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Numerical modelling and simulation can be used to gain insight about rock excavation processes such as rock drilling. Since rock materials are heterogeneous by nature due to varying mechanical and geometrical properties of constituent minerals, laboratory observations exhibit a certain degree of unpredictability, e.g. with regard to measured strength and crack propagation. In this work, a recently published heterogeneous bonded particle model is further developed and used to investigate dynamic rock fracture in a Brazilian disc test. The rock heterogeneities are introduced in two steps—a geometrical heterogeneity due to statistically distributed grain sizes and shapes, and a mechanical heterogeneity by distributing mechanical properties using three Weibull distributions. The first distribution is used for assigning average bond properties of the grains, the second one for the intragranular bond properties and the third one for the bond properties of the intergranular cementing. The model is calibrated for Kuru black diorite using previously published experimental data from high-deformation rate tests of Brazilian discs in a split-Hopkinson pressure bar device, where high-speed imaging was used to detect initiations of cracks and their growth. A parametric study is conducted on the Weibull heterogeneity index of the average bond properties and the grain cement strength and evaluated in terms of crack initiation and propagation, indirect tensile stress, strain and strain rate. The results show that this modelling approach is able to reproduce key phenomena of the dynamic rock fracture, such as stochastic crack initiation and propagation, as well as the magnitude and variations of measured quantities. Furthermore, the cement strength is found to be a key parameter for crack propagation path and time, overloading magnitudes and indirect tensile strain rate., Validerad;2024;Nivå 2;2024-06-26 (joosat);Full text license: CC BY, DigiRock

En viktig detalj vid vägbyggen är att säkerställa en ordentlig vidhäftning hos beläggningsfogar mellan olika material för att förhindra uppkomsten av tidiga skador på beläggningarna. Riskerna för skador ökar när ett asfaltlager läggs bredvid ett lager med betydligt styvare och jämnare material så som betong. Exempel på dessa fogar kan ses vid busshållplatser, brodäck, spårvagnsplattor etc. En del praktiska försök att bygga sådana fogar med högre kvalitet än brukligt har gjorts men det finns fortfarande ett behov av en vetenskaplig och standardiserad metod för att testa fogar. Detta projekt syftar till att ge ett vetenskapligt underlag om möjliga effekter av olika byggmetoder på kvaliteten på beläggningsfogar mellan angränsande asfalt- och betongskikt. Projektet genomfördes dels med modelleringar och dels i en experimentell del. Modelleringsdelen gjorde det möjligt att undersöka möjliga effekter av olika konstruktionsparametrar på skjuvkapaciteten hos beläggningsfogar. I laboratoriedelen produceras betong-vs-asfaltfogar och utvärderades med hjälp av nyutvecklade mekaniska tester för att karaktärisera deras skjuv- och direkta draghållfastheter. Metodiken och de erhållna resultaten från detta projekt kan användas som underlag för att bygga högkvalitativa beläggningsfogar mellan betong- och asfaltbeläggningar i framtiden., One of the important considerations in road construction is to provide a proper adhesion at the pavement joints between different materials to prevent the initiation of premature failures on pavements. The situation becomes even more critical when an asphalt layer meets a layer with a significantly stiffer and smoother material such as concrete. Examples of these joints can be seen at bus stops, bridge decks, tram slabs, etc. Despite some practical attempts to build such joints with better quality, there is still a need for a scientific method to find solutions with the capacity of becoming standardized for further use in the road industry. This project aims to provide a scientific basis about possible effects of different construction methods on the quality of pavement joints between adjoining asphalt and concrete layers. Hence, an investigation consisting of a modeling and an experimental part was carried out. The modeling part enabled investigating possible impacts of different construction parameters on improving the shear capacity of pavement joints. In addition, the laboratory part helped producing concrete-vs-asphalt joints and evaluating them with newly developed mechanical tests for their shear and direct tensile strengths. The methodology as well as the obtained results of this project can be used as a basis for constructing high quality pavement joints between concrete and asphalt pavements in future., Undersökning av konstruktionens påverkan på beläggningsfogars mekaniska egenskaper mellan ett asfaltmaterial och ett icke-asfaltmaterial / Investigation of the influence of construction on the mechanical properties of pavement joints between an asphalt and a non-asphalt mater

Aufgrund der steigenden Bedeutung von filigraneren, leichteren und damit nachhaltigeren Betonstrukturen wird der Bedarf an ultrahochfesten Betonen (UHPC - ultra-high performance concrete) immer größer. Trotz der beeindruckenden mechanischen Eigenschaften muss festgehalten werden, dass die Toleranz gegenüber zyklischen Belastungen im Vergleich zu Normalbeton deutlich reduziert ist. Bisher erfolgte die Beschreibung des Ermüdungswiderstandes über makroskopische Zusammenhänge. Eine Untersuchung der Mechanismen auf kleineren Skalen fand im Hinblick auf die Ermüdungsproblematik aber nicht statt. Infolgedessen verfolgt diese Arbeit das Ziel, ermüdungsinduzierte Schädigungen auf der Nano-, Mikro- sowie Meso- und Makroskala mithilfe experimenteller (REM, TEM) und numerischer Methoden (Bonded Particle Model) zu untersuchen. Im Zuge einer umfangreichen mechanischen Charakterisierung eines UHPC wurden sowohl statische als auch zyklische Versuche durchgeführt. Ein eigens entwickeltes rheologisches Ermüdungsmodell ermöglichte es, Ermüdungssimulationen durchzuführen, welche die essenziellen Ermüdungscharakteristika des Materials wiedergeben. Hervorzuheben ist dabei der schädigende Einfluss der Gesteinskörnung, der zu Spannungsspitzen im Gefüge führt und somit eine Schlüsselrolle in den mesoskaligen Schädigungsmechanismen spielt. Darüber hinaus wurde im Rahmen dieser Arbeit eine Zyklensprungmethode entwickelt, um tiefergehende Einblicke während hochzyklischer Belastung zu erlangen. Diese Methode wurde in Verbindung mit Erkenntnissen über den Einfluss des unhydratisierten Zements auf die Bruchlastspielzahlen gebracht, wodurch mögliche Erklärungen für die beobachteten experimentellen Streuungen gezeigt werden konnten. Zudem zeigten TEM Untersuchungen signifikante Gefügeveränderungen in der C-S-H-Struktur und eine Ausbildung von Rissvorstufen während der Ermüdung. Durch eine höhere Konzentration von Schwefel und Aluminium im umliegenden Bereich der Rissvorstufen wird vermutet, dass di, Due to the growing demand for more delicate, lighter and therefore more sustainable concrete structures, the need for UHPC is becoming more and more significant. Despite the impressive mechanical properties, it must be noted that the tolerance to cyclic loads is significantly reduced compared to normal concrete. Until now, the description of fatigue resistance has been based on macroscopic relationships. However, an investigation of the mechanisms on smaller scales did not take place with regard to the fatigue problem. Consequently, this work pursues the goal of investigating fatigue-induced damage on the nano, micro, meso and macro scales using experimental (SEM, TEM) and numerical methods (Bonded-Particle-Model). In the scope of mechanical characterisation of the UHPC, both static and cyclic tests were carried out. A specially developed rheological fatigue model made it possible to carry out fatigue simulations that reflect the essential fatigue characteristics of the material. The damaging influence of the aggregate, which leads to stress peaks in the microstructure and thus plays a key role in the mesoscale damage mechanisms, should be emphasised. Furthermore, a cycle jump method was developed within the scope of this work in order to gain deeper insights during high-cycle loading. This method was combined with findings on the influence of the unhydrated cement on the fracture load cycles, showing possible explanations for the observed experimental scatter. In addition, TEM investigations showed significant microstructural changes in the C-S-H structure and a formation of crack precursors during fatigue. Due to a higher concentration of sulphur and aluminium in the surrounding area of the crack precursors, it is suspected that the changes are associated with the presence and recrystallisation of ettringite. The joint coupling of the applied experimental and numerical methods proved to be an effective tool for the investigations on nano, micro, meso and macro sca, Deutsche Forschungsgemeinschaft (DFG)

