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At least 109 records · Page 6

Turn Your Half-Cut Cells for a Stronger Module

Here, we employ an existing model of crystalline silicon photovoltaic module cell fracture to explore the effect of cell size and orientation on their probability of fracture under module uniform loading. In addition, we also apply continuum damage mechanics to modify this model to consider the effect of cell fracture on the probability of subsequent cell fracture. We elucidate that cell fracture increases the probability of subsequent cell fracture and that rectangular modules containing half-cells aligned with the module's long orientation are much more robust against cell fracture than full-cell and half-cell short orientation modules.

14 SOLAR ENERGY↗

Inferring Reliability Model Parameters from Expert Opinion

Here, we propose a method for constructing bathtub models of reliability from opinion. The method is intended for reliability studies early in the design and prototyping of a new system, before data concerning reliability has become available. A stylized bathtub curve is presented for soliciting best engineering judgement from technical experts. By pooling these stylized curves, we produce data that can be used to infer parameters for a piece-wise Weibull model of reliability. A numerical example demonstrates the practicality of the method while also highlighting potential pitfalls when working with subjective data.

42 ENGINEERING↗

Program For Evaluation Of Reliability Of Ceramic Parts

CARES/LIFE predicts probability of failure of monolithic ceramic component as function of service time. Assesses risk that component fractures prematurely as result of subcritical crack growth (SCG). Effect of proof testing of components prior to service also considered. Coupled to such commercially available finite-element programs as ANSYS, ABAQUS, MARC, MSC/NASTRAN, and COSMOS/M. Also retains all capabilities of previous CARES code, which includes estimation of fast-fracture component reliability and Weibull parameters from inert strength (without SCG contributing to failure) specimen data. Estimates parameters that characterize SCG from specimen data as well. Written in ANSI FORTRAN 77 to be machine-independent. Program runs on any computer in which sufficient addressable memory (at least 8MB) and FORTRAN 77 compiler available. For IBM-compatible personal computer with minimum 640K memory, limited program available (CARES/PC, COSMIC number LEW-15248).

Nemeth, N.↗

Joint Modeling of Wind Speed and Wind Direction Through a Conditional Approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work, we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction, a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms two other approaches in estimation efficiency: one that utilizes periodic spline quantile regression and another that generates data from the commonly used Abe-Ley distribution for cylindrical data. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios. Our method indicates significant changes in the variation of wind speed with respect to some directions.

17 WIND ENERGY↗

Integrating high resolution drone imagery and forest inventory to distinguish canopy and understory trees and quantify their contributions to forest structure and dynamics

Tree growth and survival differ strongly between canopy trees (those directly exposed to overhead light), and understory trees. However, the structural complexity of many tropical forests makes it difficult to determine canopy positions. The integration of remote sensing and ground-based data enables this determination and measurements of how canopy and understory trees differ in structure and dynamics. Here we analyzed 2 cm resolution RGB imagery collected by a Remotely Piloted Aircraft System (RPAS), also known as drone, together with two decades of bi-annual tree censuses for 2 ha of old growth forest in the Central Amazon. We delineated all crowns visible in the imagery and linked each crown to a tagged stem through field work. Canopy trees constituted 40% of the 1244 inventoried trees with diameter at breast height (DBH) > 10 cm, and accounted for ~70% of aboveground carbon stocks and wood productivity. The probability of being in the canopy increased logistically with tree diameter, passing through 50% at 23.5 cm DBH. Diameter growth was on average twice as large in canopy trees as in understory trees. Growth rates were unrelated to diameter in canopy trees and positively related to diameter in understory trees, consistent with the idea that light availability increases with diameter in the understory but not the canopy. The whole stand size distribution was best fit by a Weibull distribution, whereas the separate size distributions of understory trees or canopy trees > 25 cm DBH were equally well fit by exponential and Weibull distributions, consistent with mechanistic forest models. The identification and field mapping of crowns seen in a high resolution orthomosaic revealed new patterns in the structure and dynamics of trees of canopy vs. understory at this site, demonstrating the value of traditional tree censuses with drone remote sensing.

