DEM study of the flow of cohesive particles in a screw feeder

Feasibility and Application of Local Closed-Loop Materials to Produce Compressed and Stabilized Earth Blocks

The validation of a feasible application for the production of sustainable bricks with local materials in humid and hot climates, which would allow the current housing needs of a constantly growing population with scarce economic resources to be met while also reducing energy inputs for climate control, is a current challenge without a definitive solution. Therefore, this research studied the incorporation of local aggregates and two second-generation materials to produce lime-stabilized Compressed Earth Blocks (CSEBs) using a semi-automatic machine for their manufacture. An initial matrix was designed as a baseline, and three more were developed with variations to incorporate second-generation materials individually and as mixtures. The stabilizer was added in concentrations of 5, 10, and 15%, resulting in a total of 12 batches of CSEBs. Eleven of the studied batches exceed the normative limits for simple compressive strength and initial water absorption coefficient. The best result of simple compressive strength was obtained in two batches of the same matrix that used construction demolition waste (CDW), reaching 4.3 MPa (43% above the minimum limit established by the most restrictive regulations and 115% above the least restrictive). It was possible to produce sustainable bricks in situ with average ambient temperatures of 32 °C and relative humidity of 91%.

Feed factor profile prediction model for two-component mixed powder in the twin-screw feeder

In continuous pharmaceutical manufacturing processes, it is crucial to control the powder flow rate. The feeding process is characterized by the amount of powder delivered per screw rotation, referred to as the feed factor. This study aims to develop models for predicting the feed factor profiles (FFPs) of two-component mixed powders with various formulations, while most previous studies have focused on single-component powders. It further aims to identify the suitable model type and to determine the significance of material properties in enhancing prediction accuracy by using several FFP prediction models with different input variables. Four datasets from the experiment were generated with different ranges of the mass fraction of active pharmaceutical ingredients (API) and the powder weight in the hopper. The candidates for the model inputs are (a) the mass fraction of API, (b) process parameters, and (c) material properties. It is desirable to construct a high-performance prediction model without the material properties because their measurement is laborious. The results show that using (c) as input variables did not improve the prediction accuracy as much, thus there is no need to use them.

Particle Behavior and Aperture Optimization of Variable Vibration-Amplitude Screening Based on Discrete Element Method Simulation

Recently, some novel screens were proposed based on the improved understanding of screening processes from particle-scale studies, one of which is the novel variable amplitude equal thickness vibration screen (VAETVS). This paper presents an investigation of using different aperture sizes to further optimize the VAETVS by the discrete element method (DEM). The screen was divided into three panels, and the aperture size of each panel was varied in the simulation. The particles' dynamics and spatial distribution were investigated to better understand the effects of varied amplitudes and aperture sizes on the screening efficiency. The results showed that the VAETVS can be effectively optimized by varied amplitude as well as varied aperture size for different screen panels. The amplitude variance is more effective for hard sieve particles and hindrance particles. It is also found that from the feed end to the discharge end, the difference in the distribution of particle mass between the coarse particles and the fine particles increases. Generally, such a difference can be increased with increasing aperture sizes. However, the effects of the apertures of the different panels were not the same. The simulated data were further analyzed by the Box-Behnken response surface method, which gave a mathematical model to predict the screening efficiency η with the varied apertures. From the model, the optimal aperture sizes are 7.5, 7.58, and 6.81 mm, yielding the maximum screening efficiency of 86.35%, and the optimal opening areas for the three panels are 35, 40, and 40%, respectively, yielding the maximum screening efficiency of 87.82%.

Reviewing the Impact of Powder Cohesion on Continuous Direct Compression (CDC) Performance

The pharmaceutical industry is undergoing a paradigm shift towards continuous processing from batch, where continuous direct compression (CDC) is considered to offer the most straightforward implementation amongst powder processes due to the relatively low number of unit operations or handling steps. Due to the nature of continuous processing, the bulk properties of the formulation will require sufficient flowability and tabletability in order to be processed and transported effectively to and from each unit operation. Powder cohesion presents one of the greatest obstacles to the CDC process as it inhibits powder flow. As a result, there have been many studies investigating potential manners in which to overcome the effects of cohesion with, to date, little consideration of how these controls may affect downstream unit operations. The aim of this literature review is to explore and consolidate this literature, considering the impact of powder cohesion and cohesion control measures on the three-unit operations of the CDC process (feeding, mixing, and tabletting). This review will also cover the consequences of implementing such control measures whilst highlighting subject matter which could be of value for future research to better understand how to manage cohesive powders for CDC manufacture.

