astrophysics Data System (ADS)

Beal, Jacob; Bennett, Sara

A group of Colombian indigenous communities and Amacayacu National Park are cooperating to make regulations for sustainable use of their shared natural resources, especially the fish populations. To aid this effort, we are modeling the interactions among these communities and their ecosystem with the objective of predicting the stability of regulations, identifying potential failure modes, and guiding investment of scarce resources. The goal is to improve the probability of actually achieving fair, sustainable and community-managed subsistence fishing in the region.

Reverse and Forward Translational Neuropharmacology in Psychiatric Drug Discovery.

PubMed

Shaffer, Christopher L

2018-02-01

The probability of achieving marketing approval of a novel therapeutic for psychiatric indications is extremely low due largely to the inability to demonstrate durable and reproducible efficacy in phase II trials and beyond. These failures are often attributed to the lack of translation of the underlying neuropharmacology from animal model(s) to the disease population. However, how assured is such a conclusion considering the clinical efficacy path rarely meticulously parallels the preclinical experiment(s) that underwrote it? © 2017 American Society for Clinical Pharmacology and Therapeutics.

Role of HIV Infection Duration and CD4 Cell Level at Initiation of Combination Anti-Retroviral Therapy on Risk of Failure

PubMed Central

Lodi, Sara; Phillips, Andrew; Fidler, Sarah; Hawkins, David; Gilson, Richard; McLean, Ken; Fisher, Martin; Post, Frank; Johnson, Anne M.; Walker-Nthenda, Louise; Dunn, David; Porter, Kholoud

2013-01-01

Background The development of HIV drug resistance and subsequent virological failure are often cited as potential disadvantages of early cART initiation. However, their long-term probability is not known, and neither is the role of duration of infection at the time of initiation. Methods Patients enrolled in the UK Register of HIV seroconverters were followed-up from cART initiation to last HIV-RNA measurement. Through survival analysis we examined predictors of virologic failure (2HIV-RNA ≥400 c/l while on cART) including CD4 count and HIV duration at initiation. We also estimated the cumulative probabilities of failure and drug resistance (from the available HIV nucleotide sequences) for early initiators (cART within 12 months of seroconversion). Results Of 1075 starting cART at a median (IQR) CD4 count 272 (190,370) cells/mm3 and HIV duration 3 (1,6) years, virological failure occurred in 163 (15%). Higher CD4 count at initiation, but not HIV infection duration at cART initiation, was independently associated with lower risk of failure (p=0.033 and 0.592 respectively). Among 230 patients initiating cART early, 97 (42%) discontinued it after a median of 7 months; cumulative probabilities of resistance and failure by 8 years were 7% (95% CI 4,11) and 19% (13,25), respectively. Conclusion Although the rate of discontinuation of early cART in our cohort was high, the long-term rate of virological failure was low. Our data do not support early cART initiation being associated with increased risk of failure and drug resistance. PMID:24086588

Cost-effectiveness of Out-of-Hospital Continuous Positive Airway Pressure for Acute Respiratory Failure.

PubMed

Thokala, Praveen; Goodacre, Steve; Ward, Matt; Penn-Ashman, Jerry; Perkins, Gavin D

2015-05-01

We determine the cost-effectiveness of out-of-hospital continuous positive airway pressure (CPAP) compared with standard care for adults presenting to emergency medical services with acute respiratory failure. We developed an economic model using a United Kingdom health care system perspective to compare the costs and health outcomes of out-of-hospital CPAP to standard care (inhospital noninvasive ventilation) when applied to a hypothetical cohort of patients with acute respiratory failure. The model assigned each patient a probability of intubation or death, depending on the patient's characteristics and whether he or she had out-of-hospital CPAP or standard care. The patients who survived accrued lifetime quality-adjusted life-years (QALYs) and health care costs according to their age and sex. Costs were accrued through intervention and hospital treatment costs, which depended on patient outcomes. All results were converted into US dollars, using the Organisation for Economic Co-operation and Development purchasing power parities rates. Out-of-hospital CPAP was more effective than standard care but was also more expensive, with an incremental cost-effectiveness ratio of £20,514 per QALY ($29,720/QALY) and a 49.5% probability of being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold. The probability of out-of-hospital CPAP's being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold depended on the incidence of eligible patients and varied from 35.4% when a low estimate of incidence was used to 93.8% with a high estimate. Variation in the incidence of eligible patients also had a marked influence on the expected value of sample information for a future randomized trial. The cost-effectiveness of out-of-hospital CPAP is uncertain. The incidence of patients eligible for out-of-hospital CPAP appears to be the key determinant of cost-effectiveness. Copyright © 2015 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Cost-effectiveness of Out-of-Hospital Continuous Positive Airway Pressure for Acute Respiratory Failure

PubMed Central

Thokala, Praveen; Goodacre, Steve; Ward, Matt; Penn-Ashman, Jerry; Perkins, Gavin D.

2015-01-01

Study objective We determine the cost-effectiveness of out-of-hospital continuous positive airway pressure (CPAP) compared with standard care for adults presenting to emergency medical services with acute respiratory failure. Methods We developed an economic model using a United Kingdom health care system perspective to compare the costs and health outcomes of out-of-hospital CPAP to standard care (inhospital noninvasive ventilation) when applied to a hypothetical cohort of patients with acute respiratory failure. The model assigned each patient a probability of intubation or death, depending on the patient’s characteristics and whether he or she had out-of-hospital CPAP or standard care. The patients who survived accrued lifetime quality-adjusted life-years (QALYs) and health care costs according to their age and sex. Costs were accrued through intervention and hospital treatment costs, which depended on patient outcomes. All results were converted into US dollars, using the Organisation for Economic Co-operation and Development purchasing power parities rates. Results Out-of-hospital CPAP was more effective than standard care but was also more expensive, with an incremental cost-effectiveness ratio of £20,514 per QALY ($29,720/QALY) and a 49.5% probability of being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold. The probability of out-of-hospital CPAP’s being cost-effective at the £20,000 per QALY ($29,000/QALY) threshold depended on the incidence of eligible patients and varied from 35.4% when a low estimate of incidence was used to 93.8% with a high estimate. Variation in the incidence of eligible patients also had a marked influence on the expected value of sample information for a future randomized trial. Conclusion The cost-effectiveness of out-of-hospital CPAP is uncertain. The incidence of patients eligible for out-of-hospital CPAP appears to be the key determinant of cost-effectiveness. PMID:25737210

Analysis of the progressive failure of brittle matrix composites

NASA Technical Reports Server (NTRS)

Thomas, David J.

1995-01-01

This report investigates two of the most common modes of localized failures, namely, periodic fiber-bridged matrix cracks and transverse matrix cracks. A modification of Daniels' bundle theory is combined with Weibull's weakest link theory to model the statistical distribution of the periodic matrix cracking strength for an individual layer. Results of the model predictions are compared with experimental data from the open literature. Extensions to the model are made to account for possible imperfections within the layer (i.e., nonuniform fiber lengths, irregular crack spacing, and degraded in-situ fiber properties), and the results of these studies are presented. A generalized shear-lag analysis is derived which is capable of modeling the development of transverse matrix cracks in material systems having a general multilayer configuration and under states of full in-plane load. A method for computing the effective elastic properties for the damaged layer at the global level is detailed based upon the solution for the effects of the damage at the local level. This methodology is general in nature and is therefore also applicable to (0(sub m)/90(sub n))(sub s) systems. The characteristic stress-strain response for more general cases is shown to be qualitatively correct (experimental data is not available for a quantitative evaluation), and the damage evolution is recorded in terms of the matrix crack density as a function of the applied strain. Probabilistic effects are introduced to account for the statistical nature of the material strengths, thus allowing cumulative distribution curves for the probability of failure to be generated for each of the example laminates. Additionally, Oh and Finney's classic work on fracture location in brittle materials is extended and combined with the shear-lag analysis. The result is an analytical form for predicting the probability density function for the location of the next transverse crack occurrence within a crack bounded region. The results of this study verified qualitatively the validity of assuming a uniform crack spacing (as was done in the shear-lag model).

Performance analysis of the word synchronization properties of the outer code in a TDRSS decoder

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Lin, S.

1984-01-01

A self-synchronizing coding scheme for NASA's TDRSS satellite system is a concatenation of a (2,1,7) inner convolutional code with a (255,223) Reed-Solomon outer code. Both symbol and word synchronization are achieved without requiring that any additional symbols be transmitted. An important parameter which determines the performance of the word sync procedure is the ratio of the decoding failure probability to the undetected error probability. Ideally, the former should be as small as possible compared to the latter when the error correcting capability of the code is exceeded. A computer simulation of a (255,223) Reed-Solomon code as carried out. Results for decoding failure probability and for undetected error probability are tabulated and compared.

Earth reencounter probabilities for aborted space disposal of hazardous nuclear waste

NASA Technical Reports Server (NTRS)

Friedlander, A. L.; Feingold, H.

1977-01-01

A quantitative assessment is made of the long-term risk of earth reencounter and reentry associated with aborted disposal of hazardous material in the space environment. Numerical results are presented for 10 candidate disposal options covering a broad spectrum of disposal destinations and deployment propulsion systems. Based on representative models of system failure, the probability that a single payload will return and collide with earth within a period of 250,000 years is found to lie in the range .0002-.006. Proportionately smaller risk attaches to shorter time intervals. Risk-critical factors related to trajectory geometry and system reliability are identified as possible mechanisms of hazard reduction.

Towards improving software security by using simulation to inform requirements and conceptual design

DOE PAGES

Nutaro, James J.; Allgood, Glenn O.; Kuruganti, Teja

2015-06-17

We illustrate the use of modeling and simulation early in the system life-cycle to improve security and reduce costs. The models that we develop for this illustration are inspired by problems in reliability analysis and supervisory control, for which similar models are used to quantify failure probabilities and rates. In the context of security, we propose that models of this general type can be used to understand trades between risk and cost while writing system requirements and during conceptual design, and thereby significantly reduce the need for expensive security corrections after a system enters operation

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.

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).

Statin Treatment and Clinical Outcomes of Heart Failure Among Africans: An Inverse Probability Treatment Weighted Analysis.

PubMed

Bonsu, Kwadwo Osei; Owusu, Isaac Kofi; Buabeng, Kwame Ohene; Reidpath, Daniel D; Kadirvelu, Amudha

2017-04-01

Randomized control trials of statins have not demonstrated significant benefits in outcomes of heart failure (HF). However, randomized control trials may not always be generalizable. The aim was to determine whether statin and statin type-lipophilic or -hydrophilic improve long-term outcomes in Africans with HF. This was a retrospective longitudinal study of HF patients aged ≥18 years hospitalized at a tertiary healthcare center between January 1, 2009 and December 31, 2013 in Ghana. Patients were eligible if they were discharged from first admission for HF (index admission) and followed up to time of all-cause, cardiovascular, and HF mortality or end of study. Multivariable time-dependent Cox model and inverse-probability-of-treatment weighting of marginal structural model were used to estimate associations between statin treatment and outcomes. Adjusted hazard ratios were also estimated for lipophilic and hydrophilic statin compared with no statin use. The study included 1488 patients (mean age 60.3±14.2 years) with 9306 person-years of observation. Using the time-dependent Cox model, the 5-year adjusted hazard ratios with 95% CI for statin treatment on all-cause, cardiovascular, and HF mortality were 0.68 (0.55-0.83), 0.67 (0.54-0.82), and 0.63 (0.51-0.79), respectively. Use of inverse-probability-of-treatment weighting resulted in estimates of 0.79 (0.65-0.96), 0.77 (0.63-0.96), and 0.77 (0.61-0.95) for statin treatment on all-cause, cardiovascular, and HF mortality, respectively, compared with no statin use. Among Africans with HF, statin treatment was associated with significant reduction in mortality. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Reliability Quantification of Advanced Stirling Convertor (ASC) Components

NASA Technical Reports Server (NTRS)

Shah, Ashwin R.; Korovaichuk, Igor; Zampino, Edward

2010-01-01

The Advanced Stirling Convertor, is intended to provide power for an unmanned planetary spacecraft and has an operational life requirement of 17 years. Over this 17 year mission, the ASC must provide power with desired performance and efficiency and require no corrective maintenance. Reliability demonstration testing for the ASC was found to be very limited due to schedule and resource constraints. Reliability demonstration must involve the application of analysis, system and component level testing, and simulation models, taken collectively. Therefore, computer simulation with limited test data verification is a viable approach to assess the reliability of ASC components. This approach is based on physics-of-failure mechanisms and involves the relationship among the design variables based on physics, mechanics, material behavior models, interaction of different components and their respective disciplines such as structures, materials, fluid, thermal, mechanical, electrical, etc. In addition, these models are based on the available test data, which can be updated, and analysis refined as more data and information becomes available. The failure mechanisms and causes of failure are included in the analysis, especially in light of the new information, in order to develop guidelines to improve design reliability and better operating controls to reduce the probability of failure. Quantified reliability assessment based on fundamental physical behavior of components and their relationship with other components has demonstrated itself to be a superior technique to conventional reliability approaches based on utilizing failure rates derived from similar equipment or simply expert judgment.

Risk Analysis and Prediction of Floor Failure Mechanisms at Longwall Face in Parvadeh-I Coal Mine using Rock Engineering System (RES)

NASA Astrophysics Data System (ADS)

Aghababaei, Sajjad; Saeedi, Gholamreza; Jalalifar, Hossein

2016-05-01

The floor failure at longwall face decreases productivity and safety, increases operation costs, and causes other serious problems. In Parvadeh-I coal mine, the timber is used to prevent the puncture of powered support base into the floor. In this paper, a rock engineering system (RES)-based model is presented to evaluate the risk of floor failure mechanisms at the longwall face of E 2 and W 1 panels. The presented model is used to determine the most probable floor failure mechanism, effective factors, damaged regions and remedial actions. From the analyzed results, it is found that soft floor failure is dominant in the floor failure mechanism at Parvadeh-I coal mine. The average of vulnerability index (VI) for soft, buckling and compressive floor failure mechanisms was estimated equal to 52, 43 and 30 for both panels, respectively. By determining the critical VI for soft floor failure mechanism equal to 54, the percentage of regions with VIs beyond the critical VI in E 2 and W 1 panels is equal to 65.5 and 30, respectively. The percentage of damaged regions showed that the excess amount of used timber to prevent the puncture of weak floor below the powered support base is equal to 4,180,739 kg. RES outputs and analyzed results showed that setting and yielding load of powered supports, length of face, existent water at face, geometry of powered supports, changing the cutting pattern at longwall face and limiting the panels to damaged regions with supercritical VIs could be considered to control the soft floor failure in this mine. The results of this research could be used as a useful tool to identify the damaged regions prior to mining operation at longwall panel for the same conditions.

Design of high temperature ceramic components against fast fracture and time-dependent failure using cares/life

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

Jadaan, O.M.; Powers, L.M.; Nemeth, N.N.

1995-08-01

A probabilistic design methodology which predicts the fast fracture and time-dependent failure behavior of thermomechanically loaded ceramic components is discussed using the CARES/LIFE integrated design computer program. Slow crack growth (SCG) is assumed to be the mechanism responsible for delayed failure behavior. Inert strength and dynamic fatigue data obtained from testing coupon specimens (O-ring and C-ring specimens) are initially used to calculate the fast fracture and SCG material parameters as a function of temperature using the parameter estimation techniques available with the CARES/LIFE code. Finite element analysis (FEA) is used to compute the stress distributions for the tube as amore » function of applied pressure. Knowing the stress and temperature distributions and the fast fracture and SCG material parameters, the life time for a given tube can be computed. A stress-failure probability-time to failure (SPT) diagram is subsequently constructed for these tubes. Such a diagram can be used by design engineers to estimate the time to failure at a given failure probability level for a component subjected to a given thermomechanical load.« less

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

Reliability modelling and analysis of a multi-state element based on a dynamic Bayesian network

PubMed Central

Xu, Tingxue; Gu, Junyuan; Dong, Qi; Fu, Linyu

2018-01-01

This paper presents a quantitative reliability modelling and analysis method for multi-state elements based on a combination of the Markov process and a dynamic Bayesian network (DBN), taking perfect repair, imperfect repair and condition-based maintenance (CBM) into consideration. The Markov models of elements without repair and under CBM are established, and an absorbing set is introduced to determine the reliability of the repairable element. According to the state-transition relations between the states determined by the Markov process, a DBN model is built. In addition, its parameters for series and parallel systems, namely, conditional probability tables, can be calculated by referring to the conditional degradation probabilities. Finally, the power of a control unit in a failure model is used as an example. A dynamic fault tree (DFT) is translated into a Bayesian network model, and subsequently extended to a DBN. The results show the state probabilities of an element and the system without repair, with perfect and imperfect repair, and under CBM, with an absorbing set plotted by differential equations and verified. Through referring forward, the reliability value of the control unit is determined in different kinds of modes. Finally, weak nodes are noted in the control unit. PMID:29765629

Efficient Probability of Failure Calculations for QMU using Computational Geometry LDRD 13-0144 Final Report

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

Mitchell, Scott A.; Ebeida, Mohamed Salah; Romero, Vicente J.

2015-09-01

This SAND report summarizes our work on the Sandia National Laboratory LDRD project titled "Efficient Probability of Failure Calculations for QMU using Computational Geometry" which was project #165617 and proposal #13-0144. This report merely summarizes our work. Those interested in the technical details are encouraged to read the full published results, and contact the report authors for the status of the software and follow-on projects.

Oman India Pipeline: An operational repair strategy based on a rational assessment of risk

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

German, P.

1996-12-31

This paper describes the development of a repair strategy for the operational phase of the Oman India Pipeline based upon the probability and consequences of a pipeline failure. Risk analyses and cost benefit analyses performed provide guidance on the level of deepwater repair development effort appropriate for the Oman India Pipeline project and identifies critical areas toward which more intense development effort should be directed. The risk analysis results indicate that the likelihood of a failure of the Oman India Pipeline during its 40-year life is low. Furthermore, the probability of operational failure of the pipeline in deepwater regions ismore » extremely low, the major proportion of operational failure risk being associated with the shallow water regions.« less

Lessons Learned from Dependency Usage in HERA: Implications for THERP-Related HRA Methods

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

April M. Whaley; Ronald L. Boring; Harold S. Blackman

Dependency occurs when the probability of success or failure on one action changes the probability of success or failure on a subsequent action. Dependency may serve as a modifier on the human error probabilities (HEPs) for successive actions in human reliability analysis (HRA) models. Discretion should be employed when determining whether or not a dependency calculation is warranted: dependency should not be assigned without strongly grounded reasons. Human reliability analysts may sometimes assign dependency in cases where it is unwarranted. This inappropriate assignment is attributed to a lack of clear guidance to encompass the range of scenarios human reliability analystsmore » are addressing. Inappropriate assignment of dependency produces inappropriately elevated HEP values. Lessons learned about dependency usage in the Human Event Repository and Analysis (HERA) system may provide clarification and guidance for analysts using first-generation HRA methods. This paper presents the HERA approach to dependency assessment and discusses considerations for dependency usage in HRA, including the cognitive basis for dependency, direction for determining when dependency should be assessed, considerations for determining the dependency level, temporal issues to consider when assessing dependency, (e.g., considering task sequence versus overall event sequence, and dependency over long periods of time), and diagnosis and action influences on dependency.« less

Performance Analysis of IEEE 802.15.6 CSMA/CA Protocol for WBAN Medical Scenario through DTMC Model.

PubMed

Kumar, Vivek; Gupta, Bharat

2016-12-01

The newly drafted IEEE 802.15.6 standard for Wireless Body Area Networks (WBAN) has been concentrating on a numerous medical and non-medical applications. Such short range wireless communication standard offers ultra-low power consumption with variable data rates from few Kbps to Mbps in, on or around the proximity of the human body. In this paper, the performance analysis of carrier sense multiple access with collision avoidance (CSMA/CA) scheme based on IEEE 802.15.6 standard in terms of throughput, reliability, clear channel assessment (CCA) failure probability, packet drop probability, and end-to-end delay has been presented. We have developed a discrete-time Markov chain (DTMC) to significantly evaluate the performances of IEEE 802.15.6 CSMA/CA under non-ideal channel condition having saturated traffic condition including node wait time and service time. We also visualize that, as soon as the payload length increases the CCA failure probability increases, which results in lower node's reliability. Also, we have calculated the end-to-end delay in order to prioritize the node wait time cause by backoff and retransmission. The user priority (UP) wise DTMC analysis has been performed to show the importance of the standard especially for medical scenario.

Effect of Surge Current Testing on Reliability of Solid Tantalum Capacitors

NASA Technical Reports Server (NTRS)

Teverovsky, Alexander

2008-01-01

Tantalum capacitors manufactured per military specifications are established reliability components and have less than 0.001% of failures per 1000 hours for grades D or S, thus positioning these parts among electronic components with the highest reliability characteristics. Still, failures of tantalum capacitors do happen and when it occurs it might have catastrophic consequences for the system. To reduce this risk, further development of a screening and qualification system with special attention to the possible deficiencies in the existing procedures is necessary. The purpose of this work is evaluation of the effect of surge current stress testing on reliability of the parts at both steady-state and multiple surge current stress conditions. In order to reveal possible degradation and precipitate more failures, various part types were tested and stressed in the range of voltage and temperature conditions exceeding the specified limits. A model to estimate the probability of post-surge current testing-screening failures and measures to improve the effectiveness of the screening process has been suggested.

PROCRU: A model for analyzing crew procedures in approach to landing

NASA Technical Reports Server (NTRS)

Baron, S.; Muralidharan, R.; Lancraft, R.; Zacharias, G.

1980-01-01

A model for analyzing crew procedures in approach to landing is developed. The model employs the information processing structure used in the optimal control model and in recent models for monitoring and failure detection. Mechanisms are added to this basic structure to model crew decision making in this multi task environment. Decisions are based on probability assessments and potential mission impact (or gain). Sub models for procedural activities are included. The model distinguishes among external visual, instrument visual, and auditory sources of information. The external visual scene perception models incorporate limitations in obtaining information. The auditory information channel contains a buffer to allow for storage in memory until that information can be processed.

A novel risk assessment method for landfill slope failure: Case study application for Bhalswa Dumpsite, India.

PubMed

Jahanfar, Ali; Amirmojahedi, Mohsen; Gharabaghi, Bahram; Dubey, Brajesh; McBean, Edward; Kumar, Dinesh

2017-03-01

Rapid population growth of major urban centres in many developing countries has created massive landfills with extraordinary heights and steep side-slopes, which are frequently surrounded by illegal low-income residential settlements developed too close to landfills. These extraordinary landfills are facing high risks of catastrophic failure with potentially large numbers of fatalities. This study presents a novel method for risk assessment of landfill slope failure, using probabilistic analysis of potential failure scenarios and associated fatalities. The conceptual framework of the method includes selecting appropriate statistical distributions for the municipal solid waste (MSW) material shear strength and rheological properties for potential failure scenario analysis. The MSW material properties for a given scenario is then used to analyse the probability of slope failure and the resulting run-out length to calculate the potential risk of fatalities. In comparison with existing methods, which are solely based on the probability of slope failure, this method provides a more accurate estimate of the risk of fatalities associated with a given landfill slope failure. The application of the new risk assessment method is demonstrated with a case study for a landfill located within a heavily populated area of New Delhi, India.

On reliable control system designs. Ph.D. Thesis; [actuators

NASA Technical Reports Server (NTRS)

Birdwell, J. D.

1978-01-01

A mathematical model for use in the design of reliable multivariable control systems is discussed with special emphasis on actuator failures and necessary actuator redundancy levels. The model consists of a linear time invariant discrete time dynamical system. Configuration changes in the system dynamics are governed by a Markov chain that includes transition probabilities from one configuration state to another. The performance index is a standard quadratic cost functional, over an infinite time interval. The actual system configuration can be deduced with a one step delay. The calculation of the optimal control law requires the solution of a set of highly coupled Riccati-like matrix difference equations. Results can be used for off-line studies relating the open loop dynamics, required performance, actuator mean time to failure, and functional or identical actuator redundancy, with and without feedback gain reconfiguration strategies.

Joint analysis of epistemic and aleatory uncertainty in stability analysis for geo-hazard assessments

NASA Astrophysics Data System (ADS)

Rohmer, Jeremy; Verdel, Thierry

2017-04-01

Uncertainty analysis is an unavoidable task of stability analysis of any geotechnical systems. Such analysis usually relies on the safety factor SF (if SF is below some specified threshold), the failure is possible). The objective of the stability analysis is then to estimate the failure probability P for SF to be below the specified threshold. When dealing with uncertainties, two facets should be considered as outlined by several authors in the domain of geotechnics, namely "aleatoric uncertainty" (also named "randomness" or "intrinsic variability") and "epistemic uncertainty" (i.e. when facing "vague, incomplete or imprecise information" such as limited databases and observations or "imperfect" modelling). The benefits of separating both facets of uncertainty can be seen from a risk management perspective because: - Aleatoric uncertainty, being a property of the system under study, cannot be reduced. However, practical actions can be taken to circumvent the potentially dangerous effects of such variability; - Epistemic uncertainty, being due to the incomplete/imprecise nature of available information, can be reduced by e.g., increasing the number of tests (lab or in site survey), improving the measurement methods or evaluating calculation procedure with model tests, confronting more information sources (expert opinions, data from literature, etc.). Uncertainty treatment in stability analysis usually restricts to the probabilistic framework to represent both facets of uncertainty. Yet, in the domain of geo-hazard assessments (like landslides, mine pillar collapse, rockfalls, etc.), the validity of this approach can be debatable. In the present communication, we propose to review the major criticisms available in the literature against the systematic use of probability in situations of high degree of uncertainty. On this basis, the feasibility of using a more flexible uncertainty representation tool is then investigated, namely Possibility distributions (e.g., Baudrit et al., 2007) for geo-hazard assessments. A graphical tool is then developed to explore: 1. the contribution of both types of uncertainty, aleatoric and epistemic; 2. the regions of the imprecise or random parameters which contribute the most to the imprecision on the failure probability P. The method is applied on two case studies (a mine pillar and a steep slope stability analysis, Rohmer and Verdel, 2014) to investigate the necessity for extra data acquisition on parameters whose imprecision can hardly be modelled by probabilities due to the scarcity of the available information (respectively the extraction ratio and the cliff geometry). References Baudrit, C., Couso, I., & Dubois, D. (2007). Joint propagation of probability and possibility in risk analysis: Towards a formal framework. International Journal of Approximate Reasoning, 45(1), 82-105. Rohmer, J., & Verdel, T. (2014). Joint exploration of regional importance of possibilistic and probabilistic uncertainty in stability analysis. Computers and Geotechnics, 61, 308-315.