59 BASIC BIOLOGICAL SCIENCES↗

Probability Distribution Estimated From the Minimum, Maximum, and Most Likely Values: Applied to Turbine Inlet Temperature Uncertainty

Modern engineering design practices are tending more toward the treatment of design parameters as random variables as opposed to fixed, or deterministic, values. The probabilistic design approach attempts to account for the uncertainty in design parameters by representing them as a distribution of values rather than as a single value. The motivations for this effort include preventing excessive overdesign as well as assessing and assuring reliability, both of which are important for aerospace applications. However, the determination of the probability distribution is a fundamental problem in reliability analysis. A random variable is often defined by the parameters of the theoretical distribution function that gives the best fit to experimental data. In many cases the distribution must be assumed from very limited information or data. Often the types of information that are available or reasonably estimated are the minimum, maximum, and most likely values of the design parameter. For these situations the beta distribution model is very convenient because the parameters that define the distribution can be easily determined from these three pieces of information. Widely used in the field of operations research, the beta model is very flexible and is also useful for estimating the mean and standard deviation of a random variable given only the aforementioned three values. However, an assumption is required to determine the four parameters of the beta distribution from only these three pieces of information (some of the more common distributions, like the normal, lognormal, gamma, and Weibull distributions, have two or three parameters). The conventional method assumes that the standard deviation is a certain fraction of the range. The beta parameters are then determined by solving a set of equations simultaneously. A new method developed in-house at the NASA Glenn Research Center assumes a value for one of the beta shape parameters based on an analogy with the normal distribution (ref.1). This new approach allows for a very simple and direct algebraic solution without restricting the standard deviation. The beta parameters obtained by the new method are comparable to the conventional method (and identical when the distribution is symmetrical). However, the proposed method generally produces a less peaked distribution with a slightly larger standard deviation (up to 7 percent) than the conventional method in cases where the distribution is asymmetric or skewed. The beta distribution model has now been implemented into the Fast Probability Integration (FPI) module used in the NESSUS computer code for probabilistic analyses of structures (ref. 2).

Holland, Frederic A., Jr.↗

A method for developing design diagrams for ceramic and glass materials using fatigue data

The service lifetime of glass and ceramic materials can be expressed as a plot of time-to-failure versus applied stress whose plot is parametric in percent probability of failure. This type of plot is called a design diagram. Confidence interval estimates for such plots depend on the type of test that is used to generate the data, on assumptions made concerning the statistical distribution of the test results, and on the type of analysis used. This report outlines the development of design diagrams for glass and ceramic materials in engineering terms using static or dynamic fatigue tests, assuming either no particular statistical distribution of test results or a Weibull distribution and using either median value or homologous ratio analysis of the test results.

Heslin, T. M.↗

Cracked Gridline Wear Out Follows a Power Law

Cracks can form in Silicon solar cells in photovoltaic modules due to mechanical stresses arising from various extrinsic factors like handling and weather. While the immediate performance degradation may be minor, continuous loading overtime will degrade module performance. One probable reason is gridline surface wear across the cracked silicon with increased cyclic loading. In this work we propose a method to correlate gridline wear to module electrical degradation. We begin by conducting cyclic four-point bending tests on laminated silicon solar cells with a single crack and 22 intact gridlines for 10,000 cycles. We measure the progressive change in resistance during each loading cycle. We correlate it to a length scale called critical crack opening displacement (CCOD) that signifies failure of individual gridlines. By employing Weibull analysis, we determine the characteristic CCOD for all cycles and fit this data to a modified version of a wear power law. We observe that this i ts the data well. We also propose to study the effect of individual parameters in the power law equation and extend the equation to include material properties.

bending↗

Initial development of a high temperature life prediction method directly accounting for variability in material properties

This report presents the initial development of a life prediction method that accounts for the variability of the material properties in Grade 91 steel. We account for material variability by both fitting a variable 3-parameter Weibull distribution to the rupture data of the material and by quantifying the effect that the creep deformation properties have on stresses via a Monte Carlo approach. To ensure a reasonable time frame when applying Monte Carlo to the creep stress, we propose a methodology that models the material as an extremely viscous Stokes flow with a non-Newtonian viscosity, therefore solving the problem in a single step. We use the final probabilistic model for structural failure developed in this document to evaluate a Flat Head Vessel designed with the Section III, Division 5 ASME Boiler Pressure and Vessel Code rules with a 100,000h design life and assess its probability of premature failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Flight inspection data and crack initiation times

Lockheed C-130 service-flight inspection data is reduced by means of fracture mechanics and statistical analysis into a form from which the probability of time to crack initiation and the distribution of initial flaw sizes for various locations on the aircraft can be determined. Crack sizes are normalized by extrapolating a growing crack backwards from its first recorded size to .03 inches (crack initiation size) yielding the time to crack initiation. In a similar fashion, the crack is grown backwards to a time equal to zero to yield an initial flaw size. In order to perform the discussed computations, crack growth constants were computed for each individual location and were analyzed statistically. Statistical distributions were fitted to times to crack initiation and to initial flaw sizes in order to describe their expected behavior. Weibull and Johnson distributions have been found to fit the data reasonably well but for a better fit convolution integrals of Poisson load distributions and Weibull strength distributions are needed.

