Deep Bayesian survival analysis of rail useful lifetime

Reliable estimation of rail useful lifetime can provide valuable information for predictive maintenance in railway systems. However, in most cases, lifetime data is incomplete because not all pieces of rail experience failure by the end of the study horizon, a problem known as censoring. Ignoring or otherwise mistreating the censored cases...

4S3F Diagnostic Bayesian Network method: discussion about application and technical design

In practice, automated energy performance fault diagnosis systems are seldom installed in HVAC systems. The main reason is that a specific Fault Detection and Diagnosis (FDD) setup is time-consuming and expensive because the existing methods are component-specific, not aligned with HVAC design practices, and not fully automated. 4S3F (four...

A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion...

Resilience-based approach to safety barrier performance assessment in process facilities

The performance assessment of safety barriers is essential to find vulnerable elements in a safety barrier system. Traditional performance assessment approaches mainly focus on using several static indicators for quantifying the performance of safety barriers. However, with the increasing complexity of the system, emerging hazards are highly...

Bayesian calibration at the urban scale: A case study on a large residential heating demand application in Amsterdam

A bottom-up building energy modelling at the urban scale based on Geographic Information System and semantic 3D city models can provide quantitative insights to tackle critical urban energy challenges. Nevertheless, incomplete information is a common obstacle to produce reliable modelling results. The residential building heating demand...

A Bayesian Network Approach for Condition Monitoring of High-Speed Railway Catenaries

The growing variety of data from condition monitoring of high-speed railways offer unprecedented opportunities to improve railway infrastructure maintenance. For condition monitoring of railway catenaries, this paper proposes a data-driven approach that uses a Bayesian network (BN) to integrate the inspection data from catenaries into a key...

Risk analysis of earth-rock dam breach based on dynamic Bayesian network

Despite the fact that the Bayesian network has great advantages in logical reasoning and calculation compared with the other traditional risk analysis methods, there are still obvious shortcomings in the study of dynamic risk. The risk factors of the earth-rock dam breach are complex, which vary with time during the operation period. Static...

A numerical Bayesian-calibrated characterization method for multiscale prepreg preforming simulations with tension-shear coupling

Carbon fiber reinforced plastics (CFRPs) are attracting growing attention in industry because of their enhanced properties. Preforming of thermoset carbon fiber prepregs is one of the most common production techniques of CFRPs. To simulate preforming, several computational methods have been developed. Most of these methods, however, obtain...

Bayesian oma of offshore rock lighthouses: Surprises with close modes, symmetry and alignment

A set of seven rock lighthouses around the British Isles was studied by a combination of forced and ambient vibration tests executed with some extreme logistical constraints. Forced vibration testing of the circular section masonry towers combined with experimental modal analysis identified modes with alignment assumed the same as the shaker...

Application of Probabilistic Damage Identification to Civil Engineering Structures: A Marriage of Structural Health Monitoring and Bayesian Statistics

The rapid development in statistics, information technology, and computational power have en- abled numerous innovative methods to emerge in Structural Health Monitoring (SHM) for structural damage detection, both in practical application and research. The intention of such methods is to use the data obtained from the monitoring system to...

Urban building energy modeling using a 3D city model and minimizing uncertainty through Bayesian inference: A case study focuses on Amsterdam residential heating demand simulation

To cut down immense greenhouse gases emission and energy consumption in the rapidly urbanizing world, a holistic understanding and rethinking of our dynamic urban energy system are inevitable. Performing bottom-up building energy modelings at urban scale based on Geographic Information System (GIS) and semantic 3D city models could be a...

A data-driven approach for optimal design of integrated air quality monitoring network in a chemical cluster

The chemical industry is of paramount importance to the world economy and this industrial sector represents a substantial income source for developing countries. However, the chemical plants producing inside an industrial district pose a great threat to the surrounding atmospheric environment and human health. Therefore, designing an...