New advances in large scale industrial DEM modeling towards energy efficient processes

Granular material processing is crucial to a number of industries such as pharmaceuticals, construction, mining, geology and primary utilities. The handling and processing of granular materials represents roughly 10% of the annual energy consumption [1]. A recent study indicated that in the US alone, current energy requirements across Coal, Metal and Mineral Mining amounts to 1246 TBtu/yr, whereas the practical minimum energy consumption is estimated to be 579 TBtu/yr, while the theoretical limited is estimated around 184 TBtu/yr [2]. It is evident that design modification allowing for process optimization can play a significant role in realizing a more energy efficient industry sector that can have significant implications on the annual global energy demands. The status quo in industry when facing the complex physics governing granular materials, is that current industry developed strategies to handle granular materials remain overly conservative and often energy-wasteful to prevent or reduce industrial-related bulk material handling problems like segregation, arching formation, insufficient handleability. Granular scale approaches have also been developed to both understand the fundamental physics governing granular flow and to study industrial applications, especially to improve the understanding and estimation of energy dissipation and energy efficiency of granular flow processes. The Discrete Element Method (DEM) proposed by Cundall and Strack [3] is starting to mature and evolve into a systematic approach to estimate and predict the response of granular systems. However, DEM is computationally intensive and is limited by the number of particles that can be considered realistically are limited to hundreds of thousands or low millions. However, before DEM can be practically considered for industrial applications the number of particles need be increased to tens of millions particles for a sufficient amount of processing time. This study discusses new advances and perspectives made possible by the Graphical Processor Unit (GPU) when simulating discrete element models, specifically for granular industrial applications. Attention is specifically focussed on the newly developed BlazeDEM3D-GPU framework for an industrial flow investigation [4]. Note that BlazeDEM3D-GPU is an open-source DEM code developed by Govender et al. [5] that has been validated for industrial ball mill simulations and hopper discharge applications using ten of millions of particles using a single NVIDIA GPU card on a desktop computer [4, 6]. The industrial granular flow investigation considered in this study is of the storage silos located at the industrial concrete central in France. The typical silo diameter is 8m with a height of around 17m. Three dimensional DEM studies were been performed to investigate the influence of particle sizes and inter-particle cohesion on the bulk flow rate and induced shear stresses for various hopper designs located at concrete central. As required for this industrially relevant application, up to 32 million particles were required to be simulated within a reasonable computing time. These simulations were performed within these requirements but only made possible by the utilization of GPUs. These results show that the GPU computing allows for realistically relevant number of simulated particles for the 3D DEM applications within a reasonable time frame. This makes large-scale analysis practically relevant but more importantly allows for a number of analyses to be conducted to steer granular processing solutions towards an increased efficiency in energy utilization

Discrete element model study into effects of particle shape on backfill response to cyclic loading behind an integral bridge abutment

The discrete element method, implemented in a modular GPU based framework that supports polyhedral shaped particles (Blaze-DEM), was used to investigate effects of particle shape on backfill response behind integral bridge abutments during temperature-induced displacement cycles. The rate and magnitude of horizontal stress build-up were found to be strongly related to particle sphericity. The stress build-up in particles of high sphericity was gradual and related to densification extending relatively far from the abutment. With increasing angularities, densification was localised near the abutment, but larger and more rapid stress build-up occurred, supported by particle reorientation and interlock developing further away.https://link.springer.com/journal/100352019-11-01hj2018Civil EngineeringMechanical and Aeronautical Engineerin

3D laser scanning technique coupled with DEM GPU simulations for railway ballasts

Spheres with complex contact models or clumped sphere models are classically used to model ballast for railway applications with the Discrete Element Method (DEM). These simplifications omits the angularity of the actual ballast by assuming the ballast is either round or has rounded edges. This is done by necessity to allow for practically com- putable simulations that may consist of a few hundred particles. This study demonstrates that an experimentally validated DEM simulation environment, BlazeDEM-3DGPU, that computes on the graphical processing unit (GPU) is able to simulate railway ballast with a more realistic shapes that includes angularity for railway applications. In particular, a procedure is developed that extracts polyhedral shaped ballast geometries digitized from 3D-laser scanning for use in DEM simulations. The results show that much larger number of particles can be successfully modelled allowing for new possibilities offered by the GPUs to investigate model railway problems using DEM. Specifically, in this study a typical experimental ballast box that contains up to 60 000 polyhedral particles have been simulated with the BlazeDEM-3DGPU computing environment within reasonable computing times