Dune systems have recently become fundamental natural solutions for the protection of the coast. The study of its morphodynamic features in storm situations is well documented in the literature. However, the morphological behaviour of these ecosystems when they are artificially modified by humans is still not adequately known. In this study, the morphological parameters of the restored dunes of Viveros Beach in Guardamar del Segura, Spain, are analysed. For this, a profile study was carried out using digital elevation models (DEM). In addition, the waves and incident storms are studied and, finally, a statistical analysis of the different variables that define the three dune zones is conducted. Results show that during periods of increased wave intensity and duration (2016–2017 and 2017–2020), there is correspondingly greater erosion in the dune. Additionally, the slope and the height of the dune present a strong correlation with changes in its volume. Greater volumetric losses occur the greater the slope of the foredune and the dune height. This situation occurs especially in the northernmost area, located next to the breakwater at the mouth of Segura River (Zone 1), where they reach up to 53° and 10.24 m, respectively. A better understanding of these factors provides coastal managers with effective tools for designing new dune landforms or conserving existing ones.

Gap-graded granular soils have a wider grain size distribution and more heterogeneous fabric structure than normal soils. It is critical to choose the sample size of element tests in a faithful and repeatable manner. The Discrete Element Method (DEM) is utilized to determine the size of representative volume element (RVE) of gap-graded mixtures with varying particle size distributions. Over seven hundred triaxial tests are performed to investigate the effect of particle size ratio and coarse fraction on the typical RVE size. Microscopic parameters are analyzed to validate the reproducibility of the determined RVE sizes. The optimal RVE size is negatively proportional to particle size ratio and positively correlated with the coarse fraction. Empirical equations are further established to correlate the RVE sizes with particle size ratios for different coarse fractions. The findings may provide a useful reference for experimental and numerical studies in choosing the RVE size for gap-graded soils. © 2023

Macromolecular structural formation and hierarchical self-assembly is crucial for a variety of systems in both nature and technology. Such systems may retain a remarkable structural organization from the atomistic up to the macroscopic scale enabling crucial features for their function. Many of these systems achieve this through self-assembly and consequently do not rely on external assembly mechanisms. In the field of material science one example is hydrogels, which achieve significant mechanical strength through polymer network formation on the molecular level. In the field of biology examples are abundant including most enzymes and viruses. One example is the hepatitis B virus, which contains a structural protein that assembles into regular spherical structures to transport the genetic material of the virus. Another example is the pyruvate dehydrogenase complex, which is crucial for cellular respiration and achieves its high biocatalytic activity through structural formation, thereby enabling features such as metabolic channeling. While there is an abundant amount of examples, investigation is challenging both experimentally and numerically. The phenomena involved in such structural assembly spread over vast scales in length and time and contain not only regular structures, but often also disordered elements. Consequently, capturing the mechanisms of formation, especially their kinetics, is inherently difficult. In order to improve understanding of these phenomena, this work proposes a physics-based and data-driven multiscale modeling framework capable of describing structural formation on the micro-meter and milli-second scale, while retaining large amounts of molecular detail. The framework achieves this by abstracting the elementary macromolecules of a system as anisotropic unit objects and describes the interaction between units as well as the environment through data-driven models, e.g. 6D interaction potential fields. The models are parameterized in a botto, Deutsche Forschungsgemeinschaft (DFG), Höchstleistungsrechenzentrum Stuttgart (HLRS)

Landslides are one of the most widespread, yet difficult to predict, geohazards in the world. Theyrepresent a major threat to society, which is why it is so important to understand and study them.Landslide detection is one of the approaches that help scientists to gain a better knowledge of landslides,how they form and the characteristics they hold. In this work, a new landslide detection technique istested in the Klarälven Region, Sweden. The method involves using multi-temporal DEMs generatedfrom LiDAR point clouds from 2010 and 2020. Once two respective DEMs are generated from theoriginal point cloud data sets, a DEM of Difference (DoD) is obtained by subtracting the 2010 DEMfrom the 2020 DEM. The DoD highlights areas of vertical change over the ten-year period. In order todetect potential landslides, a Level of detection (LoD) threshold is applied, as well as a second upperthreshold filtering out elevation difference resulting from anthropogenic activities. Lastly, a spatialthreshold is applied to eliminate any remaining potential errors clusters that are too small to belandslides. Once this stage is completed, the study area is surveyed, focusing on certain areacharacterised by particular slope angles and soil types most likely to exhibit mass movement. Thishelped in the analysis and interpretation of the data. In order to discuss the results as fully as possible,four types of region were studied in more detail using four representative examples. Since a few doubtfulcases were found, potential sources of error are also being explored. Despite minor inaccuracies, themethod appears to be a relevant technique for detecting differences in altitude, even if it also considersunnatural mass movements.