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.

The competing risks Cox model with auxiliary case covariates under weaker missing-at-random cause of failure.

PubMed

Nevo, Daniel; Nishihara, Reiko; Ogino, Shuji; Wang, Molin

2017-08-04

In the analysis of time-to-event data with multiple causes using a competing risks Cox model, often the cause of failure is unknown for some of the cases. The probability of a missing cause is typically assumed to be independent of the cause given the time of the event and covariates measured before the event occurred. In practice, however, the underlying missing-at-random assumption does not necessarily hold. Motivated by colorectal cancer molecular pathological epidemiology analysis, we develop a method to conduct valid analysis when additional auxiliary variables are available for cases only. We consider a weaker missing-at-random assumption, with missing pattern depending on the observed quantities, which include the auxiliary covariates. We use an informative likelihood approach that will yield consistent estimates even when the underlying model for missing cause of failure is misspecified. The superiority of our method over naive methods in finite samples is demonstrated by simulation study results. We illustrate the use of our method in an analysis of colorectal cancer data from the Nurses' Health Study cohort, where, apparently, the traditional missing-at-random assumption fails to hold.

Development of GENOA Progressive Failure Parallel Processing Software Systems

NASA Technical Reports Server (NTRS)

Abdi, Frank; Minnetyan, Levon

1999-01-01

A capability consisting of software development and experimental techniques has been developed and is described. The capability is integrated into GENOA-PFA to model polymer matrix composite (PMC) structures. The capability considers the physics and mechanics of composite materials and structure by integration of a hierarchical multilevel macro-scale (lamina, laminate, and structure) and micro scale (fiber, matrix, and interface) simulation analyses. The modeling involves (1) ply layering methodology utilizing FEM elements with through-the-thickness representation, (2) simulation of effects of material defects and conditions (e.g., voids, fiber waviness, and residual stress) on global static and cyclic fatigue strengths, (3) including material nonlinearities (by updating properties periodically) and geometrical nonlinearities (by Lagrangian updating), (4) simulating crack initiation. and growth to failure under static, cyclic, creep, and impact loads. (5) progressive fracture analysis to determine durability and damage tolerance. (6) identifying the percent contribution of various possible composite failure modes involved in critical damage events. and (7) determining sensitivities of failure modes to design parameters (e.g., fiber volume fraction, ply thickness, fiber orientation. and adhesive-bond thickness). GENOA-PFA progressive failure analysis is now ready for use to investigate the effects on structural responses to PMC material degradation from damage induced by static, cyclic (fatigue). creep, and impact loading in 2D/3D PMC structures subjected to hygrothermal environments. Its use will significantly facilitate targeting design parameter changes that will be most effective in reducing the probability of a given failure mode occurring.

Experiences with Probabilistic Analysis Applied to Controlled Systems

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Giesy, Daniel P.

2004-01-01

This paper presents a semi-analytic method for computing frequency dependent means, variances, and failure probabilities for arbitrarily large-order closed-loop dynamical systems possessing a single uncertain parameter or with multiple highly correlated uncertain parameters. The approach will be shown to not suffer from the same computational challenges associated with computing failure probabilities using conventional FORM/SORM techniques. The approach is demonstrated by computing the probabilistic frequency domain performance of an optimal feed-forward disturbance rejection scheme.

A Big Data Analysis Approach for Rail Failure Risk Assessment.

PubMed

Jamshidi, Ali; Faghih-Roohi, Shahrzad; Hajizadeh, Siamak; Núñez, Alfredo; Babuska, Robert; Dollevoet, Rolf; Li, Zili; De Schutter, Bart

2017-08-01

Railway infrastructure monitoring is a vital task to ensure rail transportation safety. A rail failure could result in not only a considerable impact on train delays and maintenance costs, but also on safety of passengers. In this article, the aim is to assess the risk of a rail failure by analyzing a type of rail surface defect called squats that are detected automatically among the huge number of records from video cameras. We propose an image processing approach for automatic detection of squats, especially severe types that are prone to rail breaks. We measure the visual length of the squats and use them to model the failure risk. For the assessment of the rail failure risk, we estimate the probability of rail failure based on the growth of squats. Moreover, we perform severity and crack growth analyses to consider the impact of rail traffic loads on defects in three different growth scenarios. The failure risk estimations are provided for several samples of squats with different crack growth lengths on a busy rail track of the Dutch railway network. The results illustrate the practicality and efficiency of the proposed approach. © 2017 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

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.

Long-term strength and damage accumulation in laminates

NASA Astrophysics Data System (ADS)

Dzenis, Yuris A.; Joshi, Shiv P.

1993-04-01

A modified version of the probabilistic model developed by authors for damage evolution analysis of laminates subjected to random loading is utilized to predict long-term strength of laminates. The model assumes that each ply in a laminate consists of a large number of mesovolumes. Probabilistic variation functions for mesovolumes stiffnesses as well as strengths are used in the analysis. Stochastic strains are calculated using the lamination theory and random function theory. Deterioration of ply stiffnesses is calculated on the basis of the probabilities of mesovolumes failures using the theory of excursions of random process beyond the limits. Long-term strength and damage accumulation in a Kevlar/epoxy laminate under tension and complex in-plane loading are investigated. Effects of the mean level and stochastic deviation of loading on damage evolution and time-to-failure of laminate are discussed. Long-term cumulative damage at the time of the final failure at low loading levels is more than at high loading levels. The effect of the deviation in loading is more pronounced at lower mean loading levels.

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.

EPRI-NASA Cooperative Project on Stress Corrosion Cracking of Zircaloys. [nuclear fuel failures

NASA Technical Reports Server (NTRS)

Cubicciotti, D.; Jones, R. L.

1978-01-01

Examinations of the inside surface of irradiated fuel cladding from two reactors show the Zircaloy cladding is exposed to a number of aggressive substances, among them iodine, cadmium, and iron-contaminated cesium. Iodine-induced stress corrosion cracking (SCC) of well characterized samples of Zircaloy sheet and tubing was studied. Results indicate that a threshold stress must be exceeded for iodine SCC to occur. The existence of a threshold stress indicates that crack formation probably is the key step in iodine SCC. Investigation of the crack formation process showed that the cracks responsible for SCC failure nucleated at locations in the metal surface that contained higher than average concentrations of alloying elements and impurities. A four-stage model of iodine SCC is proposed based on the experimental results and the relevance of the observations to pellet cladding interaction failures is discussed.

Sophisticated Calculation of the 1oo4-architecture for Safety-related Systems Conforming to IEC61508

NASA Astrophysics Data System (ADS)

Hayek, A.; Bokhaiti, M. Al; Schwarz, M. H.; Boercsoek, J.

2012-05-01

With the publication and enforcement of the standard IEC 61508 of safety related systems, recent system architectures have been presented and evaluated. Among a number of techniques and measures to the evaluation of safety integrity level (SIL) for safety-related systems, several measures such as reliability block diagrams and Markov models are used to analyze the probability of failure on demand (PFD) and mean time to failure (MTTF) which conform to IEC 61508. The current paper deals with the quantitative analysis of the novel 1oo4-architecture (one out of four) presented in recent work. Therefore sophisticated calculations for the required parameters are introduced. The provided 1oo4-architecture represents an advanced safety architecture based on on-chip redundancy, which is 3-failure safe. This means that at least one of the four channels have to work correctly in order to trigger the safety function.

Toward a Probabilistic Phenological Model for Wheat Growing Degree Days (GDD)

NASA Astrophysics Data System (ADS)

Rahmani, E.; Hense, A.

2017-12-01

Are there deterministic relations between phenological and climate parameters? The answer is surely `No'. This answer motivated us to solve the problem through probabilistic theories. Thus, we developed a probabilistic phenological model which has the advantage of giving additional information in terms of uncertainty. To that aim, we turned to a statistical analysis named survival analysis. Survival analysis deals with death in biological organisms and failure in mechanical systems. In survival analysis literature, death or failure is considered as an event. By event, in this research we mean ripening date of wheat. We will assume only one event in this special case. By time, we mean the growing duration from sowing to ripening as lifetime for wheat which is a function of GDD. To be more precise we will try to perform the probabilistic forecast for wheat ripening. The probability value will change between 0 and 1. Here, the survivor function gives the probability that the not ripened wheat survives longer than a specific time or will survive to the end of its lifetime as a ripened crop. The survival function at each station is determined by fitting a normal distribution to the GDD as the function of growth duration. Verification of the models obtained is done using CRPS skill score (CRPSS). The positive values of CRPSS indicate the large superiority of the probabilistic phonologic survival model to the deterministic models. These results demonstrate that considering uncertainties in modeling are beneficial, meaningful and necessary. We believe that probabilistic phenological models have the potential to help reduce the vulnerability of agricultural production systems to climate change thereby increasing food security.

Consecutive rebounds in plasma viral load are associated with virological failure at 52 weeks among HIV-infected patients.

PubMed

Raboud, Janet M; Rae, Sandra; Woods, Ryan; Harris, Marianne; Montaner, Julio S G

2002-08-16

To describe the characteristics and predictors of transient plasma viral load (pVL) rebounds among patients on stable antiretroviral therapy and to determine the effect of one or more pVL rebounds on virological response at week 52. Individual data were combined from 358 patients from the INCAS, AVANTI-2 and AVANTI-3 studies. Logistic regression models were used to determine the relationship between the magnitude of an increase in pVL and the probability of returning to the lower limit of quantification (LLOQ: 20-50 copies/ml) and to determine the odds of virological success at 52 weeks associated with single and consecutive pVL rebounds. A group of 165 patients achieved a pVL nadir < LLOQ; of these, 85 patients experienced pVL rebounds within 52 weeks. The probability of a pVL rebound was greater among patients who did not adhere to treatment (68% vs 49%; P < 0.05). The probability of reachieving virological suppression after a pVL rebound was not associated with the magnitude of the rebound [odds ratio (OR), 0.86; P = 0.56] but was associated with triple therapy (OR, 2.22; P = 0.06) or non-adherence (OR, 0.40; P = 0.04). The probability of virological success at week 52 was not associated with an isolated pVL rebound but was less likely after detectable pVL at two consecutive visits. An isolated pVL rebound was not associated with virological success at 52 weeks but rebounds at two consecutive visits decreased the probability of later virological success. Given their high risk of short-term virological failure, patients who present with consecutive detectable pVL measurements following complete suppression should be considered ideal candidates for intervention studies.

Probability of loss of assured safety in systems with multiple time-dependent failure modes.

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

Helton, Jon Craig; Pilch, Martin.; Sallaberry, Cedric Jean-Marie.

2012-09-01

Weak link (WL)/strong link (SL) systems are important parts of the overall operational design of high-consequence systems. In such designs, the SL system is very robust and is intended to permit operation of the entire system under, and only under, intended conditions. In contrast, the WL system is intended to fail in a predictable and irreversible manner under accident conditions and render the entire system inoperable before an accidental operation of the SL system. The likelihood that the WL system will fail to deactivate the entire system before the SL system fails (i.e., degrades into a configuration that could allowmore » an accidental operation of the entire system) is referred to as probability of loss of assured safety (PLOAS). Representations for PLOAS for situations in which both link physical properties and link failure properties are time-dependent are derived and numerically evaluated for a variety of WL/SL configurations, including PLOAS defined by (i) failure of all SLs before failure of any WL, (ii) failure of any SL before failure of any WL, (iii) failure of all SLs before failure of all WLs, and (iv) failure of any SL before failure of all WLs. The effects of aleatory uncertainty and epistemic uncertainty in the definition and numerical evaluation of PLOAS are considered.« less

Material wear and failure mode analysis of breakfast cereal extruder barrels and screw elements

NASA Astrophysics Data System (ADS)

Mastio, Michael Joseph, Jr.

2005-11-01

Nearly seventy-five years ago, the single screw extruder was introduced as a means to produce metal products. Shortly after that, the extruder found its way into the plastics industry. Today much of the world's polymer industry utilizes extruders to produce items such as soda bottles, PVC piping, and toy figurines. Given the significant economical advantages of extruders over conventional batch flow systems, extruders have also migrated into the food industry. Food applications include the meat, pet food, and cereal industries to name just a few. Cereal manufacturers utilize extruders to produce various forms of Ready-to-Eat (RTE) cereals. These cereals are made from grains such as rice, oats, wheat, and corn. The food industry has been incorrectly viewed as an extruder application requiring only minimal energy control and performance capability. This misconception has resulted in very little research in the area of material wear and failure mode analysis of breakfast cereal extruders. Breakfast cereal extruder barrels and individual screw elements are subjected to the extreme pressures and temperatures required to shear and cook the cereal ingredients, resulting in excessive material wear and catastrophic failure of these components. Therefore, this project focuses on the material wear and failure mode analysis of breakfast cereal extruder barrels and screw elements, modeled as a Discrete Time Markov Chain (DTMC) process in which historical data is used to predict future failures. Such predictive analysis will yield cost savings opportunities by providing insight into extruder maintenance scheduling and interchangeability of screw elements. In this DTMC wear analysis, four states of wear are defined and a probability transition matrix is determined based upon 24,041 hours of operational data. This probability transition matrix is used to predict when an extruder component will move to the next state of wear and/or failure. This information can be used to determine maintenance schedules and screw element interchangeability.

Elastic Rock Heterogeneity Controls Brittle Rock Failure during Hydraulic Fracturing

NASA Astrophysics Data System (ADS)

Langenbruch, C.; Shapiro, S. A.

2014-12-01

For interpretation and inversion of microseismic data it is important to understand, which properties of the reservoir rock control the occurrence probability of brittle rock failure and associated seismicity during hydraulic stimulation. This is especially important, when inverting for key properties like permeability and fracture conductivity. Although it became accepted that seismic events are triggered by fluid flow and the resulting perturbation of the stress field in the reservoir rock, the magnitude of stress perturbations, capable of triggering failure in rocks, can be highly variable. The controlling physical mechanism of this variability is still under discussion. We compare the occurrence of microseismic events at the Cotton Valley gas field to elastic rock heterogeneity, obtained from measurements along the treatment wells. The heterogeneity is characterized by scale invariant fluctuations of elastic properties. We observe that the elastic heterogeneity of the rock formation controls the occurrence of brittle failure. In particular, we find that the density of events is increasing with the Brittleness Index (BI) of the rock, which is defined as a combination of Young's modulus and Poisson's ratio. We evaluate the physical meaning of the BI. By applying geomechanical investigations we characterize the influence of fluctuating elastic properties in rocks on the probability of brittle rock failure. Our analysis is based on the computation of stress fluctuations caused by elastic heterogeneity of rocks. We find that elastic rock heterogeneity causes stress fluctuations of significant magnitude. Moreover, the stress changes necessary to open and reactivate fractures in rocks are strongly related to fluctuations of elastic moduli. Our analysis gives a physical explanation to the observed relation between elastic heterogeneity of the rock formation and the occurrence of brittle failure during hydraulic reservoir stimulations. A crucial factor for understanding seismicity in unconventional reservoirs is the role of anisotropy of rocks. We evaluate an elastic VTI rock model corresponding to a shale gas reservoir in the Horn River Basin to understand the relation between stress, event occurrence and elastic heterogeneity in anisotropic rocks.

Enhancing MPLS Protection Method with Adaptive Segment Repair

NASA Astrophysics Data System (ADS)

Chen, Chin-Ling

We propose a novel adaptive segment repair mechanism to improve traditional MPLS (Multi-Protocol Label Switching) failure recovery. The proposed mechanism protects one or more contiguous high failure probability links by dynamic setup of segment protection. Simulations demonstrate that the proposed mechanism reduces failure recovery time while also increasing network resource utilization.

Probabilistic inspection strategies for minimizing service failures

NASA Technical Reports Server (NTRS)

Brot, Abraham

1994-01-01

The INSIM computer program is described which simulates the 'limited fatigue life' environment in which aircraft structures generally operate. The use of INSIM to develop inspection strategies which aim to minimize service failures is demonstrated. Damage-tolerance methodology, inspection thresholds and customized inspections are simulated using the probability of failure as the driving parameter.

Effect of Preconditioning and Soldering on Failures of Chip Tantalum Capacitors

NASA Technical Reports Server (NTRS)

Teverovsky, Alexander A.

2014-01-01

Soldering of molded case tantalum capacitors can result in damage to Ta205 dielectric and first turn-on failures due to thermo-mechanical stresses caused by CTE mismatch between materials used in the capacitors. It is also known that presence of moisture might cause damage to plastic cases due to the pop-corning effect. However, there are only scarce literature data on the effect of moisture content on the probability of post-soldering electrical failures. In this work, that is based on a case history, different groups of similar types of CWR tantalum capacitors from two lots were prepared for soldering by bake, moisture saturation, and longterm storage at room conditions. Results of the testing showed that both factors: initial quality of the lot, and preconditioning affect the probability of failures. Baking before soldering was shown to be effective to prevent failures even in lots susceptible to pop-corning damage. Mechanism of failures is discussed and recommendations for pre-soldering bake are suggested based on analysis of moisture characteristics of materials used in the capacitors' design.

ZERODUR: deterministic approach for strength design

NASA Astrophysics Data System (ADS)

Hartmann, Peter

2012-12-01

There is an increasing request for zero expansion glass ceramic ZERODUR substrates being capable of enduring higher operational static loads or accelerations. The integrity of structures such as optical or mechanical elements for satellites surviving rocket launches, filigree lightweight mirrors, wobbling mirrors, and reticle and wafer stages in microlithography must be guaranteed with low failure probability. Their design requires statistically relevant strength data. The traditional approach using the statistical two-parameter Weibull distribution suffered from two problems. The data sets were too small to obtain distribution parameters with sufficient accuracy and also too small to decide on the validity of the model. This holds especially for the low failure probability levels that are required for reliable applications. Extrapolation to 0.1% failure probability and below led to design strengths so low that higher load applications seemed to be not feasible. New data have been collected with numbers per set large enough to enable tests on the applicability of the three-parameter Weibull distribution. This distribution revealed to provide much better fitting of the data. Moreover it delivers a lower threshold value, which means a minimum value for breakage stress, allowing of removing statistical uncertainty by introducing a deterministic method to calculate design strength. Considerations taken from the theory of fracture mechanics as have been proven to be reliable with proof test qualifications of delicate structures made from brittle materials enable including fatigue due to stress corrosion in a straight forward way. With the formulae derived, either lifetime can be calculated from given stress or allowable stress from minimum required lifetime. The data, distributions, and design strength calculations for several practically relevant surface conditions of ZERODUR are given. The values obtained are significantly higher than those resulting from the two-parameter Weibull distribution approach and no longer subject to statistical uncertainty.

Clinical implementation and failure mode and effects analysis of HDR skin brachytherapy using Valencia and Leipzig surface applicators.

PubMed

Sayler, Elaine; Eldredge-Hindy, Harriet; Dinome, Jessie; Lockamy, Virginia; Harrison, Amy S

2015-01-01

The planning procedure for Valencia and Leipzig surface applicators (VLSAs) (Nucletron, Veenendaal, The Netherlands) differs substantially from CT-based planning; the unfamiliarity could lead to significant errors. This study applies failure modes and effects analysis (FMEA) to high-dose-rate (HDR) skin brachytherapy using VLSAs to ensure safety and quality. A multidisciplinary team created a protocol for HDR VLSA skin treatments and applied FMEA. Failure modes were identified and scored by severity, occurrence, and detectability. The clinical procedure was then revised to address high-scoring process nodes. Several key components were added to the protocol to minimize risk probability numbers. (1) Diagnosis, prescription, applicator selection, and setup are reviewed at weekly quality assurance rounds. Peer review reduces the likelihood of an inappropriate treatment regime. (2) A template for HDR skin treatments was established in the clinic's electronic medical record system to standardize treatment instructions. This reduces the chances of miscommunication between the physician and planner as well as increases the detectability of an error. (3) A screen check was implemented during the second check to increase detectability of an error. (4) To reduce error probability, the treatment plan worksheet was designed to display plan parameters in a format visually similar to the treatment console display, facilitating data entry and verification. (5) VLSAs are color coded and labeled to match the electronic medical record prescriptions, simplifying in-room selection and verification. Multidisciplinary planning and FMEA increased detectability and reduced error probability during VLSA HDR brachytherapy. This clinical model may be useful to institutions implementing similar procedures. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Computing Reliabilities Of Ceramic Components Subject To Fracture

NASA Technical Reports Server (NTRS)

Nemeth, N. N.; Gyekenyesi, J. P.; Manderscheid, J. M.

1992-01-01

CARES calculates fast-fracture reliability or failure probability of macroscopically isotropic ceramic components. Program uses results from commercial structural-analysis program (MSC/NASTRAN or ANSYS) to evaluate reliability of component in presence of inherent surface- and/or volume-type flaws. Computes measure of reliability by use of finite-element mathematical model applicable to multiple materials in sense model made function of statistical characterizations of many ceramic materials. Reliability analysis uses element stress, temperature, area, and volume outputs, obtained from two-dimensional shell and three-dimensional solid isoparametric or axisymmetric finite elements. Written in FORTRAN 77.

Assessment of the risk due to release of carbon fiber in civil aircraft accidents, phase 2

NASA Technical Reports Server (NTRS)

Pocinki, L.; Cornell, M. E.; Kaplan, L.

1980-01-01

The risk associated with the potential use of carbon fiber composite material in commercial jet aircraft is investigated. A simulation model developed to generate risk profiles for several airports is described. The risk profiles show the probability that the cost due to accidents in any year exceeds a given amount. The computer model simulates aircraft accidents with fire, release of fibers, their downwind transport and infiltration of buildings, equipment failures, and resulting ecomomic impact. The individual airport results were combined to yield the national risk profile.

Structural reliability analysis under evidence theory using the active learning kriging model

NASA Astrophysics Data System (ADS)

Yang, Xufeng; Liu, Yongshou; Ma, Panke

2017-11-01

Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush-Kuhn-Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.

An Evidence Theoretic Approach to Design of Reliable Low-Cost UAVs

DTIC Science & Technology

2009-07-28

given period. For complex systems with various stages of missions, “ success ” becomes hard to define. For a UAV, for example, is success defined as...For this reason, the proposed methods in this thesis investigate probability of failure (PoF ) rather than probability of success . Further, failure will...reduction in system PoF . Figure 25 illustrates this; a single component 43 (A) from the original system (Figure 25a) is modified to act in a subsystem with

Reliability analysis of the F-8 digital fly-by-wire system

NASA Technical Reports Server (NTRS)

Brock, L. D.; Goodman, H. A.

1981-01-01

The F-8 Digital Fly-by-Wire (DFBW) flight test program intended to provide the technology for advanced control systems, giving aircraft enhanced performance and operational capability is addressed. A detailed analysis of the experimental system was performed to estimated the probabilities of two significant safety critical events: (1) loss of primary flight control function, causing reversion to the analog bypass system; and (2) loss of the aircraft due to failure of the electronic flight control system. The analysis covers appraisal of risks due to random equipment failure, generic faults in design of the system or its software, and induced failure due to external events. A unique diagrammatic technique was developed which details the combinatorial reliability equations for the entire system, promotes understanding of system failure characteristics, and identifies the most likely failure modes. The technique provides a systematic method of applying basic probability equations and is augmented by a computer program written in a modular fashion that duplicates the structure of these equations.

A multistate dynamic site occupancy model for spatially aggregated sessile communities

USGS Publications Warehouse

Fukaya, Keiichi; Royle, J. Andrew; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2017-01-01

Estimation of transition probabilities of sessile communities seems easy in principle but may still be difficult in practice because resampling error (i.e. a failure to resample exactly the same location at fixed points) may cause significant estimation bias. Previous studies have developed novel analytical methods to correct for this estimation bias. However, they did not consider the local structure of community composition induced by the aggregated distribution of organisms that is typically observed in sessile assemblages and is very likely to affect observations.We developed a multistate dynamic site occupancy model to estimate transition probabilities that accounts for resampling errors associated with local community structure. The model applies a nonparametric multivariate kernel smoothing methodology to the latent occupancy component to estimate the local state composition near each observation point, which is assumed to determine the probability distribution of data conditional on the occurrence of resampling error.By using computer simulations, we confirmed that an observation process that depends on local community structure may bias inferences about transition probabilities. By applying the proposed model to a real data set of intertidal sessile communities, we also showed that estimates of transition probabilities and of the properties of community dynamics may differ considerably when spatial dependence is taken into account.Results suggest the importance of accounting for resampling error and local community structure for developing management plans that are based on Markovian models. Our approach provides a solution to this problem that is applicable to broad sessile communities. It can even accommodate an anisotropic spatial correlation of species composition, and may also serve as a basis for inferring complex nonlinear ecological dynamics.

Using volcanic tremor for eruption forecasting at White Island volcano (Whakaari), New Zealand

NASA Astrophysics Data System (ADS)

Chardot, Lauriane; Jolly, Arthur D.; Kennedy, Ben M.; Fournier, Nicolas; Sherburn, Steven

2015-09-01

Eruption forecasting is a challenging task because of the inherent complexity of volcanic systems. Despite remarkable efforts to develop complex models in order to explain volcanic processes prior to eruptions, the material Failure Forecast Method (FFM) is one of the very few techniques that can provide a forecast time for an eruption. However, the method requires testing and automation before being used as a real-time eruption forecasting tool at a volcano. We developed an automatic algorithm to issue forecasts from volcanic tremor increase episodes recorded by Real-time Seismic Amplitude Measurement (RSAM) at one station and optimised this algorithm for the period August 2011-January 2014 which comprises the recent unrest period at White Island volcano (Whakaari), New Zealand. A detailed residual analysis was paramount to select the most appropriate model explaining the RSAM time evolutions. In a hindsight simulation, four out of the five small eruptions reported during this period occurred within a failure window forecast by our optimised algorithm and the probability of an eruption on a day within a failure window was 0.21, which is 37 times higher than the probability of having an eruption on any day during the same period (0.0057). Moreover, the forecasts were issued prior to the eruptions by a few hours which is important from an emergency management point of view. Whereas the RSAM time evolutions preceding these four eruptions have a similar goodness-of-fit with the FFM, their spectral characteristics are different. The duration-amplitude distributions of the precursory tremor episodes support the hypothesis that several processes were likely occurring prior to these eruptions. We propose that slow rock failure and fluid flow processes are plausible candidates for the tremor source of these episodes. This hindsight exercise can be useful for future real-time implementation of the FFM at White Island. A similar methodology could also be tested at other volcanoes even if only a limited network is available.

