京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第18223号 / 工博第3815号 / 新制||工||1585(附属図書館) / 31081 / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 後藤 仁志, 教授 細田 尚, 准教授 KHAYYER Abbas / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Background. Physically-based snow simulation is computationally expensive and not yet applicable to real-time applications. Some of the prime factors for this cost are the complex physics, the large number of particles, and the small time step required for a high-quality and stable simulation.Simplified methods, such as height maps, are used instead to emulate snow accumulation. A way of improving performance is finding ways of doing less computations. In the field of computer graphics, adaptive methods have been developed to focus computation to where it is most needed. These works will serve as inspiration for this thesis. Objectives. This thesis aims to reduce the total particle workload of an existing Discrete Element Method (DEM) application, thereby improving performance. The aim consists of the following objectives. Integrate a spatial method, thereby lessening the total number of particles through particle merging and splitting, and implement a temporal method, thereby lessening the workload by freezing certain particles in time. The performance of both these techniques will then be tested and analyzed in multiple scenarios. Methods. Spatially and temporally adaptive methods were implemented in an existing snow simulator. The methods were both measured and compared using quantitative tests in three different scenes with varying particle counts. Results. Performance tests show that both the spatial and temporal adaptivity reduce the execution time compared to the base method. The improvements from temporal adaptivity are consistently around 1.25x while the spatial adaptivity shows a larger range of improvements between 1.23x and 2.86x. Combining both adaptive techniques provides an improvement of up to 3.58x. Conclusions. Both spatially and temporally adaptive techniques are viable ways to improve the performance of a DEM-based snow simulation. The current implementation has some issues with performance overhead and with the visual results while using spatial adaptivity, but there is a lot of potential for the future. / Bakgrund. Fysikbaserad snösimulering är beräkningsmässigt dyrt och ännu inte tillämpligt på realtidsapplikationer. Några av de viktigaste faktorerna för denna kostnad är den komplexa fysiken, stora mängden partiklar och det lilla tidssteg som krävs för en högkvalitativ och stabil simulering. Förenklade metoder, såsom höjdkartor, används istället för att efterlikna ansamlingen av snö. Ett sätt att förbättra prestandan är hitta sätt att göra färre beräkningar. Inom området datorgrafik har adaptiva metoder utvecklats för att fokusera beräkningen där den behövs som mest. Dessa verk kommer att användas som inspiration för detta arbete. Syfte. Detta examensarbete syftar till att minska den totala partikelbelastningen för en befintlig applikation baserat på Discrete Element Method (DEM), och därigenom förbättra prestandan. Målet består av följande mål. Integrera en rumslig metod, och därigenom minska det totala antalet partiklar genom partikelsammanslagning och -splittring, och implementera en tidsmässig metod, och därigenom minska arbetsbelastningen genom att frysa vissa partiklar i tiden. Båda dessa teknikers prestanda kommer sedan att testas och analyseras i flera scenarier. Metod. Metoder för rumslig- och tidsmässig adaptivitet implementerades i en befintlig snösimulator. Metoderna både mättes och jämfördes med hjälp av kvantitativa tester i tre olika scener med varierande partikelantal. Resultat. Prestandatester visar att både den rumsliga och tidsmässiga adaptiviteten minskar exekveringstiden jämfört med basmetoden. Förbättringarna från tidsmässig adaptivitet är konsekvent runt 1,25x medan den rumsliga adaptiviteten visar en större bredd av förbättringar mellan 1,23x och 2,86x. Kombinering av båda adaptiva teknikerna ger en förbättring på upp till 3,58x. Slutsatser. Både rumsligt och tidsmässigt adaptiva tekniker är användbara sätt att förbättra prestandan för en DEM-baserad snösimulering. Den nuvarande implementationen har vissa problem med prestanda och med de visuella resultaten vid användning av rumslig adaptivitet, men det finns mycket potential för framtiden.

