Failure Time Research Articles

Sex Differences in 'Life's Essential 8' cardiovascular health and Type 2 Diabetes Mellitus Risk Across Menopause Stages.

The purpose of this paper is to explore sex-based differences in cardiovascular health (CVH) and the incidence of type 2 diabetes mellitus (T2DM) among women at different menopausal stages and men. A prospective cohort study was conducted, involving 126,818 participants without pre-existing T2DM from the UK Biobank. CVH was assessed using the Life's Essential 8. Absolute risks (ARs) and hazard ratios (HRs) were separately employed to assess the association between increased CVH and T2DM risk. The Accelerated Failure Time model assessed the impact of CVH on the time to T2DM onset. Over a mean follow-up of 168 months, 4,315 cases of T2DM were documented. In men, each one-point increase in CVH was associated with a 0.268% decrease in AR and a 6.4% decrease in HR for T2DM. In premenopausal, perimenopausal and postmenopausal women, each unit increase in CVH resulted in a 0.105%, 0.180% and 0.166% decrease in AR and a 7.7%, 5.2% and 6.4% decrease in HR of T2DM. The adjusted median time to T2DM onset was delayed by 12.46, 9.83, 11.5 and 21.43 months in the highest quintile of men, premenopausal, perimenopausal and postmenopausal women, respectively, compared with the lowest CVH quintile. As CVH improved, the reduction in AR for T2DM was more prominent in men than in women. HR trends for CVH and T2DM were similar in men and postmenopausal women. Increased CVH delayed the onset of T2MD in both men and women, with the most significant delay observed in postmenopausal women.

Probabilistic evaluation of failure time of reinforced concrete frame in post‐earthquake fire scenario

AbstractThis paper aims at assessing the failure time of a 7‐story reinforced concrete (RC) frame in a post‐earthquake fire (PEF) event probabilistically. Cumulative distribution functions (CDF) of the studied frame's failure time in various seismic load intensities have been calculated and presented with the aid of Monte Carlo analysis. Seismic load intensity, failure time, and failure probability are three parameters that are correlated through probabilistic analysis. The effects of cracking, spalling, and residual deformations resulted from the seismic load are considered in the strength of structure against the fire load. Seismic load intensity, materials properties, gravity load, and geometry are considered as random variables and one probabilistic analysis has been carried out for each seismic load intensity. The results have illustrated that in low seismic load intensities, probabilistic values of failure time in a structure subjected to pure fire load are equal to the one exposed to PEF. With the increase of seismic load intensity, the effects of cracking, spalling, and residual deformations would lead to a decline in the strength of structural elements against PEF scenario. The failure time in 50% failure probability for Sa = 0.2 g, Sa = 1 g, and Sa = 2 g intensities has been calculated as 14,300, 12,200, and 5100 s, respectively. The analysis results have shown that in an unspecified seismic load intensity, the failure time of the 7‐story RC frame for the 50% occurrence probability is equal to 9750 s.

Profit Comparison of Computer System with Hardware Redundancy Subject to Different Repair Activities

In this research paper, main concentrate of the authors on the profit comparison of computer system with hardware redundancy by introducing the concept of priority to software up-gradation, hardware preventive maintenance (PM) and hardware maximum repair time (MRT). The system fails independently from normal mode. All the repair activities such as hardware repair, software up-gradation, hardware preventive maintenance before failure and hardware replacement after maximum repair time are carried out by a single server immediately on need basis. All random variables are statistically independent. The negative exponential distribution is taken for the failure time of the component while the distributions of repair time, up-gradation time, preventive maintenance and replacement time are assumed arbitrary with different probability density functions. Semi-Markov process and regenerative point technique are used. The behaviour of profits of the system models have been examined for different parameters and costs.

Healthy worker hire and survivor effects in a cohort of medical radiation workers.

