Assessment of calanchi and rill-interrill erosion susceptibility in northern Liguria, Italy: A case study using a probabilistic modelling framework

Geoderma ◽  
2020 ◽  
Vol 371 ◽  
pp. 114367 ◽  
Author(s):  
Michael Maerker ◽  
Alberto Bosino ◽  
Claudia Scopesi ◽  
Paolo Giordani ◽  
Marco Firpo ◽  
...  
Keyword(s):  
Probabilistic Modelling ◽  
Modelling Framework ◽  
Interrill Erosion

A geostatistical approach to winter road surface condition estimation using mobile RWIS data

2019 ◽  
Vol 46 (6) ◽  
pp. 511-521
Author(s):  
Lian Gu ◽  
Tae J. Kwon ◽  
Tony Z. Qiu
Keyword(s):  
Robust Regression ◽  
Surface Condition ◽  
Road Surface ◽  
Road Maintenance ◽  
Surface Conditions ◽  
Modelling Framework ◽  
Geostatistical Approach ◽  
Winter Road ◽  
Systematic Framework

In winter, it is critical for cold regions to have a full understanding of the spatial variation of road surface conditions such that hot spots (e.g., black ice) can be identified for an effective mobilization of winter road maintenance operations. Acknowledging the limitations in present study, this paper proposes a systematic framework to estimate road surface temperature (RST) via the geographic information system (GIS). The proposed method uses a robust regression kriging method to take account for various geographical factors that may affect the variation of RST. A case study of highway segments in Alberta, Canada is used to demonstrate the feasibility and applicability of the method proposed herein. The findings of this study suggest that the geostatistical modelling framework proposed in this paper can accurately estimate RST with help of various covariates included in the model and further promote the possibility of continuous monitoring and visualization of road surface conditions.

scholarly journals The application of a hybrid simulation modelling framework as a decision-making tool for TPM improvement

2019 ◽  
Vol 25 (3) ◽  
pp. 476-498 ◽  
Author(s):  
Omogbai Oleghe ◽  
Konstantinos Salonitis
Keyword(s):  
Discrete Event Simulation ◽  
Hybrid Model ◽  
Discrete Event ◽  
Simulation Modelling ◽  
Hybrid Modelling ◽  
Content Type ◽  
Event Simulation ◽  
Modelling Framework ◽  
Field Notes

Purpose The purpose of this paper is to promote a system dynamics-discrete event simulation (SD-DES) hybrid modelling framework, one that is useful for investigating problems comprising multifaceted elements which interact and evolve over time, such as is found in TPM. Design/methodology/approach The hybrid modelling framework commences with system observation using field notes which culminate in model conceptualization to structure the problem. Thereafter, an SD-DEShybrid model is designed for the system, and simulated to proffer improvement programmes. The hybrid model emphasises the interactions between key constructs relating to the system, feedback structures and process flow concepts that are the hallmarks of many problems in production. The modelling framework is applied to the TPM operations of a bottling plant where sub-optimal TPM performance was affecting throughput performance. Findings Simulation results for the case study show that intangible human factors such as worker motivation do not significantly affect TPM performance. What is most critical is ensuring full compliance to routine and scheduled maintenance tasks and coordinating the latter to align with rate of machine defect creation. Research limitations/implications The framework was developed with completeness, generality and reuse in view. It remains to be applied to a wide variety of TPM and non-TPM-related problems. Practical implications The developed hybrid model is scalable and can fit into an existing discrete event simulation model of a production system. The case study findings indicate where TPM managers should focus their efforts. Originality/value The investigation of TPM using SD-DES hybrid modelling is a novelty.

Can recreational ecosystem services be inferred by integrating non-parametric scale estimators within a modelling framework? The birdwatching potential index as a case study

2019 ◽  
Vol 103 ◽  
pp. 395-409 ◽  
Author(s):  
Mário Santos ◽  
Diogo Carvalho ◽  
Antonio Luis ◽  
Rita Bastos ◽  
Samantha Jane Hughes ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Modelling Framework ◽  
Potential Index ◽  
Non Parametric

MULTI–STATE ANALYSIS OF PROCESS STATUS USING MULTILEVEL FLOW MODELLING AND BAYESIAN NETWORK

2016 ◽  
Vol 78 (8-3) ◽  
Author(s):  
Mohamed A. R. Khalil ◽  
Arshad Ahmad ◽  
Tuan Amran Tuan Abdullah ◽  
Ali Al-Shatri ◽  
Ali Al-Shanini
Keyword(s):  
Bayesian Network ◽  
Fault Detection And Diagnosis ◽  
Success Rates ◽  
Probabilistic Information ◽  
Modelling Framework ◽  
Predicting Success ◽  
Detection And Diagnosis ◽  
Probability Information ◽  
Multilevel Flow Modeling

Multilevel Flow Modeling (MFM) model maps functionality of components in a system through logical interconnections and is effective in predicting success rates of tasks undertaken. However, the output of this model is binary, which is taken at its extrema, i.e., success and failure, while in reality, the operational status of plant components often spans between these end. In this paper, a multi-state model is proposed by adding probabilistic information to the modelling framework. Using a heat exchanger pilot plant as a case study, the MFM model is transformed into its fault tree [1] equivalent to incorporate failure probability information. To facilitate computations, the FT model is transformed into Bayesian Network model, and applied for fault detection and diagnosis problems. The results obtained illustrate the effectiveness and feasibility of the proposed method.

Distribution of joints: probabilistic modelling and case study near Cardiff (Wales, U.K.)

1997 ◽  
Vol 19 (10) ◽  
pp. 1273-1284 ◽  
Author(s):  
Christophe Pascal ◽  
Jacques Angelier ◽  
Marie-Christine Cacas ◽  
Paul L. Hancock
Keyword(s):  
Probabilistic Modelling
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