Experimental exploration of cryogenic CO2 capture utilising a moving bed

It is widely accepted that climate change is a result of the increase in greenhouse gases in the atmosphere. The continued combustion of fossil fuels and subsequent emission of CO2 is leading to an increase in global temperatures, which has led to interest in decarbonising the energy sector. Carbon capture and storage (CCS) is a method of reducing carbon emissions from fossil fuel power plants by capturing CO2 from exhaust gases and storing it in underground gas stores. Carbon capture using chemical solvents is the most matured technology for capturing emissions from the energy sector, however as the energy sector continues to decarbonise with the arrival of renewable sources focus is shifting to other industries to reduce their carbon footprint. Solvent carbon capture has disadvantages including requiring large equipment and large amounts of heat to regenerate solvent for capture, meaning it would be difficult to scale the technology down and apply it to other industrial applications. Cryogenic carbon capture (CCC) is one proposed method of CCS at smaller scale, which captures CO2 by freezing CO2 out of the exhaust gases as CO2 forms a frost on a heat transfer surface. One disadvantage of CCC is the accumulation of CO2 frost reduces the efficiency of the capture process. The process must be periodically shut down to regenerate the heat transfer surface and collect CO2 that has been frozen out of exhaust gases. This thesis proposes to overcome the frost accumulation through the use of a moving packed bed of small spherical metal beads as the heat transfer surface. As CO2 is fed into a capture column and freezes onto the metal beads, the metal beads are removed from the column, regenerated to recover the CO2, then cooled and recirculated back into the capture column. This prevents the accumulation of frost and allows continuous CO2 capture. There are many difficulties identified in this project, primarily a lack of knowledge on CO2 frost formation and how heat transfer in a moving bed affects frost formation. The research done on a purpose built experimental rig is critical in improving the future design work of a next generation moving bed CCC system. The frost accumulation in a capture column is known as a frost front, which advanced through the capture column at a fixed velocity until the column is saturated with frost. Experimental results had shown that the frost front velocity is predictable for varying CO2 concentrations and gas flow rates, with frost front velocities between 0.46-0.78 mm/s for CO2 concentrations between 4-18% v/v and 0.36-0.98 mm/s for gas flow rates between 50-120 LPM. These frost front velocity experiments in a fixed packed bed allowed the design of a moving packed bed column to set the bed flow rate to match the frost front velocity. The moving bed experiments show that the excessive accumulation of CO2 frost within the capture column can be prevented by utilising the moving bed. The successful development of a moving bed CCC system would result in a cost effective solution to the requirements of certain smaller applications that need to capture CO2, which make up a significant portion of emissions. In particular this technology is very economical for biogas upgrading, where the CO2 content of biogas must be removed before the gas can be introduced to the UK’s larger gas network. There is also a growing interest for use in shipping and other maritime applications, capturing CO2 from ship exhaust emissions during transit

Modeling of realistic microstructures on the basis of quantitative mineralogical analyses