The healthy worker effect may distort the association between exposure and health effects in workers. However, few studies have investigated both the healthy worker hire and survival effects simultaneously, and they are limited to mortality studies in male workers. We utilized a data set comprising South Korean diagnostic medical radiation workers registered in the National Dose Registry between 1996 and 2011, and merged it with mortality and cancer incidence data. Standardized mortality ratios (SMRs) and standardized incidence ratios (SIRs) were computed for comparison with the general population. To account for time-varying confounders influenced by prior occupational radiation exposure, we applied g-estimation using structural nested accelerated failure time models and compared the outcomes with those from Weibull regression. A total of 1831 deaths and 3759 first primary cancer cases were identified among 93 918 workers. Both male (SMR = 0.44; 95% CI: 0.42, 0.46) and female workers (SMR = 0.53; 95% CI: 0.46, 0.60) showed lower mortality rates compared with national rates. In the SIR analysis, male workers exhibited reduced risks of solid cancer whereas female workers had increased risks. The g-estimation-derived hazard ratios (HRs) from radiation exposure exceeded those from Weibull regression estimates for all-cause death (HR = 2.55; 95% CI: 1.97, 3.23) and all-cancer incidence (HR = 1.96; 95% CI: 1.52, 2.55) in male workers whereas female workers showed the opposite results. Comprehensive consideration of the healthy worker effect by sex is essential for estimating the unbiased impact of occupational exposure on health outcomes, notably in studies focusing on male mortality.

Shaping of the risk of a series-parallel manufacturing structure maintenance according to quasi-coherence and the [formula omitted]-th survival value

The paper presents the authors’ model for determining the probability value of the survival function of the difference of two random variables: TP – the amount of time of correct operation and TB – the amount of time of failure. For this purpose, the concept of K-th survival value is introduced. The K-th survival value defines the probability that the total time of correct operation of the production system will be longer by at least k time units (for k≥0) than the total amount of time of failures. The model was exemplified by a real production system with a series–parallel structure. In the nesting manufacturing structure, the availability of machines determines the number and the type of flow streams of the processed material. To formalise the chains of relations at a given Δt, this paper utilises the quasi-coherence property. The paper identifies four possible cases of system operation: 1) a fully operational system in which every machine is capable of meeting the assumed production schedule; 2) a system which has lost the property of quasi-coherence (certain system objects are in an inoperable state) but it is possible to meet the assumed production schedule; 3) a system which has lost the property of quasi-coherence but the assumed task schedule is possible to meet after redefining the material flow streams; 4) a system which has lost the property of quasi-coherence and it is impossible to meet the assumed production schedule. Based on the definition of the survival function [1] S of the random variable T: ST:=PT>τ=1-FTτ,τ∈R, the concept of K-th survival value was introduced. For possible cases, K-th survival value was defined as: KT1,Ti=PT1-Ti≥k=1-FT1-Tik (for i=2,3,4), where T1 and Ti are random variables with given probability distributions. In turn, k is a deterministic value that determines the total number of time units of correct system operation in relation to the total failure time. The application of the developed algorithm enables the system to be analysed in terms of three aspects: (1) to determine the probability of on-time execution of tasks, taking into account historical values of machine failure and correct operation durations; (2) to determine the stability of the system based on empirical data; (3) to monitor the level of risk in real time. The paper validates the model by determining the stability of the analysed system for real machine failure data. The introduced criterion of stochastic stability of the production system has been verified for data in which distributions of correct operation times and failure times are random variables from the family of Gamma distributions. The presented model can be included in the group of multifactorial risk assessment methods.

AFFECT: an R package for accelerated functional failure time model with error-contaminated survival times and applications to gene expression data

BackgroundSurvival analysis has been used to characterize the time-to-event data. In medical studies, a typical application is to analyze the survival time of specific cancers by using high-dimensional gene expressions. The main challenges include the involvement of non-informaive gene expressions and possibly nonlinear relationship between survival time and gene expressions. Moreover, due to possibly imprecise data collection or wrong record, measurement error might be ubiquitous in the survival time and its censoring status. Ignoring measurement error effects may incur biased estimator and wrong conclusion.ResultsTo tackle those challenges and derive a reliable estimation with efficiently computational implementation, we develop the R package AFFECT, which is referred to Accelerated Functional Failure time model with Error-Contaminated survival Times.ConclusionsThis package aims to correct for measurement error effects in survival times and implements a boosting algorithm under corrected data to determine informative gene expressions as well as derive the corresponding nonlinear functions.