Development of a predictive model for gravimetric powder feeding from an API-rich materials properties library

A model was developed for predicting the feed factor profile of a powder, processed through a gravimetric feeder, as a function of material properties and process parameters. Predictive models proposed in existing literature have often used excipients and active pharmaceutical ingredients (APIs) with good powder flow characteristics in their development. In this work, a material properties library containing a large proportion of APIs, as well as excipients and co-processed blends, was used to build the model and enhance the prediction of feed factor profile for cohesive powders. Gravimetric feeder trials were performed at varying mass flow rates and screw geometries to determine the feed factor profiles. A semi-empirical exponential model, with parameters f_max, f_min, and β, was then used to fit the experimental feed factor profiles. Bayesian optimisation and Support Vector Regression (SVR) modelling techniques were utilised to optimise and predict the exponential model parameters as a function of material properties. The parameters found to strongly influence the model were particle size, bulk density, FFC and FT4 rheometer parameters. Results showed low prediction errors between the estimated and experimental data. The final model produces good estimations of the feed factor profile and requires minimal powder consumption.

Chrono::GPU: An Open-Source Simulation Package for Granular Dynamics Using the Discrete Element Method

We report on an open-source, publicly available C++ software module called Chrono::GPU, which uses the Discrete Element Method (DEM) to simulate large granular systems on Graphics Processing Unit (GPU) cards. The solver supports the integration of granular material with geometries defined by triangle meshes, as well as co-simulation with the multi-physics simulation engine Chrono. Chrono::GPU adopts a smooth contact formulation and implements various common contact force models, such as the Hertzian model for normal force and the Mindlin friction force model, which takes into account the history of tangential displacement, rolling frictional torques, and cohesion. We report on the code structure and highlight its use of mixed data types for reducing the memory footprint and increasing simulation speed. We discuss several validation tests (wave propagation, rotating drum, direct shear test, crater test) that compare the simulation results against experimental data or results reported in the literature. In another benchmark test, we demonstrate linear scaling with a problem size up to the GPU memory capacity; specifically, for systems with 130 million DEM elements. The simulation infrastructure is demonstrated in conjunction with simulations of the NASA Curiosity rover, which is currently active on Mars.

Process Model Approach to Predict Tablet Weight Variability for Direct Compression Formulations at Pilot and Production Scale

Optimizing processing conditions to achieve a critical quality attribute (CQA) is an integral part of pharmaceutical quality by design (QbD). It identifies combinations of material and processing parameters ensuring that processing conditions achieve a targeted CQA. Optimum processing conditions are formulation and equipment-dependent. Therefore, it is challenging to translate a process design between formulations, pilot-scale and production-scale equipment. In this study, an empirical model was developed to determine optimum processing conditions for direct compression formulations with varying flow properties, across pilot- and production-scale tablet presses. The CQA of interest was tablet weight variability, expressed as percentage relative standard deviation. An experimental design was executed for three model placebo blends with varying flow properties. These blends were compacted on one pilot-scale and two production-scale presses. The process model developed enabled the optimization of processing parameters for each formulation, on each press, with respect to a target tablet weight variability of <1%RSD. The model developed was successfully validated using data for additional placebo and active formulations. Validation formulations were benchmarked to formulations used for model development, employing permeability index values to indicate blend flow.

Study of the capsule-filling dosator process via calibrated DEM simulations

Capsule filling is frequently accomplished via the dosator process. Controlling the main quality attributes, i.e., the fill weight and the fill weight variability, requires excellent process understanding. For the investigation of critical process parameters of low-dose capsule filling, DEM simulations were used. Two contact models (Hertz model and Luding model) were calibrated and validated to represent the lactose powder Lactohale 100. Both models gave good results, yet the Luding model resulted in better predictions. Since the dosator process is a volume-based approach, the dosator geometry is an important factor. We provide evidence that not only the volume, but also the proportions of the dosator affect the capsule fill weight. Slim nozzle chambers cause lower mass due to increased wall friction impact. The process is not volumetric, as a fill weight to volume correlation does not exist. Furthermore, the fill weight increases with higher powder beds and smaller gaps between the nozzle tip and the container bottom due to higher densification of the powder. Fill weight variations due to bed inhomogeneity were investigated by varying the bulk density of the initial powder bed.

