Consistent Levels Of Reliability Research Articles

Self- vs. External-Regulation Behavior ScaleTM in different psychological contexts: A validation study.

The self- vs. external-regulation behavior theory, SR-ER Theory (2021) model has postulated the Self-Regulation /Non or De-Regulation/Dys-regulation (SR-NR-DR) continuum in the person and in their context. The model also generates a behavioral heuristic that allows us to predict and explain the variability of other dependent behavioral variables in a range of scenarios (clinical, educational, health and technology contexts). Consequently, the objective of this study was to validate the different scales prepared on the basis of the theory presented. A total of 469 students voluntarily completed at different times the five questionnaires presented, to give a total of 1,385 completed questionnaires. Using an ex post facto design, descriptive, correlational, confirmatory factorial analysis (CFA), reliability, and concurrent validity analyses were carried out. The scales were analyzed individually and as a whole. The results showed the acceptable structure of scale and consistent levels of reliability. The five levels generated by the SR-NR-DR (personal and contextual) combinatory heuristic that arises from the theoretical model determined significant differences in the levels of the variables analyzed for each psychological context. We discuss the theoretical implications and the implications for the assessment and improvement of the behaviors analyzed in function of the personal and contextual regulation levels evaluated.

Effect of environmental modelling and inspection strategy on the optimal design of floating wind turbines

In order to reduce design conservatism and consequently the cost of energy, appropriate and cost-optimal safety factors should be derived, in light of environmental load uncertainties and lifetime costs. In the present work, a linearized dynamic model has been used together with Monte Carlo simulations and a numerical design optimization procedure to evaluate the impact of the description of wind and wave loads on the fatigue reliability and optimal design of a 10 MW spar floating wind turbine. Trade-offs between design costs and inspection costs with different design fatigue factors (DFFs) have also been assessed. The analyses have been performed for a realistic wind park site, where an environmental model has been developed based on hindcast data. Considering stochastic turbulence intensity, wind-wave misalignment, wind directional distribution, and a two-peak wave spectrum reduced the long-term fatigue damage by approximately two-thirds along the fatigue-critical part of the support structure compared to the base model. Re-designing the tower and platform with the full environmental model resulted in 11% reduction in CAPEX. However, due to the applied design optimization procedure, consistent reliability levels were achieved along the tower length, which resulted in important system side effects for the total structural reliability. Trade-offs between CAPEX and OPEX were derived based on a probabilistic fracture mechanics model and reliability updating through inspections. The necessary inspection intervals to achieve the same accumulated reliability after 20 years of operation were identified with different DFFs, and cost-optimal safety factors were computed with different OPEX costs and interest rates.

Uncertainty modeling in reliability analysis of floating wind turbine support structures

Accurate structural reliability assessment of floating wind turbine (FWT) systems is a desideratum for achieving consistent optimal reliability levels and cost-effective design. Such reliability assessment should consider relevant system uncertainties—a nontrivial task. Formulation of the reliability problem requires structural demand in form of load and load effect. Support structure loads are predicted with time-domain dynamic simulations. This represents a challenge when thousands of such simulations are required to capture the uncertainty associated with design variables. Finite element analysis (FEA) is commonly used to evaluate load effects such as stresses, strains etc. This can be computationally expensive if not prohibitive when such evaluation is carried out for every time step. To tackle these issues, a framework for expeditious load effect computation and robust reliability analysis of FWT support structures under ultimate limit state design is presented. The framework employs linear elastic FEA and Kriging surrogate models. The adequacy of Kriging as applied in this study is investigated using high fidelity simulation data. The results highlight the importance of incorporating the Kriging uncertainty in the formulation of the limit state function. With the framework presented, FWT support structures can be designed at consistent reliability levels leading to cost reductions.

Reliability analysis of precast prestressed hollow core slabs

The precast concrete elements encompass uncertainty, due to randomness of the applied loads, concrete characteristics and dimensional inaccuracies. The proposed work focuses on reliability analysis of precast Prestressed Hollow Core (PHC) slabs in terms of statistical properties of the contributing parameters using Monte Carlo simulation. The random variables relating to geometrical dimensions of PHC slab such as effective depth (dp) and web-width (bw) for different grades of concrete (fc) are considered for analysis. The numerical models on ANSYS APDL release18.1 and Concise Beam ver.4.7 are validated with the experimental results with respect to failure load and deflection. The bending moments corresponding to failure loads under single Line Loading (LL) at mid span, Two Line Loading (TLL) and Uniformly Distributed Loading (UDL) cases were evaluated by modelling using Concise Beam software. The reliability analysis was implemented by developing a program in MATLAB R2015a software. It was observed that there is consistent level of reliability in the design methodology adopted in ACI-318.