Investigating work-related distraction’s impact on male taxi driver safety: A hazard-based duration model

With the increasing use of phone-based ride-hailing apps, concerns have arisen regarding road safety and driver distraction. Despite the recognized safety risks of driver distraction, limited research has explored how distractions from various ride-hailing systems affect drivers in the taxi industry. To close this gap, the current research utilized a driving simulator experiment involving 51 male taxi drivers in two road environments (urban street and motorway) and three distracted driving conditions (no distraction, auditory distraction via radio dispatching system, and visual-manual distraction via mobile application). A car-following scenario with sudden brake events was incorporated into the experiments because this is a typical safety–critical situation where attention will determine the outcome. The collected performance indicators include brake reaction time, time headway, and car-following distance. The grouped random parameters Weibull accelerated failure time model was applied to model the duration data under different road conditions. The brake reaction time and time headway are dependent variables, while the car-following distance is a covariate in the models. The results indicate that although taxi drivers show longer brake reaction time when distracted by mobile app and radio system, this does not necessarily equate with greater risk or reduced safety since they compensate for the risk of rear-end crashes by maintaining a longer time headway. In general, taxi drivers’ brake reaction time and time headway are more profoundly affected by mobile apps when distracted in both urban and motorway scenarios. This highlights the elevated risks associated with such technologies. In addition, significant interaction effects revealed the observed heterogeneity, which suggests that drivers’ personal characteristics influence the relationship between distraction type and driving performance. This research provides valuable insights for designing safer ride-hailing operations and systems.

An Empirical Estimation of NCAA Head Football Coaches Contract Duration

Abstract While previous research on head coach dismissals finds that team performance and managerial characteristics impact employment survival, these studies ignore the impact of contract modifications. Using an accelerated failure time survival model with hand-collected college head football coach contract data, I find that race/ethnicity affects the hazard rate of contract modifications but not the hazard rate of a head coach’s dismissal. Additionally, analysis of employment duration ignoring contract modifications may result in erroneous conclusions with respect to the effect that race/ethnicity has on a head coach’s dismissal.

Imperfect maintenance modelling and estimation for interval-censored data

The paper proposes a new maintenance model for a repairable system. The system is inspected at deterministic times. If a failure occurs between two successive inspections, a minimal repair is performed. At inspection times, two types of maintenance actions can be performed. The first originality of the paper is to consider that the choice between these two types of maintenance depends on the fact that there has been a failure or not since the previous inspection. If no failure has occurred since the last inspection, the maintenance, simply denoted PM, corresponds to a basic preventive maintenance action, whose effect is planned by the initial maintenance plan. If at least one failure has occurred since the last inspection, the maintenance, denoted PCM, includes both the preventive action planned by the initial maintenance plan, and a specific corrective action which aims to fix the defects that have happened since the last inspection. Both types of maintenances are assumed to be imperfect, of the ARA (Arithmetic Reduction of Age) type, with different parameters. Moreover, the paper derives several statistical inference methods for this model. The usual case of complete data is first considered. The second originality of the paper is to analyse interval-censored data in this imperfect maintenance framework. This situation holds when failure times are not observed, and the only information is the fact that failures have occurred or not between two inspections. The quality of the proposed methods is assessed on simulated data. Finally, a real dataset from a gas transmission system operator is provided and analysed with the proposed approach.

How to Perform a Statistical Analysis of Non-Destructive Degradation Data to Study Crack Growth in Wind Blades as a Function of the Number of Cycles

Objective: The aim of this paper is to show the application of the Exponential Regression Model to study the failure time of a system over time. The data was taken from the paper (Wang et al., 2021). Theoretical framework: The linear regression model, where the response is associated with the explanatory variables by means of a linear model, is the best known. To formulate the model, it is necessary to specify a deterministic component and a random (stochastic) component. The exponential model should be used when it is assumed that risk is constant over time. Once the model has been specified, its parameters are estimated. In the absence of normal errors and especially in the presence of censoring, a more appropriate option is the maximum likelihood method. As the equations are non-linear in their parameters and do not have an analytical solution, it is necessary to use the Newton-Raphson numerical method. Due to the simplicity of the exponential regression model, few situations in practice are adequately adjusted by this model. The Weibull regression model is widely used in survival analysis (Bastos Lyra et al., 2008) Method: Data taken from the article (Wang et al., 2021) e foi utilizado a Regressão Exponencial para modelar os dados. Final Considerations: This result indicates that Exponential Regression is a very viable option when the aim is to monitor the number of cracks as a function of time to check whether a system will fail. In this specific Case Study, it is clear that one of the blades is better than the others and that there are some Probability Distribution models that are suitable for the model. Implications of the research: The use cases of Exponential Regression are more restricted in the scientific literature and because of this, this case study is interesting to show that this model is effective for treating data in the area of reliability. Originality/value: Despite being a well-known statistical tool, Exponential Regression has a specific application in monitoring the number of cracks over time in a system.

Improving estimation efficiency of case-cohort studies with interval-censored failure time data.

