Results of a Demonstration Assessment of Passive System Reliability Utilizing the Reliability Method for Passive Systems (RMPS)

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

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia

2015-04-26

Advanced small modular reactor designs include many advantageous design features such as passively driven safety systems that are arguably more reliable and cost effective relative to conventional active systems. Despite their attractiveness, a reliability assessment of passive systems can be difficult using conventional reliability methods due to the nature of passive systems. Simple deviations in boundary conditions can induce functional failures in a passive system, and intermediate or unexpected operating modes can also occur. As part of an ongoing project, Argonne National Laboratory is investigating various methodologies to address passive system reliability. The Reliability Method for Passive Systems (RMPS), amore » systematic approach for examining reliability, is one technique chosen for this analysis. This methodology is combined with the Risk-Informed Safety Margin Characterization (RISMC) approach to assess the reliability of a passive system and the impact of its associated uncertainties. For this demonstration problem, an integrated plant model of an advanced small modular pool-type sodium fast reactor with a passive reactor cavity cooling system is subjected to a station blackout using RELAP5-3D. This paper discusses important aspects of the reliability assessment, including deployment of the methodology, the uncertainty identification and quantification process, and identification of key risk metrics.« less

Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.

PubMed

Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander

2018-04-10

A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing techniques and assessment of soft computing techniques to predict reliability. The parameter considered while estimating and prediction of reliability are also discussed. This study can be used in estimation and prediction of the reliability of various instruments used in the medical system, software engineering, computer engineering and mechanical engineering also. These concepts can be applied to both software and hardware, to predict the reliability using CBSE.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks.

PubMed

Dâmaso, Antônio; Rosa, Nelson; Maciel, Paulo

2017-11-05

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

Hierarchical specification of the SIFT fault tolerant flight control system

NASA Technical Reports Server (NTRS)

Melliar-Smith, P. M.; Schwartz, R. L.

1981-01-01

The specification and mechanical verification of the Software Implemented Fault Tolerance (SIFT) flight control system is described. The methodology employed in the verification effort is discussed, and a description of the hierarchical models of the SIFT system is given. To meet the objective of NASA for the reliability of safety critical flight control systems, the SIFT computer must achieve a reliability well beyond the levels at which reliability can be actually measured. The methodology employed to demonstrate rigorously that the SIFT computer meets as reliability requirements is described. The hierarchy of design specifications from very abstract descriptions of system function down to the actual implementation is explained. The most abstract design specifications can be used to verify that the system functions correctly and with the desired reliability since almost all details of the realization were abstracted out. A succession of lower level models refine these specifications to the level of the actual implementation, and can be used to demonstrate that the implementation has the properties claimed of the abstract design specifications.

Evaluation of Scale Reliability with Binary Measures Using Latent Variable Modeling

ERIC Educational Resources Information Center

Raykov, Tenko; Dimitrov, Dimiter M.; Asparouhov, Tihomir

2010-01-01

A method for interval estimation of scale reliability with discrete data is outlined. The approach is applicable with multi-item instruments consisting of binary measures, and is developed within the latent variable modeling methodology. The procedure is useful for evaluation of consistency of single measures and of sum scores from item sets…

Evaluation of Weighted Scale Reliability and Criterion Validity: A Latent Variable Modeling Approach

ERIC Educational Resources Information Center

Raykov, Tenko

2007-01-01

A method is outlined for evaluating the reliability and criterion validity of weighted scales based on sets of unidimensional measures. The approach is developed within the framework of latent variable modeling methodology and is useful for point and interval estimation of these measurement quality coefficients in counseling and education…

Reliability and maintainability assessment factors for reliable fault-tolerant systems

NASA Technical Reports Server (NTRS)

Bavuso, S. J.

1984-01-01

A long term goal of the NASA Langley Research Center is the development of a reliability assessment methodology of sufficient power to enable the credible comparison of the stochastic attributes of one ultrareliable system design against others. This methodology, developed over a 10 year period, is a combined analytic and simulative technique. An analytic component is the Computer Aided Reliability Estimation capability, third generation, or simply CARE III. A simulative component is the Gate Logic Software Simulator capability, or GLOSS. The numerous factors that potentially have a degrading effect on system reliability and the ways in which these factors that are peculiar to highly reliable fault tolerant systems are accounted for in credible reliability assessments. Also presented are the modeling difficulties that result from their inclusion and the ways in which CARE III and GLOSS mitigate the intractability of the heretofore unworkable mathematics.

An approach to solving large reliability models

NASA Technical Reports Server (NTRS)

Boyd, Mark A.; Veeraraghavan, Malathi; Dugan, Joanne Bechta; Trivedi, Kishor S.

1988-01-01

This paper describes a unified approach to the problem of solving large realistic reliability models. The methodology integrates behavioral decomposition, state trunction, and efficient sparse matrix-based numerical methods. The use of fault trees, together with ancillary information regarding dependencies to automatically generate the underlying Markov model state space is proposed. The effectiveness of this approach is illustrated by modeling a state-of-the-art flight control system and a multiprocessor system. Nonexponential distributions for times to failure of components are assumed in the latter example. The modeling tool used for most of this analysis is HARP (the Hybrid Automated Reliability Predictor).

Reliability based design optimization: Formulations and methodologies

NASA Astrophysics Data System (ADS)

Agarwal, Harish

Modern products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modern engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Simulation based design plays an important role in designing almost any kind of automotive, aerospace, and consumer products under these competitive conditions. Single discipline simulations used for analysis are being coupled together to create complex coupled simulation tools. This investigation focuses on the development of efficient and robust methodologies for reliability based design optimization in a simulation based design environment. Original contributions of this research are the development of a novel efficient and robust unilevel methodology for reliability based design optimization, the development of an innovative decoupled reliability based design optimization methodology, the application of homotopy techniques in unilevel reliability based design optimization methodology, and the development of a new framework for reliability based design optimization under epistemic uncertainty. The unilevel methodology for reliability based design optimization is shown to be mathematically equivalent to the traditional nested formulation. Numerical test problems show that the unilevel methodology can reduce computational cost by at least 50% as compared to the nested approach. The decoupled reliability based design optimization methodology is an approximate technique to obtain consistent reliable designs at lesser computational expense. Test problems show that the methodology is computationally efficient compared to the nested approach. A framework for performing reliability based design optimization under epistemic uncertainty is also developed. A trust region managed sequential approximate optimization methodology is employed for this purpose. Results from numerical test studies indicate that the methodology can be used for performing design optimization under severe uncertainty.

Advanced reliability modeling of fault-tolerant computer-based systems

NASA Technical Reports Server (NTRS)

Bavuso, S. J.

1982-01-01

Two methodologies for the reliability assessment of fault tolerant digital computer based systems are discussed. The computer-aided reliability estimation 3 (CARE 3) and gate logic software simulation (GLOSS) are assessment technologies that were developed to mitigate a serious weakness in the design and evaluation process of ultrareliable digital systems. The weak link is based on the unavailability of a sufficiently powerful modeling technique for comparing the stochastic attributes of one system against others. Some of the more interesting attributes are reliability, system survival, safety, and mission success.

Validation of urban freeway models.

DOT National Transportation Integrated Search

2015-01-01

This report describes the methodology, data, conclusions, and enhanced models regarding the validation of two sets of models developed in the Strategic Highway Research Program 2 (SHRP 2) Reliability Project L03, Analytical Procedures for Determining...

Calculating system reliability with SRFYDO

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

Morzinski, Jerome; Anderson - Cook, Christine M; Klamann, Richard M

2010-01-01

SRFYDO is a process for estimating reliability of complex systems. Using information from all applicable sources, including full-system (flight) data, component test data, and expert (engineering) judgment, SRFYDO produces reliability estimates and predictions. It is appropriate for series systems with possibly several versions of the system which share some common components. It models reliability as a function of age and up to 2 other lifecycle (usage) covariates. Initial output from its Exploratory Data Analysis mode consists of plots and numerical summaries so that the user can check data entry and model assumptions, and help determine a final form for themore » system model. The System Reliability mode runs a complete reliability calculation using Bayesian methodology. This mode produces results that estimate reliability at the component, sub-system, and system level. The results include estimates of uncertainty, and can predict reliability at some not-too-distant time in the future. This paper presents an overview of the underlying statistical model for the analysis, discusses model assumptions, and demonstrates usage of SRFYDO.« less

Reliable design of a closed loop supply chain network under uncertainty: An interval fuzzy possibilistic chance-constrained model

NASA Astrophysics Data System (ADS)

Vahdani, Behnam; Tavakkoli-Moghaddam, Reza; Jolai, Fariborz; Baboli, Arman

2013-06-01

This article seeks to offer a systematic approach to establishing a reliable network of facilities in closed loop supply chains (CLSCs) under uncertainties. Facilities that are located in this article concurrently satisfy both traditional objective functions and reliability considerations in CLSC network designs. To attack this problem, a novel mathematical model is developed that integrates the network design decisions in both forward and reverse supply chain networks. The model also utilizes an effective reliability approach to find a robust network design. In order to make the results of this article more realistic, a CLSC for a case study in the iron and steel industry has been explored. The considered CLSC is multi-echelon, multi-facility, multi-product and multi-supplier. Furthermore, multiple facilities exist in the reverse logistics network leading to high complexities. Since the collection centres play an important role in this network, the reliability concept of these facilities is taken into consideration. To solve the proposed model, a novel interactive hybrid solution methodology is developed by combining a number of efficient solution approaches from the recent literature. The proposed solution methodology is a bi-objective interval fuzzy possibilistic chance-constraint mixed integer linear programming (BOIFPCCMILP). Finally, computational experiments are provided to demonstrate the applicability and suitability of the proposed model in a supply chain environment and to help decision makers facilitate their analyses.

Scaled CMOS Technology Reliability Users Guide

NASA Technical Reports Server (NTRS)

White, Mark

2010-01-01

The desire to assess the reliability of emerging scaled microelectronics technologies through faster reliability trials and more accurate acceleration models is the precursor for further research and experimentation in this relevant field. The effect of semiconductor scaling on microelectronics product reliability is an important aspect to the high reliability application user. From the perspective of a customer or user, who in many cases must deal with very limited, if any, manufacturer's reliability data to assess the product for a highly-reliable application, product-level testing is critical in the characterization and reliability assessment of advanced nanometer semiconductor scaling effects on microelectronics reliability. A methodology on how to accomplish this and techniques for deriving the expected product-level reliability on commercial memory products are provided.Competing mechanism theory and the multiple failure mechanism model are applied to the experimental results of scaled SDRAM products. Accelerated stress testing at multiple conditions is applied at the product level of several scaled memory products to assess the performance degradation and product reliability. Acceleration models are derived for each case. For several scaled SDRAM products, retention time degradation is studied and two distinct soft error populations are observed with each technology generation: early breakdown, characterized by randomly distributed weak bits with Weibull slope (beta)=1, and a main population breakdown with an increasing failure rate. Retention time soft error rates are calculated and a multiple failure mechanism acceleration model with parameters is derived for each technology. Defect densities are calculated and reflect a decreasing trend in the percentage of random defective bits for each successive product generation. A normalized soft error failure rate of the memory data retention time in FIT/Gb and FIT/cm2 for several scaled SDRAM generations is presented revealing a power relationship. General models describing the soft error rates across scaled product generations are presented. The analysis methodology may be applied to other scaled microelectronic products and their key parameters.

Multidisciplinary System Reliability Analysis

NASA Technical Reports Server (NTRS)

Mahadevan, Sankaran; Han, Song; Chamis, Christos C. (Technical Monitor)

2001-01-01

The objective of this study is to develop a new methodology for estimating the reliability of engineering systems that encompass multiple disciplines. The methodology is formulated in the context of the NESSUS probabilistic structural analysis code, developed under the leadership of NASA Glenn Research Center. The NESSUS code has been successfully applied to the reliability estimation of a variety of structural engineering systems. This study examines whether the features of NESSUS could be used to investigate the reliability of systems in other disciplines such as heat transfer, fluid mechanics, electrical circuits etc., without considerable programming effort specific to each discipline. In this study, the mechanical equivalence between system behavior models in different disciplines are investigated to achieve this objective. A new methodology is presented for the analysis of heat transfer, fluid flow, and electrical circuit problems using the structural analysis routines within NESSUS, by utilizing the equivalence between the computational quantities in different disciplines. This technique is integrated with the fast probability integration and system reliability techniques within the NESSUS code, to successfully compute the system reliability of multidisciplinary systems. Traditional as well as progressive failure analysis methods for system reliability estimation are demonstrated, through a numerical example of a heat exchanger system involving failure modes in structural, heat transfer and fluid flow disciplines.

Multi-Disciplinary System Reliability Analysis

NASA Technical Reports Server (NTRS)

Mahadevan, Sankaran; Han, Song

1997-01-01

The objective of this study is to develop a new methodology for estimating the reliability of engineering systems that encompass multiple disciplines. The methodology is formulated in the context of the NESSUS probabilistic structural analysis code developed under the leadership of NASA Lewis Research Center. The NESSUS code has been successfully applied to the reliability estimation of a variety of structural engineering systems. This study examines whether the features of NESSUS could be used to investigate the reliability of systems in other disciplines such as heat transfer, fluid mechanics, electrical circuits etc., without considerable programming effort specific to each discipline. In this study, the mechanical equivalence between system behavior models in different disciplines are investigated to achieve this objective. A new methodology is presented for the analysis of heat transfer, fluid flow, and electrical circuit problems using the structural analysis routines within NESSUS, by utilizing the equivalence between the computational quantities in different disciplines. This technique is integrated with the fast probability integration and system reliability techniques within the NESSUS code, to successfully compute the system reliability of multi-disciplinary systems. Traditional as well as progressive failure analysis methods for system reliability estimation are demonstrated, through a numerical example of a heat exchanger system involving failure modes in structural, heat transfer and fluid flow disciplines.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

PubMed Central

Dâmaso, Antônio; Maciel, Paulo

2017-01-01

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way. PMID:29113078

Independent predictors of reliability between full time employee-dependent acquisition of functional outcomes compared to non-full time employee-dependent methodologies: a prospective single institutional study.

PubMed

Adogwa, Owoicho; Elsamadicy, Aladine A; Cheng, Joseph; Bagley, Carlos

2016-03-01

The prospective acquisition of reliable patient-reported outcomes (PROs) measures demonstrating the effectiveness of spine surgery, or lack thereof, remains a challenge. The aims of this study are to compare the reliability of functional outcomes metrics obtained using full time employee (FTE) vs. non-FTE-dependent methodologies and to determine the independent predictors of response reliability using non FTE-dependent methodologies. One hundred and nineteen adult patients (male: 65, female: 54) undergoing one- and two-level lumbar fusions at Duke University Medical Center were enrolled in this prospective study. Enrollment criteria included available demographic, clinical and baseline functional outcomes data. All patients were administered two similar sets of baseline questionnaires-(I) phone interviews (FTE-dependent) and (II) hardcopy in clinic (patient self-survey, non-FTE-dependent). All patients had at least a two-week washout period between phone interviews and in-clinic self-surveys to minimize effect of recall. Questionnaires included Oswestry disability index (ODI) and Visual Analog Back and Leg Pain Scale (VAS-BP/LP). Reliability was assessed by the degree to which patient responses to baseline questionnaires differed between both time points. About 26.89% had a history an anxiety disorder and 28.57% reported a history of depression. At least 97.47% of patients had a High School Diploma or GED, with 49.57% attaining a 4-year college degree or post-graduate degree. 29.94% reported full-time employment and 14.28% were on disability. There was a very high correlation between baseline PRO's data captured between FTE-dependent compared to non-FTE-dependent methodologies (r=0.89). In a multivariate logistic regression model, the absence of anxiety and depression, higher levels of education (college or greater) and full-time employment, were independently associated with high response reliability using non-FTE-dependent methodologies. Our study suggests that capturing health-related quality of life data using non-FTE-dependent methodologies is highly reliable and maybe a more cost-effective alternative. Well-educated patients who are employed full-time appear to be the most reliable.

Lifetime prediction and reliability estimation methodology for Stirling-type pulse tube refrigerators by gaseous contamination accelerated degradation testing

NASA Astrophysics Data System (ADS)

Wan, Fubin; Tan, Yuanyuan; Jiang, Zhenhua; Chen, Xun; Wu, Yinong; Zhao, Peng

2017-12-01

Lifetime and reliability are the two performance parameters of premium importance for modern space Stirling-type pulse tube refrigerators (SPTRs), which are required to operate in excess of 10 years. Demonstration of these parameters provides a significant challenge. This paper proposes a lifetime prediction and reliability estimation method that utilizes accelerated degradation testing (ADT) for SPTRs related to gaseous contamination failure. The method was experimentally validated via three groups of gaseous contamination ADT. First, the performance degradation model based on mechanism of contamination failure and material outgassing characteristics of SPTRs was established. Next, a preliminary test was performed to determine whether the mechanism of contamination failure of the SPTRs during ADT is consistent with normal life testing. Subsequently, the experimental program of ADT was designed for SPTRs. Then, three groups of gaseous contamination ADT were performed at elevated ambient temperatures of 40 °C, 50 °C, and 60 °C, respectively and the estimated lifetimes of the SPTRs under normal condition were obtained through acceleration model (Arrhenius model). The results show good fitting of the degradation model with the experimental data. Finally, we obtained the reliability estimation of SPTRs through using the Weibull distribution. The proposed novel methodology enables us to take less than one year time to estimate the reliability of the SPTRs designed for more than 10 years.

Allometric scaling theory applied to FIA biomass estimation

Treesearch

David C. Chojnacky

2002-01-01

Tree biomass estimates in the Forest Inventory and Analysis (FIA) database are derived from numerous methodologies whose abundance and complexity raise questions about consistent results throughout the U.S. A new model based on allometric scaling theory ("WBE") offers simplified methodology and a theoretically sound basis for improving the reliability and...

Diagnostic accuracy and measurement sensitivity of digital models for orthodontic purposes: A systematic review.

PubMed

Rossini, Gabriele; Parrini, Simone; Castroflorio, Tommaso; Deregibus, Andrea; Debernardi, Cesare L

2016-02-01

Our objective was to assess the accuracy, validity, and reliability of measurements obtained from virtual dental study models compared with those obtained from plaster models. PubMed, PubMed Central, National Library of Medicine Medline, Embase, Cochrane Central Register of Controlled Clinical trials, Web of Knowledge, Scopus, Google Scholar, and LILACs were searched from January 2000 to November 2014. A grading system described by the Swedish Council on Technology Assessment in Health Care and the Cochrane tool for risk of bias assessment were used to rate the methodologic quality of the articles. Thirty-five relevant articles were selected. The methodologic quality was high. No significant differences were observed for most of the studies in all the measured parameters, with the exception of the American Board of Orthodontics Objective Grading System. Digital models are as reliable as traditional plaster models, with high accuracy, reliability, and reproducibility. Landmark identification, rather than the measuring device or the software, appears to be the greatest limitation. Furthermore, with their advantages in terms of cost, time, and space required, digital models could be considered the new gold standard in current practice. Copyright © 2016 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Use of Model-Based Design Methods for Enhancing Resiliency Analysis of Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Knox, Lenora A.

The most common traditional non-functional requirement analysis is reliability. With systems becoming more complex, networked, and adaptive to environmental uncertainties, system resiliency has recently become the non-functional requirement analysis of choice. Analysis of system resiliency has challenges; which include, defining resilience for domain areas, identifying resilience metrics, determining resilience modeling strategies, and understanding how to best integrate the concepts of risk and reliability into resiliency. Formal methods that integrate all of these concepts do not currently exist in specific domain areas. Leveraging RAMSoS, a model-based reliability analysis methodology for Systems of Systems (SoS), we propose an extension that accounts for resiliency analysis through evaluation of mission performance, risk, and cost using multi-criteria decision-making (MCDM) modeling and design trade study variability modeling evaluation techniques. This proposed methodology, coined RAMSoS-RESIL, is applied to a case study in the multi-agent unmanned aerial vehicle (UAV) domain to investigate the potential benefits of a mission architecture where functionality to complete a mission is disseminated across multiple UAVs (distributed) opposed to being contained in a single UAV (monolithic). The case study based research demonstrates proof of concept for the proposed model-based technique and provides sufficient preliminary evidence to conclude which architectural design (distributed vs. monolithic) is most resilient based on insight into mission resilience performance, risk, and cost in addition to the traditional analysis of reliability.

Proposed reliability cost model

NASA Technical Reports Server (NTRS)

Delionback, L. M.

1973-01-01

The research investigations which were involved in the study include: cost analysis/allocation, reliability and product assurance, forecasting methodology, systems analysis, and model-building. This is a classic example of an interdisciplinary problem, since the model-building requirements include the need for understanding and communication between technical disciplines on one hand, and the financial/accounting skill categories on the other. The systems approach is utilized within this context to establish a clearer and more objective relationship between reliability assurance and the subcategories (or subelements) that provide, or reenforce, the reliability assurance for a system. Subcategories are further subdivided as illustrated by a tree diagram. The reliability assurance elements can be seen to be potential alternative strategies, or approaches, depending on the specific goals/objectives of the trade studies. The scope was limited to the establishment of a proposed reliability cost-model format. The model format/approach is dependent upon the use of a series of subsystem-oriented CER's and sometimes possible CTR's, in devising a suitable cost-effective policy.

Comprehensive Design Reliability Activities for Aerospace Propulsion Systems

NASA Technical Reports Server (NTRS)

Christenson, R. L.; Whitley, M. R.; Knight, K. C.

2000-01-01

This technical publication describes the methodology, model, software tool, input data, and analysis result that support aerospace design reliability studies. The focus of these activities is on propulsion systems mechanical design reliability. The goal of these activities is to support design from a reliability perspective. Paralleling performance analyses in schedule and method, this requires the proper use of metrics in a validated reliability model useful for design, sensitivity, and trade studies. Design reliability analysis in this view is one of several critical design functions. A design reliability method is detailed and two example analyses are provided-one qualitative and the other quantitative. The use of aerospace and commercial data sources for quantification is discussed and sources listed. A tool that was developed to support both types of analyses is presented. Finally, special topics discussed include the development of design criteria, issues of reliability quantification, quality control, and reliability verification.

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

Grabaskas, David; Brunett, Acacia J.; Passerini, Stefano

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory (Argonne) participated in a two year collaboration to modernize and update the probabilistic risk assessment (PRA) for the PRISM sodium fast reactor. At a high level, the primary outcome of the project was the development of a next-generation PRA that is intended to enable risk-informed prioritization of safety- and reliability-focused research and development. A central Argonne task during this project was a reliability assessment of passive safety systems, which included the Reactor Vessel Auxiliary Cooling System (RVACS) and the inherent reactivity feedbacks of the metal fuel core. Both systems were examinedmore » utilizing a methodology derived from the Reliability Method for Passive Safety Functions (RMPS), with an emphasis on developing success criteria based on mechanistic system modeling while also maintaining consistency with the Fuel Damage Categories (FDCs) of the mechanistic source term assessment. This paper provides an overview of the reliability analyses of both systems, including highlights of the FMEAs, the construction of best-estimate models, uncertain parameter screening and propagation, and the quantification of system failure probability. In particular, special focus is given to the methodologies to perform the analysis of uncertainty propagation and the determination of the likelihood of violating FDC limits. Additionally, important lessons learned are also reviewed, such as optimal sampling methodologies for the discovery of low likelihood failure events and strategies for the combined treatment of aleatory and epistemic uncertainties.« less

Reliable estimates of predictive uncertainty for an Alpine catchment using a non-parametric methodology

NASA Astrophysics Data System (ADS)

Matos, José P.; Schaefli, Bettina; Schleiss, Anton J.

2017-04-01

Uncertainty affects hydrological modelling efforts from the very measurements (or forecasts) that serve as inputs to the more or less inaccurate predictions that are produced. Uncertainty is truly inescapable in hydrology and yet, due to the theoretical and technical hurdles associated with its quantification, it is at times still neglected or estimated only qualitatively. In recent years the scientific community has made a significant effort towards quantifying this hydrologic prediction uncertainty. Despite this, most of the developed methodologies can be computationally demanding, are complex from a theoretical point of view, require substantial expertise to be employed, and are constrained by a number of assumptions about the model error distribution. These assumptions limit the reliability of many methods in case of errors that show particular cases of non-normality, heteroscedasticity, or autocorrelation. The present contribution builds on a non-parametric data-driven approach that was developed for uncertainty quantification in operational (real-time) forecasting settings. The approach is based on the concept of Pareto optimality and can be used as a standalone forecasting tool or as a postprocessor. By virtue of its non-parametric nature and a general operating principle, it can be applied directly and with ease to predictions of streamflow, water stage, or even accumulated runoff. Also, it is a methodology capable of coping with high heteroscedasticity and seasonal hydrological regimes (e.g. snowmelt and rainfall driven events in the same catchment). Finally, the training and operation of the model are very fast, making it a tool particularly adapted to operational use. To illustrate its practical use, the uncertainty quantification method is coupled with a process-based hydrological model to produce statistically reliable forecasts for an Alpine catchment located in Switzerland. Results are presented and discussed in terms of their reliability and resolution.

CMOS Active Pixel Sensor Technology and Reliability Characterization Methodology

NASA Technical Reports Server (NTRS)

Chen, Yuan; Guertin, Steven M.; Pain, Bedabrata; Kayaii, Sammy

2006-01-01

This paper describes the technology, design features and reliability characterization methodology of a CMOS Active Pixel Sensor. Both overall chip reliability and pixel reliability are projected for the imagers.

Rollover risk prediction of heavy vehicles by reliability index and empirical modelling

NASA Astrophysics Data System (ADS)

Sellami, Yamine; Imine, Hocine; Boubezoul, Abderrahmane; Cadiou, Jean-Charles

2018-03-01

This paper focuses on a combination of a reliability-based approach and an empirical modelling approach for rollover risk assessment of heavy vehicles. A reliability-based warning system is developed to alert the driver to a potential rollover before entering into a bend. The idea behind the proposed methodology is to estimate the rollover risk by the probability that the vehicle load transfer ratio (LTR) exceeds a critical threshold. Accordingly, a so-called reliability index may be used as a measure to assess the vehicle safe functioning. In the reliability method, computing the maximum of LTR requires to predict the vehicle dynamics over the bend which can be in some cases an intractable problem or time-consuming. With the aim of improving the reliability computation time, an empirical model is developed to substitute the vehicle dynamics and rollover models. This is done by using the SVM (Support Vector Machines) algorithm. The preliminary obtained results demonstrate the effectiveness of the proposed approach.

A Methodology for Quantifying Certain Design Requirements During the Design Phase

NASA Technical Reports Server (NTRS)

Adams, Timothy; Rhodes, Russel

2005-01-01

A methodology for developing and balancing quantitative design requirements for safety, reliability, and maintainability has been proposed. Conceived as the basis of a more rational approach to the design of spacecraft, the methodology would also be applicable to the design of automobiles, washing machines, television receivers, or almost any other commercial product. Heretofore, it has been common practice to start by determining the requirements for reliability of elements of a spacecraft or other system to ensure a given design life for the system. Next, safety requirements are determined by assessing the total reliability of the system and adding redundant components and subsystems necessary to attain safety goals. As thus described, common practice leaves the maintainability burden to fall to chance; therefore, there is no control of recurring costs or of the responsiveness of the system. The means that have been used in assessing maintainability have been oriented toward determining the logistical sparing of components so that the components are available when needed. The process established for developing and balancing quantitative requirements for safety (S), reliability (R), and maintainability (M) derives and integrates NASA s top-level safety requirements and the controls needed to obtain program key objectives for safety and recurring cost (see figure). Being quantitative, the process conveniently uses common mathematical models. Even though the process is shown as being worked from the top down, it can also be worked from the bottom up. This process uses three math models: (1) the binomial distribution (greaterthan- or-equal-to case), (2) reliability for a series system, and (3) the Poisson distribution (less-than-or-equal-to case). The zero-fail case for the binomial distribution approximates the commonly known exponential distribution or "constant failure rate" distribution. Either model can be used. The binomial distribution was selected for modeling flexibility because it conveniently addresses both the zero-fail and failure cases. The failure case is typically used for unmanned spacecraft as with missiles.

Enhanced methods for determining operational capabilities and support costs of proposed space systems

NASA Technical Reports Server (NTRS)

Ebeling, Charles

1993-01-01

This report documents the work accomplished during the first two years of research to provide support to NASA in predicting operational and support parameters and costs of proposed space systems. The first year's research developed a methodology for deriving reliability and maintainability (R & M) parameters based upon the use of regression analysis to establish empirical relationships between performance and design specifications and corresponding mean times of failure and repair. The second year focused on enhancements to the methodology, increased scope of the model, and software improvements. This follow-on effort expands the prediction of R & M parameters and their effect on the operations and support of space transportation vehicles to include other system components such as booster rockets and external fuel tanks. It also increases the scope of the methodology and the capabilities of the model as implemented by the software. The focus is on the failure and repair of major subsystems and their impact on vehicle reliability, turn times, maintenance manpower, and repairable spares requirements. The report documents the data utilized in this study, outlines the general methodology for estimating and relating R&M parameters, presents the analyses and results of application to the initial data base, and describes the implementation of the methodology through the use of a computer model. The report concludes with a discussion on validation and a summary of the research findings and results.

A consistent modelling methodology for secondary settling tanks: a reliable numerical method.

PubMed

Bürger, Raimund; Diehl, Stefan; Farås, Sebastian; Nopens, Ingmar; Torfs, Elena

2013-01-01

The consistent modelling methodology for secondary settling tanks (SSTs) leads to a partial differential equation (PDE) of nonlinear convection-diffusion type as a one-dimensional model for the solids concentration as a function of depth and time. This PDE includes a flux that depends discontinuously on spatial position modelling hindered settling and bulk flows, a singular source term describing the feed mechanism, a degenerating term accounting for sediment compressibility, and a dispersion term for turbulence. In addition, the solution itself is discontinuous. A consistent, reliable and robust numerical method that properly handles these difficulties is presented. Many constitutive relations for hindered settling, compression and dispersion can be used within the model, allowing the user to switch on and off effects of interest depending on the modelling goal as well as investigate the suitability of certain constitutive expressions. Simulations show the effect of the dispersion term on effluent suspended solids and total sludge mass in the SST. The focus is on correct implementation whereas calibration and validation are not pursued.

Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks

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

Gearhart, Jared Lee; Kurtz, Nolan Scot

2014-09-01

The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance aremore » investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.« less

The reliability analysis of a separated, dual fail operational redundant strapdown IMU. [inertial measurement unit

NASA Technical Reports Server (NTRS)

Motyka, P.

1983-01-01

A methodology for quantitatively analyzing the reliability of redundant avionics systems, in general, and the dual, separated Redundant Strapdown Inertial Measurement Unit (RSDIMU), in particular, is presented. The RSDIMU is described and a candidate failure detection and isolation system presented. A Markov reliability model is employed. The operational states of the system are defined and the single-step state transition diagrams discussed. Graphical results, showing the impact of major system parameters on the reliability of the RSDIMU system, are presented and discussed.

Space Transportation Operations: Assessment of Methodologies and Models

NASA Technical Reports Server (NTRS)

Joglekar, Prafulla

2001-01-01

The systems design process for future space transportation involves understanding multiple variables and their effect on lifecycle metrics. Variables such as technology readiness or potential environmental impact are qualitative, while variables such as reliability, operations costs or flight rates are quantitative. In deciding what new design concepts to fund, NASA needs a methodology that would assess the sum total of all relevant qualitative and quantitative lifecycle metrics resulting from each proposed concept. The objective of this research was to review the state of operations assessment methodologies and models used to evaluate proposed space transportation systems and to develop recommendations for improving them. It was found that, compared to the models available from other sources, the operations assessment methodology recently developed at Kennedy Space Center has the potential to produce a decision support tool that will serve as the industry standard. Towards that goal, a number of areas of improvement in the Kennedy Space Center's methodology are identified.

Space Transportation Operations: Assessment of Methodologies and Models

NASA Technical Reports Server (NTRS)

Joglekar, Prafulla

2002-01-01

The systems design process for future space transportation involves understanding multiple variables and their effect on lifecycle metrics. Variables such as technology readiness or potential environmental impact are qualitative, while variables such as reliability, operations costs or flight rates are quantitative. In deciding what new design concepts to fund, NASA needs a methodology that would assess the sum total of all relevant qualitative and quantitative lifecycle metrics resulting from each proposed concept. The objective of this research was to review the state of operations assessment methodologies and models used to evaluate proposed space transportation systems and to develop recommendations for improving them. It was found that, compared to the models available from other sources, the operations assessment methodology recently developed at Kennedy Space Center has the potential to produce a decision support tool that will serve as the industry standard. Towards that goal, a number of areas of improvement in the Kennedy Space Center's methodology are identified.

Reliability and Maintainability model (RAM) user and maintenance manual. Part 2

NASA Technical Reports Server (NTRS)

Ebeling, Charles E.

1995-01-01

This report documents the procedures for utilizing and maintaining the Reliability and Maintainability Model (RAM) developed by the University of Dayton for the NASA Langley Research Center (LaRC). The RAM model predicts reliability and maintainability (R&M) parameters for conceptual space vehicles using parametric relationships between vehicle design and performance characteristics and subsystem mean time between maintenance actions (MTBM) and manhours per maintenance action (MH/MA). These parametric relationships were developed using aircraft R&M data from over thirty different military aircraft of all types. This report describes the general methodology used within the model, the execution and computational sequence, the input screens and data, the output displays and reports, and study analyses and procedures. A source listing is provided.

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.

Estimating the reliability of repeatedly measured endpoints based on linear mixed-effects models. A tutorial.

PubMed

Van der Elst, Wim; Molenberghs, Geert; Hilgers, Ralf-Dieter; Verbeke, Geert; Heussen, Nicole

2016-11-01

There are various settings in which researchers are interested in the assessment of the correlation between repeated measurements that are taken within the same subject (i.e., reliability). For example, the same rating scale may be used to assess the symptom severity of the same patients by multiple physicians, or the same outcome may be measured repeatedly over time in the same patients. Reliability can be estimated in various ways, for example, using the classical Pearson correlation or the intra-class correlation in clustered data. However, contemporary data often have a complex structure that goes well beyond the restrictive assumptions that are needed with the more conventional methods to estimate reliability. In the current paper, we propose a general and flexible modeling approach that allows for the derivation of reliability estimates, standard errors, and confidence intervals - appropriately taking hierarchies and covariates in the data into account. Our methodology is developed for continuous outcomes together with covariates of an arbitrary type. The methodology is illustrated in a case study, and a Web Appendix is provided which details the computations using the R package CorrMixed and the SAS software. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Assessing the reliability and validity of anti-tobacco attitudes/beliefs in the context of a campaign strategy.

PubMed

Arheart, Kristopher L; Sly, David F; Trapido, Edward J; Rodriguez, Richard D; Ellestad, Amy J

2004-11-01

To identify multi-item attitude/belief scales associated with the theoretical foundations of an anti-tobacco counter-marketing campaign and assess their reliability and validity. The data analyzed are from two state-wide, random, cross-sectional telephone surveys [n(S1)=1,079, n(S2)=1,150]. Items forming attitude/belief scales are identified using factor analysis. Reliability is assessed with Chronbach's alpha. Relationships among scales are explored using Pearson correlation. Validity is assessed by testing associations derived from the Centers for Disease Control and Prevention's (CDC) logic model for tobacco control program development and evaluation linking media exposure to attitudes/beliefs, and attitudes/beliefs to smoking-related behaviors. Adjusted odds ratios are employed for these analyses. Three factors emerged: traditional attitudes/beliefs about tobacco and tobacco use, tobacco industry manipulation and anti-tobacco empowerment. Reliability coefficients are in the range of 0.70 and vary little between age groups. The factors are correlated with one-another as hypothesized. Associations between media exposure and the attitude/belief scales and between these scales and behaviors are consistent with the CDC logic model. Using reliable, valid multi-item scales is theoretically and methodologically more sound than employing single-item measures of attitudes/beliefs. Methodological, theoretical and practical implications are discussed.

Reliability Centered Maintenance - Methodologies

NASA Technical Reports Server (NTRS)

Kammerer, Catherine C.

2009-01-01

Journal article about Reliability Centered Maintenance (RCM) methodologies used by United Space Alliance, LLC (USA) in support of the Space Shuttle Program at Kennedy Space Center. The USA Reliability Centered Maintenance program differs from traditional RCM programs because various methodologies are utilized to take advantage of their respective strengths for each application. Based on operational experience, USA has customized the traditional RCM methodology into a streamlined lean logic path and has implemented the use of statistical tools to drive the process. USA RCM has integrated many of the L6S tools into both RCM methodologies. The tools utilized in the Measure, Analyze, and Improve phases of a Lean Six Sigma project lend themselves to application in the RCM process. All USA RCM methodologies meet the requirements defined in SAE JA 1011, Evaluation Criteria for Reliability-Centered Maintenance (RCM) Processes. The proposed article explores these methodologies.

Seals Research at AlliedSignal

NASA Technical Reports Server (NTRS)

Ullah, M. Rifat

1996-01-01

A consortium has been formed to address seal problems in the Aerospace sector of Allied Signal, Inc. The consortium is represented by makers of Propulsion Engines, Auxiliary Power Units, Gas Turbine Starters, etc. The goal is to improve Face Seal reliability, since Face Seals have become reliability drivers in many of our product lines. Several research programs are being implemented simultaneously this year. They include: Face Seal Modeling and Analysis Methodology; Oil Cooling of Seals; Seal Tracking Dynamics; Coking Formation & Prevention; and Seal Reliability Methods.

Three-dimensional viscous design methodology for advanced technology aircraft supersonic inlet systems

NASA Technical Reports Server (NTRS)

Anderson, B. H.

1983-01-01

A broad program to develop advanced, reliable, and user oriented three-dimensional viscous design techniques for supersonic inlet systems, and encourage their transfer into the general user community is discussed. Features of the program include: (1) develop effective methods of computing three-dimensional flows within a zonal modeling methodology; (2) ensure reasonable agreement between said analysis and selective sets of benchmark validation data; (3) develop user orientation into said analysis; and (4) explore and develop advanced numerical methodology.

Developing and Validating the Socio-Technical Model in Ontology Engineering

NASA Astrophysics Data System (ADS)

Silalahi, Mesnan; Indra Sensuse, Dana; Giri Sucahyo, Yudho; Fadhilah Akmaliah, Izzah; Rahayu, Puji; Cahyaningsih, Elin

2018-03-01

This paper describes results from an attempt to develop a model in ontology engineering methodology and a way to validate the model. The approach to methodology in ontology engineering is from the point view of socio-technical system theory. Qualitative research synthesis is used to build the model using meta-ethnography. In order to ensure the objectivity of the measurement, inter-rater reliability method was applied using a multi-rater Fleiss Kappa. The results show the accordance of the research output with the diamond model in the socio-technical system theory by evidence of the interdependency of the four socio-technical variables namely people, technology, structure and task.

Ancient DNA studies: new perspectives on old samples

PubMed Central

2012-01-01

In spite of past controversies, the field of ancient DNA is now a reliable research area due to recent methodological improvements. A series of recent large-scale studies have revealed the true potential of ancient DNA samples to study the processes of evolution and to test models and assumptions commonly used to reconstruct patterns of evolution and to analyze population genetics and palaeoecological changes. Recent advances in DNA technologies, such as next-generation sequencing make it possible to recover DNA information from archaeological and paleontological remains allowing us to go back in time and study the genetic relationships between extinct organisms and their contemporary relatives. With the next-generation sequencing methodologies, DNA sequences can be retrieved even from samples (for example human remains) for which the technical pitfalls of classical methodologies required stringent criteria to guaranty the reliability of the results. In this paper, we review the methodologies applied to ancient DNA analysis and the perspectives that next-generation sequencing applications provide in this field. PMID:22697611

Developing an oropharyngeal cancer (OPC) knowledge and behaviors survey.

PubMed

Dodd, Virginia J; Riley Iii, Joseph L; Logan, Henrietta L

2012-09-01

To use the community participation research model to (1) develop a survey assessing knowledge about mouth and throat cancer and (2) field test and establish test-retest reliability with newly developed instrument. Cognitive interviews with primarily rural African American adults to assess their perception and interpretation of survey items. Test-retest reliability was established with a racially diverse rural population. Test-retest reliabilities ranged from .79 to .40 for screening awareness and .74 to .19 for knowledge. Coefficients increased for composite scores. Community participation methodology provided a culturally appropriate survey instrument that demonstrated acceptable levels of reliability.

Software reliability report

NASA Technical Reports Server (NTRS)

Wilson, Larry

1991-01-01

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Unfortunately, the models appear to be unable to account for the random nature of the data. If the same code is debugged multiple times and one of the models is used to make predictions, intolerable variance is observed in the resulting reliability predictions. It is believed that data replication can remove this variance in lab type situations and that it is less than scientific to talk about validating a software reliability model without considering replication. It is also believed that data replication may prove to be cost effective in the real world, thus the research centered on verification of the need for replication and on methodologies for generating replicated data in a cost effective manner. The context of the debugging graph was pursued by simulation and experimentation. Simulation was done for the Basic model and the Log-Poisson model. Reasonable values of the parameters were assigned and used to generate simulated data which is then processed by the models in order to determine limitations on their accuracy. These experiments exploit the existing software and program specimens which are in AIR-LAB to measure the performance of reliability models.

AMOVA ["Accumulative Manifold Validation Analysis"]: An Advanced Statistical Methodology Designed to Measure and Test the Validity, Reliability, and Overall Efficacy of Inquiry-Based Psychometric Instruments

ERIC Educational Resources Information Center

Osler, James Edward, II

2015-01-01

This monograph provides an epistemological rational for the Accumulative Manifold Validation Analysis [also referred by the acronym "AMOVA"] statistical methodology designed to test psychometric instruments. This form of inquiry is a form of mathematical optimization in the discipline of linear stochastic modelling. AMOVA is an in-depth…

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

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

Davis, J. Lynn

2017-05-31

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

A Method for Evaluating the Safety Impacts of Air Traffic Automation

NASA Technical Reports Server (NTRS)

Kostiuk, Peter; Shapiro, Gerald; Hanson, Dave; Kolitz, Stephan; Leong, Frank; Rosch, Gene; Bonesteel, Charles

1998-01-01

This report describes a methodology for analyzing the safety and operational impacts of emerging air traffic technologies. The approach integrates traditional reliability models of the system infrastructure with models that analyze the environment within which the system operates, and models of how the system responds to different scenarios. Products of the analysis include safety measures such as predicted incident rates, predicted accident statistics, and false alarm rates; and operational availability data. The report demonstrates the methodology with an analysis of the operation of the Center-TRACON Automation System at Dallas-Fort Worth International Airport.

Designing a Pedagogical Model for Web Engineering Education: An Evolutionary Perspective

ERIC Educational Resources Information Center

Hadjerrouit, Said

2005-01-01

In contrast to software engineering, which relies on relatively well established development approaches, there is a lack of a proven methodology that guides Web engineers in building reliable and effective Web-based systems. Currently, Web engineering lacks process models, architectures, suitable techniques and methods, quality assurance, and a…

Reliability Analysis of Uniaxially Ground Brittle Materials

NASA Technical Reports Server (NTRS)

Salem, Jonathan A.; Nemeth, Noel N.; Powers, Lynn M.; Choi, Sung R.

1995-01-01

The fast fracture strength distribution of uniaxially ground, alpha silicon carbide was investigated as a function of grinding angle relative to the principal stress direction in flexure. Both as-ground and ground/annealed surfaces were investigated. The resulting flexural strength distributions were used to verify reliability models and predict the strength distribution of larger plate specimens tested in biaxial flexure. Complete fractography was done on the specimens. Failures occurred from agglomerates, machining cracks, or hybrid flaws that consisted of a machining crack located at a processing agglomerate. Annealing eliminated failures due to machining damage. Reliability analyses were performed using two and three parameter Weibull and Batdorf methodologies. The Weibull size effect was demonstrated for machining flaws. Mixed mode reliability models reasonably predicted the strength distributions of uniaxial flexure and biaxial plate specimens.

Development of robust flexible OLED encapsulations using simulated estimations and experimental validations

NASA Astrophysics Data System (ADS)

Lee, Chang-Chun; Shih, Yan-Shin; Wu, Chih-Sheng; Tsai, Chia-Hao; Yeh, Shu-Tang; Peng, Yi-Hao; Chen, Kuang-Jung

2012-07-01

This work analyses the overall stress/strain characteristic of flexible encapsulations with organic light-emitting diode (OLED) devices. A robust methodology composed of a mechanical model of multi-thin film under bending loads and related stress simulations based on nonlinear finite element analysis (FEA) is proposed, and validated to be more reliable compared with related experimental data. With various geometrical combinations of cover plate, stacked thin films and plastic substrate, the position of the neutral axis (NA) plate, which is regarded as a key design parameter to minimize stress impact for the concerned OLED devices, is acquired using the present methodology. The results point out that both the thickness and mechanical properties of the cover plate help in determining the NA location. In addition, several concave and convex radii are applied to examine the reliable mechanical tolerance and to provide an insight into the estimated reliability of foldable OLED encapsulations.

Fuzzy logic modeling of high performance rechargeable batteries

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

Singh, P.; Fennie, C. Jr.; Reisner, D.E.

1998-07-01

Accurate battery state-of-charge (SOC) measurements are critical in many portable electronic device applications. Yet conventional techniques for battery SOC estimation are limited in their accuracy, reliability, and flexibility. In this paper the authors present a powerful new approach to estimate battery SOC using a fuzzy logic-based methodology. This approach provides a universally applicable, accurate method for battery SOC estimation either integrated within, or as an external monitor to, an electronic device. The methodology is demonstrated in modeling impedance measurements on Ni-MH cells and discharge voltage curves of Li-ion cells.

Appraising Healthcare Delivery Provision: A Framework to Model Business Processes.

PubMed

Luzi, Daniela; Pecoraro, Fabrizio; Tamburis, Oscar

2017-01-01

Children are dependent on a reliable healthcare system, especially for the delivery of care which crosses the primary/secondary care boundary. A methodology based on UML has been developed to capture and single out meaningful parts of the child healthcare pathways in order to facilitate comparison among 30 EU countries within the MOCHA project. A first application of this methodology has been reported considering asthma management as an example.

The determination of operational and support requirements and costs during the conceptual design of space systems

NASA Technical Reports Server (NTRS)

Ebeling, Charles

1991-01-01

The primary objective is to develop a methodology for predicting operational and support parameters and costs of proposed space systems. The first phase consists of: (1) the identification of data sources; (2) the development of a methodology for determining system reliability and maintainability parameters; (3) the implementation of the methodology through the use of prototypes; and (4) support in the development of an integrated computer model. The phase 1 results are documented and a direction is identified to proceed to accomplish the overall objective.

Reliability Modeling Methodology for Independent Approaches on Parallel Runways Safety Analysis

NASA Technical Reports Server (NTRS)

Babcock, P.; Schor, A.; Rosch, G.

1998-01-01

This document is an adjunct to the final report An Integrated Safety Analysis Methodology for Emerging Air Transport Technologies. That report presents the results of our analysis of the problem of simultaneous but independent, approaches of two aircraft on parallel runways (independent approaches on parallel runways, or IAPR). This introductory chapter presents a brief overview and perspective of approaches and methodologies for performing safety analyses for complex systems. Ensuing chapter provide the technical details that underlie the approach that we have taken in performing the safety analysis for the IAPR concept.

A decomposition model and voxel selection framework for fMRI analysis to predict neural response of visual stimuli.

PubMed

Raut, Savita V; Yadav, Dinkar M

2018-03-28

This paper presents an fMRI signal analysis methodology using geometric mean curve decomposition (GMCD) and mutual information-based voxel selection framework. Previously, the fMRI signal analysis has been conducted using empirical mean curve decomposition (EMCD) model and voxel selection on raw fMRI signal. The erstwhile methodology loses frequency component, while the latter methodology suffers from signal redundancy. Both challenges are addressed by our methodology in which the frequency component is considered by decomposing the raw fMRI signal using geometric mean rather than arithmetic mean and the voxels are selected from EMCD signal using GMCD components, rather than raw fMRI signal. The proposed methodologies are adopted for predicting the neural response. Experimentations are conducted in the openly available fMRI data of six subjects, and comparisons are made with existing decomposition models and voxel selection frameworks. Subsequently, the effect of degree of selected voxels and the selection constraints are analyzed. The comparative results and the analysis demonstrate the superiority and the reliability of the proposed methodology.

Stochastic model for fatigue crack size and cost effective design decisions. [for aerospace structures

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1975-01-01

This paper describes a methodology for making cost effective fatigue design decisions. The methodology is based on a probabilistic model for the stochastic process of fatigue crack growth with time. The development of a particular model for the stochastic process is also discussed in the paper. The model is based on the assumption of continuous time and discrete space of crack lengths. Statistical decision theory and the developed probabilistic model are used to develop the procedure for making fatigue design decisions on the basis of minimum expected cost or risk function and reliability bounds. Selections of initial flaw size distribution, NDT, repair threshold crack lengths, and inspection intervals are discussed.

Toward enhancing estimates of Kentucky's heavy truck tax liabilities.

DOT National Transportation Integrated Search

2002-08-01

The focus of this report is the effectiveness and reliability of the current models employed to calculate the weight-distance tax and fuel surtax liabilities. This report examines the current methodology utilized to estimate potential tax liabilities...

Performance-Based Service Quality Model: An Empirical Study on Japanese Universities

ERIC Educational Resources Information Center

Sultan, Parves; Wong, Ho

2010-01-01

Purpose: This paper aims to develop and empirically test the performance-based higher education service quality model. Design/methodology/approach: The study develops 67-item instrument for measuring performance-based service quality with a particular focus on the higher education sector. Scale reliability is confirmed using the Cronbach's alpha.…

A new methodology for accurate 3-dimensional coronary artery reconstruction using routine intravascular ultrasound and angiographic data: implications for widespread assessment of endothelial shear stress in humans.

PubMed

Bourantas, Christos V; Papafaklis, Michail I; Athanasiou, Lambros; Kalatzis, Fanis G; Naka, Katerina K; Siogkas, Panagiotis K; Takahashi, Saeko; Saito, Shigeru; Fotiadis, Dimitrios I; Feldman, Charles L; Stone, Peter H; Michalis, Lampros K

2013-09-01

To develop and validate a new methodology that allows accurate 3-dimensional (3-D) coronary artery reconstruction using standard, simple angiographic and intravascular ultrasound (IVUS) data acquired during routine catheterisation enabling reliable assessment of the endothelial shear stress (ESS) distribution. Twenty-two patients (22 arteries: 7 LAD; 7 LCx; 8 RCA) who underwent angiography and IVUS examination were included. The acquired data were used for 3-D reconstruction using a conventional method and a new methodology that utilised the luminal 3-D centreline to place the detected IVUS borders and anatomical landmarks to estimate their orientation. The local ESS distribution was assessed by computational fluid dynamics. In corresponding consecutive 3 mm segments, lumen, plaque and ESS measurements in the 3-D models derived by the centreline approach were highly correlated to those derived from the conventional method (r>0.98 for all). The centreline methodology had a 99.5% diagnostic accuracy for identifying segments exposed to low ESS and provided similar estimations to the conventional method for the association between the change in plaque burden and ESS (centreline method: slope= -1.65%/Pa, p=0.078; conventional method: slope= -1.64%/Pa, p=0.084; p =0.69 for difference between the two methodologies). The centreline methodology provides geometrically correct models and permits reliable ESS computation. The ability to utilise data acquired during routine coronary angiography and IVUS examination will facilitate clinical investigation of the role of local ESS patterns in the natural history of coronary atherosclerosis.

Sample size requirements for the design of reliability studies: precision consideration.

PubMed

Shieh, Gwowen

2014-09-01

In multilevel modeling, the intraclass correlation coefficient based on the one-way random-effects model is routinely employed to measure the reliability or degree of resemblance among group members. To facilitate the advocated practice of reporting confidence intervals in future reliability studies, this article presents exact sample size procedures for precise interval estimation of the intraclass correlation coefficient under various allocation and cost structures. Although the suggested approaches do not admit explicit sample size formulas and require special algorithms for carrying out iterative computations, they are more accurate than the closed-form formulas constructed from large-sample approximations with respect to the expected width and assurance probability criteria. This investigation notes the deficiency of existing methods and expands the sample size methodology for the design of reliability studies that have not previously been discussed in the literature.

Reliability of Soft Tissue Model Based Implant Surgical Guides; A Methodological Mistake.

PubMed

Sabour, Siamak; Dastjerdi, Elahe Vahid

2012-08-20

Abstract We were interested to read the paper by Maney P and colleagues published in the July 2012 issue of J Oral Implantol. The authors aimed to assess the reliability of soft tissue model based implant surgical guides reported that the accuracy was evaluated using software. 1 I found the manuscript title of Maney P, et al. incorrect and misleading. Moreover, they reported twenty-two sites (46.81%) were considered accurate (13 of 24 maxillary and 9 of 23 mandibular sites). As the authors point out in their conclusion, Soft tissue models do not always provide sufficient accuracy for implant surgical guide fabrication.Reliability (precision) and validity (accuracy) are two different methodological issues in researches. Sensitivity, specificity, PPV, NPV, likelihood ratio positive (true positive/false negative) and likelihood ratio negative (false positive/ true negative) as well as odds ratio (true results\\false results - preferably more than 50) are among the tests to evaluate the validity (accuracy) of a single test compared to a gold standard.2-4 It is not clear that the reported twenty-two sites (46.81%) which were considered accurate related to which of the above mentioned estimates for validity analysis. Reliability (repeatability or reproducibility) is being assessed by different statistical tests such as Pearson r, least square and paired t.test which all of them are among common mistakes in reliability analysis 5. Briefly, for quantitative variable Intra Class Correlation Coefficient (ICC) and for qualitative variables weighted kappa should be used with caution because kappa has its own limitation too. Regarding reliability or agreement, it is good to know that for computing kappa value, just concordant cells are being considered, whereas discordant cells should also be taking into account in order to reach a correct estimation of agreement (Weighted kappa).2-4 As a take home message, for reliability and validity analysis, appropriate tests should be applied.

Analyzing System on A Chip Single Event Upset Responses using Single Event Upset Data, Classical Reliability Models, and Space Environment Data

NASA Technical Reports Server (NTRS)

Berg, Melanie; LaBel, Kenneth; Campola, Michael; Xapsos, Michael

2017-01-01

We are investigating the application of classical reliability performance metrics combined with standard single event upset (SEU) analysis data. We expect to relate SEU behavior to system performance requirements. Our proposed methodology will provide better prediction of SEU responses in harsh radiation environments with confidence metrics. single event upset (SEU), single event effect (SEE), field programmable gate array devises (FPGAs)

A reliability evaluation methodology for memory chips for space applications when sample size is small

NASA Technical Reports Server (NTRS)

Chen, Y.; Nguyen, D.; Guertin, S.; Berstein, J.; White, M.; Menke, R.; Kayali, S.

2003-01-01

This paper presents a reliability evaluation methodology to obtain the statistical reliability information of memory chips for space applications when the test sample size needs to be kept small because of the high cost of the radiation hardness memories.

Hybrid time-variant reliability estimation for active control structures under aleatory and epistemic uncertainties

NASA Astrophysics Data System (ADS)

Wang, Lei; Xiong, Chuang; Wang, Xiaojun; Li, Yunlong; Xu, Menghui

2018-04-01

Considering that multi-source uncertainties from inherent nature as well as the external environment are unavoidable and severely affect the controller performance, the dynamic safety assessment with high confidence is of great significance for scientists and engineers. In view of this, the uncertainty quantification analysis and time-variant reliability estimation corresponding to the closed-loop control problems are conducted in this study under a mixture of random, interval, and convex uncertainties. By combining the state-space transformation and the natural set expansion, the boundary laws of controlled response histories are first confirmed with specific implementation of random items. For nonlinear cases, the collocation set methodology and fourth Rounge-Kutta algorithm are introduced as well. Enlightened by the first-passage model in random process theory as well as by the static probabilistic reliability ideas, a new definition of the hybrid time-variant reliability measurement is provided for the vibration control systems and the related solution details are further expounded. Two engineering examples are eventually presented to demonstrate the validity and applicability of the methodology developed.

Reliability analysis of repairable systems using Petri nets and vague Lambda-Tau methodology.

PubMed

Garg, Harish

2013-01-01

The main objective of the paper is to developed a methodology, named as vague Lambda-Tau, for reliability analysis of repairable systems. Petri net tool is applied to represent the asynchronous and concurrent processing of the system instead of fault tree analysis. To enhance the relevance of the reliability study, vague set theory is used for representing the failure rate and repair times instead of classical(crisp) or fuzzy set theory because vague sets are characterized by a truth membership function and false membership functions (non-membership functions) so that sum of both values is less than 1. The proposed methodology involves qualitative modeling using PN and quantitative analysis using Lambda-Tau method of solution with the basic events represented by intuitionistic fuzzy numbers of triangular membership functions. Sensitivity analysis has also been performed and the effects on system MTBF are addressed. The methodology improves the shortcomings of the existing probabilistic approaches and gives a better understanding of the system behavior through its graphical representation. The washing unit of a paper mill situated in a northern part of India, producing approximately 200 ton of paper per day, has been considered to demonstrate the proposed approach. The results may be helpful for the plant personnel for analyzing the systems' behavior and to improve their performance by adopting suitable maintenance strategies. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback

PubMed Central

Cisler, Josh M.; Bush, Keith; James, G. Andrew; Smitherman, Sonet; Kilts, Clinton D.

2015-01-01

Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD. PMID:26241958

Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback.

PubMed

Cisler, Josh M; Bush, Keith; James, G Andrew; Smitherman, Sonet; Kilts, Clinton D

2015-01-01

Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD.