The dynamic fracture process of rock materials is of importance for several industries, such as the rock drilling process in geothermal and mining applications. Gaining knowledge and understanding of dynamic rock fracture through numerical simulations can enhance the rock drilling process, for example by optimising the drill bit geometry and drilling parameters. In order for a numerical simulation of rock fracture processes to be accurate, the model needs to be able to capture key aspects of rock materials. Generally, rock materials are said to be britle and heterogeneous. The heterogeneity is partly due to the varying mechanical properties of constituent minerals, and partly due to the varying sizes, shapes, and directions of these minerals. The main objective of this thesis is the development of a heterogeneous rock model to be used for dynamic drilling processes. In the first article in this thesis, a heterogeneous bonded particle model is developed. Here, the heterogeneity is introduced in two steps – a geometrical heterogeneity using statistically distributed grain shapes and sizes, and a mechanical heterogeneity by distributing bonding parameters using a Weibull distribution. The model is applied to the quasi-static Brazilian disc test and a parametric study is conducted on the heterogeneity index and intergranular cement strength. The results show that crack initiation and propagation are highly dependent on the degree of heterogeneity. In general, the model was found to replicate typical phenomena associated with britle heterogeneous materials, for example unpredictability of macroscopic strength and crack properties. In the second paper of this thesis, an extensive dynamic experimental characterization of two igneous rock materials – Kuru grey granite and Kuru black diorite – is conducted. Here, a Split-Hopkinson configuration together with high-speed photography and digital image correlation is utilized to obtain the compressive and indirect tensile behavi

Bed permeability is a crucial factor in blast furnace performance which depends on the material distribution achieved through charging. Since a homogeneous bed of pellet and sinter is recommended, it is crucial to understand whether segregation of the pellet-sinter mixture occurs during charging. The Discrete Element Method is useful in this regard; however, simulations of pellet-sinter mixture charging currently lack credibility since pellet-sinter interaction parameters have not yet been calibrated and validated. Determining pellet-sinter interaction parameters will require significant efforts, so it is useful to know whether mixture segregation and the resulting bed permeability are sensitive to these parameters. In this work, we investigate to what extent the restitution coefficient, sliding friction coefficient and rolling friction coefficient between pellet and sinter affect segregation during bed formation and the resulting permeability in terms of porosity using a simplified charging setup. The investigation is done for different mixture compositions and flow velocities, and analysis settings including sample size and sampling directions. We conclude that all parameters affect segregation and porosity, regardless of the composition and velocity. Hence, all mixture parameters including the interaction parameters between the components must be carefully calibrated when developing a model for predicting permeability., Transport Engineering and Logistics

A convex pattern surface is proposed and optimized to mitigate the sliding wear of bulk handling equipment caused by interaction with bulk solids. This work investigates the effectiveness of the convex pattern surface on wear reduction during interactions with non-spherical particles. Multiple representative particles, obtained through a sampling method, are reconstructed using a photogrammetry technique. Two contact parameters between particles are calibrated through shear box and drawdown tests to ensure flow behavior similar to the real material. The numerical results indicate that the convex pattern surface can effectively reduce wear compared to a plain sample when involving both spherical and non-spherical particles. For a plain sample, the wear volume remains independent of particle shapes and increases linearly with numerical revolutions. For the convex pattern surface, the wear volume demonstrates a quadratic relationship with the test revolutions as the deformation of convex elements weakens the effectiveness of the sample on wear reduction. The particle flow behavior analysis reveals that the convex pattern surface experiences the lowest wear volume when in contact with non-spherical particles. This can be attributed to the non-spherical particles sliding shorter distances and rotating with higher angular velocities on the convex pattern surface., Transport Engineering and Logistics, Marine and Transport Technology, Offshore and Dredging Engineering

Geomorphometric analysis provides crucial insights into the hydrological characteristics by delineating the land-surface features of a drainage basin. The study focused on analyzing the geomorphometric parameters of the Montenegrin segment of the Ibar River drainage basin using the ALOS Global Digital Surface Model 30 m (AW3D30). Geomorphometric parameters, covering linear and areal parameters, were computed using standard mathematical formulas in LibreOffice Calc software and hydrology tools in commercial GIS software ArcGIS, as well as open-source software QGIS with SAGA GIS modules. Results reveal a dendritic pattern in the stream network, with an inverse relationship between stream length and order, and an elevated bifurcation ratio indicating heightened vulnerability to flooding, influenced by geological, geomorphological, and climatic factors. Furthermore, examination of diverse areal morphometric parameters, such as drainage density, stream frequency, form factor, circularity ratio, and elongation ratio, unveils the hydrological dynamics of the Ibar basin. This characterization illustrates the region as possessing high permeability and dense vegetation cover, suggesting vulnerability to erosion and consequent effects on water and sediment discharge. Additionally, this study underscores the significance of user-defined parameters in geomorphometric modeling, particularly in selecting algorithms within analysis software, which significantly impact drainage basin parameters.