Diese Forschung zielt darauf ab, den Einsatz realistischer Mineralmikrostrukturen in Mineralverarbeitungssimulationen Simulationen von Aufbereitungsprozessen zu ermöglichen. Insbesondere Zerkleinerungsprozesse, wie z.B. das Brechen und Mahlen von mineralischen Rohmaterialien, werden stark von der mineralischen Mikrostruktur beeinflusst, da die Textur und die Struktur der vielen Körner und ihre mikromechanischen Eigenschaften das makroskopische Bruchverhalten bestimmen. Ein Beispiel: Stellen wir uns vor, wir haben ein mineralisches Material, das im Wesentlichen aus Körnern zweier verschiedener Mineralphasen, wie Quarz und Feldspat, besteht. Wenn die mikromechanischen Eigenschaften dieser beiden Phasen unterschiedlich sind, wird sich dies wahrscheinlich auf das makroskopische Bruchverhalten auswirken. Unter der Annahme, dass die Körner eines der Minerale bei geringeren Belastungen brechen, ist es wahrscheinlich, dass sich ein Riss durch einen Stein dieses Materials durch die schwächeren Körner ausbreitet. Tatsächlich ist dies eine wichtige Eigenschaft für die Erzaufbereitung. Um wertvolle Mineralien aus einem Erz zu gewinnen, ist es wichtig, sie aus dem kommerziell wertlosen Material, in dem sie vorkommen, zu befreien. Dazu ist es wichtig zu wissen und zu verstehen, wie das Material auf Korngrößenebene bricht. Um diesen Bruch simulieren zu können, ist es wichtig, realistische Modelle der mineralischen Mikrostrukturen zu verwenden. Diese Studie zeigt, wie solche realistischen zweidimensionalen Mikrostrukturen auf der Grundlage der quantitativen Mikrostrukturanalyse am Computer erzeugt werden können. Darüber hinaus zeigt die Studie, wie diese synthetischen Mikrostrukturen dann in die gut etablierte Diskrete-Elemente-Methode integriert werden können, bei der der Bruch von mineralischem Material auf Korngrößenebene simuliert werden kann.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 237This research aims to make it possible to use realistic mineral microstructures in simulations of mineral processing. In particular, comminution processes, such as the crushing and grinding of raw mineral materials, are highly aff ected by the mineral microstructure, since the texture and structure of the many grains and their micromechanical properties determine the macroscopic fracture behavior. To illustrate this, consider a mineral material that essentially consists of grains of two diff erent mineral phases, such as quartz and feldspar. If the micromechanical properties of these two phases are diff erent, this will likely have an impact on the macroscopic fracture behavior. Assuming that the grains of one of the minerals break at lower loads, it is likely that a crack through a stone of that material will spread through the weaker grains. In fact, this is an important property for ore processing. In order to extract valuable minerals from an ore, it is important to liberate them from the commercially worthless material in which they are found. For this, it is essential to know and understand how the material breaks at grain-size level. To be able to simulate this breakage, it is important to use realistic models of the mineral microstructures. This study demonstrates how such realistic two-dimensional microstructures can be generated on the computer based on quantitative microstructural analysis. Furthermore, the study shows how these synthetic microstructures can then be incorporated into the well-established discrete element method, where the breakage of mineral material can be simulated at grain-size level.:List of Acronyms VII List of Latin Symbols IX List of Greek Symbols XV 1 Introduction 1 1.1 Motivation for using realistic microstructures in Discrete Element Method (DEM) 1 1.2 Possibilities for using realistic mineral microstructures in DEM simulations . 4 1.3 Objective and disposition of the thesis . . . . . . . . . . . . . . . . . . . . 7 2 Background 9 2.1 Discrete Element Method (DEM) . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Fundamentals of the Discrete Element Method (DEM) . . . . . . . . 9 2.1.2 Applications of DEM in comminution science . . . . . . . . . . . . . 21 2.1.3 Limitations of DEM in comminution science . . . . . . . . . . . . . . 26 2.2 Quantitative Microstructural Analysis . . . . . . . . . . . . . . . . . . . . . 29 2.2.1 Fundamentals of the Quantitative Microstructural Analysis . . . . . . 29 2.2.2 Applied QMA in mineral processing . . . . . . . . . . . . . . . . . . 49 2.2.3 Applicability of the QMA for the synthesis of realistic microstructures 49 3 Synthesis of realistic mineral microstructures for DEM simulations 51 3.1 Development of a computer-assisted QMA for the analysis of real and synthetic mineral microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.1.1 Fundamentals of the computer-assisted QMA . . . . . . . . . . . . 53 3.1.2 The requirements for the false-color image. . . . . . . . . . . . . . 54 3.1.3 The conversion of a given real mineral microstructure into a false-color image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 3.1.4 Implementation of the point, line, and area analysis . . . . . . . . . 59 3.1.5 Selection of appropriate QMA parameters for analyzing two-dimensional microstructures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 3.1.6 Summary of the principles of the adapted Quantitative Microstructural Analysis (QMA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 3.2 Analysis of possible strategies for the microstructure synthesis . . . . . . . . 71 3.3 Implementation of the drawing method . . . . . . . . . . . . . . . . . . . . 76 3.3.1 Drawing of a single grain . . . . . . . . . . . . . . . . . . . . . . . 77 XVIII List of Greek Symbols 3.3.2 Drawing of multiple grains, which form a synthetic microstructure . . 81 3.3.3 Synthesizing mineral microstructures consisting of multiple phases . 85 3.4 The final program for microstructure analysis and synthesis . . . . . . . . . 89 3.4.1 Synthesis and analysis of an example microstructure . . . . . . . . . 90 3.4.2 Procedure for generating a realistic synthetic microstructure of a given real microstructure . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 4 Validation of the synthesis approach 103 4.1 Methodical considerations . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.1.1 The basic idea of the validation procedure . . . . . . . . . . . . . . 103 4.1.2 The experimental realizations . . . . . . . . . . . . . . . . . . . . . 108 4.2 Basic indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 4.2.1 Considerations for the basic indenter test . . . . . . . . . . . . . . . 109 4.2.2 Realization and evaluation of the real basic indenter test . . . . . . . 114 4.2.3 Realization and evaluation of the simulated basic indenter test . . . 127 4.2.4 Conclusions on the basic indenter test . . . . . . . . . . . . . . . . . 138 4.3 Extended indenter test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 4.3.1 Basic considerations for the extended indenter test . . . . . . . . . . 139 4.3.2 Realization and evaluation of the real extended indenter test . . . . 142 4.3.3 Realization and evaluation of the simulated extended indenter test . 154 4.3.4 Conclusions on the extended indenter test . . . . . . . . . . . . . . 171 4.4 Particle bed test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4.4.1 Basic considerations for the particle bed test . . . . . . . . . . . . . 173 4.4.2 Realization and evaluation of the real particle bed test . . . . . . . . 176 4.4.3 Realization and evaluation of the simulated particle bed test . . . . . 188 4.4.4 Conclusions on the particle bed test . . . . . . . . . . . . . . . . . . 203 5 Conclusions and directions for future development 205 6 References 211 List of Figures 229 List of Tables 235 Appendix 23