Fire Fragility Functions for Steel Frame Buildings: Sensitivity Analysis and Reliability Framework

Fire fragility functions are a powerful method to characterize the probabilistic vulnerability of buildings to fire in the context of urban resilience assessment. But this method is recent and the influence of the different uncertain parameters on the functions has not been systematically studied. The first objective of this paper is to identify the prevailing parameters in constructing fire fragility functions for steel frame buildings. To this end, sensitivity analyses are conducted using Monte Carlo Simulations and a variance-based method, focusing on column failure fragilities. Fragilities for buildings with 3 to 12 stories, 0 to 3 h fire resistance rating and various occupancies are compared, assuming compartment areas ranging from 15 m2 to 80 m2. Results show that uncertainties in fire, heat transfer and structural models all generate significant variability in the fire fragility. In addition to fire load as the intensity measure, significant probabilistic parameters are the compartment geometry and openings, the thickness and thermal conductivity of fire protection, and the temperature dependent mechanical properties of steel. The second objective is to clarify the incorporation of fragility functions in a comprehensive structural fire reliability framework. A methodology for combining the functions with the ignition likelihood per year and with the fire loading in MJ/m2 is described, yielding annual probability estimates of column failure due to fire in the buildings. For a sprinklered office building designed according to prescriptive provisions, this annual probability ranges from 1.90 × 10−7 to 0.12 × 10−7 per year as a function of the building height. The probabilistic modeling techniques proposed in this paper can be used to establish consistent reliability levels in different buildings and to evaluate resilience for fire scenarios.

Probabilistic Lateral Buckling Assessment

This paper presents a probabilistic method to assess the lateral buckling response of a pipeline. The method is based on a Monte Carlo (MC) simulation in which the lateral buckling response is predicted through the use of a surrogate model that employs artificial neural networks (ANNs) calibrated from nonlinear finite element (FE) analyses. The method presented intends to improve on current industry best practice by directly considering the limit states relevant to global buckling to produce designs with consistent levels of reliability.

Static load test interpretation using the t-z model and LRFD resistance factors for auger cast-in-place (AC IP) and drilled displacement (DD) piles

Static load test data for augered cast-in-place (ACIP) and drilled displacement (DD) piles were interpreted using the <i>t-z</i> model method. Eighteen load tests consisting of load-settlement and load transfer data were obtained from two different construction sites. A series of back-calculations were performed using the <i>t-z</i> model method to enhance the static load test data, which were then analyzed to obtain resistance bias factors for the currently used ACIP and DD pile design methods. The <i>t-z</i> model method enhanced load test data provides the ability to interpret field data for loading conditions beyond those measured during test. The resistance bias for the various design methods were then used to obtain the resistance factors based upon the traditional calibration approach. Furthermore, resistance factors were also obtained using probabilistic analysis based upon the <i>t-z</i> model method. The comparison of these two sets of resistance factor indicates that those obtained from the traditional calibration approach contain a wide range of magnitudes, while the resistance factors from the <i>t-z</i> model method design result in a consistent level of reliability.

Uncertainty and Bias in Evaluation of LRFD Ultimate Limit State for Axially Loaded Driven Piles

AbstractSelection of resistance factors within Load and Resistance Factor Design (LRFD) requires accurate assessment of uncertainty and bias in load and resistance. To date, many studies have focused predominantly on the assessment of uncertainty, while the potential for bias appears to be the dominant factor in design for consistent levels of reliability under a variety of situations. Bias comes from factors which have been ignored in design method development but significantly influence resistance when extrapolating from conditions typical of databases to those at a given site. Uncertainty and bias can be quantified as the coefficient of variation and mean (or median) of a data set, respectively, for statistical assessment of load and resistance factors. This paper first presents an overview of statistical assessment of resistance factors, and then discusses factors that influence uncertainty and bias when extrapolating to situations outside of conventional databases of driven pile axial capacity.

