Adaptive age replacement.
Loss structure models concerning age replacement policies, discussing mathematical aspects of maintenance with dynamic programming formulation
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Loss structure models concerning age replacement policies, discussing mathematical aspects of maintenance with dynamic programming formulation
Thermal, mechanical, and physical properties have been measured on fiberboard samples following accelerated aging for up to 16 years. The aging environments include elevated temperature up to 250 ºF (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. Accelerated aging results have been analyzed and used to build aging models. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions, and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in K-Area Complex (KAC), these models allow development of service life predictions. KAC completed calculations that supported extending the service life of 9975 packages with 3013 and non3013 containers in storage from 15 years to 20 years. These calculations addressed the potential for degraded fiberboard properties following 20 years in storage using degradation models developed previously. The updated degradation models developed in this report have been compared to the assumptions in these calculations, and the current results for fiberboard dimensions, density, radial thermal conductivity, and energy absorption remain consistent with those calculations. The axial thermal conductivity degradation rate slightly exceeds calculations estimate of 0.5% per year between 130 and 160 °F. Additional data will continue to be collected to permit future refinements to the models and assumptions. Some of the predicted degradation rates presented in this report are extreme. However, these relate to environments that do not exist within KAC or would be postulated only as upset conditions that would not likely persist for an extended period. For a typical package stored in KAC with approximately 10-12 watts internal heat load or less, and ambient temperatures below 90 ºF, the fiberboard assemblies experience storage conditions less severe than any of the aging environments. Fiberboard in conforming packages with lower internal heat loads should experience little or no degradation and is expected to provide a service life beyond the currently approved 20 year storage period. Packages with higher internal heat loads may not continue to perform their required safety functions beyond 20 years. Ultimately, service life will be determined by the cumulative effect of degradation from all the conditions these packages might encounter. The results and model predictions presented in this report are applicable to 9975 packages with cane or softwood fiberboard overpack assemblies. These degradation models do not address the effects of nonconforming conditions such as the presence of excess moisture and mold or beetle infestations.
Thermal, mechanical, and physical properties have been measured on fiberboard samples following accelerated aging for up to 17 years. The aging environments include elevated temperature up to 250 °F (the maximum allowed service temperature for fiberboard in 9975 packages) and elevated humidity. Accelerated aging results have been analyzed and used to build aging models. Correlations relating several properties (thermal conductivity, energy absorption, weight, dimensions, and density) to their rate of change in potential storage environments have been developed. Combined with an estimate of the actual conditions the fiberboard experiences in K-Area Complex (KAC), these models allow development of service life predictions. KAC completed calculations that supported extending the service life of 9975 packages with 3013 containers in storage from 20 years to 40 years. These calculations addressed the potential for degraded fiberboard properties following 40 years in storage using degradation models developed previously. Due to differences in containers, 9975 packages with non-3013 containers are only approved for 20 years of storage. The updated degradation models developed in this report have been compared to the assumptions in those calculations, and the current results for fiberboard dimensions, density, radial thermal conductivity, and energy absorption remain consistent with those calculations. The axial thermal conductivity degradation rate slightly exceeds calculations estimate of 0.5% per year between 130 and 160 °F. Additional data will continue to be collected to permit future refinements to the models and assumptions. Some of the predicted degradation rates presented in this report are extreme. However, these relate to environments that do not exist within KAC or would be postulated only as upset conditions that would not likely persist for an extended period. For a typical package stored in KAC with approximately 10-12 watts internal heat load or less, and ambient temperatures below 90 °F, the fiberboard assemblies experience storage conditions less severe than any of the aging environments. Fiberboard in conforming packages with lower internal heat loads should experience little or no degradation and is expected to provide a service life beyond the currently approved 40 year storage period. Packages with higher internal heat loads may not continue to perform their required safety functions beyond 40 years. Ultimately, service life will be determined by the cumulative effect of degradation from all the conditions these packages might encounter. The results and model predictions presented in this report are applicable to 9975 packages with cane or softwood fiberboard overpack assemblies. These degradation models do not address the effects of non-conforming conditions such as the presence of excess moisture and mold or beetle infestations.