The case-cohort design is a commonly used cost-effective sampling strategy for large cohort studies, where some covariates are expensive to measure or obtain. In this paper, we consider regression analysis under a case-cohort study with interval-censored failure time data, where the failure time is only known to fall within an interval instead of being exactly observed. A common approach to analyzing data from a case-cohort study is the inverse probability weighting approach, where only subjects in the case-cohort sample are used in estimation, and the subjects are weighted based on the probability of inclusion into the case-cohort sample. This approach, though consistent, is generally inefficient as it does not incorporate information outside the case-cohort sample. To improve efficiency, we first develop a sieve maximum weighted likelihood estimator under the Cox model based on the case-cohort sample and then propose a procedure to update this estimator by using information in the full cohort. We show that the update estimator is consistent, asymptotically normal, and at least as efficient asthe original estimator. The proposed method can flexibly incorporate auxiliary variables to improve estimation efficiency. A weighted bootstrap procedure is employed for variance estimation. Simulation results indicate that the proposed method works well in practical situations. An application to a Phase 3 HIV vaccine efficacy trial is provided for illustration.

Assessment of loss of life owing to dam-failure flooding considering population distribution and evacuation

Dam failures pose a serious threat to the safety of downstream populations. Scientifically assessing loss of life (LOL) from dam-failure flooding contributes to the emergency response. Population distribution varies spatially and temporally even within a day, and has different information dissemination and response speeds, which impacts the chances of safe evacuation. This study established an LOL assessment model that considers the initial population distribution and population evacuation process. Shared bike big data and other multi-source data were used to identify daily population activity. The evacuation process includes receiving warnings, responses, and horizontal or vertical evacuation choices, and the evacuation results were then evaluated. This model was applied to a dam in China. During nighttime, commuting, and working hours, the issuance of warnings 214 min, 137 min, and 0 min prior to dam failure, respectively, significantly mitigated LOL. Under the same communication and response speeds, the commuting period poses the highest risk of LOL. Assessments of LOL due to dam failure flooding need to consider the impact of the timing of dam failure and population distribution. The model used in this study proposes varying effective early warning times based on the time of dam failure occurrence, which can contribute to effective dam risk management, helping prevent personnel loss.

Orthostatic Hypotension and Risk of Mild Cognitive Impairment and Dementia in Parkinson's Disease.

Orthostatic hypotension (OH) is a common condition in Parkinson's disease (PD) with a possible link to cognitive decline. The aim was to explore the association between OH and PD-associated mild cognitive impairment (PD-MCI) and dementia (PDD) over 9 years in a population-based incident PD cohort. We prospectively followed up patients from PD diagnosis with serial blood pressure measurements, clinical examinations, and neuropsychological assessments. We defined OH using (1) consensus-based criteria and (2) clinically significant OH by mean arterial pressure (MAP) in standing position ≤75 mmHg. PD-MCI and PDD were diagnosed according to acknowledged criteria. We applied generalized estimating equations models to investigate associations between OH measurements and cognitive impairment over time. Weibull accelerated failure time regression models were used to study if early OH (≤3 years of PD diagnosis) accelerates the time to incident PD-MCI and PDD. Of 186 enrolled patients, consensus-based OH affected 68.8%, clinically significant OH 33.9%, PD-MCI 60.8%, and PDD 31.2%. Consensus-based OH was associated with PD-MCI (odds ratio [OR]: 2.04, 95% confidence interval: 1.44-2.90, P < 0.001), whereas clinically significant OH was associated with both PD-MCI (OR: 1.95, 1.11-3.43, P = 0.020) and PDD (OR: 3.66, 1.95-6.86, P < 0.001). Early clinically significant OH, but not early consensus-based OH, reduced time to incident PD-MCI by 54% (P = 0.021) and time to PDD by 44% (P = 0.003) independently of potential confounders, including supine hypertension and cardiovascular disease. MAP in standing position emerged as a stronger predictor of cognitive decline than OH determined using consensus-based criteria. These findings have implications for both research and clinical practice.