Currently, one of the biggest challenges humanity faces is climate change. Reduction of fossil fuels is demanded in the future, hence an energy transition is required. A promising potential alternative fuel is the energy carrier NaBH4 which contains hydrogen (H2). Handling and storing NaBH4 provides challenges and the bulk behaviour of NaBH4 is not well-known. NaBH4 is potentially affected by time consolidation when storing the material inside a silo and to capture the effect on NaBH4 a method to model time consolidation using the Discrete Element Method is proposed. To calibrate the simulation model, data is required and to gather data, time consolidation experiments were performed using Schulze's Ring Shear Tester. The shear stress was determined for different consolidation times. Next, the simulation model's two most influential parameters (static friction and surface energy) were selected to calibrate and verify the contact model based on the experimental data. The found relationship of the two parameters over time can be used to instantly create a time-consolidated particle bed after a certain consolidation time, reducing the computational time required to analyse the material behaviour after longer storage periods., Marine Technology | Transport Engineering and Logistics

Human civilization has an increasingly powerful influence on the earthsystem. Affected by climate change and land-use change, floods are occurringacross the globe and are expected to increase in the coming years. Currentsituations urge more focus on efficient monitoring of floods and detecting impactedareas. Earth observations are an invaluable source for monitoring theEarth’s surface at a large scale. In particular, the Sentinel-1 Synthetic ApertureRadar (SAR) and Sentinel-2 MultiSpectral Instrument (MSI) missionsoffer high-resolution data with frequent global revisits that are widely usedfor flood detection.Current solutions such as Copernicus Emergency Management Services(CEMS), MODIS (Moderate Resolution Imaging Spectroradiometer) globalflood product, and many others use data from Sentinel and multiple othersatellites to detect floods. Although existing solutions are helpful, they alsohave several limitations. For instance, solutions like MODIS global floodproduct detect floods solely on optical images causing poor or no detection incloudy areas. In addition, these solutions are threshold-based and often requirecriteria-based adjustments. Furthermore, these solutions do not leveragerich spatial information between neighboring pixels and don’t use temporalfeatures of time series data. Therefore, advanced processing algorithms areneeded to provide a reliable method for flood detection.This thesis presents three Deep Learning (DL) models for flood detection.The first two models are supervised segmentation models proposed todetect floods on uni-temporal Sentinel-1 SAR data. The study sites containfloods from Bolivia, Ghana, India, Mekong, Nigeria, Pakistan, Paraguay,Somalia, Spain, Sri Lanka and USA. The third model is an unsupervised spatiotemporalchange detection (CD) model that detects floods on time series ofSentinel-1 SAR data. The study sites contain floods from Slovakia, Somalia,Spain, Bolivia, Mekong, Bosnia, Australia, Scotland and Germany.The two supervise, Den mänskliga civilisationen har ett allt starkare inflytande på jordsystemet. Påverkad av klimatförändringar och förändringar i markanvändningen sker översvämningar över hela världen och förväntas öka under de kommande åren. Nuvarande situationer kräver mer fokus på effektiv övervakning av översvämningar och upptäckt av drabbade områden. Jordobservationer är en ovärderlig källa för att övervaka jordens yta i stor skala. Särskilt Sentinel- 1 Synthetic Aperture Radar (SAR) och Sentinel-2 MultiSpectral Instrument (MSI)-uppdrag erbjuder högupplösta data med frekventa globala återbesök som används ofta för att detektera översvämningar. Aktuella lösningar som Copernicus Emergency Management Services (CEMS), MODIS (Moderate Resolution Imaging Spectroradiometer) globala översvämningsprodukter och många andra använder data från Sentinel och flera andra satelliter för att upptäcka översvämningar. Även om befintliga lösningar är användbara, har de också flera begränsningar. Till exempel upptäcker lösningar som MODIS globala översvämningsprodukt översvämningar enbart på optiska bilder som orsakar dålig eller ingen detektering i molniga områden. Dessutom är dessa lösningar tröskelbaserade och kräver ofta kriteriebaserade justeringar. Dessutom utnyttjar dessa lösningar inte rik rumslig information mellan angränsande pixlar och använder inte tidsseriedata. Därför behövs avancerade bearbetningsalgoritmer för att tillhandahålla en tillförlitlig metod för översvämningsdetektering. Denna avhandling presenterar tre modeller för djupinlärning (DL) för översvämningsdetektering. De två första modellerna är övervakade segmenteringsmodeller som föreslagits för att upptäcka översvämningar på uni-temporala Sentinel-1 SAR-data. Studieplatserna innehåller översvämningar från Bolivia, Ghana, Indien, Mekong, Nigeria, Pakistan, Paraguay, Somalia, Spanien, Sri Lanka och USA. Den tredje modellen är en oövervakad modell för upptäckt av spatiotemporal förändring (CD) som detekterar översvämningar på, QC 20231030

Cone crushers are used in both the construction and mining industries for the production of aggregates and extraction of ores. Aggregates are used when building for example houses, roads and railways, hence the cone crushers are a vital part of modern society. To ensure the performance of the cone crusher, it is important to properly adjust the feeding conditions. Using computational methods to virtually analyze the performance of the crushers is a more time and cost efficient solution compared to physical testing. This thesis was divided into two parts, where the main objective of the first part was to use the discrete element method (DEM) to analyze the segregation in cone crushers. Three different methods were developed, which later were utilized to compare the segregation for four different feeding conditions. Two of the analysis methods only considered the segregation in the feed hopper, whilst the third method aimed to give an understanding ofthe segregation inside the crushing chamber. The two first methods could successfully be used to compare how segregated the feed material was for the four feeding conditions, however, the third method proved to be both hard to validate and highly dependent on proper material flow inside the crushing chamber. The main objective during the second part of the thesis was to investigate the possibility of running the DEM simulations coupled to a multibody simulation (MBS) software. The simulation routine was then used to compare the foundation loads for the same four feeding conditions as in the first part. The subframe was later modeled as a flexible body to analyze and compare the stresses the subframe was subject to during operation for the same four feeding conditions. Setting up and running the coupled simulation was successful. Different simulation settings were tested, anda general guideline on how those settings should be defined was set up. The actual impact the coupling had on the foundation loads and stresses in the

The out-of-plane flexural bending capacity of masonry is a fundamental property for understanding the behavior of masonry structures. This study investigates the behavior of unreinforced masonry wallettes subjected to combined compression-flexural loading using the discrete element method (DEM), and provides a novel framework to estimate the masonry strength. A simplified micro-modeling strategy is utilized to analyze a masonry wallette, including the variation of the mechanical properties in masonry units and joints. Stochastic DEM analyses are performed to simulate brickwork assemblages, assuming a strong unit-weak joint material model typical of most masonry buildings, including historical ones. Once the proposed computational approach is validated against the experimental findings, the effect of spatial and non-spatial variation of mechanical properties is explored. Two failure types are identified: joint failure and brick failure. For each failure mechanism, the variability of the response and the effects of the modeling parameters on the load-carrying capacity is quantified. Afterward, Lasso regression is employed to determine predictive equations in terms of the material properties and vertical pressure on the wallette. The results show that the most important parameters changing the response are the joint tensile strength and the amount of vertical stress for joint failure, whereas the unit tensile strength dominates the response for brick failure. Overall, this research proposes a novel framework adopting validated advanced computational models that feed on simple test results to generate data that is further utilized for training response prediction models for complex structures., Peer Reviewed, Postprint (published version)

