Global Sensitivity Analysis (GSA) is key to assisting appraisal of the behavior of hydrological systems through model diagnosis considering multiple sources of uncertainty. Uncertainty sources ...typically comprise incomplete knowledge in (a) conceptual and mathematical formulation of models and (b) parameters embedded in the models. In this context, there is the need for detailed investigations aimed at a robust quantification of the importance of model and parameter uncertainties in a rigorous multi‐model context. This study aims at evaluating and comparing two modern multi‐model GSA methodologies. These are the first GSA approaches embedding both model and parameter uncertainty sources and encompass the variance‐based framework based on Sobol indices (as derived by Dai & Ye, 2015, https://doi.org/10.1016/j.jhydrol.2015.06.034) and the moment‐based approach upon which the formulation of the multi‐model AMA indices (as derived by Dell'Oca et al., 2020, https://doi.org/10.1029/2019wr025754) is based. We provide an assessment of various aspects of sensitivity upon considering a joint analysis of these two approaches in a multi‐model context. Our work relies on well‐established scenarios that comprise (a) a synthetic setting related to reactive transport across a groundwater system and (b) an experimentally‐based study considering heavy metal sorption onto a soil. Our study documents that the joint use of these GSA approaches can provide different while complementary information to assess mutual consistency of approaches and to enrich the information content provided by GSA under model and parameter uncertainty. While being related to groundwater settings, our results can be considered as reference for future GSA studies coping with model and parameter uncertainty.
Key Points
Two modern multi‐model Global Sensitivity Analysis (GSA) approaches are evaluated and compared upon considering two groundwater‐related scenarios
The results of the two multi‐model GSA methods can be markedly different due to their differing theoretical bases
Joint use of the two GSA methods enhances one's ability for model diagnosis and assessment of system behaviors
Abstract This research analyzes the adverse impact of white noise on collective quantum measurements and argues that such noise poses a significant obstacle for the otherwise straightforward ...deployment of collective measurements in quantum communications. Our findings then suggests addressing this issue by correlating outcomes of these measurements with quantum state purity. To test the concept, a support vector machine is employed to boost the performance of several collective entanglement witnesses by incorporating state purity into the classification task of distinguishing entangled states from separable ones. Furthermore, the application of machine learning allows to optimize specificity of entanglement detection given a target value of sensitivity. A response operating characteristic curve is reconstructed based on this optimization and the area under curve calculated to assess the efficacy of the proposed model. Finally, we test the presented approach on an experimental dataset of Werner states.
Abstract This study compares postoperative visual outcomes and optical aberrations after Small Incision Lenticule Extraction (SMILE) in patients with both small (S-Kappa: Kappa angle < 0.2 mm) and ...large Kappa (L-Kappa: Kappa angle ≥ 0.2 mm) angles. The evaluated aberrations include total higher-order aberrations (HOAs), horizontal coma (HC), vertical coma (VC), and spherical aberrations (SA), with procedures incorporating intraoperative Kappa angle adjustments. We retrospectively analyzed patient records undergoing SMILE utilizing linear mixed models (LMM). We assessed adjusted mean uncorrected distance visual acuity (UDVA), Strehl ratio (SR), total HOAs, VC, and SA at pupils of 3 mm and 6 mm for both S-Kappa and L-Kappa. The disparities between S-Kappa and L-Kappa were evaluated by LMM's adjusted mean differences. The differences in optical metrics were also assessed in eyes grouped by myopia levels: low, moderate, and high. A sensitivity analysis was conducted on a threshold of Kappa angle at 0.3 mm. Eight-five patients (169 eyes) were analyzed, and no significant pre-operative difference was found in UDVA ( p = .222) or spherical equivalent ( p = .433). Post-operative differences were found in SR at 3 mm pupil size (−0.06, p = .022), total HOA 3 mm (0.15, p = .022), HC 3 mm (0.04, p = .042), VC 3 mm and 6 mm (−0.08, p = .041; 0.04, p = .041). The stratified analysis for high myopia revealed significant differences in UDVA (−0.04, p = .037), HC 3 mm (0.07, p = .03), VC 6 mm (−0.21, p = .001), and SA 3 mm and 6 mm (0.07, p = .037; −0.09, p = .037). Sensitivity analysis showed no significant difference using a 0.3 mm Kappa threshold. While some optical aberrations exhibited statistical differences between S-Kappa and L-Kappa, their clinical significance is limited. Thus, a large Kappa angle might not substantially influence post-operative optical aberrations when intraoperative Kappa angle adjustments are implemented.