Contaminated recyclables, which are frequently discarded as waste, pose a significant challenge to the implementation of a circular economy. These contaminated recyclables impede the circulation of resources, resulting in higher processing costs at material recovery facilities (MRFs). Over the past few decades, machine learning (ML) models such as linear regression (LR), support vector machine (SVM), and random forest (RF) have evolved to provide new methods for predicting inbound contamination rates in addition to traditional statistical models. In this study, we applied ML models to predict inbound contamination rates using demographic features from 15 counties in the U.S. with different curbside collection strategies. In general, we found that ML models outperformed linear mixed models. Specifically, SVM models had the highest performance (R 2 = 0.75; mean absolute error (MAE) = 0.06), which may be due to their ability to model nonlinear relationships between features and inbound contamination rates. Further, the key predictor was population, with poverty rate being positively correlated and median age negatively correlated with inbound contamination rates. To improve the management of contamination and enhance the implementation of a circular economy, better models are needed to understand and estimate inbound contamination rates as well as identify critical factors in the present and future.
OBJECTIVES: We sought to develop and validate a model that estimates the risk of obstructive coronary artery disease in patients undergoing operations for mitral valve degeneration and to demonstrate its potential clinical utility. METHODS: A total of 722 patients (67% men; age, 61 +/- 12 years) without a history of myocardial infarction, ischemic electrocardiographic changes, or angina who underwent routine coronary angiography before mitral valve prolapse operations between 1989 and 1996 were analyzed. A bootstrap-validated logistic regression model on the basis of clinical risk factors was developed to identify low-risk (< or =5%) patients. Obstructive coronary atherosclerosis was defined as 50% or more luminal narrowing in one or more major epicardial vessels, as determined by means of coronary angiography. RESULTS: One hundred thirty-nine (19%) patients had obstructive coronary atherosclerosis. Independent predictors of coronary artery disease include age, male sex, hypertension, diabetes mellitus,and hyperlipidemia. Two hundred twenty patients were designated as low risk according to the logistic model. Of these patients, only 3 (1.3%) had single-vessel disease, and none had multivessel disease. The model showed good discrimination, with an area under the receiver-operating characteristic curve of 0.84. Cost analysis indicated that application of this model could safely eliminate 30% of coronary angiograms, corresponding to cost savings of $430,000 per 1000 patients without missing any case of high-risk coronary artery disease. CONCLUSION: A model with standard clinical predictors can reliably estimate the prevalence of obstructive coronary atherosclerosis in patients undergoing mitral valve prolapse operations. This model can identify low-risk patients in whom routine preoperative angiography may be safely avoided.
The frequency of stable chromosome aberrations (sCA) in lymphocytes is a recognized radiation biological dosimeter. Its analysis can provide insights into factors that affect individual susceptibility as well as into the adequacy of radiation dose estimates used in studies of atomic bomb survivors. We analyzed the relationship between atomic bomb radiation exposure using the most recent DS02R1 dose estimates and the frequency of sCA as determined by FISH in 1,868 atomic bomb survivors. We investigated factors that may affect the background sCA rate and the shape and magnitude of the dose response. As in previous analyses of sCA in atomic bomb survivors that were based on Giemsa staining methods and used older DS86 dose estimates, the relationship between radiation dose and sCA rate was significant (P < 0.0001) with a linear-quadratic relationship at lower doses that did not persist at higher doses. As before, age at the time of the bombing and type of radiation shielding were significant dose-effect modifiers (P < 0.0001), but in contrast the difference in dose response by city was not so pronounced (P = 0.026) with a city effect not evident at doses below 1.25Gy. Background sCA rate increased with age at the time of examination (P < 0.0001), but neither sex, city, nor smoking was significantly associated with background rate. Based on FISH methods and recent dosimetry, the relationship between radiation dose and sCA frequency is largely consistent with previous findings, although the lesser importance of city as an effect modifier may reflect better dosimetry as well as more reproducible scoring of sCA. The persisting difference in sCA dose response by shielding category points to remaining problems with the accuracy or precision of radiation dose estimates in some A-bomb survivors.
Biomass burning aerosol (BBA) from agricultural fires in southern Africa contributes about one-third of the global carbonaceous aerosol load. These particles have strong radiative effects in the southeast Atlantic (SEA), which depend in part on the radiative contrast between the aerosol layer in the free troposphere (FT) and the underlying cloud layer. However, there is large disagreement in model estimates of aerosol-driven climate forcing due to uncertainties in the vertical distribution, optical properties, and life cycle of these particles. This study applies a novel method combining remote sensing observations with regional model outputs to investigate the aging of the BBA and its impact on the optical properties during transatlantic transport from emission sources in Africa to the SEA. Results show distinct variations in extinction Ångström exponent (EAE) and single-scattering albedo (SSA) as aerosols age. Near the source, fresh aerosols are characterized by low mean SSA (0.84) and high EAE (1.85), indicating smaller, highly absorbing particles. By isolating marine contributions from the total column during BBA transport across the SEA, our analysis reveals an initial decrease in BBA absorptivity, with mean FT SSA of 0.87 after 6–7 d, followed by increased absorptivity with mean FT SSA of 0.84 after 10 d, suggesting enhanced absorption due to chemical aging. These findings indicate that BBA becomes more absorbing during extended transport across the SEA, with implications for reducing model uncertainties. Our remote-sensing-based results agree well with previous in situ studies and offer new insights into aerosol–radiation interactions and the energy balance over the SEA.