A Methodology for the Development of a Reliability Database for an Advanced Reactor Probabilistic Risk Assessment

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

Grabaskas, Dave; Brunett, Acacia J.; Bucknor, Matthew

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory are currently engaged in a joint effort to modernize and develop probabilistic risk assessment (PRA) techniques for advanced non-light water reactors. At a high level the primary outcome of this project will be the development of next-generation PRA methodologies that will enable risk-informed prioritization of safety- and reliability-focused research and development, while also identifying gaps that may be resolved through additional research. A subset of this effort is the development of a reliability database (RDB) methodology to determine applicable reliability data for inclusion in the quantification of the PRA. The RDBmore » method developed during this project seeks to satisfy the requirements of the Data Analysis element of the ASME/ANS Non-LWR PRA standard. The RDB methodology utilizes a relevancy test to examine reliability data and determine whether it is appropriate to include as part of the reliability database for the PRA. The relevancy test compares three component properties to establish the level of similarity to components examined as part of the PRA. These properties include the component function, the component failure modes, and the environment/boundary conditions of the component. The relevancy test is used to gauge the quality of data found in a variety of sources, such as advanced reactor-specific databases, non-advanced reactor nuclear databases, and non-nuclear databases. The RDB also establishes the integration of expert judgment or separate reliability analysis with past reliability data. This paper provides details on the RDB methodology, and includes an example application of the RDB methodology for determining the reliability of the intermediate heat exchanger of a sodium fast reactor. The example explores a variety of reliability data sources, and assesses their applicability for the PRA of interest through the use of the relevancy test.« less

A Comparison of Two Methods of Determining Interrater Reliability

ERIC Educational Resources Information Center

Fleming, Judith A.; Taylor, Janeen McCracken; Carran, Deborah

2004-01-01

This article offers an alternative methodology for practitioners and researchers to use in establishing interrater reliability for testing purposes. The majority of studies on interrater reliability use a traditional methodology where by two raters are compared using a Pearson product-moment correlation. This traditional method of estimating…

Development of a methodology for assessing the safety of embedded software systems

NASA Technical Reports Server (NTRS)

Garrett, C. J.; Guarro, S. B.; Apostolakis, G. E.

1993-01-01

A Dynamic Flowgraph Methodology (DFM) based on an integrated approach to modeling and analyzing the behavior of software-driven embedded systems for assessing and verifying reliability and safety is discussed. DFM is based on an extension of the Logic Flowgraph Methodology to incorporate state transition models. System models which express the logic of the system in terms of causal relationships between physical variables and temporal characteristics of software modules are analyzed to determine how a certain state can be reached. This is done by developing timed fault trees which take the form of logical combinations of static trees relating the system parameters at different point in time. The resulting information concerning the hardware and software states can be used to eliminate unsafe execution paths and identify testing criteria for safety critical software functions.

A coupled stochastic inverse-management framework for dealing with nonpoint agriculture pollution under groundwater parameter uncertainty

NASA Astrophysics Data System (ADS)

Llopis-Albert, Carlos; Palacios-Marqués, Daniel; Merigó, José M.

2014-04-01

In this paper a methodology for the stochastic management of groundwater quality problems is presented, which can be used to provide agricultural advisory services. A stochastic algorithm to solve the coupled flow and mass transport inverse problem is combined with a stochastic management approach to develop methods for integrating uncertainty; thus obtaining more reliable policies on groundwater nitrate pollution control from agriculture. The stochastic inverse model allows identifying non-Gaussian parameters and reducing uncertainty in heterogeneous aquifers by constraining stochastic simulations to data. The management model determines the spatial and temporal distribution of fertilizer application rates that maximizes net benefits in agriculture constrained by quality requirements in groundwater at various control sites. The quality constraints can be taken, for instance, by those given by water laws such as the EU Water Framework Directive (WFD). Furthermore, the methodology allows providing the trade-off between higher economic returns and reliability in meeting the environmental standards. Therefore, this new technology can help stakeholders in the decision-making process under an uncertainty environment. The methodology has been successfully applied to a 2D synthetic aquifer, where an uncertainty assessment has been carried out by means of Monte Carlo simulation techniques.

Predicting operator workload during system design

NASA Technical Reports Server (NTRS)

Aldrich, Theodore B.; Szabo, Sandra M.

1988-01-01

A workload prediction methodology was developed in response to the need to measure workloads associated with operation of advanced aircraft. The application of the methodology will involve: (1) conducting mission/task analyses of critical mission segments and assigning estimates of workload for the sensory, cognitive, and psychomotor workload components of each task identified; (2) developing computer-based workload prediction models using the task analysis data; and (3) exercising the computer models to produce predictions of crew workload under varying automation and/or crew configurations. Critical issues include reliability and validity of workload predictors and selection of appropriate criterion measures.

SMART empirical approaches for predicting field performance of PV modules from results of reliability tests

NASA Astrophysics Data System (ADS)

Hardikar, Kedar Y.; Liu, Bill J. J.; Bheemreddy, Venkata

2016-09-01

Gaining an understanding of degradation mechanisms and their characterization are critical in developing relevant accelerated tests to ensure PV module performance warranty over a typical lifetime of 25 years. As newer technologies are adapted for PV, including new PV cell technologies, new packaging materials, and newer product designs, the availability of field data over extended periods of time for product performance assessment cannot be expected within the typical timeframe for business decisions. In this work, to enable product design decisions and product performance assessment for PV modules utilizing newer technologies, Simulation and Mechanism based Accelerated Reliability Testing (SMART) methodology and empirical approaches to predict field performance from accelerated test results are presented. The method is demonstrated for field life assessment of flexible PV modules based on degradation mechanisms observed in two accelerated tests, namely, Damp Heat and Thermal Cycling. The method is based on design of accelerated testing scheme with the intent to develop relevant acceleration factor models. The acceleration factor model is validated by extensive reliability testing under different conditions going beyond the established certification standards. Once the acceleration factor model is validated for the test matrix a modeling scheme is developed to predict field performance from results of accelerated testing for particular failure modes of interest. Further refinement of the model can continue as more field data becomes available. While the demonstration of the method in this work is for thin film flexible PV modules, the framework and methodology can be adapted to other PV products.

MEMS reliability: The challenge and the promise

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

Miller, W.M.; Tanner, D.M.; Miller, S.L.

1998-05-01

MicroElectroMechanical Systems (MEMS) that think, sense, act and communicate will open up a broad new array of cost effective solutions only if they prove to be sufficiently reliable. A valid reliability assessment of MEMS has three prerequisites: (1) statistical significance; (2) a technique for accelerating fundamental failure mechanisms, and (3) valid physical models to allow prediction of failures during actual use. These already exist for the microelectronics portion of such integrated systems. The challenge lies in the less well understood micromachine portions and its synergistic effects with microelectronics. This paper presents a methodology addressing these prerequisites and a description ofmore » the underlying physics of reliability for micromachines.« less

A study of the selection of microcomputer architectures to automate planetary spacecraft power systems

NASA Technical Reports Server (NTRS)

Nauda, A.

1982-01-01

Performance and reliability models of alternate microcomputer architectures as a methodology for optimizing system design were examined. A methodology for selecting an optimum microcomputer architecture for autonomous operation of planetary spacecraft power systems was developed. Various microcomputer system architectures are analyzed to determine their application to spacecraft power systems. It is suggested that no standardization formula or common set of guidelines exists which provides an optimum configuration for a given set of specifications.

Methodology for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

Cancer.gov

The HINTS is designed to produce reliable estimates at the national and regional levels. GIS maps using HINTS data have been used to provide a visual representation of possible geographic relationships in HINTS cancer-related variables.

EXPOSURE METHODOLOGIES AND SYSTEMS FOR LONG-TERM CHEMICAL CARCINOGENICITY STUDIES WITH SMALL FISH SPECIES

EPA Science Inventory

Testing waterborne chemical carcinogens in fish models requires accurate, reliable, and reproducible exposures. Because carcinogenesis is a chronic toxicological process and is often associated with prolonged latency periods, systems must accommodate lengthy in-life test periods ...

Methodology of homogeneous and non-homogeneous Markov Chains for modeling bridge element deterioration.

DOT National Transportation Integrated Search

2008-08-01

Bridge management is an important activity of transportation agencies in the US : and in many other countries. A critical aspect of bridge management is to reliably predict : the deterioration of bridge structures, so that appropriate or optimal acti...

Development and Validation of Methodology to Model Flow in Ventilation Systems Commonly Found in Nuclear Facilities. Phase I

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

Strons, Philip; Bailey, James L.; Davis, John

2016-03-01

In this work, we apply the CFD in modeling airflow and particulate transport. This modeling is then compared to field validation studies to both inform and validate the modeling assumptions. Based on the results of field tests, modeling assumptions and boundary conditions are refined and the process is repeated until the results are found to be reliable with a high level of confidence.

Model uncertainty and multimodel inference in reliability estimation within a longitudinal framework.

PubMed

Alonso, Ariel; Laenen, Annouschka

2013-05-01

Laenen, Alonso, and Molenberghs (2007) and Laenen, Alonso, Molenberghs, and Vangeneugden (2009) proposed a method to assess the reliability of rating scales in a longitudinal context. The methodology is based on hierarchical linear models, and reliability coefficients are derived from the corresponding covariance matrices. However, finding a good parsimonious model to describe complex longitudinal data is a challenging task. Frequently, several models fit the data equally well, raising the problem of model selection uncertainty. When model uncertainty is high one may resort to model averaging, where inferences are based not on one but on an entire set of models. We explored the use of different model building strategies, including model averaging, in reliability estimation. We found that the approach introduced by Laenen et al. (2007, 2009) combined with some of these strategies may yield meaningful results in the presence of high model selection uncertainty and when all models are misspecified, in so far as some of them manage to capture the most salient features of the data. Nonetheless, when all models omit prominent regularities in the data, misleading results may be obtained. The main ideas are further illustrated on a case study in which the reliability of the Hamilton Anxiety Rating Scale is estimated. Importantly, the ambit of model selection uncertainty and model averaging transcends the specific setting studied in the paper and may be of interest in other areas of psychometrics. © 2012 The British Psychological Society.

It's not that Difficult: An Interrater Reliability Study of the DSM–5 Section III Alternative Model for Personality Disorders

DOE PAGES

Garcia, Darren J.; Skadberg, Rebecca M.; Schmidt, Megan; ...

2018-03-05

The Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM–5]; American Psychiatric Association, 2013) Section III Alternative Model for Personality Disorders (AMPD) represents a novel approach to the diagnosis of personality disorder (PD). In this model, PD diagnosis requires evaluation of level of impairment in personality functioning (Criterion A) and characterization by pathological traits (Criterion B). Questions about clinical utility, complexity, and difficulty in learning and using the AMPD have been expressed in recent scholarly literature. We examined the learnability, interrater reliability, and clinical utility of the AMPD using a vignette methodology and graduate student raters. Results showed thatmore » student clinicians can learn Criterion A of the AMPD to a high level of interrater reliability and agreement with expert ratings. Interrater reliability of the 25 trait facets of the AMPD varied but showed overall acceptable levels of agreement. Examination of severity indexes of PD impairment showed the level of personality functioning (LPF) added information beyond that of global assessment of functioning (GAF). Clinical utility ratings were generally strong. Lastly, the satisfactory interrater reliability of components of the AMPD indicates the model, including the LPF, is very learnable.« less

It's not that Difficult: An Interrater Reliability Study of the DSM–5 Section III Alternative Model for Personality Disorders

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

Garcia, Darren J.; Skadberg, Rebecca M.; Schmidt, Megan

The Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM–5]; American Psychiatric Association, 2013) Section III Alternative Model for Personality Disorders (AMPD) represents a novel approach to the diagnosis of personality disorder (PD). In this model, PD diagnosis requires evaluation of level of impairment in personality functioning (Criterion A) and characterization by pathological traits (Criterion B). Questions about clinical utility, complexity, and difficulty in learning and using the AMPD have been expressed in recent scholarly literature. We examined the learnability, interrater reliability, and clinical utility of the AMPD using a vignette methodology and graduate student raters. Results showed thatmore » student clinicians can learn Criterion A of the AMPD to a high level of interrater reliability and agreement with expert ratings. Interrater reliability of the 25 trait facets of the AMPD varied but showed overall acceptable levels of agreement. Examination of severity indexes of PD impairment showed the level of personality functioning (LPF) added information beyond that of global assessment of functioning (GAF). Clinical utility ratings were generally strong. Lastly, the satisfactory interrater reliability of components of the AMPD indicates the model, including the LPF, is very learnable.« less

Superior model for fault tolerance computation in designing nano-sized circuit systems

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

Singh, N. S. S., E-mail: narinderjit@petronas.com.my; Muthuvalu, M. S., E-mail: msmuthuvalu@gmail.com; Asirvadam, V. S., E-mail: vijanth-sagayan@petronas.com.my

2014-10-24

As CMOS technology scales nano-metrically, reliability turns out to be a decisive subject in the design methodology of nano-sized circuit systems. As a result, several computational approaches have been developed to compute and evaluate reliability of desired nano-electronic circuits. The process of computing reliability becomes very troublesome and time consuming as the computational complexity build ups with the desired circuit size. Therefore, being able to measure reliability instantly and superiorly is fast becoming necessary in designing modern logic integrated circuits. For this purpose, the paper firstly looks into the development of an automated reliability evaluation tool based on the generalizationmore » of Probabilistic Gate Model (PGM) and Boolean Difference-based Error Calculator (BDEC) models. The Matlab-based tool allows users to significantly speed-up the task of reliability analysis for very large number of nano-electronic circuits. Secondly, by using the developed automated tool, the paper explores into a comparative study involving reliability computation and evaluation by PGM and, BDEC models for different implementations of same functionality circuits. Based on the reliability analysis, BDEC gives exact and transparent reliability measures, but as the complexity of the same functionality circuits with respect to gate error increases, reliability measure by BDEC tends to be lower than the reliability measure by PGM. The lesser reliability measure by BDEC is well explained in this paper using distribution of different signal input patterns overtime for same functionality circuits. Simulation results conclude that the reliability measure by BDEC depends not only on faulty gates but it also depends on circuit topology, probability of input signals being one or zero and also probability of error on signal lines.« less

Beyond annual streamflow reconstructions for the Upper Colorado River Basin: a paleo-water-balance approach

USGS Publications Warehouse

Gangopadhyay, Subhrendu; McCabe, Gregory J.; Woodhouse, Connie A.

2015-01-01

In this paper, we present a methodology to use annual tree-ring chronologies and a monthly water balance model to generate annual reconstructions of water balance variables (e.g., potential evapotrans- piration (PET), actual evapotranspiration (AET), snow water equivalent (SWE), soil moisture storage (SMS), and runoff (R)). The method involves resampling monthly temperature and precipitation from the instrumental record directed by variability indicated by the paleoclimate record. The generated time series of monthly temperature and precipitation are subsequently used as inputs to a monthly water balance model. The methodology is applied to the Upper Colorado River Basin, and results indicate that the methodology reliably simulates water-year runoff, maximum snow water equivalent, and seasonal soil moisture storage for the instrumental period. As a final application, the methodology is used to produce time series of PET, AET, SWE, SMS, and R for the 1404–1905 period for the Upper Colorado River Basin.

Probabilistic design of fibre concrete structures

NASA Astrophysics Data System (ADS)

Pukl, R.; Novák, D.; Sajdlová, T.; Lehký, D.; Červenka, J.; Červenka, V.

2017-09-01

Advanced computer simulation is recently well-established methodology for evaluation of resistance of concrete engineering structures. The nonlinear finite element analysis enables to realistically predict structural damage, peak load, failure, post-peak response, development of cracks in concrete, yielding of reinforcement, concrete crushing or shear failure. The nonlinear material models can cover various types of concrete and reinforced concrete: ordinary concrete, plain or reinforced, without or with prestressing, fibre concrete, (ultra) high performance concrete, lightweight concrete, etc. Advanced material models taking into account fibre concrete properties such as shape of tensile softening branch, high toughness and ductility are described in the paper. Since the variability of the fibre concrete material properties is rather high, the probabilistic analysis seems to be the most appropriate format for structural design and evaluation of structural performance, reliability and safety. The presented combination of the nonlinear analysis with advanced probabilistic methods allows evaluation of structural safety characterized by failure probability or by reliability index respectively. Authors offer a methodology and computer tools for realistic safety assessment of concrete structures; the utilized approach is based on randomization of the nonlinear finite element analysis of the structural model. Uncertainty of the material properties or their randomness obtained from material tests are accounted in the random distribution. Furthermore, degradation of the reinforced concrete materials such as carbonation of concrete, corrosion of reinforcement, etc. can be accounted in order to analyze life-cycle structural performance and to enable prediction of the structural reliability and safety in time development. The results can serve as a rational basis for design of fibre concrete engineering structures based on advanced nonlinear computer analysis. The presented methodology is illustrated on results from two probabilistic studies with different types of concrete structures related to practical applications and made from various materials (with the parameters obtained from real material tests).

Using Model Replication to Improve the Reliability of Agent-Based Models

NASA Astrophysics Data System (ADS)

Zhong, Wei; Kim, Yushim

The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

A Review on VSC-HVDC Reliability Modeling and Evaluation Techniques

NASA Astrophysics Data System (ADS)

Shen, L.; Tang, Q.; Li, T.; Wang, Y.; Song, F.

2017-05-01

With the fast development of power electronics, voltage-source converter (VSC) HVDC technology presents cost-effective ways for bulk power transmission. An increasing number of VSC-HVDC projects has been installed worldwide. Their reliability affects the profitability of the system and therefore has a major impact on the potential investors. In this paper, an overview of the recent advances in the area of reliability evaluation for VSC-HVDC systems is provided. Taken into account the latest multi-level converter topology, the VSC-HVDC system is categorized into several sub-systems and the reliability data for the key components is discussed based on sources with academic and industrial backgrounds. The development of reliability evaluation methodologies is reviewed and the issues surrounding the different computation approaches are briefly analysed. A general VSC-HVDC reliability evaluation procedure is illustrated in this paper.

PAI-OFF: A new proposal for online flood forecasting in flash flood prone catchments

NASA Astrophysics Data System (ADS)

Schmitz, G. H.; Cullmann, J.

2008-10-01

SummaryThe Process Modelling and Artificial Intelligence for Online Flood Forecasting (PAI-OFF) methodology combines the reliability of physically based, hydrologic/hydraulic modelling with the operational advantages of artificial intelligence. These operational advantages are extremely low computation times and straightforward operation. The basic principle of the methodology is to portray process models by means of ANN. We propose to train ANN flood forecasting models with synthetic data that reflects the possible range of storm events. To this end, establishing PAI-OFF requires first setting up a physically based hydrologic model of the considered catchment and - optionally, if backwater effects have a significant impact on the flow regime - a hydrodynamic flood routing model of the river reach in question. Both models are subsequently used for simulating all meaningful and flood relevant storm scenarios which are obtained from a catchment specific meteorological data analysis. This provides a database of corresponding input/output vectors which is then completed by generally available hydrological and meteorological data for characterizing the catchment state prior to each storm event. This database subsequently serves for training both a polynomial neural network (PoNN) - portraying the rainfall-runoff process - and a multilayer neural network (MLFN), which mirrors the hydrodynamic flood wave propagation in the river. These two ANN models replace the hydrological and hydrodynamic model in the operational mode. After presenting the theory, we apply PAI-OFF - essentially consisting of the coupled "hydrologic" PoNN and "hydrodynamic" MLFN - to the Freiberger Mulde catchment in the Erzgebirge (Ore-mountains) in East Germany (3000 km 2). Both the demonstrated computational efficiency and the prediction reliability underline the potential of the new PAI-OFF methodology for online flood forecasting.

A study on the real-time reliability of on-board equipment of train control system

NASA Astrophysics Data System (ADS)

Zhang, Yong; Li, Shiwei

2018-05-01

Real-time reliability evaluation is conducive to establishing a condition based maintenance system for the purpose of guaranteeing continuous train operation. According to the inherent characteristics of the on-board equipment, the connotation of reliability evaluation of on-board equipment is defined and the evaluation index of real-time reliability is provided in this paper. From the perspective of methodology and practical application, the real-time reliability of the on-board equipment is discussed in detail, and the method of evaluating the realtime reliability of on-board equipment at component level based on Hidden Markov Model (HMM) is proposed. In this method the performance degradation data is used directly to realize the accurate perception of the hidden state transition process of on-board equipment, which can achieve a better description of the real-time reliability of the equipment.

MoPCoM Methodology: Focus on Models of Computation

NASA Astrophysics Data System (ADS)

Koudri, Ali; Champeau, Joël; Le Lann, Jean-Christophe; Leilde, Vincent

Today, developments of Real Time Embedded Systems have to face new challenges. On the one hand, Time-To-Market constraints require a reliable development process allowing quick design space exploration. On the other hand, rapidly developing technology, as stated by Moore's law, requires techniques to handle the resulting productivity gap. In a previous paper, we have presented our Model Based Engineering methodology addressing those issues. In this paper, we make a focus on Models of Computation design and analysis. We illustrate our approach on a Cognitive Radio System development implemented on an FPGA. This work is part of the MoPCoM research project gathering academic and industrial organizations (http://www.mopcom.fr).

A Chip and Pixel Qualification Methodology on Imaging Sensors

NASA Technical Reports Server (NTRS)

Chen, Yuan; Guertin, Steven M.; Petkov, Mihail; Nguyen, Duc N.; Novak, Frank

2004-01-01

This paper presents a qualification methodology on imaging sensors. In addition to overall chip reliability characterization based on sensor s overall figure of merit, such as Dark Rate, Linearity, Dark Current Non-Uniformity, Fixed Pattern Noise and Photon Response Non-Uniformity, a simulation technique is proposed and used to project pixel reliability. The projected pixel reliability is directly related to imaging quality and provides additional sensor reliability information and performance control.

Residual stress investigation of via-last through-silicon via by polarized Raman spectroscopy measurement and finite element simulation

NASA Astrophysics Data System (ADS)

Feng, Wei; Watanabe, Naoya; Shimamoto, Haruo; Aoyagi, Masahiro; Kikuchi, Katsuya

2018-07-01

The residual stresses induced around through-silicon vias (TSVs) by a fabrication process is one of the major concerns of reliability. We proposed a methodology to investigate the residual stress in a via-last TSV. Firstly, radial and axial thermal stresses were measured by polarized Raman spectroscopy. The agreement between the simulated stress level and measured results validated the detail simulation model. Furthermore, the validated simulation model was adopted to the study of residual stress by element death/birth methods. The residual stress at room temperature concentrates at passivation layers owing to the high fabrication process temperatures of 420 °C for SiN film and 350 °C for SiO2 films. For a Si substrate, a high-level stress was observed near potential device locations, which requires attention to address reliability concerns in stress-sensitive devices. This methodology of residual stress analysis can be adopted to investigate the residual stress in other devices.

Multi-criteria decision making development of ion chromatographic method for determination of inorganic anions in oilfield waters based on artificial neural networks retention model.

PubMed

Stefanović, Stefica Cerjan; Bolanča, Tomislav; Luša, Melita; Ukić, Sime; Rogošić, Marko

2012-02-24

This paper describes the development of ad hoc methodology for determination of inorganic anions in oilfield water, since their composition often significantly differs from the average (concentration of components and/or matrix). Therefore, fast and reliable method development has to be performed in order to ensure the monitoring of desired properties under new conditions. The method development was based on computer assisted multi-criteria decision making strategy. The used criteria were: maximal value of objective functions used, maximal robustness of the separation method, minimal analysis time, and maximal retention distance between two nearest components. Artificial neural networks were used for modeling of anion retention. The reliability of developed method was extensively tested by the validation of performance characteristics. Based on validation results, the developed method shows satisfactory performance characteristics, proving the successful application of computer assisted methodology in the described case study. Copyright © 2011 Elsevier B.V. All rights reserved.

A stochastic method for stand-alone photovoltaic system sizing

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

Cabral, Claudia Valeria Tavora; Filho, Delly Oliveira; Martins, Jose Helvecio

Photovoltaic systems utilize solar energy to generate electrical energy to meet load demands. Optimal sizing of these systems includes the characterization of solar radiation. Solar radiation at the Earth's surface has random characteristics and has been the focus of various academic studies. The objective of this study was to stochastically analyze parameters involved in the sizing of photovoltaic generators and develop a methodology for sizing of stand-alone photovoltaic systems. Energy storage for isolated systems and solar radiation were analyzed stochastically due to their random behavior. For the development of the methodology proposed stochastic analysis were studied including the Markov chainmore » and beta probability density function. The obtained results were compared with those for sizing of stand-alone using from the Sandia method (deterministic), in which the stochastic model presented more reliable values. Both models present advantages and disadvantages; however, the stochastic one is more complex and provides more reliable and realistic results. (author)« less

Development of a Valid and Reliable Knee Articular Cartilage Condition-Specific Study Methodological Quality Score.

PubMed

Harris, Joshua D; Erickson, Brandon J; Cvetanovich, Gregory L; Abrams, Geoffrey D; McCormick, Frank M; Gupta, Anil K; Verma, Nikhil N; Bach, Bernard R; Cole, Brian J

2014-02-01

Condition-specific questionnaires are important components in evaluation of outcomes of surgical interventions. No condition-specific study methodological quality questionnaire exists for evaluation of outcomes of articular cartilage surgery in the knee. To develop a reliable and valid knee articular cartilage-specific study methodological quality questionnaire. Cross-sectional study. A stepwise, a priori-designed framework was created for development of a novel questionnaire. Relevant items to the topic were identified and extracted from a recent systematic review of 194 investigations of knee articular cartilage surgery. In addition, relevant items from existing generic study methodological quality questionnaires were identified. Items for a preliminary questionnaire were generated. Redundant and irrelevant items were eliminated, and acceptable items modified. The instrument was pretested and items weighed. The instrument, the MARK score (Methodological quality of ARticular cartilage studies of the Knee), was tested for validity (criterion validity) and reliability (inter- and intraobserver). A 19-item, 3-domain MARK score was developed. The 100-point scale score demonstrated face validity (focus group of 8 orthopaedic surgeons) and criterion validity (strong correlation to Cochrane Quality Assessment score and Modified Coleman Methodology Score). Interobserver reliability for the overall score was good (intraclass correlation coefficient [ICC], 0.842), and for all individual items of the MARK score, acceptable to perfect (ICC, 0.70-1.000). Intraobserver reliability ICC assessed over a 3-week interval was strong for 2 reviewers (≥0.90). The MARK score is a valid and reliable knee articular cartilage condition-specific study methodological quality instrument. This condition-specific questionnaire may be used to evaluate the quality of studies reporting outcomes of articular cartilage surgery in the knee.

Design verification of SIFT

NASA Technical Reports Server (NTRS)

Moser, Louise; Melliar-Smith, Michael; Schwartz, Richard

1987-01-01

A SIFT reliable aircraft control computer system, designed to meet the ultrahigh reliability required for safety critical flight control applications by use of processor replications and voting, was constructed for SRI, and delivered to NASA Langley for evaluation in the AIRLAB. To increase confidence in the reliability projections for SIFT, produced by a Markov reliability model, SRI constructed a formal specification, defining the meaning of reliability in the context of flight control. A further series of specifications defined, in increasing detail, the design of SIFT down to pre- and post-conditions on Pascal code procedures. Mechanically checked mathematical proofs were constructed to demonstrate that the more detailed design specifications for SIFT do indeed imply the formal reliability requirement. An additional specification defined some of the assumptions made about SIFT by the Markov model, and further proofs were constructed to show that these assumptions, as expressed by that specification, did indeed follow from the more detailed design specifications for SIFT. This report provides an outline of the methodology used for this hierarchical specification and proof, and describes the various specifications and proofs performed.

An overview of maternal separation effects on behavioural outcomes in mice: Evidence from a four-stage methodological systematic review.

PubMed

Tractenberg, Saulo G; Levandowski, Mateus L; de Azeredo, Lucas Araújo; Orso, Rodrigo; Roithmann, Laura G; Hoffmann, Emerson S; Brenhouse, Heather; Grassi-Oliveira, Rodrigo

2016-09-01

Early life stress (ELS) developmental effects have been widely studied by preclinical researchers. Despite the growing body of evidence from ELS models, such as the maternal separation paradigm, the reported results have marked inconsistencies. The maternal separation model has several methodological pitfalls that could influence the reliability of its results. Here, we critically review 94 mice studies that addressed the effects of maternal separation on behavioural outcomes. We also discuss methodological issues related to the heterogeneity of separation protocols and the quality of reporting methods. Our findings indicate a lack of consistency in maternal separation effects: major studies of behavioural and biological phenotypes failed to find significant deleterious effects. Furthermore, we identified several specific variations in separation methodological procedures. These methodological variations could contribute to the inconsistency of maternal separation effects by producing different degrees of stress exposure in maternal separation-reared pups. These methodological problems, together with insufficient reporting, might lead to inaccurate and unreliable effect estimates in maternal separation studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

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

Feng, Cong; Cui, Mingjian; Hodge, Bri-Mathias

With the growing wind penetration into the power system worldwide, improving wind power forecasting accuracy is becoming increasingly important to ensure continued economic and reliable power system operations. In this paper, a data-driven multi-model wind forecasting methodology is developed with a two-layer ensemble machine learning technique. The first layer is composed of multiple machine learning models that generate individual forecasts. A deep feature selection framework is developed to determine the most suitable inputs to the first layer machine learning models. Then, a blending algorithm is applied in the second layer to create an ensemble of the forecasts produced by firstmore » layer models and generate both deterministic and probabilistic forecasts. This two-layer model seeks to utilize the statistically different characteristics of each machine learning algorithm. A number of machine learning algorithms are selected and compared in both layers. This developed multi-model wind forecasting methodology is compared to several benchmarks. The effectiveness of the proposed methodology is evaluated to provide 1-hour-ahead wind speed forecasting at seven locations of the Surface Radiation network. Numerical results show that comparing to the single-algorithm models, the developed multi-model framework with deep feature selection procedure has improved the forecasting accuracy by up to 30%.« less

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

NASA Technical Reports Server (NTRS)

1991-01-01

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

A Framework for Reliability and Safety Analysis of Complex Space Missions

NASA Technical Reports Server (NTRS)

Evans, John W.; Groen, Frank; Wang, Lui; Austin, Rebekah; Witulski, Art; Mahadevan, Nagabhushan; Cornford, Steven L.; Feather, Martin S.; Lindsey, Nancy

2017-01-01

Long duration and complex mission scenarios are characteristics of NASA's human exploration of Mars, and will provide unprecedented challenges. Systems reliability and safety will become increasingly demanding and management of uncertainty will be increasingly important. NASA's current pioneering strategy recognizes and relies upon assurance of crew and asset safety. In this regard, flexibility to develop and innovate in the emergence of new design environments and methodologies, encompassing modeling of complex systems, is essential to meet the challenges.

Electropyroelectric technique: A methodology free of fitting procedures for thermal effusivity determination in liquids.

PubMed

Ivanov, R; Marin, E; Villa, J; Gonzalez, E; Rodríguez, C I; Olvera, J E

2015-06-01

This paper describes an alternative methodology to determine the thermal effusivity of a liquid sample using the recently proposed electropyroelectric technique, without fitting the experimental data with a theoretical model and without having to know the pyroelectric sensor related parameters, as in most previous reported approaches. The method is not absolute, because a reference liquid with known thermal properties is needed. Experiments have been performed that demonstrate the high reliability and accuracy of the method with measurement uncertainties smaller than 3%.

Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance

NASA Astrophysics Data System (ADS)

Chattopadhyaya, Pradip Kumar; Basu, Sushil Kumar; Majumdar, Manik Chandra

2017-06-01

In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence `random number simulation' is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.

Whale Hearing Models

DTIC Science & Technology

2005-06-20

methodologies and partnership projects developed under the ONR Effect of Sound in the Marine Environment (ESME) Program. The effort involved an integration...computational models to predict audiograms for these species. National Security These data will assist in designing effective noise mitigation measures and...includes marine species for which there are reliable hearing data as well as sample sources with appropriate distance effects in their renditions, including

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.

Middle Cerebral Artery Occlusion Model of Stroke in Rodents: A Step-by-Step Approach

PubMed Central

Shahjouei, Shima; Cai, Peter Y.; Ansari, Saeed; Sharififar, Sharareh; Azari, Hassan; Ganji, Sarah; Zand, Ramin

2016-01-01

Stroke is one of the leading causes of morbidity and mortality in developed countries and an immense amount of medical care resources are devoted to combat the poststroke debilitating consequences. The key to develop effective and clinically applicable treatment methodologies is a better understanding of the pathophysiology of the disease, including the root causes and targets for pharmacology. Developing these foundations requires the use of standard animal models that mimic the physicochemical process of the diseases that can reliably replicate results in order to test and fine-tune therapeutic modalities. Middle cerebral artery occlusion (MCAO), endothelin-1-induced ischemic stroke, photothrombosis, devascularization, embolization, and spontaneous infarction using hemorrhage are some examples of different animal models. Reliability of MCAO has been proved and due to the ability to induce reperfusion similar to tissue plasminogen activator (tPA) therapy, this model is widely used in preclinical studies. Here, we describe a detailed methodology on how to develop MCAO stroke in rodents using intra-arterial insertion of filament to occlude the middle cerebral artery. This approach allows for the study of a wide array of basic pathophysiology mechanisms, regenerative medicine and rehabilitation therapy. PMID:26958146

Developing a stochastic conflict resolution model for urban runoff quality management: Application of info-gap and bargaining theories

NASA Astrophysics Data System (ADS)

Ghodsi, Seyed Hamed; Kerachian, Reza; Estalaki, Siamak Malakpour; Nikoo, Mohammad Reza; Zahmatkesh, Zahra

2016-02-01

In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargaining methodologies are proposed for urban runoff quality management. In the proposed methodologies, a calibrated Storm Water Management Model (SWMM) is used to simulate stormwater runoff quantity and quality for different urban stormwater runoff management scenarios, which have been defined considering several Low Impact Development (LID) techniques. In the deterministic methodology, the best management scenario, representing location and area of LID controls, is identified using the bargaining model. In the stochastic methodology, uncertainties of some key parameters of SWMM are analyzed using the info-gap theory. For each water quality management scenario, robustness and opportuneness criteria are determined based on utility functions of different stakeholders. Then, to find the best solution, the bargaining model is performed considering a combination of robustness and opportuneness criteria for each scenario based on utility function of each stakeholder. The results of applying the proposed methodology in the Velenjak urban watershed located in the northeastern part of Tehran, the capital city of Iran, illustrate its practical utility for conflict resolution in urban water quantity and quality management. It is shown that the solution obtained using the deterministic model cannot outperform the result of the stochastic model considering the robustness and opportuneness criteria. Therefore, it can be concluded that the stochastic model, which incorporates the main uncertainties, could provide more reliable results.

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.

Canis familiaris As a Model for Non-Invasive Comparative Neuroscience.

PubMed

Bunford, Nóra; Andics, Attila; Kis, Anna; Miklósi, Ádám; Gácsi, Márta

2017-07-01

There is an ongoing need to improve animal models for investigating human behavior and its biological underpinnings. The domestic dog (Canis familiaris) is a promising model in cognitive neuroscience. However, before it can contribute to advances in this field in a comparative, reliable, and valid manner, several methodological issues warrant attention. We review recent non-invasive canine neuroscience studies, primarily focusing on (i) variability among dogs and between dogs and humans in cranial characteristics, and (ii) generalizability across dog and dog-human studies. We argue not for methodological uniformity but for functional comparability between methods, experimental designs, and neural responses. We conclude that the dog may become an innovative and unique model in comparative neuroscience, complementing more traditional models. Copyright © 2017 Elsevier Ltd. All rights reserved.

The reliability of physical examination tests for the diagnosis of anterior cruciate ligament rupture--A systematic review.

PubMed

Lange, Toni; Freiberg, Alice; Dröge, Patrik; Lützner, Jörg; Schmitt, Jochen; Kopkow, Christian

2015-06-01

Systematic literature review. Despite their frequent application in routine care, a systematic review on the reliability of clinical examination tests to evaluate the integrity of the ACL is missing. To summarize and evaluate intra- and interrater reliability research on physical examination tests used for the diagnosis of ACL tears. A comprehensive systematic literature search was conducted in MEDLINE, EMBASE and AMED until May 30th 2013. Studies were included if they assessed the intra- and/or interrater reliability of physical examination tests for the integrity of the ACL. Methodological quality was evaluated with the Quality Appraisal of Reliability Studies (QAREL) tool by two independent reviewers. 110 hits were achieved of which seven articles finally met the inclusion criteria. These studies examined the reliability of four physical examination tests. Intrarater reliability was assessed in three studies and ranged from fair to almost perfect (Cohen's k = 0.22-1.00). Interrater reliability was assessed in all included studies and ranged from slight to almost perfect (Cohen's k = 0.02-0.81). The Lachman test is the physical tests with the highest intrarater reliability (Cohen's k = 1.00), the Lachman test performed in prone position the test with the highest interrater reliability (Cohen's k = 0.81). Included studies were partly of low methodological quality. A meta-analysis could not be performed due to the heterogeneity in study populations, reliability measures and methodological quality of included studies. Systematic investigations on the reliability of physical examination tests to assess the integrity of the ACL are scarce and of varying methodological quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

Reliability-Based Stability Analysis of Rock Slopes Using Numerical Analysis and Response Surface Method

NASA Astrophysics Data System (ADS)

Dadashzadeh, N.; Duzgun, H. S. B.; Yesiloglu-Gultekin, N.

2017-08-01

While advanced numerical techniques in slope stability analysis are successfully used in deterministic studies, they have so far found limited use in probabilistic analyses due to their high computation cost. The first-order reliability method (FORM) is one of the most efficient probabilistic techniques to perform probabilistic stability analysis by considering the associated uncertainties in the analysis parameters. However, it is not possible to directly use FORM in numerical slope stability evaluations as it requires definition of a limit state performance function. In this study, an integrated methodology for probabilistic numerical modeling of rock slope stability is proposed. The methodology is based on response surface method, where FORM is used to develop an explicit performance function from the results of numerical simulations. The implementation of the proposed methodology is performed by considering a large potential rock wedge in Sumela Monastery, Turkey. The accuracy of the developed performance function to truly represent the limit state surface is evaluated by monitoring the slope behavior. The calculated probability of failure is compared with Monte Carlo simulation (MCS) method. The proposed methodology is found to be 72% more efficient than MCS, while the accuracy is decreased with an error of 24%.

Multi-Model Ensemble Wake Vortex Prediction

NASA Technical Reports Server (NTRS)

Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

2015-01-01

Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

Disturbance characteristics of half-selected cells in a cross-point resistive switching memory array

NASA Astrophysics Data System (ADS)

Chen, Zhe; Li, Haitong; Chen, Hong-Yu; Chen, Bing; Liu, Rui; Huang, Peng; Zhang, Feifei; Jiang, Zizhen; Ye, Hongfei; Gao, Bin; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng; Wong, H.-S. Philip; Yu, Shimeng

2016-05-01

Disturbance characteristics of cross-point resistive random access memory (RRAM) arrays are comprehensively studied in this paper. An analytical model is developed to quantify the number of pulses (#Pulse) the cell can bear before disturbance occurs under various sub-switching voltage stresses based on physical understanding. An evaluation methodology is proposed to assess the disturb behavior of half-selected (HS) cells in cross-point RRAM arrays by combining the analytical model and SPICE simulation. The characteristics of cross-point RRAM arrays such as energy consumption, reliable operating cycles and total error bits are evaluated by the methodology. A possible solution to mitigate disturbance is proposed.

Rater methodology for stroboscopy: a systematic review.

PubMed

Bonilha, Heather Shaw; Focht, Kendrea L; Martin-Harris, Bonnie

2015-01-01

Laryngeal endoscopy with stroboscopy (LES) remains the clinical gold standard for assessing vocal fold function. LES is used to evaluate the efficacy of voice treatments in research studies and clinical practice. LES as a voice treatment outcome tool is only as good as the clinician interpreting the recordings. Research using LES as a treatment outcome measure should be evaluated based on rater methodology and reliability. The purpose of this literature review was to evaluate the rater-related methodology from studies that use stroboscopic findings as voice treatment outcome measures. Systematic literature review. Computerized journal databases were searched for relevant articles using terms: stroboscopy and treatment. Eligible articles were categorized and evaluated for the use of rater-related methodology, reporting of number of raters, types of raters, blinding, and rater reliability. Of the 738 articles reviewed, 80 articles met inclusion criteria. More than one-third of the studies included in the review did not report the number of raters who participated in the study. Eleven studies reported results of rater reliability analysis with only two studies reporting good inter- and intrarater reliability. The comparability and use of results from treatment studies that use LES are limited by a lack of rigor in rater methodology and variable, mostly poor, inter- and intrarater reliability. To improve our ability to evaluate and use the findings from voice treatment studies that use LES features as outcome measures, greater consistency of reporting rater methodology characteristics across studies and improved rater reliability is needed. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Predicting pedestrian flow: a methodology and a proof of concept based on real-life data.

PubMed

Davidich, Maria; Köster, Gerta

2013-01-01

Building a reliable predictive model of pedestrian motion is very challenging: Ideally, such models should be based on observations made in both controlled experiments and in real-world environments. De facto, models are rarely based on real-world observations due to the lack of available data; instead, they are largely based on intuition and, at best, literature values and laboratory experiments. Such an approach is insufficient for reliable simulations of complex real-life scenarios: For instance, our analysis of pedestrian motion under natural conditions at a major German railway station reveals that the values for free-flow velocities and the flow-density relationship differ significantly from widely used literature values. It is thus necessary to calibrate and validate the model against relevant real-life data to make it capable of reproducing and predicting real-life scenarios. In this work we aim at constructing such realistic pedestrian stream simulation. Based on the analysis of real-life data, we present a methodology that identifies key parameters and interdependencies that enable us to properly calibrate the model. The success of the approach is demonstrated for a benchmark model, a cellular automaton. We show that the proposed approach significantly improves the reliability of the simulation and hence the potential prediction accuracy. The simulation is validated by comparing the local density evolution of the measured data to that of the simulated data. We find that for our model the most sensitive parameters are: the source-target distribution of the pedestrian trajectories, the schedule of pedestrian appearances in the scenario and the mean free-flow velocity. Our results emphasize the need for real-life data extraction and analysis to enable predictive simulations.

Evaluation of the HARDMAN comparability methodology for manpower, personnel and training

NASA Technical Reports Server (NTRS)

Zimmerman, W.; Butler, R.; Gray, V.; Rosenberg, L.

1984-01-01

The methodology evaluation and recommendation are part of an effort to improve Hardware versus Manpower (HARDMAN) methodology for projecting manpower, personnel, and training (MPT) to support new acquisition. Several different validity tests are employed to evaluate the methodology. The methodology conforms fairly well with both the MPT user needs and other accepted manpower modeling techniques. Audits of three completed HARDMAN applications reveal only a small number of potential problem areas compared to the total number of issues investigated. The reliability study results conform well with the problem areas uncovered through the audits. The results of the accuracy studies suggest that the manpower life-cycle cost component is only marginally sensitive to changes in other related cost variables. Even with some minor problems, the methodology seem sound and has good near term utility to the Army. Recommendations are provided to firm up the problem areas revealed through the evaluation.

AN IN VIVO MICRODIALYSIS METHOD FOR THE QUALITATIVE ANALYSIS OF HEPATIC PHASE I METABOLITES OF PHENOL IN RAINBOW TROUT (ONCORHYNCHUS MYKISS)

EPA Science Inventory

Development of reliable and accurate methodologies for determination of xenobiotic hepatic biotransformation rate and capacity parameters is important to the derivation of precise physiologically-based toxicokinetic (PB-TK) models. Biotransformation data incorporated into PB-TK m...

Methodology for the development of normative data for Spanish-speaking pediatric populations.

PubMed

Rivera, D; Arango-Lasprilla, J C

2017-01-01

To describe the methodology utilized to calculate reliability and the generation of norms for 10 neuropsychological tests for children in Spanish-speaking countries. The study sample consisted of over 4,373 healthy children from nine countries in Latin America (Chile, Cuba, Ecuador, Guatemala, Honduras, Mexico, Paraguay, Peru, and Puerto Rico) and Spain. Inclusion criteria for all countries were to have between 6 to 17 years of age, an Intelligence Quotient of≥80 on the Test of Non-Verbal Intelligence (TONI-2), and score of <19 on the Children's Depression Inventory. Participants completed 10 neuropsychological tests. Reliability and norms were calculated for all tests. Test-retest analysis showed excellent or good- reliability on all tests (r's>0.55; p's<0.001) except M-WCST perseverative errors whose coefficient magnitude was fair. All scores were normed using multiple linear regressions and standard deviations of residual values. Age, age2, sex, and mean level of parental education (MLPE) were included as predictors in the models by country. The non-significant variables (p > 0.05) were removed and the analysis were run again. This is the largest Spanish-speaking children and adolescents normative study in the world. For the generation of normative data, the method based on linear regression models and the standard deviation of residual values was used. This method allows determination of the specific variables that predict test scores, helps identify and control for collinearity of predictive variables, and generates continuous and more reliable norms than those of traditional methods.

APPLICATION OF TRAVEL TIME RELIABILITY FOR PERFORMANCE ORIENTED OPERATIONAL PLANNING OF EXPRESSWAYS

NASA Astrophysics Data System (ADS)

Mehran, Babak; Nakamura, Hideki

Evaluation of impacts of congestion improvement scheme s on travel time reliability is very significant for road authorities since travel time reliability repr esents operational performance of expressway segments. In this paper, a methodology is presented to estimate travel tim e reliability prior to implementation of congestion relief schemes based on travel time variation modeling as a function of demand, capacity, weather conditions and road accident s. For subject expressway segmen ts, traffic conditions are modeled over a whole year considering demand and capacity as random variables. Patterns of demand and capacity are generated for each five minute interval by appl ying Monte-Carlo simulation technique, and accidents are randomly generated based on a model that links acci dent rate to traffic conditions. A whole year analysis is performed by comparing de mand and available capacity for each scenario and queue length is estimated through shockwave analysis for each time in terval. Travel times are estimated from refined speed-flow relationships developed for intercity expressways and buffer time index is estimated consequently as a measure of travel time reliability. For validation, estimated reliability indices are compared with measured values from empirical data, and it is shown that the proposed method is suitable for operational evaluation and planning purposes.

Acquisition Challenge: The Importance of Incompressibility in Comparing Learning Curve Models

DTIC Science & Technology

2015-10-01

parameters for all four learning mod- els used in the study . The learning rate factor, b, is the slope of the linear regression line, which in this case is...incorporated within the DoD acquisition environment. This study tested three alternative learning models (the Stanford-B model, DeJong’s learning formula...appropriate tools to calculate accurate and reliable predictions. However, conventional learning curve methodology has been in practice since the pre

Service quality assessment of workers compensation health care delivery programs in New York using SERVQUAL.

PubMed

Arunasalam, Mark; Paulson, Albert; Wallace, William

2003-01-01

Preferred provider organizations (PPOs) provide healthcare services to an expanding proportion of the U.S. population. This paper presents a programmatic assessment of service quality in the workers' compensation environment using two different models: the PPO program model and the fee-for-service (FFS) payor model. The methodology used here will augment currently available research in workers' compensation, which has been lacking in measuring service quality determinants and assessing programmatic success/failure of managed care type programs. Results indicated that the SERVQUAL tool provided a reliable and valid clinical quality assessment tool that ascertained that PPO marketers should focus on promoting physician outreach (to show empathy) and accessibility (to show reliability) for injured workers.

A Measurement and Simulation Based Methodology for Cache Performance Modeling and Tuning

NASA Technical Reports Server (NTRS)

Waheed, Abdul; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

We present a cache performance modeling methodology that facilitates the tuning of uniprocessor cache performance for applications executing on shared memory multiprocessors by accurately predicting the effects of source code level modifications. Measurements on a single processor are initially used for identifying parts of code where cache utilization improvements may significantly impact the overall performance. Cache simulation based on trace-driven techniques can be carried out without gathering detailed address traces. Minimal runtime information for modeling cache performance of a selected code block includes: base virtual addresses of arrays, virtual addresses of variables, and loop bounds for that code block. Rest of the information is obtained from the source code. We show that the cache performance predictions are as reliable as those obtained through trace-driven simulations. This technique is particularly helpful to the exploration of various "what-if' scenarios regarding the cache performance impact for alternative code structures. We explain and validate this methodology using a simple matrix-matrix multiplication program. We then apply this methodology to predict and tune the cache performance of two realistic scientific applications taken from the Computational Fluid Dynamics (CFD) domain.

Determining minimum staffing levels during snowstorms using an integrated simulation, regression, and reliability model.

PubMed

Kunkel, Amber; McLay, Laura A

2013-03-01

Emergency medical services (EMS) provide life-saving care and hospital transport to patients with severe trauma or medical conditions. Severe weather events, such as snow events, may lead to adverse patient outcomes by increasing call volumes and service times. Adequate staffing levels during such weather events are critical for ensuring that patients receive timely care. To determine staffing levels that depend on weather, we propose a model that uses a discrete event simulation of a reliability model to identify minimum staffing levels that provide timely patient care, with regression used to provide the input parameters. The system is said to be reliable if there is a high degree of confidence that ambulances can immediately respond to a given proportion of patients (e.g., 99 %). Four weather scenarios capture varying levels of snow falling and snow on the ground. An innovative feature of our approach is that we evaluate the mitigating effects of different extrinsic response policies and intrinsic system adaptation. The models use data from Hanover County, Virginia to quantify how snow reduces EMS system reliability and necessitates increasing staffing levels. The model and its analysis can assist in EMS preparedness by providing a methodology to adjust staffing levels during weather events. A key observation is that when it is snowing, intrinsic system adaptation has similar effects on system reliability as one additional ambulance.

A reliability as an independent variable (RAIV) methodology for optimizing test planning for liquid rocket engines

NASA Astrophysics Data System (ADS)

Strunz, Richard; Herrmann, Jeffrey W.

2011-12-01

The hot fire test strategy for liquid rocket engines has always been a concern of space industry and agency alike because no recognized standard exists. Previous hot fire test plans focused on the verification of performance requirements but did not explicitly include reliability as a dimensioning variable. The stakeholders are, however, concerned about a hot fire test strategy that balances reliability, schedule, and affordability. A multiple criteria test planning model is presented that provides a framework to optimize the hot fire test strategy with respect to stakeholder concerns. The Staged Combustion Rocket Engine Demonstrator, a program of the European Space Agency, is used as example to provide the quantitative answer to the claim that a reduced thrust scale demonstrator is cost beneficial for a subsequent flight engine development. Scalability aspects of major subsystems are considered in the prior information definition inside the Bayesian framework. The model is also applied to assess the impact of an increase of the demonstrated reliability level on schedule and affordability.

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

NASA Technical Reports Server (NTRS)

Motyka, P.

1983-01-01

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

Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory

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

Kerner, Boris S.

It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliable used for control and optimization in traffic networks. It is shown that generally accepted fundamentals and methodologies of traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of traffic and transportation theory belong (i) Lighthill-Whitham-Richards (LWR) theory, (ii) the General Motors (GM) model class (formore » example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular stochastic value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of traffic and transportation theory, we discuss three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.« less

Elastic plastic fracture mechanics methodology for surface cracks

NASA Astrophysics Data System (ADS)

Ernst, Hugo A.; Boatwright, D. W.; Curtin, W. J.; Lambert, D. M.

1993-08-01

The Elastic Plastic Fracture Mechanics (EPFM) Methodology has evolved significantly in the last several years. Nevertheless, some of these concepts need to be extended further before the whole methodology can be safely applied to structural parts. Specifically, there is a need to include the effect of constraint in the characterization of material resistance to crack growth and also to extend these methods to the case of 3D defects. As a consequence, this project was started as a 36 month research program with the general objective of developing an EPFM methodology to assess the structural reliability of pressure vessels and other parts of interest to NASA containing defects. This report covers a computer modelling algorithm used to simulate the growth of a semi-elliptical surface crack; the presentation of a finite element investigation that compared the theoretical (HRR) stress field to that produced by elastic and elastic-plastic models; and experimental efforts to characterize three dimensional aspects of fracture present in 'two dimensional', or planar configuration specimens.

Elastic plastic fracture mechanics methodology for surface cracks

NASA Technical Reports Server (NTRS)

Ernst, Hugo A.; Boatwright, D. W.; Curtin, W. J.; Lambert, D. M.

1993-01-01

The Elastic Plastic Fracture Mechanics (EPFM) Methodology has evolved significantly in the last several years. Nevertheless, some of these concepts need to be extended further before the whole methodology can be safely applied to structural parts. Specifically, there is a need to include the effect of constraint in the characterization of material resistance to crack growth and also to extend these methods to the case of 3D defects. As a consequence, this project was started as a 36 month research program with the general objective of developing an EPFM methodology to assess the structural reliability of pressure vessels and other parts of interest to NASA containing defects. This report covers a computer modelling algorithm used to simulate the growth of a semi-elliptical surface crack; the presentation of a finite element investigation that compared the theoretical (HRR) stress field to that produced by elastic and elastic-plastic models; and experimental efforts to characterize three dimensional aspects of fracture present in 'two dimensional', or planar configuration specimens.

Development of Testing Methodologies for the Mechanical Properties of MEMS

NASA Technical Reports Server (NTRS)

Ekwaro-Osire, Stephen

2003-01-01

This effort is to investigate and design testing strategies to determine the mechanical properties of MicroElectroMechanical Systems (MEMS) as well as investigate the development of a MEMS Probabilistic Design Methodology (PDM). One item of potential interest is the design of a test for the Weibull size effect in pressure membranes. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. However, the primary area of investigation will most likely be analysis and modeling of material interfaces for strength as well as developing a strategy to handle stress singularities at sharp corners, filets, and material interfaces. This will be a continuation of the previous years work. The ultimate objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads.

Probabilistic sizing of laminates with uncertainties

NASA Technical Reports Server (NTRS)

Shah, A. R.; Liaw, D. G.; Chamis, C. C.

1993-01-01

A reliability based design methodology for laminate sizing and configuration for a special case of composite structures is described. The methodology combines probabilistic composite mechanics with probabilistic structural analysis. The uncertainties of constituent materials (fiber and matrix) to predict macroscopic behavior are simulated using probabilistic theory. Uncertainties in the degradation of composite material properties are included in this design methodology. A multi-factor interaction equation is used to evaluate load and environment dependent degradation of the composite material properties at the micromechanics level. The methodology is integrated into a computer code IPACS (Integrated Probabilistic Assessment of Composite Structures). Versatility of this design approach is demonstrated by performing a multi-level probabilistic analysis to size the laminates for design structural reliability of random type structures. The results show that laminate configurations can be selected to improve the structural reliability from three failures in 1000, to no failures in one million. Results also show that the laminates with the highest reliability are the least sensitive to the loading conditions.

On a methodology for robust segmentation of nonideal iris images.

PubMed

Schmid, Natalia A; Zuo, Jinyu

2010-06-01

Iris biometric is one of the most reliable biometrics with respect to performance. However, this reliability is a function of the ideality of the data. One of the most important steps in processing nonideal data is reliable and precise segmentation of the iris pattern from remaining background. In this paper, a segmentation methodology that aims at compensating various nonidealities contained in iris images during segmentation is proposed. The virtue of this methodology lies in its capability to reliably segment nonideal imagery that is simultaneously affected with such factors as specular reflection, blur, lighting variation, occlusion, and off-angle images. We demonstrate the robustness of our segmentation methodology by evaluating ideal and nonideal data sets, namely, the Chinese Academy of Sciences iris data version 3 interval subdirectory, the iris challenge evaluation data, the West Virginia University (WVU) data, and the WVU off-angle data. Furthermore, we compare our performance to that of our implementation of Camus and Wildes's algorithm and Masek's algorithm. We demonstrate considerable improvement in segmentation performance over the formerly mentioned algorithms.

The cleanroom case study in the Software Engineering Laboratory: Project description and early analysis

NASA Technical Reports Server (NTRS)

Green, Scott; Kouchakdjian, Ara; Basili, Victor; Weidow, David

1990-01-01

This case study analyzes the application of the cleanroom software development methodology to the development of production software at the NASA/Goddard Space Flight Center. The cleanroom methodology emphasizes human discipline in program verification to produce reliable software products that are right the first time. Preliminary analysis of the cleanroom case study shows that the method can be applied successfully in the FDD environment and may increase staff productivity and product quality. Compared to typical Software Engineering Laboratory (SEL) activities, there is evidence of lower failure rates, a more complete and consistent set of inline code documentation, a different distribution of phase effort activity, and a different growth profile in terms of lines of code developed. The major goals of the study were to: (1) assess the process used in the SEL cleanroom model with respect to team structure, team activities, and effort distribution; (2) analyze the products of the SEL cleanroom model and determine the impact on measures of interest, including reliability, productivity, overall life-cycle cost, and software quality; and (3) analyze the residual products in the application of the SEL cleanroom model, such as fault distribution, error characteristics, system growth, and computer usage.

A system methodology for optimization design of the structural crashworthiness of a vehicle subjected to a high-speed frontal crash

NASA Astrophysics Data System (ADS)

Xia, Liang; Liu, Weiguo; Lv, Xiaojiang; Gu, Xianguang

2018-04-01

The structural crashworthiness design of vehicles has become an important research direction to ensure the safety of the occupants. To effectively improve the structural safety of a vehicle in a frontal crash, a system methodology is presented in this study. The surrogate model of Online support vector regression (Online-SVR) is adopted to approximate crashworthiness criteria and different kernel functions are selected to enhance the accuracy of the model. The Online-SVR model is demonstrated to have the advantages of solving highly nonlinear problems and saving training costs, and can effectively be applied for vehicle structural crashworthiness design. By combining the non-dominated sorting genetic algorithm II and Monte Carlo simulation, both deterministic optimization and reliability-based design optimization (RBDO) are conducted. The optimization solutions are further validated by finite element analysis, which shows the effectiveness of the RBDO solution in the structural crashworthiness design process. The results demonstrate the advantages of using RBDO, resulting in not only increased energy absorption and decreased structural weight from a baseline design, but also a significant improvement in the reliability of the design.

Psychometric Evaluation of the D-Catch, an Instrument to Measure the Accuracy of Nursing Documentation.

PubMed

D'Agostino, Fabio; Barbaranelli, Claudio; Paans, Wolter; Belsito, Romina; Juarez Vela, Raul; Alvaro, Rosaria; Vellone, Ercole

2017-07-01

To evaluate the psychometric properties of the D-Catch instrument. A cross-sectional methodological study. Validity and reliability were estimated with confirmatory factor analysis (CFA) and internal consistency and inter-rater reliability, respectively. A sample of 250 nursing documentations was selected. CFA showed the adequacy of a 1-factor model (chronologically descriptive accuracy) with an outlier item (nursing diagnosis accuracy). Internal consistency and inter-rater reliability were adequate. The D-Catch is a valid and reliable instrument for measuring the accuracy of nursing documentation. Caution is needed when measuring diagnostic accuracy since only one item measures this dimension. The D-Catch can be used as an indicator of the accuracy of nursing documentation and the quality of nursing care. © 2015 NANDA International, Inc.