A technique for estimating the probability of radiation-stimulated failures of integrated microcircuits in low-intensity radiation fields: Application to the Spektr-R spacecraft

NASA Astrophysics Data System (ADS)

Popov, V. D.; Khamidullina, N. M.

2006-10-01

In developing radio-electronic devices (RED) of spacecraft operating in the fields of ionizing radiation in space, one of the most important problems is the correct estimation of their radiation tolerance. The “weakest link” in the element base of onboard microelectronic devices under radiation effect is the integrated microcircuits (IMC), especially of large scale (LSI) and very large scale (VLSI) degree of integration. The main characteristic of IMC, which is taken into account when making decisions on using some particular type of IMC in the onboard RED, is the probability of non-failure operation (NFO) at the end of the spacecraft’s lifetime. It should be noted that, until now, the NFO has been calculated only from the reliability characteristics, disregarding the radiation effect. This paper presents the so-called “reliability” approach to determination of radiation tolerance of IMC, which allows one to estimate the probability of non-failure operation of various types of IMC with due account of radiation-stimulated dose failures. The described technique is applied to RED onboard the Spektr-R spacecraft to be launched in 2007.

14 CFR 25.729 - Retracting mechanism.

Code of Federal Regulations, 2014 CFR

2014-01-01

... design take-off weight), occurring during retraction and extension at any airspeed up to 1.5 VSR1 (with... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any...

14 CFR 25.729 - Retracting mechanism.

Code of Federal Regulations, 2013 CFR

2013-01-01

... design take-off weight), occurring during retraction and extension at any airspeed up to 1.5 VSR1 (with... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any...

Animal Models for Studying Triazole Resistance in Aspergillus fumigatus.

PubMed

Lewis, Russell E; Verweij, Paul E

2017-08-15

Infections caused by triazole-resistant Aspergillus fumigatus are associated with a higher probability of treatment failure and mortality. Because clinical experience in managing these infections is still limited, mouse models of invasive aspergillosis fulfill a critical void for studying treatment regimens designed to overcome resistance. The type of immunosuppression, the route of infection, the timing of antifungal administration, and the end points used to assess antifungal activity affect the interpretation of data from these models. Nevertheless, these models provide important insights that help guide treatment decisions in patients with triazole-resistant invasive aspergillosis. Animal models confirmed that a high triazole minimal inhibitory concentration corresponded with triazole treatment failure and that the efficacy of other classes of drugs, such as the polyenes and echinocandins, was not affected by the presence of triazole resistance mutations. Furthermore, the feasibility of triazole dose escalation, combination therapy, and prophylaxis were explored as strategies to overcome resistance. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Economic and organizational determinants of HMO mergers and failures.

PubMed

Feldman, R; Wholey, D; Christianson, J

1996-01-01

This study analyzed data from all operational health maintenance organizations (HMOs) in the United States from 1986 through 1993. Eighty HMOs disappeared through mergers and 149 failed over that period. We estimated a multinomial logit model to predict whether an HMO would merge and survive, merge and disappear, or fail, relative to the probability of no event. We found that enrollment and profitability play a critical role in explaining HMO mergers and failures: large and profitable HMOs were more likely to merge and survive, but less likely to merge and disappear or fail. These results explain why HMO merger and failure rates fell after 1988, as most surviving HMOs became larger and more profitable. Among several market-area variables in the model, state anti-takeover regulations had a negative impact on mergers. Mergers were more likely in markets with more competing HMOs, but the overall market penetration of HMOs had no effect on mergers. This result may have important implications for the current debate over the future of the competitive health care strategy. If public policy successfully stimulates the development of large numbers of new HMOs, another wave of mergers and failures is likely to occur. But it appears that growth in overall HMO penetration will not lead inevitably to increased market concentration.

Does probability guided hysteroscopy reduce costs in women investigated for postmenopausal bleeding?

PubMed

Breijer, M C; van Hanegem, N; Visser, N C M; Verheijen, R H M; Mol, B W J; Pijnenborg, J M A; Opmeer, B C; Timmermans, A

2015-01-01

To evaluate whether a model to predict a failed endometrial biopsy in women with postmenopausal bleeding (PMB) and a thickened endometrium can reduce costs without compromising diagnostic accuracy. Model based cost-minimization analysis. A decision analytic model was designed to compare two diagnostic strategies for women with PMB: (I) attempting office endometrial biopsy and performing outpatient hysteroscopy after failed biopsy and (II) predicted probability of a failed endometrial biopsy based on patient characteristics to guide the decision for endometrial biopsy or immediate hysteroscopy. Robustness of assumptions regarding costs was evaluated in sensitivity analyses. Costs for the different strategies. At different cut-offs for the predicted probability of failure of an endometrial biopsy, strategy I was generally less expensive than strategy II. The costs for strategy I were always € 460; the costs for strategy II varied between € 457 and € 475. At a 65% cut-off, a possible saving of € 3 per woman could be achieved. Individualizing the decision to perform an endometrial biopsy or immediate hysteroscopy in women presenting with postmenopausal bleeding based on patient characteristics does not increase the efficiency of the diagnostic work-up.

Failure Surfaces for the Design of Ceramic-Lined Gun Tubes

DTIC Science & Technology

2004-12-01

density than steel making them attractive candidates as gun tube liners . A new design approach is necessary to address the large variability in strength...systems. Having established the failure criterion for the ceramic liner as the Weibull probability of failure, the need for a suitable failure...Report AMMRC SP-82-1, Materials Technology Laboratory, Watertown, Massachusetts, 1982. 7 R. Katz, Ceramic Gun Barrel Liners : Retrospect and Prospect

Second allogeneic hematopoietic cell transplantation for Patients with Fanconi anemia and Bone Marrow Failure

PubMed Central

Ayas, Mouhab; Eapen, Mary; Le-Rademacher, Jennifer; Carreras, Jeanette; Abdel-Azim, Hisham; Alter, Blanche P.; Anderlini, Paolo; Battiwalla, Minoo; Bierings, Marc; Buchbinder, David K.; Bonfim, Carmem; Camitta, Bruce M.; Fasth, Anders L.; Gale, Robert Peter; Lee, Michelle A.; Lund, Troy C.; Myers, Kasiani C.; Olsson, Richard F.; Page, Kristin M.; Prestidge, Tim D.; Radhi, Mohamed; Shah, Ami J.; Schultz, Kirk R.; Wirk, Baldeep; Wagner, John E.; Deeg, H. Joachim

2015-01-01

Second allogeneic hematopoietic cell transplantation (HCT) is the only salvage option for those for develop graft failure after their first HCT. Data on outcomes after second HCT in Fanconi anemia (FA) are scarce. We report outcomes after second allogeneic HCT for FA (n=81). The indication for second HCT was graft failure after the first HCT. Transplants occurred between 1990 and 2012. The timing of second transplantation predicted subsequent graft failure and survival. Graft failure was high when the second transplant occurred less than 3 months from the first. The 3-month probability of graft failure was 69% when the interval between first and second transplant was less than 3 months compared to 23% when the interval was longer (p<0.001). Consequently, survival rates were substantially lower when the interval between first and second transplant was less than 3 months, 23% at 1-year compared to 58%, when the interval was longer (p=0.001). The corresponding 5-year probabilities of survival were 16% and 45%, respectively (p=0.006). Taken together, these data suggest that fewer than half of FA patients undergoing a second HCT for graft failure are long-term survivors. There is an urgent need to develop strategies to lower graft failure after first HCT. PMID:26116087

A probabilistic analysis of the implications of instrument failures on ESA's Swarm mission for its individual satellite orbit deployments

NASA Astrophysics Data System (ADS)

Jackson, Andrew

2015-07-01

On launch, one of Swarm's absolute scalar magnetometers (ASMs) failed to function, leaving an asymmetrical arrangement of redundant spares on different spacecrafts. A decision was required concerning the deployment of individual satellites into the low-orbit pair or the higher "lonely" orbit. I analyse the probabilities for successful operation of two of the science components of the Swarm mission in terms of a classical probabilistic failure analysis, with a view to concluding a favourable assignment for the satellite with the single working ASM. I concentrate on the following two science aspects: the east-west gradiometer aspect of the lower pair of satellites and the constellation aspect, which requires a working ASM in each of the two orbital planes. I use the so-called "expert solicitation" probabilities for instrument failure solicited from Mission Advisory Group (MAG) members. My conclusion from the analysis is that it is better to have redundancy of ASMs in the lonely satellite orbit. Although the opposite scenario, having redundancy (and thus four ASMs) in the lower orbit, increases the chance of a working gradiometer late in the mission; it does so at the expense of a likely constellation. Although the results are presented based on actual MAG members' probabilities, the results are rather generic, excepting the case when the probability of individual ASM failure is very small; in this case, any arrangement will ensure a successful mission since there is essentially no failure expected at all. Since the very design of the lower pair is to enable common mode rejection of external signals, it is likely that its work can be successfully achieved during the first 5 years of the mission.

Misinterpretation of statistical distance in security of quantum key distribution shown by simulation

NASA Astrophysics Data System (ADS)

Iwakoshi, Takehisa; Hirota, Osamu

2014-10-01

This study will test an interpretation in quantum key distribution (QKD) that trace distance between the distributed quantum state and the ideal mixed state is a maximum failure probability of the protocol. Around 2004, this interpretation was proposed and standardized to satisfy both of the key uniformity in the context of universal composability and operational meaning of the failure probability of the key extraction. However, this proposal has not been verified concretely yet for many years while H. P. Yuen and O. Hirota have thrown doubt on this interpretation since 2009. To ascertain this interpretation, a physical random number generator was employed to evaluate key uniformity in QKD. In this way, we calculated statistical distance which correspond to trace distance in quantum theory after a quantum measurement is done, then we compared it with the failure probability whether universal composability was obtained. As a result, the degree of statistical distance of the probability distribution of the physical random numbers and the ideal uniformity was very large. It is also explained why trace distance is not suitable to guarantee the security in QKD from the view point of quantum binary decision theory.

Fatigue Failure of External Hexagon Connections on Cemented Implant-Supported Crowns.

PubMed

Malta Barbosa, João; Navarro da Rocha, Daniel; Hirata, Ronaldo; Freitas, Gileade; Bonfante, Estevam A; Coelho, Paulo G

2018-01-17

To evaluate the probability of survival and failure modes of different external hexagon connection systems restored with anterior cement-retained single-unit crowns. The postulated null hypothesis was that there would be no differences under accelerated life testing. Fifty-four external hexagon dental implants (∼4 mm diameter) were used for single cement-retained crown replacement and divided into 3 groups: (3i) Full OSSEOTITE, Biomet 3i (n = 18); (OL) OEX P4, Osseolife Implants (n = 18); and (IL) Unihex, Intra-Lock International (n = 18). Abutments were torqued to the implants, and maxillary central incisor crowns were cemented and subjected to step-stress-accelerated life testing in water. Use-level probability Weibull curves and probability of survival for a mission of 100,000 cycles at 200 N (95% 2-sided confidence intervals) were calculated. Stereo and scanning electron microscopes were used for failure inspection. The beta values for 3i, OL, and IL (1.60, 1.69, and 1.23, respectively) indicated that fatigue accelerated the failure of the 3 groups. Reliability for the 3i and OL (41% and 68%, respectively) was not different between each other, but both were significantly lower than IL group (98%). Abutment screw fracture was the failure mode consistently observed in all groups. Because the reliability was significantly different between the 3 groups, our postulated null hypothesis was rejected.

International Space Station (ISS) Meteoroid/Orbital Debris Shielding

NASA Technical Reports Server (NTRS)

Christiansen, Eric L.

1999-01-01

Design practices to provide protection for International Space Station (ISS) crew and critical equipment from meteoroid and orbital debris (M/OD) Impacts have been developed. Damage modes and failure criteria are defined for each spacecraft system. Hypervolocity Impact -1 - and analyses are used to develop ballistic limit equations (BLEs) for each exposed spacecraft system. BLEs define Impact particle sizes that result in threshold failure of a particular spacecraft system as a function of Impact velocity, angles and particle density. The BUMPER computer code Is used to determine the probability of no penetration (PNP) that falls the spacecraft shielding based on NASA standard meteoroid/debris models, a spacecraft geometry model, and the BLEs. BUMPER results are used to verify spacecraft shielding requirements Low-weight, high-performance shielding alternatives have been developed at the NASA Johnson Space Center (JSC) Hypervelocity Impact Technology Facility (HITF) to meet spacecraft protection requirements.

Emerging environmental technologies and environmental technology policy

NASA Astrophysics Data System (ADS)

Clarke, Leon Edward

This dissertation explores the role and design of environmental technology policy when environmental innovation is embodied in emerging environmental technologies such as photovoltaic cells or fuel cells. The dissertation consists of three individual studies, all of which use a simplified, general model industry between an emerging environmental technology and an entrenched, more-polluting technology. It clarifies the situations in which environmental technology policy can achieve high welfare and those in which it cannot; and it separates the possible situations an emerging environmental technology might face into four scenarios, each with its own technology policy recommendations. The second study attempts to clarify which of two factors is having a larger limiting effect on private investment in photovoltaics: the failure to internalize the environmental costs of fossil fuel electricity generation or a broad set of innovation market failures that apply to innovation irrespective of environmental concerns. The study indicates that innovation market failures are probably having a significantly larger impact than incomplete internalization. The third study explores the effectiveness of adoption subsidies at encouraging private-sector innovation. The conclusion is that adoption subsidies probably have only a limited effect on long-term, private-sector research. Two important general conclusions of the dissertation are (1) that optimal technology policy should begin with technology-push measures and end with demand-pull measures; and (2) that the technological response to internalization instruments, such as emissions taxes, may be highly nonlinear.

Security Threat Assessment of an Internet Security System Using Attack Tree and Vague Sets

PubMed Central

2014-01-01

Security threat assessment of the Internet security system has become a greater concern in recent years because of the progress and diversification of information technology. Traditionally, the failure probabilities of bottom events of an Internet security system are treated as exact values when the failure probability of the entire system is estimated. However, security threat assessment when the malfunction data of the system's elementary event are incomplete—the traditional approach for calculating reliability—is no longer applicable. Moreover, it does not consider the failure probability of the bottom events suffered in the attack, which may bias conclusions. In order to effectively solve the problem above, this paper proposes a novel technique, integrating attack tree and vague sets for security threat assessment. For verification of the proposed approach, a numerical example of an Internet security system security threat assessment is adopted in this paper. The result of the proposed method is compared with the listing approaches of security threat assessment methods. PMID:25405226

Cascading failures with local load redistribution in interdependent Watts-Strogatz networks

NASA Astrophysics Data System (ADS)

Hong, Chen; Zhang, Jun; Du, Wen-Bo; Sallan, Jose Maria; Lordan, Oriol

2016-05-01

Cascading failures of loads in isolated networks have been studied extensively over the last decade. Since 2010, such research has extended to interdependent networks. In this paper, we study cascading failures with local load redistribution in interdependent Watts-Strogatz (WS) networks. The effects of rewiring probability and coupling strength on the resilience of interdependent WS networks have been extensively investigated. It has been found that, for small values of the tolerance parameter, interdependent networks are more vulnerable as rewiring probability increases. For larger values of the tolerance parameter, the robustness of interdependent networks firstly decreases and then increases as rewiring probability increases. Coupling strength has a different impact on robustness. For low values of coupling strength, the resilience of interdependent networks decreases with the increment of the coupling strength until it reaches a certain threshold value. For values of coupling strength above this threshold, the opposite effect is observed. Our results are helpful to understand and design resilient interdependent networks.

Security threat assessment of an Internet security system using attack tree and vague sets.

PubMed

Chang, Kuei-Hu

2014-01-01

Security threat assessment of the Internet security system has become a greater concern in recent years because of the progress and diversification of information technology. Traditionally, the failure probabilities of bottom events of an Internet security system are treated as exact values when the failure probability of the entire system is estimated. However, security threat assessment when the malfunction data of the system's elementary event are incomplete--the traditional approach for calculating reliability--is no longer applicable. Moreover, it does not consider the failure probability of the bottom events suffered in the attack, which may bias conclusions. In order to effectively solve the problem above, this paper proposes a novel technique, integrating attack tree and vague sets for security threat assessment. For verification of the proposed approach, a numerical example of an Internet security system security threat assessment is adopted in this paper. The result of the proposed method is compared with the listing approaches of security threat assessment methods.

Development of a prognostic nomogram for cirrhotic patients with upper gastrointestinal bleeding.

PubMed

Zhou, Yu-Jie; Zheng, Ji-Na; Zhou, Yi-Fan; Han, Yi-Jing; Zou, Tian-Tian; Liu, Wen-Yue; Braddock, Martin; Shi, Ke-Qing; Wang, Xiao-Dong; Zheng, Ming-Hua

2017-10-01

Upper gastrointestinal bleeding (UGIB) is a complication with a high mortality rate in critically ill patients presenting with cirrhosis. Today, there exist few accurate scoring models specifically designed for mortality risk assessment in critically ill cirrhotic patients with upper gastrointestinal bleeding (CICGIB). Our aim was to develop and evaluate a novel nomogram-based model specific for CICGIB. Overall, 540 consecutive CICGIB patients were enrolled. On the basis of Cox regression analyses, the nomogram was constructed to estimate the probability of 30-day, 90-day, 270-day, and 1-year survival. An upper gastrointestinal bleeding-chronic liver failure-sequential organ failure assessment (UGIB-CLIF-SOFA) score was derived from the nomogram. Performance assessment and internal validation of the model were performed using Harrell's concordance index (C-index), calibration plot, and bootstrap sample procedures. UGIB-CLIF-SOFA was also compared with other prognostic models, such as CLIF-SOFA and model for end-stage liver disease, using C-indices. Eight independent factors derived from Cox analysis (including bilirubin, creatinine, international normalized ratio, sodium, albumin, mean artery pressure, vasopressin used, and hematocrit decrease>10%) were assembled into the nomogram and the UGIB-CLIF-SOFA score. The calibration plots showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram using bootstrap (0.729; 95% confidence interval: 0.689-0.766) was higher than that of the other models for predicting survival of CICGIB. We have developed and internally validated a novel nomogram and an easy-to-use scoring system that accurately predicts the mortality probability of CICGIB on the basis of eight easy-to-obtain parameters. External validation is now warranted in future clinical studies.

Spacecraft expected cost analysis with k-out-of-n:G subsystems

NASA Technical Reports Server (NTRS)

Patterson, Richard; Suich, Ron

1991-01-01

In designing a subsystem for a spacecraft, the design engineer is often faced with a number of options ranging from planning an inexpensive subsystem with low reliability to selecting a highly reliable system that would cost much more. We minimize the total of the cost of the subsytem and the costs that would occur if the subsystem fails. We choose the subsystem with the lowest total. A k-out-of-n:G subsystem has n modules, of which k are required to be good for the subsystem to be good. We examine two models to illustrate the principles of the k-out-of-n:G subsystem designs. For the first model, the following assumptions are necessary: the probability of failure of any module in the system is not affected by the failure of any other module; and each of the modules has the same probabillity of success. For the second model we are also free to choose k in our subsystem.

Percolation on bipartite scale-free networks

NASA Astrophysics Data System (ADS)

Hooyberghs, H.; Van Schaeybroeck, B.; Indekeu, J. O.

2010-08-01

Recent studies introduced biased (degree-dependent) edge percolation as a model for failures in real-life systems. In this work, such process is applied to networks consisting of two types of nodes with edges running only between nodes of unlike type. Such bipartite graphs appear in many social networks, for instance in affiliation networks and in sexual-contact networks in which both types of nodes show the scale-free characteristic for the degree distribution. During the depreciation process, an edge between nodes with degrees k and q is retained with a probability proportional to (, where α is positive so that links between hubs are more prone to failure. The removal process is studied analytically by introducing a generating functions theory. We deduce exact self-consistent equations describing the system at a macroscopic level and discuss the percolation transition. Critical exponents are obtained by exploiting the Fortuin-Kasteleyn construction which provides a link between our model and a limit of the Potts model.

Vibroacoustic test plan evaluation: Parameter variation study

NASA Technical Reports Server (NTRS)

Stahle, C. V.; Gongloef, H. R.

1976-01-01

Statistical decision models are shown to provide a viable method of evaluating the cost effectiveness of alternate vibroacoustic test plans and the associated test levels. The methodology developed provides a major step toward the development of a realistic tool to quantitatively tailor test programs to specific payloads. Testing is considered at the no test, component, subassembly, or system level of assembly. Component redundancy and partial loss of flight data are considered. Most and probabilistic costs are considered, and incipient failures resulting from ground tests are treated. Optimums defining both component and assembly test levels are indicated for the modified test plans considered. modeling simplifications must be considered in interpreting the results relative to a particular payload. New parameters introduced were a no test option, flight by flight failure probabilities, and a cost to design components for higher vibration requirements. Parameters varied were the shuttle payload bay internal acoustic environment, the STS launch cost, the component retest/repair cost, and the amount of redundancy in the housekeeping section of the payload reliability model.

Shuttle payload vibroacoustic test plan evaluation. Free flyer payload applications and sortie payload parametric variations

NASA Technical Reports Server (NTRS)

Stahle, C. V.; Gongloff, H. R.

1977-01-01

A preliminary assessment of vibroacoustic test plan optimization for free flyer STS payloads is presented and the effects on alternate test plans for Spacelab sortie payloads number of missions are also examined. The component vibration failure probability and the number of components in the housekeeping subassemblies are provided. Decision models are used to evaluate the cost effectiveness of seven alternate test plans using protoflight hardware.

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

Predicting Quarantine Failure Rates

PubMed Central

2004-01-01

Preemptive quarantine through contact-tracing effectively controls emerging infectious diseases. Occasionally this quarantine fails, however, and infected persons are released. The probability of quarantine failure is typically estimated from disease-specific data. Here a simple, exact estimate of the failure rate is derived that does not depend on disease-specific parameters. This estimate is universally applicable to all infectious diseases. PMID:15109418

Using occupancy models to understand the distribution of an amphibian pathogen, Batrachochytrium dendrobatidis

USGS Publications Warehouse

Adams, Michael J.; Chelgren, Nathan; Reinitz, David M.; Cole, Rebecca A.; Rachowicz, L.J.; Galvan, Stephanie; Mccreary, Brome; Pearl, Christopher A.; Bailey, Larissa L.; Bettaso, Jamie B.; Bull, Evelyn L.; Leu, Matthias

2010-01-01

Batrachochytrium dendrobatidis is a fungal pathogen that is receiving attention around the world for its role in amphibian declines. Study of its occurrence patterns is hampered by false negatives: the failure to detect the pathogen when it is present. Occupancy models are a useful but currently underutilized tool for analyzing detection data when the probability of detecting a species is <1. We use occupancy models to evaluate hypotheses concerning the occurrence and prevalence of B. dendrobatidis and discuss how this application differs from a conventional occupancy approach. We found that the probability of detecting the pathogen, conditional on presence of the pathogen in the anuran population, was related to amphibian development stage, day of the year, elevation, and human activities. Batrachochytrium dendrobatidis was found throughout our study area but was only estimated to occur in 53.4% of 78 populations of native amphibians and 66.4% of 40 populations of nonnative Rana catesbeiana tested. We found little evidence to support any spatial hypotheses concerning the probability that the pathogen occurs in a population, but did find evidence of some taxonomic variation. We discuss the interpretation of occupancy model parameters, when, unlike a conventional occupancy application, the number of potential samples or observations is finite.

Further examination of embedded performance validity indicators for the Conners' Continuous Performance Test and Brief Test of Attention in a large outpatient clinical sample.

PubMed

Sharland, Michael J; Waring, Stephen C; Johnson, Brian P; Taran, Allise M; Rusin, Travis A; Pattock, Andrew M; Palcher, Jeanette A

2018-01-01

Assessing test performance validity is a standard clinical practice and although studies have examined the utility of cognitive/memory measures, few have examined attention measures as indicators of performance validity beyond the Reliable Digit Span. The current study further investigates the classification probability of embedded Performance Validity Tests (PVTs) within the Brief Test of Attention (BTA) and the Conners' Continuous Performance Test (CPT-II), in a large clinical sample. This was a retrospective study of 615 patients consecutively referred for comprehensive outpatient neuropsychological evaluation. Non-credible performance was defined two ways: failure on one or more PVTs and failure on two or more PVTs. Classification probability of the BTA and CPT-II into non-credible groups was assessed. Sensitivity, specificity, positive predictive value, and negative predictive value were derived to identify clinically relevant cut-off scores. When using failure on two or more PVTs as the indicator for non-credible responding compared to failure on one or more PVTs, highest classification probability, or area under the curve (AUC), was achieved by the BTA (AUC = .87 vs. .79). CPT-II Omission, Commission, and Total Errors exhibited higher classification probability as well. Overall, these findings corroborate previous findings, extending them to a large clinical sample. BTA and CPT-II are useful embedded performance validity indicators within a clinical battery but should not be used in isolation without other performance validity indicators.

Modeling Disease Vector Occurrence when Detection Is Imperfect: Infestation of Amazonian Palm Trees by Triatomine Bugs at Three Spatial Scales

PubMed Central

Abad-Franch, Fernando; Ferraz, Gonçalo; Campos, Ciro; Palomeque, Francisco S.; Grijalva, Mario J.; Aguilar, H. Marcelo; Miles, Michael A.