Electrical railways constitute a vital component of transportation infrastructure worldwide, with rolling stock representing a key element of these systems. Given the extensive operational hours of ...such systems, effective maintenance scheduling and asset management are imperative to ensure reliability and safety while mitigating costs. This paper addresses the challenge of optimizing maintenance practices for railway rolling stock by introducing a novel implementation of reliability-centered maintenance (RCM) grounded in the reliability block diagram (RBD) framework. This methodology meticulously incorporates reliability parameters into maintenance strategies, aiming to enhance the operational efficiency of railway systems. Leveraging the criticality index, the study identifies components crucial for train reliability, facilitating cost-effective maintenance management. The proposed approach is applied and validated on the Tabriz line 1 metro in Iran, a system with over six years of operational history. Analysis reveals the bogie subsystem's criticality due to its interconnected components, with parts exhibiting significant mean time to repair (MTTR). Conversely, the brake system emerges as the most reliable subsystem. Additionally, sensitivity analysis demonstrates an inverse relationship between repair rates and component sensitivity, highlighting the pivotal role of efficient repair processes in bolstering system reliability. This research contributes a comprehensive and validated methodology for RCM in railway rolling stock, emphasizing cost reduction, system reliability, and strategic prioritization of maintenance efforts. As the approached method in this research is not limited to the specific case study and can be applied in any system by generating the RBD and reliability parameters of the system we want to study The findings hold significant implications for the global planning and execution of railway maintenance operations, setting a new standard for reliability-centered maintenance practices in the field.
The majority of published sensitivity analyses (SAs) are either local or one factor-at-a-time (OAT) analyses, relying on unjustified assumptions of model linearity and additivity. Global approaches ...to sensitivity analyses (GSA) which would obviate these shortcomings, are applied by a minority of researchers.
By reviewing the academic literature on SA, we here present a bibliometric analysis of the trends of different SA practices in last decade. The review has been conducted both on some top ranking journals (Nature and Science) and through an extended analysis in the Elsevier's Scopus database of scientific publications.
After correcting for the global growth in publications, the amount of papers performing a generic SA has notably increased over the last decade. Even if OAT is still the most largely used technique in SA, there is a clear increase in the use of GSA with preference respectively for regression and variance-based techniques. Even after adjusting for the growth of publications in the sole modelling field, to which SA and GSA normally apply, the trend is confirmed. Data about regions of origin and discipline are also briefly discussed. The results above are confirmed when zooming on the sole articles published in chemical modelling, a field historically proficient in the use of SA methods.
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•Sensitivity analysis is critical to gauge the relevance and plausibility of models.•Sensitivity analysis is either overlooked or performed unsatisfactorily.•We look at how things have changed over the last years performing bibliometric analyses.•We see sign of improvements in the take up of global sensitivity analysis.•Journals could play a role to improve responsible use of quantitative information.
The most general quantities of interest (called “responses”) produced by the computational model of a linear physical system can depend on both the forward and adjoint state functions that describe ...the respective system. This work presents the Fourth-Order Comprehensive Adjoint Sensitivity Analysis Methodology (4th-CASAM) for linear systems, which enables the efficient computation of the exact expressions of the 1st-, 2nd-, 3rd- and 4th-order sensitivities of a generic system response, which can depend on both the forward and adjoint state functions, with respect to all of the parameters underlying the respective forward/adjoint systems. Among the best known such system responses are various Lagrangians, including the Schwinger and Roussopoulos functionals, for analyzing ratios of reaction rates, the Rayleigh quotient for analyzing eigenvalues and/or separation constants, etc., which require the simultaneous consideration of both the forward and adjoint systems when computing them and/or their sensitivities (i.e., functional derivatives) with respect to the model parameters. Evidently, such responses encompass, as particular cases, responses that may depend just on the forward or just on the adjoint state functions pertaining to the linear system under consideration. This work also compares the CPU-times needed by the 4th-CASAM versus other deterministic methods (e.g., finite-difference schemes) for computing response sensitivities These comparisons underscore the fact that the 4th-CASAM is the only practically implementable methodology for obtaining and subsequently computing the exact expressions (i.e., free of methodologically-introduced approximations) of the 1st-, 2nd, 3rd- and 4th-order sensitivities (i.e., functional derivatives) of responses to system parameters, for coupled forward/adjoint linear systems. By enabling the practical computation of any and all of the 1st-, 2nd, 3rd- and 4th-order response sensitivities to model parameters, the 4th-CASAM makes it possible to compare the relative values of the sensitivities of various order, in order to assess which sensitivities are important and which may actually be neglected, thus enabling future investigations of the convergence of the (multivariate) Taylor series expansion of the response in terms of parameter variations, as well as investigating the range of validity of other important quantities (e.g., response variances/covariance, skewness, kurtosis, etc.) that are derived from Taylor-expansion of the response as a function of the model’s parameters. The 4th-CASAM presented in this work provides the basis for significant future advances towards overcoming the “curse of dimensionality” in sensitivity analysis, uncertainty quantification and predictive modeling.
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