Reliability measurement for mixed mode failures of 33/11 kilovolt electric power distribution stations.

PubMed

Alwan, Faris M; Baharum, Adam; Hassan, Geehan S

2013-01-01

The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter [Formula: see text] and shape parameters [Formula: see text] and [Formula: see text]. Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models.

Reliability Measurement for Mixed Mode Failures of 33/11 Kilovolt Electric Power Distribution Stations

PubMed Central

Alwan, Faris M.; Baharum, Adam; Hassan, Geehan S.

2013-01-01

The reliability of the electrical distribution system is a contemporary research field due to diverse applications of electricity in everyday life and diverse industries. However a few research papers exist in literature. This paper proposes a methodology for assessing the reliability of 33/11 Kilovolt high-power stations based on average time between failures. The objective of this paper is to find the optimal fit for the failure data via time between failures. We determine the parameter estimation for all components of the station. We also estimate the reliability value of each component and the reliability value of the system as a whole. The best fitting distribution for the time between failures is a three parameter Dagum distribution with a scale parameter and shape parameters and . Our analysis reveals that the reliability value decreased by 38.2% in each 30 days. We believe that the current paper is the first to address this issue and its analysis. Thus, the results obtained in this research reflect its originality. We also suggest the practicality of using these results for power systems for both the maintenance of power systems models and preventive maintenance models. PMID:23936346

Mining data from hemodynamic simulations for generating prediction and explanation models.

PubMed

Bosnić, Zoran; Vračar, Petar; Radović, Milos D; Devedžić, Goran; Filipović, Nenad D; Kononenko, Igor

2012-03-01

One of the most common causes of human death is stroke, which can be caused by carotid bifurcation stenosis. In our work, we aim at proposing a prototype of a medical expert system that could significantly aid medical experts to detect hemodynamic abnormalities (increased artery wall shear stress). Based on the acquired simulated data, we apply several methodologies for1) predicting magnitudes and locations of maximum wall shear stress in the artery, 2) estimating reliability of computed predictions, and 3) providing user-friendly explanation of the model's decision. The obtained results indicate that the evaluated methodologies can provide a useful tool for the given problem domain. © 2012 IEEE

Measurement-based reliability prediction methodology. M.S. Thesis

NASA Technical Reports Server (NTRS)

Linn, Linda Shen

1991-01-01

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Hard and Soft Constraints in Reliability-Based Design Optimization

NASA Technical Reports Server (NTRS)

Crespo, L.uis G.; Giesy, Daniel P.; Kenny, Sean P.

2006-01-01

This paper proposes a framework for the analysis and design optimization of models subject to parametric uncertainty where design requirements in the form of inequality constraints are present. Emphasis is given to uncertainty models prescribed by norm bounded perturbations from a nominal parameter value and by sets of componentwise bounded uncertain variables. These models, which often arise in engineering problems, allow for a sharp mathematical manipulation. Constraints can be implemented in the hard sense, i.e., constraints must be satisfied for all parameter realizations in the uncertainty model, and in the soft sense, i.e., constraints can be violated by some realizations of the uncertain parameter. In regard to hard constraints, this methodology allows (i) to determine if a hard constraint can be satisfied for a given uncertainty model and constraint structure, (ii) to generate conclusive, formally verifiable reliability assessments that allow for unprejudiced comparisons of competing design alternatives and (iii) to identify the critical combination of uncertain parameters leading to constraint violations. In regard to soft constraints, the methodology allows the designer (i) to use probabilistic uncertainty models, (ii) to calculate upper bounds to the probability of constraint violation, and (iii) to efficiently estimate failure probabilities via a hybrid method. This method integrates the upper bounds, for which closed form expressions are derived, along with conditional sampling. In addition, an l(sub infinity) formulation for the efficient manipulation of hyper-rectangular sets is also proposed.

On Information Retrieval (IR) Systems: Revisiting Their Development, Evaluation Methodologies, and Assumptions (SIGs LAN, ED).

ERIC Educational Resources Information Center

Stirling, Keith

2000-01-01

Describes a session on information retrieval systems that planned to discuss relevance measures with Web-based information retrieval; retrieval system performance and evaluation; probabilistic independence of index terms; vector-based models; metalanguages and digital objects; how users assess the reliability, timeliness and bias of information;…

A novel integrated assessment methodology of urban water reuse.

PubMed

Listowski, A; Ngo, H H; Guo, W S; Vigneswaran, S

2011-01-01

Wastewater is no longer considered a waste product and water reuse needs to play a stronger part in securing urban water supply. Although treatment technologies for water reclamation have significantly improved the question that deserves further analysis is, how selection of a particular wastewater treatment technology relates to performance and sustainability? The proposed assessment model integrates; (i) technology, characterised by selected quantity and quality performance parameters; (ii) productivity, efficiency and reliability criteria; (iii) quantitative performance indicators; (iv) development of evaluation model. The challenges related to hierarchy and selections of performance indicators have been resolved through the case study analysis. The goal of this study is to validate a new assessment methodology in relation to performance of the microfiltration (MF) technology, a key element of the treatment process. Specific performance data and measurements were obtained at specific Control and Data Acquisition Points (CP) to satisfy the input-output inventory in relation to water resources, products, material flows, energy requirements, chemicals use, etc. Performance assessment process contains analysis and necessary linking across important parametric functions leading to reliable outcomes and results.

The determination of operational and support requirements and costs during the conceptual design of space systems

NASA Technical Reports Server (NTRS)

Ebeling, Charles; Beasley, Kenneth D.

1992-01-01

The first year of research to provide NASA support in predicting operational and support parameters and costs of proposed space systems is reported. Some of the specific research objectives were (1) to develop a methodology for deriving reliability and maintainability parameters and, based upon their estimates, determine the operational capability and support costs, and (2) to identify data sources and establish an initial data base to implement the methodology. Implementation of the methodology is accomplished through the development of a comprehensive computer model. While the model appears to work reasonably well when applied to aircraft systems, it was not accurate when used for space systems. The model is dynamic and should be updated as new data become available. It is particularly important to integrate the current aircraft data base with data obtained from the Space Shuttle and other space systems since subsystems unique to a space vehicle require data not available from aircraft. This research only addressed the major subsystems on the vehicle.

Coastal aquifer management under parameter uncertainty: Ensemble surrogate modeling based simulation-optimization

NASA Astrophysics Data System (ADS)

Janardhanan, S.; Datta, B.

2011-12-01

Surrogate models are widely used to develop computationally efficient simulation-optimization models to solve complex groundwater management problems. Artificial intelligence based models are most often used for this purpose where they are trained using predictor-predictand data obtained from a numerical simulation model. Most often this is implemented with the assumption that the parameters and boundary conditions used in the numerical simulation model are perfectly known. However, in most practical situations these values are uncertain. Under these circumstances the application of such approximation surrogates becomes limited. In our study we develop a surrogate model based coupled simulation optimization methodology for determining optimal pumping strategies for coastal aquifers considering parameter uncertainty. An ensemble surrogate modeling approach is used along with multiple realization optimization. The methodology is used to solve a multi-objective coastal aquifer management problem considering two conflicting objectives. Hydraulic conductivity and the aquifer recharge are considered as uncertain values. Three dimensional coupled flow and transport simulation model FEMWATER is used to simulate the aquifer responses for a number of scenarios corresponding to Latin hypercube samples of pumping and uncertain parameters to generate input-output patterns for training the surrogate models. Non-parametric bootstrap sampling of this original data set is used to generate multiple data sets which belong to different regions in the multi-dimensional decision and parameter space. These data sets are used to train and test multiple surrogate models based on genetic programming. The ensemble of surrogate models is then linked to a multi-objective genetic algorithm to solve the pumping optimization problem. Two conflicting objectives, viz, maximizing total pumping from beneficial wells and minimizing the total pumping from barrier wells for hydraulic control of saltwater intrusion are considered. The salinity levels resulting at strategic locations due to these pumping are predicted using the ensemble surrogates and are constrained to be within pre-specified levels. Different realizations of the concentration values are obtained from the ensemble predictions corresponding to each candidate solution of pumping. Reliability concept is incorporated as the percent of the total number of surrogate models which satisfy the imposed constraints. The methodology was applied to a realistic coastal aquifer system in Burdekin delta area in Australia. It was found that all optimal solutions corresponding to a reliability level of 0.99 satisfy all the constraints and as reducing reliability level decreases the constraint violation increases. Thus ensemble surrogate model based simulation-optimization was found to be useful in deriving multi-objective optimal pumping strategies for coastal aquifers under parameter uncertainty.

Deliberate Imagery Practice: The Reliability of Using a Retrospective Recall Methodology

ERIC Educational Resources Information Center

Cumming, Jennifer; Hall, Craig; Starkes, Janet L.

2005-01-01

This study examined the reliability of a retrospective recall methodology for providing evidence of deliberate imagery practice. A secondary purpose was to determine which imagery activities constituted the sport-specific definition of deliberate practice (Starkes, Deakin, Allard, Hodges, & Hayes, 1996). Ninety-three Canadian athletes from one…

Methodology to improve design of accelerated life tests in civil engineering projects.

PubMed

Lin, Jing; Yuan, Yongbo; Zhou, Jilai; Gao, Jie

2014-01-01

For reliability testing an Energy Expansion Tree (EET) and a companion Energy Function Model (EFM) are proposed and described in this paper. Different from conventional approaches, the EET provides a more comprehensive and objective way to systematically identify external energy factors affecting reliability. The EFM introduces energy loss into a traditional Function Model to identify internal energy sources affecting reliability. The combination creates a sound way to enumerate the energies to which a system may be exposed during its lifetime. We input these energies into planning an accelerated life test, a Multi Environment Over Stress Test. The test objective is to discover weak links and interactions among the system and the energies to which it is exposed, and design them out. As an example, the methods are applied to the pipe in subsea pipeline. However, they can be widely used in other civil engineering industries as well. The proposed method is compared with current methods.

A reliability-based cost effective fail-safe design procedure

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1976-01-01

The authors have developed a methodology for cost-effective fatigue design of structures subject to random fatigue loading. A stochastic model for fatigue crack propagation under random loading has been discussed. Fracture mechanics is then used to estimate the parameters of the model and the residual strength of structures with cracks. The stochastic model and residual strength variations have been used to develop procedures for estimating the probability of failure and its changes with inspection frequency. This information on reliability is then used to construct an objective function in terms of either a total weight function or cost function. A procedure for selecting the design variables, subject to constraints, by optimizing the objective function has been illustrated by examples. In particular, optimum design of stiffened panel has been discussed.

Chapter 15: Reliability of Wind Turbines

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

Sheng, Shuangwen; O'Connor, Ryan

The global wind industry has witnessed exciting developments in recent years. The future will be even brighter with further reductions in capital and operation and maintenance costs, which can be accomplished with improved turbine reliability, especially when turbines are installed offshore. One opportunity for the industry to improve wind turbine reliability is through the exploration of reliability engineering life data analysis based on readily available data or maintenance records collected at typical wind plants. If adopted and conducted appropriately, these analyses can quickly save operation and maintenance costs in a potentially impactful manner. This chapter discusses wind turbine reliability bymore » highlighting the methodology of reliability engineering life data analysis. It first briefly discusses fundamentals for wind turbine reliability and the current industry status. Then, the reliability engineering method for life analysis, including data collection, model development, and forecasting, is presented in detail and illustrated through two case studies. The chapter concludes with some remarks on potential opportunities to improve wind turbine reliability. An owner and operator's perspective is taken and mechanical components are used to exemplify the potential benefits of reliability engineering analysis to improve wind turbine reliability and availability.« less

Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis.

PubMed

Moreno-Conde, Alberto; Moner, David; Cruz, Wellington Dimas da; Santos, Marcelo R; Maldonado, José Alberto; Robles, Montserrat; Kalra, Dipak

2015-07-01

This systematic review aims to identify and compare the existing processes and methodologies that have been published in the literature for defining clinical information models (CIMs) that support the semantic interoperability of electronic health record (EHR) systems. Following the preferred reporting items for systematic reviews and meta-analyses systematic review methodology, the authors reviewed published papers between 2000 and 2013 that covered that semantic interoperability of EHRs, found by searching the PubMed, IEEE Xplore, and ScienceDirect databases. Additionally, after selection of a final group of articles, an inductive content analysis was done to summarize the steps and methodologies followed in order to build CIMs described in those articles. Three hundred and seventy-eight articles were screened and thirty six were selected for full review. The articles selected for full review were analyzed to extract relevant information for the analysis and characterized according to the steps the authors had followed for clinical information modeling. Most of the reviewed papers lack a detailed description of the modeling methodologies used to create CIMs. A representative example is the lack of description related to the definition of terminology bindings and the publication of the generated models. However, this systematic review confirms that most clinical information modeling activities follow very similar steps for the definition of CIMs. Having a robust and shared methodology could improve their correctness, reliability, and quality. Independently of implementation technologies and standards, it is possible to find common patterns in methods for developing CIMs, suggesting the viability of defining a unified good practice methodology to be used by any clinical information modeler. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Operations and support cost modeling of conceptual space vehicles

NASA Technical Reports Server (NTRS)

Ebeling, Charles

1994-01-01

The University of Dayton is pleased to submit this annual report to the National Aeronautics and Space Administration (NASA) Langley Research Center which documents the development of an operations and support (O&S) cost model as part of a larger life cycle cost (LCC) structure. It is intended for use during the conceptual design of new launch vehicles and spacecraft. This research is being conducted under NASA Research Grant NAG-1-1327. This research effort changes the focus from that of the first two years in which a reliability and maintainability model was developed to the initial development of an operations and support life cycle cost model. Cost categories were initially patterned after NASA's three axis work breakdown structure consisting of a configuration axis (vehicle), a function axis, and a cost axis. A revised cost element structure (CES), which is currently under study by NASA, was used to established the basic cost elements used in the model. While the focus of the effort was on operations and maintenance costs and other recurring costs, the computerized model allowed for other cost categories such as RDT&E and production costs to be addressed. Secondary tasks performed concurrent with the development of the costing model included support and upgrades to the reliability and maintainability (R&M) model. The primary result of the current research has been a methodology and a computer implementation of the methodology to provide for timely operations and support cost analysis during the conceptual design activities.

The reliability of the Glasgow Coma Scale: a systematic review.

PubMed

Reith, Florence C M; Van den Brande, Ruben; Synnot, Anneliese; Gruen, Russell; Maas, Andrew I R

2016-01-01

The Glasgow Coma Scale (GCS) provides a structured method for assessment of the level of consciousness. Its derived sum score is applied in research and adopted in intensive care unit scoring systems. Controversy exists on the reliability of the GCS. The aim of this systematic review was to summarize evidence on the reliability of the GCS. A literature search was undertaken in MEDLINE, EMBASE and CINAHL. Observational studies that assessed the reliability of the GCS, expressed by a statistical measure, were included. Methodological quality was evaluated with the consensus-based standards for the selection of health measurement instruments checklist and its influence on results considered. Reliability estimates were synthesized narratively. We identified 52 relevant studies that showed significant heterogeneity in the type of reliability estimates used, patients studied, setting and characteristics of observers. Methodological quality was good (n = 7), fair (n = 18) or poor (n = 27). In good quality studies, kappa values were ≥0.6 in 85%, and all intraclass correlation coefficients indicated excellent reliability. Poor quality studies showed lower reliability estimates. Reliability for the GCS components was higher than for the sum score. Factors that may influence reliability include education and training, the level of consciousness and type of stimuli used. Only 13% of studies were of good quality and inconsistency in reported reliability estimates was found. Although the reliability was adequate in good quality studies, further improvement is desirable. From a methodological perspective, the quality of reliability studies needs to be improved. From a clinical perspective, a renewed focus on training/education and standardization of assessment is required.

Integrated Design Methodology for Highly Reliable Liquid Rocket Engine

NASA Astrophysics Data System (ADS)

Kuratani, Naoshi; Aoki, Hiroshi; Yasui, Masaaki; Kure, Hirotaka; Masuya, Goro

The Integrated Design Methodology is strongly required at the conceptual design phase to achieve the highly reliable space transportation systems, especially the propulsion systems, not only in Japan but also all over the world in these days. Because in the past some catastrophic failures caused some losses of mission and vehicle (LOM/LOV) at the operational phase, moreover did affect severely the schedule delays and cost overrun at the later development phase. Design methodology for highly reliable liquid rocket engine is being preliminarily established and investigated in this study. The sensitivity analysis is systematically performed to demonstrate the effectiveness of this methodology, and to clarify and especially to focus on the correlation between the combustion chamber, turbopump and main valve as main components. This study describes the essential issues to understand the stated correlations, the need to apply this methodology to the remaining critical failure modes in the whole engine system, and the perspective on the engine development in the future.

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models

PubMed Central

2018-01-01

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the ‘Internet of Things’ (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds. PMID:29748521

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

Predicting the Reliability of Ceramics Under Transient Loads and Temperatures With CARES/Life

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Jadaan, Osama M.; Palfi, Tamas; Baker, Eric H.

2003-01-01

A methodology is shown for predicting the time-dependent reliability of ceramic components against catastrophic rupture when subjected to transient thermomechanical loads (including cyclic loads). The methodology takes into account the changes in material response that can occur with temperature or time (i.e., changing fatigue and Weibull parameters with temperature or time). This capability has been added to the NASA CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. The code has been modified to have the ability to interface with commercially available finite element analysis (FEA) codes executed for transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

Reliability Analysis and Reliability-Based Design Optimization of Circular Composite Cylinders Under Axial Compression

NASA Technical Reports Server (NTRS)

Rais-Rohani, Masoud

2001-01-01

This report describes the preliminary results of an investigation on component reliability analysis and reliability-based design optimization of thin-walled circular composite cylinders with average diameter and average length of 15 inches. Structural reliability is based on axial buckling strength of the cylinder. Both Monte Carlo simulation and First Order Reliability Method are considered for reliability analysis with the latter incorporated into the reliability-based structural optimization problem. To improve the efficiency of reliability sensitivity analysis and design optimization solution, the buckling strength of the cylinder is estimated using a second-order response surface model. The sensitivity of the reliability index with respect to the mean and standard deviation of each random variable is calculated and compared. The reliability index is found to be extremely sensitive to the applied load and elastic modulus of the material in the fiber direction. The cylinder diameter was found to have the third highest impact on the reliability index. Also the uncertainty in the applied load, captured by examining different values for its coefficient of variation, is found to have a large influence on cylinder reliability. The optimization problem for minimum weight is solved subject to a design constraint on element reliability index. The methodology, solution procedure and optimization results are included in this report.

Comparison of power curve monitoring methods

NASA Astrophysics Data System (ADS)

Cambron, Philippe; Masson, Christian; Tahan, Antoine; Torres, David; Pelletier, Francis

2017-11-01

Performance monitoring is an important aspect of operating wind farms. This can be done through the power curve monitoring (PCM) of wind turbines (WT). In the past years, important work has been conducted on PCM. Various methodologies have been proposed, each one with interesting results. However, it is difficult to compare these methods because they have been developed using their respective data sets. The objective of this actual work is to compare some of the proposed PCM methods using common data sets. The metric used to compare the PCM methods is the time needed to detect a change in the power curve. Two power curve models will be covered to establish the effect the model type has on the monitoring outcomes. Each model was tested with two control charts. Other methodologies and metrics proposed in the literature for power curve monitoring such as areas under the power curve and the use of statistical copulas have also been covered. Results demonstrate that model-based PCM methods are more reliable at the detecting a performance change than other methodologies and that the effectiveness of the control chart depends on the types of shift observed.

Estimation of reliability of predictions and model applicability domain evaluation in the analysis of acute toxicity (LD50).

PubMed

Sazonovas, A; Japertas, P; Didziapetris, R

2010-01-01

This study presents a new type of acute toxicity (LD(50)) prediction that enables automated assessment of the reliability of predictions (which is synonymous with the assessment of the Model Applicability Domain as defined by the Organization for Economic Cooperation and Development). Analysis involved nearly 75,000 compounds from six animal systems (acute rat toxicity after oral and intraperitoneal administration; acute mouse toxicity after oral, intraperitoneal, intravenous, and subcutaneous administration). Fragmental Partial Least Squares (PLS) with 100 bootstraps yielded baseline predictions that were automatically corrected for non-linear effects in local chemical spaces--a combination called Global, Adjusted Locally According to Similarity (GALAS) modelling methodology. Each prediction obtained in this manner is provided with a reliability index value that depends on both compound's similarity to the training set (that accounts for similar trends in LD(50) variations within multiple bootstraps) and consistency of experimental results with regard to the baseline model in the local chemical environment. The actual performance of the Reliability Index (RI) was proven by its good (and uniform) correlations with Root Mean Square Error (RMSE) in all validation sets, thus providing quantitative assessment of the Model Applicability Domain. The obtained models can be used for compound screening in the early stages of drug development and prioritization for experimental in vitro testing or later in vivo animal acute toxicity studies.

R. & D. in Psychometrics: Technical Reports on Latent Structure Models.

ERIC Educational Resources Information Center

Wilcox, Rand R.

This document contains three papers from the Methodology Project of the Center for the Study of Evaluation. Methods for characterizing test accuracy are reported in the first two papers. "Bounds on the K Out of N Reliability of a Test, and an Exact Test for Hierarchically Related Items" describes and illustrates how an extension of a…

Inclusion of Community in Self Scale: A Single-Item Pictorial Measure of Community Connectedness

ERIC Educational Resources Information Center

Mashek, Debra; Cannaday, Lisa W.; Tangney, June P.

2007-01-01

We developed a single-item pictorial measure of community connectedness, building on the theoretical and methodological traditions of the self-expansion model (Aron & Aron, 1986). The Inclusion of Community in the Self (ICS) Scale demonstrated excellent test-retest reliability, convergent validity, and discriminant validity in a sample of 190…

A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose; Kulkarni, Chetan; Biswas, Gautam; Saha, Sankalita; Goebel, Kai

2011-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Towards A Model-Based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan S.; Biswas, Gautam; Goebel, Kai

2012-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

How Root Cause Analysis Can Improve the Value Methodology

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

Wixson, James Robert

2002-05-01

Root cause analysis (RCA) is an important methodology that can be integrated with the VE Job Plan to generate superior results from the VE Methodology. The point at which RCA is most appropriate is after the function analysis and FAST Model have been built and functions for improvement have been chosen. These functions are then subjected to a simple, but, rigorous RCA to get to the root cause of their deficiencies, whether it is high cost/poor value, poor quality, or poor reliability. Once the most probable causes for these problems have been arrived at, better solutions for improvement can bemore » developed in the creativity phase because the team better understands the problems associated with these functions.« less

MASTER: a model to improve and standardize clinical breakpoints for antimicrobial susceptibility testing using forecast probabilities.

PubMed

Blöchliger, Nicolas; Keller, Peter M; Böttger, Erik C; Hombach, Michael

2017-09-01

The procedure for setting clinical breakpoints (CBPs) for antimicrobial susceptibility has been poorly standardized with respect to population data, pharmacokinetic parameters and clinical outcome. Tools to standardize CBP setting could result in improved antibiogram forecast probabilities. We propose a model to estimate probabilities for methodological categorization errors and defined zones of methodological uncertainty (ZMUs), i.e. ranges of zone diameters that cannot reliably be classified. The impact of ZMUs on methodological error rates was used for CBP optimization. The model distinguishes theoretical true inhibition zone diameters from observed diameters, which suffer from methodological variation. True diameter distributions are described with a normal mixture model. The model was fitted to observed inhibition zone diameters of clinical Escherichia coli strains. Repeated measurements for a quality control strain were used to quantify methodological variation. For 9 of 13 antibiotics analysed, our model predicted error rates of < 0.1% applying current EUCAST CBPs. Error rates were > 0.1% for ampicillin, cefoxitin, cefuroxime and amoxicillin/clavulanic acid. Increasing the susceptible CBP (cefoxitin) and introducing ZMUs (ampicillin, cefuroxime, amoxicillin/clavulanic acid) decreased error rates to < 0.1%. ZMUs contained low numbers of isolates for ampicillin and cefuroxime (3% and 6%), whereas the ZMU for amoxicillin/clavulanic acid contained 41% of all isolates and was considered not practical. We demonstrate that CBPs can be improved and standardized by minimizing methodological categorization error rates. ZMUs may be introduced if an intermediate zone is not appropriate for pharmacokinetic/pharmacodynamic or drug dosing reasons. Optimized CBPs will provide a standardized antibiotic susceptibility testing interpretation at a defined level of probability. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Rating the methodological quality of single-subject designs and n-of-1 trials: introducing the Single-Case Experimental Design (SCED) Scale.

PubMed

Tate, Robyn L; McDonald, Skye; Perdices, Michael; Togher, Leanne; Schultz, Regina; Savage, Sharon

2008-08-01

Rating scales that assess methodological quality of clinical trials provide a means to critically appraise the literature. Scales are currently available to rate randomised and non-randomised controlled trials, but there are none that assess single-subject designs. The Single-Case Experimental Design (SCED) Scale was developed for this purpose and evaluated for reliability. Six clinical researchers who were trained and experienced in rating methodological quality of clinical trials developed the scale and participated in reliability studies. The SCED Scale is an 11-item rating scale for single-subject designs, of which 10 items are used to assess methodological quality and use of statistical analysis. The scale was developed and refined over a 3-year period. Content validity was addressed by identifying items to reduce the main sources of bias in single-case methodology as stipulated by authorities in the field, which were empirically tested against 85 published reports. Inter-rater reliability was assessed using a random sample of 20/312 single-subject reports archived in the Psychological Database of Brain Impairment Treatment Efficacy (PsycBITE). Inter-rater reliability for the total score was excellent, both for individual raters (overall ICC = 0.84; 95% confidence interval 0.73-0.92) and for consensus ratings between pairs of raters (overall ICC = 0.88; 95% confidence interval 0.78-0.95). Item reliability was fair to excellent for consensus ratings between pairs of raters (range k = 0.48 to 1.00). The results were replicated with two independent novice raters who were trained in the use of the scale (ICC = 0.88, 95% confidence interval 0.73-0.95). The SCED Scale thus provides a brief and valid evaluation of methodological quality of single-subject designs, with the total score demonstrating excellent inter-rater reliability using both individual and consensus ratings. Items from the scale can also be used as a checklist in the design, reporting and critical appraisal of single-subject designs, thereby assisting to improve standards of single-case methodology.

Generalized Reliability Methodology Applied to Brittle Anisotropic Single Crystals. Degree awarded by Washington Univ., 1999

NASA Technical Reports Server (NTRS)

Salem, Jonathan A.

2002-01-01

A generalized reliability model was developed for use in the design of structural components made from brittle, homogeneous anisotropic materials such as single crystals. The model is based on the Weibull distribution and incorporates a variable strength distribution and any equivalent stress failure criteria. In addition to the reliability model, an energy based failure criterion for elastically anisotropic materials was formulated. The model is different from typical Weibull-based models in that it accounts for strength anisotropy arising from fracture toughness anisotropy and thereby allows for strength and reliability predictions of brittle, anisotropic single crystals subjected to multiaxial stresses. The model is also applicable to elastically isotropic materials exhibiting strength anisotropy due to an anisotropic distribution of flaws. In order to develop and experimentally verify the model, the uniaxial and biaxial strengths of a single crystal nickel aluminide were measured. The uniaxial strengths of the <100> and <110> crystal directions were measured in three and four-point flexure. The biaxial strength was measured by subjecting <100> plates to a uniform pressure in a test apparatus that was developed and experimentally verified. The biaxial strengths of the single crystal plates were estimated by extending and verifying the displacement solution for a circular, anisotropic plate to the case of a variable radius and thickness. The best correlation between the experimental strength data and the model predictions occurred when an anisotropic stress analysis was combined with the normal stress criterion and the strength parameters associated with the <110> crystal direction.

Reliability based design including future tests and multiagent approaches

NASA Astrophysics Data System (ADS)

Villanueva, Diane

The initial stages of reliability-based design optimization involve the formulation of objective functions and constraints, and building a model to estimate the reliability of the design with quantified uncertainties. However, even experienced hands often overlook important objective functions and constraints that affect the design. In addition, uncertainty reduction measures, such as tests and redesign, are often not considered in reliability calculations during the initial stages. This research considers two areas that concern the design of engineering systems: 1) the trade-off of the effect of a test and post-test redesign on reliability and cost and 2) the search for multiple candidate designs as insurance against unforeseen faults in some designs. In this research, a methodology was developed to estimate the effect of a single future test and post-test redesign on reliability and cost. The methodology uses assumed distributions of computational and experimental errors with re-design rules to simulate alternative future test and redesign outcomes to form a probabilistic estimate of the reliability and cost for a given design. Further, it was explored how modeling a future test and redesign provides a company an opportunity to balance development costs versus performance by simultaneously designing the design and the post-test redesign rules during the initial design stage. The second area of this research considers the use of dynamic local surrogates, or surrogate-based agents, to locate multiple candidate designs. Surrogate-based global optimization algorithms often require search in multiple candidate regions of design space, expending most of the computation needed to define multiple alternate designs. Thus, focusing on solely locating the best design may be wasteful. We extended adaptive sampling surrogate techniques to locate multiple optima by building local surrogates in sub-regions of the design space to identify optima. The efficiency of this method was studied, and the method was compared to other surrogate-based optimization methods that aim to locate the global optimum using two two-dimensional test functions, a six-dimensional test function, and a five-dimensional engineering example.

Modelling Single Tree Structure with Terrestrial Laser Scanner

NASA Astrophysics Data System (ADS)

Yurtseven, H.; Akgül, M.; Gülci, S.

2017-11-01

Recent technological developments, which has reliable accuracy and quality for all engineering works, such as remote sensing tools have wide range use in forestry applications. Last decade, sustainable use and management opportunities of forest resources are favorite topics. Thus, precision of obtained data plays an important role in evaluation of current status of forests' value. The use of aerial and terrestrial laser technology has more reliable and effective models to advance the appropriate natural resource management. This study investigates the use of terrestrial laser scanner (TLS) technology in forestry, and also the methodological data processing stages for tree volume extraction is explained. Z+F Imager 5010C TLS system was used for measure single tree information such as tree height, diameter of breast height, branch volume and canopy closure. In this context more detailed and accurate data can be obtained than conventional inventory sampling in forestry by using TLS systems. However the accuracy of obtained data is up to the experiences of TLS operator in the field. Number of scan stations and its positions are other important factors to reduce noise effect and accurate 3D modelling. The results indicated that the use of point cloud data to extract tree information for forestry applications are promising methodology for precision forestry.

Efficient free energy calculations of quantum systems through computer simulations

NASA Astrophysics Data System (ADS)

Antonelli, Alex; Ramirez, Rafael; Herrero, Carlos; Hernandez, Eduardo

2009-03-01

In general, the classical limit is assumed in computer simulation calculations of free energy. This approximation, however, is not justifiable for a class of systems in which quantum contributions for the free energy cannot be neglected. The inclusion of quantum effects is important for the determination of reliable phase diagrams of these systems. In this work, we present a new methodology to compute the free energy of many-body quantum systems [1]. This methodology results from the combination of the path integral formulation of statistical mechanics and efficient non-equilibrium methods to estimate free energy, namely, the adiabatic switching and reversible scaling methods. A quantum Einstein crystal is used as a model to show the accuracy and reliability the methodology. This new method is applied to the calculation of solid-liquid coexistence properties of neon. Our findings indicate that quantum contributions to properties such as, melting point, latent heat of fusion, entropy of fusion, and slope of melting line can be up to 10% of the calculated values using the classical approximation. [1] R. M. Ramirez, C. P. Herrero, A. Antonelli, and E. R. Hernández, Journal of Chemical Physics 129, 064110 (2008)

Integrated HTA-FMEA/FMECA methodology for the evaluation of robotic system in urology and general surgery.

PubMed

Frosini, Francesco; Miniati, Roberto; Grillone, Saverio; Dori, Fabrizio; Gentili, Guido Biffi; Belardinelli, Andrea

2016-11-14

The following study proposes and tests an integrated methodology involving Health Technology Assessment (HTA) and Failure Modes, Effects and Criticality Analysis (FMECA) for the assessment of specific aspects related to robotic surgery involving safety, process and technology. The integrated methodology consists of the application of specific techniques coming from the HTA joined to the aid of the most typical models from reliability engineering such as FMEA/FMECA. The study has also included in-site data collection and interviews to medical personnel. The total number of robotic procedures included in the analysis was 44: 28 for urology and 16 for general surgery. The main outcomes refer to the comparative evaluation between robotic, laparoscopic and open surgery. Risk analysis and mitigation interventions come from FMECA application. The small sample size available for the study represents an important bias, especially for the clinical outcomes reliability. Despite this, the study seems to confirm the better trend for robotics' surgical times with comparison to the open technique as well as confirming the robotics' clinical benefits in urology. More complex situation is observed for general surgery, where robotics' clinical benefits directly measured are the lowest blood transfusion rate.

Differentiation of Ecuadorian National and CCN-51 cocoa beans and their mixtures by computer vision.

PubMed

Jimenez, Juan C; Amores, Freddy M; Solórzano, Eddyn G; Rodríguez, Gladys A; La Mantia, Alessandro; Blasi, Paolo; Loor, Rey G

2018-05-01

Ecuador exports two major types of cocoa beans, the highly regarded and lucrative National, known for its fine aroma, and the CCN-51 clone type, used in bulk for mass chocolate products. In order to discourage exportation of National cocoa adulterated with CCN-51, a fast and objective methodology for distinguishing between the two types of cocoa beans is needed. This study reports a methodology based on computer vision, which makes it possible to recognize these beans and determine the percentage of their mixture. The methodology was challenged with 336 samples of National cocoa and 127 of CCN-51. By excluding the samples with a low fermentation level and white beans, the model discriminated with a precision higher than 98%. The model was also able to identify and quantify adulterations in 75 export batches of National cocoa and separate out poorly fermented beans. A scientifically reliable methodology able to discriminate between Ecuadorian National and CCN-51 cocoa beans and their mixtures was successfully developed. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Design Development Test and Evaluation (DDT and E) Considerations for Safe and Reliable Human Rated Spacecraft Systems

NASA Technical Reports Server (NTRS)

Miller, James; Leggett, Jay; Kramer-White, Julie

2008-01-01

A team directed by the NASA Engineering and Safety Center (NESC) collected methodologies for how best to develop safe and reliable human rated systems and how to identify the drivers that provide the basis for assessing safety and reliability. The team also identified techniques, methodologies, and best practices to assure that NASA can develop safe and reliable human rated systems. The results are drawn from a wide variety of resources, from experts involved with the space program since its inception to the best-practices espoused in contemporary engineering doctrine. This report focuses on safety and reliability considerations and does not duplicate or update any existing references. Neither does it intend to replace existing standards and policy.

Regression to fuzziness method for estimation of remaining useful life in power plant components

NASA Astrophysics Data System (ADS)

Alamaniotis, Miltiadis; Grelle, Austin; Tsoukalas, Lefteri H.

2014-10-01

Mitigation of severe accidents in power plants requires the reliable operation of all systems and the on-time replacement of mechanical components. Therefore, the continuous surveillance of power systems is a crucial concern for the overall safety, cost control, and on-time maintenance of a power plant. In this paper a methodology called regression to fuzziness is presented that estimates the remaining useful life (RUL) of power plant components. The RUL is defined as the difference between the time that a measurement was taken and the estimated failure time of that component. The methodology aims to compensate for a potential lack of historical data by modeling an expert's operational experience and expertise applied to the system. It initially identifies critical degradation parameters and their associated value range. Once completed, the operator's experience is modeled through fuzzy sets which span the entire parameter range. This model is then synergistically used with linear regression and a component's failure point to estimate the RUL. The proposed methodology is tested on estimating the RUL of a turbine (the basic electrical generating component of a power plant) in three different cases. Results demonstrate the benefits of the methodology for components for which operational data is not readily available and emphasize the significance of the selection of fuzzy sets and the effect of knowledge representation on the predicted output. To verify the effectiveness of the methodology, it was benchmarked against the data-based simple linear regression model used for predictions which was shown to perform equal or worse than the presented methodology. Furthermore, methodology comparison highlighted the improvement in estimation offered by the adoption of appropriate of fuzzy sets for parameter representation.

A Reliable Methodology for Determining Seed Viability by Using Hyperspectral Data from Two Sides of Wheat Seeds.

PubMed

Zhang, Tingting; Wei, Wensong; Zhao, Bin; Wang, Ranran; Li, Mingliu; Yang, Liming; Wang, Jianhua; Sun, Qun

2018-03-08

This study investigated the possibility of using visible and near-infrared (VIS/NIR) hyperspectral imaging techniques to discriminate viable and non-viable wheat seeds. Both sides of individual seeds were subjected to hyperspectral imaging (400-1000 nm) to acquire reflectance spectral data. Four spectral datasets, including the ventral groove side, reverse side, mean (the mean of two sides' spectra of every seed), and mixture datasets (two sides' spectra of every seed), were used to construct the models. Classification models, partial least squares discriminant analysis (PLS-DA), and support vector machines (SVM), coupled with some pre-processing methods and successive projections algorithm (SPA), were built for the identification of viable and non-viable seeds. Our results showed that the standard normal variate (SNV)-SPA-PLS-DA model had high classification accuracy for whole seeds (>85.2%) and for viable seeds (>89.5%), and that the prediction set was based on a mixed spectral dataset by only using 16 wavebands. After screening with this model, the final germination of the seed lot could be higher than 89.5%. Here, we develop a reliable methodology for predicting the viability of wheat seeds, showing that the VIS/NIR hyperspectral imaging is an accurate technique for the classification of viable and non-viable wheat seeds in a non-destructive manner.

A Reliable Methodology for Determining Seed Viability by Using Hyperspectral Data from Two Sides of Wheat Seeds

PubMed Central

Zhang, Tingting; Wei, Wensong; Zhao, Bin; Wang, Ranran; Li, Mingliu; Yang, Liming; Wang, Jianhua; Sun, Qun

2018-01-01

This study investigated the possibility of using visible and near-infrared (VIS/NIR) hyperspectral imaging techniques to discriminate viable and non-viable wheat seeds. Both sides of individual seeds were subjected to hyperspectral imaging (400–1000 nm) to acquire reflectance spectral data. Four spectral datasets, including the ventral groove side, reverse side, mean (the mean of two sides’ spectra of every seed), and mixture datasets (two sides’ spectra of every seed), were used to construct the models. Classification models, partial least squares discriminant analysis (PLS-DA), and support vector machines (SVM), coupled with some pre-processing methods and successive projections algorithm (SPA), were built for the identification of viable and non-viable seeds. Our results showed that the standard normal variate (SNV)-SPA-PLS-DA model had high classification accuracy for whole seeds (>85.2%) and for viable seeds (>89.5%), and that the prediction set was based on a mixed spectral dataset by only using 16 wavebands. After screening with this model, the final germination of the seed lot could be higher than 89.5%. Here, we develop a reliable methodology for predicting the viability of wheat seeds, showing that the VIS/NIR hyperspectral imaging is an accurate technique for the classification of viable and non-viable wheat seeds in a non-destructive manner. PMID:29517991

Evaluation of speech errors in Putonghua speakers with cleft palate: a critical review of methodology issues.

PubMed

Jiang, Chenghui; Whitehill, Tara L

2014-04-01

Speech errors associated with cleft palate are well established for English and several other Indo-European languages. Few articles describing the speech of Putonghua (standard Mandarin Chinese) speakers with cleft palate have been published in English language journals. Although methodological guidelines have been published for the perceptual speech evaluation of individuals with cleft palate, there has been no critical review of methodological issues in studies of Putonghua speakers with cleft palate. A literature search was conducted to identify relevant studies published over the past 30 years in Chinese language journals. Only studies incorporating perceptual analysis of speech were included. Thirty-seven articles which met inclusion criteria were analyzed and coded on a number of methodological variables. Reliability was established by having all variables recoded for all studies. This critical review identified many methodological issues. These design flaws make it difficult to draw reliable conclusions about characteristic speech errors in this group of speakers. Specific recommendations are made to improve the reliability and validity of future studies, as well to facilitate cross-center comparisons.

Probability-based methodology for buckling investigation of sandwich composite shells with and without cut-outs

NASA Astrophysics Data System (ADS)

Alfano, M.; Bisagni, C.

2017-01-01

The objective of the running EU project DESICOS (New Robust DESign Guideline for Imperfection Sensitive COmposite Launcher Structures) is to formulate an improved shell design methodology in order to meet the demand of aerospace industry for lighter structures. Within the project, this article discusses the development of a probability-based methodology developed at Politecnico di Milano. It is based on the combination of the Stress-Strength Interference Method and the Latin Hypercube Method with the aim to predict the bucking response of three sandwich composite cylindrical shells, assuming a loading condition of pure compression. The three shells are made of the same material, but have different stacking sequence and geometric dimensions. One of them presents three circular cut-outs. Different types of input imperfections, treated as random variables, are taken into account independently and in combination: variability in longitudinal Young's modulus, ply misalignment, geometric imperfections, and boundary imperfections. The methodology enables a first assessment of the structural reliability of the shells through the calculation of a probabilistic buckling factor for a specified level of probability. The factor depends highly on the reliability level, on the number of adopted samples, and on the assumptions made in modeling the input imperfections. The main advantage of the developed procedure is the versatility, as it can be applied to the buckling analysis of laminated composite shells and sandwich composite shells including different types of imperfections.

A Practical, Robust Methodology for Acquiring New Observation Data Using Computationally Expensive Groundwater Models

NASA Astrophysics Data System (ADS)

Siade, Adam J.; Hall, Joel; Karelse, Robert N.

2017-11-01

Regional groundwater flow models play an important role in decision making regarding water resources; however, the uncertainty embedded in model parameters and model assumptions can significantly hinder the reliability of model predictions. One way to reduce this uncertainty is to collect new observation data from the field. However, determining where and when to obtain such data is not straightforward. There exist a number of data-worth and experimental design strategies developed for this purpose. However, these studies often ignore issues related to real-world groundwater models such as computational expense, existing observation data, high-parameter dimension, etc. In this study, we propose a methodology, based on existing methods and software, to efficiently conduct such analyses for large-scale, complex regional groundwater flow systems for which there is a wealth of available observation data. The method utilizes the well-established d-optimality criterion, and the minimax criterion for robust sampling strategies. The so-called Null-Space Monte Carlo method is used to reduce the computational burden associated with uncertainty quantification. And, a heuristic methodology, based on the concept of the greedy algorithm, is proposed for developing robust designs with subsets of the posterior parameter samples. The proposed methodology is tested on a synthetic regional groundwater model, and subsequently applied to an existing, complex, regional groundwater system in the Perth region of Western Australia. The results indicate that robust designs can be obtained efficiently, within reasonable computational resources, for making regional decisions regarding groundwater level sampling.

Probabilistic fatigue life prediction of metallic and composite materials

NASA Astrophysics Data System (ADS)

Xiang, Yibing

Fatigue is one of the most common failure modes for engineering structures, such as aircrafts, rotorcrafts and aviation transports. Both metallic materials and composite materials are widely used and affected by fatigue damage. Huge uncertainties arise from material properties, measurement noise, imperfect models, future anticipated loads and environmental conditions. These uncertainties are critical issues for accurate remaining useful life (RUL) prediction for engineering structures in service. Probabilistic fatigue prognosis considering various uncertainties is of great importance for structural safety. The objective of this study is to develop probabilistic fatigue life prediction models for metallic materials and composite materials. A fatigue model based on crack growth analysis and equivalent initial flaw size concept is proposed for metallic materials. Following this, the developed model is extended to include structural geometry effects (notch effect), environmental effects (corroded specimens) and manufacturing effects (shot peening effects). Due to the inhomogeneity and anisotropy, the fatigue model suitable for metallic materials cannot be directly applied to composite materials. A composite fatigue model life prediction is proposed based on a mixed-mode delamination growth model and a stiffness degradation law. After the development of deterministic fatigue models of metallic and composite materials, a general probabilistic life prediction methodology is developed. The proposed methodology combines an efficient Inverse First-Order Reliability Method (IFORM) for the uncertainty propogation in fatigue life prediction. An equivalent stresstransformation has been developed to enhance the computational efficiency under realistic random amplitude loading. A systematical reliability-based maintenance optimization framework is proposed for fatigue risk management and mitigation of engineering structures.

Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

DOE PAGES

Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.; ...

2017-01-18

Currently, Constraint-Based Reconstruction and Analysis (COBRA) is the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Furthermore, standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We also developed a quadrupleprecision version of ourmore » linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.« less

Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression

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

Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.

Currently, Constraint-Based Reconstruction and Analysis (COBRA) is the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many orders of magnitude. Data values also have greatly varying magnitudes. Furthermore, standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME models have 70,000 constraints and variables and will grow larger). We also developed a quadrupleprecision version of ourmore » linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging problems tested here. DQQ will enable extensive use of large linear and nonlinear models in systems biology and other applications involving multiscale data.« less

Use of measurement theory for operationalization and quantification of psychological constructs in systems dynamics modelling

NASA Astrophysics Data System (ADS)

Fitkov-Norris, Elena; Yeghiazarian, Ara

2016-11-01

The analytical tools available to social scientists have traditionally been adapted from tools originally designed for analysis of natural science phenomena. This article discusses the applicability of systems dynamics - a qualitative based modelling approach, as a possible analysis and simulation tool that bridges the gap between social and natural sciences. After a brief overview of the systems dynamics modelling methodology, the advantages as well as limiting factors of systems dynamics to the potential applications in the field of social sciences and human interactions are discussed. The issues arise with regards to operationalization and quantification of latent constructs at the simulation building stage of the systems dynamics methodology and measurement theory is proposed as a ready and waiting solution to the problem of dynamic model calibration, with a view of improving simulation model reliability and validity and encouraging the development of standardised, modular system dynamics models that can be used in social science research.

76 FR 65504 - Proposed Agency Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-21

..., including the validity of the methodology and assumptions used; (c) ways to enhance the quality, utility... Reliability Standard, FAC- 008-3--Facility Ratings, developed by the North American Electric Reliability... Reliability Standard FAC- 008-3 is pending before the Commission. The proposed Reliability Standard modifies...

Reliability-Based Design Optimization of a Composite Airframe Component

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2009-01-01

A stochastic design optimization methodology (SDO) has been developed to design components of an airframe structure that can be made of metallic and composite materials. The design is obtained as a function of the risk level, or reliability, p. The design method treats uncertainties in load, strength, and material properties as distribution functions, which are defined with mean values and standard deviations. A design constraint or a failure mode is specified as a function of reliability p. Solution to stochastic optimization yields the weight of a structure as a function of reliability p. Optimum weight versus reliability p traced out an inverted-S-shaped graph. The center of the inverted-S graph corresponded to 50 percent (p = 0.5) probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponds to unity for reliability p (or p = 1). Weight can be reduced to a small value for the most failure-prone design with a reliability that approaches zero (p = 0). Reliability can be changed for different components of an airframe structure. For example, the landing gear can be designed for a very high reliability, whereas it can be reduced to a small extent for a raked wingtip. The SDO capability is obtained by combining three codes: (1) The MSC/Nastran code was the deterministic analysis tool, (2) The fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and (3) NASA Glenn Research Center s optimization testbed 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 raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.

Principle of maximum entropy for reliability analysis in the design of machine components

NASA Astrophysics Data System (ADS)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

New methodologies for multi-scale time-variant reliability analysis of complex lifeline networks

NASA Astrophysics Data System (ADS)

Kurtz, Nolan Scot

The cost of maintaining existing civil infrastructure is enormous. Since the livelihood of the public depends on such infrastructure, its state must be managed appropriately using quantitative approaches. Practitioners must consider not only which components are most fragile to hazard, e.g. seismicity, storm surge, hurricane winds, etc., but also how they participate on a network level using network analysis. Focusing on particularly damaged components does not necessarily increase network functionality, which is most important to the people that depend on such infrastructure. Several network analyses, e.g. S-RDA, LP-bounds, and crude-MCS, and performance metrics, e.g. disconnection bounds and component importance, are available for such purposes. Since these networks are existing, the time state is also important. If networks are close to chloride sources, deterioration may be a major issue. Information from field inspections may also have large impacts on quantitative models. To address such issues, hazard risk analysis methodologies for deteriorating networks subjected to seismicity, i.e. earthquakes, have been created from analytics. A bridge component model has been constructed for these methodologies. The bridge fragilities, which were constructed from data, required a deeper level of analysis as these were relevant for specific structures. Furthermore, chloride-induced deterioration network effects were investigated. Depending on how mathematical models incorporate new information, many approaches are available, such as Bayesian model updating. To make such procedures more flexible, an adaptive importance sampling scheme was created for structural reliability problems. Additionally, such a method handles many kinds of system and component problems with singular or multiple important regions of the limit state function. These and previously developed analysis methodologies were found to be strongly sensitive to the network size. Special network topologies may be more or less computationally difficult, while the resolution of the network also has large affects. To take advantage of some types of topologies, network hierarchical structures with super-link representation have been used in the literature to increase the computational efficiency by analyzing smaller, densely connected networks; however, such structures were based on user input and subjective at times. To address this, algorithms must be automated and reliable. These hierarchical structures may indicate the structure of the network itself. This risk analysis methodology has been expanded to larger networks using such automated hierarchical structures. Component importance is the most important objective from such network analysis; however, this may only provide the information of which bridges to inspect/repair earliest and little else. High correlations influence such component importance measures in a negative manner. Additionally, a regional approach is not appropriately modelled. To investigate a more regional view, group importance measures based on hierarchical structures have been created. Such structures may also be used to create regional inspection/repair approaches. Using these analytical, quantitative risk approaches, the next generation of decision makers may make both component and regional-based optimal decisions using information from both network function and further effects of infrastructure deterioration.

Parts and Components Reliability Assessment: A Cost Effective Approach

NASA Technical Reports Server (NTRS)

Lee, Lydia

2009-01-01

System reliability assessment is a methodology which incorporates reliability analyses performed at parts and components level such as Reliability Prediction, Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) to assess risks, perform design tradeoffs, and therefore, to ensure effective productivity and/or mission success. The system reliability is used to optimize the product design to accommodate today?s mandated budget, manpower, and schedule constraints. Stand ard based reliability assessment is an effective approach consisting of reliability predictions together with other reliability analyses for electronic, electrical, and electro-mechanical (EEE) complex parts and components of large systems based on failure rate estimates published by the United States (U.S.) military or commercial standards and handbooks. Many of these standards are globally accepted and recognized. The reliability assessment is especially useful during the initial stages when the system design is still in the development and hard failure data is not yet available or manufacturers are not contractually obliged by their customers to publish the reliability estimates/predictions for their parts and components. This paper presents a methodology to assess system reliability using parts and components reliability estimates to ensure effective productivity and/or mission success in an efficient manner, low cost, and tight schedule.

Reliability approach to rotating-component design. [fatigue life and stress concentration

NASA Technical Reports Server (NTRS)

Kececioglu, D. B.; Lalli, V. R.

1975-01-01

A probabilistic methodology for designing rotating mechanical components using reliability to relate stress to strength is explained. The experimental test machines and data obtained for steel to verify this methodology are described. A sample mechanical rotating component design problem is solved by comparing a deterministic design method with the new design-by reliability approach. The new method shows that a smaller size and weight can be obtained for specified rotating shaft life and reliability, and uses the statistical distortion-energy theory with statistical fatigue diagrams for optimum shaft design. Statistical methods are presented for (1) determining strength distributions for steel experimentally, (2) determining a failure theory for stress variations in a rotating shaft subjected to reversed bending and steady torque, and (3) relating strength to stress by reliability.

Methodology to Improve Design of Accelerated Life Tests in Civil Engineering Projects

PubMed Central

Lin, Jing; Yuan, Yongbo; Zhou, Jilai; Gao, Jie

2014-01-01

For reliability testing an Energy Expansion Tree (EET) and a companion Energy Function Model (EFM) are proposed and described in this paper. Different from conventional approaches, the EET provides a more comprehensive and objective way to systematically identify external energy factors affecting reliability. The EFM introduces energy loss into a traditional Function Model to identify internal energy sources affecting reliability. The combination creates a sound way to enumerate the energies to which a system may be exposed during its lifetime. We input these energies into planning an accelerated life test, a Multi Environment Over Stress Test. The test objective is to discover weak links and interactions among the system and the energies to which it is exposed, and design them out. As an example, the methods are applied to the pipe in subsea pipeline. However, they can be widely used in other civil engineering industries as well. The proposed method is compared with current methods. PMID:25111800

Analyzing degradation data with a random effects spline regression model

DOE PAGES

Fugate, Michael Lynn; Hamada, Michael Scott; Weaver, Brian Phillip

2017-03-17

This study proposes using a random effects spline regression model to analyze degradation data. Spline regression avoids having to specify a parametric function for the true degradation of an item. A distribution for the spline regression coefficients captures the variation of the true degradation curves from item to item. We illustrate the proposed methodology with a real example using a Bayesian approach. The Bayesian approach allows prediction of degradation of a population over time and estimation of reliability is easy to perform.

Analyzing degradation data with a random effects spline regression model

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

Fugate, Michael Lynn; Hamada, Michael Scott; Weaver, Brian Phillip

This study proposes using a random effects spline regression model to analyze degradation data. Spline regression avoids having to specify a parametric function for the true degradation of an item. A distribution for the spline regression coefficients captures the variation of the true degradation curves from item to item. We illustrate the proposed methodology with a real example using a Bayesian approach. The Bayesian approach allows prediction of degradation of a population over time and estimation of reliability is easy to perform.

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

PubMed

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

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

Radojcic, Riko; Nowak, Matt; Nakamoto, Mark

The status of the development of a Design-for-Stress simulation flow that captures the stress effects in packaged 3D-stacked Si products like integrated circuits (ICs) using advanced via-middle Through Si Via technology is outlined. The next set of challenges required to proliferate the methodology and to deploy it for making and dispositioning real Si product decisions are described here. These include the adoption and support of a Process Design Kit (PDK) that includes the relevant material properties, the development of stress simulation methodologies that operate at higher levels of abstraction in a design flow, and the development and adoption of suitablemore » models required to make real product reliability decisions.« less

Probing Reliability of Transport Phenomena Based Heat Transfer and Fluid Flow Analysis in Autogeneous Fusion Welding Process

NASA Astrophysics Data System (ADS)

Bag, S.; de, A.

2010-09-01

The transport phenomena based heat transfer and fluid flow calculations in weld pool require a number of input parameters. Arc efficiency, effective thermal conductivity, and viscosity in weld pool are some of these parameters, values of which are rarely known and difficult to assign a priori based on the scientific principles alone. The present work reports a bi-directional three-dimensional (3-D) heat transfer and fluid flow model, which is integrated with a real number based genetic algorithm. The bi-directional feature of the integrated model allows the identification of the values of a required set of uncertain model input parameters and, next, the design of process parameters to achieve a target weld pool dimension. The computed values are validated with measured results in linear gas-tungsten-arc (GTA) weld samples. Furthermore, a novel methodology to estimate the overall reliability of the computed solutions is also presented.

Development of Probabilistic Life Prediction Methodologies and Testing Strategies for MEMS and CMC's

NASA Technical Reports Server (NTRS)

Jadaan, Osama

2003-01-01

This effort is to investigate probabilistic life prediction methodologies for ceramic matrix composites and MicroElectroMechanical Systems (MEMS) and to analyze designs that determine stochastic properties of MEMS. For CMC's this includes a brief literature survey regarding lifing methodologies. Also of interest for MEMS is the design of a proper test for the Weibull size effect in thin film (bulge test) specimens. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. A main objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures/Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads. A second set of objectives is to determine the applicability/suitability of the CARES/Life methodology for CMC analysis, what changes would be needed to the methodology and software, and if feasible, run a demonstration problem. Also important is an evaluation of CARES/Life coupled to the ANSYS Probabilistic Design System (PDS) and the potential of coupling transient reliability analysis to the ANSYS PDS.

Rating the raters in a mixed model: An approach to deciphering the rater reliability

NASA Astrophysics Data System (ADS)

Shang, Junfeng; Wang, Yougui

2013-05-01

Rating the raters has attracted extensive attention in recent years. Ratings are quite complex in that the subjective assessment and a number of criteria are involved in a rating system. Whenever the human judgment is a part of ratings, the inconsistency of ratings is the source of variance in scores, and it is therefore quite natural for people to verify the trustworthiness of ratings. Accordingly, estimation of the rater reliability will be of great interest and an appealing issue. To facilitate the evaluation of the rater reliability in a rating system, we propose a mixed model where the scores of the ratees offered by a rater are described with the fixed effects determined by the ability of the ratees and the random effects produced by the disagreement of the raters. In such a mixed model, for the rater random effects, we derive its posterior distribution for the prediction of random effects. To quantitatively make a decision in revealing the unreliable raters, the predictive influence function (PIF) serves as a criterion which compares the posterior distributions of random effects between the full data and rater-deleted data sets. The benchmark for this criterion is also discussed. This proposed methodology of deciphering the rater reliability is investigated in the multiple simulated and two real data sets.

Test-Retest Reliability of Pediatric Heart Rate Variability: A Meta-Analysis.

PubMed

Weiner, Oren M; McGrath, Jennifer J

2017-01-01

Heart rate variability (HRV), an established index of autonomic cardiovascular modulation, is associated with health outcomes (e.g., obesity, diabetes) and mortality risk. Time- and frequency-domain HRV measures are commonly reported in longitudinal adult and pediatric studies of health. While test-retest reliability has been established among adults, less is known about the psychometric properties of HRV among infants, children, and adolescents. The objective was to conduct a meta-analysis of the test-retest reliability of time- and frequency-domain HRV measures from infancy to adolescence. Electronic searches (PubMed, PsycINFO; January 1970-December 2014) identified studies with nonclinical samples aged ≤ 18 years; ≥ 2 baseline HRV recordings separated by ≥ 1 day; and sufficient data for effect size computation. Forty-nine studies ( N = 5,170) met inclusion criteria. Methodological variables coded included factors relevant to study protocol, sample characteristics, electrocardiogram (ECG) signal acquisition and preprocessing, and HRV analytical decisions. Fisher's Z was derived as the common effect size. Analyses were age-stratified (infant/toddler < 5 years, n = 3,329; child/adolescent 5-18 years, n = 1,841) due to marked methodological differences across the pediatric literature. Meta-analytic results revealed HRV demonstrated moderate reliability; child/adolescent studies ( Z = 0.62, r = 0.55) had significantly higher reliability than infant/toddler studies ( Z = 0.42, r = 0.40). Relative to other reported measures, HF exhibited the highest reliability among infant/toddler studies ( Z = 0.42, r = 0.40), while rMSSD exhibited the highest reliability among child/adolescent studies ( Z = 1.00, r = 0.76). Moderator analyses indicated greater reliability with shorter test-retest interval length, reported exclusion criteria based on medical illness/condition, lower proportion of males, prerecording acclimatization period, and longer recording duration; differences were noted across age groups. HRV is reliable among pediatric samples. Reliability is sensitive to pertinent methodological decisions that require careful consideration by the researcher. Limited methodological reporting precluded several a priori moderator analyses. Suggestions for future research, including standards specified by Task Force Guidelines, are discussed.

