The glass filling of diamonds Part 2: a possible filling process

1994 ◽  
Vol 24 (2) ◽  
pp. 94-103 ◽  
Author(s):  
James B. Nelson
Keyword(s):  
Filling Process

Analysis of the Mold Filling Process with Phase Change Considering the Non-steady Effect

1996 ◽  
Vol 11 (1) ◽  
pp. 58-67 ◽  
Author(s):  
M. S. Kim ◽  
W. I. Lee ◽  
J. S. Lee
Keyword(s):  
Phase Change ◽  
Mold Filling ◽  
Filling Process

scholarly journals Impact of Powder Properties on the Rheological Behavior of Excipients

Pharmaceutics ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1198
Author(s):  
Pauline H. M. Janssen ◽  
Sébastien Depaifve ◽  
Aurélien Neveu ◽  
Filip Francqui ◽  
Bastiaan H. J. Dickhoff
Keyword(s):  
Flow Field ◽  
Rheological Behavior ◽  
Quality By Design ◽  
Filling Process ◽  
Dynamic Flow ◽  
Die Filling ◽  
Flow Characterization ◽  
Wide Range ◽  
Powder Properties ◽  
The Impact

With the emergence of quality by design in the pharmaceutical industry, it becomes imperative to gain a deeper mechanistic understanding of factors impacting the flow of a formulation into tableting dies. Many flow characterization techniques are present, but so far only a few have shown to mimic the die filling process successfully. One of the challenges in mimicking the die filling process is the impact of rheological powder behavior as a result of differences in flow field in the feeding frame. In the current study, the rheological behavior was investigated for a wide range of excipients with a wide range of material properties. A new parameter for rheological behavior was introduced, which is a measure for the change in dynamic cohesive index upon changes in flow field. Particle size distribution was identified as a main contributing factor to the rheological behavior of powders. The presence of fines between larger particles turned out to reduce the rheological index, which the authors explain by improved particle separation at more dynamic flow fields. This study also revealed that obtained insights on rheological behavior can be used to optimize agitator settings in a tableting machine.

scholarly journals A Modelling and Validation Approach for Predicting Particle Concentrations of Airborne Dust during the Filling Process of Cylindrical Silos

2021 ◽  
Vol 11 (4) ◽  
pp. 1794
Author(s):  
Luke Stone ◽  
Stefan Zigan ◽  
Lahiru L. Lulbadda Waduge ◽  
David B. Hastie
Keyword(s):  
Measurement Techniques ◽  
Health And Safety ◽  
Feasibility Studies ◽  
Experimental Tests ◽  
Discrete Element Modelling ◽  
Significant Finding ◽  
Filling Process ◽  
Airborne Dust ◽  
Process Simulations ◽  
Quality Of Products

Traditionally, when undertaking feasibility studies for designing new storage facilities such as storage silos, engineers will extract design information from experiments and evaluate potential risks associated with health and safety, suitability design for reliable material flow, and quality of products. The simulation approach applied incorporates Computational Fluid Dynamics (CFD), and Discrete Element Modelling (DEM) approaches and experimental tests will be used for validating these simulation results. One important aspect related to handling fine and dusty materials (particles smaller than 100 microns) is the associated risk of dust explosions, which needs to be evaluated before the commissioning of storage silos; to evaluate the accumulation of fines during the silo filling process, simulations and experiments were conducted. Alumina and salt were used here as reference materials for calibration and the validation purposes. The validation efforts are significant due to the fact that the data that is accessible in simulations is vastly different to the accessible data in experiments, which is restricted by measurement techniques and equipment. Such restrictions are observed in the evaluation of particle concentrations in a large confined volume. A new methodology has been developed to evaluate concentrations in both simulations and experiments by employing a non-dimensional factor [k], here called “Concentration Rank Factor” (CRF). A significant finding of this research is that experiments and simulations can be compared using CRF. It has been found to be within 2% of the experiment averaged value of 0.64.

scholarly journals Spatiotemporal Monitoring and Evaluation Method for Sand-Filling of Immersed Tube Tunnel Foundation

2021 ◽  
Vol 11 (3) ◽  
pp. 1084
Author(s):  
Peng Wu ◽  
Ailan Che
Keyword(s):  
Neural Network ◽  
Elastic Wave ◽  
Frequency Domain ◽  
Bp Neural Network ◽  
Evaluation Method ◽  
Monitoring And Evaluation ◽  
Strong Nonlinearity ◽  
Filling Process ◽  
Time Frequency ◽  
Feature Parameters

The sand-filling method has been widely used in immersed tube tunnel engineering. However, for the problem of monitoring during the sand-filling process, the traditional methods can be inadequate for evaluating the state of sand deposits in real-time. Based on the high efficiency of elastic wave monitoring, and the superiority of the backpropagation (BP) neural network on solving nonlinear problems, a spatiotemporal monitoring and evaluation method is proposed for the filling performance of foundation cushion. Elastic wave data were collected during the sand-filling process, and the waveform, frequency spectrum, and time–frequency features were analysed. The feature parameters of the elastic wave were characterized by the time domain, frequency domain, and time-frequency domain. By analysing the changes of feature parameters with the sand-filling process, the feature parameters exhibited dynamic and strong nonlinearity. The data of elastic wave feature parameters and the corresponding sand-filling state were trained to establish the evaluation model using the BP neural network. The accuracy of the trained network model reached 93%. The side holes and middle holes were classified and analysed, revealing the characteristics of the dynamic expansion of the sand deposit along the diffusion radius. The evaluation results are consistent with the pressure gauge monitoring data, indicating the effectiveness of the evaluation and monitoring model for the spatiotemporal performance of sand deposits. For the sand-filling and grouting engineering, the machine-learning method could offer a better solution for spatiotemporal monitoring and evaluation in a complex environment.

Analysis on vibration characteristics of screw in filling process of dynamic injection molding machine

2016 ◽  
Vol 36 (8) ◽  
pp. 861-866 ◽  
Author(s):  
Quan Wang ◽  
Zhenghuan Wu
Keyword(s):  
Injection Molding ◽  
Processing Parameters ◽  
Axial Vibration ◽  
Filling Process ◽  
Molding Machine ◽  
Lumped Mass ◽  
Injection Molding Machine ◽  
Injection Speed ◽  
And Performance ◽  
Injection Screw

Abstract This paper presents a study of the characteristics of axial vibration of a screw in the filling process for a novel dynamic injection molding machine. By simplifying a generalized model of the injection screw, physical and mathematic models are established to describe the dynamic response of the axial vibration of a screw using the method of lumped-mass. The damping coefficient of the screw is calculated in the dynamic filling process. The amplitude-frequency characteristics are analyzed by the simulation and experimental test of polypropylene. The results show that the amplitude of a dynamic injection molding machine is not only is related to structure parameters of the screw and performance of the material, such as non-Newtonian index, but also depends on the processing parameters, such as vibration intensity and injection speed.

Sign in / Sign up

Export Citation Format

Share Document