Strength Model Uncertainties of Burst, Yielding, and Excessive Bending of Piping

Nuclear safety-piping is designed according to the ASME Boiler and Pressure Vessel Code, Sections III, NB-, NC-, and ND-3600 that use the allowable stress design method (ASD). The potential use instead of reliability-based design equations for nuclear piping could benefit the structural design by providing, among others, consistent reliability levels for piping. For the development of such equations, not only the probabilistic characteristics of the design variables are needed, but also the quantification of the uncertainties introduced by the strength models that are used in order to estimate the resistance of pipes subjected to different loadings. This paper evaluates strength models, and therefore provides necessary information for the reliability-based design of pipes for burst or yielding due to internal pressure and for excessive bending.

Reliability-Based Procedure for Developing Load and Resistance Factor Seismic Bridge Design Specifications

Load and resistance factor design (LRFD) codes are calibrated to produce designs with consistent and uniform levels of risk for the whole range of design applications. Ongoing research concerned with the development of LRFD seismic design specifications for bridges has concentrated on the application of seismic hazard analysis procedures to propose uniform hazard design spectra without directly addressing the contributions of the uncertainties in bridge response estimation and material properties to the overall risk of bridge failure. A proposed procedure includes the uncertainties associated with estimating the response of concrete bridge columns as represented by their response modification factors during the risk analysis of typical bridge columns. The effects of the random nature of the material properties and those of the modeling uncertainties on the risk and reliability of bridge columns are evaluated. This information, along with results from probabilistic seismic hazard analyses, is used in a comprehensive reliability analysis to calibrate a balanced set of response modification factors for the force-based design of bridge columns at a representative high-seismicity site in San Francisco, California. The implementation of such a reliability-based calibration of the response modification factors into future versions of the AASHTO bridge seismic specifications will ensure that the code will provide uniform and consistent levels of reliability for bridges of different configurations situated in various regions of the United States.

Assessment of Variable Uncertainties for Reliability-Based Design of Foundations

LRFD shows promise as a viable alternative to the present working stress design (WSD) approach to shallow foundation design. The key improvements of LRFD over the traditional WSD are the ability to provide a more consistent level of reliability and the possibility of accounting for load and resistance uncertainties separately. For LRFD to gain acceptance in geotechnical engineering, a framework for the objective assessment of resistance factors is needed. Such a framework, based on reliability analysis, is proposed in this paper. Probability density functions (PDFs), representing design variable uncertainties, are required for analysis. A systematic approach to the selection of PDFs is presented. A procedure such as that proposed provides a rational probabilistic basis for the development of LRFD methods in geotechnical engineering.

Resistance Factors for Use in Shallow Foundation LRFD

In shallow foundation design, the key improvements offered by LRFD over the traditional working stress design (WSD) are the ability to provide a more consistent level of reliability between different designs and the possibility of accounting for load and resistance uncertainties separately. In the development of LRFD, a framework for the objective, logical assessment of resistance factors is needed. Additionally, in order for LRFD to fulfill its promise for designs with more consistent reliability, the methods used to execute a design must be consistent with the methods assumed in the development of the LRFD factors. In this paper, a methodology for the estimation of soil parameters for use in design equations is proposed that should allow for more statistical consistency in design inputs than is possible in traditional methods. Resistance factors for ultimate bearing capacity are computed using reliability analysis for shallow foundations both in sand and in clay, with input parameters obtained from both the cone penetration test and the standard penetration test, and for both ASCE-7 2000 and AASHTO 1998 load factors. Resistance factor values are dependent upon the values of load factors used. Thus, a method to adjust the resistance factors to account for code-specified load factors is also presented.

Load and Resistance Factor Calibration For Wood Bridges

The paper presents the calibration procedure and background data for the development of design code provisions for wood bridges. The structural types considered include sawn lumber stringers, glued-laminated girders, and various wood deck types. Load and resistance parameters are treated as random variables, and therefore, the structural performance is measured in terms of the reliability index. The statistical parameters of dead load and live (traffic) load, are based on the results of previous studies. Material resistance is taken from the available test data, which includes consideration of the post-elastic response. The resistance of components and structural systems is based on the available experimental data and finite element analysis results. Statistical parameters of resistance are computed for deck and girder subsystems as well as individual components. The reliability analysis was performed for wood bridges designed according to the AASHTO Standard Specifications and a significant variation in reliability indices was observed. The recommended load and resistance factors are provided that result in consistent levels of reliability at the target levels.