Experimental investigations on the behaviour of structural-sized wood-CFRP composite beams in local fire

AbstractThe study involved combustion of 24 structural-sized beams under three-point bending subjected to substantial loading prior to ignition, reaching 90% of characteristic load-carrying capacity. A localised fire exposure zone was established proximal to the region experiencing the highest bending moment. The specimens were categorised into two groups: the first consisted of tituted by glued-laminated timber (B), and the second comprised wood-CFRP (carbon fibre reinforced polymer) composite (BW). Initial measurements encompassed pre-ignition static deflection and load. Subsequently, the specimens underwent controlled combustion, during which parameters including burning duration and deflection up to failure, were documented. Following cooling with sand, two cross-sectional slices were extracted from each fractured beam, enabling to find vector-based contours of the remaining cross-section. The charring rate and the approximate heat flux density for each test were determined, enabling a direct comparison of the results. A statistically significant number of specimens was examined, facilitating a comparative analysis between reinforced and unreinforced beams concerning failure time and form. Incorporating CFRP tapes among wooden constituents was found to increase the fire resistance of the structure, however, the thickness of the wooden material enveloping the CFRP composite emerges as a pivotal determinant. This issue needs thorough testing under standard fire in the future. Nevertheless, the fact is that adding CFRP tapes engenders a distinct form of beam collapse, transitioning from instantaneous cracking in B-beams to ductile failure in BW-beams.

Association between cytokines, nitric oxide, hemodynamic and microcirculation in a porcine model of sepsis

Systemic inflammation and hemodynamic or microvascular alterations are a hallmark of sepsis and play a role in organs hypoperfusion and dysfunction. Pimobendan, an inodilator agent, could be an interesting option for inotropic support and microcirculation preservation during shock. The objectives of this study were to evaluate effect of pimobendan on cytokine and nitric oxide (NO) release and investigate whether changes of macro and microcirculation parameters are associated with the release of cytokines and NO in pigs sepsis model. After circulatory failure, induced by intravenous inoculation of live Pseudomonas aeruginosa, eight animals were treated with pimobendan and eight with placebo.Pimobendan did not affect cytokines secretion (TNF-α, IL-6 and IL-10), but decreased time-dependently NO release. Data of macro and microcirculation parameters, NO and TNF- α recorded at the time of circulatory failure (Thypotension) and the time maximum of production cytokines was used for analyses. A positive correlation was observed between TNF-α and cardiac index (r = 0.55, p = 0.03) and a negative with systemic vascular resistance (r = −0.52, p = 0.04). Positive correlations were seen both between IL-10, 30 min after resuscitation (T30min), and systolic arterial pressure (r = 0.57, p = 0.03) and cardiac index (r = 0.67, p = 0.01), and also between IL-6, taken 2 h after resuscitation and systolic arterial pressure (r = 0.53, p = 0.04). Negative correlations were found between IL-10 and lactate, measured resuscitation time (r = −0.58, p = 0.03). Regarding microcirculation parameters, we observed a positive correlation between IL-6 and IL-10 with the microvascular flow index (r = 0.52, p = 0.05; r = 0.84, p = 0.0003) and a negative correlation with the heterogeneity index with TNF-α and IL-10 (r = −0.51, p = 0.05; r = −0.74, p = 0.003) respectively. NO derivatives showed a positive correlation with temperature gradient (r = 0.54, p = 0.04).Pimobendan did not show anti-inflammatory effects in cytokines release. Our results also, suggest changes of macro- and microcirculation are associated mainly with low levels of IL-10 in sepsis.

A hybrid reliability assessment method based on health index construction and reliability modeling for rolling bearing

AbstractThe assessment of rolling bearing reliability is vital for ensuring mechanical operational safety and minimizing maintenance costs. Due to the difficulty in obtaining data on the performance degradation and failure time of rolling bearings, traditional methods for reliability assessment are challenged. This paper introduces a novel hybrid method for the reliability assessment of rolling bearings, combining the convolutional neural network (CNN)‐convolutional block attention module (CBAM)‐ bidirectional long short‐term memory (BiLSTM) network with the Wiener process. The approach comprises three distinct stages: Initially, it involves acquiring two‐dimensional time‐frequency representations of bearings at various operational phases using Continuous Wavelet Transform. Subsequently, the CNN‐CBAM‐BiLSTM network is employed to establish health index (HI) for the bearings and to facilitate the extraction of deep features, serving as input for the Wiener process. The final stage applies the Wiener process to evaluate the bearings’ reliability, characterizing the HI and quantifying uncertainties. The experiment is performed on bearing degradation data and the results indicate the effectiveness and superiority of the proposed hybrid method.