The primary aim of this dissertation is to map the geology of the East Rand Basin accurately by creating a 3D model. This was done by using borehole data from the National Groundwater Archive Geodatabase, which the Department of Water and Sanitation collected, and the average depths derived from the literature. Triangulated irregular networks (TINs) and digital elevation models (DEMs) surfaces were created from these data points to determine the depths for areas with no borehole data. Using these surfaces, three methods were used to create three main models. These models were then compared to one another, other geological maps and cross-sections to determine the most accurate and practical model of the three. It was found that the quality and quantity of the data from the National Groundwater Archive Geodatabase were not sufficient for these models; therefore, the results and accuracy of each layer was questionable. This dissertation found that these methods can be used for basic geological studies if the data are of the same quality and quantity. However, if the data are more evenly distributed and higher in quantity, these methods can be used to create more accurate models. Furthermore, the use of commercial software was recommended in this study. The reason for recommending these tools is that they have been specifically designed to create geological layers from boreholes within the ArcGIS software. These tools also allow the user to create cross-sections within ArcGIS. / MSc (Geography and Environmental Management), North-West University, Potchefstroom Campus, 2015

The primary aim of this dissertation is to map the geology of the East Rand Basin accurately by creating a 3D model. This was done by using borehole data from the National Groundwater Archive Geodatabase, which the Department of Water and Sanitation collected, and the average depths derived from the literature. Triangulated irregular networks (TINs) and digital elevation models (DEMs) surfaces were created from these data points to determine the depths for areas with no borehole data. Using these surfaces, three methods were used to create three main models. These models were then compared to one another, other geological maps and cross-sections to determine the most accurate and practical model of the three. It was found that the quality and quantity of the data from the National Groundwater Archive Geodatabase were not sufficient for these models; therefore, the results and accuracy of each layer was questionable. This dissertation found that these methods can be used for basic geological studies if the data are of the same quality and quantity. However, if the data are more evenly distributed and higher in quantity, these methods can be used to create more accurate models. Furthermore, the use of commercial software was recommended in this study. The reason for recommending these tools is that they have been specifically designed to create geological layers from boreholes within the ArcGIS software. These tools also allow the user to create cross-sections within ArcGIS. / MSc (Geography and Environmental Management), North-West University, Potchefstroom Campus, 2015

Many powders and particulate solids are stored and handled in large quantities across various industries. These solids often encounter handling and storage difficulties that are caused by the material cohesion. The cohesive strength of a bulk material is a function of its past consolidation stress. For example, high material cohesive strength as a result from high storage stresses in a silo can cause ratholing problems during discharge. Therefore, it is essential to consider the stress-history dependence when evaluating such handling behaviour. In recent years the Discrete Element Method (DEM) has been used extensively to study the complex behaviour of granular materials. Whilst extensive DEM studies have been performed on cohesionless solids, much less work exists on modelling of cohesive solids. The commonly used DEM models to model adhesion such as the JKR, DMT and linear cohesion models have been shown to have difficulty in predicting the stress-history dependent behaviour for cohesive solids. DEM modelling of cohesive solid at individual particle level is very challenging. To apply the model at single particle level accurately would require one to determine the model parameters at particle level and consider the enormous complexity of interfacial interaction. Additionally it is computationally prohibitive to model each and every individual particle and cohesion arising from several different phenomena. In this study an adhesive elasto-plastic contact model for the mesoscopic discrete element method (DEM) with three dimensional non-spherical particles is proposed with the aim of achieving quantitative predictions of cohesive powder flowability. Simulations have been performed for uniaxial consolidation followed by unconfined compression to failure using this model. Additionally, the scaling laws necessary to produce scale independent predictions for cohesionless and cohesive solids was also investigated. The influence of DEM input parameters and model implementation have been explored to study the effect of particle (meso-scale) properties on the bulk behaviour in uniaxial test simulation. The DEM model calibration was achieved using the Edinburgh Powder Tester (EPT) – an extended uniaxial tester to measure flowability of bulk solids. The EPT produced highly repeatable flowability measurements and was shown to be a good candidate for DEM model calibration. The implemented contact model has been shown to be capable of predicting the experimental flow function (unconfined compressive strength versus the prior consolidation stress) for a limestone powder which has been selected as a reference solid in the Europe wide PARDEM research network. Contact plasticity in the model is shown to affect the flowability significantly and is thus essential for producing satisfactory computations of the behaviour of a cohesive granular material. The model predicted a linear relationship between a normalized unconfined compressive strength and the product of coordination number and solid fraction. Significantly, it has been found that contribution of adhesive force to the limiting friction has a significant effect on bulk unconfined strength. Failure to include the adhesive contribution in the calculation of the frictional resistance may lead to under-prediction of unconfined strength and incorrect failure mode. The results provide new insights and propose a micromechanical based measure for characterising the strength and flowability of cohesive granular materials. Scaling of DEM input parameters in a 3D simulation of the loading regimes in a uniaxial test indicated that whilst both normal and tangential contact stiffness (loading, unloading, and load dependent) scales linearly with radius of the particle, the adhesive forces scales with the square of the radius of the particles. This is a first step towards a mesoscopic representation of a cohesive powder that is phenomenological based to produce the key bulk characteristics of a granular solid and the results indicate that it has potential to gain considerable computational advantage for large scale DEM simulations. The contact model parameters explored include particle contact normal loading stiffness, tangential stiffness, and contact friction coefficient. The DEM model implementation parameters included numerical time step, strain rate, and boundary condition. Many useful observations have been made with significant implications for the relative importance of the DEM input parameters. Finally the calibration procedure was applied to a spray dried detergent powder and the simulation results are compared to whole spectrum of loading regime in a uniaxial experiment. The experimental and simulation results were found to be in reasonable agreement for the flow function and compression behaviour.

Syftet med denna studie är att med hjälp av kvalitativ metod få en förståelse till vilka strategier invandrare väljer att använda sig utav för att etablera sitt liv i ett nytt land. Frågeställningarna i denna studie är: Hur upplevs förändringsprocessen från flyktingskap till etablering i ett nytt samhälle? Vilka utmaningar upplever människor i dessa processer?

Debris-flows pose serious hazards to communities in mountainous regions of the world and are often responsible for loss of life and damages to infrastructure. Characterised by high flow velocity, large impact forces and long runout, debris-flows have potential discharges several times greater than clear water flood discharges and possess much greater erosive and destructive potential. In combination with poor temporal predictability, they present a significant hazard to settlements, transport routes and other infrastructure located at the drainage points (fan-heads) of watersheds. Thus, it is important that areas vulnerable to debris-flows are identified in order to aid decisions on appropriate land-uses for alluvial fans. This research has developed and tested a new GIS-based procedure for identifying areas prone to debris-flow hazards in the Coromandel/Kaimai region, North Island, New Zealand. The procedure was developed using ESRI Arc View software, utilising the NZ 25 x 25 m DEM as the primary input. When run, it enabled watersheds and their associated morphometric parameters to be derived for selected streams in the study area. Two specific parameters, Melton ratio (R) and watershed length were then correlated against field evidence for debris-flows, debris-floods and fluvial processes at stream watershed locations in the study area. Overall, strong relationships were observed to exist between the evidence observed for these phenomena and the parameters, thus confirming the utility of the GIS procedure for the preliminary identification of hydrogeomorphic hazards such as debris-flow in the Coromandel/Kaimai region study area. In consideration of the results, the procedure could prove a useful tool for regional councils and CDEM groups in regional debris-flow hazard assessment for the identification of existing developments at risk of debris-flow disaster. Furthermore, the procedure could be used to provide justification for subsequent, more intensive local investigations to fully quantify the risk to people and property at stream fan and watershed locations in such areas.