2010-01-01

Background Failure to detect a disease agent or vector where it actually occurs constitutes a serious drawback in epidemiology. In the pervasive situation where no sampling technique is perfect, the explicit analytical treatment of detection failure becomes a key step in the estimation of epidemiological parameters. We illustrate this approach with a study of Attalea palm tree infestation by Rhodnius spp. (Triatominae), the most important vectors of Chagas disease (CD) in northern South America. Methodology/Principal Findings The probability of detecting triatomines in infested palms is estimated by repeatedly sampling each palm. This knowledge is used to derive an unbiased estimate of the biologically relevant probability of palm infestation. We combine maximum-likelihood analysis and information-theoretic model selection to test the relationships between environmental covariates and infestation of 298 Amazonian palm trees over three spatial scales: region within Amazonia, landscape, and individual palm. Palm infestation estimates are high (40–60%) across regions, and well above the observed infestation rate (24%). Detection probability is higher (∼0.55 on average) in the richest-soil region than elsewhere (∼0.08). Infestation estimates are similar in forest and rural areas, but lower in urban landscapes. Finally, individual palm covariates (accumulated organic matter and stem height) explain most of infestation rate variation. Conclusions/Significance Individual palm attributes appear as key drivers of infestation, suggesting that CD surveillance must incorporate local-scale knowledge and that peridomestic palm tree management might help lower transmission risk. Vector populations are probably denser in rich-soil sub-regions, where CD prevalence tends to be higher; this suggests a target for research on broad-scale risk mapping. Landscape-scale effects indicate that palm triatomine populations can endure deforestation in rural areas, but become rarer in heavily disturbed urban settings. Our methodological approach has wide application in infectious disease research; by improving eco-epidemiological parameter estimation, it can also significantly strengthen vector surveillance-control strategies. PMID:20209149

Progressive failure on the North Anatolian fault since 1939 by earthquake stress triggering

USGS Publications Warehouse

Stein, R.S.; Barka, A.A.; Dieterich, J.H.

1997-01-01

10 M ??? 6.7 earthquakes ruptured 1000 km of the North Anatolian fault (Turkey) during 1939-1992, providing an unsurpassed opportunity to study how one large shock sets up the next. We use the mapped surface slip and fault geometry to infer the transfer of stress throughout the sequence. Calculations of the change in Coulomb failure stress reveal that nine out of 10 ruptures were brought closer to failure by the preceding shocks, typically by 1-10 bar, equivalent to 3-30 years of secular stressing. We translate the calculated stress changes into earthquake probability gains using an earthquake-nucleation constitutive relation, which includes both permanent and transient effects of the sudden stress changes. The transient effects of the stress changes dominate during the mean 10 yr period between triggering and subsequent rupturing shocks in the Anatolia sequence. The stress changes result in an average three-fold gain in the net earthquake probability during the decade after each event. Stress is calculated to be high today at several isolated sites along the fault. During the next 30 years, we estimate a 15 per cent probability of a M ??? 6.7 earthquake east of the major eastern centre of Ercinzan, and a 12 per cent probability for a large event south of the major western port city of Izmit. Such stress-based probability calculations may thus be useful to assess and update earthquake hazards elsewhere.

Aneuploidy theory explains tumor formation, the absence of immune surveillance, and the failure of chemotherapy.

PubMed

Rasnick, David

2002-07-01

The autocatalyzed progression of aneuploidy accounts for all cancer-specific phenotypes, the Hayflick limit of cultured cells, carcinogen-induced tumors in mice, the age distribution of human cancer, and multidrug-resistance. Here aneuploidy theory addresses tumor formation. The logistic equation, phi(n)(+1) = rphi(n) (1 - phi(n)), models the autocatalyzed progression of aneuploidy in vivo and in vitro. The variable phi(n)(+1) is the average aneuploid fraction of a population of cells at the n+1 cell division and is determined by the value at the nth cell division. The value r is the growth control parameter. The logistic equation was used to compute the probability distribution for values of phi after numerous divisions of aneuploid cells. The autocatalyzed progression of aneuploidy follows the laws of deterministic chaos, which means that certain values of phi are more probable than others. The probability map of the logistic equation shows that: 1) an aneuploid fraction of at least 0.30 is necessary to sustain a population of cancer cells; and 2) the most likely aneuploid fraction after many population doublings is 0.70, which is equivalent to a DNA(index)=1.7, the point of maximum disorder of the genome that still sustains life. Aneuploidy theory also explains the lack of immune surveillance and the failure of chemotherapy.

Public health consequences of macrolide use in food animals: a deterministic risk assessment.

PubMed

Hurd, H Scott; Doores, Stephanie; Hayes, Dermot; Mathew, Alan; Maurer, John; Silley, Peter; Singer, Randall S; Jones, Ronald N

2004-05-01

The potential impact on human health from antibiotic-resistant bacteria selected by use of antibiotics in food animals has resulted in many reports and recommended actions. The U.S. Food and Drug Administration Center for Veterinary Medicine has issued Guidance Document 152, which advises veterinary drug sponsors of one potential process for conducting a qualitative risk assessment of drug use in food animals. Using this guideline, we developed a deterministic model to assess the risk from two macrolide antibiotics, tylosin and tilmicosin. The scope of modeling included all label claim uses of both macrolides in poultry, swine, and beef cattle. The Guidance Document was followed to define the hazard, which is illness (i) caused by foodborne bacteria with a resistance determinant, (ii) attributed to a specified animal-derived meat commodity, and (iii) treated with a human use drug of the same class. Risk was defined as the probability of this hazard combined with the consequence of treatment failure due to resistant Campylobacter spp. or Enterococcus faecium. A binomial event model was applied to estimate the annual risk for the U.S. general population. Parameters were derived from industry drug use surveys, scientific literature, medical guidelines, and government documents. This unique farm-to-patient risk assessment demonstrated that use of tylosin and tilmicosin in food animals presents a very low risk of human treatment failure, with an approximate annual probability of less than 1 in 10 million Campylobacter-derived and approximately 1 in 3 billion E. faecium-derived risk.

Differentiated protection services with failure probability guarantee for workflow-based applications

NASA Astrophysics Data System (ADS)

Zhong, Yaoquan; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng

2010-12-01

A cost-effective and service-differentiated provisioning strategy is very desirable to service providers so that they can offer users satisfactory services, while optimizing network resource allocation. Providing differentiated protection services to connections for surviving link failure has been extensively studied in recent years. However, the differentiated protection services for workflow-based applications, which consist of many interdependent tasks, have scarcely been studied. This paper investigates the problem of providing differentiated services for workflow-based applications in optical grid. In this paper, we develop three differentiated protection services provisioning strategies which can provide security level guarantee and network-resource optimization for workflow-based applications. The simulation demonstrates that these heuristic algorithms provide protection cost-effectively while satisfying the applications' failure probability requirements.

N-mix for fish: estimating riverine salmonid habitat selection via N-mixture models

USGS Publications Warehouse

Som, Nicholas A.; Perry, Russell W.; Jones, Edward C.; De Juilio, Kyle; Petros, Paul; Pinnix, William D.; Rupert, Derek L.

2018-01-01

Models that formulate mathematical linkages between fish use and habitat characteristics are applied for many purposes. For riverine fish, these linkages are often cast as resource selection functions with variables including depth and velocity of water and distance to nearest cover. Ecologists are now recognizing the role that detection plays in observing organisms, and failure to account for imperfect detection can lead to spurious inference. Herein, we present a flexible N-mixture model to associate habitat characteristics with the abundance of riverine salmonids that simultaneously estimates detection probability. Our formulation has the added benefits of accounting for demographics variation and can generate probabilistic statements regarding intensity of habitat use. In addition to the conceptual benefits, model application to data from the Trinity River, California, yields interesting results. Detection was estimated to vary among surveyors, but there was little spatial or temporal variation. Additionally, a weaker effect of water depth on resource selection is estimated than that reported by previous studies not accounting for detection probability. N-mixture models show great promise for applications to riverine resource selection.

Estimating the empirical probability of submarine landslide occurrence

USGS Publications Warehouse

Geist, Eric L.; Parsons, Thomas E.; Mosher, David C.; Shipp, Craig; Moscardelli, Lorena; Chaytor, Jason D.; Baxter, Christopher D. P.; Lee, Homa J.; Urgeles, Roger

2010-01-01

The empirical probability for the occurrence of submarine landslides at a given location can be estimated from age dates of past landslides. In this study, tools developed to estimate earthquake probability from paleoseismic horizons are adapted to estimate submarine landslide probability. In both types of estimates, one has to account for the uncertainty associated with age-dating individual events as well as the open time intervals before and after the observed sequence of landslides. For observed sequences of submarine landslides, we typically only have the age date of the youngest event and possibly of a seismic horizon that lies below the oldest event in a landslide sequence. We use an empirical Bayes analysis based on the Poisson-Gamma conjugate prior model specifically applied to the landslide probability problem. This model assumes that landslide events as imaged in geophysical data are independent and occur in time according to a Poisson distribution characterized by a rate parameter λ. With this method, we are able to estimate the most likely value of λ and, importantly, the range of uncertainty in this estimate. Examples considered include landslide sequences observed in the Santa Barbara Channel, California, and in Port Valdez, Alaska. We confirm that given the uncertainties of age dating that landslide complexes can be treated as single events by performing statistical test of age dates representing the main failure episode of the Holocene Storegga landslide complex.

Is pre-transplant sensitization against angiotensin II type 1 receptor still a risk factor of graft and patient outcome in kidney transplantation in the anti-HLA Luminex era? A retrospective study.

PubMed

Deltombe, Clement; Gillaizeau, Florence; Anglicheau, Daniel; Morelon, Emmanuel; Trébern-Launay, Katy; Le Borgne, Florent; Rimbert, Marie; Guérif, Pierrick; Malard-Castagnet, Stéphanie; Foucher, Yohann; Giral, Magali

2017-11-01

We aimed to assess the correlation of anti-angiotensin II type 1 receptor antibodies (anti-AT1R-Abs) before transplantation on a multicentric cohort of kidney transplant recipients (2008-2012), under tacrolimus and mycophenolate mofetil (MMF), screened by Luminex technology for anti-HLA immunization. Anti-AT1R antibody levels were measured by ELISA in pretransplantation sera of 940 kidney recipients from three French centers of the DIVAT cohort. Multivariable Cox models estimated the association between pretransplant anti-angiotensin II type 1 receptor antibodies and time to acute rejection episodes (ARE) or time to graft failure. Within our cohort, 387 patients (41.2%) had pretransplant AT1R-Abs higher than 10 U/ml and only 8% (72/970) greater than 17 U/ml. The cumulative probability of clinically relevant (cr)-ARE was 22.5% at 1 year post-transplantation [95% CI (19.9-25.4%)]. The cumulative probability of graft failure and patient death were 10.6% [95% CI (8.4-13.3%)] and 5.7% [95% CI (4.0-8.1%)] at 3 years post-transplantation, respectively. Multivariate Cox models indicated that pretransplant anti-AT1R antibody levels higher than 10 U/ml were not significantly independently associated with higher risks of acute rejection episodes [HR = 1.04, 95% CI (0.80-1.35)] nor with risk of graft failure [HR = 0.86, 95% CI (0.56-1.33)]. Our study did not confirm an association between pretransplant anti-AT1R antibody levels and kidney transplant outcomes. © 2017 Steunstichting ESOT.

Reliability analysis of a wastewater treatment plant using fault tree analysis and Monte Carlo simulation.

PubMed

Taheriyoun, Masoud; Moradinejad, Saber

2015-01-01

The reliability of a wastewater treatment plant is a critical issue when the effluent is reused or discharged to water resources. Main factors affecting the performance of the wastewater treatment plant are the variation of the influent, inherent variability in the treatment processes, deficiencies in design, mechanical equipment, and operational failures. Thus, meeting the established reuse/discharge criteria requires assessment of plant reliability. Among many techniques developed in system reliability analysis, fault tree analysis (FTA) is one of the popular and efficient methods. FTA is a top down, deductive failure analysis in which an undesired state of a system is analyzed. In this study, the problem of reliability was studied on Tehran West Town wastewater treatment plant. This plant is a conventional activated sludge process, and the effluent is reused in landscape irrigation. The fault tree diagram was established with the violation of allowable effluent BOD as the top event in the diagram, and the deficiencies of the system were identified based on the developed model. Some basic events are operator's mistake, physical damage, and design problems. The analytical method is minimal cut sets (based on numerical probability) and Monte Carlo simulation. Basic event probabilities were calculated according to available data and experts' opinions. The results showed that human factors, especially human error had a great effect on top event occurrence. The mechanical, climate, and sewer system factors were in subsequent tier. Literature shows applying FTA has been seldom used in the past wastewater treatment plant (WWTP) risk analysis studies. Thus, the developed FTA model in this study considerably improves the insight into causal failure analysis of a WWTP. It provides an efficient tool for WWTP operators and decision makers to achieve the standard limits in wastewater reuse and discharge to the environment.

Antibiotic-induced population fluctuations and stochastic clearance of bacteria

PubMed Central

Le, Dai; Şimşek, Emrah; Chaudhry, Waqas

2018-01-01

Effective antibiotic use that minimizes treatment failures remains a challenge. A better understanding of how bacterial populations respond to antibiotics is necessary. Previous studies of large bacterial populations established the deterministic framework of pharmacodynamics. Here, characterizing the dynamics of population extinction, we demonstrated the stochastic nature of eradicating bacteria with antibiotics. Antibiotics known to kill bacteria (bactericidal) induced population fluctuations. Thus, at high antibiotic concentrations, the dynamics of bacterial clearance were heterogeneous. At low concentrations, clearance still occurred with a non-zero probability. These striking outcomes of population fluctuations were well captured by our probabilistic model. Our model further suggested a strategy to facilitate eradication by increasing extinction probability. We experimentally tested this prediction for antibiotic-susceptible and clinically-isolated resistant bacteria. This new knowledge exposes fundamental limits in our ability to predict bacterial eradication. Additionally, it demonstrates the potential of using antibiotic concentrations that were previously deemed inefficacious to eradicate bacteria. PMID:29508699

A Computational Framework to Control Verification and Robustness Analysis

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2010-01-01

This paper presents a methodology for evaluating the robustness of a controller based on its ability to satisfy the design requirements. The framework proposed is generic since it allows for high-fidelity models, arbitrary control structures and arbitrary functional dependencies between the requirements and the uncertain parameters. The cornerstone of this contribution is the ability to bound the region of the uncertain parameter space where the degradation in closed-loop performance remains acceptable. The size of this bounding set, whose geometry can be prescribed according to deterministic or probabilistic uncertainty models, is a measure of robustness. The robustness metrics proposed herein are the parametric safety margin, the reliability index, the failure probability and upper bounds to this probability. The performance observed at the control verification setting, where the assumptions and approximations used for control design may no longer hold, will fully determine the proposed control assessment.

The Application of Failure Modes and Effects Analysis Methodology to Intrathecal Drug Delivery for Pain Management

PubMed Central

Patel, Teresa; Fisher, Stanley P.

2016-01-01

Objective This study aimed to utilize failure modes and effects analysis (FMEA) to transform clinical insights into a risk mitigation plan for intrathecal (IT) drug delivery in pain management. Methods The FMEA methodology, which has been used for quality improvement, was adapted to assess risks (i.e., failure modes) associated with IT therapy. Ten experienced pain physicians scored 37 failure modes in the following categories: patient selection for therapy initiation (efficacy and safety concerns), patient safety during IT therapy, and product selection for IT therapy. Participants assigned severity, probability, and detection scores for each failure mode, from which a risk priority number (RPN) was calculated. Failure modes with the highest RPNs (i.e., most problematic) were discussed, and strategies were proposed to mitigate risks. Results Strategic discussions focused on 17 failure modes with the most severe outcomes, the highest probabilities of occurrence, and the most challenging detection. The topic of the highest‐ranked failure mode (RPN = 144) was manufactured monotherapy versus compounded combination products. Addressing failure modes associated with appropriate patient and product selection was predicted to be clinically important for the success of IT therapy. Conclusions The methodology of FMEA offers a systematic approach to prioritizing risks in a complex environment such as IT therapy. Unmet needs and information gaps are highlighted through the process. Risk mitigation and strategic planning to prevent and manage critical failure modes can contribute to therapeutic success. PMID:27477689

Failure modes and effects criticality analysis and accelerated life testing of LEDs for medical applications

NASA Astrophysics Data System (ADS)

Sawant, M.; Christou, A.

2012-12-01

While use of LEDs in Fiber Optics and lighting applications is common, their use in medical diagnostic applications is not very extensive. Since the precise value of light intensity will be used to interpret patient results, understanding failure modes [1-4] is very important. We used the Failure Modes and Effects Criticality Analysis (FMECA) tool to identify the critical failure modes of the LEDs. FMECA involves identification of various failure modes, their effects on the system (LED optical output in this context), their frequency of occurrence, severity and the criticality of the failure modes. The competing failure modes/mechanisms were degradation of: active layer (where electron-hole recombination occurs to emit light), electrodes (provides electrical contact to the semiconductor chip), Indium Tin Oxide (ITO) surface layer (used to improve current spreading and light extraction), plastic encapsulation (protective polymer layer) and packaging failures (bond wires, heat sink separation). A FMECA table is constructed and the criticality is calculated by estimating the failure effect probability (β), failure mode ratio (α), failure rate (λ) and the operating time. Once the critical failure modes were identified, the next steps were generation of prior time to failure distribution and comparing with our accelerated life test data. To generate the prior distributions, data and results from previous investigations were utilized [5-33] where reliability test results of similar LEDs were reported. From the graphs or tabular data, we extracted the time required for the optical power output to reach 80% of its initial value. This is our failure criterion for the medical diagnostic application. Analysis of published data for different LED materials (AlGaInP, GaN, AlGaAs), the Semiconductor Structures (DH, MQW) and the mode of testing (DC, Pulsed) was carried out. The data was categorized according to the materials system and LED structure such as AlGaInP-DH-DC, AlGaInP-MQW-DC, GaN-DH-DC, and GaN-DH-DC. Although the reported testing was carried out at different temperature and current, the reported data was converted to the present application conditions of the medical environment. Comparisons between the model data and accelerated test results carried out in the present are reported. The use of accelerating agent modeling and regression analysis was also carried out. We have used the Inverse Power Law model with the current density J as the accelerating agent and the Arrhenius model with temperature as the accelerating agent. Finally, our reported methodology is presented as an approach for analyzing LED suitability for the target medical diagnostic applications.

Influence of Climate Change on Flood Hazard using Climate Informed Bayesian Hierarchical Model in Johnson Creek River

NASA Astrophysics Data System (ADS)

Zarekarizi, M.; Moradkhani, H.

2015-12-01

Extreme events are proven to be affected by climate change, influencing hydrologic simulations for which stationarity is usually a main assumption. Studies have discussed that this assumption would lead to large bias in model estimations and higher flood hazard consequently. Getting inspired by the importance of non-stationarity, we determined how the exceedance probabilities have changed over time in Johnson Creek River, Oregon. This could help estimate the probability of failure of a structure that was primarily designed to resist less likely floods according to common practice. Therefore, we built a climate informed Bayesian hierarchical model and non-stationarity was considered in modeling framework. Principle component analysis shows that North Atlantic Oscillation (NAO), Western Pacific Index (WPI) and Eastern Asia (EA) are mostly affecting stream flow in this river. We modeled flood extremes using peaks over threshold (POT) method rather than conventional annual maximum flood (AMF) mainly because it is possible to base the model on more information. We used available threshold selection methods to select a suitable threshold for the study area. Accounting for non-stationarity, model parameters vary through time with climate indices. We developed a couple of model scenarios and chose one which could best explain the variation in data based on performance measures. We also estimated return periods under non-stationarity condition. Results show that ignoring stationarity could increase the flood hazard up to four times which could increase the probability of an in-stream structure being overtopped.

On the Viability of Conspiratorial Beliefs

PubMed Central

Grimes, David Robert

2016-01-01

Conspiratorial ideation is the tendency of individuals to believe that events and power relations are secretly manipulated by certain clandestine groups and organisations. Many of these ostensibly explanatory conjectures are non-falsifiable, lacking in evidence or demonstrably false, yet public acceptance remains high. Efforts to convince the general public of the validity of medical and scientific findings can be hampered by such narratives, which can create the impression of doubt or disagreement in areas where the science is well established. Conversely, historical examples of exposed conspiracies do exist and it may be difficult for people to differentiate between reasonable and dubious assertions. In this work, we establish a simple mathematical model for conspiracies involving multiple actors with time, which yields failure probability for any given conspiracy. Parameters for the model are estimated from literature examples of known scandals, and the factors influencing conspiracy success and failure are explored. The model is also used to estimate the likelihood of claims from some commonly-held conspiratorial beliefs; these are namely that the moon-landings were faked, climate-change is a hoax, vaccination is dangerous and that a cure for cancer is being suppressed by vested interests. Simulations of these claims predict that intrinsic failure would be imminent even with the most generous estimates for the secret-keeping ability of active participants—the results of this model suggest that large conspiracies (≥1000 agents) quickly become untenable and prone to failure. The theory presented here might be useful in counteracting the potentially deleterious consequences of bogus and anti-science narratives, and examining the hypothetical conditions under which sustainable conspiracy might be possible. PMID:26812482

Mechanical aspects of degree of cement bonding and implant wedge effect.

PubMed

Yoon, Yong-San; Oxland, Thomas R; Hodgson, Antony J; Duncan, Clive P; Masri, Bassam A; Choi, Donok

2008-11-01

The degree of bonding between the femoral stem and cement in total hip replacement remains controversial. Our objective was to determine the wedge effect by debonding and stem taper angle on the structural behavior of axisymmetric stem-cement-bone cylinder models. Stainless steel tapered plugs with a rough (i.e. bonded) or smooth (i.e. debonded) surface finish were used to emulate the femoral stem. Three different stem taper angles (5 degrees , 7.5 degrees , 10 degrees ) were used for the debonded constructs. Non-tapered and tapered (7.5 degrees ) aluminum cylindrical shells were used to emulate the diaphyseal and metaphyseal segments of the femur. The cement-aluminum cylinder interface was designed to have a shear strength that simulated bone-cement interfaces ( approximately 8MPa). The test involved applying axial compression at a rate of 0.02mm/s until failure. Six specimens were tested for each combination of the variables. Finite element analysis was used to enhance the understanding of the wedge effect. The debonded stems sustained about twice as much load as the bonded stem, regardless of taper angle. The metaphyseal model carried 35-50% greater loads than the diaphyseal models and the stem taper produced significant differences. Based on the finite element analysis, failure was most probably by shear at the cement-bone interface. Our results in this simplified model suggest that smooth (i.e. debonded) stems have greater failure loads and will incur less slippage or shear failure at the cement-bone interface than rough (i.e. bonded) stems.

Long-term cost-effectiveness of disease management in systolic heart failure.

PubMed

Miller, George; Randolph, Stephen; Forkner, Emma; Smith, Brad; Galbreath, Autumn Dawn

2009-01-01

Although congestive heart failure (CHF) is a primary target for disease management programs, previous studies have generated mixed results regarding the effectiveness and cost savings of disease management when applied to CHF. We estimated the long-term impact of systolic heart failure disease management from the results of an 18-month clinical trial. We used data generated from the trial (starting population distributions, resource utilization, mortality rates, and transition probabilities) in a Markov model to project results of continuing the disease management program for the patients' lifetimes. Outputs included distribution of illness severity, mortality, resource consumption, and the cost of resources consumed. Both cost and effectiveness were discounted at a rate of 3% per year. Cost-effectiveness was computed as cost per quality-adjusted life year (QALY) gained. Model results were validated against trial data and indicated that, over their lifetimes, patients experienced a lifespan extension of 51 days. Combined discounted lifetime program and medical costs were $4850 higher in the disease management group than the control group, but the program had a favorable long-term discounted cost-effectiveness of $43,650/QALY. These results are robust to assumptions regarding mortality rates, the impact of aging on the cost of care, the discount rate, utility values, and the targeted population. Estimation of the clinical benefits and financial burden of disease management can be enhanced by model-based analyses to project costs and effectiveness. Our results suggest that disease management of heart failure patients can be cost-effective over the long term.

Spatial and temporal variability in rates of landsliding in seismically active mountain ranges

NASA Astrophysics Data System (ADS)

Parker, R.; Petley, D.; Rosser, N.; Densmore, A.; Gunasekera, R.; Brain, M.

2012-04-01

Where earthquake and precipitation driven disasters occur in steep, mountainous regions, landslides often account for a large proportion of the associated damage and losses. This research addresses spatial and temporal variability in rates of landslide occurrence in seismically active mountain ranges as a step towards developing better regional scale prediction of losses in such events. In the first part of this paper we attempt to explain reductively the variability in spatial rates of landslide occurrence, using data from five major earthquakes. This is achieved by fitting a regression-based conditional probability model to spatial probabilities of landslide occurrence, using as predictor variables proxies for spatial patterns of seismic ground motion and modelled hillslope stability. A combined model for all earthquakes performs well in hindcasting spatial probabilities of landslide occurrence as a function of readily-attainable spatial variables. We present validation of the model and demonstrate the extent to which it may be applied globally to derive landslide probabilities for future earthquakes. In part two we examine the temporal behaviour of rates of landslide occurrence. This is achieved through numerical modelling to simulate the behaviour of a hypothetical landscape. The model landscape is composed of hillslopes that continually weaken, fail and reset in response to temporally-discrete forcing events that represent earthquakes. Hillslopes with different geometries require different amounts of weakening to fail, such that they fail and reset at different temporal rates. Our results suggest that probabilities of landslide occurrence are not temporally constant, but rather vary with time, irrespective of changes in forcing event magnitudes or environmental conditions. Various parameters influencing the magnitude and temporal patterns of this variability are identified, highlighting areas where future research is needed. This model has important implications for landslide hazard and risk analysis in mountain areas as existing techniques usually assume that susceptibility to failure does not change with time.

Partially silencing brain toll-like receptor 4 prevents in part left ventricular remodeling with sympathoinhibition in rats with myocardial infarction-induced heart failure.