Available capacity, power, and cell conductance figure centrally into performance characterization of electrochemical cells (such as Li-ion cells) over their service life. For example, capacity loss in Li-ion cells is due to a combination of mechanisms, including loss of free available lithium, loss of active host sites, shifts in the potential-capacity curve, etc. Further distinctions can be made regarding irreversible and reversible capacity loss mechanisms. There are tandem needs for accurate interpretation of capacity at characterization conditions (cycling rate, temperature, etc.) and for robust self-consistent modeling techniques that can be used for diagnostic analysis of cell data as well as forecasting of future performance. Analogous issues exist for aging effects on cell conductance and available power. To address these needs, a modeling capability was developed that provides a systematic analysis of the contributing factors to battery performance loss over aging and to act as a regression/prediction platform for cell performance. The modeling basis is a summation of self-consistent chemical kinetics rate expressions, which as individual expressions each covers a distinct mechanism (e.g., loss of active host sites, lithium loss), but collectively account for the net loss of premier metrics (e.g., capacity) over time for a particular characterization condition. Specifically, sigmoid-based rate expressions are utilized to describe each contribution to performance loss. Through additional mathematical development another tier of expressions is derived and used to perform differential analyses and segregate irreversible versus reversible contributions, as well as to determine concentration profiles over cell aging for affected Li+ ion inventory and fraction of active sites that remain at each time step. Reversible fade components are surmised by comparing fade rates at fast versus slow cycling conditions. The model is easily utilized for predictive calculations so that future capacity performance can be estimated. The invention covers mathematical and theoretical frameworks, and demonstrates application to various Li-ion cells covering test periods that vary in duration, and shows model predictions well past the end of test periods. Version 2.0 Enhancements: the code now covers path-dependent aging scenarios, wherein the framework allows for arbitrarily-chosen aging conditions over a timeline to accommodate prediction of battery aging over a multiplicity of changing conditions. The code framework also allows for cell conductance and power loss evaluations over cell aging, analysis of series strings that contain a thermal anomaly (hot spot), and evaluation of battery thermal management parameters that impact battery lifetimes. Lastly, a comprehensive GUI now resides in the Ver. 2.0 code.
We study the host galaxy properties of the tidal disruption object Swift J164449.3+573451 using long-term optical to near-infrared (NIR) data. First, we decompose the galaxy surface brightness distribution and analyze the morphology of the host galaxy using high-resolution Hubble Space Telescope WFC3 images. We conclude that the host galaxy is bulge-dominant and well described by a single Sérsic model with Sérsic index n=3.43±0.05. Adding a disk component, the bulge to total host galaxy flux ratio (B/ T) is 0.83 ± 0.03, which still indicates a bulge-dominant galaxy. Second, we estimate multi-band fluxes of the host galaxy through long-term light curves. Our long-term NIR light curves reveal the pure host galaxy fluxes ∼500 days after the burst. We fit spectral energy distribution models to the multi-band fluxes from the optical to NIR of the host galaxy and determine its properties. The stellar mass, the star formation rate, and the age of the stellar population are log(M{sub ⋆}/M{sub ⊙})=9.14{sub −0.10}{sup +0.13}, 0.03{sub −0.03}{sup +0.28} M{sub ⊙} yr{sup −1}, and 0.63{sub −0.43}{sup +0.95} Gyr. Finally, we estimate the mass of the central super massive black hole which is responsible for the tidal disruption event. The black hole mass is estimated to be 10{sup 6.7±0.4} M{sub ⊙} from M{sub BH}–M{sub ⋆,bul} and M{sub BH}–L{sub bul} relations for the K band, although a smaller value of ∼10{sup 5} M{sub ⊙} cannot be excluded convincingly if the host galaxy harbors a pseudobulge.