The Discrete element method (DEM) is a methodology to investigatethe interactions among granular materials. It analyzes the behavior of par-ticulate environments by solving force-displacement equations that adhereto Newton’s second law of motion. Despite its usefulness, the DEM is notwithout limitations, and researchers are still facing certain challenges thatrestrict them from performing detailed analyses of granular materials. Thisstudy addresses two issues in DEM modeling of granular materials in rail-way embankments. Firstly, the long computational time required by theDEM for modeling fine angular particles in granular materials is addressedby exploring the effects of particle scaling on the shear behavior of granularmaterial. This study investigates the impact of particle size distribution,particle angularity, and the amount of scaling on the accuracy and compu-tational efficiency of DEM. Secondly, the limitations of DEM in includingthe continuous rail beam structure in the track are addressed by verifyinga DEM model against physical measurements of a full-scale ballasted trackand investigating the influence of including the rail beam structure on high-speed railway ballasted tracks. The results show that the use of particlescaling in the first study significantly improves the computational efficiencyof the DEM while maintaining accuracy, and this method is used in thesecond study to investigate the influence of the rail beam structure on thebehavior of railway tracks., Diskreta elementmetoden (DEM) är en effektiv metod för att undersö-ka interaktioner i granulära material. Metoden analyserar samverkan mellanpartiklar genom att lösa kraft-deformationsekvationer som följer Newtonsandra lag. Trots dess användbarhet har DEM vissa begränsningar och fors-kare stöter fortfarande på vissa utmaningar som hindrar dem från att ge-nomföra detaljerade analyser av granulära material. Denna studie tar upptvå frågeställningar vid DEM-modellering av granulära material i järnvägs-bankar. För det första behandlas den långa beräkningstiden som krävs föratt modellera granulära material genom att utforska effekterna av parti-kelskalning på skjuvbeteendet. Studien undersöker effekten av partikelstor-leksfördelning och spetsighet på noggrannheten och beräkningseffektivite-ten. För det andra behandlas begränsningarna hos DEM när det gäller attinkludera den kontinuerliga rälsstrukturen i spåret genom att verifiera enDEM-modell mot fysiska mätningar av ett ballasterat spår i full skala ochundersöka inverkan av att inkludera rälsstrukturen. Resultaten i den förstastudien visar att tillämpningen av partikelskalning avsevärt förbättrar be-räkningseffektiviteten samtidigt som noggrannheten bibehålls. Partikelskal-ning används i den andra studien för att undersöka inverkan av rälsstruk-turen på beteendet hos järnvägsspår., Utform av övergångszoner för höghastighetsjvg med fix spår

Sound speed dispersion and frequency dependence of attenuation in marine sediments are important for any undersea activities using acoustics, such as remote sensing and target detection. Current established models use grain shearing and fluid viscosity as the source of loss in sediments, both of which may not be significant given the relatively small strains imposed by most acoustics' signals. In this paper, we analyze a source of attenuation due to compressional losses in grains, modeled with a dashpot term. Discrete element modelling (DEM) using Large Scale Atomic Molecular Massively Parallel Simulator (LAMMPS) was used to model motions of distinct particles in the system. A small amplitude pressure wave was introduced into the channel via an oscillating boundary wall and its effect on each discrete particle was measured to obtain the sound speed and attenuation coefficient. The measurements with sets of varying frequencies for system size of up to 50000 particles exhibit similar relationships with experimental data used for comparison in this paper. In particular, we were able to recover the observed frequency dependence of attenuation, following a power law of frequency squared at low frequencies and the square root of frequency at high frequencies for all system sizes used in our analysis. The small number of parameters used in our theory present a much more tractable and parsimonious problem for geo-acoustic inversion than the more complicated established models., Major, Republic of Singapore Navy, Approved for public release. Distribution is unlimited.

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, 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 visu

Perturbations arising from mining operations significantly affect the stability of rock masses, and the influences aggerates with the rapid increase of mining-operation depths during recent years. The subsurface structures with major discontinuities subject to seismic hazards resulted from the shear-slip behaviors of rock masses. In order to identify the shear-slip regime of discontinuities and calculate seismic moment and seismic energy involved with shear-slip behaviors, we use discrete element modeling to study the shear slip failure along discontinuities in an underground mine. The recorded characteristic and properties of sub-contacts in DEM provide a basis for computing and visualizing the temporal and spatial distribution of seismic moment and seismic energy with mining operations. We computed the seismic energy and seismic moment using the numerical modeling method and the analytic method. We compared the result of summing seismic energy and seismic moment from the subcontacts of numerical models and the result of the analytic method. We confirmed that this tool can be used in comparative analyses. We also found that seismic moment and seismic energy, associated with shear stress drop and shear displacement increase, accumulate in the vicinity of major discontinuities. Mining operations at a greater depth cause greater changes of seismic moment and seismic energy, leading to a higher risk of inducing seismic hazards. Quantifying seismic potential using discrete element modeling can greatly facilitate the investigation of instability of geological discontinuities and thereby can help estimate the potential of seismic hazards., Validerad;2023;Nivå 2;2023-02-08 (joosat);Funder: LKAB; China National Key Research and Development Program (Grant no.: 2021YFC3000603)Licens fulltext: CC BY License

The Greenland ice sheet melting status is critical for global sea level rise and climate change. Based on the CryoSat-2 altimetry data from 2011 to 2021, the 5 km × 5 km DEMs of the Greenland ice sheet were derived by adopting the kriging interpolation method. Then the changes in elevation and volume of the ice sheet were calculated by using the intersection method. The changes in the ice sheet were analysed, and the results show that: (1) The accuracy of the Greenland DEMs obtained based on satellite altimetry data is region-dependent, with better accuracy in inland areas and higher elevation errors in marginal areas. (2) The inland area elevation remains unchanged basically or even shows an increasing trend, and there is an apparent melting trend in the marginal area, especially on the west coast. The contribution of the ice sheet melting mainly comes from elevations below 2000 m. (3) The main body of the Greenland ice sheet is melting with an elevation change rate of −13.27 ± 0.86 cm·a−1 and a volume change rate of −202.47 ± 14.8 km³·a−1. The rate of the Greenland ice sheet thinning has slowed down compared with the changes from 2003 to 2009.