Calibration of Discrete-Element-Method Parameters for Cohesive Materials Using Dynamic-Yield-Strength and Shear-Cell Experiments

This study tested the effectiveness of using dynamic yield strength (DYS) and shear-cell experiments to calibrate the following discrete-element-method (DEM) parameters: surface energy, and the coefficients of sliding and rolling friction. These experiments were carried out on cohesive granules, and DEM models were developed for these experiment setups using the JKR cohesion contact model. Parameter-sensitivity analysis on the DYS model showed that the DYS results in the simulations were highly sensitive to surface energy and were also impacted by the values of the two friction coefficients. These results indicated that the DYS model could be used to calibrate the surface energy parameter once the friction coefficients were fixed. Shear-cell sensitivity analysis study found that the influence of surface energy on the critical-state shear value cannot be neglected. It was inferred that the shear-cell model has to be used together with the DYS model to identify the right set of friction parameters. Next, surface energy was calibrated using DYS simulations for a chosen set of friction parameters. Calibrations were successfully conducted for simulations involving experimentally sized particles, scaled-up particles, a different shear modulus, and a different set of friction parameters. In all these cases, the simulation DYS results were found to be linearly correlated with surface energy and were within 5% of the experimental DYS result. Shear-cell simulations were then used to compare calibrated surface-energy values for the scaled-up particles with the experimentally sized particles. Both the simulations resulted in similar critical-state shear values. Finally, it was demonstrated that a combination of DYS and shear-cell simulations could be used to compare two sets of friction parameters and their corresponding calibrated surface energy values to identify the set of parameters that better represent the flow behavior demonstrated by the experimental system.

Self-assembly of granular spheres under one-dimensional vibration

The self-assembly of uniform granular spheres is related to the fundamentals of granular matter such as the transitions of phases, order/disorder and jamming states. This paper presents a DEM (discrete element method) study of the continuous self-assembly of uniform granular spheres from random close packing (RCP) to partially and nearly fully ordered packings under one-dimensional (1D) sinusoidal vibration without other interventions. The effects of the vibration amplitude and frequency are investigated in a wide range. The structures of the packings are characterized in terms of packing fraction and other microscopic structural parameters, including the coordination number, bond-orientational orders, and, in particular, ordered clusters, by adaptive common neighbor analysis (a-CNA). It is shown that 1D vibrations can also lead to the self-assembly of uniform granular spheres with packing fractions exceeding the RCP limit, and FCC (face centered cubic) and HCP (hexagonal close packed) structures coexist in the self-assembled packings while their total fraction can reach nearly 100%. The structures of these packings can be better correlated with the vibration velocity amplitude rather than the commonly used vibration intensity. The dynamics of such self-assembly is also preliminarily analyzed. Our study not only presents the conditions for the self-assembly of uniform granular spheres under 1D vibration, but also characterizes the order-disorder transitions during the process, which can improve our understanding of the fundamentals of granular materials and jamming states.

Pharmaceutical excipients properties and screw feeder performance in continuous processing lines: a Quality by Design (QbD) approach

Screw feeder performance is a critical aspect in continuous manufacturing processes. Pharmaceutical excipients, such as mannitol, microcrystalline cellulose, lactose monohydrate, and anhydrous dibasic calcium phosphate can present problems in ensuring a continuous stable feed rate due to their sub-optimal flow properties. In alignment with Quality by Design (QbD) goals, the aim of this work was to identify and explain critical sources of variability of some powder excipients delivery by screw feeding, in particular to continuous processing lines. Pharmaceutical excipients with a wide range of material properties were selected, and the impact of their flow and density properties on screw feeder performance was investigated. The analysis of the powder conveying by the screws was performed at different hopper fills and different screw speeds. A multivariable model involving bulk density (CBD) and parameters from FT4 dynamic downwards testing (SI) and dynamic upwards testing (SE) explained 95.7% of excipients feed rates (p < .001). The study gathers valuable information about the screw feeder performance and input materials properties that can help process understanding and QbD-based development of solid dosage forms in continuous processing lines.