Test-Retest Reliability of Pediatric Heart Rate Variability

PubMed Central

Weiner, Oren M.; McGrath, Jennifer J.

2017-01-01

Heart rate variability (HRV), an established index of autonomic cardiovascular modulation, is associated with health outcomes (e.g., obesity, diabetes) and mortality risk. Time- and frequency-domain HRV measures are commonly reported in longitudinal adult and pediatric studies of health. While test-retest reliability has been established among adults, less is known about the psychometric properties of HRV among infants, children, and adolescents. The objective was to conduct a meta-analysis of the test-retest reliability of time- and frequency-domain HRV measures from infancy to adolescence. Electronic searches (PubMed, PsycINFO; January 1970–December 2014) identified studies with nonclinical samples aged ≤ 18 years; ≥ 2 baseline HRV recordings separated by ≥ 1 day; and sufficient data for effect size computation. Forty-nine studies (N = 5,170) met inclusion criteria. Methodological variables coded included factors relevant to study protocol, sample characteristics, electrocardiogram (ECG) signal acquisition and preprocessing, and HRV analytical decisions. Fisher’s Z was derived as the common effect size. Analyses were age-stratified (infant/toddler < 5 years, n = 3,329; child/adolescent 5–18 years, n = 1,841) due to marked methodological differences across the pediatric literature. Meta-analytic results revealed HRV demonstrated moderate reliability; child/adolescent studies (Z = 0.62, r = 0.55) had significantly higher reliability than infant/toddler studies (Z = 0.42, r = 0.40). Relative to other reported measures, HF exhibited the highest reliability among infant/toddler studies (Z = 0.42, r = 0.40), while rMSSD exhibited the highest reliability among child/adolescent studies (Z = 1.00, r = 0.76). Moderator analyses indicated greater reliability with shorter test-retest interval length, reported exclusion criteria based on medical illness/condition, lower proportion of males, prerecording acclimatization period, and longer recording duration; differences were noted across age groups. HRV is reliable among pediatric samples. Reliability is sensitive to pertinent methodological decisions that require careful consideration by the researcher. Limited methodological reporting precluded several a priori moderator analyses. Suggestions for future research, including standards specified by Task Force Guidelines, are discussed. PMID:29307951

Monte Carlo simulation methodology for the reliabilty of aircraft structures under damage tolerance considerations

NASA Astrophysics Data System (ADS)

Rambalakos, Andreas

Current federal aviation regulations in the United States and around the world mandate the need for aircraft structures to meet damage tolerance requirements through out the service life. These requirements imply that the damaged aircraft structure must maintain adequate residual strength in order to sustain its integrity that is accomplished by a continuous inspection program. The multifold objective of this research is to develop a methodology based on a direct Monte Carlo simulation process and to assess the reliability of aircraft structures. Initially, the structure is modeled as a parallel system with active redundancy comprised of elements with uncorrelated (statistically independent) strengths and subjected to an equal load distribution. Closed form expressions for the system capacity cumulative distribution function (CDF) are developed by expanding the current expression for the capacity CDF of a parallel system comprised by three elements to a parallel system comprised with up to six elements. These newly developed expressions will be used to check the accuracy of the implementation of a Monte Carlo simulation algorithm to determine the probability of failure of a parallel system comprised of an arbitrary number of statistically independent elements. The second objective of this work is to compute the probability of failure of a fuselage skin lap joint under static load conditions through a Monte Carlo simulation scheme by utilizing the residual strength of the fasteners subjected to various initial load distributions and then subjected to a new unequal load distribution resulting from subsequent fastener sequential failures. The final and main objective of this thesis is to present a methodology for computing the resulting gradual deterioration of the reliability of an aircraft structural component by employing a direct Monte Carlo simulation approach. The uncertainties associated with the time to crack initiation, the probability of crack detection, the exponent in the crack propagation rate (Paris equation) and the yield strength of the elements are considered in the analytical model. The structural component is assumed to consist of a prescribed number of elements. This Monte Carlo simulation methodology is used to determine the required non-periodic inspections so that the reliability of the structural component will not fall below a prescribed minimum level. A sensitivity analysis is conducted to determine the effect of three key parameters on the specification of the non-periodic inspection intervals: namely a parameter associated with the time to crack initiation, the applied nominal stress fluctuation and the minimum acceptable reliability level.

Developing high-resolution urban scale heavy-duty truck emission inventory using the data-driven truck activity model output

NASA Astrophysics Data System (ADS)

Perugu, Harikishan; Wei, Heng; Yao, Zhuo

2017-04-01

Air quality modelers often rely on regional travel demand models to estimate the vehicle activity data for emission models, however, most of the current travel demand models can only output reliable person travel activity rather than goods/service specific travel activity. This paper presents the successful application of data-driven, Spatial Regression and output optimization Truck model (SPARE-Truck) to develop truck-related activity inputs for the mobile emission model, and eventually to produce truck specific gridded emissions. To validate the proposed methodology, the Cincinnati metropolitan area in United States was selected as a case study site. From the results, it is found that the truck miles traveled predicted using traditional methods tend to underestimate - overall 32% less than proposed model- truck miles traveled. The coefficient of determination values for different truck types range between 0.82 and 0.97, except the motor homes which showed least model fit with 0.51. Consequently, the emission inventories calculated from the traditional methods were also underestimated i.e. -37% for NOx, -35% for SO2, -43% for VOC, -43% for BC, -47% for OC and - 49% for PM2.5. Further, the proposed method also predicted within ∼7% of the national emission inventory for all pollutants. The bottom-up gridding methodology used in this paper could allocate the emissions to grid cell where more truck activity is expected, and it is verified against regional land-use data. Most importantly, using proposed method it is easy to segregate gridded emission inventory by truck type, which is of particular interest for decision makers, since currently there is no reliable method to test different truck-category specific travel-demand management strategies for air pollution control.

Transient Reliability of Ceramic Structures For Heat Engine Applications

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Jadaan, Osama M.

2002-01-01

The objectives of this report was to develop a methodology to predict the time-dependent reliability (probability of failure) of brittle material components subjected to transient thermomechanical loading, taking into account the change in material response with time. This methodology for computing the transient reliability in ceramic components subjected to fluctuation thermomechanical loading was developed, assuming SCG (Slow Crack Growth) as the delayed mode of failure. It takes into account the effect of varying Weibull modulus and materials with time. It was also coded into a beta version of NASA's CARES/Life code, and an example demonstrating its viability was presented.

Reliability Based Design for a Raked Wing Tip of an Airframe

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2011-01-01

A reliability-based optimization methodology has been developed to design the raked wing tip of the Boeing 767-400 extended range airliner made of composite and metallic materials. Design is formulated for an accepted level of risk or reliability. The design variables, weight and the constraints became functions of reliability. Uncertainties in the load, strength and the material properties, as well as the design variables, were modeled as random parameters with specified distributions, like normal, Weibull or Gumbel functions. The objective function and constraint, or a failure mode, became derived functions of the risk-level. Solution to the problem produced the optimum design with weight, variables and constraints as a function of the risk-level. Optimum weight versus reliability traced out an inverted-S shaped graph. The center of the graph corresponded to a 50 percent probability of success, or one failure in two samples. Under some assumptions, this design would be quite close to the deterministic optimum solution. The weight increased when reliability exceeded 50 percent, and decreased when the reliability was compromised. A design could be selected depending on the level of risk acceptable to a situation. The optimization process achieved up to a 20-percent reduction in weight over traditional design.

Reliability evaluation methodology for NASA applications

NASA Technical Reports Server (NTRS)

Taneja, Vidya S.

1992-01-01

Liquid rocket engine technology has been characterized by the development of complex systems containing large number of subsystems, components, and parts. The trend to even larger and more complex system is continuing. The liquid rocket engineers have been focusing mainly on performance driven designs to increase payload delivery of a launch vehicle for a given mission. In otherwords, although the failure of a single inexpensive part or component may cause the failure of the system, reliability in general has not been considered as one of the system parameters like cost or performance. Up till now, quantification of reliability has not been a consideration during system design and development in the liquid rocket industry. Engineers and managers have long been aware of the fact that the reliability of the system increases during development, but no serious attempts have been made to quantify reliability. As a result, a method to quantify reliability during design and development is needed. This includes application of probabilistic models which utilize both engineering analysis and test data. Classical methods require the use of operating data for reliability demonstration. In contrast, the method described in this paper is based on similarity, analysis, and testing combined with Bayesian statistical analysis.

Mechanical system reliability for long life space systems

NASA Technical Reports Server (NTRS)

Kowal, Michael T.

1994-01-01

The creation of a compendium of mechanical limit states was undertaken in order to provide a reference base for the application of first-order reliability methods to mechanical systems in the context of the development of a system level design methodology. The compendium was conceived as a reference source specific to the problem of developing the noted design methodology, and not an exhaustive or exclusive compilation of mechanical limit states. The compendium is not intended to be a handbook of mechanical limit states for general use. The compendium provides a diverse set of limit-state relationships for use in demonstrating the application of probabilistic reliability methods to mechanical systems. The compendium is to be used in the reliability analysis of moderately complex mechanical systems.

The Scaling of Performance and Losses in Miniature Internal Combustion Engines

DTIC Science & Technology

2010-01-01

reliable measurements of engine performance and losses in these small engines. Methodologies are also developed for measuring volumetric, heat transfer...making reliable measurements of engine performance and losses in these small engines. Methodologies are also developed for measuring volumetric, heat ...the most important challenge as it accounts for 60-70% of total energy losses. Combustion losses are followed in order of importance by heat transfer

A Microstructure-Based Time-Dependent Crack Growth Model for Life and Reliability Prediction of Turbopropulsion Systems

NASA Astrophysics Data System (ADS)

Chan, Kwai S.; Enright, Michael P.; Moody, Jonathan; Fitch, Simeon H. K.

2014-01-01

The objective of this investigation was to develop an innovative methodology for life and reliability prediction of hot-section components in advanced turbopropulsion systems. A set of generic microstructure-based time-dependent crack growth (TDCG) models was developed and used to assess the sources of material variability due to microstructure and material parameters such as grain size, activation energy, and crack growth threshold for TDCG. A comparison of model predictions and experimental data obtained in air and in vacuum suggests that oxidation is responsible for higher crack growth rates at high temperatures, low frequencies, and long dwell times, but oxidation can also induce higher crack growth thresholds (Δ K th or K th) under certain conditions. Using the enhanced risk analysis tool and material constants calibrated to IN 718 data, the effect of TDCG on the risk of fracture in turboengine components was demonstrated for a generic rotor design and a realistic mission profile using the DARWIN® probabilistic life-prediction code. The results of this investigation confirmed that TDCG and cycle-dependent crack growth in IN 718 can be treated by a simple summation of the crack increments over a mission. For the temperatures considered, TDCG in IN 718 can be considered as a K-controlled or a diffusion-controlled oxidation-induced degradation process. This methodology provides a pathway for evaluating microstructural effects on multiple damage modes in hot-section components.

Estimation of environment-related properties of chemicals for design of sustainable processes: development of group-contribution+ (GC+) property models and uncertainty analysis.

PubMed

Hukkerikar, Amol Shivajirao; Kalakul, Sawitree; Sarup, Bent; Young, Douglas M; Sin, Gürkan; Gani, Rafiqul

2012-11-26

The aim of this work is to develop group-contribution(+) (GC(+)) method (combined group-contribution (GC) method and atom connectivity index (CI) method) based property models to provide reliable estimations of environment-related properties of organic chemicals together with uncertainties of estimated property values. For this purpose, a systematic methodology for property modeling and uncertainty analysis is used. The methodology includes a parameter estimation step to determine parameters of property models and an uncertainty analysis step to establish statistical information about the quality of parameter estimation, such as the parameter covariance, the standard errors in predicted properties, and the confidence intervals. For parameter estimation, large data sets of experimentally measured property values of a wide range of chemicals (hydrocarbons, oxygenated chemicals, nitrogenated chemicals, poly functional chemicals, etc.) taken from the database of the US Environmental Protection Agency (EPA) and from the database of USEtox is used. For property modeling and uncertainty analysis, the Marrero and Gani GC method and atom connectivity index method have been considered. In total, 22 environment-related properties, which include the fathead minnow 96-h LC(50), Daphnia magna 48-h LC(50), oral rat LD(50), aqueous solubility, bioconcentration factor, permissible exposure limit (OSHA-TWA), photochemical oxidation potential, global warming potential, ozone depletion potential, acidification potential, emission to urban air (carcinogenic and noncarcinogenic), emission to continental rural air (carcinogenic and noncarcinogenic), emission to continental fresh water (carcinogenic and noncarcinogenic), emission to continental seawater (carcinogenic and noncarcinogenic), emission to continental natural soil (carcinogenic and noncarcinogenic), and emission to continental agricultural soil (carcinogenic and noncarcinogenic) have been modeled and analyzed. The application of the developed property models for the estimation of environment-related properties and uncertainties of the estimated property values is highlighted through an illustrative example. The developed property models provide reliable estimates of environment-related properties needed to perform process synthesis, design, and analysis of sustainable chemical processes and allow one to evaluate the effect of uncertainties of estimated property values on the calculated performance of processes giving useful insights into quality and reliability of the design of sustainable processes.

Development of a Quantitative Methodology to Assess the Impacts of Urban Transport Interventions and Related Noise on Well-Being

PubMed Central

Braubach, Matthias; Tobollik, Myriam; Mudu, Pierpaolo; Hiscock, Rosemary; Chapizanis, Dimitris; Sarigiannis, Denis A.; Keuken, Menno; Perez, Laura; Martuzzi, Marco

2015-01-01

Well-being impact assessments of urban interventions are a difficult challenge, as there is no agreed methodology and scarce evidence on the relationship between environmental conditions and well-being. The European Union (EU) project “Urban Reduction of Greenhouse Gas Emissions in China and Europe” (URGENCHE) explored a methodological approach to assess traffic noise-related well-being impacts of transport interventions in three European cities (Basel, Rotterdam and Thessaloniki) linking modeled traffic noise reduction effects with survey data indicating noise-well-being associations. Local noise models showed a reduction of high traffic noise levels in all cities as a result of different urban interventions. Survey data indicated that perception of high noise levels was associated with lower probability of well-being. Connecting the local noise exposure profiles with the noise-well-being associations suggests that the urban transport interventions may have a marginal but positive effect on population well-being. This paper also provides insight into the methodological challenges of well-being assessments and highlights the range of limitations arising from the current lack of reliable evidence on environmental conditions and well-being. Due to these limitations, the results should be interpreted with caution. PMID:26016437

Development of a quantitative methodology to assess the impacts of urban transport interventions and related noise on well-being.

PubMed

Braubach, Matthias; Tobollik, Myriam; Mudu, Pierpaolo; Hiscock, Rosemary; Chapizanis, Dimitris; Sarigiannis, Denis A; Keuken, Menno; Perez, Laura; Martuzzi, Marco

2015-05-26

Well-being impact assessments of urban interventions are a difficult challenge, as there is no agreed methodology and scarce evidence on the relationship between environmental conditions and well-being. The European Union (EU) project "Urban Reduction of Greenhouse Gas Emissions in China and Europe" (URGENCHE) explored a methodological approach to assess traffic noise-related well-being impacts of transport interventions in three European cities (Basel, Rotterdam and Thessaloniki) linking modeled traffic noise reduction effects with survey data indicating noise-well-being associations. Local noise models showed a reduction of high traffic noise levels in all cities as a result of different urban interventions. Survey data indicated that perception of high noise levels was associated with lower probability of well-being. Connecting the local noise exposure profiles with the noise-well-being associations suggests that the urban transport interventions may have a marginal but positive effect on population well-being. This paper also provides insight into the methodological challenges of well-being assessments and highlights the range of limitations arising from the current lack of reliable evidence on environmental conditions and well-being. Due to these limitations, the results should be interpreted with caution.

Addressing drug adherence using an operations management model.

PubMed

Nunlee, Martin; Bones, Michelle

2014-01-01

OBJECTIVE To provide a model that enables health systems and pharmacy benefit managers to provide medications reliably and test for reliability and validity in the analysis of adherence to drug therapy of chronic disease. SUMMARY The quantifiable model described here can be used in conjunction with behavioral designs of drug adherence assessments. The model identifies variables that can be reproduced and expanded across the management of chronic diseases with drug therapy. By creating a reorder point system for reordering medications, the model uses a methodology commonly seen in operations research. The design includes a safety stock of medication and current supply of medication, which increases the likelihood that patients will have a continuous supply of medications, thereby positively affecting adherence by removing barriers. CONCLUSION This method identifies an adherence model that quantifies variables related to recommendations from health care providers; it can assist health care and service delivery systems in making decisions that influence adherence based on the expected order cycle days and the expected daily quantity of medication administered. This model addresses the possession of medication as a barrier to adherence.

A new statistical model for subgrid dispersion in large eddy simulations of particle-laden flows

NASA Astrophysics Data System (ADS)

Muela, Jordi; Lehmkuhl, Oriol; Pérez-Segarra, Carles David; Oliva, Asensi

2016-09-01

Dispersed multiphase turbulent flows are present in many industrial and commercial applications like internal combustion engines, turbofans, dispersion of contaminants, steam turbines, etc. Therefore, there is a clear interest in the development of models and numerical tools capable of performing detailed and reliable simulations about these kind of flows. Large Eddy Simulations offer good accuracy and reliable results together with reasonable computational requirements, making it a really interesting method to develop numerical tools for particle-laden turbulent flows. Nonetheless, in multiphase dispersed flows additional difficulties arises in LES, since the effect of the unresolved scales of the continuous phase over the dispersed phase is lost due to the filtering procedure. In order to solve this issue a model able to reconstruct the subgrid velocity seen by the particles is required. In this work a new model for the reconstruction of the subgrid scale effects over the dispersed phase is presented and assessed. This innovative methodology is based in the reconstruction of statistics via Probability Density Functions (PDFs).

Development of Detonation Modeling Capabilities for Rocket Test Facilities: Hydrogen-Oxygen-Nitrogen Mixtures

NASA Technical Reports Server (NTRS)

Allgood, Daniel C.

2016-01-01

The objective of the presented work was to develop validated computational fluid dynamics (CFD) based methodologies for predicting propellant detonations and their associated blast environments. Applications of interest were scenarios relevant to rocket propulsion test and launch facilities. All model development was conducted within the framework of the Loci/CHEM CFD tool due to its reliability and robustness in predicting high-speed combusting flow-fields associated with rocket engines and plumes. During the course of the project, verification and validation studies were completed for hydrogen-fueled detonation phenomena such as shock-induced combustion, confined detonation waves, vapor cloud explosions, and deflagration-to-detonation transition (DDT) processes. The DDT validation cases included predicting flame acceleration mechanisms associated with turbulent flame-jets and flow-obstacles. Excellent comparison between test data and model predictions were observed. The proposed CFD methodology was then successfully applied to model a detonation event that occurred during liquid oxygen/gaseous hydrogen rocket diffuser testing at NASA Stennis Space Center.

EMD-regression for modelling multi-scale relationships, and application to weather-related cardiovascular mortality

NASA Astrophysics Data System (ADS)

Masselot, Pierre; Chebana, Fateh; Bélanger, Diane; St-Hilaire, André; Abdous, Belkacem; Gosselin, Pierre; Ouarda, Taha B. M. J.

2018-01-01

In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.

A methodology for the rigorous verification of plasma simulation codes

NASA Astrophysics Data System (ADS)

Riva, Fabio

2016-10-01

The methodology used to assess the reliability of numerical simulation codes constitutes the Verification and Validation (V&V) procedure. V&V is composed by two separate tasks: the verification, which is a mathematical issue targeted to assess that the physical model is correctly solved, and the validation, which determines the consistency of the code results, and therefore of the physical model, with experimental data. In the present talk we focus our attention on the verification, which in turn is composed by the code verification, targeted to assess that a physical model is correctly implemented in a simulation code, and the solution verification, that quantifies the numerical error affecting a simulation. Bridging the gap between plasma physics and other scientific domains, we introduced for the first time in our domain a rigorous methodology for the code verification, based on the method of manufactured solutions, as well as a solution verification based on the Richardson extrapolation. This methodology was applied to GBS, a three-dimensional fluid code based on a finite difference scheme, used to investigate the plasma turbulence in basic plasma physics experiments and in the tokamak scrape-off layer. Overcoming the difficulty of dealing with a numerical method intrinsically affected by statistical noise, we have now generalized the rigorous verification methodology to simulation codes based on the particle-in-cell algorithm, which are employed to solve Vlasov equation in the investigation of a number of plasma physics phenomena.

A methodology for model-based development and automated verification of software for aerospace systems

NASA Astrophysics Data System (ADS)

Martin, L.; Schatalov, M.; Hagner, M.; Goltz, U.; Maibaum, O.

Today's software for aerospace systems typically is very complex. This is due to the increasing number of features as well as the high demand for safety, reliability, and quality. This complexity also leads to significant higher software development costs. To handle the software complexity, a structured development process is necessary. Additionally, compliance with relevant standards for quality assurance is a mandatory concern. To assure high software quality, techniques for verification are necessary. Besides traditional techniques like testing, automated verification techniques like model checking become more popular. The latter examine the whole state space and, consequently, result in a full test coverage. Nevertheless, despite the obvious advantages, this technique is rarely yet used for the development of aerospace systems. In this paper, we propose a tool-supported methodology for the development and formal verification of safety-critical software in the aerospace domain. The methodology relies on the V-Model and defines a comprehensive work flow for model-based software development as well as automated verification in compliance to the European standard series ECSS-E-ST-40C. Furthermore, our methodology supports the generation and deployment of code. For tool support we use the tool SCADE Suite (Esterel Technology), an integrated design environment that covers all the requirements for our methodology. The SCADE Suite is well established in avionics and defense, rail transportation, energy and heavy equipment industries. For evaluation purposes, we apply our approach to an up-to-date case study of the TET-1 satellite bus. In particular, the attitude and orbit control software is considered. The behavioral models for the subsystem are developed, formally verified, and optimized.

Enhanced Self Tuning On-Board Real-Time Model (eSTORM) for Aircraft Engine Performance Health Tracking

NASA Technical Reports Server (NTRS)

Volponi, Al; Simon, Donald L. (Technical Monitor)

2008-01-01

A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. This report describes the development of a hybrid engine model for a propulsion gas turbine engine, which is the result of fusing two diverse modeling methodologies: a physics-based model approach and an empirical model approach. The report describes the process and methods involved in deriving and implementing a hybrid model configuration for a commercial turbofan engine. Among the intended uses for such a model is to enable real-time, on-board tracking of engine module performance changes and engine parameter synthesis for fault detection and accommodation.

Transient Reliability Analysis Capability Developed for CARES/Life

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

2001-01-01

The CARES/Life software developed at the NASA Glenn Research Center provides a general-purpose design tool that predicts the probability of the failure of a ceramic component as a function of its time in service. This award-winning software has been widely used by U.S. industry to establish the reliability and life of a brittle material (e.g., ceramic, intermetallic, and graphite) structures in a wide variety of 21st century applications.Present capabilities of the NASA CARES/Life code include probabilistic life prediction of ceramic components subjected to fast fracture, slow crack growth (stress corrosion), and cyclic fatigue failure modes. Currently, this code can compute the time-dependent reliability of ceramic structures subjected to simple time-dependent loading. For example, in slow crack growth failure conditions CARES/Life can handle sustained and linearly increasing time-dependent loads, whereas in cyclic fatigue applications various types of repetitive constant-amplitude loads can be accounted for. However, in real applications applied loads are rarely that simple but vary with time in more complex ways such as engine startup, shutdown, and dynamic and vibrational loads. In addition, when a given component is subjected to transient environmental and or thermal conditions, the material properties also vary with time. A methodology has now been developed to allow the CARES/Life computer code to perform reliability analysis of ceramic components undergoing transient thermal and mechanical loading. This means that CARES/Life will be able to analyze finite element models of ceramic components that simulate dynamic engine operating conditions. The methodology developed is generalized to account for material property variation (on strength distribution and fatigue) as a function of temperature. This allows CARES/Life to analyze components undergoing rapid temperature change in other words, components undergoing thermal shock. In addition, the capability has been developed to perform reliability analysis for components that undergo proof testing involving transient loads. This methodology was developed for environmentally assisted crack growth (crack growth as a function of time and loading), but it will be extended to account for cyclic fatigue (crack growth as a function of load cycles) as well.

A diameter-sensitive flow entropy method for reliability consideration in water distribution system design

NASA Astrophysics Data System (ADS)

Liu, Haixing; Savić, Dragan; Kapelan, Zoran; Zhao, Ming; Yuan, Yixing; Zhao, Hongbin

2014-07-01

Flow entropy is a measure of uniformity of pipe flows in water distribution systems. By maximizing flow entropy one can identify reliable layouts or connectivity in networks. In order to overcome the disadvantage of the common definition of flow entropy that does not consider the impact of pipe diameter on reliability, an extended definition of flow entropy, termed as diameter-sensitive flow entropy, is proposed. This new methodology is then assessed by using other reliability methods, including Monte Carlo Simulation, a pipe failure probability model, and a surrogate measure (resilience index) integrated with water demand and pipe failure uncertainty. The reliability assessment is based on a sample of WDS designs derived from an optimization process for each of the two benchmark networks. Correlation analysis is used to evaluate quantitatively the relationship between entropy and reliability. To ensure reliability, a comparative analysis between the flow entropy and the new method is conducted. The results demonstrate that the diameter-sensitive flow entropy shows consistently much stronger correlation with the three reliability measures than simple flow entropy. Therefore, the new flow entropy method can be taken as a better surrogate measure for reliability and could be potentially integrated into the optimal design problem of WDSs. Sensitivity analysis results show that the velocity parameters used in the new flow entropy has no significant impact on the relationship between diameter-sensitive flow entropy and reliability.

A Co-modeling Method Based on Component Features for Mechatronic Devices in Aero-engines

NASA Astrophysics Data System (ADS)

Wang, Bin; Zhao, Haocen; Ye, Zhifeng

2017-08-01

Data-fused and user-friendly design of aero-engine accessories is required because of their structural complexity and stringent reliability. This paper gives an overview of a typical aero-engine control system and the development process of key mechatronic devices used. Several essential aspects of modeling and simulation in the process are investigated. Considering the limitations of a single theoretic model, feature-based co-modeling methodology is suggested to satisfy the design requirements and compensate for diversity of component sub-models for these devices. As an example, a stepper motor controlled Fuel Metering Unit (FMU) is modeled in view of the component physical features using two different software tools. An interface is suggested to integrate the single discipline models into the synthesized one. Performance simulation of this device using the co-model and parameter optimization for its key components are discussed. Comparison between delivery testing and the simulation shows that the co-model for the FMU has a high accuracy and the absolute superiority over a single model. Together with its compatible interface with the engine mathematical model, the feature-based co-modeling methodology is proven to be an effective technical measure in the development process of the device.

Assessment of environmental impacts part one. Intervention analysis

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

Hipel, Keith William; Lettenmaier, Dennis P.; McLeod, A. Ian

The use of intervention analysis as a statistical method of gauging the effects of environmental changes is discussed. The Box-Jenkins model, serves as the basis for the intervention analysis methodology. Environmental studies of the Aswan Dam, the South Saskatchewan River, and a forest fire near the Pipers Hole River, Canada, are included as case studies in which intervention analysis was employed. Methods of data collection for intervention analysis are found to have a significant impact on model reliability; effective data collection processes for the Box-Jenkins model are provided. (15 graphs, 27 references, 2 tables)

Score Reliability: A Retrospective Look Back at 12 Years of Reliability Generalization Studies

ERIC Educational Resources Information Center

Vacha-Haase, Tammi; Thompson, Bruce

2011-01-01

The present study was conducted to characterize (a) the features of the thousands of primary reports synthesized in 47 reliability generalization (RG) measurement meta-analysis studies and (b) typical methodological practice within the RG literature to date. With respect to the treatment of score reliability in the literature, in an astounding…

Trade-associated pathways of alien forest insect entries in Canada

Treesearch

Denys Yemshanov; Frank H. Koch; Mark Ducey; Klaus Koehler

2012-01-01

Long-distance introductions of new invasive species have often been driven by socioeconomic factors, such that traditional ‘‘biological’’ invasion models may not be capable of estimating spread fully and reliably. In this study we present a new methodology to characterize and predict pathways of human-assisted entries of alien forest insects. We have developed a...

Minimum Control Requirements for Advanced Life Support Systems

NASA Technical Reports Server (NTRS)

Boulange, Richard; Jones, Harry; Jones, Harry

2002-01-01

Advanced control technologies are not necessary for the safe, reliable and continuous operation of Advanced Life Support (ALS) systems. ALS systems can and are adequately controlled by simple, reliable, low-level methodologies and algorithms. The automation provided by advanced control technologies is claimed to decrease system mass and necessary crew time by reducing buffer size and minimizing crew involvement. In truth, these approaches increase control system complexity without clearly demonstrating an increase in reliability across the ALS system. Unless these systems are as reliable as the hardware they control, there is no savings to be had. A baseline ALS system is presented with the minimal control system required for its continuous safe reliable operation. This baseline control system uses simple algorithms and scheduling methodologies and relies on human intervention only in the event of failure of the redundant backup equipment. This ALS system architecture is designed for reliable operation, with minimal components and minimal control system complexity. The fundamental design precept followed is "If it isn't there, it can't fail".

From "models" to "reality", and Return. Some Reflections on the Interaction Between Survey and Interpretative Methods for Built Heritage Conservation

NASA Astrophysics Data System (ADS)

Ottoni, F.; Freddi, F.; Zerbi, A.

2017-05-01

It's well known that more and more accurate methodologies and automatic tools are now available in the field of geometric survey and image processing and they constitute a fundamental instrument for cultural heritage knowledge and preservation; on the other side, very smart and precise numerical models are continuously improved and used in order to simulate the mechanical behaviour of masonry structures: both instruments and technologies are important part of a global process of knowledge which is at the base of any conservation project of cultural heritage. Despite the high accuracy and automation level reached by both technologies and programs, the transfer of data between them is not an easy task and defining the most reliable way to translate and exchange information without data loosing is still an open issue. The goal of the present paper is to analyse the complex process of translation from the very precise (and sometimes redundant) information obtainable by the modern survey methodologies for historic buildings (as laser scanner), into the very simplified (may be too much) schemes used to understand their real structural behaviour, with the final aim to contribute to the discussion on reliable methods for cultural heritage knowledge improvement, through empiricism.

Validity, Reliability, and the Questionable Role of Psychometrics in Plastic Surgery

PubMed Central

2014-01-01

Summary: This report examines the meaning of validity and reliability and the role of psychometrics in plastic surgery. Study titles increasingly include the word “valid” to support the authors’ claims. Studies by other investigators may be labeled “not validated.” Validity simply refers to the ability of a device to measure what it intends to measure. Validity is not an intrinsic test property. It is a relative term most credibly assigned by the independent user. Similarly, the word “reliable” is subject to interpretation. In psychometrics, its meaning is synonymous with “reproducible.” The definitions of valid and reliable are analogous to accuracy and precision. Reliability (both the reliability of the data and the consistency of measurements) is a prerequisite for validity. Outcome measures in plastic surgery are intended to be surveys, not tests. The role of psychometric modeling in plastic surgery is unclear, and this discipline introduces difficult jargon that can discourage investigators. Standard statistical tests suffice. The unambiguous term “reproducible” is preferred when discussing data consistency. Study design and methodology are essential considerations when assessing a study’s validity. PMID:25289354

Model of load balancing using reliable algorithm with multi-agent system

NASA Astrophysics Data System (ADS)

Afriansyah, M. F.; Somantri, M.; Riyadi, M. A.

2017-04-01

Massive technology development is linear with the growth of internet users which increase network traffic activity. It also increases load of the system. The usage of reliable algorithm and mobile agent in distributed load balancing is a viable solution to handle the load issue on a large-scale system. Mobile agent works to collect resource information and can migrate according to given task. We propose reliable load balancing algorithm using least time first byte (LFB) combined with information from the mobile agent. In system overview, the methodology consisted of defining identification system, specification requirements, network topology and design system infrastructure. The simulation method for simulated system was using 1800 request for 10 s from the user to the server and taking the data for analysis. Software simulation was based on Apache Jmeter by observing response time and reliability of each server and then compared it with existing method. Results of performed simulation show that the LFB method with mobile agent can perform load balancing with efficient systems to all backend server without bottleneck, low risk of server overload, and reliable.

Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: a practical guide.

PubMed

Bilcke, Joke; Beutels, Philippe; Brisson, Marc; Jit, Mark

2011-01-01

Accounting for uncertainty is now a standard part of decision-analytic modeling and is recommended by many health technology agencies and published guidelines. However, the scope of such analyses is often limited, even though techniques have been developed for presenting the effects of methodological, structural, and parameter uncertainty on model results. To help bring these techniques into mainstream use, the authors present a step-by-step guide that offers an integrated approach to account for different kinds of uncertainty in the same model, along with a checklist for assessing the way in which uncertainty has been incorporated. The guide also addresses special situations such as when a source of uncertainty is difficult to parameterize, resources are limited for an ideal exploration of uncertainty, or evidence to inform the model is not available or not reliable. for identifying the sources of uncertainty that influence results most are also described. Besides guiding analysts, the guide and checklist may be useful to decision makers who need to assess how well uncertainty has been accounted for in a decision-analytic model before using the results to make a decision.

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

PubMed Central

Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems. PMID:27187178

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking.

PubMed

Pârvu, Ovidiu; Gilbert, David

2016-01-01

Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

Methodology Development for Passive Component Reliability Modeling in a Multi-Physics Simulation Environment

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

Aldemir, Tunc; Denning, Richard; Catalyurek, Umit

Reduction in safety margin can be expected as passive structures and components undergo degradation with time. Limitations in the traditional probabilistic risk assessment (PRA) methodology constrain its value as an effective tool to address the impact of aging effects on risk and for quantifying the impact of aging management strategies in maintaining safety margins. A methodology has been developed to address multiple aging mechanisms involving large numbers of components (with possibly statistically dependent failures) within the PRA framework in a computationally feasible manner when the sequencing of events is conditioned on the physical conditions predicted in a simulation environment, suchmore » as the New Generation System Code (NGSC) concept. Both epistemic and aleatory uncertainties can be accounted for within the same phenomenological framework and maintenance can be accounted for in a coherent fashion. The framework accommodates the prospective impacts of various intervention strategies such as testing, maintenance, and refurbishment. The methodology is illustrated with several examples.« less

New analytical methodology for analysing S(IV) species at low pH solutions by one stage titration method (bichromatometry) with a clear colour change. Could potentially replace the state-of-art-method iodometry at low pH analysis due higher accuracy

PubMed Central

Galfi, Istvan; Virtanen, Jorma; Gasik, Michael M.

2017-01-01

A new, faster and more reliable analytical methodology for S(IV) species analysis at low pH solutions by bichromatometry is proposed. For decades the state of the art methodology has been iodometry that is still well justified method for neutral solutions, thus at low pH media possess various side reactions increasing inaccuracy. In contrast, the new methodology has no side reactions at low pH media, requires only one titration step and provides a clear color change if S(IV) species are present in the solution. The method is validated using model solutions with known concentrations and applied to analyses of gaseous SO2 from purged solution in low pH media samples. The results indicate that bichromatometry can accurately analyze SO2 from liquid samples having pH even below 0 relevant to metallurgical industrial processes. PMID:29145479

Reliability analysis of composite structures

NASA Technical Reports Server (NTRS)

Kan, Han-Pin

1992-01-01

A probabilistic static stress analysis methodology has been developed to estimate the reliability of a composite structure. Closed form stress analysis methods are the primary analytical tools used in this methodology. These structural mechanics methods are used to identify independent variables whose variations significantly affect the performance of the structure. Once these variables are identified, scatter in their values is evaluated and statistically characterized. The scatter in applied loads and the structural parameters are then fitted to appropriate probabilistic distribution functions. Numerical integration techniques are applied to compute the structural reliability. The predicted reliability accounts for scatter due to variability in material strength, applied load, fabrication and assembly processes. The influence of structural geometry and mode of failure are also considerations in the evaluation. Example problems are given to illustrate various levels of analytical complexity.

Generalized quantum kinetic expansion: Higher-order corrections to multichromophoric Förster theory

NASA Astrophysics Data System (ADS)

Wu, Jianlan; Gong, Zhihao; Tang, Zhoufei

2015-08-01

For a general two-cluster energy transfer network, a new methodology of the generalized quantum kinetic expansion (GQKE) method is developed, which predicts an exact time-convolution equation for the cluster population evolution under the initial condition of the local cluster equilibrium state. The cluster-to-cluster rate kernel is expanded over the inter-cluster couplings. The lowest second-order GQKE rate recovers the multichromophoric Förster theory (MCFT) rate. The higher-order corrections to the MCFT rate are systematically included using the continued fraction resummation form, resulting in the resummed GQKE method. The reliability of the GQKE methodology is verified in two model systems, revealing the relevance of higher-order corrections.

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

Wixson, J. R.

Root cause analysis (RCA) is an important methodology that can be integrated with the VE Job Plan to generate superior results from the VE Methodology. The point at which RCA is most appropriate is after the function analysis and FAST Model have been built and functions for improvement have been chosen. These functions are then subjected to a simple, but, rigorous RCA to get to the root cause of their deficiencies, whether it is high cost/poor value, poor quality, or poor reliability. Once the most probable causes for these problems have been arrived at, better solutions for improvement can bemore » developed in the creativity phase because the team better understands the problems associated with these functions.« less

Fine reservoir structure modeling based upon 3D visualized stratigraphic correlation between horizontal wells: methodology and its application

NASA Astrophysics Data System (ADS)

Chenghua, Ou; Chaochun, Li; Siyuan, Huang; Sheng, James J.; Yuan, Xu

2017-12-01

As the platform-based horizontal well production mode has been widely applied in petroleum industry, building a reliable fine reservoir structure model by using horizontal well stratigraphic correlation has become very important. Horizontal wells usually extend between the upper and bottom boundaries of the target formation, with limited penetration points. Using these limited penetration points to conduct well deviation correction means the formation depth information obtained is not accurate, which makes it hard to build a fine structure model. In order to solve this problem, a method of fine reservoir structure modeling, based on 3D visualized stratigraphic correlation among horizontal wells, is proposed. This method can increase the accuracy when estimating the depth of the penetration points, and can also effectively predict the top and bottom interfaces in the horizontal penetrating section. Moreover, this method will greatly increase not only the number of points of depth data available, but also the accuracy of these data, which achieves the goal of building a reliable fine reservoir structure model by using the stratigraphic correlation among horizontal wells. Using this method, four 3D fine structure layer models have been successfully built of a specimen shale gas field with platform-based horizontal well production mode. The shale gas field is located to the east of Sichuan Basin, China; the successful application of the method has proven its feasibility and reliability.

Structural design methodologies for ceramic-based material systems

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Chulya, Abhisak; Gyekenyesi, John P.

1991-01-01

One of the primary pacing items for realizing the full potential of ceramic-based structural components is the development of new design methods and protocols. The focus here is on low temperature, fast-fracture analysis of monolithic, whisker-toughened, laminated, and woven ceramic composites. A number of design models and criteria are highlighted. Public domain computer algorithms, which aid engineers in predicting the fast-fracture reliability of structural components, are mentioned. Emphasis is not placed on evaluating the models, but instead is focused on the issues relevant to the current state of the art.

Adaptive Sampling using Support Vector Machines

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

D. Mandelli; C. Smith

2012-11-01

Reliability/safety analysis of stochastic dynamic systems (e.g., nuclear power plants, airplanes, chemical plants) is currently performed through a combination of Event-Tress and Fault-Trees. However, these conventional methods suffer from certain drawbacks: • Timing of events is not explicitly modeled • Ordering of events is preset by the analyst • The modeling of complex accident scenarios is driven by expert-judgment For these reasons, there is currently an increasing interest into the development of dynamic PRA methodologies since they can be used to address the deficiencies of conventional methods listed above.

Stress-Strain Characterization for Reversed Loading Path and Constitutive Modeling for AHSS Springback Predictions

NASA Astrophysics Data System (ADS)

Zhu, Hong; Huang, Mai; Sadagopan, Sriram; Yao, Hong

2017-09-01

With increasing vehicle fuel economy standards, automotive OEMs are widely using various AHSS grades including DP, TRIP, CP and 3rd Gen AHSS to reduce vehicle weight due to their good combination of strength and formability. As one of enabling technologies for AHSS application, the requirement for requiring accurate prediction of springback for cold stamped AHSS parts stimulated a large number of investigations in the past decade with reversed loading path at large strains followed by constitutive modeling. With a spectrum of complex loading histories occurring in production stamping processes, there were many challenges in this field including issues of test data reliability, loading path representability, constitutive model robustness and non-unique constitutive parameter-identification. In this paper, various testing approaches and constitutive modeling will be reviewed briefly and a systematic methodology from stress-strain characterization, constitutive model parameter identification for material card generation will be presented in order to support automotive OEM’s need on virtual stamping. This systematic methodology features a tension-compression test at large strain with robust anti-buckling device with concurrent friction force correction, properly selected loading paths to represent material behavior during different springback modes as well as the 10-parameter Yoshida model with knowledge-based parameter-identification through nonlinear optimization. Validation cases for lab AHSS parts will also be discussed to check applicability of this methodology.

Performance analysis of complex repairable industrial systems using PSO and fuzzy confidence interval based methodology.

PubMed

Garg, Harish

2013-03-01

The main objective of the present paper is to propose a methodology for analyzing the behavior of the complex repairable industrial systems. In real-life situations, it is difficult to find the most optimal design policies for MTBF (mean time between failures), MTTR (mean time to repair) and related costs by utilizing available resources and uncertain data. For this, the availability-cost optimization model has been constructed for determining the optimal design parameters for improving the system design efficiency. The uncertainties in the data related to each component of the system are estimated with the help of fuzzy and statistical methodology in the form of the triangular fuzzy numbers. Using these data, the various reliability parameters, which affects the system performance, are obtained in the form of the fuzzy membership function by the proposed confidence interval based fuzzy Lambda-Tau (CIBFLT) methodology. The computed results by CIBFLT are compared with the existing fuzzy Lambda-Tau methodology. Sensitivity analysis on the system MTBF has also been addressed. The methodology has been illustrated through a case study of washing unit, the main part of the paper industry. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

RICOR's new development of a highly reliable integral rotary cooler: engineering and reliability aspects

NASA Astrophysics Data System (ADS)

Filis, Avishai; Pundak, Nachman; Barak, Moshe; Porat, Ze'ev; Jaeger, Mordechai

2011-06-01

The growing demand for EO applications that work around the clock 24hr/7days a week, such as in border surveillance systems, emphasizes the need for a highly reliable cryocooler having increased operational availability and decreased integrated system Life Cycle (ILS) cost. In order to meet this need RICOR has developed a new rotary Stirling cryocooler, model K508N, intended to double the K508's operating MTTF achieving 20,000 operating MTTF hours. The K508N employs RICOR's latest mechanical design technologies such as optimized bearings and greases, bearings preloading, advanced seals, laser welded cold finger and robust design structure with increased natural frequency compared to the K508 model. The cooler enhanced MTTF was demonstrated by a Validation and Verification (V&V) plan comprising analytical means and a comparative accelerated life test between the standard K508 and the K508N models. Particularly, point estimate and confidence interval for the MTTF improvement factor where calculated periodically during and after the test. The (V&V) effort revealed that the K508N meets its MTTF design goal. The paper will focus on the technical and engineering aspects of the new design. In addition it will discuss the market needs and expectations, investigate the reliability data of the present reference K508 model; and report the accelerate life test data and the statistical analysis methodology as well as its underlying assumptions and results.

An experimental procedure to determine heat transfer properties of turbochargers

NASA Astrophysics Data System (ADS)

Serrano, J. R.; Olmeda, P.; Páez, A.; Vidal, F.

2010-03-01

Heat transfer phenomena in turbochargers have been a subject of investigation due to their importance for the correct determination of compressor real work when modelling. The commonly stated condition of adiabaticity for turbochargers during normal operation of an engine has been revaluated because important deviations from adiabatic behaviour have been stated in many studies in this issue especially when the turbocharger is running at low rotational speeds/loads. The deviations mentioned do not permit us to assess properly the turbine and compressor efficiencies since the pure aerodynamic effects cannot be separated from the non-desired heat transfer due to the presence of both phenomena during turbocharger operation. The correction of the aforesaid facts is necessary to properly feed engine models with reliable information and in this way increase the quality of the results in any modelling process. The present work proposes a thermal characterization methodology successfully applied in a turbocharger for a passenger car which is based on the physics of the turbocharger. Its application helps to understand the thermal behaviour of the turbocharger, and the results obtained constitute vital information for future modelling efforts which involve the use of the information obtained from the proposed methodology. The conductance values obtained from the proposed methodology have been applied to correct a procedure for measuring the mechanical efficiency of the tested turbocharger.

Analytical Round Robin for Elastic-Plastic Analysis of Surface Cracked Plates: Phase I Results

NASA Technical Reports Server (NTRS)

Wells, D. N.; Allen, P. A.

2012-01-01

An analytical round robin for the elastic-plastic analysis of surface cracks in flat plates was conducted with 15 participants. Experimental results from a surface crack tension test in 2219-T8 aluminum plate provided the basis for the inter-laboratory study (ILS). The study proceeded in a blind fashion given that the analysis methodology was not specified to the participants, and key experimental results were withheld. This approach allowed the ILS to serve as a current measure of the state of the art for elastic-plastic fracture mechanics analysis. The analytical results and the associated methodologies were collected for comparison, and sources of variability were studied and isolated. The results of the study revealed that the J-integral analysis methodology using the domain integral method is robust, providing reliable J-integral values without being overly sensitive to modeling details. General modeling choices such as analysis code, model size (mesh density), crack tip meshing, or boundary conditions, were not found to be sources of significant variability. For analyses controlled only by far-field boundary conditions, the greatest source of variability in the J-integral assessment is introduced through the constitutive model. This variability can be substantially reduced by using crack mouth opening displacements to anchor the assessment. Conclusions provide recommendations for analysis standardization.

Bulk Fuel Pricing: DOD Needs to Take Additional Actions to Establish a More Reliable Methodology

DTIC Science & Technology

2015-11-19

Page 1 GAO-16-78R Bulk Fuel Pricing 441 G St. N.W. Washington, DC 20548 November 19, 2015 The Honorable Ashton Carter The Secretary of...Defense Bulk Fuel Pricing : DOD Needs to Take Additional Actions to Establish a More Reliable Methodology Dear Secretary Carter: Each fiscal...year, the Office of the Under Secretary of Defense (Comptroller), in coordination with the Defense Logistics Agency, sets a standard price per barrel

Allocating SMART Reliability and Maintainability Goals to NASA Ground Systems

NASA Technical Reports Server (NTRS)

Gillespie, Amanda; Monaghan, Mark

2013-01-01

This paper will describe the methodology used to allocate Reliability and Maintainability (R&M) goals to Ground Systems Development and Operations (GSDO) subsystems currently being designed or upgraded.

The Use of Object-Oriented Analysis Methods in Surety Analysis

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

Craft, Richard L.; Funkhouser, Donald R.; Wyss, Gregory D.

1999-05-01

Object-oriented analysis methods have been used in the computer science arena for a number of years to model the behavior of computer-based systems. This report documents how such methods can be applied to surety analysis. By embodying the causality and behavior of a system in a common object-oriented analysis model, surety analysts can make the assumptions that underlie their models explicit and thus better communicate with system designers. Furthermore, given minor extensions to traditional object-oriented analysis methods, it is possible to automatically derive a wide variety of traditional risk and reliability analysis methods from a single common object model. Automaticmore » model extraction helps ensure consistency among analyses and enables the surety analyst to examine a system from a wider variety of viewpoints in a shorter period of time. Thus it provides a deeper understanding of a system's behaviors and surety requirements. This report documents the underlying philosophy behind the common object model representation, the methods by which such common object models can be constructed, and the rules required to interrogate the common object model for derivation of traditional risk and reliability analysis models. The methodology is demonstrated in an extensive example problem.« less

Methodologies for Crawler Based Web Surveys.

ERIC Educational Resources Information Center

Thelwall, Mike

2002-01-01

Describes Web survey methodologies used to study the content of the Web, and discusses search engines and the concept of crawling the Web. Highlights include Web page selection methodologies; obstacles to reliable automatic indexing of Web sites; publicly indexable pages; crawling parameters; and tests for file duplication. (Contains 62…

Reporting and methodological quality of survival analysis in articles published in Chinese oncology journals

PubMed Central

Zhu, Xiaoyan; Zhou, Xiaobin; Zhang, Yuan; Sun, Xiao; Liu, Haihua; Zhang, Yingying

2017-01-01

Abstract Survival analysis methods have gained widespread use in the filed of oncology. For achievement of reliable results, the methodological process and report quality is crucial. This review provides the first examination of methodological characteristics and reporting quality of survival analysis in articles published in leading Chinese oncology journals. To examine methodological and reporting quality of survival analysis, to identify some common deficiencies, to desirable precautions in the analysis, and relate advice for authors, readers, and editors. A total of 242 survival analysis articles were included to be evaluated from 1492 articles published in 4 leading Chinese oncology journals in 2013. Articles were evaluated according to 16 established items for proper use and reporting of survival analysis. The application rates of Kaplan–Meier, life table, log-rank test, Breslow test, and Cox proportional hazards model (Cox model) were 91.74%, 3.72%, 78.51%, 0.41%, and 46.28%, respectively, no article used the parametric method for survival analysis. Multivariate Cox model was conducted in 112 articles (46.28%). Follow-up rates were mentioned in 155 articles (64.05%), of which 4 articles were under 80% and the lowest was 75.25%, 55 articles were100%. The report rates of all types of survival endpoint were lower than 10%. Eleven of 100 articles which reported a loss to follow-up had stated how to treat it in the analysis. One hundred thirty articles (53.72%) did not perform multivariate analysis. One hundred thirty-nine articles (57.44%) did not define the survival time. Violations and omissions of methodological guidelines included no mention of pertinent checks for proportional hazard assumption; no report of testing for interactions and collinearity between independent variables; no report of calculation method of sample size. Thirty-six articles (32.74%) reported the methods of independent variable selection. The above defects could make potentially inaccurate, misleading of the reported results, or difficult to interpret. There are gaps in the conduct and reporting of survival analysis in studies published in Chinese oncology journals, severe deficiencies were noted. More endorsement by journals of the report guideline for survival analysis may improve articles quality, and the dissemination of reliable evidence to oncology clinicians. We recommend authors, readers, reviewers, and editors to consider survival analysis more carefully and cooperate more closely with statisticians and epidemiologists. PMID:29390340

An Assessment Methodology to Evaluate In-Flight Engine Health Management Effectiveness

NASA Astrophysics Data System (ADS)

Maggio, Gaspare; Belyeu, Rebecca; Pelaccio, Dennis G.

2002-01-01

flight effectiveness of candidate engine health management system concepts. A next generation engine health management system will be required to be both reliable and robust in terms of anomaly detection capability. The system must be able to operate successfully in the hostile, high-stress engine system environment. This implies that its system components, such as the instrumentation, process and control, and vehicle interface and support subsystems, must be highly reliable. Additionally, the system must be able to address a vast range of possible engine operation anomalies through a host of different types of measurements supported by a fast algorithm/architecture processing capability that can identify "true" (real) engine operation anomalies. False anomaly condition reports for such a system must be essentially eliminated. The accuracy of identifying only real anomaly conditions has been an issue with the Space Shuttle Main Engine (SSME) in the past. Much improvement in many of the technologies to address these areas is required. The objectives of this study were to identify and demonstrate a consistent assessment methodology that can evaluate the capability of next generation engine health management system concepts to respond in a correct, timely manner to alleviate an operational engine anomaly condition during flight. Science Applications International Corporation (SAIC), with support from NASA Marshall Space Flight Center, identified a probabilistic modeling approach to assess engine health management system concept effectiveness using a deterministic anomaly-time event assessment modeling approach that can be applied in the engine preliminary design stage of development to assess engine health management system concept effectiveness. Much discussion in this paper focuses on the formulation and application approach in performing this assessment. This includes detailed discussion of key modeling assumptions, the overall assessment methodology approach identified, and the identification of key supporting engine health management system concept design/operation and fault mode information required to utilize this methodology. At the paper's conclusion, discussion focuses on a demonstration benchmark study that applied this methodology to the current SSME health management system. A summary of study results and lessons learned are provided. Recommendations for future work in this area are also identified at the conclusion of the paper. * Please direct all correspondence/communication pertaining to this paper to Dennis G. Pelaccio, Science

Scale of attitudes toward alcohol - Spanish version: evidences of validity and reliability 1

PubMed Central

Ramírez, Erika Gisseth León; de Vargas, Divane

2017-01-01

ABSTRACT Objective: validate the Scale of attitudes toward alcohol, alcoholism and individuals with alcohol use disorders in its Spanish version. Method: methodological study, involving 300 Colombian nurses. Adopting the classical theory, confirmatory factor analysis was applied without prior examination, based on the strong historical evidence of the factorial structure of the original scale to determine the construct validity of this Spanish version. To assess the reliability, Cronbach’s Alpha and Mc Donalid’s Omega coefficients were used. Results: the confirmatory factor analysis indicated the good fit of the scale model in a four-factor distribution, with a cut-off point at 3.2, demonstrating 66.7% of sensitivity. Conclusions: the Scale of attitudes toward alcohol, alcoholism and individuals with alcohol use disorders in Spanish presented robust psychometric qualities, affirming that the instrument possesses a solid factorial structure and reliability and is capable of precisely measuring the nurses’ atittudes towards the phenomenon proposed. PMID:28793126

Verification methodology for fault-tolerant, fail-safe computers applied to maglev control computer systems. Final report, July 1991-May 1993

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

Lala, J.H.; Nagle, G.A.; Harper, R.E.

1993-05-01

The Maglev control computer system should be designed to verifiably possess high reliability and safety as well as high availability to make Maglev a dependable and attractive transportation alternative to the public. A Maglev control computer system has been designed using a design-for-validation methodology developed earlier under NASA and SDIO sponsorship for real-time aerospace applications. The present study starts by defining the maglev mission scenario and ends with the definition of a maglev control computer architecture. Key intermediate steps included definitions of functional and dependability requirements, synthesis of two candidate architectures, development of qualitative and quantitative evaluation criteria, and analyticalmore » modeling of the dependability characteristics of the two architectures. Finally, the applicability of the design-for-validation methodology was also illustrated by applying it to the German Transrapid TR07 maglev control system.« less

Sliding Mode Approaches for Robust Control, State Estimation, Secure Communication, and Fault Diagnosis in Nuclear Systems

NASA Astrophysics Data System (ADS)

Ablay, Gunyaz

Using traditional control methods for controller design, parameter estimation and fault diagnosis may lead to poor results with nuclear systems in practice because of approximations and uncertainties in the system models used, possibly resulting in unexpected plant unavailability. This experience has led to an interest in development of robust control, estimation and fault diagnosis methods. One particularly robust approach is the sliding mode control methodology. Sliding mode approaches have been of great interest and importance in industry and engineering in the recent decades due to their potential for producing economic, safe and reliable designs. In order to utilize these advantages, sliding mode approaches are implemented for robust control, state estimation, secure communication and fault diagnosis in nuclear plant systems. In addition, a sliding mode output observer is developed for fault diagnosis in dynamical systems. To validate the effectiveness of the methodologies, several nuclear plant system models are considered for applications, including point reactor kinetics, xenon concentration dynamics, an uncertain pressurizer model, a U-tube steam generator model and a coupled nonlinear nuclear reactor model.

Reliability Sensitivity Analysis and Design Optimization of Composite Structures Based on Response Surface Methodology

NASA Technical Reports Server (NTRS)

Rais-Rohani, Masoud

2003-01-01

This report discusses the development and application of two alternative strategies in the form of global and sequential local response surface (RS) techniques for the solution of reliability-based optimization (RBO) problems. The problem of a thin-walled composite circular cylinder under axial buckling instability is used as a demonstrative example. In this case, the global technique uses a single second-order RS model to estimate the axial buckling load over the entire feasible design space (FDS) whereas the local technique uses multiple first-order RS models with each applied to a small subregion of FDS. Alternative methods for the calculation of unknown coefficients in each RS model are explored prior to the solution of the optimization problem. The example RBO problem is formulated as a function of 23 uncorrelated random variables that include material properties, thickness and orientation angle of each ply, cylinder diameter and length, as well as the applied load. The mean values of the 8 ply thicknesses are treated as independent design variables. While the coefficients of variation of all random variables are held fixed, the standard deviations of ply thicknesses can vary during the optimization process as a result of changes in the design variables. The structural reliability analysis is based on the first-order reliability method with reliability index treated as the design constraint. In addition to the probabilistic sensitivity analysis of reliability index, the results of the RBO problem are presented for different combinations of cylinder length and diameter and laminate ply patterns. The two strategies are found to produce similar results in terms of accuracy with the sequential local RS technique having a considerably better computational efficiency.