The Greenland ice sheet melting status is critical for global sea level rise and climate change. Based on the CryoSat-2 altimetry data from 2011 to 2021, the 5 km × 5 km DEMs of the Greenland ice sheet were derived by adopting the kriging interpolation method. Then the changes in elevation and volume of the ice sheet were calculated by using the intersection method. The changes in the ice sheet were analysed, and the results show that: (1) The accuracy of the Greenland DEMs obtained based on satellite altimetry data is region-dependent, with better accuracy in inland areas and higher elevation errors in marginal areas. (2) The inland area elevation remains unchanged basically or even shows an increasing trend, and there is an apparent melting trend in the marginal area, especially on the west coast. The contribution of the ice sheet melting mainly comes from elevations below 2000 m. (3) The main body of the Greenland ice sheet is melting with an elevation change rate of −13.27 ± 0.86 cm·a−1 and a volume change rate of −202.47 ± 14.8 km³·a−1. The rate of the Greenland ice sheet thinning has slowed down compared with the changes from 2003 to 2009.

Washino K., Chan E.L., Nishida Y., et al. Coarse grained DEM simulation of non-spherical and poly-dispersed particles using Scaled-Up Particle (SUP) model. Powder Technology 426, 118676 (2023); https://doi.org/10.1016/j.powtec.2023.118676., In this work, the validity of the Scaled-Up Particle (SUP) model, which is a novel coarse grain model for Discrete Element Method (DEM), is examined to simulate a flow of non-spherical and poly-dispersed particles. The SUP model is based on the authors’ previous work and the scaling law is derived from the continuum assumption of an arbitrary particles flow. We discuss that the model is applicable not only to spherical and mono-dispersed particles, as is the case tested in the previous work, but also to non-spherical and poly-dispersed particles. Simulations of various systems are performed such as compression of a particle bed, heap formation, high shear mixer, large scale rotary drum and V-mixer. It is shown that the results obtained from the SUP model are in both qualitative and quantitative agreement with those from the original particles as long as the resolution is sufficiently high.

The main goal of this study is to evaluate the applicability of drone usage and their respective sensors in coffee growing for a producing region in the centre of Colombia, which can be extrapolated and comparable to other zones in the country. This project aims to analysethe products obtained withRGB and multispectral sensors,evaluating the utility theymay have for coffee growers in their regular work over the year. The first analysis is focused on the development of orthophotomaps, digital elevation models and derivedproducts. Secondly,the analysis offlight planning over precipitous zones with important gradients has allowed to select which the most suitable configuration based on several flights at different heights and data acquisition conditions. The results of multispectral imaging obtained data with the different bands, showedvegetationindexes and false colour imagery, from various campaignson separate days. The objective of this part ofthe study is to also suggest a method to obtain an approximate value of the production of each smallholding, El objetivo de este estudio es valorar la aplicabilidad del uso de los drones y sus respectivos sensores en el cultivo de café para una región productora del centro de Colombia, extrapolable y comparable al resto de zonas del país. Este proyecto pretende analizar los productos obtenidos con sensores RGB y multiespectral, evaluando la utilidad que puedan tener para los caficultores en su trabajo habitual a lo largo del año. Un primer análisis se centra a modo general en la elaboración de ortofotomapas, modelos digitales de elevaciones y productos derivados. En segundo lugar, se analiza la planificación de vuelos en zonas abruptas de fuertes pendientes para seleccionar el más apropiado a partir de varios vuelos a distintas alturas y condiciones de adquisición de datos. Los resultados de los datos multiespectrales obtenidos con las diferentes bandas muestran índices de vegetación e imágenes en falso color, de diversas tomas y en distintos días. La finalidad de esta parte del estudio es, además, proponer una metodología para conseguir un aproximado de la producción por parcela.

Machine learning approaches have found immense potential to revolutionise the constitutive modelling of granular materials. However, data scarcity poses a significant challenge to this emerging paradigm. This study aims to tackle this issue by presenting two transfer learning-based strategies that harness well-established constitutive knowledge and similar material data to reduce data demands for data-driven material modelling. The first approach utilises phenomenological constitutive models to generate massive synthetic data which reflect the targeted material behaviour to train a base model. This base model is then repurposed for a new task based on numerical simulation data via transfer learning. The other approach involves using available material data to train a base model, which is then applied to other new materials that are similar but with limited data. The proposed transfer learning methods are tested on both particle-scale simulations of representative volume elements (RVEs) and hierarchical multiscale modelling of boundary value problems (BVPs) of granular materials. The trained data-driven material model is embedded in numerical simulations with the finite element method (FEM) to validate its accuracy, efficiency, and stability. The results demonstrate that transfer learning can effectively achieve high-quality machine learning predictions with limited data. The transfer learning strategy presented in this study is expected to be widely applicable to small data-driven material modelling. © 2023 Elsevier Ltd

In this paper we introduce the open-source code MercuryDPM: a code for simulating discrete particles. The paper discusses software and management issues that may be interesting for the developers of other open-source codes. Then we review the new features that have been added since the last publication: an improved Hertz-Mindlin model; a new liquid bridge model of Lian and Seville; a droplet-spray model; better support for re-creating complex, measured particle size distributions; a new implementation of rigid clumps; an implementation of elastic membranes; a wear model for walls; a soft-kill feature and a cloud-deployment interface for AWS., Transport Engineering and Logistics