Across industry the majority of raw materials handled are particulate in nature, ranging in size and properties from aggregates to powders. The stress regimes experienced by the granular solids vary and the exhibited bulk behaviours can be complex and unexpected. The prevalence of granular solids makes them an area of interest for industry and researchers alike as many challenges still remain, such as dealing with complex cohesive behaviour in materials, which often gives rise to handling difficulties. Storage and transportation are an important part of the process chain for industries where particulate solids are commonplace. Failure to properly account for the cohesive nature of a particulate solid can be costly as it can easily lead to blockages in a silo such as ratholing or arching near the outlet during discharge. The cohesive strength of a bulk material depends on the consolidation stress it has experienced. As a result, the stress history in the material leading up to a handling scenario needs to be considered when evaluating its handling behaviour. The Discrete Element Method (DEM) has been extensively used to simulate the behaviour of granular materials, however the majority of the focus has been on noncohesive systems. For cohesive solids, it is crucial that the stress history dependent behaviour is adequately captured. Many of the contact models commonly used in DEM simulations to simulate cohesive granular materials such as the JKR model or liquid bridge models are elastic in nature and may not capture the stress history dependent behaviour observed in cohesive particulate solids. A comprehensive study on the effect of cohesion arising from the addition of moisture on the behaviour of two types of LKAB iron ore fines (KPBO and KPRS) has been carried out. The addition of moisture to the sample has been found to have a significant effect on both kinds of fines. KPRS fines were found to have a much higher unconfined strength and flow function at higher moisture contents, and also show a greater increase in cohesion with the addition of moisture, while at moisture contents of less than 2% the KPBO fines demonstrate higher unconfined yield strength. The KPBO fines were also found to achieve a significantly looser initial packing at much lower moisture content when compared to the KPRS fines. The lateral pressure ratio has also been evaluated. In this study a mesoscopic adhesive contact model that accounts for contact plasticity and stress history dependency in the bulk solid, the Edinburgh Elasto-Plastic Adhesion (EEPA) mode, has been presented and mathematically verified. A parametric study of the DEM contact model parameters was conducted to gain a deeper understating of the effect of input parameters on the simulated cohesive bulk behaviour. The EEPA contact model has been used to predict an experimental flow function of KPRS iron ore fines. The contact model has demonstrated the ability to capture the stress history dependent behaviour that exists in cohesive granular solids. The DEM simulations provide a very close match to the experimental flow functions, with the predicted unconfined strengths found to be within the standard deviations of the experimental results. Investigations into the failure mode predicted by the DEM simulations show that the samples are failing from the development of shear planes similar to those observed experimentally. The effect of increasing levels of adhesion has been explored for a flat bottomed silo where the level of adhesion has been varied. The DEM simulations were found to capture the major phenomena occurring in silo discharge including the various flow zones associated with a flat bottomed silo. Funnel flow, the effective transition and mass flow which are associated with a mixed flow pattern were observed in the model silo. The location of the effective transition height was identified: above this was mass flow. The velocity determined from the discharge rate was found to be in excellent agreement with the velocity profiles found in the zones of mass flow. A high velocity core flow zone was observed above the outlet where velocities were greater than 1.25 times the mass flow velocity, VMF. The level of adhesion in the silo was found to affect the discharge rate - a reduced flow rate was found until the eventual blockage of the silo at a high level of adhesion was found. As the level of adhesion increased the probability of arching also increased, and the formation of intermittent arching behaviour was noted in the cases with higher levels of adhesion in the system. The development of both temporary and permanent cohesive arches over the silo outlet were also observed with stopped flow from the silo.