Paleosols form when soils are buried through deposition by aeolian, colluvial, alluvial or other processes. Burial of former topsoil isolates soil organic matter (SOM) from surface conditions, allowing carbon to accumulate and potentially remain stable for millennia. In this study, SOM composition, distribution, and persistence were analyzed in the Brady Soil of Nebraska, USA to compare SOM spatial variability in modern and buried soils, as well as the impact of erosional exposure on SOM stability. The Brady Soil, formed as a surface soil during the Pleistocene-Holocene transition and now a paleosol buried up to 6 m deep (or more) by loess deposition during the Holocene, was sampled along burial (up to 5.8 m depth) and erosional (up to 1.8 m depth) transects to compare SOM dynamics in different geomorphic settings. Fourier Transform Infrared Spectroscopy (FTIR) and Fourier Transform ion cyclotron resonance mass spectrometry (FTICR-MS) were used to analyze SOM composition, while δ 13 C isotope analyses identified SOM sources and radiocarbon values were used to estimate turnover rates. Results confirmed a vegetation shift from C3 to C4 plants after Brady Soil formation, reflecting warming climatic conditions. Increasing SOM age and decreasing δ 13 C and δ 15 N values with depth indicated slowing of decomposition rate in buried soils. Higher pH in the Brady Soil suggested greater base cation content, supporting SOM stabilization through organo-mineral associations and aggregate formation. However, exposure of the Brady Soil due to surface erosion caused faster SOM turnover. This result suggested susceptibility of buried SOM to losses via decomposition upon erosional exposure, possibly accelerated by priming in response to modern SOM inputs. These findings highlight the potential loss of carbon stocks in buried soils under future climate change, as shifts in soil physicochemical properties may destabilize long-preserved SOM.
Purpose: Current National Comprehensive Cancer Network guidelines recommend postoperative radiation therapy (PORT) for patients with resected non-small cell lung cancer (NSCLC) with N2 involvement. We investigated the relationship between nodal stage and local-regional recurrence (LR), distant recurrence (DR) and overall survival (OS) for patients having an R0 resection. Methods and Materials: A multi-institutional database of consecutive patients undergoing R0 resection for stage I-IIIA NSCLC from 1995 to 2008 was used. Patients receiving any radiation therapy before relapse were excluded. A total of 1241, 202, and 125 patients were identified with N0, N1, and N2 involvement, respectively; 161 patients received chemotherapy. Cumulative incidence rates were calculated for LR and DR as first sites of failure, and Kaplan-Meier estimates were made for OS. Competing risk analysis and proportional hazards models were used to examine LR, DR, and OS. Independent variables included age, sex, surgical procedure, extent of lymph node sampling, histology, lymphatic or vascular invasion, tumor size, tumor grade, chemotherapy, nodal stage, and visceral pleural invasion. Results: The median follow-up time was 28.7 months. Patients with N1 or N2 nodal stage had rates of LR similar to those of patients with N0 disease, but were at significantly increased risk for both DR (N1, hazard ratio [HR] = 1.84, 95% confidence interval [CI]: 1.30-2.59; P=.001; N2, HR = 2.32, 95% CI: 1.55-3.48; P<.001) and death (N1, HR = 1.46, 95% CI: 1.18-1.81; P<.001; N2, HR = 2.33, 95% CI: 1.78-3.04; P<.001). LR was associated with squamous histology, visceral pleural involvement, tumor size, age, wedge resection, and segmentectomy. The most frequent site of LR was the mediastinum. Conclusions: Our investigation demonstrated that nodal stage is directly associated with DR and OS but not with LR. Thus, even some patients with, N0-N1 disease are at relatively high risk of local recurrence. Prospective identification of risk factors for local recurrence may aid in selecting an appropriate population for further study of postoperative radiation therapy.
The respiratory disease COVID-19 reached global pandemic status in 2020. Excessive inflammation is believed to result in the most severe symptoms and death from this disease. Because treatment options for patients with severe COVID-19 related pulmonary symptoms remain limited, whole-lung low-dose radiation therapy is being evaluated as an anti-inflammatory modality. However, there is concern about the long-term risks associated with low-dose pulmonary irradiation. To help quantify the benefit-risk balance of low-dose radiation therapy for COVID-19, we estimated radiation-induced lifetime risks of both lung cancer and heart disease (major coronary events) for patients of different sexes, treated at ages 50 to 85, with and without other relevant risk factors (cigarette smoking and baseline heart disease risk).