In-line powder flow behaviour measured using electrostatic technology

Within solid-dose manufacturing processes, powder flow and powder triboelectrification are critical to the quality of the final product. Off-line testers do not simulate the shear and packing conditions that a powder would experience in-process and may be unreliable in predicting in-line flow and charging properties, which are key components to successful formulation and process design. In this work, a dual-electrode, electrostatic powder flow sensor (EPFS) was used to obtain electrostatic signals that were generated in response to the pattern of flow of pharmaceutical powders in two density modes: The first being powders in lean phase flow, generated by free-fall of the powder from the outlet of a screw-feeder. The second being dense phase flow, through either 19.1 mm Ii.Dd. stainless-steel pipe or at the outlet of a tablet-press hopper. Powders were selected from a range of low to high cohesivity so as to study the effect of powder cohesion on the flow pattern. Electrostatic signals were then analysed by three distinct signal processing methods (RMS signal averaging, cross correlation, and Fast-Fourier-Transform) with a view to determining certain characteristics of powder flow, i.e. mass flow rate; cohesivity; and triboelectrification. In the first application a calibration was attempted to establish the link between the root-mean-square (RMS) of the electrostatic signal and the mass flow, as determined by the accumulation of mass on a balance placed below the screw-feeder (in the case of lean phase application) and the 19.1 mm i.d. pipe (in the case of dense phase application). In both cases it proved unsuccessful, owing to the instability in the electrostatic signal (i.e. its dependence on factors other than mass flow, for example inherent and induced charge fluctuations and moisture content). An alternative method for determining mass flow rate was proposed based on the second signal processing method, which involved the cross-correlation of signal from both sensors to determine the free-fall velocity. This method might work in future applications if combined with a suitable technique for determining the powder density. In the second application, a Fast-Fourier-Transform (FFT) of the electrostatic signal to yield an FFT spectrum was used to establish whether this technique could determine aspects of powder cohesivity. A correlation in rank order of cohesivity was observed between the ratio of the summed or averaged amplitudes at the three principle frequencies to the summed or averaged of the baseline components respectively, and the cohesivity of the powders, as determined by off-line powder rheometry assessments of dynamic flow and bulk properties. In the third application, the RMS signal normalised to the powder mass flow rate was used to study the time-dependent powder charging behaviour, which is induced by the transportation of the powder within the screw feeder. Characteristic relative charging profiles were obtained for each powder, which in some cases were coupled to charge-induced adhesion of the powder to the equipment. In the last application, the RMS signal generated from the EPFS sensor located at the outlet of the hopper on a rotary tablet press was used to interrogate the dense-phase intermittent-flow resulting from the dosing of the tablet die. Those more cohesive powders gave a larger RMS signal at the lower electrode (relative to the upper electrode) whereas less cohesive powders had similar RMS signals at each electrode. While the exact explanation of this effect is currently unknown these results suggest that the technique might be useful in the determination of die filling as a function of the input material characteristics. In summary, this work has provided some insight into the potential applications of EPFS for in-line measurement of powder flow and charging characteristics. Future work should focus on (i) developing an integrated sensor with an independent measurement of density to yield the powder mass flow using an inferential approach, (ii) co-use of techniques (such as Faraday-cup and charge decay analysers) to validate the in-line charging behaviour, (iii) further exploration of the significance of the signal amplitude difference at the tablet press hopper outlet in on the characteristics of the tablet compact