A Passive System Reliability Analysis for a Station Blackout

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

Brunett, Acacia; Bucknor, Matthew; Grabaskas, David

2015-05-03

The latest iterations of advanced reactor designs have included increased reliance on passive safety systems to maintain plant integrity during unplanned sequences. While these systems are advantageous in reducing the reliance on human intervention and availability of power, the phenomenological foundations on which these systems are built require a novel approach to a reliability assessment. Passive systems possess the unique ability to fail functionally without failing physically, a result of their explicit dependency on existing boundary conditions that drive their operating mode and capacity. Argonne National Laboratory is performing ongoing analyses that demonstrate various methodologies for the characterization of passivemore » system reliability within a probabilistic framework. Two reliability analysis techniques are utilized in this work. The first approach, the Reliability Method for Passive Systems, provides a mechanistic technique employing deterministic models and conventional static event trees. The second approach, a simulation-based technique, utilizes discrete dynamic event trees to treat time- dependent phenomena during scenario evolution. For this demonstration analysis, both reliability assessment techniques are used to analyze an extended station blackout in a pool-type sodium fast reactor (SFR) coupled with a reactor cavity cooling system (RCCS). This work demonstrates the entire process of a passive system reliability analysis, including identification of important parameters and failure metrics, treatment of uncertainties and analysis of results.« less

Designing trials for pressure ulcer risk assessment research: methodological challenges.

PubMed

Balzer, K; Köpke, S; Lühmann, D; Haastert, B; Kottner, J; Meyer, G

2013-08-01

For decades various pressure ulcer risk assessment scales (PURAS) have been developed and implemented into nursing practice despite uncertainty whether use of these tools helps to prevent pressure ulcers. According to current methodological standards, randomised controlled trials (RCTs) are required to conclusively determine the clinical efficacy and safety of this risk assessment strategy. In these trials, PURAS-aided risk assessment has to be compared to nurses' clinical judgment alone in terms of its impact on pressure ulcer incidence and adverse outcomes. However, RCTs evaluating diagnostic procedures are prone to specific risks of bias and threats to the statistical power which may challenge their validity and feasibility. This discussion paper critically reflects on the rigour and feasibility of experimental research needed to substantiate the clinical efficacy of PURAS-aided risk assessment. Based on reflections of the methodological literature, a critical appraisal of available trials on this subject and an analysis of a protocol developed for a methodologically robust cluster-RCT, this paper arrives at the following conclusions: First, available trials do not provide reliable estimates of the impact of PURAS-aided risk assessment on pressure ulcer incidence compared to nurses' clinical judgement alone due to serious risks of bias and insufficient sample size. Second, it seems infeasible to assess this impact by means of rigorous experimental studies since sample size would become extremely high if likely threats to validity and power are properly taken into account. Third, means of evidence linkages seem to currently be the most promising approaches for evaluating the clinical efficacy and safety of PURAS-aided risk assessment. With this kind of secondary research, the downstream effect of use of PURAS on pressure ulcer incidence could be modelled by combining best available evidence for single parts of this pathway. However, to yield reliable modelling results, more robust experimental research evaluating specific parts of the pressure ulcer risk assessment-prevention pathway is needed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mission Reliability Estimation for Repairable Robot Teams

NASA Technical Reports Server (NTRS)

Trebi-Ollennu, Ashitey; Dolan, John; Stancliff, Stephen

2010-01-01

A mission reliability estimation method has been designed to translate mission requirements into choices of robot modules in order to configure a multi-robot team to have high reliability at minimal cost. In order to build cost-effective robot teams for long-term missions, one must be able to compare alternative design paradigms in a principled way by comparing the reliability of different robot models and robot team configurations. Core modules have been created including: a probabilistic module with reliability-cost characteristics, a method for combining the characteristics of multiple modules to determine an overall reliability-cost characteristic, and a method for the generation of legitimate module combinations based on mission specifications and the selection of the best of the resulting combinations from a cost-reliability standpoint. The developed methodology can be used to predict the probability of a mission being completed, given information about the components used to build the robots, as well as information about the mission tasks. In the research for this innovation, sample robot missions were examined and compared to the performance of robot teams with different numbers of robots and different numbers of spare components. Data that a mission designer would need was factored in, such as whether it would be better to have a spare robot versus an equivalent number of spare parts, or if mission cost can be reduced while maintaining reliability using spares. This analytical model was applied to an example robot mission, examining the cost-reliability tradeoffs among different team configurations. Particularly scrutinized were teams using either redundancy (spare robots) or repairability (spare components). Using conservative estimates of the cost-reliability relationship, results show that it is possible to significantly reduce the cost of a robotic mission by using cheaper, lower-reliability components and providing spares. This suggests that the current design paradigm of building a minimal number of highly robust robots may not be the best way to design robots for extended missions.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

PubMed

Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

2015-02-01

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

A systematic review of the collaborative clinical education model to inform speech-language pathology practice.

PubMed

Briffa, Charmaine; Porter, Judi

2013-12-01

A shortage of clinical education placements for allied health students internationally has led to the need to explore innovative models of clinical education. The collaborative model where one clinical educator supervises two or more students completing a clinical placement concurrently is one model enabling expansion of student placements. The aims of this review were to investigate advantages and disadvantages of the collaborative model and to explore its implementation across allied health. A systematic search of the literature was conducted using three electronic databases (CINAHL, Medline, and Embase). Two independent reviewers evaluated studies for methodological quality. Seventeen studies met inclusion/exclusion criteria. Advantages and disadvantages identified were consistent across disciplines. A key advantage of the model was the opportunity afforded for peer learning, whilst a frequently reported disadvantage was reduced time for individual supervision of students. The methodological quality of many included studies was poor, impacting on interpretation of the evidence base. Insufficient data were provided on how the model was implemented across studies. There is a need for high quality research to guide implementation of this model across a wider range of allied health disciplines and to determine educational outcomes using reliable and validated measures.

Comment on Hall et al. (2017), "How to Choose Between Measures of Tinnitus Loudness for Clinical Research? A Report on the Reliability and Validity of an Investigator-Administered Test and a Patient-Reported Measure Using Baseline Data Collected in a Phase IIa Drug Trial".

PubMed

Sabour, Siamak

2018-03-08

The purpose of this letter, in response to Hall, Mehta, and Fackrell (2017), is to provide important knowledge about methodology and statistical issues in assessing the reliability and validity of an audiologist-administered tinnitus loudness matching test and a patient-reported tinnitus loudness rating. The author uses reference textbooks and published articles regarding scientific assessment of the validity and reliability of a clinical test to discuss the statistical test and the methodological approach in assessing validity and reliability in clinical research. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess reliability and validity. The qualitative variables of sensitivity, specificity, positive predictive value, negative predictive value, false positive and false negative rates, likelihood ratio positive and likelihood ratio negative, as well as odds ratio (i.e., ratio of true to false results), are the most appropriate estimates to evaluate validity of a test compared to a gold standard. In the case of quantitative variables, depending on distribution of the variable, Pearson r or Spearman rho can be applied. Diagnostic accuracy (validity) and diagnostic precision (reliability or agreement) are two completely different methodological issues. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess validity.

Stereotype Threat and College Academic Performance: A Latent Variables Approach*

PubMed Central

Owens, Jayanti; Massey, Douglas S.

2013-01-01

Stereotype threat theory has gained experimental and survey-based support in helping explain the academic underperformance of minority students at selective colleges and universities. Stereotype threat theory states that minority students underperform because of pressures created by negative stereotypes about their racial group. Past survey-based studies, however, are characterized by methodological inefficiencies and potential biases: key theoretical constructs have only been measured using summed indicators and predicted relationships modeled using ordinary least squares. Using the National Longitudinal Survey of Freshman, this study overcomes previous methodological shortcomings by developing a latent construct model of stereotype threat. Theoretical constructs and equations are estimated simultaneously from multiple indicators, yielding a more reliable, valid, and parsimonious test of key propositions. Findings additionally support the view that social stigma can indeed have strong negative effects on the academic performance of pejoratively stereotyped racial-minority group members, not only in laboratory settings, but also in the real world. PMID:23950616

Using information Theory in Optimal Test Point Selection for Health Management in NASA's Exploration Vehicles

NASA Technical Reports Server (NTRS)

Mehr, Ali Farhang; Tumer, Irem

2005-01-01

In this paper, we will present a new methodology that measures the "worth" of deploying an additional testing instrument (sensor) in terms of the amount of information that can be retrieved from such measurement. This quantity is obtained using a probabilistic model of RLV's that has been partially developed in the NASA Ames Research Center. A number of correlated attributes are identified and used to obtain the worth of deploying a sensor in a given test point from an information-theoretic viewpoint. Once the information-theoretic worth of sensors is formulated and incorporated into our general model for IHM performance, the problem can be formulated as a constrained optimization problem where reliability and operational safety of the system as a whole is considered. Although this research is conducted specifically for RLV's, the proposed methodology in its generic form can be easily extended to other domains of systems health monitoring.

Optimization of ultrasonic-assisted extraction of bioactive alkaloid compounds from rhizoma coptidis (Coptis chinensis Franch.) using response surface methodology.

PubMed

Teng, Hui; Choi, Yong Hee

2014-01-01

The optimum extraction conditions for the maximum recovery of total alkaloid content (TAC), berberine content (BC), palmatine content (PC), and the highest antioxidant capacity (AC) from rhizoma coptidis subjected to ultrasonic-assisted extraction (UAE) were determined using response surface methodology (RSM). Central composite design (CCD) with three variables and five levels was employed, and response surface plots were constructed in accordance with a second order polynomial model. Analysis of variance (ANOVA) showed that the quadratic model was well fitted and significant for responses of TAC, BC, PC, and AA. The optimum conditions obtained through the overlapped contour plot were as follows: ethanol concentration of 59%, extraction time of 46.57min, and temperature of 66.22°C. Verification experiment was carried out, and no significant difference was found between observed and estimated values for each response, suggesting that the estimated models were reliable and valid for UAE of alkaloids. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

HTGR plant availability and reliability evaluations. Volume I. Summary of evaluations

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

Cadwallader, G.J.; Hannaman, G.W.; Jacobsen, F.K.

1976-12-01

The report (1) describes a reliability assessment methodology for systematically locating and correcting areas which may contribute to unavailability of new and uniquely designed components and systems, (2) illustrates the methodology by applying it to such components in a high-temperature gas-cooled reactor (Public Service Company of Colorado's Fort St. Vrain 330-MW(e) HTGR), and (3) compares the results of the assessment with actual experience. The methodology can be applied to any component or system; however, it is particularly valuable for assessments of components or systems which provide essential functions, or the failure or mishandling of which could result in relatively largemore » economic losses.« less

Optimal maintenance of a multi-unit system under dependencies

NASA Astrophysics Data System (ADS)

Sung, Ho-Joon

The availability, or reliability, of an engineering component greatly influences the operational cost and safety characteristics of a modern system over its life-cycle. Until recently, the reliance on past empirical data has been the industry-standard practice to develop maintenance policies that provide the minimum level of system reliability. Because such empirically-derived policies are vulnerable to unforeseen or fast-changing external factors, recent advancements in the study of topic on maintenance, which is known as optimal maintenance problem, has gained considerable interest as a legitimate area of research. An extensive body of applicable work is available, ranging from those concerned with identifying maintenance policies aimed at providing required system availability at minimum possible cost, to topics on imperfect maintenance of multi-unit system under dependencies. Nonetheless, these existing mathematical approaches to solve for optimal maintenance policies must be treated with caution when considered for broader applications, as they are accompanied by specialized treatments to ease the mathematical derivation of unknown functions in both objective function and constraint for a given optimal maintenance problem. These unknown functions are defined as reliability measures in this thesis, and theses measures (e.g., expected number of failures, system renewal cycle, expected system up time, etc.) do not often lend themselves to possess closed-form formulas. It is thus quite common to impose simplifying assumptions on input probability distributions of components' lifetime or repair policies. Simplifying the complex structure of a multi-unit system to a k-out-of-n system by neglecting any sources of dependencies is another commonly practiced technique intended to increase the mathematical tractability of a particular model. This dissertation presents a proposal for an alternative methodology to solve optimal maintenance problems by aiming to achieve the same end-goals as Reliability Centered Maintenance (RCM). RCM was first introduced to the aircraft industry in an attempt to bridge the gap between the empirically-driven and theory-driven approaches to establishing optimal maintenance policies. Under RCM, qualitative processes that enable the prioritizing of functions based on the criticality and influence would be combined with mathematical modeling to obtain the optimal maintenance policies. Where this thesis work deviates from RCM is its proposal to directly apply quantitative processes to model the reliability measures in optimal maintenance problem. First, Monte Carlo (MC) simulation, in conjunction with a pre-determined Design of Experiments (DOE) table, can be used as a numerical means of obtaining the corresponding discrete simulated outcomes of the reliability measures based on the combination of decision variables (e.g., periodic preventive maintenance interval, trigger age for opportunistic maintenance, etc.). These discrete simulation results can then be regressed as Response Surface Equations (RSEs) with respect to the decision variables. Such an approach to represent the reliability measures with continuous surrogate functions (i.e., the RSEs) not only enables the application of the numerical optimization technique to solve for optimal maintenance policies, but also obviates the need to make mathematical assumptions or impose over-simplifications on the structure of a multi-unit system for the sake of mathematical tractability. The applicability of the proposed methodology to a real-world optimal maintenance problem is showcased through its application to a Time Limited Dispatch (TLD) of Full Authority Digital Engine Control (FADEC) system. In broader terms, this proof-of-concept exercise can be described as a constrained optimization problem, whose objective is to identify the optimal system inspection interval that guarantees a certain level of availability for a multi-unit system. A variety of reputable numerical techniques were used to model the problem as accurately as possible, including algorithms for the MC simulation, imperfect maintenance model from quasi renewal processes, repair time simulation, and state transition rules. Variance Reduction Techniques (VRTs) were also used in an effort to enhance MC simulation efficiency. After accurate MC simulation results are obtained, the RSEs are generated based on the goodness-of-fit measure to yield as parsimonious model as possible to construct the optimization problem. Under the assumption of constant failure rate for lifetime distributions, the inspection interval from the proposed methodology was found to be consistent with the one from the common approach used in industry that leverages Continuous Time Markov Chain (CTMC). While the latter does not consider maintenance cost settings, the proposed methodology enables an operator to consider different types of maintenance cost settings, e.g., inspection cost, system corrective maintenance cost, etc., to result in more flexible maintenance policies. When the proposed methodology was applied to the same TLD of FADEC example, but under the more generalized assumption of strictly Increasing Failure Rate (IFR) for lifetime distribution, it was shown to successfully capture component wear-out, as well as the economic dependencies among the system components.

Implementing and Evaluating a National Certification Technical Skills Examination: The Colorectal Objective Structured Assessment of Technical Skill.

PubMed

de Montbrun, Sandra; Roberts, Patricia L; Satterthwaite, Lisa; MacRae, Helen

2016-07-01

To implement the Colorectal Objective Structured Assessment of Technical skill (COSATS) into American Board of Colon and Rectal Surgery (ABCRS) certification and build evidence of validity for the interpretation of the scores of this high stakes assessment tool. Currently, technical skill assessment is not a formal component of board certification. With the technical demands of surgical specialties, documenting competence in technical skill at the time of certification with a valid tool is ideal. In September 2014, the COSATS was a mandatory component of ABCRS certification. Seventy candidates took the examination, with their performance evaluated by expert colorectal surgeons using a task-specific checklist, global rating scale, and overall performance scale. Passing scores were set and compared using 2 standard setting methodologies, using a compensatory and conjunctive model. Inter-rater reliability and the reliability of the pass/fail decision were calculated using Cronbach alpha and Subkoviak methodology, respectively. Overall COSATS scores and pass/fail status were compared with results on the ABCRS oral examination. The pass rate ranged from 85.7% to 90%. Inter-rater reliability (0.85) and reliability of the pass/fail decision (0.87 and 0.84) were high. A low positive correlation (r= 0.25) was seen between the COSATS and oral examination. All individuals who failed the COSATS passed the ABCRS oral examination. COSATS is the first technical skill examination used in national surgical board certification. This study suggests that the current certification process may be failing to identify individuals who have demonstrated technical deficiencies on this standardized assessment tool.

Fatigue criterion to system design, life and reliability

NASA Technical Reports Server (NTRS)

Zaretsky, E. V.

1985-01-01

A generalized methodology to structural life prediction, design, and reliability based upon a fatigue criterion is advanced. The life prediction methodology is based in part on work of W. Weibull and G. Lundberg and A. Palmgren. The approach incorporates the computed life of elemental stress volumes of a complex machine element to predict system life. The results of coupon fatigue testing can be incorporated into the analysis allowing for life prediction and component or structural renewal rates with reasonable statistical certainty.

Methodology for Software Reliability Prediction. Volume 1.

DTIC Science & Technology

1987-11-01

SPACECRAFT 0 MANNED SPACECRAFT B ATCH SYSTEM AIRBORNE AVIONICS 0 UNMANNED EVENT C014TROL a REAL TIME CLOSED 0 UNMANNED SPACECRAFT LOOP OPERATINS SPACECRAFT...software reliability. A Software Reliability Measurement Framework was established which spans the life cycle of a software system and includes the...specification, prediction, estimation, and assessment of software reliability. Data from 59 systems , representing over 5 million lines of code, were

Evaluating the uncertainty of predicting future climate time series at the hourly time scale

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2011-12-01

A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.

Prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy: a systematic review and external validation study.

PubMed

Hilkens, N A; Algra, A; Greving, J P

2016-01-01

ESSENTIALS: Prediction models may help to identify patients at high risk of bleeding on antiplatelet therapy. We identified existing prediction models for bleeding and validated them in patients with cerebral ischemia. Five prediction models were identified, all of which had some methodological shortcomings. Performance in patients with cerebral ischemia was poor. Background Antiplatelet therapy is widely used in secondary prevention after a transient ischemic attack (TIA) or ischemic stroke. Bleeding is the main adverse effect of antiplatelet therapy and is potentially life threatening. Identification of patients at increased risk of bleeding may help target antiplatelet therapy. This study sought to identify existing prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy and evaluate their performance in patients with cerebral ischemia. We systematically searched PubMed and Embase for existing prediction models up to December 2014. The methodological quality of the included studies was assessed with the CHARMS checklist. Prediction models were externally validated in the European Stroke Prevention Study 2, comprising 6602 patients with a TIA or ischemic stroke. We assessed discrimination and calibration of included prediction models. Five prediction models were identified, of which two were developed in patients with previous cerebral ischemia. Three studies assessed major bleeding, one studied intracerebral hemorrhage and one gastrointestinal bleeding. None of the studies met all criteria of good quality. External validation showed poor discriminative performance, with c-statistics ranging from 0.53 to 0.64 and poor calibration. A limited number of prediction models is available that predict intracranial hemorrhage or major bleeding in patients on antiplatelet therapy. The methodological quality of the models varied, but was generally low. Predictive performance in patients with cerebral ischemia was poor. In order to reliably predict the risk of bleeding in patients with cerebral ischemia, development of a prediction model according to current methodological standards is needed. © 2015 International Society on Thrombosis and Haemostasis.

Reliability and precision of pellet-group counts for estimating landscape-level deer density

Treesearch

David S. deCalesta

2013-01-01

This study provides hitherto unavailable methodology for reliably and precisely estimating deer density within forested landscapes, enabling quantitative rather than qualitative deer management. Reliability and precision of the deer pellet-group technique were evaluated in 1 small and 2 large forested landscapes. Density estimates, adjusted to reflect deer harvest and...

Complexity, Representation and Practice: Case Study as Method and Methodology

ERIC Educational Resources Information Center

Miles, Rebecca

2015-01-01

While case study is considered a common approach to examining specific and particular examples in research disciplines such as law, medicine and psychology, in the social sciences case study is often treated as a lesser, flawed or undemanding methodology which is less valid, reliable or theoretically rigorous than other methodologies. Building on…

Psychometric evaluation of commonly used game-specific skills tests in rugby: A systematic review

PubMed Central

Oorschot, Sander; Chiwaridzo, Matthew; CM Smits-Engelsman, Bouwien

2017-01-01

Objectives To (1) give an overview of commonly used game-specific skills tests in rugby and (2) evaluate available psychometric information of these tests. Methods The databases PubMed, MEDLINE CINAHL and Africa Wide information were systematically searched for articles published between January 1995 and March 2017. First, commonly used game-specific skills tests were identified. Second, the available psychometrics of these tests were evaluated and the methodological quality of the studies assessed using the Consensus-based Standards for the selection of health Measurement Instruments checklist. Studies included in the first step had to report detailed information on the construct and testing procedure of at least one game-specific skill, and studies included in the second step had additionally to report at least one psychometric property evaluating reliability, validity or responsiveness. Results 287 articles were identified in the first step, of which 30 articles met the inclusion criteria and 64 articles were identified in the second step of which 10 articles were included. Reactive agility, tackling and simulated rugby games were the most commonly used tests. All 10 studies reporting psychometrics reported reliability outcomes, revealing mainly strong evidence. However, all studies scored poor or fair on methodological quality. Four studies reported validity outcomes in which mainly moderate evidence was indicated, but all articles had fair methodological quality. Conclusion Game-specific skills tests indicated mainly high reliability and validity evidence, but the studies lacked methodological quality. Reactive agility seems to be a promising domain, but the specific tests need further development. Future high methodological quality studies are required in order to develop valid and reliable test batteries for rugby talent identification. Trial registration number PROSPERO CRD42015029747. PMID:29259812

Developing Mathematical Provisions for Assessment of Liquid Hydrocarbon Emissions in Emergency Situations

NASA Astrophysics Data System (ADS)

Zemenkova, M. Yu; Zemenkov, Yu D.; Shantarin, V. D.

2016-10-01

The paper reviews the development of methodology for calculation of hydrocarbon emissions during seepage and evaporation to monitor the reliability and safety of hydrocarbon storage and transportation. The authors have analyzed existing methods, models and techniques for assessing the amount of evaporated oil. Models used for predicting the material balance of multicomponent two-phase systems have been discussed. The results of modeling the open-air hydrocarbon evaporation from an oil spill are provided and exemplified by an emergency pit. Dependences and systems of differential equations have been obtained to assess parameters of mass transfer from the open surface of a liquid multicomponent mixture.

Battery Pack Life Estimation through Cell Degradation Data and Pack Thermal Modeling for BAS+ Li-Ion Batteries. Cooperative Research and Development Final Report, CRADA Number CRD-12-489

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

Smith, Kandler

Battery Life estimation is one of the key inputs required for Hybrid applications for all GM Hybrid/EV/EREV/PHEV programs. For each Hybrid vehicle program, GM has instituted multi-parameter Design of Experiments generating test data at Cell level and also Pack level on a reduced basis. Based on experience, generating test data on a pack level is found to be very expensive, resource intensive and sometimes less reliable. The proposed collaborative project will focus on a methodology to estimate Battery life based on cell degradation data combined with pack thermal modeling. NREL has previously developed cell-level battery aging models and pack-level thermal/electricalmore » network models, though these models are currently not integrated. When coupled together, the models are expected to describe pack-level thermal and aging response of individual cells. GM and NREL will use data collected for GM's Bas+ battery system for evaluation of the proposed methodology and assess to what degree these models can replace pack-level aging experiments in the future.« less

Drought and Heat Wave Impacts on Electricity Grid Reliability in Illinois

NASA Astrophysics Data System (ADS)

Stillwell, A. S.; Lubega, W. N.

2016-12-01

A large proportion of thermal power plants in the United States use cooling systems that discharge large volumes of heated water into rivers and cooling ponds. To minimize thermal pollution from these discharges, restrictions are placed on temperatures at the edge of defined mixing zones in the receiving waters. However, during extended hydrological droughts and heat waves, power plants are often granted thermal variances permitting them to exceed these temperature restrictions. These thermal variances are often deemed necessary for maintaining electricity reliability, particularly as heat waves cause increased electricity demand. Current practice, however, lacks tools for the development of grid-scale operational policies specifying generator output levels that ensure reliable electricity supply while minimizing thermal variances. Such policies must take into consideration characteristics of individual power plants, topology and characteristics of the electricity grid, and locations of power plants within the river basin. In this work, we develop a methodology for the development of these operational policies that captures necessary factors. We develop optimal rules for different hydrological and meteorological conditions, serving as rule curves for thermal power plants. The rules are conditioned on leading modes of the ambient hydrological and meteorological conditions at the different power plant locations, as the locations are geographically close and hydrologically connected. Heat dissipation in the rivers and cooling ponds is modeled using the equilibrium temperature concept. Optimal rules are determined through a Monte Carlo sampling optimization framework. The methodology is applied to a case study of eight power plants in Illinois that were granted thermal variances in the summer of 2012, with a representative electricity grid model used in place of the actual electricity grid.

Reliability and Probabilistic Risk Assessment - How They Play Together

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.; Stutts, Richard G.; Zhaofeng, Huang

2015-01-01

PRA methodology is one of the probabilistic analysis methods that NASA brought from the nuclear industry to assess the risk of LOM, LOV and LOC for launch vehicles. PRA is a system scenario based risk assessment that uses a combination of fault trees, event trees, event sequence diagrams, and probability and statistical data to analyze the risk of a system, a process, or an activity. It is a process designed to answer three basic questions: What can go wrong? How likely is it? What is the severity of the degradation? Since 1986, NASA, along with industry partners, has conducted a number of PRA studies to predict the overall launch vehicles risks. Planning Research Corporation conducted the first of these studies in 1988. In 1995, Science Applications International Corporation (SAIC) conducted a comprehensive PRA study. In July 1996, NASA conducted a two-year study (October 1996 - September 1998) to develop a model that provided the overall Space Shuttle risk and estimates of risk changes due to proposed Space Shuttle upgrades. After the Columbia accident, NASA conducted a PRA on the Shuttle External Tank (ET) foam. This study was the most focused and extensive risk assessment that NASA has conducted in recent years. It used a dynamic, physics-based, integrated system analysis approach to understand the integrated system risk due to ET foam loss in flight. Most recently, a PRA for Ares I launch vehicle has been performed in support of the Constellation program. Reliability, on the other hand, addresses the loss of functions. In a broader sense, reliability engineering is a discipline that involves the application of engineering principles to the design and processing of products, both hardware and software, for meeting product reliability requirements or goals. It is a very broad design-support discipline. It has important interfaces with many other engineering disciplines. Reliability as a figure of merit (i.e. the metric) is the probability that an item will perform its intended function(s) for a specified mission profile. In general, the reliability metric can be calculated through the analyses using reliability demonstration and reliability prediction methodologies. Reliability analysis is very critical for understanding component failure mechanisms and in identifying reliability critical design and process drivers. The following sections discuss the PRA process and reliability engineering in detail and provide an application where reliability analysis and PRA were jointly used in a complementary manner to support a Space Shuttle flight risk assessment.

Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain

NASA Astrophysics Data System (ADS)

Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.

2015-12-01

In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.

Predicting the Reliability of Brittle Material Structures Subjected to Transient Proof Test and Service Loading

NASA Astrophysics Data System (ADS)

Nemeth, Noel N.; Jadaan, Osama M.; Palfi, Tamas; Baker, Eric H.

Brittle materials today are being used, or considered, for a wide variety of high tech applications that operate in harsh environments, including static and rotating turbine parts, thermal protection systems, dental prosthetics, fuel cells, oxygen transport membranes, radomes, and MEMS. Designing brittle material components to sustain repeated load without fracturing while using the minimum amount of material requires the use of a probabilistic design methodology. The NASA CARES/Life 1 (Ceramic Analysis and Reliability Evaluation of Structure/Life) code provides a general-purpose analysis tool that predicts the probability of failure of a ceramic component as a function of its time in service. This capability includes predicting the time-dependent failure probability of ceramic components against catastrophic rupture when subjected to transient thermomechanical loads (including cyclic loads). The developed methodology allows for changes in material response that can occur with temperature or time (i.e. changing fatigue and Weibull parameters with temperature or time). For this article an overview of the transient reliability methodology and how this methodology is extended to account for proof testing is described. The CARES/Life code has been modified to have the ability to interface with commercially available finite element analysis (FEA) codes executed for transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

Structural design considerations for micromachined solid-oxide fuel cells

NASA Astrophysics Data System (ADS)

Srikar, V. T.; Turner, Kevin T.; Andrew Ie, Tze Yung; Spearing, S. Mark

Micromachined solid-oxide fuel cells (μSOFCs) are among a class of devices being investigated for portable power generation. Optimization of the performance and reliability of such devices requires robust, scale-dependent, design methodologies. In this first analysis, we consider the structural design of planar, electrolyte-supported, μSOFCs from the viewpoints of electrochemical performance, mechanical stability and reliability, and thermal behavior. The effect of electrolyte thickness on fuel cell performance is evaluated using a simple analytical model. Design diagrams that account explicitly for thermal and intrinsic residual stresses are presented to identify geometries that are resistant to fracture and buckling. Analysis of energy loss due to in-plane heat conduction highlights the importance of efficient thermal isolation in microscale fuel cell design.

Optimisation of warpage on plastic injection moulding part using response surface methodology (RSM) and genetic algorithm method (GA)

NASA Astrophysics Data System (ADS)

Miza, A. T. N. A.; Shayfull, Z.; Nasir, S. M.; Fathullah, M.; Hazwan, M. H. M.

2017-09-01

In this study, Computer Aided Engineering was used for injection moulding simulation. The method of Design of experiment (DOE) was utilize according to the Latin Square orthogonal array. The relationship between the injection moulding parameters and warpage were identify based on the experimental data that used. Response Surface Methodology (RSM) was used as to validate the model accuracy. Then, the RSM and GA method were combine as to examine the optimum injection moulding process parameter. Therefore the optimisation of injection moulding is largely improve and the result shown an increasing accuracy and also reliability. The propose method by combining RSM and GA method also contribute in minimising the warpage from occur.

An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design

NASA Technical Reports Server (NTRS)

Lin, Risheng; Afjeh, Abdollah A.

2003-01-01

Crucial to an efficient aircraft simulation-based design is a robust data modeling methodology for both recording the information and providing data transfer readily and reliably. To meet this goal, data modeling issues involved in the aircraft multidisciplinary design are first analyzed in this study. Next, an XML-based. extensible data object model for multidisciplinary aircraft design is constructed and implemented. The implementation of the model through aircraft databinding allows the design applications to access and manipulate any disciplinary data with a lightweight and easy-to-use API. In addition, language independent representation of aircraft disciplinary data in the model fosters interoperability amongst heterogeneous systems thereby facilitating data sharing and exchange between various design tools and systems.

A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

PubMed

Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

2014-11-01

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method.

The weighted priors approach for combining expert opinions in logistic regression experiments

DOE PAGES

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

2017-04-24

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

The weighted priors approach for combining expert opinions in logistic regression experiments

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

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

Methodology for urban rail and construction technology research and development planning

NASA Technical Reports Server (NTRS)

Rubenstein, L. D.; Land, J. E.; Deshpande, G.; Dayman, B.; Warren, E. H.

1980-01-01

A series of transit system visits, organized by the American Public Transit Association (APTA), was conducted in which the system operators identified the most pressing development needs. These varied by property and were reformulated into a series of potential projects. To assist in the evaluation, a data base useful for estimating the present capital and operating costs of various transit system elements was generated from published data. An evaluation model was developed which considered the rate of deployment of the research and development project, potential benefits, development time and cost. An outline of an evaluation methodology that considered benefits other than capital and operating cost savings was also presented. During the course of the study, five candidate projects were selected for detailed investigation; (1) air comfort systems; (2) solid state auxiliary power conditioners; (3) door systems; (4) escalators; and (5) fare collection systems. Application of the evaluation model to these five examples showed the usefulness of modeling deployment rates and indicated a need to increase the scope of the model to quantitatively consider reliability impacts.

The failure analysis and lifetime prediction for the solder joint of the magnetic head

NASA Astrophysics Data System (ADS)

Xiao, Xianghui; Peng, Minfang; Cardoso, Jaime S.; Tang, Rongjun; Zhou, YingLiang

2015-02-01

Micro-solder joint (MSJ) lifetime prediction methodology and failure analysis (FA) are to assess reliability by fatigue model with a series of theoretical calculations, numerical simulation and experimental method. Due to shortened time of solder joints on high-temperature, high-frequency sampling error that is not allowed in productions may exist in various models, including round-off error. Combining intermetallic compound (IMC) growth theory and the FA technology for the magnetic head in actual production, this thesis puts forward a new growth model to predict life expectancy for solder joint of the magnetic head. And the impact of IMC, generating from interface reaction between slider (magnetic head, usually be called slider) and bonding pad, on mechanical performance during aging process is analyzed in it. By further researching on FA of solder ball bonding, thesis chooses AuSn4 growth model that affects least to solder joint mechanical property to indicate that the IMC methodology is suitable to forecast the solder lifetime. And the diffusion constant under work condition 60 °C is 0.015354; the solder lifetime t is 14.46 years.

Regional climates in the GISS global circulation model - Synoptic-scale circulation

NASA Technical Reports Server (NTRS)

Hewitson, B.; Crane, R. G.

1992-01-01

A major weakness of current general circulation models (GCMs) is their perceived inability to predict reliably the regional consequences of a global-scale change, and it is these regional-scale predictions that are necessary for studies of human-environmental response. For large areas of the extratropics, the local climate is controlled by the synoptic-scale atmospheric circulation, and it is the purpose of this paper to evaluate the synoptic-scale circulation of the Goddard Institute for Space Studies (GISS) GCM. A methodology for validating the daily synoptic circulation using Principal Component Analysis is described, and the methodology is then applied to the GCM simulation of sea level pressure over the continental United States (excluding Alaska). The analysis demonstrates that the GISS 4 x 5 deg GCM Model II effectively simulates the synoptic-scale atmospheric circulation over the United States. The modes of variance describing the atmospheric circulation of the model are comparable to those found in the observed data, and these modes explain similar amounts of variance in their respective datasets. The temporal behavior of these circulation modes in the synoptic time frame are also comparable.

Integrating Formal Methods and Testing 2002

NASA Technical Reports Server (NTRS)

Cukic, Bojan

2002-01-01

Traditionally, qualitative program verification methodologies and program testing are studied in separate research communities. None of them alone is powerful and practical enough to provide sufficient confidence in ultra-high reliability assessment when used exclusively. Significant advances can be made by accounting not only tho formal verification and program testing. but also the impact of many other standard V&V techniques, in a unified software reliability assessment framework. The first year of this research resulted in the statistical framework that, given the assumptions on the success of the qualitative V&V and QA procedures, significantly reduces the amount of testing needed to confidently assess reliability at so-called high and ultra-high levels (10-4 or higher). The coming years shall address the methodologies to realistically estimate the impacts of various V&V techniques to system reliability and include the impact of operational risk to reliability assessment. Combine formal correctness verification, process and product metrics, and other standard qualitative software assurance methods with statistical testing with the aim of gaining higher confidence in software reliability assessment for high-assurance applications. B) Quantify the impact of these methods on software reliability. C) Demonstrate that accounting for the effectiveness of these methods reduces the number of tests needed to attain certain confidence level. D) Quantify and justify the reliability estimate for systems developed using various methods.

A Simple and Reliable Method of Design for Standalone Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Srinivasarao, Mantri; Sudha, K. Rama; Bhanu, C. V. K.

2017-06-01

Standalone photovoltaic (SAPV) systems are seen as a promoting method of electrifying areas of developing world that lack power grid infrastructure. Proliferations of these systems require a design procedure that is simple, reliable and exhibit good performance over its life time. The proposed methodology uses simple empirical formulae and easily available parameters to design SAPV systems, that is, array size with energy storage. After arriving at the different array size (area), performance curves are obtained for optimal design of SAPV system with high amount of reliability in terms of autonomy at a specified value of loss of load probability (LOLP). Based on the array to load ratio (ALR) and levelized energy cost (LEC) through life cycle cost (LCC) analysis, it is shown that the proposed methodology gives better performance, requires simple data and is more reliable when compared with conventional design using monthly average daily load and insolation.

Methodological challenges when doing research that includes ethnic minorities: a scoping review.

PubMed

Morville, Anne-Le; Erlandsson, Lena-Karin

2016-11-01

There are challenging methodological issues in obtaining valid and reliable results on which to base occupational therapy interventions for ethnic minorities. The aim of this scoping review is to describe the methodological problems within occupational therapy research, when ethnic minorities are included. A thorough literature search yielded 21 articles obtained from the scientific databases PubMed, Cinahl, Web of Science and PsychInfo. Analysis followed Arksey and O'Malley's framework for scoping reviews, applying content analysis. The results showed methodological issues concerning the entire research process from defining and recruiting samples, the conceptual understanding, lack of appropriate instruments, data collection using interpreters to analyzing data. In order to avoid excluding the ethnic minorities from adequate occupational therapy research and interventions, development of methods for the entire research process is needed. It is a costly and time-consuming process, but the results will be valid and reliable, and therefore more applicable in clinical practice.

Reliability Quantification of the Flexure: A Critical Stirling Convertor Component

NASA Technical Reports Server (NTRS)

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

2004-01-01

Uncertainties in the manufacturing, fabrication process, material behavior, loads, and boundary conditions results in the variation of the stresses and strains induced in the flexures and its fatigue life. Past experience and the test data at material coupon levels revealed a significant amount of scatter of the fatigue life. Owing to these facts, the design of the flexure, using conventional approaches based on safety factor or traditional reliability based on similar equipment considerations does not provide a direct measure of reliability. Additionally, it may not be feasible to run actual long term fatigue tests due to cost and time constraints. Therefore it is difficult to ascertain material fatigue strength limit. The objective of the paper is to present a methodology and quantified results of numerical simulation for the reliability of flexures used in the Stirling convertor for their structural performance. The proposed approach is based on application of finite element analysis method in combination with the random fatigue limit model, which includes uncertainties in material fatigue life. Additionally, sensitivity of fatigue life reliability to the design variables is quantified and its use to develop guidelines to improve design, manufacturing, quality control and inspection design process is described.

Short-term forecasting of turbidity in trunk main networks.

PubMed

Meyers, Gregory; Kapelan, Zoran; Keedwell, Edward

2017-11-01

Water discolouration is an increasingly important and expensive issue due to rising customer expectations, tighter regulatory demands and ageing Water Distribution Systems (WDSs) in the UK and abroad. This paper presents a new turbidity forecasting methodology capable of aiding operational staff and enabling proactive management strategies. The turbidity forecasting methodology developed here is completely data-driven and does not require hydraulic or water quality network model that is expensive to build and maintain. The methodology is tested and verified on a real trunk main network with observed turbidity measurement data. Results obtained show that the methodology can detect if discolouration material is mobilised, estimate if sufficient turbidity will be generated to exceed a preselected threshold and approximate how long the material will take to reach the downstream meter. Classification based forecasts of turbidity can be reliably made up to 5 h ahead although at the expense of increased false alarm rates. The methodology presented here could be used as an early warning system that can enable a multitude of cost beneficial proactive management strategies to be implemented as an alternative to expensive trunk mains cleaning programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

A methodology of the assessment of environmental and human health risks from amine emissions from post combustion CO2 capture technology

NASA Astrophysics Data System (ADS)

Korre, Anna; Manzoor, Saba; Simperler, Alexandra

2015-04-01

Post combustion CO2 capture (PCCC) technology in power plants using amines as solvent for CO2 capture, is one of the reduction technologies employed to combat escalating levels of CO2 in the atmosphere. However, amine solvents used for capturing CO2 produce negative emissions such as, nitrosamines and nitramines, which are suspected to be potent carcinogens. It is therefore essential to assess the atmospheric fate of these amine emissions in the atmosphere by studying their atmospheric chemistry, dispersion and transport pathways away from the source and deposition in the environment, so as to be able to assess accurately the risk posed to human health and the natural environment. An important knowledge gap until recently has been the consideration of the atmospheric chemistry of these amine emissions simultaneously with dispersion and deposition studies so as to perform reliable human health and environmental risk assessments. The authors have developed a methodology to assess the distribution of such emissions away from a post-combustion facility by studying the atmospheric chemistry of monoethanolamine, the most commonly used solvent for CO2 capture, and those of the resulting degradation amines, methylamine and dimethylamine. This was coupled with dispersion modeling calculations (Manzoor, et al., 2014; Manzoor et al,2015). Rate coefficients describing the entire atmospheric chemistry schemes of the amines studied were evaluated employing quantum chemical theoretical and kinetic modeling calculations. These coefficients were used to solve the advection-dispersion-chemical equation using an atmospheric dispersion model, ADMS 5. This methodology is applicable to any size of a power plant and at any geographical location. In this paper, the humman health risk assessment is integrated in the modelling study. The methodology is demonstrated on a case study on the UK's largest capture pilot plant, Ferrybridge CCPilot 100+, to estimate the dispersion, chemical transformation and transport pathways of the amines and their degradation products away from the emitting facilities for the worst case scenario. The obtained results are used in calculating the cancer risks centred on oral cancer slope factor (CSF), risk-specific dose (RSD) and tolerant risk level of these chemical discharges. According to the CSF and RSD relationship (WQSA, 2011), at high CSF the RSD is small i.e. resulting in a high potent carcinogen risk. The health risk assessment is performed by following the US EPA method (USEPA, 1992) which considers atmospheric concentrations of these pollutants (mg m-3, evaluated by the dispersion model), daily intake through inhalation (mg kg-1 d-1), inhalation rate (m3 d-1), body weight (kg), average time (d), exposure time (d), exposure frequency (d), absorption factor and retention factor. Deterministic and probabilistic risk estimation of human health risks caused by exposure to these chemical pollutant discharges are conducted as well. From the findings of this study, it is suggested that the developed methodology is reliable in determining the risk these amine emissions from PCCC technology pose to human health. With this reliable and a universal approach it is possible to assess the fate of the amine emissions which remains a key area to address for the large scale CCS implementation.

Evaluating test-retest reliability in patient-reported outcome measures for older people: A systematic review.

PubMed

Park, Myung Sook; Kang, Kyung Ja; Jang, Sun Joo; Lee, Joo Yun; Chang, Sun Ju

2018-03-01

This study aimed to evaluate the components of test-retest reliability including time interval, sample size, and statistical methods used in patient-reported outcome measures in older people and to provide suggestions on the methodology for calculating test-retest reliability for patient-reported outcomes in older people. This was a systematic literature review. MEDLINE, Embase, CINAHL, and PsycINFO were searched from January 1, 2000 to August 10, 2017 by an information specialist. This systematic review was guided by both the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and the guideline for systematic review published by the National Evidence-based Healthcare Collaborating Agency in Korea. The methodological quality was assessed by the Consensus-based Standards for the selection of health Measurement Instruments checklist box B. Ninety-five out of 12,641 studies were selected for the analysis. The median time interval for test-retest reliability was 14days, and the ratio of sample size for test-retest reliability to the number of items in each measure ranged from 1:1 to 1:4. The most frequently used statistical methods for continuous scores was intraclass correlation coefficients (ICCs). Among the 63 studies that used ICCs, 21 studies presented models for ICC calculations and 30 studies reported 95% confidence intervals of the ICCs. Additional analyses using 17 studies that reported a strong ICC (>0.09) showed that the mean time interval was 12.88days and the mean ratio of the number of items to sample size was 1:5.37. When researchers plan to assess the test-retest reliability of patient-reported outcome measures for older people, they need to consider an adequate time interval of approximately 13days and the sample size of about 5 times the number of items. Particularly, statistical methods should not only be selected based on the types of scores of the patient-reported outcome measures, but should also be described clearly in the studies that report the results of test-retest reliability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ensuring reliability in expansion schemes.

PubMed

Kamal-Uddin, Abu Sayed; Williams, Donald Leigh

2005-01-01

Existing electricity power supplies must serve, or be adapted to serve, the expansion of hospital buildings. With the existing power supply assets of many hospitals being up to 20 years old, assessing the security and reliability of the power system must be given appropriate priority to avoid unplanned outages due to overloads and equipment failures. It is imperative that adequate contingency is planned for essential and non-essential electricity circuits. This article describes the methodology undertaken, and the subsequent recommendations that were made, when evaluating the security and reliability of electricity power supplies to a number of major London hospitals. The methodology described aligns with the latest issue of NHS Estates HTM 2011 'Primary Electrical Infrastructure Emergency Electrical Services Design Guidance' (to which ERA Technology has contributed).

A soft-computing methodology for noninvasive time-spatial temperature estimation.

PubMed

Teixeira, César A; Ruano, Maria Graça; Ruano, António E; Pereira, Wagner C A

2008-02-01

The safe and effective application of thermal therapies is restricted due to lack of reliable noninvasive temperature estimators. In this paper, the temporal echo-shifts of backscattered ultrasound signals, collected from a gel-based phantom, were tracked and assigned with the past temperature values as radial basis functions neural networks input information. The phantom was heated using a piston-like therapeutic ultrasound transducer. The neural models were assigned to estimate the temperature at different intensities and points arranged across the therapeutic transducer radial line (60 mm apart from the transducer face). Model inputs, as well as the number of neurons were selected using the multiobjective genetic algorithm (MOGA). The best attained models present, in average, a maximum absolute error less than 0.5 degrees C, which is pointed as the borderline between a reliable and an unreliable estimator in hyperthermia/diathermia. In order to test the spatial generalization capacity, the best models were tested using spatial points not yet assessed, and some of them presented a maximum absolute error inferior to 0.5 degrees C, being "elected" as the best models. It should be also stressed that these best models present implementational low-complexity, as desired for real-time applications.

Coupling long and short term decisions in the design of urban water supply infrastructure for added reliability and flexibility

NASA Astrophysics Data System (ADS)

Marques, G.; Fraga, C. C. S.; Medellin-Azuara, J.

2016-12-01

The expansion and operation of urban water supply systems under growing demands, hydrologic uncertainty and water scarcity requires a strategic combination of supply sources for reliability, reduced costs and improved operational flexibility. The design and operation of such portfolio of water supply sources involves integration of long and short term planning to determine what and when to expand, and how much to use of each supply source accounting for interest rates, economies of scale and hydrologic variability. This research presents an integrated methodology coupling dynamic programming optimization with quadratic programming to optimize the expansion (long term) and operations (short term) of multiple water supply alternatives. Lagrange Multipliers produced by the short-term model provide a signal about the marginal opportunity cost of expansion to the long-term model, in an iterative procedure. A simulation model hosts the water supply infrastructure and hydrologic conditions. Results allow (a) identification of trade offs between cost and reliability of different expansion paths and water use decisions; (b) evaluation of water transfers between urban supply systems; and (c) evaluation of potential gains by reducing water system losses as a portfolio component. The latter is critical in several developing countries where water supply system losses are high and often neglected in favor of more system expansion.

Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

PubMed

Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

2017-08-15

Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

NASA Astrophysics Data System (ADS)

Liu, Yushi; Poh, Hee Joo

2014-11-01

The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

Constraints and Opportunities in GCM Model Development

NASA Technical Reports Server (NTRS)

Schmidt, Gavin; Clune, Thomas

2010-01-01

Over the past 30 years climate models have evolved from relatively simple representations of a few atmospheric processes to complex multi-disciplinary system models which incorporate physics from bottom of the ocean to the mesopause and are used for seasonal to multi-million year timescales. Computer infrastructure over that period has gone from punchcard mainframes to modern parallel clusters. Constraints of working within an ever evolving research code mean that most software changes must be incremental so as not to disrupt scientific throughput. Unfortunately, programming methodologies have generally not kept pace with these challenges, and existing implementations now present a heavy and growing burden on further model development as well as limiting flexibility and reliability. Opportunely, advances in software engineering from other disciplines (e.g. the commercial software industry) as well as new generations of powerful development tools can be incorporated by the model developers to incrementally and systematically improve underlying implementations and reverse the long term trend of increasing development overhead. However, these methodologies cannot be applied blindly, but rather must be carefully tailored to the unique characteristics of scientific software development. We will discuss the need for close integration of software engineers and climate scientists to find the optimal processes for climate modeling.

Using meta-quality to assess the utility of volunteered geographic information for science.

PubMed

Langley, Shaun A; Messina, Joseph P; Moore, Nathan

2017-11-06

Volunteered geographic information (VGI) has strong potential to be increasingly valuable to scientists in collaboration with non-scientists. The abundance of mobile phones and other wireless forms of communication open up significant opportunities for the public to get involved in scientific research. As these devices and activities become more abundant, questions of uncertainty and error in volunteer data are emerging as critical components for using volunteer-sourced spatial data. Here we present a methodology for using VGI and assessing its sensitivity to three types of error. More specifically, this study evaluates the reliability of data from volunteers based on their historical patterns. The specific context is a case study in surveillance of tsetse flies, a health concern for being the primary vector of African Trypanosomiasis. Reliability, as measured by a reputation score, determines the threshold for accepting the volunteered data for inclusion in a tsetse presence/absence model. Higher reputation scores are successful in identifying areas of higher modeled tsetse prevalence. A dynamic threshold is needed but the quality of VGI will improve as more data are collected and the errors in identifying reliable participants will decrease. This system allows for two-way communication between researchers and the public, and a way to evaluate the reliability of VGI. Boosting the public's ability to participate in such work can improve disease surveillance and promote citizen science. In the absence of active surveillance, VGI can provide valuable spatial information given that the data are reliable.

Reliable and accurate point-based prediction of cumulative infiltration using soil readily available characteristics: A comparison between GMDH, ANN, and MLR

NASA Astrophysics Data System (ADS)

Rahmati, Mehdi

2017-08-01

Developing accurate and reliable pedo-transfer functions (PTFs) to predict soil non-readily available characteristics is one of the most concerned topic in soil science and selecting more appropriate predictors is a crucial factor in PTFs' development. Group method of data handling (GMDH), which finds an approximate relationship between a set of input and output variables, not only provide an explicit procedure to select the most essential PTF input variables, but also results in more accurate and reliable estimates than other mostly applied methodologies. Therefore, the current research was aimed to apply GMDH in comparison with multivariate linear regression (MLR) and artificial neural network (ANN) to develop several PTFs to predict soil cumulative infiltration point-basely at specific time intervals (0.5-45 min) using soil readily available characteristics (RACs). In this regard, soil infiltration curves as well as several soil RACs including soil primary particles (clay (CC), silt (Si), and sand (Sa)), saturated hydraulic conductivity (Ks), bulk (Db) and particle (Dp) densities, organic carbon (OC), wet-aggregate stability (WAS), electrical conductivity (EC), and soil antecedent (θi) and field saturated (θfs) water contents were measured at 134 different points in Lighvan watershed, northwest of Iran. Then, applying GMDH, MLR, and ANN methodologies, several PTFs have been developed to predict cumulative infiltrations using two sets of selected soil RACs including and excluding Ks. According to the test data, results showed that developed PTFs by GMDH and MLR procedures using all soil RACs including Ks resulted in more accurate (with E values of 0.673-0.963) and reliable (with CV values lower than 11 percent) predictions of cumulative infiltrations at different specific time steps. In contrast, ANN procedure had lower accuracy (with E values of 0.356-0.890) and reliability (with CV values up to 50 percent) compared to GMDH and MLR. The results also revealed that Ks exclusion from input variables list caused around 30 percent decrease in PTFs accuracy for all applied procedures. However, it seems that Ks exclusion resulted in more practical PTFs especially in the case of GMDH network applying input variables which are less time consuming than Ks. In general, it is concluded that GMDH provides more accurate and reliable estimates of cumulative infiltration (a non-readily available characteristic of soil) with a minimum set of input variables (2-4 input variables) and can be promising strategy to model soil infiltration combining the advantages of ANN and MLR methodologies.

Tailoring a Human Reliability Analysis to Your Industry Needs

NASA Technical Reports Server (NTRS)

DeMott, D. L.

2016-01-01

Companies at risk of accidents caused by human error that result in catastrophic consequences include: airline industry mishaps, medical malpractice, medication mistakes, aerospace failures, major oil spills, transportation mishaps, power production failures and manufacturing facility incidents. Human Reliability Assessment (HRA) is used to analyze the inherent risk of human behavior or actions introducing errors into the operation of a system or process. These assessments can be used to identify where errors are most likely to arise and the potential risks involved if they do occur. Using the basic concepts of HRA, an evolving group of methodologies are used to meet various industry needs. Determining which methodology or combination of techniques will provide a quality human reliability assessment is a key element to developing effective strategies for understanding and dealing with risks caused by human errors. There are a number of concerns and difficulties in "tailoring" a Human Reliability Assessment (HRA) for different industries. Although a variety of HRA methodologies are available to analyze human error events, determining the most appropriate tools to provide the most useful results can depend on industry specific cultures and requirements. Methodology selection may be based on a variety of factors that include: 1) how people act and react in different industries, 2) expectations based on industry standards, 3) factors that influence how the human errors could occur such as tasks, tools, environment, workplace, support, training and procedure, 4) type and availability of data, 5) how the industry views risk & reliability, and 6) types of emergencies, contingencies and routine tasks. Other considerations for methodology selection should be based on what information is needed from the assessment. If the principal concern is determination of the primary risk factors contributing to the potential human error, a more detailed analysis method may be employed versus a requirement to provide a numerical value as part of a probabilistic risk assessment. Industries involved with humans operating large equipment or transport systems (ex. railroads or airlines) would have more need to address the man machine interface than medical workers administering medications. Human error occurs in every industry; in most cases the consequences are relatively benign and occasionally beneficial. In cases where the results can have disastrous consequences, the use of Human Reliability techniques to identify and classify the risk of human errors allows a company more opportunities to mitigate or eliminate these types of risks and prevent costly tragedies.

Large scale nonlinear programming for the optimization of spacecraft trajectories

NASA Astrophysics Data System (ADS)

Arrieta-Camacho, Juan Jose

Despite the availability of high fidelity mathematical models, the computation of accurate optimal spacecraft trajectories has never been an easy task. While simplified models of spacecraft motion can provide useful estimates on energy requirements, sizing, and cost; the actual launch window and maneuver scheduling must rely on more accurate representations. We propose an alternative for the computation of optimal transfers that uses an accurate representation of the spacecraft dynamics. Like other methodologies for trajectory optimization, this alternative is able to consider all major disturbances. In contrast, it can handle explicitly equality and inequality constraints throughout the trajectory; it requires neither the derivation of costate equations nor the identification of the constrained arcs. The alternative consist of two steps: (1) discretizing the dynamic model using high-order collocation at Radau points, which displays numerical advantages, and (2) solution to the resulting Nonlinear Programming (NLP) problem using an interior point method, which does not suffer from the performance bottleneck associated with identifying the active set, as required by sequential quadratic programming methods; in this way the methodology exploits the availability of sound numerical methods, and next generation NLP solvers. In practice the methodology is versatile; it can be applied to a variety of aerospace problems like homing, guidance, and aircraft collision avoidance; the methodology is particularly well suited for low-thrust spacecraft trajectory optimization. Examples are presented which consider the optimization of a low-thrust orbit transfer subject to the main disturbances due to Earth's gravity field together with Lunar and Solar attraction. Other example considers the optimization of a multiple asteroid rendezvous problem. In both cases, the ability of our proposed methodology to consider non-standard objective functions and constraints is illustrated. Future research directions are identified, involving the automatic scheduling and optimization of trajectory correction maneuvers. The sensitivity information provided by the methodology is expected to be invaluable in such research pursuit. The collocation scheme and nonlinear programming algorithm presented in this work, complement other existing methodologies by providing reliable and efficient numerical methods able to handle large scale, nonlinear dynamic models.

Sampling methods to the statistical control of the production of blood components.

PubMed

Pereira, Paulo; Seghatchian, Jerard; Caldeira, Beatriz; Santos, Paula; Castro, Rosa; Fernandes, Teresa; Xavier, Sandra; de Sousa, Gracinda; de Almeida E Sousa, João Paulo

2017-12-01

The control of blood components specifications is a requirement generalized in Europe by the European Commission Directives and in the US by the AABB standards. The use of a statistical process control methodology is recommended in the related literature, including the EDQM guideline. The control reliability is dependent of the sampling. However, a correct sampling methodology seems not to be systematically applied. Commonly, the sampling is intended to comply uniquely with the 1% specification to the produced blood components. Nevertheless, on a purely statistical viewpoint, this model could be argued not to be related to a consistent sampling technique. This could be a severe limitation to detect abnormal patterns and to assure that the production has a non-significant probability of producing nonconforming components. This article discusses what is happening in blood establishments. Three statistical methodologies are proposed: simple random sampling, sampling based on the proportion of a finite population, and sampling based on the inspection level. The empirical results demonstrate that these models are practicable in blood establishments contributing to the robustness of sampling and related statistical process control decisions for the purpose they are suggested for. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reliability Modeling of Microelectromechanical Systems Using Neural Networks

NASA Technical Reports Server (NTRS)

Perera. J. Sebastian

2000-01-01

Microelectromechanical systems (MEMS) are a broad and rapidly expanding field that is currently receiving a great deal of attention because of the potential to significantly improve the ability to sense, analyze, and control a variety of processes, such as heating and ventilation systems, automobiles, medicine, aeronautical flight, military surveillance, weather forecasting, and space exploration. MEMS are very small and are a blend of electrical and mechanical components, with electrical and mechanical systems on one chip. This research establishes reliability estimation and prediction for MEMS devices at the conceptual design phase using neural networks. At the conceptual design phase, before devices are built and tested, traditional methods of quantifying reliability are inadequate because the device is not in existence and cannot be tested to establish the reliability distributions. A novel approach using neural networks is created to predict the overall reliability of a MEMS device based on its components and each component's attributes. The methodology begins with collecting attribute data (fabrication process, physical specifications, operating environment, property characteristics, packaging, etc.) and reliability data for many types of microengines. The data are partitioned into training data (the majority) and validation data (the remainder). A neural network is applied to the training data (both attribute and reliability); the attributes become the system inputs and reliability data (cycles to failure), the system output. After the neural network is trained with sufficient data. the validation data are used to verify the neural networks provided accurate reliability estimates. Now, the reliability of a new proposed MEMS device can be estimated by using the appropriate trained neural networks developed in this work.

Analysis of travel-time reliability for freight corridors connecting the Pacific Northwest.

DOT National Transportation Integrated Search

2012-11-01

A new methodology and algorithms were developed to combine diverse data sources and to estimate the impacts of recurrent and non-recurrent : congestion on freight movements reliability and delays, costs, and emissions. The results suggest that tra...

A statistical methodology for estimating transport parameters: Theory and applications to one-dimensional advectivec-dispersive systems

USGS Publications Warehouse

Wagner, Brian J.; Gorelick, Steven M.