From pharmaceutical powders to agricultural grains, a great proportion of the materials handled in industrial situations are granular or particulate in nature. The variety of stesses that the matierals may experience and the resulting bulk behaviours may be complex. In agricultural engineering, a better understanding into agricultural processes such as seeding, harvesting, transporting and storing will help to improve the handling of agricultural grains with optimised solutions. A detailed understanding of a granular system is crucial when attempting to model a system, whether it is on a micro (particle) or macro (bulk) scale. As numerical capabilities are ever increasing, the Discrete Element Method (DEM) is becoming an increasingly popular numerical technique for computing the behaviour of discrete particels for both industrial and scientific applications. A look into the literature shows a lack of validation of what DEM can predict, specifically with respect to bulk behaviour. In addition, when validation studies are conducted, discrepancies between bulk responses in physical tests and numerical predictions using measured particles properties may arise. The aire of this research is to develop a methodology to calibrate DEM models for agricultural grains using data meaured in bulk physical tests. The methodology will have a wider application to granular solids in general and will advance understanding in the area of DEM model calibration. A contrasting set of granular materials were used to develop the methodology including 3 inorganic solids (single and paired glass beads, and polyethylene terephthalate pellets) and two organic materials (black eyes beans and black kidney beans). The developed methodology consists of three steps: 1. The development of bulk physical tests to measure the bulk responses that will be used to calibrate the DEM models, 2. The creation of the numerical dataset that will describe how the DEM input parameters influence the bulk responses , and 3. The optimisation of the DEM parameters using a searching algorithm and the results from Step 1 and 2. Two laboratory devices were developed to provide calibration data for the proposed methodology: a rotating drum and an confined compression test. These devices were chosen as they can produce bulk responses that are repeatable and easy to quantify, as well as generate discriminating results in numerical simulations when DEM parameters are varied. The bulk response determined from the rotating drum device was the dynamic angle of repose Ør formed when the granular material in a 40% filled drum is rotating at a speed of 7 rpm. the confined compression apparatus was used to determine the bulk stiffness of a system by monitoring the change in void ratio from the stress applied during a loading and unloading cycle. The gradient of the loading and unloadng curves termed λ and κ respectively were chosen as the bulk responses to calibrate the DEM models. The experimental results revealed that the dynamic Ør was significantly influences by the particle aspect ration and boundary conditions. The stiffness parameters were found to be predominantly influences by the initial packing arrangement. The numerical dataset describing how the DEM input parameters influence the numerical bulk responses was created by simulating the bulk physical tests, varying selected DEM parameters and monitoring the effects on bulk parameters. To limit the number of simulations required, design of experiment (DOE) methods were used to determine a reduced factorial matrix of simulations. In additions, an extensive parametric investigation on the non-optimised parameters as well as a scaling sensitivity study was carried out. The final step in determining the optimised parameters is to use a searching algorithm to infer the DEM parameters based on the numerical dataset and used the experimental results as calibration data. To perform a comparative study, tow searching algorithms were explored: the first was a simple method based on Microsoft Excel's Solver algorithm coupled with a weighted inverse distance method. The second made used of the statistical analysis program Statistica. It was shown that the Excel Solver algorithm is simpler and quicker to use but for the present first implementation, could only perform an optimisation based on two bulk responses. Statistica required the creation of a staistical model based on the numerical dataset before using the profiling and desirability searching technique, but was able to optimise the parameter using all three bulk responses. A verification and validation of the optimisation methodology was conducted using the optimised parameters for the black eyed beans. A verification was cnducted by simulating the two calibration experiments using the optimsed parameters and comparing these with the experiments. In addition, a validation was peformed by predicting the response of ta shallow footing penetration on a bed of black eyed beans. It was found that DEM simulations using optimised parameters predicted vertical stress on the footing during penetration to an acceptable degree of accuracy for industrial applications (<10%) at penetration depths up to 30mm.

This thesis presents a new bonded particle model that accurately predicts the wideranging behaviour of cementitious materials. There is an increasing use of the Discrete Element Method (DEM) to study the behaviour of cementitious materials such as concrete and rock; the chief advantage of the DEM over continuum-based techniques is that it does not predetermine where cracking and fragmentation initiate and propagate, since the system is naturally discontinuous. The DEM’s ability to produce realistic representations of cementitious materials depends largely on the implementation of an inter-particle bonded-contact model. A new bonded-contact model is proposed, based on the Timoshenko beam theory which considers axial, shear and bending behaviour of inter-particle bonds. The developed model was implemented in the commercial EDEM code, in which a thorough verification procedure was conducted. A full parametric study then considered the uni-axial loading of a concrete cylinder; the influence of the input parameters on the bulk response was used to produce a calibrated model that has been shown to be capable of producing realistic predictions of a wide range of behaviour seen in cementitious materials. The model provides useful insights into the microscopic phenomena that result in the bulk loading responses observed for cementitious materials such as concrete. The new model was used to simulate the loading of a number of deformable structural elements including beams, frames, plates and rings; the numerical results produced by the model provided a close match to theoretical solutions.