Load Combination Factors for Extreme Events

The AASHTO load and resistance factor design (LRFD) specifications were developed with the use of a reliability-based calibration that covered the basic combination of dead load plus live load. The other load combinations were obtained from previous generations of specifications and the experience of bridge engineers and thus may not be consistent with the reliability methodology of the LRFD specifications. Work done as part of a recent NCHRP project to study in a systematic way the reliability of bridges under the combined effects of extreme load events and to develop a rational set of load combination factors consistent with the LRFD philosophy is described. The load events considered include live loads, seismic loads, wind loads, ship collision loads, and short-term scour. The analysis considered structural safety as well as foundation safety, and member safety was compared with system safety. The study recommended revisions to the AASHTO LRFD load combination factors and also calibrated new factors for combinations of events that include the presence of short-term scour. The calibration took into account previous experience with so-called safe bridge structures to provide acceptable and consistent levels of reliability.

Health-related quality of life in middle-aged African Americans.

In this article we explore the measurement properties of the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36) in 49- to 65-year-old African Americans, compare their health-related quality of life (HRQoL) with that of the nation, and evaluate the association of selected covariates with HRQoL. A probability sample of 998 African Americans in St. Louis received comprehensive in-home assessments. We used an item analysis, exploratory and confirmatory factor analysis, and internal consistency reliability to evaluate the measurement properties of the eight SF-36 scales and their interrelationships. We used a multiple linear regression analysis to characterize the effects of the demographic, socioeconomic status, psychosocial attributes, and biomedical markers. Assessments averaged 2.5 hr. Each SF-36 scale was unidimensional, all items had robust factor loadings, and all but one scale achieved excellent (alpha > or = .80) internal consistency reliability levels. The overall factor structure of the SF-36 scales was generally consistent with national norms. Substantial variance was explained by the covariates, mostly attributable to socioeconomic status and the biomedical markers. The SF-36 is a reliable and valid measure of HRQoL for use with African Americans. In this sample, the HRQoL was below national averages. Future social epidemiologic studies should include grip strength, vision, and hearing assessments, which had substantial and consistent associations with the SF-36 scale scores.

The development and administration of the Consumer Assessments of Care by New York State Office of Mental Health downstate facilities

This article reports on the work of the New York State Office of Mental Health Downstate Alliance, which is comprised of eight psychiatric centers that have formed a consortium to create new initiatives and solve common problems. The first of these initiatives are the inpatient and outpatient versions of the Consumer Assessments of Care, which assess satisfaction with care and quality of life (QOL). Consumers from peer run organizations who administered the survey used a mixed-mode administration method, which leveraged the strengths of the personal interview and anonymous self-report methods. Inpatients reported realistic levels of satisfaction and showed areas for improvement for inpatient units across facilities. Outpatients were considerably more satisfied with care, but ratings were lower on the work and community involvement dimensions of QOL. Factor analyses indicated that a one-factor model, satisfaction with care, fit the data well for the inpatient survey. A two-factor solution, satisfaction with care and QOL, was successfully fit to the outpatient data. Internal consistency reliability levels were excellent for both assessments.

Impact of FWD Testing Variability on Pavement Evaluations

Airfield pavement evaluations commonly include nondestructive testing. These evaluations are used for projecting pavement performance and for designing pavement rehabilitation options. To apply reliability concepts to these prediction and design scenarios, it is necessary to learn more about the variabilities associated with nondestructive testing and pavement evaluation procedures. In this study, twelve sites around the southeastern United States were tested with both a falling weight deflectometer and a heavy-weight deflectometer. The data were evaluated using the military procedure. The test data and the pavement evaluation results were examined for spatial variability and for test device variability. Two primary conclusions resulted from this study. The first primary conclusion is that the current military evaluation procedure does not provide a consistent level of reliability for evaluation results. The second primary conclusion is that the magnitude of the load used for deflectometer testing affects the evaluation results.

The Measurement of Family Perspectives on Extended School Year Practices with Students in Special Education

Although the provision of services beyond the traditional 180-day school year to students with disabilities-or extended school year (ESY) programs-has become a major national issue, there is a paucity of investigations designed to measure family perspectives on what ESY practices have been experienced and subsequently viewed as efficacious. The purpose of this study was to obtain validity and reliability indexes for scores on a 12-item scale developed as a result of a Louisiana consent decree that mandated the development and monitoring of guidelines for the provision of ESY services. Principal components analysis was conducted on the responses of 128 families that contained a member potentially eligible for ESY services. Results indicated that a two-component model was both valid and interpretable. Cronbach's alphas for total scale scores and the two components indicated acceptable internal consistency reliability levels.