1986-01-01

A simulation nonlinear multiple-regression methodology for estimating parameters that characterize the transport of contaminants is developed and demonstrated. Finite difference contaminant transport simulation is combined with a nonlinear weighted least squares multiple-regression procedure. The technique provides optimal parameter estimates and gives statistics for assessing the reliability of these estimates under certain general assumptions about the distributions of the random measurement errors. Monte Carlo analysis is used to estimate parameter reliability for a hypothetical homogeneous soil column for which concentration data contain large random measurement errors. The value of data collected spatially versus data collected temporally was investigated for estimation of velocity, dispersion coefficient, effective porosity, first-order decay rate, and zero-order production. The use of spatial data gave estimates that were 2–3 times more reliable than estimates based on temporal data for all parameters except velocity. Comparison of estimated linear and nonlinear confidence intervals based upon Monte Carlo analysis showed that the linear approximation is poor for dispersion coefficient and zero-order production coefficient when data are collected over time. In addition, examples demonstrate transport parameter estimation for two real one-dimensional systems. First, the longitudinal dispersivity and effective porosity of an unsaturated soil are estimated using laboratory column data. We compare the reliability of estimates based upon data from individual laboratory experiments versus estimates based upon pooled data from several experiments. Second, the simulation nonlinear regression procedure is extended to include an additional governing equation that describes delayed storage during contaminant transport. The model is applied to analyze the trends, variability, and interrelationship of parameters in a mourtain stream in northern California.

Predicting the onset and persistence of episodes of depression in primary health care. The predictD-Spain study: Methodology

PubMed Central

Bellón, Juan Ángel; Moreno-Küstner, Berta; Torres-González, Francisco; Montón-Franco, Carmen; GildeGómez-Barragán, María Josefa; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; de Dios Luna, Juan; Cervilla, Jorge A; Gutierrez, Blanca; Martínez-Cañavate, María Teresa; Oliván-Blázquez, Bárbara; Vázquez-Medrano, Ana; Sánchez-Artiaga, María Soledad; March, Sebastia; Motrico, Emma; Ruiz-García, Victor Manuel; Brangier-Wainberg, Paulette Renée; del Mar Muñoz-García, María; Nazareth, Irwin; King, Michael

2008-01-01

Background The effects of putative risk factors on the onset and/or persistence of depression remain unclear. We aim to develop comprehensive models to predict the onset and persistence of episodes of depression in primary care. Here we explain the general methodology of the predictD-Spain study and evaluate the reliability of the questionnaires used. Methods This is a prospective cohort study. A systematic random sample of general practice attendees aged 18 to 75 has been recruited in seven Spanish provinces. Depression is being measured with the CIDI at baseline, and at 6, 12, 24 and 36 months. A set of individual, environmental, genetic, professional and organizational risk factors are to be assessed at each follow-up point. In a separate reliability study, a proportional random sample of 401 participants completed the test-retest (251 researcher-administered and 150 self-administered) between October 2005 and February 2006. We have also checked 118,398 items for data entry from a random sample of 480 patients stratified by province. Results All items and questionnaires had good test-retest reliability for both methods of administration, except for the use of recreational drugs over the previous six months. Cronbach's alphas were good and their factorial analyses coherent for the three scales evaluated (social support from family and friends, dissatisfaction with paid work, and dissatisfaction with unpaid work). There were 191 (0.16%) data entry errors. Conclusion The items and questionnaires were reliable and data quality control was excellent. When we eventually obtain our risk index for the onset and persistence of depression, we will be able to determine the individual risk of each patient evaluated in primary health care. PMID:18657275

A Predictive Safety Management System Software Package Based on the Continuous Hazard Tracking and Failure Prediction Methodology

NASA Technical Reports Server (NTRS)

Quintana, Rolando

2003-01-01

The goal of this research was to integrate a previously validated and reliable safety model, called Continuous Hazard Tracking and Failure Prediction Methodology (CHTFPM), into a software application. This led to the development of a safety management information system (PSMIS). This means that the theory or principles of the CHTFPM were incorporated in a software package; hence, the PSMIS is referred to as CHTFPM management information system (CHTFPM MIS). The purpose of the PSMIS is to reduce the time and manpower required to perform predictive studies as well as to facilitate the handling of enormous quantities of information in this type of studies. The CHTFPM theory encompasses the philosophy of looking at the concept of safety engineering from a new perspective: from a proactive, than a reactive, viewpoint. That is, corrective measures are taken before a problem instead of after it happened. That is why the CHTFPM is a predictive safety because it foresees or anticipates accidents, system failures and unacceptable risks; therefore, corrective action can be taken in order to prevent all these unwanted issues. Consequently, safety and reliability of systems or processes can be further improved by taking proactive and timely corrective actions.

Quantitative Assessment of Agricultural Runoff and Soil Erosion Using Mathematical Modeling: Applications in the Mediterranean Region

NASA Astrophysics Data System (ADS)

Arhonditsis, G.; Giourga, C.; Loumou, A.; Koulouri, M.

2002-09-01

Three mathematical models, the runoff curve number equation, the universal soil loss equation, and the mass response functions, were evaluated for predicting nonpoint source nutrient loading from agricultural watersheds of the Mediterranean region. These methodologies were applied to a catchment, the gulf of Gera Basin, that is a typical terrestrial ecosystem of the islands of the Aegean archipelago. The calibration of the model parameters was based on data from experimental plots from which edge-of-field losses of sediment, water runoff, and nutrients were measured. Special emphasis was given to the transport of dissolved and solid-phase nutrients from their sources in the farmers' fields to the outlet of the watershed in order to estimate respective attenuation rates. It was found that nonpoint nutrient loading due to surface losses was high during winter, the contribution being between 50% and 80% of the total annual nutrient losses from the terrestrial ecosystem. The good fit between simulated and experimental data supports the view that these modeling procedures should be considered as reliable and effective methodological tools in Mediterranean areas for evaluating potential control measures, such as management practices for soil and water conservation and changes in land uses, aimed at diminishing soil loss and nutrient delivery to surface waters. Furthermore, the modifications of the general mathematical formulations and the experimental values of the model parameters provided by the study can be used in further application of these methodologies in watersheds with similar characteristics.

Validity and Reliability of Field-Based Measures for Assessing Movement Skill Competency in Lifelong Physical Activities: A Systematic Review.

PubMed

Hulteen, Ryan M; Lander, Natalie J; Morgan, Philip J; Barnett, Lisa M; Robertson, Samuel J; Lubans, David R

2015-10-01

It has been suggested that young people should develop competence in a variety of 'lifelong physical activities' to ensure that they can be active across the lifespan. The primary aim of this systematic review is to report the methodological properties, validity, reliability, and test duration of field-based measures that assess movement skill competency in lifelong physical activities. A secondary aim was to clearly define those characteristics unique to lifelong physical activities. A search of four electronic databases (Scopus, SPORTDiscus, ProQuest, and PubMed) was conducted between June 2014 and April 2015 with no date restrictions. Studies addressing the validity and/or reliability of lifelong physical activity tests were reviewed. Included articles were required to assess lifelong physical activities using process-oriented measures, as well as report either one type of validity or reliability. Assessment criteria for methodological quality were adapted from a checklist used in a previous review of sport skill outcome assessments. Movement skill assessments for eight different lifelong physical activities (badminton, cycling, dance, golf, racquetball, resistance training, swimming, and tennis) in 17 studies were identified for inclusion. Methodological quality, validity, reliability, and test duration (time to assess a single participant), for each article were assessed. Moderate to excellent reliability results were found in 16 of 17 studies, with 71% reporting inter-rater reliability and 41% reporting intra-rater reliability. Only four studies in this review reported test-retest reliability. Ten studies reported validity results; content validity was cited in 41% of these studies. Construct validity was reported in 24% of studies, while criterion validity was only reported in 12% of studies. Numerous assessments for lifelong physical activities may exist, yet only assessments for eight lifelong physical activities were included in this review. Generalizability of results may be more applicable if more heterogeneous samples are used in future research. Moderate to excellent levels of inter- and intra-rater reliability were reported in the majority of studies. However, future work should look to establish test-retest reliability. Validity was less commonly reported than reliability, and further types of validity other than content validity need to be established in future research. Specifically, predictive validity of 'lifelong physical activity' movement skill competency is needed to support the assertion that such activities provide the foundation for a lifetime of activity.

Space station electrical power system availability study

NASA Technical Reports Server (NTRS)

Turnquist, Scott R.; Twombly, Mark A.

1988-01-01

ARINC Research Corporation performed a preliminary reliability, and maintainability (RAM) anlaysis of the NASA space station Electric Power Station (EPS). The analysis was performed using the ARINC Research developed UNIRAM RAM assessment methodology and software program. The analysis was performed in two phases: EPS modeling and EPS RAM assessment. The EPS was modeled in four parts: the insolar power generation system, the eclipse power generation system, the power management and distribution system (both ring and radial power distribution control unit (PDCU) architectures), and the power distribution to the inner keel PDCUs. The EPS RAM assessment was conducted in five steps: the use of UNIRAM to perform baseline EPS model analyses and to determine the orbital replacement unit (ORU) criticalities; the determination of EPS sensitivity to on-orbit spared of ORUs and the provision of an indication of which ORUs may need to be spared on-orbit; the determination of EPS sensitivity to changes in ORU reliability; the determination of the expected annual number of ORU failures; and the integration of the power generator system model results with the distribution system model results to assess the full EPS. Conclusions were drawn and recommendations were made.

“Retention Projection” Enables Reliable Use of Shared Gas Chromatographic Retention Data Across Labs, Instruments, and Methods

PubMed Central

Barnes, Brian B.; Wilson, Michael B.; Carr, Peter W.; Vitha, Mark F.; Broeckling, Corey D.; Heuberger, Adam L.; Prenni, Jessica; Janis, Gregory C.; Corcoran, Henry; Snow, Nicholas H.; Chopra, Shilpi; Dhandapani, Ramkumar; Tawfall, Amanda; Sumner, Lloyd W.; Boswell, Paul G.

2014-01-01

Gas chromatography-mass spectrometry (GC-MS) is a primary tool used to identify compounds in complex samples. Both mass spectra and GC retention times are matched to those of standards, but it is often impractical to have standards on hand for every compound of interest, so we must rely on shared databases of MS data and GC retention information. Unfortunately, retention databases (e.g. linear retention index libraries) are experimentally restrictive, notoriously unreliable, and strongly instrument dependent, relegating GC retention information to a minor, often negligible role in compound identification despite its potential power. A new methodology called “retention projection” has great potential to overcome the limitations of shared chromatographic databases. In this work, we tested the reliability of the methodology in five independent laboratories. We found that even when each lab ran nominally the same method, the methodology was 3-fold more accurate than retention indexing because it properly accounted for unintentional differences between the GC-MS systems. When the labs used different methods of their own choosing, retention projections were 4- to 165-fold more accurate. More importantly, the distribution of error in the retention projections was predictable across different methods and labs, thus enabling automatic calculation of retention time tolerance windows. Tolerance windows at 99% confidence were generally narrower than those widely used even when physical standards are on hand to measure their retention. With its high accuracy and reliability, the new retention projection methodology makes GC retention a reliable, precise tool for compound identification, even when standards are not available to the user. PMID:24205931

Assessments of a Turbulence Model Based on Menter's Modification to Rotta's Two-Equation Model

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.

2013-01-01

The main objective of this paper is to construct a turbulence model with a more reliable second equation simulating length scale. In the present paper, we assess the length scale equation based on Menter s modification to Rotta s two-equation model. Rotta shows that a reliable second equation can be formed in an exact transport equation from the turbulent length scale L and kinetic energy. Rotta s equation is well suited for a term-by-term modeling and shows some interesting features compared to other approaches. The most important difference is that the formulation leads to a natural inclusion of higher order velocity derivatives into the source terms of the scale equation, which has the potential to enhance the capability of Reynolds-averaged Navier-Stokes (RANS) to simulate unsteady flows. The model is implemented in the PAB3D solver with complete formulation, usage methodology, and validation examples to demonstrate its capabilities. The detailed studies include grid convergence. Near-wall and shear flows cases are documented and compared with experimental and Large Eddy Simulation (LES) data. The results from this formulation are as good or better than the well-known SST turbulence model and much better than k-epsilon results. Overall, the study provides useful insights into the model capability in predicting attached and separated flows.

Are cannabis prevalence estimates comparable across countries and regions? A cross-cultural validation using search engine query data.

PubMed

Steppan, Martin; Kraus, Ludwig; Piontek, Daniela; Siciliano, Valeria

2013-01-01

Prevalence estimation of cannabis use is usually based on self-report data. Although there is evidence on the reliability of this data source, its cross-cultural validity is still a major concern. External objective criteria are needed for this purpose. In this study, cannabis-related search engine query data are used as an external criterion. Data on cannabis use were taken from the 2007 European School Survey Project on Alcohol and Other Drugs (ESPAD). Provincial data came from three Italian nation-wide studies using the same methodology (2006-2008; ESPAD-Italia). Information on cannabis-related search engine query data was based on Google search volume indices (GSI). (1) Reliability analysis was conducted for GSI. (2) Latent measurement models of "true" cannabis prevalence were tested using perceived availability, web-based cannabis searches and self-reported prevalence as indicators. (3) Structure models were set up to test the influences of response tendencies and geographical position (latitude, longitude). In order to test the stability of the models, analyses were conducted on country level (Europe, US) and on provincial level in Italy. Cannabis-related GSI were found to be highly reliable and constant over time. The overall measurement model was highly significant in both data sets. On country level, no significant effects of response bias indicators and geographical position on perceived availability, web-based cannabis searches and self-reported prevalence were found. On provincial level, latitude had a significant positive effect on availability indicating that perceived availability of cannabis in northern Italy was higher than expected from the other indicators. Although GSI showed weaker associations with cannabis use than perceived availability, the findings underline the external validity and usefulness of search engine query data as external criteria. The findings suggest an acceptable relative comparability of national (provincial) prevalence estimates of cannabis use that are based on a common survey methodology. Search engine query data are a too weak indicator to base prevalence estimations on this source only, but in combination with other sources (waste water analysis, sales of cigarette paper) they may provide satisfactory estimates. Copyright © 2012. Published by Elsevier B.V.

Reliability Prediction Analysis: Airborne System Results and Best Practices

NASA Astrophysics Data System (ADS)

Silva, Nuno; Lopes, Rui

2013-09-01

This article presents the results of several reliability prediction analysis for aerospace components, made by both methodologies, the 217F and the 217Plus. Supporting and complementary activities are described, as well as the differences concerning the results and the applications of both methodologies that are summarized in a set of lessons learned that are very useful for RAMS and Safety Prediction practitioners.The effort that is required for these activities is also an important point that is discussed, as is the end result and their interpretation/impact on the system design.The article concludes while positioning these activities and methodologies in an overall process for space and aeronautics equipment/components certification, and highlighting their advantages. Some good practices have also been summarized and some reuse rules have been laid down.

Prioritization Methodology for Chemical Replacement

NASA Technical Reports Server (NTRS)

Cruit, W.; Schutzenhofer, S.; Goldberg, B.; Everhart, K.

1993-01-01

This project serves to define an appropriate methodology for effective prioritization of efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semiquantitative approach derived from quality function deployment techniques (QFD Matrix). This methodology aims to weigh the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives. The results are being implemented as a guideline for consideration for current NASA propulsion systems.

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.

Overall Key Performance Indicator to Optimizing Operation of High-Pressure Homogenizers for a Reliable Quantification of Intracellular Components in Pichia pastoris.

PubMed

Garcia-Ortega, Xavier; Reyes, Cecilia; Montesinos, José Luis; Valero, Francisco

2015-01-01

The most commonly used cell disruption procedures may present lack of reproducibility, which introduces significant errors in the quantification of intracellular components. In this work, an approach consisting in the definition of an overall key performance indicator (KPI) was implemented for a lab scale high-pressure homogenizer (HPH) in order to determine the disruption settings that allow the reliable quantification of a wide sort of intracellular components. This innovative KPI was based on the combination of three independent reporting indicators: decrease of absorbance, release of total protein, and release of alkaline phosphatase activity. The yeast Pichia pastoris growing on methanol was selected as model microorganism due to it presents an important widening of the cell wall needing more severe methods and operating conditions than Escherichia coli and Saccharomyces cerevisiae. From the outcome of the reporting indicators, the cell disruption efficiency achieved using HPH was about fourfold higher than other lab standard cell disruption methodologies, such bead milling cell permeabilization. This approach was also applied to a pilot plant scale HPH validating the methodology in a scale-up of the disruption process. This innovative non-complex approach developed to evaluate the efficacy of a disruption procedure or equipment can be easily applied to optimize the most common disruption processes, in order to reach not only reliable quantification but also recovery of intracellular components from cell factories of interest.

Overall Key Performance Indicator to Optimizing Operation of High-Pressure Homogenizers for a Reliable Quantification of Intracellular Components in Pichia pastoris

PubMed Central

Garcia-Ortega, Xavier; Reyes, Cecilia; Montesinos, José Luis; Valero, Francisco

2015-01-01

The most commonly used cell disruption procedures may present lack of reproducibility, which introduces significant errors in the quantification of intracellular components. In this work, an approach consisting in the definition of an overall key performance indicator (KPI) was implemented for a lab scale high-pressure homogenizer (HPH) in order to determine the disruption settings that allow the reliable quantification of a wide sort of intracellular components. This innovative KPI was based on the combination of three independent reporting indicators: decrease of absorbance, release of total protein, and release of alkaline phosphatase activity. The yeast Pichia pastoris growing on methanol was selected as model microorganism due to it presents an important widening of the cell wall needing more severe methods and operating conditions than Escherichia coli and Saccharomyces cerevisiae. From the outcome of the reporting indicators, the cell disruption efficiency achieved using HPH was about fourfold higher than other lab standard cell disruption methodologies, such bead milling cell permeabilization. This approach was also applied to a pilot plant scale HPH validating the methodology in a scale-up of the disruption process. This innovative non-complex approach developed to evaluate the efficacy of a disruption procedure or equipment can be easily applied to optimize the most common disruption processes, in order to reach not only reliable quantification but also recovery of intracellular components from cell factories of interest. PMID:26284241

Probabilistic fatigue methodology for six nines reliability

NASA Technical Reports Server (NTRS)

Everett, R. A., Jr.; Bartlett, F. D., Jr.; Elber, Wolf

1990-01-01

Fleet readiness and flight safety strongly depend on the degree of reliability that can be designed into rotorcraft flight critical components. The current U.S. Army fatigue life specification for new rotorcraft is the so-called six nines reliability, or a probability of failure of one in a million. The progress of a round robin which was established by the American Helicopter Society (AHS) Subcommittee for Fatigue and Damage Tolerance is reviewed to investigate reliability-based fatigue methodology. The participants in this cooperative effort are in the U.S. Army Aviation Systems Command (AVSCOM) and the rotorcraft industry. One phase of the joint activity examined fatigue reliability under uniquely defined conditions for which only one answer was correct. The other phases were set up to learn how the different industry methods in defining fatigue strength affected the mean fatigue life and reliability calculations. Hence, constant amplitude and spectrum fatigue test data were provided so that each participant could perform their standard fatigue life analysis. As a result of this round robin, the probabilistic logic which includes both fatigue strength and spectrum loading variability in developing a consistant reliability analysis was established. In this first study, the reliability analysis was limited to the linear cumulative damage approach. However, it is expected that superior fatigue life prediction methods will ultimately be developed through this open AHS forum. To that end, these preliminary results were useful in identifying some topics for additional study.

Computational models of aortic coarctation in hypoplastic left heart syndrome: considerations on validation of a detailed 3D model.

PubMed

Biglino, Giovanni; Corsini, Chiara; Schievano, Silvia; Dubini, Gabriele; Giardini, Alessandro; Hsia, Tain-Yen; Pennati, Giancarlo; Taylor, Andrew M

2014-05-01

Reliability of computational models for cardiovascular investigations strongly depends on their validation against physical data. This study aims to experimentally validate a computational model of complex congenital heart disease (i.e., surgically palliated hypoplastic left heart syndrome with aortic coarctation) thus demonstrating that hemodynamic information can be reliably extrapolated from the model for clinically meaningful investigations. A patient-specific aortic arch model was tested in a mock circulatory system and the same flow conditions were re-created in silico, by setting an appropriate lumped parameter network (LPN) attached to the same three-dimensional (3D) aortic model (i.e., multi-scale approach). The model included a modified Blalock-Taussig shunt and coarctation of the aorta. Different flow regimes were tested as well as the impact of uncertainty in viscosity. Computational flow and pressure results were in good agreement with the experimental signals, both qualitatively, in terms of the shape of the waveforms, and quantitatively (mean aortic pressure 62.3 vs. 65.1 mmHg, 4.8% difference; mean aortic flow 28.0 vs. 28.4% inlet flow, 1.4% difference; coarctation pressure drop 30.0 vs. 33.5 mmHg, 10.4% difference), proving the reliability of the numerical approach. It was observed that substantial changes in fluid viscosity or using a turbulent model in the numerical simulations did not significantly affect flows and pressures of the investigated physiology. Results highlighted how the non-linear fluid dynamic phenomena occurring in vitro must be properly described to ensure satisfactory agreement. This study presents methodological considerations for using experimental data to preliminarily set up a computational model, and then simulate a complex congenital physiology using a multi-scale approach.

On the short-term uncertainty in performance f a point absorber wave energy converter

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

Coe, Ryan Geoffrey; Michelen, Carlos; Manuel, Lance

2016-03-01

Of interest, in this study, is the quantification of uncertainty in the performance of a two-body wave point absorber (Reference Model 3 or RM3), which serves as a wave energy converter (WEC). We demonstrate how simulation tools may be used to establish short-term relationships between any performance parameter of the WEC device and wave height in individual sea states. We demonstrate this methodology for two sea states. Efficient structural reliability methods, validated using more expensive Monte Carlo sampling, allow the estimation of uncertainty in performance of the device. Such methods, when combined with metocean data quantifying the likelihood of differentmore » sea states, can be useful in long-term studies and in reliability-based design.« less

Reporting and methodological quality of survival analysis in articles published in Chinese oncology journals.

PubMed

Zhu, Xiaoyan; Zhou, Xiaobin; Zhang, Yuan; Sun, Xiao; Liu, Haihua; Zhang, Yingying

2017-12-01

Survival analysis methods have gained widespread use in the filed of oncology. For achievement of reliable results, the methodological process and report quality is crucial. This review provides the first examination of methodological characteristics and reporting quality of survival analysis in articles published in leading Chinese oncology journals.To examine methodological and reporting quality of survival analysis, to identify some common deficiencies, to desirable precautions in the analysis, and relate advice for authors, readers, and editors.A total of 242 survival analysis articles were included to be evaluated from 1492 articles published in 4 leading Chinese oncology journals in 2013. Articles were evaluated according to 16 established items for proper use and reporting of survival analysis.The application rates of Kaplan-Meier, life table, log-rank test, Breslow test, and Cox proportional hazards model (Cox model) were 91.74%, 3.72%, 78.51%, 0.41%, and 46.28%, respectively, no article used the parametric method for survival analysis. Multivariate Cox model was conducted in 112 articles (46.28%). Follow-up rates were mentioned in 155 articles (64.05%), of which 4 articles were under 80% and the lowest was 75.25%, 55 articles were100%. The report rates of all types of survival endpoint were lower than 10%. Eleven of 100 articles which reported a loss to follow-up had stated how to treat it in the analysis. One hundred thirty articles (53.72%) did not perform multivariate analysis. One hundred thirty-nine articles (57.44%) did not define the survival time. Violations and omissions of methodological guidelines included no mention of pertinent checks for proportional hazard assumption; no report of testing for interactions and collinearity between independent variables; no report of calculation method of sample size. Thirty-six articles (32.74%) reported the methods of independent variable selection. The above defects could make potentially inaccurate, misleading of the reported results, or difficult to interpret.There are gaps in the conduct and reporting of survival analysis in studies published in Chinese oncology journals, severe deficiencies were noted. More endorsement by journals of the report guideline for survival analysis may improve articles quality, and the dissemination of reliable evidence to oncology clinicians. We recommend authors, readers, reviewers, and editors to consider survival analysis more carefully and cooperate more closely with statisticians and epidemiologists. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

PERFORMANCE, RELIABILITY, AND IMPROVEMENT OF A TISSUE-SPECIFIC METABOLIC SIMULATOR

EPA Science Inventory

A methodology is described that has been used to build and enhance a simulator for rat liver metabolism providing reliable predictions within a large chemical domain. The tissue metabolism simulator (TIMES) utilizes a heuristic algorithm to generate plausible metabolic maps using...

Evaluation of Explosive Strength for Young and Adult Athletes

ERIC Educational Resources Information Center

Viitasalo, Jukka T.

1988-01-01

The reliability of new electrical measurements of vertical jumping height and of throwing velocity was tested. These results were compared to traditional measurement techniques. The new method was found to give reliable results from children to adults. Methodology is discussed. (Author/JL)

A Study about Kalman Filters Applied to Embedded Sensors

PubMed Central

Valade, Aurélien; Acco, Pascal; Grabolosa, Pierre; Fourniols, Jean-Yves

2017-01-01

Over the last decade, smart sensors have grown in complexity and can now handle multiple measurement sources. This work establishes a methodology to achieve better estimates of physical values by processing raw measurements within a sensor using multi-physical models and Kalman filters for data fusion. A driving constraint being production cost and power consumption, this methodology focuses on algorithmic complexity while meeting real-time constraints and improving both precision and reliability despite low power processors limitations. Consequently, processing time available for other tasks is maximized. The known problem of estimating a 2D orientation using an inertial measurement unit with automatic gyroscope bias compensation will be used to illustrate the proposed methodology applied to a low power STM32L053 microcontroller. This application shows promising results with a processing time of 1.18 ms at 32 MHz with a 3.8% CPU usage due to the computation at a 26 Hz measurement and estimation rate. PMID:29206187

Modeling new coal projects: supercritical or subcritical?

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

Carrino, A.J.; Jones, R.B.

Decisions made on new build coal-fired plants are driven by several factors - emissions, fuel logistics and electric transmission access all provide constraints. The crucial economic decision whether to build supercritical or subcritical units often depends on assumptions concerning the reliability/availability of each technology, the cost of on-fuel operations including maintenance, the generation efficiencies and the potential for emissions credits at some future value. Modeling the influence of these key factors requires analysis and documentation to assure the assets actually meet the projected financial performance. This article addresses some of the issue related to the trade-offs that have the potentialmore » to be driven by the supercritical/subcritical decision. Solomon Associates has been collecting cost, generation and reliability data on coal-fired power generation assets for approximately 10 years using a strict methodology and taxonomy to categorize and compare actual plant operations data. This database provides validated information not only on performance, but also on alternative performance scenarios, which can provide useful insights in the pro forma financial analysis and models of new plants. 1 ref., 1 fig., 3 tabs.« less

Storage reliability analysis summary report. Volume 2: Electro mechanical devices

NASA Astrophysics Data System (ADS)

Smith, H. B., Jr.; Krulac, I. L.

1982-09-01

This document summarizes storage reliability data collected by the US Army Missile Command on electro-mechanical devices over a period of several years. Sources of data are detailed, major failure modes and mechanisms are listed and discussed. Non-operational failure rate prediction methodology is given, and conclusions and recommendations for enhancing the storage reliability of devices are drawn from the analysis of collected data.

Effects of Assuming Independent Component Failure Times, If They Are Actually Dependent, in a Series System.

DTIC Science & Technology

1985-11-26

etc.).., Major decisions involving reliability ptudies, based on competing risk methodology , have been made in the past and will continue to be made...censoring mechanism. In such instances, the methodology for estimating relevant reliabili- ty probabilities has received considerable attention (cf. David...proposal for a discussion of the general methodology . .,4..% . - ’ -. - ’ . ’ , . * I - " . . - - - - . . ,_ . . . . . . . . .4

It is Time the United States Air Force Changes the way it Feeds its Airmen

DTIC Science & Technology

2008-03-01

narrative , phenomenology , ethnography , case study , and grounded theory . In purpose, these strategies are...methodology) the research will be analyzed. Methodology A qualitative research methodology and specifically a case study strategy for the...well as theory building in chapter five . Finally, in regards to reliability, Yin’s (2003) case study protocol guidance was used as a means to

Statistics-related and reliability-physics-related failure processes in electronics devices and products

NASA Astrophysics Data System (ADS)

Suhir, E.

2014-05-01

The well known and widely used experimental reliability "passport" of a mass manufactured electronic or a photonic product — the bathtub curve — reflects the combined contribution of the statistics-related and reliability-physics (physics-of-failure)-related processes. When time progresses, the first process results in a decreasing failure rate, while the second process associated with the material aging and degradation leads to an increased failure rate. An attempt has been made in this analysis to assess the level of the reliability physics-related aging process from the available bathtub curve (diagram). It is assumed that the products of interest underwent the burn-in testing and therefore the obtained bathtub curve does not contain the infant mortality portion. It has been also assumed that the two random processes in question are statistically independent, and that the failure rate of the physical process can be obtained by deducting the theoretically assessed statistical failure rate from the bathtub curve ordinates. In the carried out numerical example, the Raleigh distribution for the statistical failure rate was used, for the sake of a relatively simple illustration. The developed methodology can be used in reliability physics evaluations, when there is a need to better understand the roles of the statistics-related and reliability-physics-related irreversible random processes in reliability evaluations. The future work should include investigations on how powerful and flexible methods and approaches of the statistical mechanics can be effectively employed, in addition to reliability physics techniques, to model the operational reliability of electronic and photonic products.

Assessing the efficacy of the Measure of Understanding of Macroevolution as a valid tool for undergraduate non-science majors

NASA Astrophysics Data System (ADS)

Romine, William Lee; Walter, Emily Marie

2014-11-01

Efficacy of the Measure of Understanding of Macroevolution (MUM) as a measurement tool has been a point of contention among scholars needing a valid measure for knowledge of macroevolution. We explored the structure and construct validity of the MUM using Rasch methodologies in the context of a general education biology course designed with an emphasis on macroevolution content. The Rasch model was utilized to quantify item- and test-level characteristics, including dimensionality, reliability, and fit with the Rasch model. Contrary to previous work, we found that the MUM provides a valid, reliable, and unidimensional scale for measuring knowledge of macroevolution in introductory non-science majors, and that its psychometric behavior does not exhibit large changes across time. While we found that all items provide productive measurement information, several depart substantially from ideal behavior, warranting a collective effort to improve these items. Suggestions for improving the measurement characteristics of the MUM at the item and test levels are put forward and discussed.

Paper spray mass spectrometry and chemometric tools for a fast and reliable identification of counterfeit blended Scottish whiskies.

PubMed

Teodoro, Janaína Aparecida Reis; Pereira, Hebert Vinicius; Sena, Marcelo Martins; Piccin, Evandro; Zacca, Jorge Jardim; Augusti, Rodinei

2017-12-15

A direct method based on the application of paper spray mass spectrometry (PS-MS) combined with a chemometric supervised method (partial least square discriminant analysis, PLS-DA) was developed and applied to the discrimination of authentic and counterfeit samples of blended Scottish whiskies. The developed methodology employed the negative ion mode MS, included 44 authentic whiskies from diverse brands and batches and 44 counterfeit samples of the same brands seized during operations of the Brazilian Federal Police, totalizing 88 samples. An exploratory principal component analysis (PCA) model showed a reasonable discrimination of the counterfeit whiskies in PC2. In spite of the samples heterogeneity, a robust, reliable and accurate PLS-DA model was generated and validated, which was able to correctly classify the samples with nearly 100% success rate. The use of PS-MS also allowed the identification of the main marker compounds associated with each type of sample analyzed: authentic or counterfeit. Copyright © 2017 Elsevier Ltd. All rights reserved.

PseudoBase: a database with RNA pseudoknots.

PubMed

van Batenburg, F H; Gultyaev, A P; Pleij, C W; Ng, J; Oliehoek, J

2000-01-01

PseudoBase is a database containing structural, functional and sequence data related to RNA pseudo-knots. It can be reached at http://wwwbio. Leiden Univ.nl/ approximately Batenburg/PKB.html. This page will direct the user to a retrieval page from where a particular pseudoknot can be chosen, or to a submission page which enables the user to add pseudoknot information to the database or to an informative page that elaborates on the various aspects of the database. For each pseudoknot, 12 items are stored, e.g. the nucleotides of the region that contains the pseudoknot, the stem positions of the pseudoknot, the EMBL accession number of the sequence that contains this pseudoknot and the support that can be given regarding the reliability of the pseudoknot. Access is via a small number of steps, using 16 different categories. The development process was done by applying the evolutionary methodology for software development rather than by applying the methodology of the classical waterfall model or the more modern spiral model.

Development of performance assessment methodology for nuclear waste isolation in geologic media

NASA Astrophysics Data System (ADS)

Bonano, E. J.; Chu, M. S. Y.; Cranwell, R. M.; Davis, P. A.

The burial of nuclear wastes in deep geologic formations as a means for their disposal is an issue of significant technical and social impact. The analysis of the processes involved can be performed only with reliable mathematical models and computer codes as opposed to conducting experiments because the time scales associated are on the order of tens of thousands of years. These analyses are concerned primarily with the migration of radioactive contaminants from the repository to the environment accessible to humans. Modeling of this phenomenon depends on a large number of other phenomena taking place in the geologic porous and/or fractured medium. These are ground-water flow, physicochemical interactions of the contaminants with the rock, heat transfer, and mass transport. Once the radionuclides have reached the accessible environment, the pathways to humans and health effects are estimated. A performance assessment methodology for a potential high-level waste repository emplaced in a basalt formation has been developed for the U.S. Nuclear Regulatory Commission.

On-time reliability impacts of ATIS. Volume III, Implications for ATIS investment strategies

DOT National Transportation Integrated Search

2003-05-01

The effect of ATIS accuracy and extent of ATIS roadway instrumentation on the on-time reliability benefits to routine users of ATIS are evaluated through the application of Heuristic On-line Web-linked Arrival Time Estimation (HOWLATE) methodology. T...

34 CFR 462.11 - What must an application contain?

Code of Federal Regulations, 2010 CFR

2010-07-01

... the methodology and procedures used to measure the reliability of the test. (h) Construct validity... previous test, and results from validity, reliability, and equating or standard-setting studies undertaken... NRS educational functioning levels (content validity). Documentation of the extent to which the items...

75 FR 5779 - Proposed Emergency Agency Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-04

... proposed collection of information, including the validity of the methodology and assumptions used; (c... Collection Request Title: Electricity Delivery and Energy Reliability Recovery Act Smart Grid Grant Program..., Chief Operating Officer, Electricity Delivery and Energy Reliability. [FR Doc. 2010-2422 Filed 2-3-10; 8...

Meta-Analysis of Coefficient Alpha

ERIC Educational Resources Information Center

Rodriguez, Michael C.; Maeda, Yukiko

2006-01-01

The meta-analysis of coefficient alpha across many studies is becoming more common in psychology by a methodology labeled reliability generalization. Existing reliability generalization studies have not used the sampling distribution of coefficient alpha for precision weighting and other common meta-analytic procedures. A framework is provided for…

Deterministic Multiaxial Creep and Creep Rupture Enhancements for CARES/Creep Integrated Design Code

NASA Technical Reports Server (NTRS)

Jadaan, Osama M.

1998-01-01

High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep rupture criterion. However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of sum, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of Ns methodology and the CARES/Creep program.

Deterministic and Probabilistic Creep and Creep Rupture Enhancement to CARES/Creep: Multiaxial Creep Life Prediction of Ceramic Structures Using Continuum Damage Mechanics and the Finite Element Method

NASA Technical Reports Server (NTRS)

Jadaan, Osama M.; Powers, Lynn M.; Gyekenyesi, John P.

1998-01-01

High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep ripture criterion However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of stress, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of this methodology and the CARES/Creep program.

A Methodology for the Integration of a Mechanistic Source Term Analysis in a Probabilistic Framework for Advanced Reactors

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

Grabaskas, Dave; Brunett, Acacia J.; Bucknor, Matthew

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory are currently engaged in a joint effort to modernize and develop probabilistic risk assessment (PRA) techniques for advanced non-light water reactors. At a high level, the primary outcome of this project will be the development of next-generation PRA methodologies that will enable risk-informed prioritization of safety- and reliability-focused research and development, while also identifying gaps that may be resolved through additional research. A subset of this effort is the development of PRA methodologies to conduct a mechanistic source term (MST) analysis for event sequences that could result in the release ofmore » radionuclides. The MST analysis seeks to realistically model and assess the transport, retention, and release of radionuclides from the reactor to the environment. The MST methods developed during this project seek to satisfy the requirements of the Mechanistic Source Term element of the ASME/ANS Non-LWR PRA standard. The MST methodology consists of separate analysis approaches for risk-significant and non-risk significant event sequences that may result in the release of radionuclides from the reactor. For risk-significant event sequences, the methodology focuses on a detailed assessment, using mechanistic models, of radionuclide release from the fuel, transport through and release from the primary system, transport in the containment, and finally release to the environment. The analysis approach for non-risk significant event sequences examines the possibility of large radionuclide releases due to events such as re-criticality or the complete loss of radionuclide barriers. This paper provides details on the MST methodology, including the interface between the MST analysis and other elements of the PRA, and provides a simplified example MST calculation for a sodium fast reactor.« less

Excessive Aggression as Model of Violence: A Critical Evaluation of Current Preclinical Methods

PubMed Central

Miczek, Klaus A.; de Boer, Sietse F.; Haller, Jozsef

2013-01-01

Rationale Preclinical experimental models of pathological aggressive behavior are a sorely understudied and difficult research area. Objectives How valid, reliable, productive and informative are the most frequently used animal models of excessive aggressive behavior? Methods The rationale, key methodological features, supporting data and arguments as well as their disadvantages and limitations of the most frequently used animal models for excessive aggressive behavior are summarized and their validity and reliability are evaluated. Results Excessive aggressive behavior is validly and reliably seen in (1) a proportion of feral-derived rats and selectively bred mice, (2) rats with compromised adrenal function resulting in a hypoglucocorticoid state, (3) a significant minority of mice, rats and monkeys after consumption of a moderate dose of alcohol, and (4) resident animals of various species after social instigation. Limitations of these procedures include restrictive animal research regulations, the requirement of expertise in surgical, pharmacological and behavioral techniques, and the behaviorally impoverished mouse strains that are used in molecular genetics research. Promising recent initiatives for novel experimental models include aggressive behaviors that are evoked by optogenetic stimulation and induced by the manipulation of early social experiences such as isolation rearing or social stress. Conclusions One of the most significant challenges for animal models of excessive, potentially abnormal aggressive behavior is the characterization of distinctive neurobiological mechanisms that differ from those governing species-typical aggressive behavior. Identifying novel targets for effective intervention requires increased understanding of the distinctive molecular, cellular and circuit mechanisms for each type of abnormal aggressive behavior. PMID:23430160

Aerospace reliability applied to biomedicine.

NASA Technical Reports Server (NTRS)

Lalli, V. R.; Vargo, D. J.

1972-01-01

An analysis is presented that indicates that the reliability and quality assurance methodology selected by NASA to minimize failures in aerospace equipment can be applied directly to biomedical devices to improve hospital equipment reliability. The Space Electric Rocket Test project is used as an example of NASA application of reliability and quality assurance (R&QA) methods. By analogy a comparison is made to show how these same methods can be used in the development of transducers, instrumentation, and complex systems for use in medicine.

Prioritization methodology for chemical replacement

NASA Technical Reports Server (NTRS)

Goldberg, Ben; Cruit, Wendy; Schutzenhofer, Scott

1995-01-01

This methodology serves to define a system for effective prioritization of efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semi quantitative approach derived from quality function deployment techniques (QFD Matrix). QFD is a conceptual map that provides a method of transforming customer wants and needs into quantitative engineering terms. This methodology aims to weight the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives.

'Emerging technologies for the changing global market' - Prioritization methodology for chemical replacement

NASA Technical Reports Server (NTRS)

Cruit, Wendy; Schutzenhofer, Scott; Goldberg, Ben; Everhart, Kurt

1993-01-01

This project served to define an appropriate methodology for effective prioritization of technology efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semiquantitative approach derived from quality function deployment techniques (QFD Matrix). This methodology aims to weight the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives. The results will be implemented as a guideline for consideration for current NASA propulsion systems.

Application of crowd-sourced data to multi-scale evolutionary exposure and vulnerability models

NASA Astrophysics Data System (ADS)

Pittore, Massimiliano

2016-04-01

Seismic exposure, defined as the assets (population, buildings, infrastructure) exposed to earthquake hazard and susceptible to damage, is a critical -but often neglected- component of seismic risk assessment. This partly stems from the burden associated with the compilation of a useful and reliable model over wide spatial areas. While detailed engineering data have still to be collected in order to constrain exposure and vulnerability models, the availability of increasingly large crowd-sourced datasets (e. g. OpenStreetMap) opens up the exciting possibility to generate incrementally evolving models. Integrating crowd-sourced and authoritative data using statistical learning methodologies can reduce models uncertainties and also provide additional drive and motivation to volunteered geoinformation collection. A case study in Central Asia will be presented and discussed.

An analytic model for footprint dispersions and its application to mission design

NASA Technical Reports Server (NTRS)

Rao, J. R. Jagannatha; Chen, Yi-Chao

1992-01-01

This is the final report on our recent research activities that are complementary to those conducted by our colleagues, Professor Farrokh Mistree and students, in the context of the Taguchi method. We have studied the mathematical model that forms the basis of the Simulation and Optimization of Rocket Trajectories (SORT) program and developed an analytic method for determining mission reliability with a reduced number of flight simulations. This method can be incorporated in a design algorithm to mathematically optimize different performance measures of a mission, thus leading to a robust and easy-to-use methodology for mission planning and design.

Maximum Likelihood Item Easiness Models for Test Theory Without an Answer Key

PubMed Central

Batchelder, William H.

2014-01-01

Cultural consensus theory (CCT) is a data aggregation technique with many applications in the social and behavioral sciences. We describe the intuition and theory behind a set of CCT models for continuous type data using maximum likelihood inference methodology. We describe how bias parameters can be incorporated into these models. We introduce two extensions to the basic model in order to account for item rating easiness/difficulty. The first extension is a multiplicative model and the second is an additive model. We show how the multiplicative model is related to the Rasch model. We describe several maximum-likelihood estimation procedures for the models and discuss issues of model fit and identifiability. We describe how the CCT models could be used to give alternative consensus-based measures of reliability. We demonstrate the utility of both the basic and extended models on a set of essay rating data and give ideas for future research. PMID:29795812

Factors Influencing the Reliability of the Glasgow Coma Scale: A Systematic Review.

PubMed

Reith, Florence Cm; Synnot, Anneliese; van den Brande, Ruben; Gruen, Russell L; Maas, Andrew Ir

2017-06-01

The Glasgow Coma Scale (GCS) characterizes patients with diminished consciousness. In a recent systematic review, we found overall adequate reliability across different clinical settings, but reliability estimates varied considerably between studies, and methodological quality of studies was overall poor. Identifying and understanding factors that can affect its reliability is important, in order to promote high standards for clinical use of the GCS. The aim of this systematic review was to identify factors that influence reliability and to provide an evidence base for promoting consistent and reliable application of the GCS. A comprehensive literature search was undertaken in MEDLINE, EMBASE, and CINAHL from 1974 to July 2016. Studies assessing the reliability of the GCS in adults or describing any factor that influences reliability were included. Two reviewers independently screened citations, selected full texts, and undertook data extraction and critical appraisal. Methodological quality of studies was evaluated with the consensus-based standards for the selection of health measurement instruments checklist. Data were synthesized narratively and presented in tables. Forty-one studies were included for analysis. Factors identified that may influence reliability are education and training, the level of consciousness, and type of stimuli used. Conflicting results were found for experience of the observer, the pathology causing the reduced consciousness, and intubation/sedation. No clear influence was found for the professional background of observers. Reliability of the GCS is influenced by multiple factors and as such is context dependent. This review points to the potential for improvement from training and education and standardization of assessment methods, for which recommendations are presented. Copyright © 2017 by the Congress of Neurological Surgeons.

Tracing catchment fine sediment sources using the new SIFT (SedIment Fingerprinting Tool) open source software.

PubMed

Pulley, S; Collins, A L

2018-09-01

The mitigation of diffuse sediment pollution requires reliable provenance information so that measures can be targeted. Sediment source fingerprinting represents one approach for supporting these needs, but recent methodological developments have resulted in an increasing complexity of data processing methods rendering the approach less accessible to non-specialists. A comprehensive new software programme (SIFT; SedIment Fingerprinting Tool) has therefore been developed which guides the user through critical data analysis decisions and automates all calculations. Multiple source group configurations and composite fingerprints are identified and tested using multiple methods of uncertainty analysis. This aims to explore the sediment provenance information provided by the tracers more comprehensively than a single model, and allows for model configurations with high uncertainties to be rejected. This paper provides an overview of its application to an agricultural catchment in the UK to determine if the approach used can provide a reduction in uncertainty and increase in precision. Five source group classifications were used; three formed using a k-means cluster analysis containing 2, 3 and 4 clusters, and two a-priori groups based upon catchment geology. Three different composite fingerprints were used for each classification and bi-plots, range tests, tracer variability ratios and virtual mixtures tested the reliability of each model configuration. Some model configurations performed poorly when apportioning the composition of virtual mixtures, and different model configurations could produce different sediment provenance results despite using composite fingerprints able to discriminate robustly between the source groups. Despite this uncertainty, dominant sediment sources were identified, and those in close proximity to each sediment sampling location were found to be of greatest importance. This new software, by integrating recent methodological developments in tracer data processing, guides users through key steps. Critically, by applying multiple model configurations and uncertainty assessment, it delivers more robust solutions for informing catchment management of the sediment problem than many previously used approaches. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Effect of Cyclic Thermo-Mechanical Loads on Fatigue Reliability in Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Shah, A. R.; Murthy, P. L. N.; Chamis, C. C.

1996-01-01

A methodology to compute probabilistic fatigue life of polymer matrix laminated composites has been developed and demonstrated. Matrix degradation effects caused by long term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress dependent multi-factor interaction relationship developed at NASA Lewis Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability- based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/- 45/90)(sub s) graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical cyclic loads and low thermal cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical cyclic loads and high thermal cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

The transparency, reliability and utility of tropical rainforest land-use and land-cover change models.

PubMed

Rosa, Isabel M D; Ahmed, Sadia E; Ewers, Robert M

2014-06-01

Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the discipline. © 2014 John Wiley & Sons Ltd.

Modelling an induced thermal plume with data from electrical resistivity tomography and distributed temperature sensing: a case study in northeast Italy

NASA Astrophysics Data System (ADS)

Cultrera, Matteo; Boaga, Jacopo; Di Sipio, Eloisa; Dalla Santa, Giorgia; De Seta, Massimiliano; Galgaro, Antonio

2018-05-01

Groundwater tracer tests are often used to improve aquifer characterization, but they present several disadvantages, such as the need to pour solutions or dyes into the aquifer system and alteration of the water's chemical properties. Thus, tracers can affect the groundwater flow mechanics and data interpretation becomes more complex, hindering effective study of ground heat pumps for low enthalpy geothermal systems. This paper presents a preliminary methodology based on a multidisciplinary application of heat as a tracer for defining the main parameters of shallow aquifers. The field monitoring techniques electrical resistivity tomography (ERT) and distributed temperature sensing (DTS) are noninvasive and were applied to a shallow-aquifer test site in northeast Italy. The combination of these measurement techniques supports the definition of the main aquifer parameters and therefore the construction of a reliable conceptual model, which is then described through the numerical code FEFLOW. This model is calibrated with DTS and validated by ERT outcomes. The reliability of the numerical model in terms of fate and transport is thereby enhanced, leading to the potential for better environmental management and protection of groundwater resources through more cost-effective solutions.

Improving the geomagnetic field modeling with a selection of high-quality archaeointensity data

NASA Astrophysics Data System (ADS)

Pavon-Carrasco, Francisco Javier; Gomez-Paccard, Miriam; Herve, Gwenael; Osete, Maria Luisa; Chauvin, Annick

2014-05-01

Geomagnetic field reconstructions for the last millennia are based on archeomagnetic data. However, the scatter of the archaeointensity data is very puzzling and clearly suggests that some of the intensity data might not be reliable. In this work we apply different selection criteria to the European and Western Asian archaeointensity data covering the last three millennia in order to investigate if the data selection affects geomagnetic field models results. Thanks to the recently developed archeomagnetic databases, new valuable information related to the methodology used to determine the archeointensity data is now available. We therefore used this information to rank the archaeointensity data in four quality categories depending on the methodology used during the laboratory treatment of the samples and on the number of specimens retained to calculate the mean intensities. Results show how the intensity geomagnetic field component given by the regional models hardly depends on the selected quality data used. When all the available data are used a different behavior of the geomagnetic field is observed in Western and Eastern Europe. However, when the regional model is obtained from a selection of high-quality intensity data the same features are observed at the European scale.

Update in the methodology of the chronic stress paradigm: internal control matters

PubMed Central

2011-01-01

To date, the reliability of induction of a depressive-like state using chronic stress models is confronted by many methodological limitations. We believe that the modifications to the stress paradigm in mice proposed herein allow some of these limitations to be overcome. Here, we discuss a variant of the standard stress paradigm, which results in anhedonia. This anhedonic state was defined by a decrease in sucrose preference that was not exhibited by all animals. As such, we propose the use of non-anhedonic, stressed mice as an internal control in experimental mouse models of depression. The application of an internal control for the effects of stress, along with optimized behavioural testing, can enable the analysis of biological correlates of stress-induced anhedonia versus the consequences of stress alone in a chronic-stress depression model. This is illustrated, for instance, by distinct physiological and molecular profiles in anhedonic and non-anhedonic groups subjected to stress. These results argue for the use of a subgroup of individuals who are negative for the induction of a depressive phenotype during experimental paradigms of depression as an internal control, for more refined modeling of this disorder in animals. PMID:21524310

Update in the methodology of the chronic stress paradigm: internal control matters.

PubMed

Strekalova, Tatyana; Couch, Yvonne; Kholod, Natalia; Boyks, Marco; Malin, Dmitry; Leprince, Pierre; Steinbusch, Harry Mw

2011-04-27

To date, the reliability of induction of a depressive-like state using chronic stress models is confronted by many methodological limitations. We believe that the modifications to the stress paradigm in mice proposed herein allow some of these limitations to be overcome. Here, we discuss a variant of the standard stress paradigm, which results in anhedonia. This anhedonic state was defined by a decrease in sucrose preference that was not exhibited by all animals. As such, we propose the use of non-anhedonic, stressed mice as an internal control in experimental mouse models of depression. The application of an internal control for the effects of stress, along with optimized behavioural testing, can enable the analysis of biological correlates of stress-induced anhedonia versus the consequences of stress alone in a chronic-stress depression model. This is illustrated, for instance, by distinct physiological and molecular profiles in anhedonic and non-anhedonic groups subjected to stress. These results argue for the use of a subgroup of individuals who are negative for the induction of a depressive phenotype during experimental paradigms of depression as an internal control, for more refined modeling of this disorder in animals.

Source Data Impacts on Epistemic Uncertainty for Launch Vehicle Fault Tree Models

NASA Technical Reports Server (NTRS)

Al Hassan, Mohammad; Novack, Steven; Ring, Robert

2016-01-01

Launch vehicle systems are designed and developed using both heritage and new hardware. Design modifications to the heritage hardware to fit new functional system requirements can impact the applicability of heritage reliability data. Risk estimates for newly designed systems must be developed from generic data sources such as commercially available reliability databases using reliability prediction methodologies, such as those addressed in MIL-HDBK-217F. Failure estimates must be converted from the generic environment to the specific operating environment of the system in which it is used. In addition, some qualification of applicability for the data source to the current system should be made. Characterizing data applicability under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This paper will demonstrate a data-source applicability classification method for suggesting epistemic component uncertainty to a target vehicle based on the source and operating environment of the originating data. The source applicability is determined using heuristic guidelines while translation of operating environments is accomplished by applying statistical methods to MIL-HDK-217F tables. The paper will provide one example for assigning environmental factors uncertainty when translating between operating environments for the microelectronic part-type components. The heuristic guidelines will be followed by uncertainty-importance routines to assess the need for more applicable data to reduce model uncertainty.

Reliability analysis of single crystal NiAl turbine blades

NASA Technical Reports Server (NTRS)

Salem, Jonathan; Noebe, Ronald; Wheeler, Donald R.; Holland, Fred; Palko, Joseph; Duffy, Stephen; Wright, P. Kennard

1995-01-01

As part of a co-operative agreement with General Electric Aircraft Engines (GEAE), NASA LeRC is modifying and validating the Ceramic Analysis and Reliability Evaluation of Structures algorithm for use in design of components made of high strength NiAl based intermetallic materials. NiAl single crystal alloys are being actively investigated by GEAE as a replacement for Ni-based single crystal superalloys for use in high pressure turbine blades and vanes. The driving force for this research lies in the numerous property advantages offered by NiAl alloys over their superalloy counterparts. These include a reduction of density by as much as a third without significantly sacrificing strength, higher melting point, greater thermal conductivity, better oxidation resistance, and a better response to thermal barrier coatings. The current drawback to high strength NiAl single crystals is their limited ductility. Consequently, significant efforts including the work agreement with GEAE are underway to develop testing and design methodologies for these materials. The approach to validation and component analysis involves the following steps: determination of the statistical nature and source of fracture in a high strength, NiAl single crystal turbine blade material; measurement of the failure strength envelope of the material; coding of statistically based reliability models; verification of the code and model; and modeling of turbine blades and vanes for rig testing.

Owls, larks, swifts, woodcocks and they are not alone: A historical review of methodology for multidimensional self-assessment of individual differences in sleep-wake pattern.

PubMed

Putilov, Arcady A

2017-01-01

Differences between the so-called larks and owls representing the opposite poles of morningness-eveningness dimension are widely known. However, scientific consensus has not yet been reached on the methodology for ranking and typing people along other dimensions of individual variation in their sleep-wake pattern. This review focused on the history and state-of-the-art of the methodology for self-assessment of individual differences in more than one trait or adaptability of the human sleep-wake cycle. The differences between this and other methodologies for the self-assessment of trait- and state-like variation in the perceived characteristics of daily rhythms were discussed and the critical issues that remained to be addressed in future studies were highlighted. These issues include a) a failure to develop a unidimensional scale for scoring chronotypological differences, b) the inconclusive results of the long-lasting search for objective markers of chronotype, c) a disagreement on both number and content of scales required for multidimensional self-assessment of chronobiological differences, d) a lack of evidence for the reliability and/or external validity of most of the proposed scales and e) an insufficient development of conceptualizations, models and model-based quantitative simulations linking the differences between people in their sleep-wake pattern with the differences in the basic parameters of underlying chronoregulatory processes. It seems that, in the nearest future, the wide implementation of portable actigraphic and somnographic devices might lead to the development of objective methodologies for multidimensional assessment and classification of sleep-wake traits and adaptabilities.

Correcting Fallacies in Validity, Reliability, and Classification

ERIC Educational Resources Information Center

Sijtsma, Klaas

2009-01-01

This article reviews three topics from test theory that continue to raise discussion and controversy and capture test theorists' and constructors' interest. The first topic concerns the discussion of the methodology of investigating and establishing construct validity; the second topic concerns reliability and its misuse, alternative definitions…

76 FR 3604 - Information Collection; Qualified Products List for Engine Driven Pumps

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-20

... levels. 2. Reliability and endurance requirements. These requirements include a 100-hour endurance test... evaluated to meet specific requirements related to safety, effectiveness, efficiency, and reliability of the... of the collection of information, including the validity of the methodology and assumptions used; (3...

Problem Solving in Biology: A Methodology

ERIC Educational Resources Information Center

Wisehart, Gary; Mandell, Mark

2008-01-01

A methodology is described that teaches science process by combining informal logic and a heuristic for rating factual reliability. This system facilitates student hypothesis formation, testing, and evaluation of results. After problem solving with this scheme, students are asked to examine and evaluate arguments for the underlying principles of…

Sampling strategies based on singular vectors for assimilated models in ocean forecasting systems

NASA Astrophysics Data System (ADS)

Fattorini, Maria; Brandini, Carlo; Ortolani, Alberto

2016-04-01

Meteorological and oceanographic models do need observations, not only as a ground truth element to verify the quality of the models, but also to keep model forecast error acceptable: through data assimilation techniques which merge measured and modelled data, natural divergence of numerical solutions from reality can be reduced / controlled and a more reliable solution - called analysis - is computed. Although this concept is valid in general, its application, especially in oceanography, raises many problems due to three main reasons: the difficulties that have ocean models in reaching an acceptable state of equilibrium, the high measurements cost and the difficulties in realizing them. The performances of the data assimilation procedures depend on the particular observation networks in use, well beyond the background quality and the used assimilation method. In this study we will present some results concerning the great impact of the dataset configuration, in particular measurements position, on the evaluation of the overall forecasting reliability of an ocean model. The aim consists in identifying operational criteria to support the design of marine observation networks at regional scale. In order to identify the observation network able to minimize the forecast error, a methodology based on Singular Vectors Decomposition of the tangent linear model is proposed. Such a method can give strong indications on the local error dynamics. In addition, for the purpose of avoiding redundancy of information contained in the data, a minimal distance among data positions has been chosen on the base of a spatial correlation analysis of the hydrodynamic fields under investigation. This methodology has been applied for the choice of data positions starting from simplified models, like an ideal double-gyre model and a quasi-geostrophic one. Model configurations and data assimilation are based on available ROMS routines, where a variational assimilation algorithm (4D-var) is included as part of the code These first applications have provided encouraging results in terms of increased predictability time and reduced forecast error, also improving the quality of the analysis used to recover the real circulation patterns from a first guess quite far from the real state.

Methodology for building confidence measures

NASA Astrophysics Data System (ADS)

Bramson, Aaron L.

2004-04-01

This paper presents a generalized methodology for propagating known or estimated levels of individual source document truth reliability to determine the confidence level of a combined output. Initial document certainty levels are augmented by (i) combining the reliability measures of multiply sources, (ii) incorporating the truth reinforcement of related elements, and (iii) incorporating the importance of the individual elements for determining the probability of truth for the whole. The result is a measure of confidence in system output based on the establishing of links among the truth values of inputs. This methodology was developed for application to a multi-component situation awareness tool under development at the Air Force Research Laboratory in Rome, New York. Determining how improvements in data quality and the variety of documents collected affect the probability of a correct situational detection helps optimize the performance of the tool overall.