PubMed

Ogawa, Kiyohiro; Hirooka, Yoshitaka; Kishi, Takuya; Ide, Tomomi; Sunagawa, Kenji

2013-01-01

Left ventricular (LV) remodeling and activation of sympathetic nervous system (SNS) are cardinal features of heart failure. We previously demonstrated that enhanced central sympathetic outflow is associated with brain toll-like receptor 4 (TLR4) probably mediated by brain angiotensin II type 1 receptor in mice with myocardial infarction (MI)-induced heart failure. The purpose of the present study was to examine whether silencing brain TLR4 could prevent LV remodeling with sympathoinhibition in MI-induced heart failure. MI-induced heart failure model rats were created by ligation of left coronary artery. The expression level of TLR4 in brainstem was significantly higher in MI-induced heart failure treated with intracerebroventricular (ICV) injection of hGAPDH-SiRNA than in sham. TLR4 in brainstem was significantly lower in MI-induced heart failure treated with ICV injection of TLR4-SiRNA than in that treated with ICV injection of hGAPDH-SiRNA. Lung weight, urinary norepinephrine excretion, and LV end-diastolic pressure were significantly lower and LV dimension was significantly smaller in MI-induced heart failure treated with TLR4-SiRNA than in that treated with hGAPDH-SiRNA for 2 weeks. Partially silencing brain TLR4 by ICV injection of TLR4-SiRNA for 2 weeks could in part prevent LV remodeling with sympathoinhibition in rats with MI-induced heart failure. Brain TLR4 has a potential to be a target of the treatment for MI-induced heart failure.

A Numerical Round Robin for the Reliability Prediction of Structural Ceramics

NASA Technical Reports Server (NTRS)

Powers, Lynn M.; Janosik, Lesley A.

1993-01-01

A round robin has been conducted on integrated fast fracture design programs for brittle materials. An informal working group (WELFEP-WEakest Link failure probability prediction by Finite Element Postprocessors) was formed to discuss and evaluate the implementation of the programs examined in the study. Results from the study have provided insight on the differences between the various programs examined. Conclusions from the study have shown that when brittle materials are used in design, analysis must understand how to apply the concepts presented herein to failure probability analysis.

Cost-Effectiveness Analysis of Plasma Versus Recombinant Factor VIIa for Placing Intracranial Pressure Monitors in Pretransplant Patients With Acute Liver Failure.

PubMed

Pham, Huy P; Sireci, Anthony N; Kim, Chong H; Schwartz, Joseph

2014-09-01

Both plasma- and recombinant activated factor VII (rFVIIa)-based algorithms can be used to correct coagulopathy in preliver transplant patients with acute liver failure requiring intracranial pressure monitor (ICPM) placement. A decision model was created to compare the cost-effectiveness of these methods. A 70-kg patient could receive either 1 round of plasma followed by coagulation testing or 2 units of plasma and 40 μg/kg rFVIIa. Intracranial pressure monitor is placed without coagulation testing after rFVIIa administration. In the plasma algorithm, the probability of ICPM placement was estimated based on expected international normalized ratio (INR) after plasma administration. Risks of rFVIIa thrombosis and transfusion reactions were also included. The model was run for patients with INRs ranging from 2 to 6 with concomitant adjustments to model parameters. The model supported the initial use of rFVIIa for ICPM placement as a cost-effective treatment when INR ≥2 (with incremental cost-effectiveness ratio of at most US$7088.02). © The Author(s) 2014.

Non-linear Equation using Plasma Brain Natriuretic Peptide Levels to Predict Cardiovascular Outcomes in Patients with Heart Failure

NASA Astrophysics Data System (ADS)

Fukuda, Hiroki; Suwa, Hideaki; Nakano, Atsushi; Sakamoto, Mari; Imazu, Miki; Hasegawa, Takuya; Takahama, Hiroyuki; Amaki, Makoto; Kanzaki, Hideaki; Anzai, Toshihisa; Mochizuki, Naoki; Ishii, Akira; Asanuma, Hiroshi; Asakura, Masanori; Washio, Takashi; Kitakaze, Masafumi

2016-11-01

Brain natriuretic peptide (BNP) is the most effective predictor of outcomes in chronic heart failure (CHF). This study sought to determine the qualitative relationship between the BNP levels at discharge and on the day of cardiovascular events in CHF patients. We devised a mathematical probabilistic model between the BNP levels at discharge (y) and on the day (t) of cardiovascular events after discharge for 113 CHF patients (Protocol I). We then prospectively evaluated this model on another set of 60 CHF patients who were readmitted (Protocol II). P(t|y) was the probability of cardiovascular events occurring after >t, the probability on t was given as p(t|y) = -dP(t|y)/dt, and p(t|y) = pP(t|y) = αyβP(t|y), along with p = αyβ (α and β were constant); the solution was p(t|y) = αyβ exp(-αyβt). We fitted this equation to the data set of Protocol I using the maximum likelihood principle, and we obtained the model p(t|y) = 0.000485y0.24788 exp(-0.000485y0.24788t). The cardiovascular event-free rate was computed as P(t) = 1/60Σi=1,…,60 exp(-0.000485yi0.24788t), based on this model and the BNP levels yi in a data set of Protocol II. We confirmed no difference between this model-based result and the actual event-free rate. In conclusion, the BNP levels showed a non-linear relationship with the day of occurrence of cardiovascular events in CHF patients.

Centralized Cryptographic Key Management and Critical Risk Assessment - CRADA Final Report For CRADA Number NFE-11-03562

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

Abercrombie, R. K.; Peters, Scott

The Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) Cyber Security for Energy Delivery Systems (CSEDS) industry led program (DE-FOA-0000359) entitled "Innovation for Increasing Cyber Security for Energy Delivery Systems (12CSEDS)," awarded a contract to Sypris Electronics LLC to develop a Cryptographic Key Management System for the smart grid (Scalable Key Management Solutions for Critical Infrastructure Protection). Oak Ridge National Laboratory (ORNL) and Sypris Electronics, LLC as a result of that award entered into a CRADA (NFE-11-03562) between ORNL and Sypris Electronics, LLC. ORNL provided its Cyber Security Econometrics System (CSES) as a tool to be modifiedmore » and used as a metric to address risks and vulnerabilities in the management of cryptographic keys within the Advanced Metering Infrastructure (AMI) domain of the electric sector. ORNL concentrated our analysis on the AMI domain of which the National Electric Sector Cyber security Organization Resource (NESCOR) Working Group 1 (WG1) has documented 29 failure scenarios. The computational infrastructure of this metric involves system stakeholders, security requirements, system components and security threats. To compute this metric, we estimated the stakes that each stakeholder associates with each security requirement, as well as stochastic matrices that represent the probability of a threat to cause a component failure and the probability of a component failure to cause a security requirement violation. We applied this model to estimate the security of the AMI, by leveraging the recently established National Institute of Standards and Technology Interagency Report (NISTIR) 7628 guidelines for smart grid security and the International Electrotechnical Commission (IEC) 63351, Part 9 to identify the life cycle for cryptographic key management, resulting in a vector that assigned to each stakeholder an estimate of their average loss in terms of dollars per day of system operation. To further address probabilities of threats, information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. The strategy for the game was developed by analyzing five electric sector representative failure scenarios contained in the AMI functional domain from NESCOR WG1. From these five selected scenarios, we characterized them into three specific threat categories affecting confidentiality, integrity and availability (CIA). The analysis using our ABGT simulation demonstrated how to model the AMI functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the AMI network with respect to CIA.« less

Cryptographic Key Management and Critical Risk Assessment

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

Abercrombie, Robert K

The Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) CyberSecurity for Energy Delivery Systems (CSEDS) industry led program (DE-FOA-0000359) entitled "Innovation for Increasing CyberSecurity for Energy Delivery Systems (12CSEDS)," awarded a contract to Sypris Electronics LLC to develop a Cryptographic Key Management System for the smart grid (Scalable Key Management Solutions for Critical Infrastructure Protection). Oak Ridge National Laboratory (ORNL) and Sypris Electronics, LLC as a result of that award entered into a CRADA (NFE-11-03562) between ORNL and Sypris Electronics, LLC. ORNL provided its Cyber Security Econometrics System (CSES) as a tool to be modified and usedmore » as a metric to address risks and vulnerabilities in the management of cryptographic keys within the Advanced Metering Infrastructure (AMI) domain of the electric sector. ORNL concentrated our analysis on the AMI domain of which the National Electric Sector Cyber security Organization Resource (NESCOR) Working Group 1 (WG1) has documented 29 failure scenarios. The computational infrastructure of this metric involves system stakeholders, security requirements, system components and security threats. To compute this metric, we estimated the stakes that each stakeholder associates with each security requirement, as well as stochastic matrices that represent the probability of a threat to cause a component failure and the probability of a component failure to cause a security requirement violation. We applied this model to estimate the security of the AMI, by leveraging the recently established National Institute of Standards and Technology Interagency Report (NISTIR) 7628 guidelines for smart grid security and the International Electrotechnical Commission (IEC) 63351, Part 9 to identify the life cycle for cryptographic key management, resulting in a vector that assigned to each stakeholder an estimate of their average loss in terms of dollars per day of system operation. To further address probabilities of threats, information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. The strategy for the game was developed by analyzing five electric sector representative failure scenarios contained in the AMI functional domain from NESCOR WG1. From these five selected scenarios, we characterized them into three specific threat categories affecting confidentiality, integrity and availability (CIA). The analysis using our ABGT simulation demonstrated how to model the AMI functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the AMI network with respect to CIA.« less

Application of the strain invariant failure theory (SIFT) to metals and fiber-polymer composites

NASA Astrophysics Data System (ADS)

Hart-Smith, L. J.

2010-11-01

The strain invariant failure theory (SIFT) model, developed to predict the onset of irreversible damage of fiber-polymer composite laminates, may be also applied to metals. Indeed, it can be applied to all solid materials. Two initial failure mechanisms are considered - distortion and dilatation. The author's experiences are confined to the structures of transport aircraft; phase changes in metals and self-destruction of laminates during curing are not covered. Doing so would need additional material properties, and probably a different failure theory. SIFT does not cover environmental attack on the interface between fibers and resin; it covers only cohesive failures within the fibers or resin, or within a homogeneous piece of metal. In the SIFT model, each damage mechanism is characterized by its own critical value of a strain invariant. Each mechanism dominates its own portion of the strain domain; there is no interaction between them. Application of SIFT to metals is explained first. Fiber-polymer composites contain two discrete constituents; each material must be characterized independently by its own two invariants. This is why fiber-polymer composites need four invariants whereas metals require only two. There is no such thing as a composite material, only composites of materials. The "composite materials" must not be modeled as homogeneous anisotropic solids because it is then not even possible to differentiate between fiber and matrix failures. The SIFT model uses measured material properties; it does not require that half of them be arbitrarily replaced by unmeasurable properties to fit laminate test data, as so many earlier composite failure criteria have. The biggest difference in using SIFT for metals and fiber-reinforced materials is internal residual thermal and moisture absorption stresses created by the gross dissimilarity in properties between embedded fibers and thermoset resin matrices. These residual stresses consume so much of the strength of unreinforced polymers for typical thermoset resins cured at high temperature, like epoxies, that little strength is available to resist mechanical loads. (Thermoplastic polymers suffer far less in this regard.) The paper explains how SIFT is used via worked examples, which demonstrate the kind of detailed information that SIFT analyses can generate.

Pharmacokinetic-Pharmacodynamic Modeling of Unboosted Atazanavir in a Cohort of Stable HIV-Infected Patients

PubMed Central

Baudry, Thomas; Gagnieu, Marie-Claude; Boibieux, André; Livrozet, Jean-Michel; Peyramond, Dominique; Tod, Michel; Ferry, Tristan

2013-01-01

Limited data on the pharmacokinetics and pharmacodynamics (PK/PD) of unboosted atazanavir (uATV) in treatment-experienced patients are available. The aim of this work was to study the PK/PD of unboosted atazanavir in a cohort of HIV-infected patients. Data were available for 58 HIV-infected patients (69 uATV-based regimens). Atazanavir concentrations were analyzed by using a population approach, and the relationship between atazanavir PK and clinical outcome was examined using logistic regression. The final PK model was a linear one-compartment model with a mixture absorption model to account for two subgroups of absorbers. The mean (interindividual variability) of population PK parameters were as follows: clearance, 13.4 liters/h (40.7%), volume of distribution, 71.1 liters (29.7%), and fraction of regular absorbers, 0.49. Seven subjects experienced virological failure after switch to uATV. All of them were identified as low absorbers in the PK modeling. The absorption rate constant (0.38 ± 0.20 versus 0.75 ± 0.28 h−1; P = 0.002) and ATV exposure (area under the concentration-time curve from 0 to 24 h [AUC0–24], 10.3 ± 2.1 versus 22.4 ± 11.2 mg · h · liter−1; P = 0.001) were significantly lower in patients with virological failure than in patients without failure. In the logistic regression analysis, both the absorption rate constant and ATV trough concentration significantly influenced the probability of virological failure. A significant relationship between ATV pharmacokinetics and virological response was observed in a cohort of HIV patients who were administered unboosted atazanavir. This study also suggests that twice-daily administration of uATV may optimize drug therapy. PMID:23147727

A Probability Problem from Real Life: The Tire Exploded.

ERIC Educational Resources Information Center

Bartlett, Albert A.

1993-01-01

Discusses the probability of seeing a tire explode or disintegrate while traveling down the highway. Suggests that a person observing 10 hours a day would see a failure on the average of once every 300 years. (MVL)

Hardware and software reliability estimation using simulations

NASA Technical Reports Server (NTRS)

Swern, Frederic L.

1994-01-01

The simulation technique is used to explore the validation of both hardware and software. It was concluded that simulation is a viable means for validating both hardware and software and associating a reliability number with each. This is useful in determining the overall probability of system failure of an embedded processor unit, and improving both the code and the hardware where necessary to meet reliability requirements. The methodologies were proved using some simple programs, and simple hardware models.

Scheduling structural health monitoring activities for optimizing life-cycle costs and reliability of wind turbines

NASA Astrophysics Data System (ADS)

Hanish Nithin, Anu; Omenzetter, Piotr

2017-04-01

Optimization of the life-cycle costs and reliability of offshore wind turbines (OWTs) is an area of immense interest due to the widespread increase in wind power generation across the world. Most of the existing studies have used structural reliability and the Bayesian pre-posterior analysis for optimization. This paper proposes an extension to the previous approaches in a framework for probabilistic optimization of the total life-cycle costs and reliability of OWTs by combining the elements of structural reliability/risk analysis (SRA), the Bayesian pre-posterior analysis with optimization through a genetic algorithm (GA). The SRA techniques are adopted to compute the probabilities of damage occurrence and failure associated with the deterioration model. The probabilities are used in the decision tree and are updated using the Bayesian analysis. The output of this framework would determine the optimal structural health monitoring and maintenance schedules to be implemented during the life span of OWTs while maintaining a trade-off between the life-cycle costs and risk of the structural failure. Numerical illustrations with a generic deterioration model for one monitoring exercise in the life cycle of a system are demonstrated. Two case scenarios, namely to build initially an expensive and robust or a cheaper but more quickly deteriorating structures and to adopt expensive monitoring system, are presented to aid in the decision-making process.

Application of Probability Methods to Assess Crash Modeling Uncertainty

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Stockwell, Alan E.; Hardy, Robin C.

2003-01-01

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stress-strain behaviors, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the effects of finite element modeling assumptions on the predicted responses. The vertical drop test of a Fokker F28 fuselage section will be the focus of this paper. The results of a probabilistic analysis using finite element simulations will be compared with experimental data.

Application of Probability Methods to Assess Crash Modeling Uncertainty

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Stockwell, Alan E.; Hardy, Robin C.

2007-01-01

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stress-strain behaviors, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the effects of finite element modeling assumptions on the predicted responses. The vertical drop test of a Fokker F28 fuselage section will be the focus of this paper. The results of a probabilistic analysis using finite element simulations will be compared with experimental data.

Evaluation of Enhanced Risk Monitors for Use on Advanced Reactors

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

Ramuhalli, Pradeep; Veeramany, Arun; Bonebrake, Christopher A.

This study provides an overview of the methodology for integrating time-dependent failure probabilities into nuclear power reactor risk monitors. This prototypic enhanced risk monitor (ERM) methodology was evaluated using a hypothetical probabilistic risk assessment (PRA) model, generated using a simplified design of a liquid-metal-cooled advanced reactor (AR). Component failure data from industry compilation of failures of components similar to those in the simplified AR model were used to initialize the PRA model. Core damage frequency (CDF) over time were computed and analyzed. In addition, a study on alternative risk metrics for ARs was conducted. Risk metrics that quantify the normalizedmore » cost of repairs, replacements, or other operations and management (O&M) actions were defined and used, along with an economic model, to compute the likely economic risk of future actions such as deferred maintenance based on the anticipated change in CDF due to current component condition and future anticipated degradation. Such integration of conventional-risk metrics with alternate-risk metrics provides a convenient mechanism for assessing the impact of O&M decisions on safety and economics of the plant. It is expected that, when integrated with supervisory control algorithms, such integrated-risk monitors will provide a mechanism for real-time control decision-making that ensure safety margins are maintained while operating the plant in an economically viable manner.« less

NESTEM-QRAS: A Tool for Estimating Probability of Failure

NASA Technical Reports Server (NTRS)

Patel, Bhogilal M.; Nagpal, Vinod K.; Lalli, Vincent A.; Pai, Shantaram; Rusick, Jeffrey J.

2002-01-01

An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.

NESTEM-QRAS: A Tool for Estimating Probability of Failure

NASA Astrophysics Data System (ADS)

Patel, Bhogilal M.; Nagpal, Vinod K.; Lalli, Vincent A.; Pai, Shantaram; Rusick, Jeffrey J.

2002-10-01

An interface between two NASA GRC specialty codes, NESTEM and QRAS has been developed. This interface enables users to estimate, in advance, the risk of failure of a component, a subsystem, and/or a system under given operating conditions. This capability would be able to provide a needed input for estimating the success rate for any mission. NESTEM code, under development for the last 15 years at NASA Glenn Research Center, has the capability of estimating probability of failure of components under varying loading and environmental conditions. This code performs sensitivity analysis of all the input variables and provides their influence on the response variables in the form of cumulative distribution functions. QRAS, also developed by NASA, assesses risk of failure of a system or a mission based on the quantitative information provided by NESTEM or other similar codes, and user provided fault tree and modes of failure. This paper will describe briefly, the capabilities of the NESTEM, QRAS and the interface. Also, in this presentation we will describe stepwise process the interface uses using an example.

A decision model for planetary missions

NASA Technical Reports Server (NTRS)

Hazelrigg, G. A., Jr.; Brigadier, W. L.

1976-01-01

Many techniques developed for the solution of problems in economics and operations research are directly applicable to problems involving engineering trade-offs. This paper investigates the use of utility theory for decision making in planetary exploration space missions. A decision model is derived that accounts for the objectives of the mission - science - the cost of flying the mission and the risk of mission failure. A simulation methodology for obtaining the probability distribution of science value and costs as a function spacecraft and mission design is presented and an example application of the decision methodology is given for various potential alternatives in a comet Encke mission.

Reliability and Maintainability Analysis of a High Air Pressure Compressor Facility

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.; Ring, Robert W.; Cole, Stuart K.

2013-01-01

This paper discusses a Reliability, Availability, and Maintainability (RAM) independent assessment conducted to support the refurbishment of the Compressor Station at the NASA Langley Research Center (LaRC). The paper discusses the methodologies used by the assessment team to derive the repair by replacement (RR) strategies to improve the reliability and availability of the Compressor Station (Ref.1). This includes a RAPTOR simulation model that was used to generate the statistical data analysis needed to derive a 15-year investment plan to support the refurbishment of the facility. To summarize, study results clearly indicate that the air compressors are well past their design life. The major failures of Compressors indicate that significant latent failure causes are present. Given the occurrence of these high-cost failures following compressor overhauls, future major failures should be anticipated if compressors are not replaced. Given the results from the RR analysis, the study team recommended a compressor replacement strategy. Based on the data analysis, the RR strategy will lead to sustainable operations through significant improvements in reliability, availability, and the probability of meeting the air demand with acceptable investment cost that should translate, in the long run, into major cost savings. For example, the probability of meeting air demand improved from 79.7 percent for the Base Case to 97.3 percent. Expressed in terms of a reduction in the probability of failing to meet demand (1 in 5 days to 1 in 37 days), the improvement is about 700 percent. Similarly, compressor replacement improved the operational availability of the facility from 97.5 percent to 99.8 percent. Expressed in terms of a reduction in system unavailability (1 in 40 to 1 in 500), the improvement is better than 1000 percent (an order of magnitude improvement). It is worthy to note that the methodologies, tools, and techniques used in the LaRC study can be used to evaluate similar high value equipment components and facilities. Also, lessons learned in data collection and maintenance practices derived from the observations, findings, and recommendations of the study are extremely important in the evaluation and sustainment of new compressor facilities.

Probability and Confidence Trade-space (PACT) Evaluation: Accounting for Uncertainty in Sparing Assessments

NASA Technical Reports Server (NTRS)

Anderson, Leif; Box, Neil; Carter, Katrina; DiFilippo, Denise; Harrington, Sean; Jackson, David; Lutomski, Michael

2012-01-01

There are two general shortcomings to the current annual sparing assessment: 1. The vehicle functions are currently assessed according to confidence targets, which can be misleading- overly conservative or optimistic. 2. The current confidence levels are arbitrarily determined and do not account for epistemic uncertainty (lack of knowledge) in the ORU failure rate. There are two major categories of uncertainty that impact Sparing Assessment: (a) Aleatory Uncertainty: Natural variability in distribution of actual failures around an Mean Time Between Failure (MTBF) (b) Epistemic Uncertainty : Lack of knowledge about the true value of an Orbital Replacement Unit's (ORU) MTBF We propose an approach to revise confidence targets and account for both categories of uncertainty, an approach we call Probability and Confidence Trade-space (PACT) evaluation.

Association of Pulmonary Tuberculosis and HIV in the Mexican Institute of Social Security, 2006-2014.

PubMed

Cabrera-Gaytán, David Alejandro; Niebla-Fuentes, María Del Rosario; Padilla-Velázquez, Rosario; Valle-Alvarado, Gabriel; Arriaga-Nieto, Lumumba; Rojas-Mendoza, Teresita; Rosado-Quiab, Ulises; Grajales-Muñiz, Concepción; Vallejos-Parás, Alfonso

2016-01-01

Tuberculosis and HIV remain a public health problem in developed countries. The objective of this study was to analyze the incidence trends of pulmonary TB and HIV comorbidity and treatment outcomes according to HIV during the period 2006 to 2014 in the Mexican Institute of Social Security. Analyzed data from this registry including pulmonary tuberculosis patients aged 15 years and older who had been diagnosed during the years 2006 to 2014 in the Mexican Institute of Social Security. The outcomes that we use were incidents rate, failure to treatment and death. Regression models were used to quantify associations between pulmonary tuberculosis and HIV mortality. During the study period, 31,352 patients were registered with pulmonary tuberculosis. The incidence rate observed during 2014 was 11.6 case of PTB per 100,000. The incidence rate for PTB and HIV was 0.345 per 100,000. The PTB incidence rate decreased by 0.07%, differences found in the PTB incidence rate by sex since in women decreased by 5.52% and in man increase by 3.62%. The pulmonary TB with HIV incidence rate decreased by 16.3% during the study period (In women increase 4.81% and in man decrease 21.6%). Analysis of PTB associated with HIV by age groups revealed that the highest incidence rates were observed for the 30 to 44 years old group. Meanwhile, the highest incidence rates of PTB without HIV occurred among the 60 and more years old individuals. We did not find statistically significant differences between treatment failure and PTB patients with HIV and without HIV. The treatment failure was associated with sex and the region of the patient. We found a strong association between HIV and the probability of dying during treatment. Our data suggested that patients suffering from both conditions (PTB and HIV) have no difference in the probability of failure of treatment contrary to other reports. Hypotheses to this is adherence to tuberculosis treatment with people living with HIV/AIDS, detection of PTB in patients suffering from HIV/AIDS or PTB patients on antiretroviral therapy were more likely to have successful treatment outcomes than those not on antiretroviral treatment. We have found that PTB and HIV increases the probability of dying during treatment compared to the cases of PTB without HIV, consistent with published other study HIV increases the mortality rates associated with PTB. No association between pulmonary tuberculosis with HIV and treatment failure was observed, but pulmonary tuberculosis and HIV increases the probability of dying during treatment compared to the pulmonary tuberculosis cases without HIV.

Compounding effects of sea level rise and fluvial flooding.

PubMed

Moftakhari, Hamed R; Salvadori, Gianfausto; AghaKouchak, Amir; Sanders, Brett F; Matthew, Richard A

2017-09-12

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.

Statistical Performance Evaluation Of Soft Seat Pressure Relief Valves

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

Harris, Stephen P.; Gross, Robert E.

2013-03-26

Risk-based inspection methods enable estimation of the probability of failure on demand for spring-operated pressure relief valves at the United States Department of Energy's Savannah River Site in Aiken, South Carolina. This paper presents a statistical performance evaluation of soft seat spring operated pressure relief valves. These pressure relief valves are typically smaller and of lower cost than hard seat (metal to metal) pressure relief valves and can provide substantial cost savings in fluid service applications (air, gas, liquid, and steam) providing that probability of failure on demand (the probability that the pressure relief valve fails to perform its intendedmore » safety function during a potentially dangerous over pressurization) is at least as good as that for hard seat valves. The research in this paper shows that the proportion of soft seat spring operated pressure relief valves failing is the same or less than that of hard seat valves, and that for failed valves, soft seat valves typically have failure ratios of proof test pressure to set pressure less than that of hard seat valves.« less

Increasing Compliance of Children with Autism: Effects of Programmed Reinforcement for High-Probability Requests and Varied Inter-Instruction Intervals

ERIC Educational Resources Information Center

Pitts, Laura; Dymond, Simon

2012-01-01

Research on the high-probability (high-p) request sequence shows that compliance with low-probability (low-p) requests generally increases when preceded by a series of high-p requests. Few studies have conducted formal preference assessments to identify the consequences used for compliance, which may partly explain treatment failures, and still…

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

DOE PAGES

Liao, Huafei N.; Groth, Katrina; Stevens-Adams, Susan

2015-07-29

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification aremore » discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.« less

Wear-Out Sensitivity Analysis Project Abstract

NASA Technical Reports Server (NTRS)

Harris, Adam

2015-01-01

During the course of the Summer 2015 internship session, I worked in the Reliability and Maintainability group of the ISS Safety and Mission Assurance department. My project was a statistical analysis of how sensitive ORU's (Orbital Replacement Units) are to a reliability parameter called the wear-out characteristic. The intended goal of this was to determine a worst case scenario of how many spares would be needed if multiple systems started exhibiting wear-out characteristics simultaneously. The goal was also to determine which parts would be most likely to do so. In order to do this, my duties were to take historical data of operational times and failure times of these ORU's and use them to build predictive models of failure using probability distribution functions, mainly the Weibull distribution. Then, I ran Monte Carlo Simulations to see how an entire population of these components would perform. From here, my final duty was to vary the wear-out characteristic from the intrinsic value, to extremely high wear-out values and determine how much the probability of sufficiency of the population would shift. This was done for around 30 different ORU populations on board the ISS.

