A System and Method for Monitoring Controlling and Troubleshooting of Abrasive Waterjet Cutting Apparatus

E-print/Working paper (2019)

The invention consists of a system and method for monitoring, controlling and troubleshooting of Abrasive Waterjet Cutting machinery. More in detail, the method exploits a network of sensors for ... [more ▼]

The invention consists of a system and method for monitoring, controlling and troubleshooting of Abrasive Waterjet Cutting machinery. More in detail, the method exploits a network of sensors for continuously monitor its vibroacoustic emission pattern. Relevant features are extracted from the data using an iterative processing method. Deviations from a benchmark are interpreted based on model training then used for automatic control and troubleshooting. The expected outcome is an improvement of waterjet automation and robustness to the excellence of Industry 4.0 with a consequent impact on both its cost effectiveness and the provided quality assurance. [less ▲]

A comparison between discrete analysis and a multiphase approach for predicting heat conduction in packed beds

in Proceedings of the 10th International Conference on Computer Modeling and Simulation (2018)

the Discrete Element Method (DEM) is a Lagrangian approach initially developed for predicting particles flow. The eXtended Discrete Element Method (XDEM) framework, developed at the LuXDEM Research Centre ... [more ▼]

the Discrete Element Method (DEM) is a Lagrangian approach initially developed for predicting particles flow. The eXtended Discrete Element Method (XDEM) framework, developed at the LuXDEM Research Centre of the University of Luxembourg, extends DEM by including the thermochemical state of particles, as well as their interaction with a Computational Fluid Dynamics (CFD) domain. The level of detail of its predictions makes the XDEM suite a powerful tool for predicting complex industrial processes like steel making, powder metallurgy and additive manufacturing. Like in any other DEM software, the critical aspect of the simulations is the computation requirement that grows rapidly as the number of particles increases. Indeed, such burden currently represents the main bottleneck to its full exploitation in large-scale scenarios. Digital Twin, a research project founded by the European Regional Development Fund (ERDF), aims at drastically accelerate XDEM through different approaches and make it an effective tool for numerical predictions in industry as well as virtual prototyping. The Multiphase Particle- In-Cell (MP-PIC) method has been introduced for reducing the computation burden of DEM. It has been initially developed for predicting particles flow and uses a two-way transfer of information between the Lagrangian entities and a computation grid. The method avoids explicit contact detection and can potentially achieve a drastic reduction of the time-to-solution respect to DEM. The present contribution introduces a multiphase approach for predicting the conductive heat transfer within a static packed bed of particles. Results from a test case are qualitatively and quantitatively compared against reference XDEM predictions. The method can be effectively exploited in combination with MP- PIC for predicting the thermochemical state of particles. [less ▲]

XDEM for Tuning Lumped Models of Thermochemical Processes Involving Materials in the Powder State

in Engineering Journal (2016), 20(5), 187-201

Processes involving materials in gaseous and powder states cannot be modelled without coupling interactions between the two states. XDEM (Extended Discrete Element Method) is a valid tool for tackling ... [more ▼]

Processes involving materials in gaseous and powder states cannot be modelled without coupling interactions between the two states. XDEM (Extended Discrete Element Method) is a valid tool for tackling this issue, since it allows a coupled CFD- DEM simulation to be run. Such strength, however, mainly finds in long computational times its main drawback. This aspect is indeed critical in several applications, since a long computational time is in contrast with the increasing demand for predictive tools that can provide fast and accurate results in order to be used in new monitoring and control strategies. This paper focuses on the use of the XDEM framework as a tool for fine tuning a lumped representation of the non-isothermal decarbonation of a CaCO3 sample in powder state. The tuning of the lumped model is performed exploiting the multi-objective optimization capability of genetic algorithms. Results demonstrate that such approach makes it possible to estimate fast and accurate models to be used, for instance, in the fields of virtual sensing and predictive control. [less ▲]

A discrete-continuous approach to describe CaCO3 decarbonation in non-steady thermal conditions

in Powder Technology (2015), 275

In cement production, direct measurements of thermal and chemical variables are often unfeasible as a consequence of aggressive environments, moving parts and physical inaccessibility, and therefore ... [more ▼]

In cement production, direct measurements of thermal and chemical variables are often unfeasible as a consequence of aggressive environments, moving parts and physical inaccessibility, and therefore prediction models are essential tools in these types of industrial applications. This article addresses the problem of the numerical prediction of the CaCO3 calcination process, which is the first and the most energy expensive process in clinker production. This study was conducted using the Extended Discrete Element Method (XDEM), a framework which allows a Eulerian approach for the gas phase to be combined with a Lagrange one for the powder phase. A detailed validation of the numerical model was performed by comparison to non-isothermal TG curves for mass loss during the CaCO3 decarbonation process. The complex three-dimensional predictions for solid and gas phases are believed to represent a first step towards a new insight into the cement production process. Thus, the high accuracy and detailed description of the problem addressed, serve as a basis to assess the uncertainty of more simplified models such as those used in soft sensors. [less ▲]