Validation of model predictions of pore-scale fluid distributions during two-phase flow

NASA Astrophysics Data System (ADS)

Bultreys, Tom; Lin, Qingyang; Gao, Ying; Raeini, Ali Q.; AlRatrout, Ahmed; Bijeljic, Branko; Blunt, Martin J.

2018-05-01

Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.

A Bayesian approach to reliability and confidence

NASA Technical Reports Server (NTRS)

Barnes, Ron

1989-01-01

The historical evolution of NASA's interest in quantitative measures of reliability assessment is outlined. The introduction of some quantitative methodologies into the Vehicle Reliability Branch of the Safety, Reliability and Quality Assurance (SR and QA) Division at Johnson Space Center (JSC) was noted along with the development of the Extended Orbiter Duration--Weakest Link study which will utilize quantitative tools for a Bayesian statistical analysis. Extending the earlier work of NASA sponsor, Richard Heydorn, researchers were able to produce a consistent Bayesian estimate for the reliability of a component and hence by a simple extension for a system of components in some cases where the rate of failure is not constant but varies over time. Mechanical systems in general have this property since the reliability usually decreases markedly as the parts degrade over time. While they have been able to reduce the Bayesian estimator to a simple closed form for a large class of such systems, the form for the most general case needs to be attacked by the computer. Once a table is generated for this form, researchers will have a numerical form for the general solution. With this, the corresponding probability statements about the reliability of a system can be made in the most general setting. Note that the utilization of uniform Bayesian priors represents a worst case scenario in the sense that as researchers incorporate more expert opinion into the model, they will be able to improve the strength of the probability calculations.

Psychometric Properties and Factor Structure of the German Version of the Clinician-Administered PTSD Scale for DSM-5.

PubMed

Müller-Engelmann, Meike; Schnyder, Ulrich; Dittmann, Clara; Priebe, Kathlen; Bohus, Martin; Thome, Janine; Fydrich, Thomas; Pfaltz, Monique C; Steil, Regina

2018-05-01

The Clinician-Administered PTSD Scale (CAPS) is a widely used diagnostic interview for posttraumatic stress disorder (PTSD). Following fundamental modifications in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition ( DSM-5), the CAPS had to be revised. This study examined the psychometric properties (internal consistency, interrater reliability, convergent and discriminant validity, and structural validity) of the German version of the CAPS-5 in a trauma-exposed sample ( n = 223 with PTSD; n =51 without PTSD). The results demonstrated high internal consistency (αs = .65-.93) and high interrater reliability (ICCs = .81-.89). With regard to convergent and discriminant validity, we found high correlations between the CAPS severity score and both the Posttraumatic Diagnostic Scale sum score ( r = .87) and the Beck Depression Inventory total score ( r = .72). Regarding the underlying factor structure, the hybrid model demonstrated the best fit, followed by the anhedonia model. However, we encountered some nonpositive estimates for the correlations of the latent variables (factors) for both models. The model with the best fit without methodological problems was the externalizing behaviors model, but the results also supported the DSM-5 model. Overall, the results demonstrate that the German version of the CAPS-5 is a psychometrically sound measure.

Comparison of two stochastic techniques for reliable urban runoff prediction by modeling systematic errors

NASA Astrophysics Data System (ADS)

Del Giudice, Dario; Löwe, Roland; Madsen, Henrik; Mikkelsen, Peter Steen; Rieckermann, Jörg

2015-07-01

In urban rainfall-runoff, commonly applied statistical techniques for uncertainty quantification mostly ignore systematic output errors originating from simplified models and erroneous inputs. Consequently, the resulting predictive uncertainty is often unreliable. Our objective is to present two approaches which use stochastic processes to describe systematic deviations and to discuss their advantages and drawbacks for urban drainage modeling. The two methodologies are an external bias description (EBD) and an internal noise description (IND, also known as stochastic gray-box modeling). They emerge from different fields and have not yet been compared in environmental modeling. To compare the two approaches, we develop a unifying terminology, evaluate them theoretically, and apply them to conceptual rainfall-runoff modeling in the same drainage system. Our results show that both approaches can provide probabilistic predictions of wastewater discharge in a similarly reliable way, both for periods ranging from a few hours up to more than 1 week ahead of time. The EBD produces more accurate predictions on long horizons but relies on computationally heavy MCMC routines for parameter inferences. These properties make it more suitable for off-line applications. The IND can help in diagnosing the causes of output errors and is computationally inexpensive. It produces best results on short forecast horizons that are typical for online applications.

Measurement properties of existing clinical assessment methods evaluating scapular positioning and function. A systematic review.

PubMed

Larsen, Camilla Marie; Juul-Kristensen, Birgit; Lund, Hans; Søgaard, Karen

2014-10-01

The aims were to compile a schematic overview of clinical scapular assessment methods and critically appraise the methodological quality of the involved studies. A systematic, computer-assisted literature search using Medline, CINAHL, SportDiscus and EMBASE was performed from inception to October 2013. Reference lists in articles were also screened for publications. From 50 articles, 54 method names were identified and categorized into three groups: (1) Static positioning assessment (n = 19); (2) Semi-dynamic (n = 13); and (3) Dynamic functional assessment (n = 22). Fifteen studies were excluded for evaluation due to no/few clinimetric results, leaving 35 studies for evaluation. Graded according to the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN checklist), the methodological quality in the reliability and validity domains was "fair" (57%) to "poor" (43%), with only one study rated as "good". The reliability domain was most often investigated. Few of the assessment methods in the included studies that had "fair" or "good" measurement property ratings demonstrated acceptable results for both reliability and validity. We found a substantially larger number of clinical scapular assessment methods than previously reported. Using the COSMIN checklist the methodological quality of the included measurement properties in the reliability and validity domains were in general "fair" to "poor". None were examined for all three domains: (1) reliability; (2) validity; and (3) responsiveness. Observational evaluation systems and assessment of scapular upward rotation seem suitably evidence-based for clinical use. Future studies should test and improve the clinimetric properties, and especially diagnostic accuracy and responsiveness, to increase utility for clinical practice.

Validity and reliability of Internet-based physiotherapy assessment for musculoskeletal disorders: a systematic review.

PubMed

Mani, Suresh; Sharma, Shobha; Omar, Baharudin; Paungmali, Aatit; Joseph, Leonard

2017-04-01

Purpose The purpose of this review is to systematically explore and summarise the validity and reliability of telerehabilitation (TR)-based physiotherapy assessment for musculoskeletal disorders. Method A comprehensive systematic literature review was conducted using a number of electronic databases: PubMed, EMBASE, PsycINFO, Cochrane Library and CINAHL, published between January 2000 and May 2015. The studies examined the validity, inter- and intra-rater reliabilities of TR-based physiotherapy assessment for musculoskeletal conditions were included. Two independent reviewers used the Quality Appraisal Tool for studies of diagnostic Reliability (QAREL) and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool to assess the methodological quality of reliability and validity studies respectively. Results A total of 898 hits were achieved, of which 11 articles based on inclusion criteria were reviewed. Nine studies explored the concurrent validity, inter- and intra-rater reliabilities, while two studies examined only the concurrent validity. Reviewed studies were moderate to good in methodological quality. The physiotherapy assessments such as pain, swelling, range of motion, muscle strength, balance, gait and functional assessment demonstrated good concurrent validity. However, the reported concurrent validity of lumbar spine posture, special orthopaedic tests, neurodynamic tests and scar assessments ranged from low to moderate. Conclusion TR-based physiotherapy assessment was technically feasible with overall good concurrent validity and excellent reliability, except for lumbar spine posture, orthopaedic special tests, neurodynamic testa and scar assessment.

Reliability Issues and Solutions in Flexible Electronics Under Mechanical Fatigue

NASA Astrophysics Data System (ADS)

Yi, Seol-Min; Choi, In-Suk; Kim, Byoung-Joon; Joo, Young-Chang

2018-07-01

Flexible devices are of significant interest due to their potential expansion of the application of smart devices into various fields, such as energy harvesting, biological applications and consumer electronics. Due to the mechanically dynamic operations of flexible electronics, their mechanical reliability must be thoroughly investigated to understand their failure mechanisms and lifetimes. Reliability issue caused by bending fatigue, one of the typical operational limitations of flexible electronics, has been studied using various test methodologies; however, electromechanical evaluations which are essential to assess the reliability of electronic devices for flexible applications had not been investigated because the testing method was not established. By employing the in situ bending fatigue test, we has studied the failure mechanism for various conditions and parameters, such as bending strain, fatigue area, film thickness, and lateral dimensions. Moreover, various methods for improving the bending reliability have been developed based on the failure mechanism. Nanostructures such as holes, pores, wires and composites of nanoparticles and nanotubes have been suggested for better reliability. Flexible devices were also investigated to find the potential failures initiated by complex structures under bending fatigue strain. In this review, the recent advances in test methodology, mechanism studies, and practical applications are introduced. Additionally, perspectives including the future advance to stretchable electronics are discussed based on the current achievements in research.

Reliability Issues and Solutions in Flexible Electronics Under Mechanical Fatigue

NASA Astrophysics Data System (ADS)

Yi, Seol-Min; Choi, In-Suk; Kim, Byoung-Joon; Joo, Young-Chang

2018-03-01

Flexible devices are of significant interest due to their potential expansion of the application of smart devices into various fields, such as energy harvesting, biological applications and consumer electronics. Due to the mechanically dynamic operations of flexible electronics, their mechanical reliability must be thoroughly investigated to understand their failure mechanisms and lifetimes. Reliability issue caused by bending fatigue, one of the typical operational limitations of flexible electronics, has been studied using various test methodologies; however, electromechanical evaluations which are essential to assess the reliability of electronic devices for flexible applications had not been investigated because the testing method was not established. By employing the in situ bending fatigue test, we has studied the failure mechanism for various conditions and parameters, such as bending strain, fatigue area, film thickness, and lateral dimensions. Moreover, various methods for improving the bending reliability have been developed based on the failure mechanism. Nanostructures such as holes, pores, wires and composites of nanoparticles and nanotubes have been suggested for better reliability. Flexible devices were also investigated to find the potential failures initiated by complex structures under bending fatigue strain. In this review, the recent advances in test methodology, mechanism studies, and practical applications are introduced. Additionally, perspectives including the future advance to stretchable electronics are discussed based on the current achievements in research.

Moving from theory to practice: A participatory social network mapping approach to address unmet need for family planning in Benin.

PubMed

Igras, Susan; Diakité, Mariam; Lundgren, Rebecka

2017-07-01

In West Africa, social factors influence whether couples with unmet need for family planning act on birth-spacing desires. Tékponon Jikuagou is testing a social network-based intervention to reduce social barriers by diffusing new ideas. Individuals and groups judged socially influential by their communities provide entrée to networks. A participatory social network mapping methodology was designed to identify these diffusion actors. Analysis of monitoring data, in-depth interviews, and evaluation reports assessed the methodology's acceptability to communities and staff and whether it produced valid, reliable data to identify influential individuals and groups who diffuse new ideas through their networks. Results indicated the methodology's acceptability. Communities were actively and equitably engaged. Staff appreciated its ability to yield timely, actionable information. The mapping methodology also provided valid and reliable information by enabling communities to identify highly connected and influential network actors. Consistent with social network theory, this methodology resulted in the selection of informal groups and individuals in both informal and formal positions. In-depth interview data suggest these actors were diffusing new ideas, further confirming their influence/connectivity. The participatory methodology generated insider knowledge of who has social influence, challenging commonly held assumptions. Collecting and displaying information fostered staff and community learning, laying groundwork for social change.

Site-specific to local-scale shallow landslides triggering zones assessment using TRIGRS

NASA Astrophysics Data System (ADS)

Bordoni, M.; Meisina, C.; Valentino, R.; Bittelli, M.; Chersich, S.

2015-05-01

Rainfall-induced shallow landslides are common phenomena in many parts of the world, affecting cultivation and infrastructure and sometimes causing human losses. Assessing the triggering zones of shallow landslides is fundamental for land planning at different scales. This work defines a reliable methodology to extend a slope stability analysis from the site-specific to local scale by using a well-established physically based model (TRIGRS-unsaturated). The model is initially applied to a sample slope and then to the surrounding 13.4 km2 area in Oltrepo Pavese (northern Italy). To obtain more reliable input data for the model, long-term hydro-meteorological monitoring has been carried out at the sample slope, which has been assumed to be representative of the study area. Field measurements identified the triggering mechanism of shallow failures and were used to verify the reliability of the model to obtain pore water pressure trends consistent with those measured during the monitoring activity. In this way, more reliable trends have been modelled for past landslide events, such as the April 2009 event that was assumed as a benchmark. The assessment of shallow landslide triggering zones obtained using TRIGRS-unsaturated for the benchmark event appears good for both the monitored slope and the whole study area, with better results when a pedological instead of geological zoning is considered at the regional scale. The sensitivity analyses of the influence of the soil input data show that the mean values of the soil properties give the best results in terms of the ratio between the true positive and false positive rates. The scheme followed in this work allows us to obtain better results in the assessment of shallow landslide triggering areas in terms of the reduction in the overestimation of unstable zones with respect to other distributed models applied in the past.

Validation of the Practice Environment Scale to the Brazilian culture.

PubMed

Gasparino, Renata C; Guirardello, Edinêis de B

2017-07-01

To validate the Brazilian version of the Practice Environment Scale. The Practice Environment Scale is a tool that evaluates the presence of characteristics that are favourable for professional nursing practice because a better work environment contributes to positive results for patients, professionals and institutions. Methodological study including 209 nurses. Validity was assessed via a confirmatory factor analysis using structural equation modelling, in which the correlations between the instrument and the following variables were tested: burnout, job satisfaction, safety climate, perception of quality of care and intention to leave the job. Subgroups were compared and the reliability was assessed using Cronbach's alpha and the composite reliability. Factor analysis resulted in exclusion of seven items. Significant correlations were obtained between the subscales and all variables in the study. The reliability was considered acceptable. The Brazilian version of the Practice Environment Scale is a valid and reliable tool used to assess the characteristics that promote professional nursing practice. Use of this tool in Brazilian culture should allow managers to implement changes that contribute to the achievement of better results, in addition to identifying and comparing the environments of health institutions. © 2017 John Wiley & Sons Ltd.

A methodology towards virtualisation-based high performance simulation platform supporting multidisciplinary design of complex products

NASA Astrophysics Data System (ADS)

Ren, Lei; Zhang, Lin; Tao, Fei; (Luke) Zhang, Xiaolong; Luo, Yongliang; Zhang, Yabin

2012-08-01

Multidisciplinary design of complex products leads to an increasing demand for high performance simulation (HPS) platforms. One great challenge is how to achieve high efficient utilisation of large-scale simulation resources in distributed and heterogeneous environments. This article reports a virtualisation-based methodology to realise a HPS platform. This research is driven by the issues concerning large-scale simulation resources deployment and complex simulation environment construction, efficient and transparent utilisation of fine-grained simulation resources and high reliable simulation with fault tolerance. A framework of virtualisation-based simulation platform (VSIM) is first proposed. Then the article investigates and discusses key approaches in VSIM, including simulation resources modelling, a method to automatically deploying simulation resources for dynamic construction of system environment, and a live migration mechanism in case of faults in run-time simulation. Furthermore, the proposed methodology is applied to a multidisciplinary design system for aircraft virtual prototyping and some experiments are conducted. The experimental results show that the proposed methodology can (1) significantly improve the utilisation of fine-grained simulation resources, (2) result in a great reduction in deployment time and an increased flexibility for simulation environment construction and (3)achieve fault tolerant simulation.

Integrating O/S models during conceptual design, part 1

NASA Technical Reports Server (NTRS)

Ebeling, Charles E.

1994-01-01

The University of Dayton is pleased to submit this report to the National Aeronautics and Space Administration (NASA), Langley Research Center, which integrates a set of models for determining operational capabilities and support requirements during the conceptual design of proposed space systems. This research provides for the integration of the reliability and maintainability (R&M) model, both new and existing simulation models, and existing operations and support (O&S) costing equations in arriving at a complete analysis methodology. Details concerning the R&M model and the O&S costing model may be found in previous reports accomplished under this grant (NASA Research Grant NAG1-1327). In the process of developing this comprehensive analysis approach, significant enhancements were made to the R&M model, updates to the O&S costing model were accomplished, and a new simulation model developed. This is the 1st part of a 3 part technical report.

The evaluation of advanced traveler information services (ATIS) impacts on truck travel time reliability : using the simulated yoked study concept

DOT National Transportation Integrated Search

2004-03-01

The ability of Advanced Traveler Information Systems (ATIS) to improve the on-time reliability of urban truck movements is evaluated through the application of the Heuristic On-Line Web- : Linked Arrival Time Estimation (HOWLATE) methodology. In HOWL...

Construct Definition Methodology and Generalizability Theory Applied to Career Education Measurement.

ERIC Educational Resources Information Center

Stenner, A. Jackson; Rohlf, Richard J.

The merits of generalizability theory in the formulation of construct definitions and in the determination of reliability estimates are discussed. The broadened conceptualization of reliability brought about by Cronbach's generalizability theory is reviewed. Career Maturity Inventory data from a sample of 60 ninth grade students is used to…

34 CFR 668.144 - Application for test approval.

Code of Federal Regulations, 2010 CFR

2010-07-01

... the comparability of scores on the current test to scores on the previous test, and data from validity... explanation of the methodology and procedures for measuring the reliability of the test; (ii) Evidence that different forms of the test, including, if applicable, short forms, are comparable in reliability; (iii...

Methodological Issues in Measuring the Development of Character

ERIC Educational Resources Information Center

Card, Noel A.

2017-01-01

In this article I provide an overview of the methodological issues involved in measuring constructs relevant to character development and education. I begin with a nontechnical overview of the 3 fundamental psychometric properties of measurement: reliability, validity, and equivalence. Developing and evaluating measures to ensure evidence of all 3…

Kohlberg's Moral Judgment Scale: Some Methodological Considerations

ERIC Educational Resources Information Center

Rubin, Kenneth H.; Trotter, Kristin T.

1977-01-01

Examined 3 methodological issues in the use of Kohlberg's Moral Judgment Scale: (1) test-retest reliability, (2) consistency of moral judgment stages from one dilemma to the next, and (3) influence of subject's verbal facility on the projective test scores. Forty children in grades 3 and 5 participated. (JMB)

Inter-rater reliability for movement pattern analysis (MPA): measuring patterning of behaviors versus discrete behavior counts as indicators of decision-making style

PubMed Central

Connors, Brenda L.; Rende, Richard; Colton, Timothy J.

2014-01-01

The unique yield of collecting observational data on human movement has received increasing attention in a number of domains, including the study of decision-making style. As such, interest has grown in the nuances of core methodological issues, including the best ways of assessing inter-rater reliability. In this paper we focus on one key topic – the distinction between establishing reliability for the patterning of behaviors as opposed to the computation of raw counts – and suggest that reliability for each be compared empirically rather than determined a priori. We illustrate by assessing inter-rater reliability for key outcome measures derived from movement pattern analysis (MPA), an observational methodology that records body movements as indicators of decision-making style with demonstrated predictive validity. While reliability ranged from moderate to good for raw counts of behaviors reflecting each of two Overall Factors generated within MPA (Assertion and Perspective), inter-rater reliability for patterning (proportional indicators of each factor) was significantly higher and excellent (ICC = 0.89). Furthermore, patterning, as compared to raw counts, provided better prediction of observable decision-making process assessed in the laboratory. These analyses support the utility of using an empirical approach to inform the consideration of measuring patterning versus discrete behavioral counts of behaviors when determining inter-rater reliability of observable behavior. They also speak to the substantial reliability that may be achieved via application of theoretically grounded observational systems such as MPA that reveal thinking and action motivations via visible movement patterns. PMID:24999336

Inter-rater reliability for movement pattern analysis (MPA): measuring patterning of behaviors versus discrete behavior counts as indicators of decision-making style.

PubMed

Connors, Brenda L; Rende, Richard; Colton, Timothy J

2014-01-01

The unique yield of collecting observational data on human movement has received increasing attention in a number of domains, including the study of decision-making style. As such, interest has grown in the nuances of core methodological issues, including the best ways of assessing inter-rater reliability. In this paper we focus on one key topic - the distinction between establishing reliability for the patterning of behaviors as opposed to the computation of raw counts - and suggest that reliability for each be compared empirically rather than determined a priori. We illustrate by assessing inter-rater reliability for key outcome measures derived from movement pattern analysis (MPA), an observational methodology that records body movements as indicators of decision-making style with demonstrated predictive validity. While reliability ranged from moderate to good for raw counts of behaviors reflecting each of two Overall Factors generated within MPA (Assertion and Perspective), inter-rater reliability for patterning (proportional indicators of each factor) was significantly higher and excellent (ICC = 0.89). Furthermore, patterning, as compared to raw counts, provided better prediction of observable decision-making process assessed in the laboratory. These analyses support the utility of using an empirical approach to inform the consideration of measuring patterning versus discrete behavioral counts of behaviors when determining inter-rater reliability of observable behavior. They also speak to the substantial reliability that may be achieved via application of theoretically grounded observational systems such as MPA that reveal thinking and action motivations via visible movement patterns.

Validating the European Health Literacy Survey Questionnaire in people with type 2 diabetes: Latent trait analyses applying multidimensional Rasch modelling and confirmatory factor analysis.

PubMed

Finbråten, Hanne Søberg; Pettersen, Kjell Sverre; Wilde-Larsson, Bodil; Nordström, Gun; Trollvik, Anne; Guttersrud, Øystein

2017-11-01

To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus. The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients. Cross-sectional study applying confirmatory latent trait analyses. Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis. Response violation (response dependency) and trait violation (multidimensionality) of local independence were identified. Fitting the "multidimensional random coefficients multinomial logit" model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items, and several subscales suffered from poor targeting and low reliability. Despite multidimensional data, we did not observe any unordered response categories. Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall "health literacy score." To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to avoid response dependency; adding "harder" items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit and avoid bias owing to person factors. © 2017 John Wiley & Sons Ltd.

Validation of highly reliable, real-time knowledge-based systems

NASA Technical Reports Server (NTRS)

Johnson, Sally C.

1988-01-01

Knowledge-based systems have the potential to greatly increase the capabilities of future aircraft and spacecraft and to significantly reduce support manpower needed for the space station and other space missions. However, a credible validation methodology must be developed before knowledge-based systems can be used for life- or mission-critical applications. Experience with conventional software has shown that the use of good software engineering techniques and static analysis tools can greatly reduce the time needed for testing and simulation of a system. Since exhaustive testing is infeasible, reliability must be built into the software during the design and implementation phases. Unfortunately, many of the software engineering techniques and tools used for conventional software are of little use in the development of knowledge-based systems. Therefore, research at Langley is focused on developing a set of guidelines, methods, and prototype validation tools for building highly reliable, knowledge-based systems. The use of a comprehensive methodology for building highly reliable, knowledge-based systems should significantly decrease the time needed for testing and simulation. A proven record of delivering reliable systems at the beginning of the highly visible testing and simulation phases is crucial to the acceptance of knowledge-based systems in critical applications.

Robust PV Degradation Methodology and Application

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

Jordan, Dirk; Deline, Christopher A; Kurtz, Sarah

The degradation rate plays an important role in predicting and assessing the long-term energy generation of PV systems. Many methods have been proposed for extracting the degradation rate from operational data of PV systems, but most of the published approaches are susceptible to bias due to inverter clipping, module soiling, temporary outages, seasonality, and sensor degradation. In this manuscript, we propose a methodology for determining PV degradation leveraging available modeled clear-sky irradiance data rather than site sensor data, and a robust year-over-year (YOY) rate calculation. We show the method to provide reliable degradation rate estimates even in the case ofmore » sensor drift, data shifts, and soiling. Compared with alternate methods, we demonstrate that the proposed method delivers the lowest uncertainty in degradation rate estimates for a fleet of 486 PV systems.« less

Robust PV Degradation Methodology and Application

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

Jordan, Dirk C.; Deline, Chris; Kurtz, Sarah R.

The degradation rate plays an important role in predicting and assessing the long-term energy generation of photovoltaics (PV) systems. Many methods have been proposed for extracting the degradation rate from operational data of PV systems, but most of the published approaches are susceptible to bias due to inverter clipping, module soiling, temporary outages, seasonality, and sensor degradation. In this paper, we propose a methodology for determining PV degradation leveraging available modeled clear-sky irradiance data rather than site sensor data, and a robust year-over-year rate calculation. We show the method to provide reliable degradation rate estimates even in the case ofmore » sensor drift, data shifts, and soiling. Compared with alternate methods, we demonstrate that the proposed method delivers the lowest uncertainty in degradation rate estimates for a fleet of 486 PV systems.« less

Robust PV Degradation Methodology and Application

DOE PAGES

Jordan, Dirk C.; Deline, Chris; Kurtz, Sarah R.; ...

2017-12-21

The degradation rate plays an important role in predicting and assessing the long-term energy generation of photovoltaics (PV) systems. Many methods have been proposed for extracting the degradation rate from operational data of PV systems, but most of the published approaches are susceptible to bias due to inverter clipping, module soiling, temporary outages, seasonality, and sensor degradation. In this paper, we propose a methodology for determining PV degradation leveraging available modeled clear-sky irradiance data rather than site sensor data, and a robust year-over-year rate calculation. We show the method to provide reliable degradation rate estimates even in the case ofmore » sensor drift, data shifts, and soiling. Compared with alternate methods, we demonstrate that the proposed method delivers the lowest uncertainty in degradation rate estimates for a fleet of 486 PV systems.« less

Optimization of extraction of polysaccharides from fruiting body of Cordyceps militaris (L.) link using response surface methodology

NASA Astrophysics Data System (ADS)

Nguyen, Hoang Chinh; Thi, Dinh Huynh Mong; Pham, Dinh Chuong

2018-04-01

Polysaccharides from fruiting body of Cordyceps militaris (L.) Link possess various pharmaceutical activities. In this study, polysaccharides from the fruiting body of C. militaris were extracted with different solvents. Of those solvents tested, distilled water was identified as the most efficient solvent for the extraction, resulting in a significant increase in polysaccharides yield. Response surface methodology was then used to optimize the extraction conditions and establish a reliable mathematical model for prediction. A maximum polysaccharides yield of 11.07% was reached at a ratio of water to raw material of 23.2:1 mL/g, an extraction time of 76 min, and a temperature of 93.6°C. This study indicates that the obtained optimal extraction conditions are an efficient method for extraction of polysaccharides from the fruiting body of C. militaris.

Melanins and melanogenesis: methods, standards, protocols.

PubMed

d'Ischia, Marco; Wakamatsu, Kazumasa; Napolitano, Alessandra; Briganti, Stefania; Garcia-Borron, José-Carlos; Kovacs, Daniela; Meredith, Paul; Pezzella, Alessandro; Picardo, Mauro; Sarna, Tadeusz; Simon, John D; Ito, Shosuke

2013-09-01

Despite considerable advances in the past decade, melanin research still suffers from the lack of universally accepted and shared nomenclature, methodologies, and structural models. This paper stems from the joint efforts of chemists, biochemists, physicists, biologists, and physicians with recognized and consolidated expertise in the field of melanins and melanogenesis, who critically reviewed and experimentally revisited methods, standards, and protocols to provide for the first time a consensus set of recommended procedures to be adopted and shared by researchers involved in pigment cell research. The aim of the paper was to define an unprecedented frame of reference built on cutting-edge knowledge and state-of-the-art methodology, to enable reliable comparison of results among laboratories and new progress in the field based on standardized methods and shared information. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease

NASA Astrophysics Data System (ADS)

Gorzelic, P.; Schiff, S. J.; Sinha, A.

2013-04-01

Objective. To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). Approach. A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. Main Results. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Significance. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Estimating liver cancer deaths in Thailand based on verbal autopsy study.

PubMed

Waeto, Salwa; Pipatjaturon, Nattakit; Tongkumchum, Phattrawan; Choonpradub, Chamnein; Saelim, Rattikan; Makaje, Nifatamah

2014-01-01

Liver cancer mortality is high in Thailand but utility of related vital statistics is limited due to national vital registration (VR) data being under reported for specific causes of deaths. Accurate methodologies and reliable supplementary data are needed to provide worthy national vital statistics. This study aimed to model liver cancer deaths based on verbal autopsy (VA) study in 2005 to provide more accurate estimates of liver cancer deaths than those reported. The results were used to estimate number of liver cancer deaths during 2000-2009. A verbal autopsy (VA) was carried out in 2005 based on a sample of 9,644 deaths from nine provinces and it provided reliable information on causes of deaths by gender, age group, location of deaths in or outside hospital, and causes of deaths of the VR database. Logistic regression was used to model liver cancer deaths and other variables. The estimated probabilities from the model were applied to liver cancer deaths in the VR database, 2000-2009. Thus, the more accurately VA-estimated numbers of liver cancer deaths were obtained. The model fits the data quite well with sensitivity 0.64. The confidence intervals from statistical model provide the estimates and their precisions. The VA-estimated numbers of liver cancer deaths were higher than the corresponding VR database with inflation factors 1.56 for males and 1.64 for females. The statistical methods used in this study can be applied to available mortality data in developing countries where their national vital registration data are of low quality and supplementary reliable data are available.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease.

PubMed

Gorzelic, P; Schiff, S J; Sinha, A

2013-04-01

To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Adverse effects of psychosocial work factors on blood pressure: systematic review of studies on demand-control-support and effort-reward imbalance models.

PubMed

Gilbert-Ouimet, Mahée; Trudel, Xavier; Brisson, Chantal; Milot, Alain; Vézina, Michel

2014-03-01

A growing body of research has investigated the adverse effects of psychosocial work factors on blood pressure (BP) elevation. There is now a clear need for an up-to-date, critical synthesis of reliable findings on this topic. This systematic review aimed to evaluate the adverse effects of psychosocial work factors of both the demand-control-support (DCS) and effort-reward imbalance (ERI) models on BP among men and women, according to the methodological quality of the studies. To be eligible, studies had to: (i) evaluate at least one psychosocial work factor, (ii) evaluate BP or hypertension, (iii) comprise ≥100 workers, (iv) be written in English or French, and (v) be published in a peer-reviewed journal. A total of 74 studies were included. Of these, 64 examined the DCS model, and 12 looked at the ERI model, with 2 studies considering both models. Approximately half the studies observed a significant adverse effect of psychosocial work factors on BP. A more consistent effect was observed, however, among men than women. For job strain, a more consistent effect was also observed in studies of higher methodological quality, ie, studies using a prospective design and ambulatory BP measures. A more consistent adverse effect of psychosocial work factors was observed among men than women and in studies of higher methodological quality. These findings contribute to the current effort of primary prevention of cardiovascular disease by documenting the psychosocial etiology of elevated BP, a major cardiovascular risk factor.

Reduction of a linear complex model for respiratory system during Airflow Interruption.

PubMed

Jablonski, Ireneusz; Mroczka, Janusz

2010-01-01

The paper presents methodology of a complex model reduction to its simpler version - an identifiable inverse model. Its main tool is a numerical procedure of sensitivity analysis (structural and parametric) applied to the forward linear equivalent designed for the conditions of interrupter experiment. Final result - the reduced analog for the interrupter technique is especially worth of notice as it fills a major gap in occlusional measurements, which typically use simple, one- or two-element physical representations. Proposed electrical reduced circuit, being structural combination of resistive, inertial and elastic properties, can be perceived as a candidate for reliable reconstruction and quantification (in the time and frequency domain) of dynamical behavior of the respiratory system in response to a quasi-step excitation by valve closure.

Improved FTA methodology and application to subsea pipeline reliability design.

PubMed

Lin, Jing; Yuan, Yongbo; Zhang, Mingyuan

2014-01-01

An innovative logic tree, Failure Expansion Tree (FET), is proposed in this paper, which improves on traditional Fault Tree Analysis (FTA). It describes a different thinking approach for risk factor identification and reliability risk assessment. By providing a more comprehensive and objective methodology, the rather subjective nature of FTA node discovery is significantly reduced and the resulting mathematical calculations for quantitative analysis are greatly simplified. Applied to the Useful Life phase of a subsea pipeline engineering project, the approach provides a more structured analysis by constructing a tree following the laws of physics and geometry. Resulting improvements are summarized in comparison table form.

Improved FTA Methodology and Application to Subsea Pipeline Reliability Design

PubMed Central

Lin, Jing; Yuan, Yongbo; Zhang, Mingyuan

2014-01-01

An innovative logic tree, Failure Expansion Tree (FET), is proposed in this paper, which improves on traditional Fault Tree Analysis (FTA). It describes a different thinking approach for risk factor identification and reliability risk assessment. By providing a more comprehensive and objective methodology, the rather subjective nature of FTA node discovery is significantly reduced and the resulting mathematical calculations for quantitative analysis are greatly simplified. Applied to the Useful Life phase of a subsea pipeline engineering project, the approach provides a more structured analysis by constructing a tree following the laws of physics and geometry. Resulting improvements are summarized in comparison table form. PMID:24667681

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

NASA Astrophysics Data System (ADS)

Wei, Helin; Wang, Kuisheng

2011-11-01

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

A comparison of fatigue life prediction methodologies for rotorcraft

NASA Technical Reports Server (NTRS)

Everett, R. A., Jr.

1990-01-01

Because of the current U.S. Army requirement that all new rotorcraft be designed to a 'six nines' reliability on fatigue life, this study was undertaken to assess the accuracy of the current safe life philosophy using the nominal stress Palmgrem-Miner linear cumulative damage rule to predict the fatigue life of rotorcraft dynamic components. It has been shown that this methodology can predict fatigue lives that differ from test lives by more than two orders of magnitude. A further objective of this work was to compare the accuracy of this methodology to another safe life method called the local strain approach as well as to a method which predicts fatigue life based solely on crack growth data. Spectrum fatigue tests were run on notched (k(sub t) = 3.2) specimens made of 4340 steel using the Felix/28 tests fairly well, being slightly on the unconservative side of the test data. The crack growth method, which is based on 'small crack' crack growth data and a crack-closure model, also predicted the fatigue lives very well with the predicted lives being slightly longer that the mean test lives but within the experimental scatter band. The crack growth model was also able to predict the change in test lives produced by the rainflow reconstructed spectra.

Modeling and replicating statistical topology and evidence for CMB nonhomogeneity

PubMed Central

Agami, Sarit

2017-01-01

Under the banner of “big data,” the detection and classification of structure in extremely large, high-dimensional, data sets are two of the central statistical challenges of our times. Among the most intriguing new approaches to this challenge is “TDA,” or “topological data analysis,” one of the primary aims of which is providing nonmetric, but topologically informative, preanalyses of data which make later, more quantitative, analyses feasible. While TDA rests on strong mathematical foundations from topology, in applications, it has faced challenges due to difficulties in handling issues of statistical reliability and robustness, often leading to an inability to make scientific claims with verifiable levels of statistical confidence. We propose a methodology for the parametric representation, estimation, and replication of persistence diagrams, the main diagnostic tool of TDA. The power of the methodology lies in the fact that even if only one persistence diagram is available for analysis—the typical case for big data applications—the replications permit conventional statistical hypothesis testing. The methodology is conceptually simple and computationally practical, and provides a broadly effective statistical framework for persistence diagram TDA analysis. We demonstrate the basic ideas on a toy example, and the power of the parametric approach to TDA modeling in an analysis of cosmic microwave background (CMB) nonhomogeneity. PMID:29078301

Software For Fault-Tree Diagnosis Of A System

NASA Technical Reports Server (NTRS)

Iverson, Dave; Patterson-Hine, Ann; Liao, Jack

1993-01-01

Fault Tree Diagnosis System (FTDS) computer program is automated-diagnostic-system program identifying likely causes of specified failure on basis of information represented in system-reliability mathematical models known as fault trees. Is modified implementation of failure-cause-identification phase of Narayanan's and Viswanadham's methodology for acquisition of knowledge and reasoning in analyzing failures of systems. Knowledge base of if/then rules replaced with object-oriented fault-tree representation. Enhancement yields more-efficient identification of causes of failures and enables dynamic updating of knowledge base. Written in C language, C++, and Common LISP.

Maximizing the spatial representativeness of NO2 monitoring data using a combination of local wind-based sectoral division and seasonal and diurnal correction factors.

PubMed

Donnelly, Aoife; Naughton, Owen; Misstear, Bruce; Broderick, Brian

2016-10-14

This article describes a new methodology for increasing the spatial representativeness of individual monitoring sites. Air pollution levels at a given point are influenced by emission sources in the immediate vicinity. Since emission sources are rarely uniformly distributed around a site, concentration levels will inevitably be most affected by the sources in the prevailing upwind direction. The methodology provides a means of capturing this effect and providing additional information regarding source/pollution relationships. The methodology allows for the division of the air quality data from a given monitoring site into a number of sectors or wedges based on wind direction and estimation of annual mean values for each sector, thus optimising the information that can be obtained from a single monitoring station. The method corrects for short-term data, diurnal and seasonal variations in concentrations (which can produce uneven weighting of data within each sector) and uneven frequency of wind directions. Significant improvements in correlations between the air quality data and the spatial air quality indicators were obtained after application of the correction factors. This suggests the application of these techniques would be of significant benefit in land-use regression modelling studies. Furthermore, the method was found to be very useful for estimating long-term mean values and wind direction sector values using only short-term monitoring data. The methods presented in this article can result in cost savings through minimising the number of monitoring sites required for air quality studies while also capturing a greater degree of variability in spatial characteristics. In this way, more reliable, but also more expensive monitoring techniques can be used in preference to a higher number of low-cost but less reliable techniques. The methods described in this article have applications in local air quality management, source receptor analysis, land-use regression mapping and modelling and population exposure studies.

Development of a probabilistic analysis methodology for structural reliability estimation

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.

1991-01-01

The novel probabilistic analysis method for assessment of structural reliability presented, which combines fast-convolution with an efficient structural reliability analysis, can after identifying the most important point of a limit state proceed to establish a quadratic-performance function. It then transforms the quadratic function into a linear one, and applies fast convolution. The method is applicable to problems requiring computer-intensive structural analysis. Five illustrative examples of the method's application are given.

An Analytical Methodology for Predicting Repair Time Distributions of Advanced Technology Aircraft.

DTIC Science & Technology

1985-12-01

1984. 3. Barlow, Richard E. "Mathematical Theory of Reliabilitys A Historical Perspective." ZEEE Transactions on Reliability, 33. 16-19 (April 1984...Technology (AU), Wright-Patterson AFB OH, March 1971. 11. Coppola, Anthony. "Reliability Engineering of J- , Electronic Equipment," ZEEE Transactions on...1982. 64. Woodruff, Brian W. at al. "Modified Goodness-o-Fit Tests for Gamma Distributions with Unknown Location and Scale Parameters," ZEEE

Selection and Reporting of Statistical Methods to Assess Reliability of a Diagnostic Test: Conformity to Recommended Methods in a Peer-Reviewed Journal

PubMed Central

Park, Ji Eun; Han, Kyunghwa; Sung, Yu Sub; Chung, Mi Sun; Koo, Hyun Jung; Yoon, Hee Mang; Choi, Young Jun; Lee, Seung Soo; Kim, Kyung Won; Shin, Youngbin; An, Suah; Cho, Hyo-Min

2017-01-01

Objective To evaluate the frequency and adequacy of statistical analyses in a general radiology journal when reporting a reliability analysis for a diagnostic test. Materials and Methods Sixty-three studies of diagnostic test accuracy (DTA) and 36 studies reporting reliability analyses published in the Korean Journal of Radiology between 2012 and 2016 were analyzed. Studies were judged using the methodological guidelines of the Radiological Society of North America-Quantitative Imaging Biomarkers Alliance (RSNA-QIBA), and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative. DTA studies were evaluated by nine editorial board members of the journal. Reliability studies were evaluated by study reviewers experienced with reliability analysis. Results Thirty-one (49.2%) of the 63 DTA studies did not include a reliability analysis when deemed necessary. Among the 36 reliability studies, proper statistical methods were used in all (5/5) studies dealing with dichotomous/nominal data, 46.7% (7/15) of studies dealing with ordinal data, and 95.2% (20/21) of studies dealing with continuous data. Statistical methods were described in sufficient detail regarding weighted kappa in 28.6% (2/7) of studies and regarding the model and assumptions of intraclass correlation coefficient in 35.3% (6/17) and 29.4% (5/17) of studies, respectively. Reliability parameters were used as if they were agreement parameters in 23.1% (3/13) of studies. Reproducibility and repeatability were used incorrectly in 20% (3/15) of studies. Conclusion Greater attention to the importance of reporting reliability, thorough description of the related statistical methods, efforts not to neglect agreement parameters, and better use of relevant terminology is necessary. PMID:29089821

How to assess the impact of a physical parameterization in simulations of moist convection?

NASA Astrophysics Data System (ADS)

Grabowski, Wojciech

2017-04-01

A numerical model capable in simulating moist convection (e.g., cloud-resolving model or large-eddy simulation model) consists of a fluid flow solver combined with required representations (i.e., parameterizations) of physical processes. The later typically include cloud microphysics, radiative transfer, and unresolved turbulent transport. Traditional approaches to investigate impacts of such parameterizations on convective dynamics involve parallel simulations with different parameterization schemes or with different scheme parameters. Such methodologies are not reliable because of the natural variability of a cloud field that is affected by the feedback between the physics and dynamics. For instance, changing the cloud microphysics typically leads to a different realization of the cloud-scale flow, and separating dynamical and microphysical impacts is difficult. This presentation will present a novel modeling methodology, the piggybacking, that allows studying the impact of a physical parameterization on cloud dynamics with confidence. The focus will be on the impact of cloud microphysics parameterization. Specific examples of the piggybacking approach will include simulations concerning the hypothesized deep convection invigoration in polluted environments, the validity of the saturation adjustment in modeling condensation in moist convection, and separation of physical impacts from statistical uncertainty in simulations applying particle-based Lagrangian microphysics, the super-droplet method.

Reporting and Methodology of Multivariable Analyses in Prognostic Observational Studies Published in 4 Anesthesiology Journals: A Methodological Descriptive Review.

PubMed

Guglielminotti, Jean; Dechartres, Agnès; Mentré, France; Montravers, Philippe; Longrois, Dan; Laouénan, Cedric

2015-10-01

Prognostic research studies in anesthesiology aim to identify risk factors for an outcome (explanatory studies) or calculate the risk of this outcome on the basis of patients' risk factors (predictive studies). Multivariable models express the relationship between predictors and an outcome and are used in both explanatory and predictive studies. Model development demands a strict methodology and a clear reporting to assess its reliability. In this methodological descriptive review, we critically assessed the reporting and methodology of multivariable analysis used in observational prognostic studies published in anesthesiology journals. A systematic search was conducted on Medline through Web of Knowledge, PubMed, and journal websites to identify observational prognostic studies with multivariable analysis published in Anesthesiology, Anesthesia & Analgesia, British Journal of Anaesthesia, and Anaesthesia in 2010 and 2011. Data were extracted by 2 independent readers. First, studies were analyzed with respect to reporting of outcomes, design, size, methods of analysis, model performance (discrimination and calibration), model validation, clinical usefulness, and STROBE (i.e., Strengthening the Reporting of Observational Studies in Epidemiology) checklist. A reporting rate was calculated on the basis of 21 items of the aforementioned points. Second, they were analyzed with respect to some predefined methodological points. Eighty-six studies were included: 87.2% were explanatory and 80.2% investigated a postoperative event. The reporting was fairly good, with a median reporting rate of 79% (75% in explanatory studies and 100% in predictive studies). Six items had a reporting rate <36% (i.e., the 25th percentile), with some of them not identified in the STROBE checklist: blinded evaluation of the outcome (11.9%), reason for sample size (15.1%), handling of missing data (36.0%), assessment of colinearity (17.4%), assessment of interactions (13.9%), and calibration (34.9%). When reported, a few methodological shortcomings were observed, both in explanatory and predictive studies, such as an insufficient number of events of the outcome (44.6%), exclusion of cases with missing data (93.6%), or categorization of continuous variables (65.1%.). The reporting of multivariable analysis was fairly good and could be further improved by checking reporting guidelines and EQUATOR Network website. Limiting the number of candidate variables, including cases with missing data, and not arbitrarily categorizing continuous variables should be encouraged.

Establishing survey validity and reliability for American Indians through "think aloud" and test-retest methods.

PubMed

Hauge, Cindy Horst; Jacobs-Knight, Jacque; Jensen, Jamie L; Burgess, Katherine M; Puumala, Susan E; Wilton, Georgiana; Hanson, Jessica D

2015-06-01

The purpose of this study was to use a mixed-methods approach to determine the validity and reliability of measurements used within an alcohol-exposed pregnancy prevention program for American Indian women. To develop validity, content experts provided input into the survey measures, and a "think aloud" methodology was conducted with 23 American Indian women. After revising the measurements based on this input, a test-retest was conducted with 79 American Indian women who were randomized to complete either the original measurements or the new, modified measurements. The test-retest revealed that some of the questions performed better for the modified version, whereas others appeared to be more reliable for the original version. The mixed-methods approach was a useful methodology for gathering feedback on survey measurements from American Indian participants and in indicating specific survey questions that needed to be modified for this population. © The Author(s) 2015.

A Methodological Critique of the ProPublica Surgeon Scorecard

PubMed Central

Friedberg, Mark W.; Pronovost, Peter J.; Shahian, David M.; Safran, Dana Gelb; Bilimoria, Karl Y.; Elliott, Marc N.; Damberg, Cheryl L.; Dimick, Justin B.; Zaslavsky, Alan M.

2016-01-01

Abstract On July 14, 2015, ProPublica published its Surgeon Scorecard, which displays “Adjusted Complication Rates” for individual, named surgeons for eight surgical procedures performed in hospitals. Public reports of provider performance have the potential to improve the quality of health care that patients receive. A valid performance report can drive quality improvement and usefully inform patients' choices of providers. However, performance reports with poor validity and reliability are potentially damaging to all involved. This article critiques the methods underlying the Scorecard and identifies opportunities for improvement. Until these opportunities are addressed, the authors advise users of the Scorecard—most notably, patients who might be choosing their surgeons—not to consider the Scorecard a valid or reliable predictor of the health outcomes any individual surgeon is likely to provide. The authors hope that this methodological critique will contribute to the development of more-valid and more-reliable performance reports in the future. PMID:28083411

Estimating the Reliability of Electronic Parts in High Radiation Fields

NASA Technical Reports Server (NTRS)

Everline, Chester; Clark, Karla; Man, Guy; Rasmussen, Robert; Johnston, Allan; Kohlhase, Charles; Paulos, Todd

2008-01-01

Radiation effects on materials and electronic parts constrain the lifetime of flight systems visiting Europa. Understanding mission lifetime limits is critical to the design and planning of such a mission. Therefore, the operational aspects of radiation dose are a mission success issue. To predict and manage mission lifetime in a high radiation environment, system engineers need capable tools to trade radiation design choices against system design and reliability, and science achievements. Conventional tools and approaches provided past missions with conservative designs without the ability to predict their lifetime beyond the baseline mission.This paper describes a more systematic approach to understanding spacecraft design margin, allowing better prediction of spacecraft lifetime. This is possible because of newly available electronic parts radiation effects statistics and an enhanced spacecraft system reliability methodology. This new approach can be used in conjunction with traditional approaches for mission design. This paper describes the fundamentals of the new methodology.

A Step Made Toward Designing Microelectromechanical System (MEMS) Structures With High Reliability

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

2003-01-01

The mechanical design of microelectromechanical systems-particularly for micropower generation applications-requires the ability to predict the strength capacity of load-carrying components over the service life of the device. These microdevices, which typically are made of brittle materials such as polysilicon, show wide scatter (stochastic behavior) in strength as well as a different average strength for different sized structures (size effect). These behaviors necessitate either costly and time-consuming trial-and-error designs or, more efficiently, the development of a probabilistic design methodology for MEMS. Over the years, the NASA Glenn Research Center s Life Prediction Branch has developed the CARES/Life probabilistic design methodology to predict the reliability of advanced ceramic components. In this study, done in collaboration with Johns Hopkins University, the ability of the CARES/Life code to predict the reliability of polysilicon microsized structures with stress concentrations is successfully demonstrated.

Coordinative Voltage Control Strategy with Multiple Resources for Distribution Systems of High PV Penetration: Preprint

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

Zhu, Xiangqi; Zhang, Yingchen

This paper presents an optimal voltage control methodology with coordination among different voltage-regulating resources, including controllable loads, distributed energy resources such as energy storage and photovoltaics (PV), and utility voltage-regulating devices such as voltage regulators and capacitors. The proposed methodology could effectively tackle the overvoltage and voltage regulation device distortion problems brought by high penetrations of PV to improve grid operation reliability. A voltage-load sensitivity matrix and voltage-regulator sensitivity matrix are used to deploy the resources along the feeder to achieve the control objectives. Mixed-integer nonlinear programming is used to solve the formulated optimization control problem. The methodology has beenmore » tested on the IEEE 123-feeder test system, and the results demonstrate that the proposed approach could actively tackle the voltage problem brought about by high penetrations of PV and improve the reliability of distribution system operation.« less

Reliability study on high power 638-nm triple emitter broad area laser diode

NASA Astrophysics Data System (ADS)

Yagi, T.; Kuramoto, K.; Kadoiwa, K.; Wakamatsu, R.; Miyashita, M.

2016-03-01

Reliabilities of the 638-nm triple emitter broad area laser diode (BA-LD) with the window-mirror structure were studied. Methodology to estimate mean time to failure (MTTF) due to catastrophic optical mirror degradation (COMD) in reasonable aging duration was newly proposed. Power at which the LD failed due to COMD (PCOMD) was measured for the aged LDs under the several aging conditions. It was revealed that the PCOMD was proportional to logarithm of aging duration, and MTTF due to COMD (MTTF(COMD)) could be estimated by using this relation. MTTF(COMD) estimated by the methodology with the aging duration of approximately 2,000 hours was consistent with that estimated by the long term aging. By using this methodology, the MTTF of the BA-LD was estimated exceeding 100,000 hours under the output of 2.5 W, duty cycles of 30% .

Use of raster-based data layers to model spatial variation of seismotectonic data in probabilistic seismic hazard assessment

NASA Astrophysics Data System (ADS)

Zolfaghari, Mohammad R.

2009-07-01

Recent achievements in computer and information technology have provided the necessary tools to extend the application of probabilistic seismic hazard mapping from its traditional engineering use to many other applications. Examples for such applications are risk mitigation, disaster management, post disaster recovery planning and catastrophe loss estimation and risk management. Due to the lack of proper knowledge with regard to factors controlling seismic hazards, there are always uncertainties associated with all steps involved in developing and using seismic hazard models. While some of these uncertainties can be controlled by more accurate and reliable input data, the majority of the data and assumptions used in seismic hazard studies remain with high uncertainties that contribute to the uncertainty of the final results. In this paper a new methodology for the assessment of seismic hazard is described. The proposed approach provides practical facility for better capture of spatial variations of seismological and tectonic characteristics, which allows better treatment of their uncertainties. In the proposed approach, GIS raster-based data models are used in order to model geographical features in a cell-based system. The cell-based source model proposed in this paper provides a framework for implementing many geographically referenced seismotectonic factors into seismic hazard modelling. Examples for such components are seismic source boundaries, rupture geometry, seismic activity rate, focal depth and the choice of attenuation functions. The proposed methodology provides improvements in several aspects of the standard analytical tools currently being used for assessment and mapping of regional seismic hazard. The proposed methodology makes the best use of the recent advancements in computer technology in both software and hardware. The proposed approach is well structured to be implemented using conventional GIS tools.

Measuring engagement in nurses: the psychometric properties of the Persian version of Utrecht Work Engagement Scale

PubMed Central

Torabinia, Mansour; Mahmoudi, Sara; Dolatshahi, Mojtaba; Abyaz, Mohamad Reza

2017-01-01

Background: Considering the overall tendency in psychology, researchers in the field of work and organizational psychology have become progressively interested in employees’ effective and optimistic experiments at work such as work engagement. This study was conducted to investigate 2 main purposes: assessing the psychometric properties of the Utrecht Work Engagement Scale, and finding any association between work engagement and burnout in nurses. Methods: The present methodological study was conducted in 2015 and included 248 females and 34 males with 6 months to 30 years of job experience. After the translation process, face and content validity were calculated by qualitative and quantitative methods. Moreover, content validation ratio, scale-level content validity index and item-level content validity index were measured for this scale. Construct validity was determined by factor analysis. Moreover, internal consistency and stability reliability were assessed. Factor analysis, test-retest, Cronbach’s alpha, and association analysis were used as statistical methods. Results: Face and content validity were acceptable. Exploratory factor analysis suggested a new 3- factor model. In this new model, some items from the construct model of the original version were dislocated with the same 17 items. The new model was confirmed by divergent Copenhagen Burnout Inventory as the Persian version of UWES. Internal consistency reliability for the total scale and the subscales was 0.76 to 0.89. Results from Pearson correlation test indicated a high degree of test-retest reliability (r = 0. 89). ICC was also 0.91. Engagement was negatively related to burnout and overtime per month, whereas it was positively related with age and job experiment. Conclusion: The Persian 3– factor model of Utrecht Work Engagement Scale is a valid and reliable instrument to measure work engagement in Iranian nurses as well as in other medical professionals. PMID:28955665

Estimating the reliability of glycemic index values and potential sources of methodological and biological variability

USDA-ARS?s Scientific Manuscript database

Background: The utility of glycemic index (GI) values for chronic disease risk management remains controversial. While absolute GI value determinations for individual foods have been shown to vary significantly in individuals with diabetes, there is a dearth of data on the reliability of GI value de...

Design of an integrated airframe/propulsion control system architecture

NASA Technical Reports Server (NTRS)

Cohen, Gerald C.; Lee, C. William; Strickland, Michael J.; Torkelson, Thomas C.

1990-01-01

The design of an integrated airframe/propulsion control system architecture is described. The design is based on a prevalidation methodology that uses both reliability and performance. A detailed account is given for the testing associated with a subset of the architecture and concludes with general observations of applying the methodology to the architecture.

How to improve the standardization and the diagnostic performance of the fecal egg count reduction test?

PubMed

Levecke, Bruno; Kaplan, Ray M; Thamsborg, Stig M; Torgerson, Paul R; Vercruysse, Jozef; Dobson, Robert J

2018-04-15

Although various studies have provided novel insights into how to best design, analyze and interpret a fecal egg count reduction test (FECRT), it is still not straightforward to provide guidance that allows improving both the standardization and the analytical performance of the FECRT across a variety of both animal and nematode species. For example, it has been suggested to recommend a minimum number of eggs to be counted under the microscope (not eggs per gram of feces), but we lack the evidence to recommend any number of eggs that would allow a reliable assessment of drug efficacy. Other aspects that need further research are the methodology of calculating uncertainty intervals (UIs; confidence intervals in case of frequentist methods and credible intervals in case of Bayesian methods) and the criteria of classifying drug efficacy into 'normal', 'suspected' and 'reduced'. The aim of this study is to provide complementary insights into the current knowledge, and to ultimately provide guidance in the development of new standardized guidelines for the FECRT. First, data were generated using a simulation in which the 'true' drug efficacy (TDE) was evaluated by the FECRT under varying scenarios of sample size, analytic sensitivity of the diagnostic technique, and level of both intensity and aggregation of egg excretion. Second, the obtained data were analyzed with the aim (i) to verify which classification criteria allow for reliable detection of reduced drug efficacy, (ii) to identify the UI methodology that yields the most reliable assessment of drug efficacy (coverage of TDE) and detection of reduced drug efficacy, and (iii) to determine the required sample size and number of eggs counted under the microscope that optimizes the detection of reduced efficacy. Our results confirm that the currently recommended criteria for classifying drug efficacy are the most appropriate. Additionally, the UI methodologies we tested varied in coverage and ability to detect reduced drug efficacy, thus a combination of UI methodologies is recommended to assess the uncertainty across all scenarios of drug efficacy estimates. Finally, based on our model estimates we were able to determine the required number of eggs to count for each sample size, enabling investigators to optimize the probability of correctly classifying a theoretical TDE while minimizing both financial and technical resources. Copyright © 2018 Elsevier B.V. All rights reserved.

Reliability based impact localization in composite panels using Bayesian updating and the Kalman filter

NASA Astrophysics Data System (ADS)

Morse, Llewellyn; Sharif Khodaei, Zahra; Aliabadi, M. H.

2018-01-01

In this work, a reliability based impact detection strategy for a sensorized composite structure is proposed. Impacts are localized using Artificial Neural Networks (ANNs) with recorded guided waves due to impacts used as inputs. To account for variability in the recorded data under operational conditions, Bayesian updating and Kalman filter techniques are applied to improve the reliability of the detection algorithm. The possibility of having one or more faulty sensors is considered, and a decision fusion algorithm based on sub-networks of sensors is proposed to improve the application of the methodology to real structures. A strategy for reliably categorizing impacts into high energy impacts, which are probable to cause damage in the structure (true impacts), and low energy non-damaging impacts (false impacts), has also been proposed to reduce the false alarm rate. The proposed strategy involves employing classification ANNs with different features extracted from captured signals used as inputs. The proposed methodologies are validated by experimental results on a quasi-isotropic composite coupon impacted with a range of impact energies.

Reliability of physical functioning tests in patients with low back pain: a systematic review.

PubMed

Denteneer, Lenie; Van Daele, Ulrike; Truijen, Steven; De Hertogh, Willem; Meirte, Jill; Stassijns, Gaetane

2018-01-01

The aim of this study was to provide a comprehensive overview of physical functioning tests in patients with low back pain (LBP) and to investigate their reliability. A systematic computerized search was finalized in four different databases on June 24, 2017: PubMed, Web of Science, Embase, and MEDLINE. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed during all stages of this review. Clinical studies that investigate the reliability of physical functioning tests in patients with LBP were eligible. The methodological quality of the included studies was assessed with the use of the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) checklist. To come to final conclusions on the reliability of the identified clinical tests, the current review assessed three factors, namely, outcome assessment, methodological quality, and consistency of description. A total of 20 studies were found eligible and 38 clinical tests were identified. Good overall test-retest reliability was concluded for the extensor endurance test (intraclass correlation coefficient [ICC]=0.93-0.97), the flexor endurance test (ICC=0.90-0.97), the 5-minute walking test (ICC=0.89-0.99), the 50-ft walking test (ICC=0.76-0.96), the shuttle walk test (ICC=0.92-0.99), the sit-to-stand test (ICC=0.91-0.99), and the loaded forward reach test (ICC=0.74-0.98). For inter-rater reliability, only one test, namely, the Biering-Sörensen test (ICC=0.88-0.99), could be concluded to have an overall good inter-rater reliability. None of the identified clinical tests could be concluded to have a good intrarater reliability. Further investigation should focus on a better overall study methodology and the use of identical protocols for the description of clinical tests. The assessment of reliability is only a first step in the recommendation process for the use of clinical tests. In future research, the identified clinical tests in the current review should be further investigated for validity. Only when these clinimetric properties of a clinical test have been thoroughly investigated can a final conclusion regarding the clinical and scientific use of the identified tests be made. Copyright © 2017 Elsevier Inc. All rights reserved.