Reliability assessment of slender concrete columns at the stability failure

NASA Astrophysics Data System (ADS)

Valašík, Adrián; Benko, Vladimír; Strauss, Alfred; Täubling, Benjamin

2018-01-01

The European Standard for designing concrete columns within the use of non-linear methods shows deficiencies in terms of global reliability, in case that the concrete columns fail by the loss of stability. The buckling failure is a brittle failure which occurs without warning and the probability of its formation depends on the columns slenderness. Experiments with slender concrete columns were carried out in cooperation with STRABAG Bratislava LTD in Central Laboratory of Faculty of Civil Engineering SUT in Bratislava. The following article aims to compare the global reliability of slender concrete columns with slenderness of 90 and higher. The columns were designed according to methods offered by EN 1992-1-1 [1]. The mentioned experiments were used as basis for deterministic nonlinear modelling of the columns and subsequent the probabilistic evaluation of structural response variability. Final results may be utilized as thresholds for loading of produced structural elements and they aim to present probabilistic design as less conservative compared to classic partial safety factor based design and alternative ECOV method.

Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

NASA Technical Reports Server (NTRS)

Gaebler, John A.; Tolson, Robert H.

2010-01-01

In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Parametric study of the effect of phase anisotropy on the micromechanical behaviour of dentin–adhesive interfaces

PubMed Central

Misra, Anil; Spencer, Paulette; Marangos, Orestes; Wang, Yong; Katz, J. Lawrence

2005-01-01

A finite element (FE) model has been developed based upon the recently measured micro-scale morphological, chemical and mechanical properties of dentin–adhesive (d–a) interfaces using confocal Raman microspectroscopy and scanning acoustic microscopy (SAM). The results computed from this FE model indicated that the stress distributions and concentrations are affected by the micro-scale elastic properties of various phases composing the d–a interface. However, these computations were performed assuming isotropic material properties for the d–a interface. The d–a interface components, such as the peritubular and intertubular dentin, the partially demineralized dentin and the so-called ‘hybrid layer’ adhesive-collagen composite, are probably anisotropic. In this paper, the FE model is extended to account for the probable anisotropic properties of these d–a interface phases. A parametric study is performed to study the effect of anisotropy on the micromechanical stress distributions in the hybrid layer and the peritubular dentin phases of the d–a interface. It is found that the anisotropy of the phases affects the region and extent of stress concentration as well as the location of the maximum stress concentrations. Thus, the anisotropy of the phases could effect the probable location of failure initiation, whether in the peritubular region or in the hybrid layer. PMID:16849175

A dual-mode generalized likelihood ratio approach to self-reorganizing digital flight control system design

NASA Technical Reports Server (NTRS)

Bueno, R.; Chow, E.; Gershwin, S. B.; Willsky, A. S.

1975-01-01

The research is reported on the problems of failure detection and reliable system design for digital aircraft control systems. Failure modes, cross detection probability, wrong time detection, application of performance tools, and the GLR computer package are discussed.

Submarine landslides of the Southern California Borderland

USGS Publications Warehouse

Lee, H.J.; Greene, H. Gary; Edwards, B.D.; Fisher, M.A.; Normark, W.R.

2009-01-01

Conventional bathymetry, sidescan-sonar and seismic-reflection data, and recent, multibeam surveys of large parts of the Southern California Borderland disclose the presence of numerous submarine landslides. Most of these features are fairly small, with lateral dimensions less than ??2 km. In areas where multibeam surveys are available, only two large landslide complexes were identified on the mainland slope- Goleta slide in Santa Barbara Channel and Palos Verdes debris avalanche on the San Pedro Escarpment south of Palos Verdes Peninsula. Both of these complexes indicate repeated recurrences of catastrophic slope failure. Recurrence intervals are not well constrained but appear to be in the range of 7500 years for the Goleta slide. The most recent major activity of the Palos Verdes debris avalanche occurred roughly 7500 years ago. A small failure deposit in Santa Barbara Channel, the Gaviota mudflow, was perhaps caused by an 1812 earthquake. Most landslides in this region are probably triggered by earthquakes, although the larger failures were likely conditioned by other factors, such as oversteepening, development of shelf-edge deltas, and high fluid pressures. If a subsequent future landslide were to occur in the area of these large landslide complexes, a tsunami would probably result. Runup distances of 10 m over a 30-km-long stretch of the Santa Barbara coastline are predicted for a recurrence of the Goleta slide, and a runup of 3 m over a comparable stretch of the Los Angeles coastline is modeled for the Palos Verdes debris avalanche. ?? 2009 The Geological Society of America.

Patient Education and Support During CKD Transitions: When the Possible Becomes Probable.

PubMed

Green, Jamie A; Boulware, L Ebony

2016-07-01

Patients transitioning from kidney disease to kidney failure require comprehensive patient-centered education and support. Efforts to prepare patients for this transition often fail to meet patients' needs due to uncertainty about which patients will progress to kidney failure, nonindividualized patient education programs, inadequate psychosocial support, or lack of assistance to guide patients through complex treatment plans. Resources are available to help overcome barriers to providing optimal care during this time, including prognostic tools, educational lesson plans, decision aids, communication skills training, peer support, and patient navigation programs. New models are being studied to comprehensively address patients' needs and improve the lives of kidney patients during this high-risk time. Copyright © 2016 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

SU-F-R-44: Modeling Lung SBRT Tumor Response Using Bayesian Network Averaging

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

Diamant, A; Ybarra, N; Seuntjens, J

2016-06-15

Purpose: The prediction of tumor control after a patient receives lung SBRT (stereotactic body radiation therapy) has proven to be challenging, due to the complex interactions between an individual’s biology and dose-volume metrics. Many of these variables have predictive power when combined, a feature that we exploit using a graph modeling approach based on Bayesian networks. This provides a probabilistic framework that allows for accurate and visually intuitive predictive modeling. The aim of this study is to uncover possible interactions between an individual patient’s characteristics and generate a robust model capable of predicting said patient’s treatment outcome. Methods: We investigatedmore » a cohort of 32 prospective patients from multiple institutions whom had received curative SBRT to the lung. The number of patients exhibiting tumor failure was observed to be 7 (event rate of 22%). The serum concentration of 5 biomarkers previously associated with NSCLC (non-small cell lung cancer) was measured pre-treatment. A total of 21 variables were analyzed including: dose-volume metrics with BED (biologically effective dose) correction and clinical variables. A Markov Chain Monte Carlo technique estimated the posterior probability distribution of the potential graphical structures. The probability of tumor failure was then estimated by averaging the top 100 graphs and applying Baye’s rule. Results: The optimal Bayesian model generated throughout this study incorporated the PTV volume, the serum concentration of the biomarker EGFR (epidermal growth factor receptor) and prescription BED. This predictive model recorded an area under the receiver operating characteristic curve of 0.94(1), providing better performance compared to competing methods in other literature. Conclusion: The use of biomarkers in conjunction with dose-volume metrics allows for the generation of a robust predictive model. The preliminary results of this report demonstrate that it is possible to accurately model the prognosis of an individual lung SBRT patient’s treatment.« less

["That flesh, pink and perishable": analysis of disease-free survival analysis in breast cancer in Gipuzkoa (Spain) in the presence of competing risks].

PubMed

Martínez-Camblor, Pablo; Larrañaga, Nerea; Sarasqueta, Cristina; Mitxelena, María José; Basterretxea, Mikel

2009-01-01

To analyze time of disease-free survival and relative survival in women diagnosed with breast cancer in the province of Gipuzkoa within the context of competing risks by assessing differences between the direct use of the Kaplan-Meier estimator and the multiple decrement method on the one hand, and relative survival on the other. All registered breast cancer cases in Gipuzkoa in 1995 and 1996 with stages other than stage IV were included. An 8-year follow-up for recurrence and a 10-year follow-up for survival were performed. Time of disease-free survival was studied by the multiple decrement model. Observed survival and survival corrected by the expected mortality in the population (relative survival) were also studied. Estimation of the probability of recurrence at 8 years with the multiple decrement method was 8.8% lower than that obtained with the Kaplan-Meier method. The difference between the observed and relative survival rates at 10 years was 10.8%. Both results show how, in this case, the Kaplan-Meier estimator overestimates both the probability of recurrence and that of mortality from the disease. Two issues are often overlooked when performing survival analyses: firstly, because of the lack of independence between survival time and censoring time, the results obtained by the Kaplan-Meier estimator are uninterpretable; secondly, it is an incontrovertible fact that one way or another, everyone causes failures. In this approach, survival analyses must take into account the probability of failure in the general population of reference. The results obtained in this study show that superficial use of the Kaplan Meier estimator overestimates both the probability of recurrence and that of mortality caused by the disease.

The SAM framework: modeling the effects of management factors on human behavior in risk analysis.

PubMed

Murphy, D M; Paté-Cornell, M E

1996-08-01

Complex engineered systems, such as nuclear reactors and chemical plants, have the potential for catastrophic failure with disastrous consequences. In recent years, human and management factors have been recognized as frequent root causes of major failures in such systems. However, classical probabilistic risk analysis (PRA) techniques do not account for the underlying causes of these errors because they focus on the physical system and do not explicitly address the link between components' performance and organizational factors. This paper describes a general approach for addressing the human and management causes of system failure, called the SAM (System-Action-Management) framework. Beginning with a quantitative risk model of the physical system, SAM expands the scope of analysis to incorporate first the decisions and actions of individuals that affect the physical system. SAM then links management factors (incentives, training, policies and procedures, selection criteria, etc.) to those decisions and actions. The focus of this paper is on four quantitative models of action that describe this last relationship. These models address the formation of intentions for action and their execution as a function of the organizational environment. Intention formation is described by three alternative models: a rational model, a bounded rationality model, and a rule-based model. The execution of intentions is then modeled separately. These four models are designed to assess the probabilities of individual actions from the perspective of management, thus reflecting the uncertainties inherent to human behavior. The SAM framework is illustrated for a hypothetical case of hazardous materials transportation. This framework can be used as a tool to increase the safety and reliability of complex technical systems by modifying the organization, rather than, or in addition to, re-designing the physical system.

Reliability assessment of multiple quantum well avalanche photodiodes

NASA Technical Reports Server (NTRS)

Yun, Ilgu; Menkara, Hicham M.; Wang, Yang; Oguzman, Isamil H.; Kolnik, Jan; Brennan, Kevin F.; May, Gray S.; Wagner, Brent K.; Summers, Christopher J.

1995-01-01

The reliability of doped-barrier AlGaAs/GsAs multi-quantum well avalanche photodiodes fabricated by molecular beam epitaxy is investigated via accelerated life tests. Dark current and breakdown voltage were the parameters monitored. The activation energy of the degradation mechanism and median device lifetime were determined. Device failure probability as a function of time was computed using the lognormal model. Analysis using the electron beam induced current method revealed the degradation to be caused by ionic impurities or contamination in the passivation layer.

Transmuted of Rayleigh Distribution with Estimation and Application on Noise Signal

NASA Astrophysics Data System (ADS)

Ahmed, Suhad; Qasim, Zainab

2018-05-01

This paper deals with transforming one parameter Rayleigh distribution, into transmuted probability distribution through introducing a new parameter (λ), since this studied distribution is necessary in representing signal data distribution and failure data model the value of this transmuted parameter |λ| ≤ 1, is also estimated as well as the original parameter (⊖) by methods of moments and maximum likelihood using different sample size (n=25, 50, 75, 100) and comparing the results of estimation by statistical measure (mean square error, MSE).

Molecular Evidence of Stress-Induced Acute Heart Injury in a Mouse Model Simulating Posttraumatic Stress Disorder

DTIC Science & Technology

2014-02-25

risk of drug or alcohol abuse. In addition, patients with PTSD often display structural changes in the pre- frontal cortex, the amygdala, and the... triglyceride levels (12–15). An 1871 report noted that serious cardiac disorders (car- diomyopathies, heart failure, heart pain, etc.) were a consequence of...epicardium probably play a key role in the EMT process (30, 31). Maintaining the proper ECM structure is critical to pre- serving the architecture and

Disasters as a necessary part of benefit-cost analyses.

PubMed

Mark, R K; Stuart-Alexander, D E

1977-09-16

Benefit-cost analyses for water projects generally have not included the expected costs (residual risk) of low-probability disasters such as dam failures, impoundment-induced earthquakes, and landslides. Analysis of the history of these types of events demonstrates that dam failures are not uncommon and that the probability of a reservoir-triggered earth-quake increases with increasing reservoir depth. Because the expected costs from such events can be significant and risk is project-specific, estimates should be made for each project. The cost of expected damage from a "high-risk" project in an urban area could be comparable to project benefits.

Postflight analysis of the single-axis acoustic system on SPAR VI and recommendations for future flights

NASA Technical Reports Server (NTRS)

Naumann, R. J.; Oran, W. A.; Whymark, R. R.; Rey, C.

1981-01-01

The single axis acoustic levitator that was flown on SPAR VI malfunctioned. The results of a series of tests, analyses, and investigation of hypotheses that were undertaken to determine the probable cause of failure are presented, together with recommendations for future flights of the apparatus. The most probable causes of the SPAR VI failure were lower than expected sound intensity due to mechanical degradation of the sound source, and an unexpected external force that caused the experiment sample to move radially and eventually be lost from the acoustic energy well.

Effect of Progressive Heart Failure on Cerebral Hemodynamics and Monoamine Metabolism in CNS.

PubMed

Mamalyga, M L; Mamalyga, L M

2017-07-01

Compensated and decompensated heart failure are characterized by different associations of disorders in the brain and heart. In compensated heart failure, the blood flow in the common carotid and basilar arteries does not change. Exacerbation of heart failure leads to severe decompensation and is accompanied by a decrease in blood flow in the carotid and basilar arteries. Changes in monoamine content occurring in the brain at different stages of heart failure are determined by various factors. The functional exercise test showed unequal monoamine-synthesizing capacities of the brain in compensated and decompensated heart failure. Reduced capacity of the monoaminergic systems in decompensated heart failure probably leads to overstrain of the central regulatory mechanisms, their gradual exhaustion, and failure of the compensatory mechanisms, which contributes to progression of heart failure.

Microdomain-Specific Modulation of L-Type Calcium Channels Leads to Triggered Ventricular Arrhythmia in Heart Failure

PubMed Central

Sanchez-Alonso, Jose L.; Bhargava, Anamika; O’Hara, Thomas; Glukhov, Alexey V.; Schobesberger, Sophie; Bhogal, Navneet; Sikkel, Markus B.; Mansfield, Catherine; Korchev, Yuri E.; Lyon, Alexander R.; Punjabi, Prakash P.; Nikolaev, Viacheslav O.; Trayanova, Natalia A.

2016-01-01

Rationale: Disruption in subcellular targeting of Ca2+ signaling complexes secondary to changes in cardiac myocyte structure may contribute to the pathophysiology of a variety of cardiac diseases, including heart failure (HF) and certain arrhythmias. Objective: To explore microdomain-targeted remodeling of ventricular L-type Ca2+ channels (LTCCs) in HF. Methods and Results: Super-resolution scanning patch-clamp, confocal and fluorescence microscopy were used to explore the distribution of single LTCCs in different membrane microdomains of nonfailing and failing human and rat ventricular myocytes. Disruption of membrane structure in both species led to the redistribution of functional LTCCs from their canonical location in transversal tubules (T-tubules) to the non-native crest of the sarcolemma, where their open probability was dramatically increased (0.034±0.011 versus 0.154±0.027, P<0.001). High open probability was linked to enhance calcium–calmodulin kinase II–mediated phosphorylation in non-native microdomains and resulted in an elevated ICa,L window current, which contributed to the development of early afterdepolarizations. A novel model of LTCC function in HF was developed; after its validation with experimental data, the model was used to ascertain how HF-induced T-tubule loss led to altered LTCC function and early afterdepolarizations. The HF myocyte model was then implemented in a 3-dimensional left ventricle model, demonstrating that such early afterdepolarizations can propagate and initiate reentrant arrhythmias. Conclusions: Microdomain-targeted remodeling of LTCC properties is an important event in pathways that may contribute to ventricular arrhythmogenesis in the settings of HF-associated remodeling. This extends beyond the classical concept of electric remodeling in HF and adds a new dimension to cardiovascular disease. PMID:27572487

Failures of cognitive control or attention? The case of stop-signal deficits in schizophrenia.

PubMed

Matzke, Dora; Hughes, Matthew; Badcock, Johanna C; Michie, Patricia; Heathcote, Andrew

2017-05-01

We used Bayesian cognitive modelling to identify the underlying causes of apparent inhibitory deficits in the stop-signal paradigm. The analysis was applied to stop-signal data reported by Badcock et al. (Psychological Medicine 32: 87-297, 2002) and Hughes et al. (Biological Psychology 89: 220-231, 2012), where schizophrenia patients and control participants made rapid choice responses, but on some trials were signalled to stop their ongoing response. Previous research has assumed an inhibitory deficit in schizophrenia, because estimates of the mean time taken to react to the stop signal are longer in patients than controls. We showed that these longer estimates are partly due to failing to react to the stop signal ("trigger failures") and partly due to a slower initiation of inhibition, implicating a failure of attention rather than a deficit in the inhibitory process itself. Correlations between the probability of trigger failures and event-related potentials reported by Hughes et al. are interpreted as supporting the attentional account of inhibitory deficits. Our results, and those of Matzke et al. (2016), who report that controls also display a substantial although lower trigger-failure rate, indicate that attentional factors need to be taken into account when interpreting results from the stop-signal paradigm.

Failure Investigation of Radiant Platen Superheater Tube of Thermal Power Plant Boiler

NASA Astrophysics Data System (ADS)

Ghosh, D.; Ray, S.; Mandal, A.; Roy, H.

2015-04-01

This paper highlights a case study of typical premature failure of a radiant platen superheater tube of 210 MW thermal power plant boiler. Visual examination, dimensional measurement and chemical analysis, are conducted as part of the investigations. Apart from these, metallographic analysis and fractography are also conducted to ascertain the probable cause of failure. Finally it has been concluded that the premature failure of the super heater tube can be attributed to localized creep at high temperature. The corrective actions has also been suggested to avoid this type of failure in near future.

Reliability analysis of redundant systems. [a method to compute transition probabilities

NASA Technical Reports Server (NTRS)

Yeh, H. Y.

1974-01-01

A method is proposed to compute the transition probability (the probability of partial or total failure) of parallel redundant system. The effect of geometry of the system, the direction of load, and the degree of redundancy on the probability of complete survival of parachute-like system are also studied. The results show that the probability of complete survival of three-member parachute-like system is very sensitive to the variation of horizontal angle of the load. However, it becomes very insignificant as the degree of redundancy increases.

Failure-to-rescue after injury is associated with preventability: The results of mortality panel review of failure-to-rescue cases in trauma.

PubMed

Kuo, Lindsay E; Kaufman, Elinore; Hoffman, Rebecca L; Pascual, Jose L; Martin, Niels D; Kelz, Rachel R; Holena, Daniel N

2017-03-01

Failure-to-rescue is defined as the conditional probability of death after a complication, and the failure-to-rescue rate reflects a center's ability to successfully "rescue" patients after complications. The validity of the failure-to-rescue rate as a quality measure is dependent on the preventability of death and the appropriateness of this measure for use in the trauma population is untested. We sought to evaluate the relationship between preventability and failure-to-rescue in trauma. All adjudications from a mortality review panel at an academic level I trauma center from 2005-2015 were merged with registry data for the same time period. The preventability of each death was determined by panel consensus as part of peer review. Failure-to-rescue deaths were defined as those occurring after any registry-defined complication. Univariate and multivariate logistic regression models between failure-to-rescue status and preventability were constructed and time to death was examined using survival time analyses. Of 26,557 patients, 2,735 (10.5%) had a complication, of whom 359 died for a failure-to-rescue rate of 13.2%. Of failure-to-rescue deaths, 272 (75.6%) were judged to be non-preventable, 65 (18.1%) were judged potentially preventable, and 22 (6.1%) were judged to be preventable by peer review. After adjusting for other patient factors, there remained a strong association between failure-to-rescue status and potentially preventable (odds ratio 2.32, 95% confidence interval, 1.47-3.66) and preventable (odds ratio 14.84, 95% confidence interval, 3.30-66.71) judgment. Despite a strong association between failure-to-rescue status and preventability adjudication, only a minority of deaths meeting the definition of failure to rescue were judged to be preventable or potentially preventable. Revision of the failure-to-rescue metric before use in trauma care benchmarking is warranted. Copyright © 2016 Elsevier Inc. All rights reserved.

Failure-to-rescue after injury is associated with preventability: The results of mortality panel review of failure-to-rescue cases in trauma

PubMed Central

Kuo, Lindsay E.; Kaufman, Elinore; Hoffman, Rebecca L.; Pascual, Jose L.; Martin, Niels D.; Kelz, Rachel R.; Holena, Daniel N.

2018-01-01

Background Failure-to-rescue is defined as the conditional probability of death after a complication, and the failure-to-rescue rate reflects a center’s ability to successfully “rescue” patients after complications. The validity of the failure-to-rescue rate as a quality measure is dependent on the preventability of death and the appropriateness of this measure for use in the trauma population is untested. We sought to evaluate the relationship between preventability and failure-to-rescue in trauma. Methods All adjudications from a mortality review panel at an academic level I trauma center from 2005–2015 were merged with registry data for the same time period. The preventability of each death was determined by panel consensus as part of peer review. Failure-to-rescue deaths were defined as those occurring after any registry-defined complication. Univariate and multivariate logistic regression models between failure-to-rescue status and preventability were constructed and time to death was examined using survival time analyses. Results Of 26,557 patients, 2,735 (10.5%) had a complication, of whom 359 died for a failure-to-rescue rate of 13.2%. Of failure-to-rescue deaths, 272 (75.6%) were judged to be non-preventable, 65 (18.1%) were judged potentially preventable, and 22 (6.1%) were judged to be preventable by peer review. After adjusting for other patient factors, there remained a strong association between failure-to-rescue status and potentially preventable (odds ratio 2.32, 95% confidence interval, 1.47–3.66) and preventable (odds ratio 14.84, 95% confidence interval, 3.30–66.71) judgment. Conclusion Despite a strong association between failure-to-rescue status and preventability adjudication, only a minority of deaths meeting the definition of failure to rescue were judged to be preventable or potentially preventable. Revision of the failure-to-rescue metric before use in trauma care benchmarking is warranted. PMID:27788924

Early High-Frequency Oscillatory Ventilation in Pediatric Acute Respiratory Failure. A Propensity Score Analysis.

PubMed

Bateman, Scot T; Borasino, Santiago; Asaro, Lisa A; Cheifetz, Ira M; Diane, Shelley; Wypij, David; Curley, Martha A Q

2016-03-01

The use of high-frequency oscillatory ventilation (HFOV) for acute respiratory failure in children is prevalent despite the lack of efficacy data. To compare the outcomes of patients with acute respiratory failure managed with HFOV within 24-48 hours of endotracheal intubation with those receiving conventional mechanical ventilation (CMV) and/or late HFOV. This is a secondary analysis of data from the RESTORE (Randomized Evaluation of Sedation Titration for Respiratory Failure) study, a prospective cluster randomized clinical trial conducted between 2009 and 2013 in 31 U.S. pediatric intensive care units. Propensity score analysis, including degree of hypoxia in the model, compared the duration of mechanical ventilation and mortality of patients treated with early HFOV matched with those treated with CMV/late HFOV. Among 2,449 subjects enrolled in RESTORE, 353 patients (14%) were ever supported on HFOV, of which 210 (59%) had HFOV initiated within 24-48 hours of intubation. The propensity score model predicting the probability of receiving early HFOV included 1,064 patients (181 early HFOV vs. 883 CMV/late HFOV) with significant hypoxia (oxygenation index ≥ 8). The degree of hypoxia was the most significant contributor to the propensity score model. After adjusting for risk category, early HFOV use was associated with a longer duration of mechanical ventilation (hazard ratio, 0.75; 95% confidence interval, 0.64-0.89; P = 0.001) but not with mortality (odds ratio, 1.28; 95% confidence interval, 0.92-1.79; P = 0.15) compared with CMV/late HFOV. In adjusted models including important oxygenation variables, early HFOV was associated with a longer duration of mechanical ventilation. These analyses make supporting the current approach to HFOV less convincing.

