Quantification of the uncertainty of shear strength models using Bayesian Inference

Different analytical models exist to predict the shear strength of reinforced concrete members. Generally, each of these shear strength models consists of a formulation based on certain underlying theory and fitted model coefficients. The model fitting parameters are usually established from the comparison with test data. Hence, the predictive...

Application of rational methods for the selection of the most plausible FE models in structural analysis

The accuracy of predictions of structural behavior by finite element analysis strongly depends on the formulation of the numerical model. Depending on the problem at hand, the analyst has to make a number of choices, which influence the numerical results to a greater or lesser extent. For complex cases, e.g. existing reinforced concrete...

Fitting fatigue test data with a novel S-N curve using frequentist and Bayesian inference

In design against fatigue, a lower bound stress range vs. endurance curve (S-N curve) is employed to characterize fatigue resistance of plain material and structural details. With respect to the inherent variability of the fatigue life, the S-N curve is related to a certain probability of exceedance, a percentile of the fatigue life. This paper...

Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis

Particulate matter (PM) is a class of malicious environmental pollutants known to be detrimental to human health. Regulatory efforts aimed at curbing PM levels in different countries often require high resolution space–time maps that can identify red-flag regions exceeding statutory concentration limits. Continuous spatio-temporal Gaussian...

Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor

Longitudinal data can be used to estimate the transition intensities between healthy and unhealthy states prior to death. An illness-death model for history of stroke is presented, where time-dependent transition intensities are regressed on a latent variable representing cognitive function. The change of this function over time is described by...

Probabilistic System Summaries for Behavior Architecting

Smart system of systems adapt to their context, current situation, and configuration. To engineer such systems’ behavior, we need to design and eval-uate system-level control strategies and the intelligent management of key scenarios. We propose a model-based approach called probabilistic system summaries to explore related design choices, e.g.,...

The Joint Multivariate Modeling of Multiple Mixed Response Sources: Relating Student Performances with Feedback Behavior

The present study concerns a Dutch computer-based assessment, which includes an assessment process about information literacy and a feedback process for students. The assessment is concerned with the measurement of skills in information literacy and the feedback process with item-based support to improve student learning. To analyze students'...

The OSIRIS Weight of Evidence approach: ITS for skin sensitisation

Within the EU FP6 project OSIRIS approaches to Integrated Testing Strategies (ITSs) were developed, with the aim to facilitate the use of non-test and non-animal testing information in regulatory risk assessment of chemicals. This paper describes an analytical Weight-of-Evidence (WoE) approach to an ITS for the endpoint of skin sensitisation. It...

Neural-symbolic cognitive agents: Architecture and theory

In real-world applications, the effective integration of learning and reasoning in a cognitive agent model is a difficult task. However, such integration may lead to a better understanding, use and construction of more realistic models. Unfortunately, existing models are either oversimplified or require much processing time, which is unsuitable...