Johnson, W. S.↗

Lifetime Reliability Prediction of Ceramic Structures Under Transient Thermomechanical Loads

An analytical methodology is developed to predict the probability of survival (reliability) of ceramic components subjected to harsh thermomechanical loads that can vary with time (transient reliability analysis). This capability enables more accurate prediction of ceramic component integrity against fracture in situations such as turbine startup and shutdown, operational vibrations, atmospheric reentry, or other rapid heating or cooling situations (thermal shock). The transient reliability analysis methodology developed herein incorporates the following features: fast-fracture transient analysis (reliability analysis without slow crack growth, SCG); transient analysis with SCG (reliability analysis with time-dependent damage due to SCG); a computationally efficient algorithm to compute the reliability for components subjected to repeated transient loading (block loading); cyclic fatigue modeling using a combined SCG and Walker fatigue law; proof testing for transient loads; and Weibull and fatigue parameters that are allowed to vary with temperature or time. Component-to-component variation in strength (stochastic strength response) is accounted for with the Weibull distribution, and either the principle of independent action or the Batdorf theory is used to predict the effect of multiaxial stresses on reliability. The reliability analysis can be performed either as a function of the component surface (for surface-distributed flaws) or component volume (for volume-distributed flaws). The transient reliability analysis capability has been added to the NASA CARES/ Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. CARES/Life was also updated to interface with commercially available finite element analysis software, such as ANSYS, when used to model the effects of transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

Nemeth, Noel N.↗

Stress and Reliability Analysis of a Metal-Ceramic Dental Crown

Interaction of mechanical and thermal stresses with the flaws and microcracks within the ceramic region of metal-ceramic dental crowns can result in catastrophic or delayed failure of these restorations. The objective of this study was to determine the combined influence of induced functional stresses and pre-existing flaws and microcracks on the time-dependent probability of failure of a metal-ceramic molar crown. A three-dimensional finite element model of a porcelain fused-to-metal (PFM) molar crown was developed using the ANSYS finite element program. The crown consisted of a body porcelain, opaque porcelain, and a metal substrate. The model had a 300 Newton load applied perpendicular to one cusp, a load of 30ON applied at 30 degrees from the perpendicular load case, directed toward the center, and a 600 Newton vertical load. Ceramic specimens were subjected to a biaxial flexure test and the load-to-failure of each specimen was measured. The results of the finite element stress analysis and the flexure tests were incorporated in the NASA developed CARES/LIFE program to determine the Weibull and fatigue parameters and time-dependent fracture reliability of the PFM crown. 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.

Anusavice, Kenneth J↗

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗

Determination of Turbine Blade Life from Engine Field Data

It is probable that no two engine companies determine the life of their engines or their components in the same way or apply the same experience and safety factors to their designs. Knowing the failure mode that is most likely to occur minimizes the amount of uncertainty and simplifies failure and life analysis. Available data regarding failure mode for aircraft engine blades, while favoring low-cycle, thermal mechanical fatigue as the controlling mode of failure, are not definitive. Sixteen high-pressure turbine (HPT) T-1 blade sets were removed from commercial aircraft engines that had been commercially flown by a single airline and inspected for damage. Each set contained 82 blades. The damage was cataloged into three categories related to their mode of failure: (1) Thermal-mechanical fatigue, (2) Oxidation/Erosion, and (3) "Other." From these field data, the turbine blade life was determined as well as the lives related to individual blade failure modes using Johnson-Weibull analysis. A simplified formula for calculating turbine blade life and reliability was formulated. The L(sub 10) blade life was calculated to be 2427 cycles (11 077 hr). The resulting blade life attributed to oxidation/erosion equaled that attributed to thermal-mechanical fatigue. The category that contributed most to blade failure was Other. If there were there no blade failures attributed to oxidation/erosion and thermal-mechanical fatigue, the overall blade L(sub 10) life would increase approximately 11 to 17 percent.

Zaretsky, Erwin V.↗

Determination of Turbine Blade Life from Engine Field Data

It is probable that no two engine companies determine the life of their engines or their components in the same way or apply the same experience and safety factors to their designs. Knowing the failure mode that is most likely to occur minimizes the amount of uncertainty and simplifies failure and life analysis. Available data regarding failure mode for aircraft engine blades, while favoring low-cycle, thermal-mechanical fatigue (TMF) as the controlling mode of failure, are not definitive. Sixteen high-pressure turbine (HPT) T-1 blade sets were removed from commercial aircraft engines that had been commercially flown by a single airline and inspected for damage. Each set contained 82 blades. The damage was cataloged into three categories related to their mode of failure: (1) TMF, (2) Oxidation/erosion (O/E), and (3) Other. From these field data, the turbine blade life was determined as well as the lives related to individual blade failure modes using Johnson-Weibull analysis. A simplified formula for calculating turbine blade life and reliability was formulated. The L10 blade life was calculated to be 2427 cycles (11 077 hr). The resulting blade life attributed to O/E equaled that attributed to TMF. The category that contributed most to blade failure was Other. If there were no blade failures attributed to O/E and TMF, the overall blade L(sub 10) life would increase approximately 11 to 17 percent.