"Big Data" in Rheumatology: Intelligent Data Modeling Improves the Quality of Imaging Data.

PubMed

Landewé, Robert B M; van der Heijde, Désirée

2018-05-01

Analysis of imaging data in rheumatology is a challenge. Reliability of scores is an issue for several reasons. Signal-to-noise ratio of most imaging techniques is rather unfavorable (too little signal in relation to too much noise). Optimal use of all available data may help to increase credibility of imaging data, but knowledge of complicated statistical methodology and the help of skilled statisticians are required. Clinicians should appreciate the merits of sophisticated data modeling and liaise with statisticians to increase the quality of imaging results, as proper imaging studies in rheumatology imply more than a supersensitive imaging technique alone. Copyright © 2018 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.

A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data.

PubMed

Vanegas, Fernando; Bratanov, Dmitry; Powell, Kevin; Weiss, John; Gonzalez, Felipe

2018-01-17

Recent advances in remote sensed imagery and geospatial image processing using unmanned aerial vehicles (UAVs) have enabled the rapid and ongoing development of monitoring tools for crop management and the detection/surveillance of insect pests. This paper describes a (UAV) remote sensing-based methodology to increase the efficiency of existing surveillance practices (human inspectors and insect traps) for detecting pest infestations (e.g., grape phylloxera in vineyards). The methodology uses a UAV integrated with advanced digital hyperspectral, multispectral, and RGB sensors. We implemented the methodology for the development of a predictive model for phylloxera detection. In this method, we explore the combination of airborne RGB, multispectral, and hyperspectral imagery with ground-based data at two separate time periods and under different levels of phylloxera infestation. We describe the technology used-the sensors, the UAV, and the flight operations-the processing workflow of the datasets from each imagery type, and the methods for combining multiple airborne with ground-based datasets. Finally, we present relevant results of correlation between the different processed datasets. The objective of this research is to develop a novel methodology for collecting, processing, analising and integrating multispectral, hyperspectral, ground and spatial data to remote sense different variables in different applications, such as, in this case, plant pest surveillance. The development of such methodology would provide researchers, agronomists, and UAV practitioners reliable data collection protocols and methods to achieve faster processing techniques and integrate multiple sources of data in diverse remote sensing applications.

Launch and Assembly Reliability Analysis for Mars Human Space Exploration Missions

NASA Technical Reports Server (NTRS)

Cates, Grant R.; Stromgren, Chel; Cirillo, William M.; Goodliff, Kandyce E.

2013-01-01

NASA s long-range goal is focused upon human exploration of Mars. Missions to Mars will require campaigns of multiple launches to assemble Mars Transfer Vehicles in Earth orbit. Launch campaigns are subject to delays, launch vehicles can fail to place their payloads into the required orbit, and spacecraft may fail during the assembly process or while loitering prior to the Trans-Mars Injection (TMI) burn. Additionally, missions to Mars have constrained departure windows lasting approximately sixty days that repeat approximately every two years. Ensuring high reliability of launching and assembling all required elements in time to support the TMI window will be a key enabler to mission success. This paper describes an integrated methodology for analyzing and improving the reliability of the launch and assembly campaign phase. A discrete event simulation involves several pertinent risk factors including, but not limited to: manufacturing completion; transportation; ground processing; launch countdown; ascent; rendezvous and docking, assembly, and orbital operations leading up to TMI. The model accommodates varying numbers of launches, including the potential for spare launches. Having a spare launch capability provides significant improvement to mission success.

A case of the birth and death of a high reliability healthcare organisation.

PubMed

Roberts, K H; Madsen, P; Desai, V; Van Stralen, D

2005-06-01

High reliability organisations (HROs) are those in which errors rarely occur. To accomplish this they conduct relatively error free operations over long periods of time and make consistently good decisions resulting in high quality and reliability. Some organisational processes that characterise HROs are process auditing, implementing appropriate reward systems, avoiding quality degradation, appropriately perceiving that risk exists and developing strategies to deal with it, and command and control. Command and control processes include migrating decision making, redundancy in people or hardware, developing situational awareness, formal rules and procedures, and training. These processes must be tailored to the specific organisation implementing them. These processes were applied to a paediatric intensive care unit (PICU) where care was derived from problem solving methodology rather than protocol. After a leadership change, the unit returned to the hierarchical medical model of care. Important outcome variables such as infant mortality, patient return to the PICU after discharge, days on the PICU, air transports, degraded. Implications for clinical practice include providing caregivers with sufficient flexibility to meet changing situations, encouraging teamwork, and avoiding shaming, naming, and blaming.

Reliability of specific physical examination tests for the diagnosis of shoulder pathologies: a systematic review and meta-analysis.

PubMed

Lange, Toni; Matthijs, Omer; Jain, Nitin B; Schmitt, Jochen; Lützner, Jörg; Kopkow, Christian

2017-03-01

Shoulder pain in the general population is common and to identify the aetiology of shoulder pain, history, motion and muscle testing, and physical examination tests are usually performed. The aim of this systematic review was to summarise and evaluate intrarater and inter-rater reliability of physical examination tests in the diagnosis of shoulder pathologies. A comprehensive systematic literature search was conducted using MEDLINE, EMBASE, Allied and Complementary Medicine Database (AMED) and Physiotherapy Evidence Database (PEDro) through 20 March 2015. Methodological quality was assessed using the Quality Appraisal of Reliability Studies (QAREL) tool by 2 independent reviewers. The search strategy revealed 3259 articles, of which 18 finally met the inclusion criteria. These studies evaluated the reliability of 62 test and test variations used for the specific physical examination tests for the diagnosis of shoulder pathologies. Methodological quality ranged from 2 to 7 positive criteria of the 11 items of the QAREL tool. This review identified a lack of high-quality studies evaluating inter-rater as well as intrarater reliability of specific physical examination tests for the diagnosis of shoulder pathologies. In addition, reliability measures differed between included studies hindering proper cross-study comparisons. PROSPERO CRD42014009018. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Development and Validation of a Collocated Exposure Monitoring Methodology using Portable Air Monitors

NASA Astrophysics Data System (ADS)

Li, Z.; Che, W.; Frey, H. C.; Lau, A. K. H.

2016-12-01

Portable air monitors are currently being developed and used to enable a move towards exposure monitoring as opposed to fixed site monitoring. Reliable methods are needed regarding capturing spatial and temporal variability in exposure concentration to obtain credible data from which to develop efficient exposure mitigation measures. However, there are few studies that quantify the validity and repeatability of the collected data. The objective of this study is to present and evaluate a collocated exposure monitoring (CEM) methodology including the calibration of portable air monitors against stationary reference equipment, side-by-side comparison of portable air monitors, personal or microenvironmental exposure monitoring and the processing and interpretation of the collected data. The CEM methodology was evaluated based on application to portable monitors TSI DustTrak II Aerosol Monitor 8530 for fine particulate matter (PM2.5) and TSI Q-Trak model 7575 with probe model 982 for CO, CO2, temperature and relative humidity. Taking a school sampling campaign in Hong Kong in January and June, 2015 as an example, the calibrated side-by-side measured 1 Hz PM2.5 concentrations showed good consistency between two sets of portable air monitors. Confidence in side-by-side comparison, PM2.5 concentrations of which most of the time were within 2 percent, enabled robust inference regarding differences when the monitors measured in classroom and pedestrian during school hour. The proposed CEM methodology can be widely applied in sampling campaigns with the objective of simultaneously characterizing pollutant concentrations in two or more locations or microenvironments. The further application of the CEM methodology to transportation exposure will be presented and discussed.

Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series

NASA Astrophysics Data System (ADS)

Fatichi, S.; Ivanov, V. Y.; Caporali, E.

2013-04-01

This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000-2009, 2046-2065 and 2081-2100, using the period of 1962-1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000-2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scales.

Reliability of Real-time Ultrasound Imaging for the Assessment of Trunk Stabilizer Muscles: A Systematic Review of the Literature.

PubMed

Taghipour, Morteza; Mohseni-Bandpei, Mohammad Ali; Behtash, Hamid; Abdollahi, Iraj; Rajabzadeh, Fatemeh; Pourahmadi, Mohammad Reza; Emami, Mahnaz

2018-04-24

Rehabilitative ultrasound (US) imaging is one of the popular methods for investigating muscle morphologic characteristics and dimensions in recent years. The reliability of this method has been investigated in different studies. As studies have been performed with different designs and quality, reported values of rehabilitative US have a wide range. The objective of this study was to systematically review the literature conducted on the reliability of rehabilitative US imaging for the assessment of deep abdominal and lumbar trunk muscle dimensions. The PubMed/MEDLINE, Scopus, Google Scholar, Science Direct, Embase, Physiotherapy Evidence, Ovid, and CINAHL databases were searched to identify original research articles conducted on the reliability of rehabilitative US imaging published from June 2007 to August 2017. The articles were qualitatively assessed; reliability data were extracted; and the methodological quality was evaluated by 2 independent reviewers. Of the 26 included studies, 16 were considered of high methodological quality. Except for 2 studies, all high-quality studies reported intraclass correlation coefficients (ICCs) for intra-rater reliability of 0.70 or greater. Also, ICCs reported for inter-rater reliability in high-quality studies were generally greater than 0.70. Among low-quality studies, reported ICCs ranged from 0.26 to 0.99 and 0.68 to 0.97 for intra- and inter-rater reliability, respectively. Also, the reported standard error of measurement and minimal detectable change for rehabilitative US were generally in an acceptable range. Generally, the results of the reviewed studies indicate that rehabilitative US imaging has good levels of both inter- and intra-rater reliability. © 2018 by the American Institute of Ultrasound in Medicine.

Sustainability of transport structures - some aspects of the nonlinear reliability assessment

NASA Astrophysics Data System (ADS)

Pukl, Radomír; Sajdlová, Tereza; Strauss, Alfred; Lehký, David; Novák, Drahomír

2017-09-01

Efficient techniques for both nonlinear numerical analysis of concrete structures and advanced stochastic simulation methods have been combined in order to offer an advanced tool for assessment of realistic behaviour, failure and safety assessment of transport structures. The utilized approach is based on randomization of the non-linear finite element analysis of the structural models. Degradation aspects such as carbonation of concrete can be accounted in order predict durability of the investigated structure and its sustainability. Results can serve as a rational basis for the performance and sustainability assessment based on advanced nonlinear computer analysis of the structures of transport infrastructure such as bridges or tunnels. In the stochastic simulation the input material parameters obtained from material tests including their randomness and uncertainty are represented as random variables or fields. Appropriate identification of material parameters is crucial for the virtual failure modelling of structures and structural elements. Inverse analysis using artificial neural networks and virtual stochastic simulations approach is applied to determine the fracture mechanical parameters of the structural material and its numerical model. Structural response, reliability and sustainability have been investigated on different types of transport structures made from various materials using the above mentioned methodology and tools.

On-line diagnosis of inter-turn short circuit fault for DC brushed motor.

PubMed

Zhang, Jiayuan; Zhan, Wei; Ehsani, Mehrdad

2018-06-01

Extensive research effort has been made in fault diagnosis of motors and related components such as winding and ball bearing. In this paper, a new concept of inter-turn short circuit fault for DC brushed motors is proposed to include the short circuit ratio and short circuit resistance. A first-principle model is derived for motors with inter-turn short circuit fault. A statistical model based on Hidden Markov Model is developed for fault diagnosis purpose. This new method not only allows detection of motor winding short circuit fault, it can also provide estimation of the fault severity, as indicated by estimation of the short circuit ratio and the short circuit resistance. The estimated fault severity can be used for making appropriate decisions in response to the fault condition. The feasibility of the proposed methodology is studied for inter-turn short circuit of DC brushed motors using simulation in MATLAB/Simulink environment. In addition, it is shown that the proposed methodology is reliable with the presence of small random noise in the system parameters and measurement. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Degradation of ticarcillin by subcritial water oxidation method: Application of response surface methodology and artificial neural network modeling.

PubMed

Yabalak, Erdal

2018-05-18

This study was performed to investigate the mineralization of ticarcillin in the artificially prepared aqueous solution presenting ticarcillin contaminated waters, which constitute a serious problem for human health. 81.99% of total organic carbon removal, 79.65% of chemical oxygen demand removal, and 94.35% of ticarcillin removal were achieved by using eco-friendly, time-saving, powerful and easy-applying, subcritical water oxidation method in the presence of a safe-to-use oxidizing agent, hydrogen peroxide. Central composite design, which belongs to the response surface methodology, was applied to design the degradation experiments, to optimize the methods, to evaluate the effects of the system variables, namely, temperature, hydrogen peroxide concentration, and treatment time, on the responses. In addition, theoretical equations were proposed in each removal processes. ANOVA tests were utilized to evaluate the reliability of the performed models. F values of 245.79, 88.74, and 48.22 were found for total organic carbon removal, chemical oxygen demand removal, and ticarcillin removal, respectively. Moreover, artificial neural network modeling was applied to estimate the response in each case and its prediction and optimizing performance was statistically examined and compared to the performance of central composite design.

Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2011-01-01

A methodology to compute probabilistically-combined thermo-mechanical fatigue life of polymer matrix laminated composites has been developed and is demonstrated. Matrix degradation effects caused by long-term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress-dependent multifactor-interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability-integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/-45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical-cyclic loads and low thermal-cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical-cyclic loads and high thermal-cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

Probabilistic Simulation for Combined Cycle Fatigue in Composites

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A methodology to compute probabilistic fatigue life of polymer matrix laminated composites has been developed and demonstrated. Matrix degradation effects caused by long term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress dependent multifactor interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/- 45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical cyclic loads and low thermal cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical cyclic loads and high thermal cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A methodology to compute probabilistically-combined thermo-mechanical fatigue life of polymer matrix laminated composites has been developed and is demonstrated. Matrix degradation effects caused by long-term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress-dependent multifactor-interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability-integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/-45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical-cyclic loads and low thermal-cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical-cyclic loads and high thermal-cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

The log-periodic-AR(1)-GARCH(1,1) model for financial crashes

NASA Astrophysics Data System (ADS)

Gazola, L.; Fernandes, C.; Pizzinga, A.; Riera, R.

2008-02-01

This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.

Reconciling the Mitscherlich's law of diminishing returns with Liebig's law of the minimum. Some results on crop modeling.

PubMed

Ferreira, Iuri E P; Zocchi, Silvio S; Baron, Daniel

2017-11-01

Reliable fertilizer recommendations depend on the correctness of the crop production models fitted to the data, but generally the crop models are built empirically, neglecting important physiological aspects related with response to fertilizers, or they are based in laws of plant mineral nutrition seen by many authors as conflicting theories: the Liebig's Law of the Minimum and Mitscherlich's Law of Diminishing Returns. We developed a new approach to modelling the crop response to fertilizers that reconcile these laws. In this study, the Liebig's Law is applied at the cellular level to explain plant production and, as a result, crop models compatible with the Law of Diminishing Returns are derived. Some classical crop models appear here as special cases of our methodology, and a new interpretation for Mitscherlich's Law is also provided. Copyright © 2017 Elsevier Inc. All rights reserved.

Assuring Electronics Reliability: What Could and Should Be Done Differently

NASA Astrophysics Data System (ADS)

Suhir, E.

The following “ ten commandments” for the predicted and quantified reliability of aerospace electronic, and photonic products are addressed and discussed: 1) The best product is the best compromise between the needs for reliability, cost effectiveness and time-to-market; 2) Reliability cannot be low, need not be higher than necessary, but has to be adequate for a particular product; 3) When reliability is imperative, ability to quantify it is a must, especially if optimization is considered; 4) One cannot design a product with quantified, optimized and assured reliability by limiting the effort to the highly accelerated life testing (HALT) that does not quantify reliability; 5) Reliability is conceived at the design stage and should be taken care of, first of all, at this stage, when a “ genetically healthy” product should be created; reliability evaluations and assurances cannot be delayed until the product is fabricated and shipped to the customer, i.e., cannot be left to the prognostics-and-health-monitoring/managing (PHM) stage; it is too late at this stage to change the design or the materials for improved reliability; that is why, when reliability is imperative, users re-qualify parts to assess their lifetime and use redundancy to build a highly reliable system out of insufficiently reliable components; 6) Design, fabrication, qualification and PHM efforts should consider and be specific for particular products and their most likely actual or at least anticipated application(s); 7) Probabilistic design for reliability (PDfR) is an effective means for improving the state-of-the-art in the field: nothing is perfect, and the difference between an unreliable product and a robust one is “ merely” the probability of failure (PoF); 8) Highly cost-effective and highly focused failure oriented accelerated testing (FOAT) geared to a particular pre-determined reliability model and aimed at understanding the physics of failure- anticipated by this model is an important constituent part of the PDfR effort; 9) Predictive modeling (PM) is another important constituent of the PDfR approach; in combination with FOAT, it is a powerful means to carry out sensitivity analyses (SA), to quantify and nearly eliminate failures (“ principle of practical confidence” ); 10) Consistent, comprehensive and physically meaningful PDfR can effectively contribute to the most feasible and the most effective qualification test (QT) methodologies, practices and specifications. The general concepts addressed in the paper are illustrated by numerical examples. It is concluded that although the suggested concept is promising and fruitful, further research, refinement, and validations are needed before this concept becomes widely accepted by the engineering community and implemented into practice. It is important that this novel approach is introduced gradually, whenever feasible and appropriate, in addition to, and in some situations even instead of, the currently employed various types and modifications of the forty year old HALT.

CARES/Life Ceramics Durability Evaluation Software Enhanced for Cyclic Fatigue

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.

1999-01-01

The CARES/Life computer program predicts the probability of a monolithic ceramic component's failure as a function of time in service. The program has many features and options for materials evaluation and component design. It couples commercial finite element programs--which resolve a component's temperature and stress distribution--to reliability evaluation and fracture mechanics routines for modeling strength-limiting defects. The capability, flexibility, and uniqueness of CARES/Life have attracted many users representing a broad range of interests and has resulted in numerous awards for technological achievements and technology transfer. Recent work with CARES/Life was directed at enhancing the program s capabilities with regards to cyclic fatigue. Only in the last few years have ceramics been recognized to be susceptible to enhanced degradation from cyclic loading. To account for cyclic loads, researchers at the NASA Lewis Research Center developed a crack growth model that combines the Power Law (time-dependent) and the Walker Law (cycle-dependent) crack growth models. This combined model has the characteristics of Power Law behavior (decreased damage) at high R ratios (minimum load/maximum load) and of Walker law behavior (increased damage) at low R ratios. In addition, a parameter estimation methodology for constant-amplitude, steady-state cyclic fatigue experiments was developed using nonlinear least squares and a modified Levenberg-Marquardt algorithm. This methodology is used to give best estimates of parameter values from cyclic fatigue specimen rupture data (usually tensile or flexure bar specimens) for a relatively small number of specimens. Methodology to account for runout data (unfailed specimens over the duration of the experiment) was also included.

Long-term ensemble forecast of snowmelt inflow into the Cheboksary Reservoir under two different weather scenarios

NASA Astrophysics Data System (ADS)

Gelfan, Alexander; Moreydo, Vsevolod; Motovilov, Yury; Solomatine, Dimitri P.

2018-04-01

A long-term forecasting ensemble methodology, applied to water inflows into the Cheboksary Reservoir (Russia), is presented. The methodology is based on a version of the semi-distributed hydrological model ECOMAG (ECOlogical Model for Applied Geophysics) that allows for the calculation of an ensemble of inflow hydrographs using two different sets of weather ensembles for the lead time period: observed weather data, constructed on the basis of the Ensemble Streamflow Prediction methodology (ESP-based forecast), and synthetic weather data, simulated by a multi-site weather generator (WG-based forecast). We have studied the following: (1) whether there is any advantage of the developed ensemble forecasts in comparison with the currently issued operational forecasts of water inflow into the Cheboksary Reservoir, and (2) whether there is any noticeable improvement in probabilistic forecasts when using the WG-simulated ensemble compared to the ESP-based ensemble. We have found that for a 35-year period beginning from the reservoir filling in 1982, both continuous and binary model-based ensemble forecasts (issued in the deterministic form) outperform the operational forecasts of the April-June inflow volume actually used and, additionally, provide acceptable forecasts of additional water regime characteristics besides the inflow volume. We have also demonstrated that the model performance measures (in the verification period) obtained from the WG-based probabilistic forecasts, which are based on a large number of possible weather scenarios, appeared to be more statistically reliable than the corresponding measures calculated from the ESP-based forecasts based on the observed weather scenarios.

A coupled hydrological-hydraulic flood inundation model calibrated using post-event measurements and integrated uncertainty analysis in a poorly gauged Mediterranean basin

NASA Astrophysics Data System (ADS)

Hdeib, Rouya; Abdallah, Chadi; Moussa, Roger; Colin, Francois

2017-04-01

Developing flood inundation maps of defined exceedance probabilities is required to provide information on the flood hazard and the associated risk. A methodology has been developed to model flood inundation in poorly gauged basins, where reliable information on the hydrological characteristics of floods are uncertain and partially captured by the traditional rain-gauge networks. Flood inundation is performed through coupling a hydrological rainfall-runoff (RR) model (HEC-HMS) with a hydraulic model (HEC-RAS). The RR model is calibrated against the January 2013 flood event in the Awali River basin, Lebanon (300 km2), whose flood peak discharge was estimated by post-event measurements. The resulting flows of the RR model are defined as boundary conditions of the hydraulic model, which is run to generate the corresponding water surface profiles and calibrated against 20 post-event surveyed cross sections after the January-2013 flood event. An uncertainty analysis is performed to assess the results of the models. Consequently, the coupled flood inundation model is simulated with design storms and flood inundation maps are generated of defined exceedance probabilities. The peak discharges estimated by the simulated RR model were in close agreement with the results from different empirical and statistical methods. This methodology can be extended to other poorly gauged basins facing common stage-gauge failure or characterized by floods with a stage exceeding the gauge measurement level, or higher than that defined by the rating curve.

Simulated Impacts of Climate Change on Water Use and Yield of Irrigated Sugarcane in South Africa

NASA Technical Reports Server (NTRS)

Jones, M.R; Singels, A.; Ruane, A. C.

2015-01-01

Reliable predictions of climate change impacts on water use, irrigation requirements and yields of irrigated sugarcane in South Africa (a water-scarce country) are necessary to plan adaptation strategies. Although previous work has been done in this regard, methodologies and results vary considerably. The objectives were (1) to estimate likely impacts of climate change on sugarcane yields, water use and irrigation demand at three irrigated sugarcane production sites in South Africa (Malelane, Pongola and La Mercy) for current (1980-2010) and future (2070-2100) climate scenarios, using an approach based on the Agricultural Model Inter-comparison and Improvement Project (AgMIP) protocols; and (2) to assess the suitability of this methodology for investigating climate change impacts on sugarcane production. Future climate datasets were generated using the Delta downscaling method and three Global Circulation Models (GCMs) assuming atmospheric CO2 concentration [CO2] of 734 ppm(A2 emissions scenario). Yield and water use were simulated using the DSSAT-Canegro v4.5 model. Irrigated cane yields are expected to increase at all three sites (between 11 and 14%), primarily due to increased interception of radiation as a result of accelerated canopy development. Evapotranspiration and irrigation requirements increased by 11% due to increased canopy cover and evaporative demand. Sucrose yields are expected to decline because of increased consumption of photo-assimilate for structural growth and maintenance respiration. Crop responses in canopy development and yield formation differed markedly between the crop cycles investigated. Possible agronomic implications of these results include reduced weed control costs due to shortened periods of partial canopy, a need for improved efficiency of irrigation to counter increased demands, and adjustments to ripening and harvest practices to counter decreased cane quality and optimize productivity. Although the Delta climate data downscaling method is considered robust, accurate and easily-understood, it does not change the future number of rain-days per month. The impacts of this and other climate data simplifications ought to be explored in future work. Shortcomings of the DSSAT-Canegro model include the simulated responses of phenological development, photosynthesis and respiration processes to high temperatures, and the disconnect between simulated biomass accumulation and expansive growth. Proposed methodology refinements should improve the reliability of predicted climate change impacts on sugarcane yield.

Computational methods for efficient structural reliability and reliability sensitivity analysis

NASA Technical Reports Server (NTRS)

Wu, Y.-T.

1993-01-01

This paper presents recent developments in efficient structural reliability analysis methods. The paper proposes an efficient, adaptive importance sampling (AIS) method that can be used to compute reliability and reliability sensitivities. The AIS approach uses a sampling density that is proportional to the joint PDF of the random variables. Starting from an initial approximate failure domain, sampling proceeds adaptively and incrementally with the goal of reaching a sampling domain that is slightly greater than the failure domain to minimize over-sampling in the safe region. Several reliability sensitivity coefficients are proposed that can be computed directly and easily from the above AIS-based failure points. These probability sensitivities can be used for identifying key random variables and for adjusting design to achieve reliability-based objectives. The proposed AIS methodology is demonstrated using a turbine blade reliability analysis problem.

Comparative Analysis of NOAA REFM and SNB3GEO Tools for the Forecast of the Fluxes of High-Energy Electrons at GEO

NASA Technical Reports Server (NTRS)

Balikhin, M. A.; Rodriguez, J. V.; Boynton, R. J.; Walker, S. N.; Aryan, Homayon; Sibeck, D. G.; Billings, S. A.

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB3GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB3GEO forecasts use solar wind density and interplanetary magnetic field B(sub z) observations at L1. The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB3GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB3GEO forecast.

Comparative analysis of NOAA REFM and SNB3GEO tools for the forecast of the fluxes of high-energy electrons at GEO.

PubMed

Balikhin, M A; Rodriguez, J V; Boynton, R J; Walker, S N; Aryan, H; Sibeck, D G; Billings, S A

2016-01-01

Reliable forecasts of relativistic electrons at geostationary orbit (GEO) are important for the mitigation of their hazardous effects on spacecraft at GEO. For a number of years the Space Weather Prediction Center at NOAA has provided advanced online forecasts of the fluence of electrons with energy >2 MeV at GEO using the Relativistic Electron Forecast Model (REFM). The REFM forecasts are based on real-time solar wind speed observations at L1. The high reliability of this forecasting tool serves as a benchmark for the assessment of other forecasting tools. Since 2012 the Sheffield SNB 3 GEO model has been operating online, providing a 24 h ahead forecast of the same fluxes. In addition to solar wind speed, the SNB 3 GEO forecasts use solar wind density and interplanetary magnetic field B z observations at L1.The period of joint operation of both of these forecasts has been used to compare their accuracy. Daily averaged measurements of electron fluxes by GOES 13 have been used to estimate the prediction efficiency of both forecasting tools. To assess the reliability of both models to forecast infrequent events of very high fluxes, the Heidke skill score was employed. The results obtained indicate that SNB 3 GEO provides a more accurate 1 day ahead forecast when compared to REFM. It is shown that the correction methodology utilized by REFM potentially can improve the SNB 3 GEO forecast.

Probabilistic structural mechanics research for parallel processing computers

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Martin, William R.

1991-01-01

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical.

Item response theory analysis of the Lichtenberg Financial Decision Screening Scale.

PubMed

Teresi, Jeanne A; Ocepek-Welikson, Katja; Lichtenberg, Peter A

2017-01-01

The focus of these analyses was to examine the psychometric properties of the Lichtenberg Financial Decision Screening Scale (LFDSS). The purpose of the screen was to evaluate the decisional abilities and vulnerability to exploitation of older adults. Adults aged 60 and over were interviewed by social, legal, financial, or health services professionals who underwent in-person training on the administration and scoring of the scale. Professionals provided a rating of the decision-making abilities of the older adult. The analytic sample included 213 individuals with an average age of 76.9 (SD = 10.1). The majority (57%) were female. Data were analyzed using item response theory (IRT) methodology. The results supported the unidimensionality of the item set. Several IRT models were tested. Ten ordinal and binary items evidenced a slightly higher reliability estimate (0.85) than other versions and better coverage in terms of the range of reliable measurement across the continuum of financial incapacity.

Durability evaluation of ceramic components using CARES/LIFE

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

1994-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker equation. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Application of this design methodology is demonstrated using experimental data from alumina bar and disk flexure specimens which exhibit SCG when exposed to water.

Durability evaluation of ceramic components using CARES/LIFE

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

Nemeth, N.N.; Janosik, L.A.; Gyekenyesi, J.P.

1996-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker equation. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength andmore » fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Application of this design methodology is demonstrated using experimental data from alumina bar and disk flexure specimens, which exhibit SCG when exposed to water.« less

Standards for Environmental Measurement Using GIS: Toward a Protocol for Protocols.

PubMed

Forsyth, Ann; Schmitz, Kathryn H; Oakes, Michael; Zimmerman, Jason; Koepp, Joel

2006-02-01

Interdisciplinary research regarding how the built environment influences physical activity has recently increased. Many research projects conducted jointly by public health and environmental design professionals are using geographic information systems (GIS) to objectively measure the built environment. Numerous methodological issues remain, however, and environmental measurements have not been well documented with accepted, common definitions of valid, reliable variables. This paper proposes how to create and document standardized definitions for measures of environmental variables using GIS with the ultimate goal of developing reliable, valid measures. Inherent problems with software and data that hamper environmental measurement can be offset by protocols combining clear conceptual bases with detailed measurement instructions. Examples demonstrate how protocols can more clearly translate concepts into specific measurement. This paper provides a model for developing protocols to allow high quality comparative research on relationships between the environment and physical activity and other outcomes of public health interest.

Qualitative Importance Measures of Systems Components - A New Approach and Its Applications

NASA Astrophysics Data System (ADS)

Chybowski, Leszek; Gawdzińska, Katarzyna; Wiśnicki, Bogusz

2016-12-01

The paper presents an improved methodology of analysing the qualitative importance of components in the functional and reliability structures of the system. We present basic importance measures, i.e. the Birnbaum's structural measure, the order of the smallest minimal cut-set, the repetition count of an i-th event in the Fault Tree and the streams measure. A subsystem of circulation pumps and fuel heaters in the main engine fuel supply system of a container vessel illustrates the qualitative importance analysis. We constructed a functional model and a Fault Tree which we analysed using qualitative measures. Additionally, we compared the calculated measures and introduced corrected measures as a tool for improving the analysis. We proposed scaled measures and a common measure taking into account the location of the component in the reliability and functional structures. Finally, we proposed an area where the measures could be applied.

Assessing the relative efficiency of water companies in the English and Welsh water industry: a metafrontier approach.

PubMed

Molinos-Senante, María; Maziotis, Alexandros; Sala-Garrido, Ramon

2015-11-01

The assessment of relative efficiency of water companies is essential for managers and authorities. This is evident in the UK water sector where there are companies with different services such as water and sewerage companies (WaSCs) and water-only companies (WoCs). Therefore, it is a critical limitation to estimate a common production frontier for both types of companies, as it might lead to biased efficiency estimates. In this paper, a robust and reliable methodology, the metafrontier model, is applied to compare the efficiency of water companies providing different services. The results illustrate the superior performance of WaSCs compared to WoCs. It also confirms the presence of economies of scope in the UK water industry. The methodology and results of this study are of great interest for both regulators and water utility managers to make informed decisions.

The PEDro scale had acceptably high convergent validity, construct validity, and interrater reliability in evaluating methodological quality of pharmaceutical trials.

PubMed

Yamato, Tie Parma; Maher, Chris; Koes, Bart; Moseley, Anne

2017-06-01

The Physiotherapy Evidence Database (PEDro) scale has been widely used to investigate methodological quality in physiotherapy randomized controlled trials; however, its validity has not been tested for pharmaceutical trials. The aim of this study was to investigate the validity and interrater reliability of the PEDro scale for pharmaceutical trials. The reliability was also examined for the Cochrane Back and Neck (CBN) Group risk of bias tool. This is a secondary analysis of data from a previous study. We considered randomized placebo controlled trials evaluating any pain medication for chronic spinal pain or osteoarthritis. Convergent validity was evaluated by correlating the PEDro score with the summary score of the CBN risk of bias tool. The construct validity was tested using a linear regression analysis to determine the degree to which the total PEDro score is associated with treatment effect sizes, journal impact factor, and the summary score for the CBN risk of bias tool. The interrater reliability was estimated using the Prevalence and Bias Adjusted Kappa coefficient and 95% confidence interval (CI) for the PEDro scale and CBN risk of bias tool. Fifty-three trials were included, with 91 treatment effect sizes included in the analyses. The correlation between PEDro scale and CBN risk of bias tool was 0.83 (95% CI 0.76-0.88) after adjusting for reliability, indicating strong convergence. The PEDro score was inversely associated with effect sizes, significantly associated with the summary score for the CBN risk of bias tool, and not associated with the journal impact factor. The interrater reliability for each item of the PEDro scale and CBN risk of bias tool was at least substantial for most items (>0.60). The intraclass correlation coefficient for the PEDro score was 0.80 (95% CI 0.68-0.88), and for the CBN, risk of bias tool was 0.81 (95% CI 0.69-0.88). There was evidence for the convergent and construct validity for the PEDro scale when used to evaluate methodological quality of pharmacological trials. Both risk of bias tools have acceptably high interrater reliability. Copyright © 2017 Elsevier Inc. All rights reserved.

Validation in the cross-cultural adaptation of the Korean version of the Oswestry Disability Index.

PubMed

Jeon, Chang-Hoon; Kim, Dong-Jae; Kim, Se-Kang; Kim, Dong-Jun; Lee, Hwan-Mo; Park, Heui-Jeon

2006-12-01

Disability questionnaires are used for clinical assessment, outcome measurement, and research methodology. Any disability measurement must be adapted culturally for comparability of data, when the patients, who are measured, use different languages. This study aimed to conduct cross-cultural adaptation in translating the original (English) version of the Oswestry Disability Index (ODI) into Korean, and then to assess the reliability of the Korean versions of the Oswestry Disability Index (KODI). We used methodology to obtain semantic, idiomatic, experimental, and conceptual equivalences for the process of cross-cultural adaptation. The KODI were tested in 116 patients with chronic low back pain. The internal consistency and reliability for the KODI reached 0.9168 (Cronbach's alpha). The test-retest reliability was assessed with 32 patients (who were not included in the assessment of Cronbach's alpha) over a time interval of 4 days. Test-retest correlation reliability was 0.9332. The entire process and the results of this study were reported to the developer (Dr. Fairbank JC), who appraised the KODI. There is little evidence of differential item functioning in KODI. The results suggest that the KODI is internally consistent and reliable. Therefore, the KODI can be recommended as a low back pain assessment tool in Korea.

Validation in the Cross-Cultural Adaptation of the Korean Version of the Oswestry Disability Index

PubMed Central

Kim, Dong-Jae; Kim, Se-Kang; Kim, Dong-Jun; Lee, Hwan-Mo; Park, Heui-Jeon

2006-01-01

Disability questionnaires are used for clinical assessment, outcome measurement, and research methodology. Any disability measurement must be adapted culturally for comparability of data, when the patients, who are measured, use different languages. This study aimed to conduct cross-cultural adaptation in translating the original (English) version of the Oswestry Disability Index (ODI) into Korean, and then to assess the reliability of the Korean versions of the Oswestry Disability Index (KODI). We used methodology to obtain semantic, idiomatic, experimental, and conceptual equivalences for the process of cross-cultural adaptation. The KODI were tested in 116 patients with chronic low back pain. The internal consistency and reliability for the KODI reached 0.9168 (Cronbach's alpha). The test-retest reliability was assessed with 32 patients (who were not included in the assessment of Cronbach's alpha) over a time interval of 4 days. Test-retest correlation reliability was 0.9332. The entire process and the results of this study were reported to the developer (Dr. Fairbank JC), who appraised the KODI. There is little evidence of differential item functioning in KODI. The results suggest that the KODI is internally consistent and reliable. Therefore, the KODI can be recommended as a low back pain assessment tool in Korea. PMID:17179693

Two-phase flow characterization based on advanced instrumentation, neural networks, and mathematical modeling

NASA Astrophysics Data System (ADS)

Mi, Ye

1998-12-01

The major objective of this thesis is focused on theoretical and experimental investigations of identifying and characterizing vertical and horizontal flow regimes in two-phase flows. A methodology of flow regime identification with impedance-based neural network systems and a comprehensive model of vertical slug flow have been developed. Vertical slug flow has been extensively investigated and characterized with geometric, kinematic and hydrodynamic parameters. A multi-sensor impedance void-meter and a multi-sensor magnetic flowmeter were developed. The impedance void-meter was cross-calibrated with other reliable techniques for void fraction measurements. The performance of the impedance void-meter to measure the void propagation velocity was evaluated by the drift flux model. It was proved that the magnetic flowmeter was applicable to vertical slug flow measurements. Separable signals from these instruments allow us to unearth most characteristics of vertical slug flow. A methodology of vertical flow regime identification was developed. Supervised neural network and self-organizing neural network systems were employed. First, they were trained with results from an idealized simulation of impedance in a two-phase mixture. The simulation was mainly based on Mishima and Ishii's flow regime map, the drift flux model, and the newly developed model of slug flow. Then, these trained systems were tested with impedance signals. The results showed that the neural network systems were appropriate classifiers of vertical flow regimes. The theoretical models and experimental databases used in the simulation were reliable. Furthermore, this approach was applied successfully to horizontal flow identification. A comprehensive model was developed to predict important characteristics of vertical slug flow. It was realized that the void fraction of the liquid slug is determined by the relative liquid motion between the Taylor bubble tail and the Taylor bubble wake. Relying on this understanding and experimental results, a special relationship was built for the void fraction of the liquid slug. The prediction of the void fraction of the liquid slug was considerably improved. Experimental characterization of vertical slug flows was performed extensively with the impedance void-meter and the magnetic flowmeter. The theoretical predictions were compared with the experimental results. The agreements between them are very satisfactory.

MODFLOW 2000 Head Uncertainty, a First-Order Second Moment Method

USGS Publications Warehouse

Glasgow, H.S.; Fortney, M.D.; Lee, J.; Graettinger, A.J.; Reeves, H.W.

2003-01-01

A computationally efficient method to estimate the variance and covariance in piezometric head results computed through MODFLOW 2000 using a first-order second moment (FOSM) approach is presented. This methodology employs a first-order Taylor series expansion to combine model sensitivity with uncertainty in geologic data. MODFLOW 2000 is used to calculate both the ground water head and the sensitivity of head to changes in input data. From a limited number of samples, geologic data are extrapolated and their associated uncertainties are computed through a conditional probability calculation. Combining the spatially related sensitivity and input uncertainty produces the variance-covariance matrix, the diagonal of which is used to yield the standard deviation in MODFLOW 2000 head. The variance in piezometric head can be used for calibrating the model, estimating confidence intervals, directing exploration, and evaluating the reliability of a design. A case study illustrates the approach, where aquifer transmissivity is the spatially related uncertain geologic input data. The FOSM methodology is shown to be applicable for calculating output uncertainty for (1) spatially related input and output data, and (2) multiple input parameters (transmissivity and recharge).

Application of hybrid life cycle approaches to emerging energy technologies--the case of wind power in the UK.

PubMed

Wiedmann, Thomas O; Suh, Sangwon; Feng, Kuishuang; Lenzen, Manfred; Acquaye, Adolf; Scott, Kate; Barrett, John R

2011-07-01

Future energy technologies will be key for a successful reduction of man-made greenhouse gas emissions. With demand for electricity projected to increase significantly in the future, climate policy goals of limiting the effects of global atmospheric warming can only be achieved if power generation processes are profoundly decarbonized. Energy models, however, have ignored the fact that upstream emissions are associated with any energy technology. In this work we explore methodological options for hybrid life cycle assessment (hybrid LCA) to account for the indirect greenhouse gas (GHG) emissions of energy technologies using wind power generation in the UK as a case study. We develop and compare two different approaches using a multiregion input-output modeling framework - Input-Output-based Hybrid LCA and Integrated Hybrid LCA. The latter utilizes the full-sized Ecoinvent process database. We discuss significance and reliability of the results and suggest ways to improve the accuracy of the calculations. The comparison of hybrid LCA methodologies provides valuable insight into the availability and robustness of approaches for informing energy and environmental policy.

Development of the hard and soft constraints based optimisation model for unit sizing of the hybrid renewable energy system designed for microgrid applications

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Kumaravel

2017-02-01

The hybrid energy systems (HESs) based electricity generation system has become a more attractive solution for rural electrification nowadays. Economically feasible and technically reliable HESs are solidly based on an optimisation stage. This article discusses about the optimal unit sizing model with the objective function to minimise the total cost of the HES. Three typical rural sites from southern part of India have been selected for the application of the developed optimisation methodology. Feasibility studies and sensitivity analysis on the optimal HES are discussed elaborately in this article. A comparison has been carried out with the Hybrid Optimization Model for Electric Renewable optimisation model for three sites. The optimal HES is found with less total net present rate and rate of energy compared with the existing method

Reliability and Validity of the International Physical Activity Questionnaire for Assessing Walking

ERIC Educational Resources Information Center

van der Ploeg, Hidde P.; Tudor-Locke, Catrine; Marshall, Alison L.; Craig, Cora; Hagstromer, Maria; Sjostrom, Michael; Bauman, Adrian

2010-01-01

The single most commonly reported physical activity in public health surveys is walking. As evidence accumulates that walking is important for preventing weight gain and reducing the risk of diabetes, there is increased need to capture this behavior in a valid and reliable manner. Although the disadvantages of a self-report methodology are well…

The Effect of Different Cultural Lenses on Reliability and Validity in Observational Data: The Example of Chinese Immigrant Parent-Toddler Dinner Interactions

ERIC Educational Resources Information Center

Wang, Yan Z.; Wiley, Angela R.; Zhou, Xiaobin

2007-01-01

This study used a mixed methodology to investigate reliability, validity, and analysis level with Chinese immigrant observational data. European-American and Chinese coders quantitatively rated 755 minutes of Chinese immigrant parent-toddler dinner interactions on parental sensitivity, intrusiveness, detachment, negative affect, positive affect,…

The Reliability of Methodological Ratings for speechBITE Using the PEDro-P Scale

ERIC Educational Resources Information Center

Murray, Elizabeth; Power, Emma; Togher, Leanne; McCabe, Patricia; Munro, Natalie; Smith, Katherine

2013-01-01

Background: speechBITE (http://www.speechbite.com) is an online database established in order to help speech and language therapists gain faster access to relevant research that can used in clinical decision-making. In addition to containing more than 3000 journal references, the database also provides methodological ratings on the PEDro-P (an…

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

A less field-intensive robust design for estimating demographic parameters with Mark-resight data

USGS Publications Warehouse

McClintock, B.T.; White, Gary C.

2009-01-01

The robust design has become popular among animal ecologists as a means for estimating population abundance and related demographic parameters with mark-recapture data. However, two drawbacks of traditional mark-recapture are financial cost and repeated disturbance to animals. Mark-resight methodology may in many circumstances be a less expensive and less invasive alternative to mark-recapture, but the models developed to date for these data have overwhelmingly concentrated only on the estimation of abundance. Here we introduce a mark-resight model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. The model may be implemented using standard statistical computing software, but it has also been incorporated into the freeware package Program MARK. We illustrate the use of our model with mainland New Zealand Robin (Petroica australis) data collected to ascertain whether this methodology may be a reliable alternative for monitoring endangered populations of a closely related species inhabiting the Chatham Islands. We found this method to be a viable alternative to traditional mark-recapture when cost or disturbance to species is of particular concern in long-term population monitoring programs. ?? 2009 by the Ecological Society of America.

In Silico Oncology: Quantification of the In Vivo Antitumor Efficacy of Cisplatin-Based Doublet Therapy in Non-Small Cell Lung Cancer (NSCLC) through a Multiscale Mechanistic Model

PubMed Central

Kolokotroni, Eleni; Dionysiou, Dimitra; Veith, Christian; Kim, Yoo-Jin; Franz, Astrid; Grgic, Aleksandar; Bohle, Rainer M.; Stamatakos, Georgios

2016-01-01

The 5-year survival of non-small cell lung cancer patients can be as low as 1% in advanced stages. For patients with resectable disease, the successful choice of preoperative chemotherapy is critical to eliminate micrometastasis and improve operability. In silico experimentations can suggest the optimal treatment protocol for each patient based on their own multiscale data. A determinant for reliable predictions is the a priori estimation of the drugs’ cytotoxic efficacy on cancer cells for a given treatment. In the present work a mechanistic model of cancer response to treatment is applied for the estimation of a plausible value range of the cell killing efficacy of various cisplatin-based doublet regimens. Among others, the model incorporates the cancer related mechanism of uncontrolled proliferation, population heterogeneity, hypoxia and treatment resistance. The methodology is based on the provision of tumor volumetric data at two time points, before and after or during treatment. It takes into account the effect of tumor microenvironment and cell repopulation on treatment outcome. A thorough sensitivity analysis based on one-factor-at-a-time and latin hypercube sampling/partial rank correlation coefficient approaches has established the volume growth rate and the growth fraction at diagnosis as key features for more accurate estimates. The methodology is applied on the retrospective data of thirteen patients with non-small cell lung cancer who received cisplatin in combination with gemcitabine, vinorelbine or docetaxel in the neoadjuvant context. The selection of model input values has been guided by a comprehensive literature survey on cancer-specific proliferation kinetics. The latin hypercube sampling has been recruited to compensate for patient-specific uncertainties. Concluding, the present work provides a quantitative framework for the estimation of the in-vivo cell-killing ability of various chemotherapies. Correlation studies of such estimates with the molecular profile of patients could serve as a basis for reliable personalized predictions. PMID:27657742

A Monte-Carlo simulation analysis for evaluating the severity distribution functions (SDFs) calibration methodology and determining the minimum sample-size requirements.

PubMed

Shirazi, Mohammadali; Reddy Geedipally, Srinivas; Lord, Dominique

2017-01-01

Severity distribution functions (SDFs) are used in highway safety to estimate the severity of crashes and conduct different types of safety evaluations and analyses. Developing a new SDF is a difficult task and demands significant time and resources. To simplify the process, the Highway Safety Manual (HSM) has started to document SDF models for different types of facilities. As such, SDF models have recently been introduced for freeway and ramps in HSM addendum. However, since these functions or models are fitted and validated using data from a few selected number of states, they are required to be calibrated to the local conditions when applied to a new jurisdiction. The HSM provides a methodology to calibrate the models through a scalar calibration factor. However, the proposed methodology to calibrate SDFs was never validated through research. Furthermore, there are no concrete guidelines to select a reliable sample size. Using extensive simulation, this paper documents an analysis that examined the bias between the 'true' and 'estimated' calibration factors. It was indicated that as the value of the true calibration factor deviates further away from '1', more bias is observed between the 'true' and 'estimated' calibration factors. In addition, simulation studies were performed to determine the calibration sample size for various conditions. It was found that, as the average of the coefficient of variation (CV) of the 'KAB' and 'C' crashes increases, the analyst needs to collect a larger sample size to calibrate SDF models. Taking this observation into account, sample-size guidelines are proposed based on the average CV of crash severities that are used for the calibration process. Copyright © 2016 Elsevier Ltd. All rights reserved.

Emerging technologies for the changing global market

NASA Technical Reports Server (NTRS)

Cruit, Wendy; Schutzenhofer, Scott; Goldberg, Ben; Everhart, Kurt

1993-01-01

This project served to define an appropriate methodology for effective prioritization of technology efforts required to develop replacement technologies mandated by imposed and forecast legislation. The methodology used is a semi-quantative approach derived from quality function deployment techniques (QFD Matrix). This methodology aims to weight the full environmental, cost, safety, reliability, and programmatic implications of replacement technology development to allow appropriate identification of viable candidates and programmatic alternatives. The results will be implemented as a guideline for consideration for current NASA propulsion systems.

Characterizing the reliability of a bioMEMS-based cantilever sensor

NASA Astrophysics Data System (ADS)

Bhalerao, Kaustubh D.

2004-12-01

The cantilever-based BioMEMS sensor represents one instance from many competing ideas of biosensor technology based on Micro Electro Mechanical Systems. The advancement of BioMEMS from laboratory-scale experiments to applications in the field will require standardization of their components and manufacturing procedures as well as frameworks to evaluate their performance. Reliability, the likelihood with which a system performs its intended task, is a compact mathematical description of its performance. The mathematical and statistical foundation of systems-reliability has been applied to the cantilever-based BioMEMS sensor. The sensor is designed to detect one aspect of human ovarian cancer, namely the over-expression of the folate receptor surface protein (FR-alpha). Even as the application chosen is clinically motivated, the objective of this study was to demonstrate the underlying systems-based methodology used to design, develop and evaluate the sensor. The framework development can be readily extended to other BioMEMS-based devices for disease detection and will have an impact in the rapidly growing $30 bn industry. The Unified Modeling Language (UML) is a systems-based framework for design and development of object-oriented information systems which has potential application for use in systems designed to interact with biological environments. The UML has been used to abstract and describe the application of the biosensor, to identify key components of the biosensor, and the technology needed to link them together in a coherent manner. The use of the framework is also demonstrated in computation of system reliability from first principles as a function of the structure and materials of the biosensor. The outcomes of applying the systems-based framework to the study are the following: (1) Characterizing the cantilever-based MEMS device for disease (cell) detection. (2) Development of a novel chemical interface between the analyte and the sensor that provides a degree of selectivity towards the disease. (3) Demonstrating the performance and measuring the reliability of the biosensor prototype, and (4) Identification of opportunities in technological development in order to further refine the proposed biosensor. Application of the methodology to design develop and evaluate the reliability of BioMEMS devices will be beneficial in the streamlining the growth of the BioMEMS industry, while providing a decision-support tool in comparing and adopting suitable technologies from available competing options.

Psychometric Properties of the Turkish Version of Caregiver Burden Index (CBI) for Parents of Children with Allergies.

PubMed

Ekim, Ayfer; Hecan, Melis; Oren, Serkan

Childhood chronic diseases have a great impact, including physiological, social and financial burdens, on parents. The concept of "caregiver burden" is gaining importance to understand the effects of allergic diseases and plan family-centered strategies. The purpose of this study was to examine the psychometric properties of the Caregiver Burden Index (CBI) in Turkish mothers of children with allergies. The participants of this methodological study were 213 mothers of children with allergies between 6 and 12years. Construct validity was evaluated through factor analysis and reliability was evaluated through internal consistency and item-total correlation. In reliability analysis, the overall Cronbach's alpha value (0.85) demonstrated a high level of reliability. The corrected item-total correlation varied between 0.63 and 0.84. In exploratory factor analysis, it was detected that 3 factors structure explained 73.6% of the total variance. This study indicated that the CBI is a valid and reliable tool to assess the caregiver burden of mothers of Turkish children with allergies. The results of this study contribute to the development and implementation of evidence based models of care that address the caregiver burden needs of parents whose children have allergies. Copyright © 2017 Elsevier Inc. All rights reserved.

Test-retest reliability of eye tracking in the visual world paradigm for the study of real-time spoken word recognition.

PubMed

Farris-Trimble, Ashley; McMurray, Bob

2013-08-01

Researchers have begun to use eye tracking in the visual world paradigm (VWP) to study clinical differences in language processing, but the reliability of such laboratory tests has rarely been assessed. In this article, the authors assess test-retest reliability of the VWP for spoken word recognition. Methods Participants performed an auditory VWP task in repeated sessions and a visual-only VWP task in a third session. The authors performed correlation and regression analyses on several parameters to determine which reflect reliable behavior and which are predictive of behavior in later sessions. Results showed that the fixation parameters most closely related to timing and degree of fixations were moderately-to-strongly correlated across days, whereas the parameters related to rate of increase or decrease of fixations to particular items were less strongly correlated. Moreover, when including factors derived from the visual-only task, the performance of the regression model was at least moderately correlated with Day 2 performance on all parameters ( R > .30). The VWP is stable enough (with some caveats) to serve as an individual measure. These findings suggest guidelines for future use of the paradigm and for areas of improvement in both methodology and analysis.

Feasibility of groundwater recharge dam projects in arid environments

NASA Astrophysics Data System (ADS)

Jaafar, H. H.

2014-05-01

A new method for determining feasibility and prioritizing investments for agricultural and domestic recharge dams in arid regions is developed and presented. The method is based on identifying the factors affecting the decision making process and evaluating these factors, followed by determining the indices in a GIS-aided environment. Evaluated parameters include results from field surveys and site visits, land cover and soils data, precipitation data, runoff data and modeling, number of beneficiaries, domestic irrigation demand, reservoir objectives, demography, reservoirs yield and reliability, dam structures, construction costs, and operation and maintenance costs. Results of a case study on more than eighty proposed dams indicate that assessment of reliability, annualized cost/demand satisfied and yield is crucial prior to investment decision making in arid areas. Irrigation demand is the major influencing parameter on yield and reliability of recharge dams, even when only 3 months of the demand were included. Reliability of the proposed reservoirs as related to their standardized size and net inflow was found to increase with increasing yield. High priority dams were less than 4% of the total, and less priority dams amounted to 23%, with the remaining found to be not feasible. The results of this methodology and its application has proved effective in guiding stakeholders for defining most favorable sites for preliminary and detailed design studies and commissioning.

Formation of integrated structural units using the systematic and integrated method when implementing high-rise construction projects

NASA Astrophysics Data System (ADS)

Abramov, Ivan

2018-03-01

Development of design documentation for a future construction project gives rise to a number of issues with the main one being selection of manpower for structural units of the project's overall implementation system. Well planned and competently staffed integrated structural construction units will help achieve a high level of reliability and labor productivity and avoid negative (extraordinary) situations during the construction period eventually ensuring improved project performance. Research priorities include the development of theoretical recommendations for enhancing reliability of a structural unit staffed as an integrated construction crew. The author focuses on identification of destabilizing factors affecting formation of an integrated construction crew; assessment of these destabilizing factors; based on the developed mathematical model, highlighting the impact of these factors on the integration criterion with subsequent identification of an efficiency and reliability criterion for the structural unit in general. The purpose of this article is to develop theoretical recommendations and scientific and methodological provisions of an organizational and technological nature in order to identify a reliability criterion for a structural unit based on manpower integration and productivity criteria. With this purpose in mind, complex scientific tasks have been defined requiring special research, development of corresponding provisions and recommendations based on the system analysis findings presented herein.

Mechanical System Reliability and Cost Integration Using a Sequential Linear Approximation Method

NASA Technical Reports Server (NTRS)

Kowal, Michael T.

1997-01-01

The development of new products is dependent on product designs that incorporate high levels of reliability along with a design that meets predetermined levels of system cost. Additional constraints on the product include explicit and implicit performance requirements. Existing reliability and cost prediction methods result in no direct linkage between variables affecting these two dominant product attributes. A methodology to integrate reliability and cost estimates using a sequential linear approximation method is proposed. The sequential linear approximation method utilizes probability of failure sensitivities determined from probabilistic reliability methods as well a manufacturing cost sensitivities. The application of the sequential linear approximation method to a mechanical system is demonstrated.

The influence of capture-recapture methodology on the evolution of the North American Bird Banding Program

USGS Publications Warehouse

Tautin, J.; Lebreton, J.-D.; North, P.M.

1993-01-01

Capture-recapture methodology has advanced greatly in the last twenty years and is now a major factor driving the continuing evolution of the North American bird banding program. Bird banding studies are becoming more scientific with improved study designs and analytical procedures. Researchers and managers are gaining more reliable knowledge which in turn betters the conservation of migratory birds. The advances in capture-recapture methodology have benefited gamebird studies primarily, but nongame bird studies will benefit similarly as they expand greatly in the next decade. Further theoretical development of capture-recapture methodology should be encouraged, and, to maximize benefits of the methodology, work on practical applications should be increased.

SU-E-T-630: Predictive Modeling of Mortality, Tumor Control, and Normal Tissue Complications After Stereotactic Body Radiotherapy for Stage I Non-Small Cell Lung Cancer

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

Lindsay, WD; Oncora Medical, LLC, Philadelphia, PA; Berlind, CG

Purpose: While rates of local control have been well characterized after stereotactic body radiotherapy (SBRT) for stage I non-small cell lung cancer (NSCLC), less data are available characterizing survival and normal tissue toxicities, and no validated models exist assessing these parameters after SBRT. We evaluate the reliability of various machine learning techniques when applied to radiation oncology datasets to create predictive models of mortality, tumor control, and normal tissue complications. Methods: A dataset of 204 consecutive patients with stage I non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT) at the University of Pennsylvania between 2009 and 2013more » was used to create predictive models of tumor control, normal tissue complications, and mortality in this IRB-approved study. Nearly 200 data fields of detailed patient- and tumor-specific information, radiotherapy dosimetric measurements, and clinical outcomes data were collected. Predictive models were created for local tumor control, 1- and 3-year overall survival, and nodal failure using 60% of the data (leaving the remainder as a test set). After applying feature selection and dimensionality reduction, nonlinear support vector classification was applied to the resulting features. Models were evaluated for accuracy and area under ROC curve on the 81-patient test set. Results: Models for common events in the dataset (such as mortality at one year) had the highest predictive power (AUC = .67, p < 0.05). For rare occurrences such as radiation pneumonitis and local failure (each occurring in less than 10% of patients), too few events were present to create reliable models. Conclusion: Although this study demonstrates the validity of predictive analytics using information extracted from patient medical records and can most reliably predict for survival after SBRT, larger sample sizes are needed to develop predictive models for normal tissue toxicities and more advanced machine learning methodologies need be consider in the future.« less

Simulating Nationwide Pandemics: Applying the Multi-scale Epidemiologic Simulation and Analysis System to Human Infectious Diseases

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

Dombroski, M; Melius, C; Edmunds, T

2008-09-24

This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to humanmore » epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future work including validating the model against reliable historical disease data, improving contact rates, spread methods, and disease parameters through discussions with epidemiological experts, and incorporating realistic behavioral assumptions.« less