Development of an economic model to assess the cost-effectiveness of hawthorn extract as an adjunct treatment for heart failure in Australia

PubMed Central

Ford, Emily; Adams, Jon; Graves, Nicholas

2012-01-01

Objective An economic model was developed to evaluate the cost-effectiveness of hawthorn extract as an adjunctive treatment for heart failure in Australia. Methods A Markov model of chronic heart failure was developed to compare the costs and outcomes of standard treatment and standard treatment with hawthorn extract. Health states were defined by the New York Heart Association (NYHA) classification system and death. For any given cycle, patients could remain in the same NYHA class, experience an improvement or deterioration in NYHA class, be hospitalised or die. Model inputs were derived from the published medical literature, and the output was quality-adjusted life years (QALYs). Probabilistic sensitivity analysis was conducted. The expected value of perfect information (EVPI) and the expected value of partial perfect information (EVPPI) were conducted to establish the value of further research and the ideal target for such research. Results Hawthorn extract increased costs by $1866.78 and resulted in a gain of 0.02 QALYs. The incremental cost-effectiveness ratio was $85 160.33 per QALY. The cost-effectiveness acceptability curve indicated that at a threshold of $40 000 the new treatment had a 0.29 probability of being cost-effective. The average incremental net monetary benefit (NMB) was −$1791.64, the average NMB for the standard treatment was $92 067.49, and for hawthorn extract $90 275.84. Additional research is potentially cost-effective if research is not proposed to cost more than $325 million. Utilities form the most important target parameter group for further research. Conclusions Hawthorn extract is not currently considered to be cost-effective in as an adjunctive treatment for heart failure in Australia. Further research in the area of utilities is warranted. PMID:22942231

Development of an economic model to assess the cost-effectiveness of hawthorn extract as an adjunct treatment for heart failure in Australia.

PubMed

Ford, Emily; Adams, Jon; Graves, Nicholas

2012-01-01

An economic model was developed to evaluate the cost-effectiveness of hawthorn extract as an adjunctive treatment for heart failure in Australia. A Markov model of chronic heart failure was developed to compare the costs and outcomes of standard treatment and standard treatment with hawthorn extract. Health states were defined by the New York Heart Association (NYHA) classification system and death. For any given cycle, patients could remain in the same NYHA class, experience an improvement or deterioration in NYHA class, be hospitalised or die. Model inputs were derived from the published medical literature, and the output was quality-adjusted life years (QALYs). Probabilistic sensitivity analysis was conducted. The expected value of perfect information (EVPI) and the expected value of partial perfect information (EVPPI) were conducted to establish the value of further research and the ideal target for such research. Hawthorn extract increased costs by $1866.78 and resulted in a gain of 0.02 QALYs. The incremental cost-effectiveness ratio was $85 160.33 per QALY. The cost-effectiveness acceptability curve indicated that at a threshold of $40 000 the new treatment had a 0.29 probability of being cost-effective. The average incremental net monetary benefit (NMB) was -$1791.64, the average NMB for the standard treatment was $92 067.49, and for hawthorn extract $90 275.84. Additional research is potentially cost-effective if research is not proposed to cost more than $325 million. Utilities form the most important target parameter group for further research. Hawthorn extract is not currently considered to be cost-effective in as an adjunctive treatment for heart failure in Australia. Further research in the area of utilities is warranted.

CPLOAS_2 User Manual.

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

Sallaberry, Cedric Jean-Marie; Helton, Jon C.

2015-05-01

Weak link (WL)/strong link (SL) systems are important parts of the overall operational design of high - consequence systems. In such designs, the SL system is very robust and is intended to permit operation of the entire system under, and only under, intended conditions. In contrast, the WL system is intended to fail in a predictable and irreversible manner under accident conditions and render the entire system inoperable before an accidental operation of the SL system. The likelihood that the WL system will fail to d eactivate the entire system before the SL system fails (i.e., degrades into a configurationmore » that could allow an accidental operation of the entire system) is referred to as probability of loss of assured safety (PLOAS). This report describes the Fortran 90 program CPLOAS_2 that implements the following representations for PLOAS for situations in which both link physical properties and link failure properties are time - dependent: (i) failure of all SLs before failure of any WL, (ii) failure of any SL before f ailure of any WL, (iii) failure of all SLs before failure of all WLs, and (iv) failure of any SL before failure of all WLs. The effects of aleatory uncertainty and epistemic uncertainty in the definition and numerical evaluation of PLOAS can be included in the calculations performed by CPLOAS_2. Keywords: Aleatory uncertainty, CPLOAS_2, Epistemic uncertainty, Probability of loss of assured safety, Strong link, Uncertainty analysis, Weak link« less

Variations of electric resistance and H2 and Rn emissions of concrete blocks under increasing uniaxial compression

USGS Publications Warehouse

King, C.-Y.; Luo, G.

1990-01-01

Electric resistance and emissions of hydrogen and radon isotopes of concrete (which is somewhat similar to fault-zone materials) under increasing uniaxial compression were continuously monitored to check whether they show any pre- and post-failure changes that may correspond to similar changes reported for earthquakes. The results show that all these parameters generally begin to increase when the applied stresses reach 20% to 90% of the corresponding failure stresses, probably due to the occurrence and growth of dilatant microcracks in the specimens. The prefailure changes have different patterns for different specimens, probably because of differences in spatial and temporal distributions of the microcracks. The resistance shows large co-failure increases, and the gas emissions show large post-failure increases. The post-failure increase of radon persists longer and stays at a higher level than that of hydrogen, suggesting a difference in the emission mechanisms for these two kinds of gases. The H2 increase may be mainly due to chemical reaction at the crack surfaces while they are fresh, whereas the Rn increases may be mainly the result of the increased emanation area of such surfaces. The results suggest that monitoring of resistivity and gas emissions may be useful for predicting earthquakes and failures of concrete structures. ?? 1990 Birkha??user Verlag.

Prognostic Factors in Severe Chagasic Heart Failure

PubMed Central

Costa, Sandra de Araújo; Rassi, Salvador; Freitas, Elis Marra da Madeira; Gutierrez, Natália da Silva; Boaventura, Fabiana Miranda; Sampaio, Larissa Pereira da Costa; Silva, João Bastista Masson

2017-01-01

Background Prognostic factors are extensively studied in heart failure; however, their role in severe Chagasic heart failure have not been established. Objectives To identify the association of clinical and laboratory factors with the prognosis of severe Chagasic heart failure, as well as the association of these factors with mortality and survival in a 7.5-year follow-up. Methods 60 patients with severe Chagasic heart failure were evaluated regarding the following variables: age, blood pressure, ejection fraction, serum sodium, creatinine, 6-minute walk test, non-sustained ventricular tachycardia, QRS width, indexed left atrial volume, and functional class. Results 53 (88.3%) patients died during follow-up, and 7 (11.7%) remained alive. Cumulative overall survival probability was approximately 11%. Non-sustained ventricular tachycardia (HR = 2.11; 95% CI: 1.04 - 4.31; p<0.05) and indexed left atrial volume ≥ 72 mL/m2 (HR = 3.51; 95% CI: 1.63 - 7.52; p<0.05) were the only variables that remained as independent predictors of mortality. Conclusions The presence of non-sustained ventricular tachycardia on Holter and indexed left atrial volume > 72 mL/m2 are independent predictors of mortality in severe Chagasic heart failure, with cumulative survival probability of only 11% in 7.5 years. PMID:28443956

Fatigue analysis of composite materials using the fail-safe concept

NASA Technical Reports Server (NTRS)

Stievenard, G.

1982-01-01

If R1 is the probability of having a crack on a flight component and R2 is the probability of seeing this crack propagate between two scheduled inspections, the global failure regulation states that this product must not exceed 0.0000001.

Human versus automation in responding to failures: an expected-value analysis

NASA Technical Reports Server (NTRS)

Sheridan, T. B.; Parasuraman, R.

2000-01-01

A simple analytical criterion is provided for deciding whether a human or automation is best for a failure detection task. The method is based on expected-value decision theory in much the same way as is signal detection. It requires specification of the probabilities of misses (false negatives) and false alarms (false positives) for both human and automation being considered, as well as factors independent of the choice--namely, costs and benefits of incorrect and correct decisions as well as the prior probability of failure. The method can also serve as a basis for comparing different modes of automation. Some limiting cases of application are discussed, as are some decision criteria other than expected value. Actual or potential applications include the design and evaluation of any system in which either humans or automation are being considered.

Risk factors for oral methotrexate failure in patients with inflammatory polyarthritis: results from a UK prospective cohort study.

PubMed

Bluett, James; Sergeant, Jamie C; MacGregor, Alex J; Chipping, Jacqueline R; Marshall, Tarnya; Symmons, Deborah P M; Verstappen, Suzanne M M

2018-03-20

Oral methotrexate (MTX) is the first-line therapy for patients with rheumatoid arthritis (RA). However, approximately one quarter of patients discontinue MTX within 12 months. MTX failure, defined as MTX cessation or the addition of another anti-rheumatic drug, is usually due adverse event(s) and/or inefficacy. The aims of this study were to evaluate the rate and predictors of oral MTX failure. Subjects were recruited from the Norfolk Arthritis Register (NOAR), a primary care-based inception cohort of patients with early inflammatory polyarthritis (IP). Subjects were eligible if they commenced MTX as their first DMARD and were recruited between 2000 and 2008. Patient-reported reasons for MTX failure were recorded and categorised as adverse event, inefficacy or other. The addition of a second DMARD during the study period was categorised as failure due to inefficacy. Cox proportional hazards regression models were used to assess potential predictors of MTX failure, accounting for competing risks. A total of 431 patients were eligible. The probability of patients remaining on MTX at 2 years was 82%. Competing risk analysis revealed that earlier MTX failure due to inefficacy was associated with rheumatoid factor (RF) positivity, younger age at symptom onset and higher baseline disease activity (DAS-28). MTX cessation due to an adverse event was less likely in the RF-positive cohort. RF-positive inflammatory polyarthritis patients who are younger with higher baseline disease activity have an increased risk of MTX failure due to inefficacy. Such patients may require combination therapy as a first-line treatment.

Service Life Extension of the Propulsion System of Long-Term Manned Orbital Stations

NASA Technical Reports Server (NTRS)

Kamath, Ulhas; Kuznetsov, Sergei; Spencer, Victor

2014-01-01

One of the critical non-replaceable systems of a long-term manned orbital station is the propulsion system. Since the propulsion system operates beginning with the launch of station elements into orbit, its service life determines the service life of the station overall. Weighing almost a million pounds, the International Space Station (ISS) is about four times as large as the Russian space station Mir and about five times as large as the U.S. Skylab. Constructed over a span of more than a decade with the help of over 100 space flights, elements and modules of the ISS provide more research space than any spacecraft ever built. Originally envisaged for a service life of fifteen years, this Earth orbiting laboratory has been in orbit since 1998. Some elements that have been launched later in the assembly sequence were not yet built when the first elements were placed in orbit. Hence, some of the early modules that were launched at the inception of the program were already nearing the end of their design life when the ISS was finally ready and operational. To maximize the return on global investments on ISS, it is essential for the valuable research on ISS to continue as long as the station can be sustained safely in orbit. This paper describes the work performed to extend the service life of the ISS propulsion system. A system comprises of many components with varying failure rates. Reliability of a system is the probability that it will perform its intended function under encountered operating conditions, for a specified period of time. As we are interested in finding out how reliable a system would be in the future, reliability expressed as a function of time provides valuable insight. In a hypothetical bathtub shaped failure rate curve, the failure rate, defined as the number of failures per unit time that a currently healthy component will suffer in a given future time interval, decreases during infant-mortality period, stays nearly constant during the service life and increases at the end when the design service life ends and wear-out phase begins. However, the component failure rates do not remain constant over the entire cycle life. The failure rate depends on various factors such as design complexity, current age of the component, operating conditions, severity of environmental stress factors, etc. Development, qualification and acceptance test processes provide rigorous screening of components to weed out imperfections that might otherwise cause infant mortality failures. If sufficient samples are tested to failure, the failure time versus failure quantity can be analyzed statistically to develop a failure probability distribution function (PDF), a statistical model of the probability of failure versus time. Driven by cost and schedule constraints however, spacecraft components are generally not tested in large numbers. Uncertainties in failure rate and remaining life estimates increase when fewer units are tested. To account for this, spacecraft operators prefer to limit useful operations to a period shorter than the maximum demonstrated service life of the weakest component. Running each component to its failure to determine the maximum possible service life of a system can become overly expensive and impractical. Spacecraft operators therefore, specify the required service life and an acceptable factor of safety (FOS). The designers use these requirements to limit the life test duration. Midway through the design life, when benefits justify additional investments, supplementary life test may be performed to demonstrate the capability to safely extend the service life of the system. An innovative approach is required to evaluate the entire system, without having to go through an elaborate test program of propulsion system elements. Evaluating every component through a brute force test program would be a cost prohibitive and time consuming endeavor. ISS propulsion system components were designed and built decades ago. There are no representative ground test articles for some of the components. A 'test everything' approach would require manufacturing new test articles. The paper outlines some of the techniques used for selective testing, by way of cherry picking candidate components based on failure mode effects analysis, system level impacts, hazard analysis, etc. The type of testing required for extending the service life depends on the design and criticality of the component, failure modes and failure mechanisms, life cycle margin provided by the original certification, operational and environmental stresses encountered, etc. When specific failure mechanism being considered and the underlying relationship of that mode to the stresses provided in the test can be correlated by supporting analysis, time and effort required for conducting life extension testing can be significantly reduced. Exposure to corrosive propellants over long periods of time, for instance, lead to specific failure mechanisms in several components used in the propulsion system. Using Arrhenius model, which is tied to chemically dependent failure mechanisms such as corrosion or chemical reactions, it is possible to subject carefully selected test articles to accelerated life test. Arrhenius model reflects the proportional relationship between time to failure of a component and the exponential of the inverse of absolute temperature acting on the component. The acceleration factor is used to perform tests at higher stresses that allow direct correlation between the times to failure at a high test temperature to the temperatures to be expected in actual use. As long as the temperatures are such that new failure mechanisms are not introduced, this becomes a very useful method for testing to failure a relatively small sample of items for a much shorter amount of time. In this article, based on the example of the propulsion system of the first ISS module Zarya, theoretical approaches and practical activities of extending the service life of the propulsion system are reviewed with the goal of determining the maximum duration of its safe operation.

Forgetting induced speeding: Can prospective memory failure account for drivers exceeding the speed limit?

PubMed

Bowden, Vanessa K; Visser, Troy A W; Loft, Shayne

2017-06-01

It is generally assumed that drivers speed intentionally because of factors such as frustration with the speed limit or general impatience. The current study examined whether speeding following an interruption could be better explained by unintentional prospective memory (PM) failure. In these situations, interrupting drivers may create a PM task, with speeding the result of drivers forgetting their newly encoded intention to travel at a lower speed after interruption. Across 3 simulated driving experiments, corrected or uncorrected speeding in recently reduced speed zones (from 70 km/h to 40 km/h) increased on average from 8% when uninterrupted to 33% when interrupted. Conversely, the probability that participants traveled under their new speed limit in recently increased speed zones (from 40 km/h to 70 km/h) increased from 1% when uninterrupted to 23% when interrupted. Consistent with a PM explanation, this indicates that interruptions lead to a general failure to follow changed speed limits, not just to increased speeding. Further testing a PM explanation, Experiments 2 and 3 manipulated variables expected to influence the probability of PM failures and subsequent speeding after interruptions. Experiment 2 showed that performing a cognitively demanding task during the interruption, when compared with unfilled interruptions, increased the probability of initially speeding from 1% to 11%, but that participants were able to correct (reduce) their speed. In Experiment 3, providing participants with 10s longer to encode the new speed limit before interruption decreased the probability of uncorrected speeding after an unfilled interruption from 30% to 20%. Theoretical implications and implications for road design interventions are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

SU-C-BRD-02: A Team Focused Clinical Implementation and Failure Mode and Effects Analysis of HDR Skin Brachytherapy Using Valencia and Leipzig Surface Applicators

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

Sayler, E; Harrison, A; Eldredge-Hindy, H

Purpose: and Leipzig applicators (VLAs) are single-channel brachytherapy surface applicators used to treat skin lesions up to 2cm diameter. Source dwell times can be calculated and entered manually after clinical set-up or ultrasound. This procedure differs dramatically from CT-based planning; the novelty and unfamiliarity could lead to severe errors. To build layers of safety and ensure quality, a multidisciplinary team created a protocol and applied Failure Modes and Effects Analysis (FMEA) to the clinical procedure for HDR VLA skin treatments. Methods: team including physicists, physicians, nurses, therapists, residents, and administration developed a clinical procedure for VLA treatment. The procedure wasmore » evaluated using FMEA. Failure modes were identified and scored by severity, occurrence, and detection. The clinical procedure was revised to address high-scoring process nodes. Results: Several key components were added to the clinical procedure to minimize risk probability numbers (RPN): -Treatments are reviewed at weekly QA rounds, where physicians discuss diagnosis, prescription, applicator selection, and set-up. Peer review reduces the likelihood of an inappropriate treatment regime. -A template for HDR skin treatments was established in the clinical EMR system to standardize treatment instructions. This reduces the chances of miscommunication between the physician and planning physicist, and increases the detectability of an error during the physics second check. -A screen check was implemented during the second check to increase detectability of an error. -To reduce error probability, the treatment plan worksheet was designed to display plan parameters in a format visually similar to the treatment console display. This facilitates data entry and verification. -VLAs are color-coded and labeled to match the EMR prescriptions, which simplifies in-room selection and verification. Conclusion: Multidisciplinary planning and FMEA increased delectability and reduced error probability during VLA HDR Brachytherapy. This clinical model may be useful to institutions implementing similar procedures.« less

neutron-Induced Failures in semiconductor Devices

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

Wender, Stephen Arthur

2017-03-13

Single Event Effects are a very significant failure mode in modern semiconductor devices that may limit their reliability. Accelerated testing is important for semiconductor industry. Considerable more work is needed in this field to mitigate the problem. Mitigation of this problem will probably come from Physicists and Electrical Engineers working together

14 CFR 29.729 - Retracting mechanism.

Code of Federal Regulations, 2014 CFR

2014-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 29.777 and 29.779. (g...

14 CFR 27.729 - Retracting mechanism.

Code of Federal Regulations, 2010 CFR

2010-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 27.777 and 27.779. (g...

14 CFR 29.729 - Retracting mechanism.

Code of Federal Regulations, 2012 CFR

2012-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 29.777 and 29.779. (g...

14 CFR 27.729 - Retracting mechanism.

Code of Federal Regulations, 2013 CFR

2013-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 27.777 and 27.779. (g...

14 CFR 29.729 - Retracting mechanism.

Code of Federal Regulations, 2011 CFR

2011-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 29.777 and 29.779. (g...

14 CFR 29.729 - Retracting mechanism.

Code of Federal Regulations, 2013 CFR

2013-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 29.777 and 29.779. (g...

14 CFR 27.729 - Retracting mechanism.

Code of Federal Regulations, 2012 CFR

2012-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 27.777 and 27.779. (g...

14 CFR 27.729 - Retracting mechanism.

Code of Federal Regulations, 2011 CFR

2011-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 27.777 and 27.779. (g...

14 CFR 27.729 - Retracting mechanism.

Code of Federal Regulations, 2014 CFR

2014-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 27.777 and 27.779. (g...

14 CFR 29.729 - Retracting mechanism.

Code of Federal Regulations, 2010 CFR

2010-01-01

... loads occurring during retraction and extension at any airspeed up to the design maximum landing gear... of— (1) Any reasonably probable failure in the normal retraction system; or (2) The failure of any... location and operation of the retraction control must meet the requirements of §§ 29.777 and 29.779. (g...

Groundwater contamination from waste management sites: The interaction between risk-based engineering design and regulatory policy: 1. Methodology

NASA Astrophysics Data System (ADS)

Massmann, Joel; Freeze, R. Allan

1987-02-01

This paper puts in place a risk-cost-benefit analysis for waste management facilities that explicitly recognizes the adversarial relationship that exists in a regulated market economy between the owner/operator of a waste management facility and the government regulatory agency under whose terms the facility must be licensed. The risk-cost-benefit analysis is set up from the perspective of the owner/operator. It can be used directly by the owner/operator to assess alternative design strategies. It can also be used by the regulatory agency to assess alternative regulatory policy, but only in an indirect manner, by examining the response of an owner/operator to the stimuli of various policies. The objective function is couched in terms of a discounted stream of benefits, costs, and risks over an engineering time horizon. Benefits are in the form of revenues for services provided; costs are those of construction and operation of the facility. Risk is defined as the cost associated with the probability of failure, with failure defined as the occurrence of a groundwater contamination event that violates the licensing requirements established for the facility. Failure requires a breach of the containment structure and contaminant migration through the hydrogeological environment to a compliance surface. The probability of failure can be estimated on the basis of reliability theory for the breach of containment and with a Monte-Carlo finite-element simulation for the advective contaminant transport. In the hydrogeological environment the hydraulic conductivity values are defined stochastically. The probability of failure is reduced by the presence of a monitoring network operated by the owner/operator and located between the source and the regulatory compliance surface. The level of reduction in the probability of failure depends on the probability of detection of the monitoring network, which can be calculated from the stochastic contaminant transport simulations. While the framework is quite general, the development in this paper is specifically suited for a landfill in which the primary design feature is one or more synthetic liners in parallel. Contamination is brought about by the release of a single, inorganic nonradioactive species into a saturated, high-permeability, advective, steady state horizontal flow system which can be analyzed with a two-dimensional analysis. It is possible to carry out sensitivity analyses for a wide variety of influences on this system, including landfill size, liner design, hydrogeological parameters, amount of exploration, extent of monitoring network, nature of remedial schemes, economic factors, and regulatory policy.

Semiparametric regression analysis of interval-censored competing risks data.

PubMed

Mao, Lu; Lin, Dan-Yu; Zeng, Donglin

2017-09-01

Interval-censored competing risks data arise when each study subject may experience an event or failure from one of several causes and the failure time is not observed directly but rather is known to lie in an interval between two examinations. We formulate the effects of possibly time-varying (external) covariates on the cumulative incidence or sub-distribution function of competing risks (i.e., the marginal probability of failure from a specific cause) through a broad class of semiparametric regression models that captures both proportional and non-proportional hazards structures for the sub-distribution. We allow each subject to have an arbitrary number of examinations and accommodate missing information on the cause of failure. We consider nonparametric maximum likelihood estimation and devise a fast and stable EM-type algorithm for its computation. We then establish the consistency, asymptotic normality, and semiparametric efficiency of the resulting estimators for the regression parameters by appealing to modern empirical process theory. In addition, we show through extensive simulation studies that the proposed methods perform well in realistic situations. Finally, we provide an application to a study on HIV-1 infection with different viral subtypes. © 2017, The International Biometric Society.

Reducing the Risk of Human Space Missions with INTEGRITY

NASA Technical Reports Server (NTRS)

Jones, Harry W.; Dillon-Merill, Robin L.; Tri, Terry O.; Henninger, Donald L.

2003-01-01

The INTEGRITY Program will design and operate a test bed facility to help prepare for future beyond-LEO missions. The purpose of INTEGRITY is to enable future missions by developing, testing, and demonstrating advanced human space systems. INTEGRITY will also implement and validate advanced management techniques including risk analysis and mitigation. One important way INTEGRITY will help enable future missions is by reducing their risk. A risk analysis of human space missions is important in defining the steps that INTEGRITY should take to mitigate risk. This paper describes how a Probabilistic Risk Assessment (PRA) of human space missions will help support the planning and development of INTEGRITY to maximize its benefits to future missions. PRA is a systematic methodology to decompose the system into subsystems and components, to quantify the failure risk as a function of the design elements and their corresponding probability of failure. PRA provides a quantitative estimate of the probability of failure of the system, including an assessment and display of the degree of uncertainty surrounding the probability. PRA provides a basis for understanding the impacts of decisions that affect safety, reliability, performance, and cost. Risks with both high probability and high impact are identified as top priority. The PRA of human missions beyond Earth orbit will help indicate how the risk of future human space missions can be reduced by integrating and testing systems in INTEGRITY.

A framework for conducting mechanistic based reliability assessments of components operating in complex systems

NASA Astrophysics Data System (ADS)

Wallace, Jon Michael

2003-10-01

Reliability prediction of components operating in complex systems has historically been conducted in a statistically isolated manner. Current physics-based, i.e. mechanistic, component reliability approaches focus more on component-specific attributes and mathematical algorithms and not enough on the influence of the system. The result is that significant error can be introduced into the component reliability assessment process. The objective of this study is the development of a framework that infuses the needs and influence of the system into the process of conducting mechanistic-based component reliability assessments. The formulated framework consists of six primary steps. The first three steps, identification, decomposition, and synthesis, are primarily qualitative in nature and employ system reliability and safety engineering principles to construct an appropriate starting point for the component reliability assessment. The following two steps are the most unique. They involve a step to efficiently characterize and quantify the system-driven local parameter space and a subsequent step using this information to guide the reduction of the component parameter space. The local statistical space quantification step is accomplished using two proposed multivariate probability models: Multi-Response First Order Second Moment and Taylor-Based Inverse Transformation. Where existing joint probability models require preliminary distribution and correlation information of the responses, these models combine statistical information of the input parameters with an efficient sampling of the response analyses to produce the multi-response joint probability distribution. Parameter space reduction is accomplished using Approximate Canonical Correlation Analysis (ACCA) employed as a multi-response screening technique. The novelty of this approach is that each individual local parameter and even subsets of parameters representing entire contributing analyses can now be rank ordered with respect to their contribution to not just one response, but the entire vector of component responses simultaneously. The final step of the framework is the actual probabilistic assessment of the component. Although the same multivariate probability tools employed in the characterization step can be used for the component probability assessment, variations of this final step are given to allow for the utilization of existing probabilistic methods such as response surface Monte Carlo and Fast Probability Integration. The overall framework developed in this study is implemented to assess the finite-element based reliability prediction of a gas turbine airfoil involving several failure responses. Results of this implementation are compared to results generated using the conventional 'isolated' approach as well as a validation approach conducted through large sample Monte Carlo simulations. The framework resulted in a considerable improvement to the accuracy of the part reliability assessment and an improved understanding of the component failure behavior. Considerable statistical complexity in the form of joint non-normal behavior was found and accounted for using the framework. Future applications of the framework elements are discussed.

Optimization of geothermal well trajectory in order to minimize borehole failure

NASA Astrophysics Data System (ADS)

Dahrabou, A.; Valley, B.; Ladner, F.; Guinot, F.; Meier, P.