Microbially induced carbonate precipitation (MICP) involves bacteria to drive calcite precipitation and naturally cement soils, thereby improving soils performance. Experimental studies have shown that bio-cemented specimen can suffer from severe spatial inhomogeneity of the calcite content, leading to large uncertainty in treatment efficiency prediction. To evaluate the effect of inhomogeneity on the mechanical behaviour of bio-cemented soils, the discrete element method (DEM) is used to model bio-cemented samples with a single carbonate distribution pattern (i.e. either bridging or contact cementing) but different characteristics of inhomogeneity. Both drained triaxial compression and triaxial extension simulations are carried out to evaluate the impact of inhomogeneity along different loading paths. The results indicate that inhomogeneity has different effects on bio-cemented samples depending on the carbonate distribution patterns and the loading path. Specifically, the shear strength in compression of samples exhibiting bridging cementation is largely affected by inhomogeneity, while the effect on shear strength in extension is negligible. On the other hand, samples with contact cementing show limited sensitivity to the variation of inhomogeneity under both triaxial compression and triaxial extension tests., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Geo-engineering

The TCRP model can be used to create a runoff pattern, taking into account the effects of tillage-induced roughness. The TCRP model has as main aim to adjust runoff patterns based on topography for tillage induced roughness. The resulting output of TCRP are runoff pattern raster maps, which can be further used as input for hydrological modelling of surface runoff processes. The methodology to create the runoff pattern includes four steps. First, a topographically controlled runoff pattern is created using the standard single-flow, steepest descent algorithm. Next, a tillage-determined runoff pattern is created, i.e. a runoff pattern based on the assumption that water will always flow in the tillage direction. Then, decision rules are applied to determine for each cell whether the water will flow in tillage direction or in topographic direction. Finally, a flow direction map can be generated by combining the topographically determined runoff pattern with the tillage-controlled runoff pattern. This repository is an updated version of the original code, adjusted to run smoothly with the current version of PCRaster (v4.4.0)

With the development of experimental measurement technology and high-fidelity numerical simulations of granular materials, empirical-based classical constitutive models may not be able to take full advantage of the rapidly increasing available datasets. Machine learning-based models can inherently avoid phenomenological assumptions to directly learn the constitutive relationship from the datasets, and the trained model is sufficiently flexible to be reconstructed once new training samples are added. In this work, a coupled finite element method and machine learning (FEM-ML) computational framework is proposed for simulating granular materials. Gaussian process-based random loading paths and coupled FEM-DEM simulations are used to generate training samples. A parametrisation of the material deformation history is used to represent the historical influence of granular materials. An uncertainty-level-based active learning is utilised to evaluate the informativeness of data points for network training and then to establish an effective resampling scheme from a massive dataset. Two examples are provided to show the applicability of the implemented FEM-ML framework. The performance of the proposed framework is also evaluated, the error is systematically analysed, and possible improvements are discussed. The results demonstrate that the FEM-ML framework offers considerable improvements in terms of computational efficiency and competence to simulate the mechanical responses of granular materials. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Das nichtlineare Dämpfungsvehalten von Partikeldämpfern und die Vielzahl an Einflussparametern hindern derzeit deren weit verbreitete industrielle Nutzung. Das Ziel dieser Arbeit ist daher die Entwicklung eines neuen Entwurfskonzeptes in Form einer Toolchain, um eine systematische Auslegung von Partikeldämpfern zu ermöglichen. Dabei werden verschiedene experimentelle als auch numerische Modelle miteinander kombiniert. Die Toolchain beginnt mit der Analyse des makroskopischen Verhaltens einzelner Partikelstöße, führt über die Analyse der Eigenschaften von vibrierenden granularen Medien und endet mit der Auslegung des Partikeldämpfers für die gewünschte Struktur. Die Wirksamkeit der Toolchain wird schlussendlich anhand von verschiedenen Beispielen demonstriert., The nonlinear damping behavior of particle dampers and the multitude of influence parameters hinder their wide industrial usage. Hence, the goal of this work is the development of a new design methodology in form of a toolchain enabling a systematic damper design. On that account, various numerical models and experimental tests are combined. The toolchain commences with investigations of the micro-mechanical behavior of single particle impacts, continues with analyzing the properties of vibrating granular matter inside different containers and ends with designing a particle damper for a desired vibrating structure. The good agreement of the experimental and numerical models and their efficiency for the damper design and dimensioning are demonstrated on multiple examples.

Libraries with pre-written codes optimize the workflow in cartography and reduce labour intensive data processing by iteratively applying scripts to implementing mapping tasks. Most existing Geographic Information System (GIS) approaches are based on traditional software with a graphical user's interface which significantly limits their performance. Although plugins are proposed to improve the functionality of many GIS programs, they are usually ad hoc in finding specific mapping solutions, e.g. cartographic projections and data conversion. We address this limitation by applying the principled approach of Geospatial Data Abstraction Library (GDAL), library for conversions between cartographic projections (PROJ) and Geographic Resources Analysis Support System (GRASS) GIS for geospatial data processing and morphometric analysis. This research presents topographic analysis of the dataset using scripting methods which include several tools: (1) GDAL, a translator library for raster and vector geospatial data formats used for converting Earth Global Relief Model (ETOPO1) GeoTIFF in XY Cartesian coordinates into World Geodetic System 1984 (WGS84) by the 'gdalwarp' utility; (2) PROJ projection transformation library used for converting ETOPO1 WGS84 grid to cartographic projections (Cassini-Soldner equirectangular, Equal Area Cylindrical, Two-Point Equidistant Azimuthal, and Oblique Mercator); and (3) GRASS GIS by sequential use of the following modules: r.info, d.mon, d.rast, r.colors, d.rast.leg, d.legend, d.northarrow, d.grid, d.text, g.region, and r.contour. The depth frequency was analysed by the module 'd.histogram'. The proposed approach provided a systematic way for morphometric measuring of topographic data and combine the advantages of the GDAL, PROJ, and GRASS GIS tools that include the informativeness, effectiveness, and representativeness in spatial data processing. The morphometric analysis included the computed slope, aspect, profile, and tangential curvatur, SCOPUS: ar.j, SCOPUS: ar.j, info:eu-repo/semantics/published

Classical particle dampers suffer from their non-robust damping behavior, \ie they can only be efficiently applied to a specific frequency range and amplitude range. The reason for that is that particle motion, also called motion mode, and damper efficiency show a strong correlation. By changing particle or container properties the motion modes are shifted to other excitation conditions but their efficient range is not much affected. To increase the damping performance and robustness of particle dampers, two approaches are presented here by introducing new motion modes. Therefore, the particle dampers are analyzed experimentally using a shaker setup and numerically using the discrete element method. The first design approach uses inner structures inside the particle damper, manufactured by a 3D printer. The inner structures consist of different numbers of beams, placed perpendicular to the container moving direction. They lead to a much more robust damper as the transition between the motion modes gets smoother. For the second approach, the container walls are equipped with different soft polymers. In this way a new motion mode at low excitation intensities is observed, leading to a high efficiency possibly on a large excitation intensity range. For an easy calculation of the necessary wall's Young's modulus an analytical formula based on Hertz impact theory is derived.