Zaretsky, Erwin V.↗

Dynamic Fatigue of ULE Glass

Ultra Low Expansion (ULE) glass is used in a number of applications which require a low thermal expansion coefficient. One such application is telescope mirror elements. An allowable stress can be calculated for this material based upon modulus of rupture data; however, this does not take into account the problem of delayed failure. Delayed failure, due to stress corrosion can significantly shorten the lifetime of a glass article. Knowledge of the factors governing the rate of subcritical flaw growth in a given environment enables the development of relations between lifetime, applied stress and failure probability for the material under study. Dynamic fatigue is one method of obtaining the necessary information to develop these relationships. In this study, the dynamic fatigue method was used to construct time-to-failure diagrams for both 230/270 ground and optically polished samples. The grinding and polishing process reduces the surface flaw size and subsurface damage, and relieves residual stress by removing materials with successively smaller grinding media. This resulted in an increase in the strength of the optic during the grinding and polishing sequence. There was also an increase in the lifetime due to grinding and polishing. It was found that using the fatigue parameters determined from the 230/270 grit surface are not significantly different from the optically polished values. Although the lower bound of the polished samples is more conservative, neither time-to-failure curves lie beyond the upper or lower bound of the confidence limits. Therefore, designers preferring conservative limits could use samples without residual stress present (polished samples) to determine the fatigue parameters and inert Weibull parameters from samples with the service condition surface, to determine time-to-failure of the optical element.

Tucker, Dennis S.↗

HEPA Filter Age Evaluation Report

In 2020, PNNL completed a literature search for high-efficiency particulate air (HEPA) filter age information. HEPA filters are used in many operations to remove particulate matter from effluent exhaust streams. They are thought to degrade over time both during proper storage and during normal operational service; however, the rate at which the filters degrade remains unknown. This brings into question if age is an adequate indicator of HEPA filter performance. Data from six previous reports were obtained from the literature search and combined to create a data set of 1600 operating filters. Filter usage was identified from multiple facilities. The various types of filters (e.g., axial flow, self-contained, and standard 24 x 24 x 11.5 inches; and both separator and separatorless) reported were constructed to the requirements Section FC (HEPA Filters) or Section FK (Special HEPA Filters) of the American Society of Mechanical Engineers AG-1 code. Filters were presumed to have continuously met the operational criteria and in particular passed both annual efficiency tests and annual DP measurements. The environmental conditions within the exhaust system were also assumed adequate for long-term filter operation. The data, by the nature of the reports, excludes rejected filters from quality assurance evaluations, intake, or installation testing. The collective data set shows over half of were operating past the current 10-year Department of Energy (DOE) limit. Data was evaluated for age lifetime using a linear trendline, survival function, probability functions, and failure rate; financial impacts were also addressed. This report supports the notion that HEPA filters can operate safely and efficiently under proper maintenance well past the 10-year lifetime established by DOE. Using the results of the four age evaluation approaches, they collectively point to the reasonableness of an operating HEPA filter lifetime of 20 years. The results are not necessarily definitive, but nevertheless, they are promising. The analysis provides reasonable assurance that when implemented using a graded approach with well-defined performance and operational requirements, extending the service life for HEPA filters beyond 10 years is low risk.

42 ENGINEERING↗

Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)

The characterization of wind speed distribution and the optimal assessment of wind energy potential are critical factors in selecting a suitable site for wind power plants (WPP). The Weibull distribution law has been used extensively to analyze the wind characteristics of candidate WPP sites, and to estimate the available and deliverable energy. This paper presents a comparative study of five wind energy resource assessment methods as they applied to the context of wind sites in West Sub-Saharan Africa. We investigated three numerical approaches, namely, the adaptive neuro-fuzzy inference system (ANFIS), the multilayer perceptron method (MLP), and support vector regression (SVR), to derive the distribution law of wind speeds and to optimally quantify the corresponding wind energy potential. Next, we compared these three approaches to two well-known Weibull distribution law-based methods: the empirical method of Justus (EMJ) and the maximum likelihood method (MLM). Case study results indicated that the neural network-based methods, ANFIS and MLP, yielded the most accurate distribution fits and wind energy potential estimates, and consequently, are the most recommended methods for the wind sites in Togo and Benin. The orders of magnitude of the root mean squared error (RMSE) in estimating the recoverable energy using ANFIS were, respectively, 10-4 and 10-5 for Lomé and Cotonou, while MLP achieved an RMSE order of magnitude of 10-3 for both sites.

17 WIND ENERGY↗