We present spatially resolved kinematics and global stellar populations and mass-to-light ratios for a sample of 39 dwarf early-type (dE) galaxies in the Virgo cluster studied as part of the SMAKCED stellar absorption-line spectroscopy and imaging survey. This sample is representative of the early-type population in the Virgo cluster in the absolute magnitude range –19.0 < M{sub r} < –16.0 and of all morphological subclasses found in this galaxy population. For each dE, we measure the rotation curve and velocity dispersion profile and fit an analytic function to the rotation curve. We study the significance of the departure of the rotation curve from the best-fit analytic function (poorly fit) and of the difference between the approaching and receding sides of the rotation curve (asymmetry). Our sample includes two dEs with kinematically decoupled cores that have been previously reported. We find that 62 ± 8% (23 out of the 39) of the dEs have a significant anomaly in their rotation curve. Analysis of the images reveals photometric anomalies for most galaxies. However, there is no clear correlation between the significance of the photometric and kinematic anomalies. We measure age-sensitive (H{sub β} and H{sub γA}) and metallicity sensitive (Fe4668 and Mgb) Lick spectral indices in the LIS-5 Å system. This population of galaxies exhibits a wide range of ages and metallicities; we also find that 4 dEs show clear evidence of emission partially filling in the Balmer absorption lines. Finally, we estimate the total masses and dark matter fractions of the dEs and plot them in the mass-size, the mass-velocity dispersion, and the fundamental plane scaling relations. The dEs seem to be the bridge between massive early-type galaxies and dSphs, and have a median total mass within the R{sub e} of log M{sub e} = 9.1 ± 0.2 and a median dark matter fraction within the R{sub e} of f {sub DM} = 46 ± 18%. Any formation model for the dE galaxy class must account for this diversity of kinematic and photometric anomalies and stellar populations.
The asteroseismology of evolved solar-like stars is experiencing growing interest due to the wealth of observational data from space-borne instruments such as the CoRoT and Kepler spacecraft. In particular, the recent detection of mixed modes, which probe both the innermost and uppermost layers of stars, paves the way for inferring the internal structure of stars along their evolution through the subgiant and red giant phases. Mixed modes can also place stringent constraints on the physics of such stars and on their global properties (mass, age, etc.). Here, using two Kepler stars (KIC 4351319 and KIC 6442183), we demonstrate that measurements of mixed mode characteristics allow us to estimate the mode inertias, providing a new and additional diagnostics on the mode trapping and subsequently on the internal structure of evolved stars. We however stress that the accuracy may be sensitive to non-adiabatic effects.
Progress in solar energy technology is reported in the following areas: aging and life prediction methodology and devices for solar cell encapsulation; the function of adhesion chemistry, primers, and a new diagnostic technique for estimations of bond durability; a study of fire retardant formulations for decreasing the potential flammability of solar modules; initial studies of the electrical insulating properties of encapsulation materials and measurement of the intrinsic dielectric strength; antisoiling compounds for the prevention of soil build-up on the outer surface of the module; and low temperature processing encapsulants that permit module fabrication at temperatures less than 100 C. Another area of study has been added to determine the degree to which formulation and processes affect the module quality and manufacturing yield.
Report discusses relationship between degree of development of waves and sea-state bias in radar altimetry. Purpose of study to increase accuracy of estimates of sea-state bias and thereby increase accuracy of estimates of sea level obtained if waves at measurement spot suppressed. Study shows sea-state bias related to parameter called "pseudo wave age."
When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.
STUDY OBJECTIVES: To determine whether wrist actigraphy is useful as a tool for space-based sleep research. Specifically, to determine whether bedtimes and waketimes can be identified from the actigraphic record, and whether actigraphic measures of sleep in space are related to polysomnographic (PSG) ones. DESIGN AND SETTING: Actigraphy, sleep diary, and Polysomnographic (PSG) measures of sleep were obtained from four subjects in two 72h measurement blocks occurring 2d and 12d into a 17d Space Shuttle mission in orbiting the earth in microgravity. PATIENTS: Four healthy male astronauts aged 38y - 47y. INTERVENTIONS: NA. MEASUREMENTS AND RESULTS: Sleep onset and offset at "night" could be quite clearly identified from the actigraphic record and were better estimated by actigraph than by diary. There was a high correlation between actigraphic and PSG estimates of sleep duration (r = 0.96) and sleep efficiency (r = 0.88), and a similarity in the mean estimates obtained. On a minute-by-minute basis, there was a good correlation between sleep stage and actigraphic movement counts, with a higher level of counts per minute recorded in epochs with lighter PSG sleep stages. There was also a high correlation (r = 0.90) between minutes of stage 0 (wake) occurring between bedtime and wake time, and number of non-zero actigraph epochs during the same interval. CONCLUSIONS: Actigraphy worked well in space both as a way of detecting bedtimes and waketimes, and as an indicant of sleep restlessness.