2017-12-01

In projects based on Enhanced Geothermal System (EGS) principle, deep boreholes are drilled to low permeability rock masses. As part of the completion operations, the permeability of existing fractures in the rock mass is enhanced by injecting large volumes of water. These stimulation treatments aim at achieving enough water circulation for heat extraction at commercial rates which makes the stimulation operations critical to the project success. The accurate placement of the stimulation treatments requires well completion with effective zonal isolation, and wellbore stability is a prerequisite to all zonal isolation techniques, be it packer sealing or cement placement. In this project, a workflow allowing a fast decision-making process for selecting an optimal well trajectory for EGS projects is developed. In fact, the well is first drilled vertically then based on logging data which are costly (100 KCHF/day), the direction in which the strongly deviated borehole section will be drilled needs to be determined in order to optimize borehole stability and to intersect the highest number of fractures that are oriented favorably for stimulation. The workflow applies to crystalline rock and includes an uncertainty and risk assessment framework. An initial sensitivity study was performed to identify the most influential parameters on borehole stability. The main challenge in these analyses is that the strength and stress profiles are unknown independently. Calibration of a geomechanical model on the observed borehole failure has been performed using data from the Basel Geothermal well BS-1. In a first approximation, a purely elastic-static analytical solution in combination with a purely cohesive failure criterion were used as it provides the most consistent prediction across failure indicators. A systematic analysis of the uncertainty on all parameters was performed to assess the reliability of the optimal trajectory selection. To each drilling scenario, failure probability and the associated risks, are computed stochastically. In addition, model uncertainty is assessed by confronting various failure modelling approaches to the available failure data from the Basel Project. Together, these results form the basis of an integrated workflow optimizing geothermal (EGS) well trajectory.

Optimization Testbed Cometboards Extended into Stochastic Domain

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.; Patnaik, Surya N.

2010-01-01

COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.

Reliability Analysis of a Green Roof Under Different Storm Scenarios

NASA Astrophysics Data System (ADS)

William, R. K.; Stillwell, A. S.

2015-12-01

Urban environments continue to face the challenges of localized flooding and decreased water quality brought on by the increasing amount of impervious area in the built environment. Green infrastructure provides an alternative to conventional storm sewer design by using natural processes to filter and store stormwater at its source. However, there are currently few consistent standards available in North America to ensure that installed green infrastructure is performing as expected. This analysis offers a method for characterizing green roof failure using a visual aid commonly used in earthquake engineering: fragility curves. We adapted the concept of the fragility curve based on the efficiency in runoff reduction provided by a green roof compared to a conventional roof under different storm scenarios. We then used the 2D distributed surface water-groundwater coupled model MIKE SHE to model the impact that a real green roof might have on runoff in different storm events. We then employed a multiple regression analysis to generate an algebraic demand model that was input into the Matlab-based reliability analysis model FERUM, which was then used to calculate the probability of failure. The use of reliability analysis as a part of green infrastructure design code can provide insights into green roof weaknesses and areas for improvement. It also supports the design of code that is more resilient than current standards and is easily testable for failure. Finally, the understanding of reliability of a single green roof module under different scenarios can support holistic testing of system reliability.

Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches.

PubMed

Chan, Jennifer S K

2016-05-01

Dropouts are common in longitudinal study. If the dropout probability depends on the missing observations at or after dropout, this type of dropout is called informative (or nonignorable) dropout (ID). Failure to accommodate such dropout mechanism into the model will bias the parameter estimates. We propose a conditional autoregressive model for longitudinal binary data with an ID model such that the probabilities of positive outcomes as well as the drop-out indicator in each occasion are logit linear in some covariates and outcomes. This model adopting a marginal model for outcomes and a conditional model for dropouts is called a selection model. To allow for the heterogeneity and clustering effects, the outcome model is extended to incorporate mixture and random effects. Lastly, the model is further extended to a novel model that models the outcome and dropout jointly such that their dependency is formulated through an odds ratio function. Parameters are estimated by a Bayesian approach implemented using the user-friendly Bayesian software WinBUGS. A methadone clinic dataset is analyzed to illustrate the proposed models. Result shows that the treatment time effect is still significant but weaker after allowing for an ID process in the data. Finally the effect of drop-out on parameter estimates is evaluated through simulation studies. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hard choices in assessing survival past dams — a comparison of single- and paired-release strategies

USGS Publications Warehouse

Zydlewski, Joseph D.; Stich, Daniel S.; Sigourney, Douglas B.

2017-01-01

Mark–recapture models are widely used to estimate survival of salmon smolts migrating past dams. Paired releases have been used to improve estimate accuracy by removing components of mortality not attributable to the dam. This method is accompanied by reduced precision because (i) sample size is reduced relative to a single, large release; and (ii) variance calculations inflate error. We modeled an idealized system with a single dam to assess trade-offs between accuracy and precision and compared methods using root mean squared error (RMSE). Simulations were run under predefined conditions (dam mortality, background mortality, detection probability, and sample size) to determine scenarios when the paired release was preferable to a single release. We demonstrate that a paired-release design provides a theoretical advantage over a single-release design only at large sample sizes and high probabilities of detection. At release numbers typical of many survival studies, paired release can result in overestimation of dam survival. Failures to meet model assumptions of a paired release may result in further overestimation of dam-related survival. Under most conditions, a single-release strategy was preferable.

Hazard function theory for nonstationary natural hazards

NASA Astrophysics Data System (ADS)

Read, L.; Vogel, R. M.

2015-12-01

Studies from the natural hazards literature indicate that many natural processes, including wind speeds, landslides, wildfires, precipitation, streamflow and earthquakes, show evidence of nonstationary behavior such as trends in magnitudes through time. Traditional probabilistic analysis of natural hazards based on partial duration series (PDS) generally assumes stationarity in the magnitudes and arrivals of events, i.e. that the probability of exceedance is constant through time. Given evidence of trends and the consequent expected growth in devastating impacts from natural hazards across the world, new methods are needed to characterize their probabilistic behavior. The field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (x) with its failure time series (t), enabling computation of corresponding average return periods and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose PDS magnitudes are assumed to follow the widely applied Poisson-GP model. We derive a 2-parameter Generalized Pareto hazard model and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard event series x, with corresponding failure time series t, should have application to a wide class of natural hazards.

Modelling indirect interactions during failure spreading in a project activity network.

PubMed

Ellinas, Christos

2018-03-12

Spreading broadly refers to the notion of an entity propagating throughout a networked system via its interacting components. Evidence of its ubiquity and severity can be seen in a range of phenomena, from disease epidemics to financial systemic risk. In order to understand the dynamics of these critical phenomena, computational models map the probability of propagation as a function of direct exposure, typically in the form of pairwise interactions between components. By doing so, the important role of indirect interactions remains unexplored. In response, we develop a simple model that accounts for the effect of both direct and subsequent exposure, which we deploy in the novel context of failure propagation within a real-world engineering project. We show that subsequent exposure has a significant effect in key aspects, including the: (a) final spreading event size, (b) propagation rate, and (c) spreading event structure. In addition, we demonstrate the existence of 'hidden influentials' in large-scale spreading events, and evaluate the role of direct and subsequent exposure in their emergence. Given the evidence of the importance of subsequent exposure, our findings offer new insight on particular aspects that need to be included when modelling network dynamics in general, and spreading processes specifically.

Sensitivity Analysis of the Bone Fracture Risk Model

NASA Technical Reports Server (NTRS)

Lewandowski, Beth; Myers, Jerry; Sibonga, Jean Diane

2017-01-01

Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including environmental factors, factors associated with the fall event, mass and anthropometric values of the astronaut, BMD characteristics, characteristics of the relationship between BMD and bone strength and bone fracture characteristics. The uncertainty in these factors is captured through the use of parameter distributions and the fracture predictions are probability distributions with a mean value and an associated uncertainty. To determine parameter sensitivity, a correlation coefficient is found between the sample set of each model parameter and the calculated fracture probabilities. Each parameters contribution to the variance is found by squaring the correlation coefficients, dividing by the sum of the squared correlation coefficients, and multiplying by 100. Results: Sensitivity analyses of BFxRM simulations of preflight, 0 days post-flight and 365 days post-flight falls onto the hip revealed a subset of the twelve factors within the model which cause the most variation in the fracture predictions. These factors include the spring constant used in the hip biomechanical model, the midpoint FRI parameter within the equation used to convert FRI to fracture probability and preflight BMD values. Future work: Plans are underway to update the BFxRM by incorporating bone strength information from finite element models (FEM) into the bone strength portion of the BFxRM. Also, FEM bone strength information along with fracture outcome data will be incorporated into the FRI to fracture probability.

Optimal Mission Abort Policy for Systems Operating in a Random Environment.

PubMed

Levitin, Gregory; Finkelstein, Maxim

2018-04-01

Many real-world critical systems, e.g., aircrafts, manned space flight systems, and submarines, utilize mission aborts to enhance their survivability. Specifically, a mission can be aborted when a certain malfunction condition is met and a rescue or recovery procedure is then initiated. For systems exposed to external impacts, the malfunctions are often caused by the consequences of these impacts. Traditional system reliability models typically cannot address a possibility of mission aborts. Therefore, in this article, we first develop the corresponding methodology for modeling and evaluation of the mission success probability and survivability of systems experiencing both internal failures and external shocks. We consider a policy when a mission is aborted and a rescue procedure is activated upon occurrence of the mth shock. We demonstrate the tradeoff between the system survivability and the mission success probability that should be balanced by the proper choice of the decision variable m. A detailed illustrative example of a mission performed by an unmanned aerial vehicle is presented. © 2017 Society for Risk Analysis.

A hierarchical approach to reliability modeling of fault-tolerant systems. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gossman, W. E.

1986-01-01

A methodology for performing fault tolerant system reliability analysis is presented. The method decomposes a system into its subsystems, evaluates vent rates derived from the subsystem's conditional state probability vector and incorporates those results into a hierarchical Markov model of the system. This is done in a manner that addresses failure sequence dependence associated with the system's redundancy management strategy. The method is derived for application to a specific system definition. Results are presented that compare the hierarchical model's unreliability prediction to that of a more complicated tandard Markov model of the system. The results for the example given indicate that the hierarchical method predicts system unreliability to a desirable level of accuracy while achieving significant computational savings relative to component level Markov model of the system.

Why earthquakes correlate weakly with the solid Earth tides: Effects of periodic stress on the rate and probability of earthquake occurrence

USGS Publications Warehouse

Beeler, N.M.; Lockner, D.A.

2003-01-01

We provide an explanation why earthquake occurrence does not correlate well with the daily solid Earth tides. The explanation is derived from analysis of laboratory experiments in which faults are loaded to quasiperiodic failure by the combined action of a constant stressing rate, intended to simulate tectonic loading, and a small sinusoidal stress, analogous to the Earth tides. Event populations whose failure times correlate with the oscillating stress show two modes of response; the response mode depends on the stressing frequency. Correlation that is consistent with stress threshold failure models, e.g., Coulomb failure, results when the period of stress oscillation exceeds a characteristic time tn; the degree of correlation between failure time and the phase of the driving stress depends on the amplitude and frequency of the stress oscillation and on the stressing rate. When the period of the oscillating stress is less than tn, the correlation is not consistent with threshold failure models, and much higher stress amplitudes are required to induce detectable correlation with the oscillating stress. The physical interpretation of tn is the duration of failure nucleation. Behavior at the higher frequencies is consistent with a second-order dependence of the fault strength on sliding rate which determines the duration of nucleation and damps the response to stress change at frequencies greater than 1/tn. Simple extrapolation of these results to the Earth suggests a very weak correlation of earthquakes with the daily Earth tides, one that would require >13,000 earthquakes to detect. On the basis of our experiments and analysis, the absence of definitive daily triggering of earthquakes by the Earth tides requires that for earthquakes, tn exceeds the daily tidal period. The experiments suggest that the minimum typical duration of earthquake nucleation on the San Andreas fault system is ???1 year.

Probabilistic metrology or how some measurement outcomes render ultra-precise estimates

NASA Astrophysics Data System (ADS)

Calsamiglia, J.; Gendra, B.; Muñoz-Tapia, R.; Bagan, E.

2016-10-01

We show on theoretical grounds that, even in the presence of noise, probabilistic measurement strategies (which have a certain probability of failure or abstention) can provide, upon a heralded successful outcome, estimates with a precision that exceeds the deterministic bounds for the average precision. This establishes a new ultimate bound on the phase estimation precision of particular measurement outcomes (or sequence of outcomes). For probe systems subject to local dephasing, we quantify such precision limit as a function of the probability of failure that can be tolerated. Our results show that the possibility of abstaining can set back the detrimental effects of noise.

Fault tree analysis for system modeling in case of intentional EMI

NASA Astrophysics Data System (ADS)

Genender, E.; Mleczko, M.; Döring, O.; Garbe, H.; Potthast, S.

2011-08-01

The complexity of modern systems on the one hand and the rising threat of intentional electromagnetic interference (IEMI) on the other hand increase the necessity for systematical risk analysis. Most of the problems can not be treated deterministically since slight changes in the configuration (source, position, polarization, ...) can dramatically change the outcome of an event. For that purpose, methods known from probabilistic risk analysis can be applied. One of the most common approaches is the fault tree analysis (FTA). The FTA is used to determine the system failure probability and also the main contributors to its failure. In this paper the fault tree analysis is introduced and a possible application of that method is shown using a small computer network as an example. The constraints of this methods are explained and conclusions for further research are drawn.

Rock Slide Risk Assessment: A Semi-Quantitative Approach

NASA Astrophysics Data System (ADS)

Duzgun, H. S. B.

2009-04-01

Rock slides can be better managed by systematic risk assessments. Any risk assessment methodology for rock slides involves identification of rock slide risk components, which are hazard, elements at risk and vulnerability. For a quantitative/semi-quantitative risk assessment for rock slides, a mathematical value the risk has to be computed and evaluated. The quantitative evaluation of risk for rock slides enables comparison of the computed risk with the risk of other natural and/or human-made hazards and providing better decision support and easier communication for the decision makers. A quantitative/semi-quantitative risk assessment procedure involves: Danger Identification, Hazard Assessment, Elements at Risk Identification, Vulnerability Assessment, Risk computation, Risk Evaluation. On the other hand, the steps of this procedure require adaptation of existing or development of new implementation methods depending on the type of landslide, data availability, investigation scale and nature of consequences. In study, a generic semi-quantitative risk assessment (SQRA) procedure for rock slides is proposed. The procedure has five consecutive stages: Data collection and analyses, hazard assessment, analyses of elements at risk and vulnerability and risk assessment. The implementation of the procedure for a single rock slide case is illustrated for a rock slope in Norway. Rock slides from mountain Ramnefjell to lake Loen are considered to be one of the major geohazards in Norway. Lake Loen is located in the inner part of Nordfjord in Western Norway. Ramnefjell Mountain is heavily jointed leading to formation of vertical rock slices with height between 400-450 m and width between 7-10 m. These slices threaten the settlements around Loen Valley and tourists visiting the fjord during summer season, as the released slides have potential of creating tsunami. In the past, several rock slides had been recorded from the Mountain Ramnefjell between 1905 and 1950. Among them, four of the slides caused formation of tsunami waves which washed up to 74 m above the lake level. Two of the slides resulted in many fatalities in the inner part of the Loen Valley as well as great damages. There are three predominant joint structures in Ramnefjell Mountain, which controls failure and the geometry of the slides. The first joint set is a foliation plane striking northeast-southwest and dipping 35˚ -40˚ to the east-southeast. The second and the third joint sets are almost perpendicular and parallel to the mountain side and scarp, respectively. These three joint sets form slices of rock columns with width ranging between 7-10 m and height of 400-450 m. It is stated that the joints in set II are opened between 1-2 m, which may bring about collection of water during heavy rainfall or snow melt causing the slices to be pressed out. It is estimated that water in the vertical joints both reduces the shear strength of sliding plane and causes reduction of normal stress on the sliding plane due to formation of uplift force. Hence rock slides in Ramnefjell mountain occur in plane failure mode. The quantitative evaluation of rock slide risk requires probabilistic analysis of rock slope stability and identification of consequences if the rock slide occurs. In this study failure probability of a rock slice is evaluated by first-order reliability method (FORM). Then in order to use the calculated probability of failure value (Pf) in risk analyses, it is required to associate this Pf with frequency based probabilities (i.ePf / year) since the computed failure probabilities is a measure of hazard and not a measure of risk unless they are associated with the consequences of the failure. This can be done by either considering the time dependent behavior of the basic variables in the probabilistic models or associating the computed Pf with frequency of the failures in the region. In this study, the frequency of previous rock slides in the previous century in Remnefjell is used for evaluation of frequency based probability to be used in risk assessment. The major consequence of a rock slide is generation of a tsunami in the lake Loen, causing inundation of residential areas around the lake. Risk is assessed by adapting damage probability matrix approach, which is originally developed for risk assessment for buildings in case of earthquake.

Study on Failure of Third-Party Damage for Urban Gas Pipeline Based on Fuzzy Comprehensive Evaluation.

PubMed

Li, Jun; Zhang, Hong; Han, Yinshan; Wang, Baodong

2016-01-01

Focusing on the diversity, complexity and uncertainty of the third-party damage accident, the failure probability of third-party damage to urban gas pipeline was evaluated on the theory of analytic hierarchy process and fuzzy mathematics. The fault tree of third-party damage containing 56 basic events was built by hazard identification of third-party damage. The fuzzy evaluation of basic event probabilities were conducted by the expert judgment method and using membership function of fuzzy set. The determination of the weight of each expert and the modification of the evaluation opinions were accomplished using the improved analytic hierarchy process, and the failure possibility of the third-party to urban gas pipeline was calculated. Taking gas pipelines of a certain large provincial capital city as an example, the risk assessment structure of the method was proved to conform to the actual situation, which provides the basis for the safety risk prevention.

Role of stress triggering in earthquake migration on the North Anatolian fault

USGS Publications Warehouse

Stein, R.S.; Dieterich, J.H.; Barka, A.A.

1996-01-01

Ten M???6.7 earthquakes ruptured 1,000 km of the North Anatolian fault (Turkey) during 1939-92, providing an unsurpassed opportunity to study how one large shock sets up the next. Calculations of the change in Coulomb failure stress reveal that 9 out of 10 ruptures were brought closer to failure by the preceding shocks, typically by 5 bars, equivalent to 20 years of secular stressing. We translate the calculated stress changes into earthquake probabilities using an earthquake-nucleation constitutive relation, which includes both permanent and transient stress effects. For the typical 10-year period between triggering and subsequent rupturing shocks in the Anatolia sequence, the stress changes yield an average three-fold gain in the ensuing earthquake probability. Stress is now calculated to be high at several isolated sites along the fault. During the next 30 years, we estimate a 15% probability of a M???6.7 earthquake east of the major eastern center of Erzincan, and a 12% probability for a large event south of the major western port city of Izmit. Such stress-based probability calculations may thus be useful to assess and update earthquake hazards elsewhere. ?? 1997 Elsevier Science Ltd.

SU-E-T-627: Failure Modes and Effect Analysis for Monthly Quality Assurance of Linear Accelerator

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

Xie, J; Xiao, Y; Wang, J

2014-06-15

Purpose: To develop and implement a failure mode and effect analysis (FMEA) on routine monthly Quality Assurance (QA) tests (physical tests part) of linear accelerator. Methods: A systematic failure mode and effect analysis method was performed for monthly QA procedures. A detailed process tree of monthly QA was created and potential failure modes were defined. Each failure mode may have many influencing factors. For each factor, a risk probability number (RPN) was calculated from the product of probability of occurrence (O), the severity of effect (S), and detectability of the failure (D). The RPN scores are in a range ofmore » 1 to 1000, with higher scores indicating stronger correlation to a given influencing factor of a failure mode. Five medical physicists in our institution were responsible to discuss and to define the O, S, D values. Results: 15 possible failure modes were identified and all RPN scores of all influencing factors of these 15 failue modes were from 8 to 150, and the checklist of FMEA in monthly QA was drawn. The system showed consistent and accurate response to erroneous conditions. Conclusion: The influencing factors of RPN greater than 50 were considered as highly-correlated factors of a certain out-oftolerance monthly QA test. FMEA is a fast and flexible tool to develop an implement a quality management (QM) frame work of monthly QA, which improved the QA efficiency of our QA team. The FMEA work may incorporate more quantification and monitoring fuctions in future.« less

Heart failure rehospitalization of the Medicare FFS patient: a state-level analysis exploring 30-day readmission factors.

PubMed

Schmeida, Mary; Savrin, Ronald A

2012-01-01

Heart failure readmission among the elderly is frequent and costly to both the patient and the Medicare trust fund. In this study, the authors explore the factors that are associated with states having heart failure readmission rates that are higher than the U.S. national rate. Acute inpatient hospital settings. 50 state-level data and multivariate regression analysis is used. The dependent variable Heart Failure 30-day Readmission Worse than U.S. Rate is based on adult Medicare Fee-for-Service patients hospitalized with a primary discharge diagnosis of heart failure and for which a subsequent inpatient readmission occurred within 30 days of their last discharge. One key variable found--states with a higher resident population speaking a primary language other than English at home--that is significantly associated with a decrease in probability in states ranking "worse" on heart failure 30-day readmission. Whereas, states with a higher median income, more total days of care per 1,000 Medicare enrollees, and a greater percentage of Medicare enrollees with prescription drug coverage have a greater probability for heart failure 30-day readmission to be "worse" than the U.S. national rate. Case management interventions targeting health literacy may be more effective than other factors to improve state-level hospital status on heart failure 30-day readmission. Factors such as total days of care per 1,000 Medicare enrollees and improving patient access to postdischarge medication(s) may not be as important as literacy. Interventions aimed to prevent disparities should consider higher income population groups as vulnerable for readmission.

Antimicrobial treatment failures in patients with community-acquired pneumonia: causes and prognostic implications.

PubMed

Arancibia, F; Ewig, S; Martinez, J A; Ruiz, M; Bauer, T; Marcos, M A; Mensa, J; Torres, A

2000-07-01

The aim of the study was to determine the causes and prognostic implications of antimicrobial treatment failures in patients with nonresponding and progressive life-threatening, community-acquired pneumonia. Forty-nine patients hospitalized with a presumptive diagnosis of community-acquired pneumonia during a 16-mo period, failure to respond to antimicrobial treatment, and documented repeated microbial investigation >/= 72 h after initiation of in-hospital antimicrobial treatment were recorded. A definite etiology of treatment failure could be established in 32 of 49 (65%) patients, and nine additional patients (18%) had a probable etiology. Treatment failures were mainly infectious in origin and included primary, persistent, and nosocomial infections (n = 10 [19%], 13 [24%], and 11 [20%] of causes, respectively). Definite but not probable persistent infections were mostly due to microbial resistance to the administered initial empiric antimicrobial treatment. Nosocomial infections were particularly frequent in patients with progressive pneumonia. Definite persistent infections and nosocomial infections had the highest associated mortality rates (75 and 88%, respectively). Nosocomial pneumonia was the only cause of treatment failure independently associated with death in multivariate analysis (RR, 16.7; 95% CI, 1.4 to 194.9; p = 0.03). We conclude that the detection of microbial resistance and the diagnosis of nosocomial pneumonia are the two major challenges in hospitalized patients with community-acquired pneumonia who do not respond to initial antimicrobial treatment. In order to establish these potentially life-threatening etiologies, a regular microbial reinvestigation seems mandatory for all patients presenting with antimicrobial treatment failures.

Life Goals Increase Self-regulation Among Male Patients with Alcohol Use Disorder.

PubMed

Won, Sung-Doo; Kim, Im-Yel

2018-01-24

Alcohol use disorder (AUD) has been conceptualized as a chronic self-regulation failure. The aim of this study was to examine the most probable pathways related to self-regulation among patients with AUD. In this study, a hypothetical model was proposed that focused on the relationship between risk factors (extrinsic life goals, emotion dysregulation) and protective factors (intrinsic life goals, self-control, and abstinence self-efficacy). Male patients with AUD (N = 188) were recruited from alcohol centers of four psychiatric hospitals between March 2015 and September 2015. All participants completed psychological assessments, including the Future Oriented Goals Scale (FOGS), the Alcohol Abstinence Self-Efficacy Scale (AASE), the Brief Self-Control Scale (BSCS), and the Difficulties in Emotion Regulation Scale (DERS) as well as sociodemographic characteristics. The final model was found to be a good fit to data. In testing indirect effects, it was shown that intrinsic life goals via emotion dysregulation, self-control, and alcohol abstinence self-efficacy decreased alcohol self-regulation failure. On the other hand, extrinsic life goals via these factors increased alcohol self-regulation failure. Conclusions/Importance: These results suggest that intrinsic goals might indirectly be the important and protective factors for AUD. Moreover, the findings implicate that self-regulation through goal setting may be necessary to alleviate symptoms and improve function among patients with AUD.

Initial Experience With the New Ahmed Glaucoma Valve Model M4: Short-term Results.

PubMed

Cvintal, Victor; Moster, Marlene R; Shyu, Andrew P; McDermott, Katie; Ekici, Feyzahan; Pro, Michael J; Waisbourd, Michael

2016-05-01

To evaluate the clinical outcomes of the new Ahmed glaucoma valve (AGV) model M4. The device consists of a porous polyethylene shell designed for improved tissue integration and reduced encapsulation of the plate for better intraocular pressure (IOP) control. Medical records of patients with an AGV M4 implantation between December 1, 2012 and December 31, 2013 were reviewed. The main outcome measure was surgical failure, defined as either (1) IOP<5 mm Hg or >21 mm Hg and/or <20% reduction of IOP at last follow-up visit, (2) a reoperation for glaucoma, and/or (3) loss of light perception. Seventy-five eyes of 73 patients were included. Postoperative IOP at all follow-up visits significantly decreased from a baseline IOP of 31.2 mm Hg (P<0.01). However, IOP increased significantly at 3 months (20.4 mm Hg), 6 months (19.3 mm Hg), and 12 months (20.3 mm Hg) compared with 1 month (13.8 mm Hg) postoperatively (P<0.05). At 6 months and 1 year, the cumulative probability of failure was 32% and 72%, respectively. The AGV M4 effectively reduced IOP in the first postoperative month, but IOP steadily increased thereafter. Consequently, failure rates were high after 1 year of follow-up.