The morphometric analysis was carried out on the Halayapura micro-watershed in Karnataka, India. Using ArcGIS 10.2.2 and applying the DEM model, the micro-watershed was subjected to quantitative investigation to determine the channel network involved and understand geo-hydrological behavior. In addition, remote sensing and geospatial techniques were used to study the micro-watershed drainage analysis and its associated parameters, such as stream order, stream length, stream frequency, drainage density, texture ratio, form factor, circulatory ratio, elongation ratio, bifurcation ratio, and compactness coefficient for the micro watershed, were evaluated. According to the findings, the stream order ranges from I to IV, with 97 streams in the micro-watershed. Streams of 72, 19, 5, and 1 are found in the I, II III, and IV order, respectively. The bifurcation values range from 3.78 to 5.00, with the average weight around 3.14. The elongation ratio and farm factor are 0.77 and 0.46, respectively. The drainage density of the micro watershed is 5.20 km/km2. The form factor, circularity, and elongation ratio contribute to a basin with an elongated shape through decreased flood proneness, erosion, and sediment transport capacity. The results of the micro-watershed morphometric assessment are critical for evaluating and managing water resources and selecting a recharge structure for future water management in the study region.

The railway ballast layer provides the function of bearing loading, resisting geometry degradation, and drainage. In those related research, the behaviour of ballast assembly can be obtained by laboratory (or in-situ) tests. Limited simulation methods can be used to analyse the behaviour of ballast particles at the mesoscopic level. The numerical simulations based on the Discrete Element Method (DEM) are employed, which treat every ballast particle as a calculation component. However, the efficiency of DEM simulation is very low due to the algorithm and a very large number of elements. This paper analysed the efficiency-related questions of the DEM modelling. The influence of particle shape and contact properties on the force behaviour is studied. Further, an optimised multi-layer ballast track model is introduced based on the most influential ballast areas. In such areas, particles are generated with an irregular shape to ensure the reliability of results, and particles except that area are generated with a rolling resisted ball shape to decrease the number of elements. A series of lateral resistance simulations are conducted to show and validate the accuracy and efficiency of this method in the dimension of the single sleeper section. Results show that this optimised multi-layer model building method largely improves efficiency, and it can provide accurate data., Railway Engineering

Microbially induced calcium carbonate precipitation (MICP) has attracted muchattention as a promising green technique for soil improvement. Despite the sig-nificance of precipitation pattern in mind, constitutive relations or numericalmodels considering the finite-strain mechanical effects of the various precipita-tion patterns are rarely developed. In this paper, we propose a novel 3D DEMmodeling scheme by using coarse particles to represent sand grains and finesas cementing agents, to reproduce the various precipitation patterns in MICP-treated sand. Based on the topological relations with adjacent particles andthe contribution to the mechanical improvement, the cementing fines are clas-sified into effective, partially effective, surface coating, and pore filling ones.The microstructural characteristics and their evolution upon external loadingare investigated quantitatively after a careful calibration and validation. Themicrostructural variation in experiments can be well reproduced, pinpointingthis variation as a possible cause for the fluctuation in experimental data. Mas-sive coating fines are produced accompanying the microstructural degradation,which is initiated by the breakage of effective bonds. The breakage of partiallyeffective bonds may become dominating later in the medium to strong cementedspecimens. One weakly cemented specimen shows diffuse failure with simulta-neous bond-breakage and friction. In contrast, the medium to strong cementedspecimens show localized failure with the dominating mechanism transitingfrom bond-breakage to friction producing notable pore filling fines. We pro-pose a relation between unconfined compressive strength and the equivalenteffective volume fraction of cementing agents normalized by the pretreatmentporosity, which reveals the coupling effects of the initial configuration and theprecipitation pattern on the mechanical improvement.

Bed permeability is a crucial factor in blast furnace efficiency and stability. The Discrete Element Method (DEM) has been used extensively to model material flow in different parts of the furnace and holds great potential for optimizing the permeability. The inherent computational load is the main bottleneck in using this method to provide detailed descriptions of different blast furnace granular phenomena on an industrial scale. In recent years, computing capabilities have been rapidly increasing and more elaborate models are being developed for the furnace as a whole. This paper reviews the recent progress in modelling relevant phenomena related to the burden distribution, and how they affect the bed permeability, using DEM. We conclude that significant efforts have been made in modelling the burden distribution; however, these models generally do not investigate the permeability. Hence, understanding of how the permeability can be optimized still requires significant efforts towards model development., Transport Engineering and Logistics

This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/abs/10.1061/JENMDT.EMENG-6930., Perforated unreinforced masonry (URM) walls are used in most existing masonry buildings as structural and nonstructural elements. Depending on the size and position, openings may detrimentally affect the stiffness and seismic capacity of URM walls. This research investigates the structural behavior of perforated URM walls with different opening sizes and proportions subjected to lateral loading using the discrete element method (DEM). In the applied modeling strategy, masonry walls are composed of rigid blocks, where their mechanical interactions are simulated via point-contact hypotheses. Once the numerical approach is validated, parametric analyses are performed to better understand the effect of different opening sizes and their aspect ratios on the failure mechanism and shear capacity of perforated URM walls. The results quantify the lateral load–carrying capacity and demonstrate its inverse relationship with the opening size. Furthermore, a slight influence of contact stiffness (varied from 10 to ) on the ultimate lateral load in DEM-based simulations is noted. Finally, the obtained shear force capacities are compared against the strength prediction equations provided in current US standards. In most cases, the predictions of the US standard provide conservative values relative to the DEM results., Peer Reviewed, Postprint (author's final draft)