Synergistic effects of graphene oxide, steel wire mesh and fibers on the impact resistance of preplaced aggregate concrete

Graphene Oxide (GO) has become a focal point of interest in civil engineering due to its exceptional mechanical and functional properties, making it a novel and promising carbon-based nanomaterial. However, the improvement in impact resistance of fibrous concrete by incorporating GO has not been explored until now. The novelty of this research is rooted in its pioneering analysis of the impact resistance of preplaced aggregate fibrous concrete, achieved through the combined incorporation of GO and steel wire mesh (SWM). This study uniquely investigates the effects of three different dosages of GO (0.1 %, 0.15 %, and 0.2 %) and three variations in the diameter of the steel wire mesh (50 mm, 100 mm, and 150 mm), alongside a fixed dosage of 3 % for steel fibers. Thirty-two distinct mixtures were prepared, with the steel wire mesh strategically placed at the midpoint of the specimen depth in each case. The specimens underwent drop-weight impact testing, with investigations conducted into their compressive strength, impact numbers related to cracking and failure, ductility index, and failure mode. The specimens incorporating a 0.2 % GO dosage with a 150 mm diameter of SWM displayed the highest observed cracking and failure impact numbers compared to those with 50 mm and 100 mm diameters of SWM. The observed increments ranged from 1.07 to 1.18 times for cracking and from 1.38 to 2.45 times for failure, compared to specimens containing 0.2 % GO without SWM. The identical specimens demonstrated the highest ductility values, ranging from 9.34 to 10.61. It is crucial to emphasize that adding GO does not induce an evolution from brittle to ductile failure of the specimen under impact loading, unlike the effect observed with steel wire mesh and steel fibre.

HIV-1 subtype-specific drug resistance on dolutegravir-based antiretroviral therapy: protocol for a multicentre study (DTG RESIST)

IntroductionHIV drug resistance poses a challenge to the United Nation’s goal of ending the HIV/AIDS epidemic. The integrase strand transfer inhibitor (InSTI) dolutegravir, which has a higher resistance barrier, was...

A complementary approach to quantify the basic GSI chart considering scale effect on rock structure

Geological strength index (GSI) has been widely used as an input parameter in predicting the strength and deformation properties of rock masses. This study derived a series of equations to satisfy the original GSI lines on the basic GSI chart. Two axes ranging from 0 to 100 were employed for surface conditions of the discontinuities and the structure of rock mass, which are independent of the input parameters. The derived equations can analyze GSI values ranging from 0 to 100 within ±5% error. The engineering dimensions (EDs) such as the slope height, tunnel width, and foundation width were used together with representative elementary volume (REV) in jointed rock mass to define scale factor (sf) from 0.2 to 1 in evaluating the rock mass structure including joint pattern. The transformation of GSI into a scale-dependent parameter based on engineering scale addresses a crucial requirement in various engineering applications. The improvements proposed in this study were applied to a real slope which was close to the time of failure. The results of stability assessments show that the new proposals have sufficient capability to define rock mass quality considering EDs.

Multi‐cohort survival of northern red oak seedlings at a northern hardwood forest transition

AbstractGlobal change has created less stable forest systems and given urgency to understanding limitations to the establishment of tree seedlings beyond current range boundaries. We quantified trends in 13 years of annual northern red oak (QURU) seedling survival data for 1733 marked individuals at a local species distribution boundary within the northern hardwood forest in New Hampshire, USA. Over the study period, the median distance of seedlings into the valley did not change, although there was a net gain of 89 plots (5 m2) occupied. For a subset of seedlings that were marked in their year of birth (N = 937), we examined relationships among terrain, vegetation community, and initial individual seedling traits, and evaluated their effects on time to seedling mortality using a parametric accelerated failure time model. The year of seedling germination had the largest effect on survival with increasing mortality rates for seedlings from more recent cohorts. Seedlings had longer survival times where oak seedling densities were lower, shrub cover was higher, and when the acorn remained attached. Additionally, survival time was increased in higher elevation plots, which were also located further into the valley. Interannual seedling survival (N = 1580) was strongly impacted by seedling condition in the previous year, particularly leaf number and amount of leaf damage. Most seedling deaths occurred over winter, and seedlings failed to break bud the following spring. Interannual variation in seasonal climate, particularly deep, heavy snowpack in 2019 followed by drought conditions in 2020, coincided with recent elevated mortality. Overall, the median survival time of 3–4 years and the rapid turnover of the oak seedling population currently limit ability for expansion, although the net gain of occupied plots and increase in survival at higher elevation plots with lower QURU densities present some mechanisms that could promote expansion if the current suboptimal understory conditions shift to favor QURU.