#Discrete Element Modelling (DEM)

[little-p-eng-engineering]

Little P.Eng. for Discrete Element Modeling (DEM) Services

In a world driven by technological advancements, the ability to understand granular systems at a particle level has never been more essential. This precise understanding has been made possible through a computational technique known as Discrete Element Modeling (DEM). While many entities offer DEM services, Little P.Eng. has carved a niche for itself as a front-runner in this specialized domain.

Understanding Discrete Element Modeling (DEM)

Before diving into the specifics of Little P.Eng.'s offerings, it's essential to demystify DEM:

DEM is Calculation-based Modeling: At the heart of DEM is mathematics. This method uses precise calculations to predict the behavior of individual particles within a system. By doing so, it can accurately predict the interactions and outcomes when these particles are subjected to various conditions.

DEM Allows for Visualizing Results: One of the standout features of DEM is its ability to provide visual results. Users can observe:

Particle Velocity: Understand the speed and direction of individual particles.

Forces: This includes shear (parallel to the surface) and normal (perpendicular to the surface) forces that the particles experience.

Moments: This refers to the bending and torsional (twisting) moments affecting the particles.

Acceleration and Material Scatter: Track how quickly particles move and the variations in their dispersion patterns.

DEM: More than just Flow Simulation: While DEM is instrumental in predicting the flow of bulk materials, its capabilities extend beyond this. It plays a crucial role in understanding:

Wear Patterns: Predict how equipment will fare over time by simulating particle interaction and the resultant wear.

Mixing: Understand how different particles mix, which is vital in industries like pharmaceuticals and food production.

Center Loading: This refers to the loading pattern where materials concentrate towards the center, crucial in industries like construction.

DEM Programs: The Power Behind the Predictions

Any tool is only as good as the software powering it. When it comes to DEM, numerous programs can be used to perform this intricate modeling:

EDEM: A market leader, renowned for its comprehensive modeling capabilities.

PFC (Particle Flow Code): Known for its versatility, offering both 2D and 3D simulations.

LIGGGHTS: An open-source powerhouse that's both versatile and widely accepted.

Rocky DEM: Its strength lies in simulating realistic particle shapes, crucial for specific industries.

Yade: An open-source tool prized for its extensibility.

Abaqus: A multi-faceted software that, beyond its renowned finite element analysis, offers DEM capabilities.

Ansys Rocky: Building on the Ansys platform's strengths, it focuses on granular flow simulations.

Barracuda Virtual Reactor: Ideal for energy sector applications, especially particle reactions.

Also there are some open sources:

Kratos Multiphysics is developed by CIMNE (International Center for Numerical Methods in Engineering) in Barcelona and covers all kinds of numerical simulations, including DEM/PEM and DEM/PEFM-FEM coupling.

YadeDEM is a DEM package that is specifically designed for geomechanics.

Woo is a fork of YadeDEM with a strong focus on parallel computing and portability.

LAMMPS is a general purpose DEM/PEM.

LIGGGHTS is a general purpose DEM software that includes heat transfer simulations and is based on LAMMPS.

ESyS Particle is developed at the University of Queensland, Australia, with a focus on geoscientic/geotechnical applications.

GranOO is a general purpose DEM.

MercuryDPM is a general purpose Discrete Particle Method (DPM) software.

Little P.Eng.: Setting the Gold Standard in DEM Services

In the expansive realm of DEM, Little P.Eng. shines brightly, and here's why:

Mastery Over Multiple Platforms: Their team is proficient in a diverse array of DEM programs, ensuring they always have the right tool for the job.

A Client-centric Approach: They tailor their solutions, ensuring that each client's unique needs and challenges are addressed.

In-depth Analysis: Beyond merely running simulations, they delve deep, integrating real-world measurements to enhance simulation accuracy.

Applications and Implications of DEM in Industries

The true power of DEM, as harnessed by Little P.Eng., lies in its diverse applications:

Equipment Design: Through DEM, companies can design equipment that's optimized for longevity and efficiency.

Optimizing Production Lines: By understanding how granular materials behave, industries can fine-tune their production lines for maximum efficiency.

Safety Protocols: Predicting particle behavior, especially in industries dealing with hazardous materials, can lead to enhanced safety protocols.

Challenges in DEM and How Little P.Eng. Overcomes Them

DEM, while powerful, isn't without its challenges. The accuracy of simulations is heavily reliant on input parameters. Additionally, the computational demands for large-scale simulations are immense.

Little P.Eng. rises above these challenges through a blend of rigorous experimental data collection and a deep understanding of the DEM software landscape. Their iterative approach ensures that simulations are continually refined for better accuracy.

Conclusion

Discrete Element Modeling (DEM) is transforming our understanding of granular systems. With its capability to provide in-depth insights at a particle level, its applications span a wide array of industries.

In this domain, Little P.Eng. emerges not just as a service provider, but as a trusted partner, guiding businesses towards better efficiency, safety, and innovation. As we venture further into an era where the micro informs the macro, the services of entities like Little P.Eng., underpinned by the power of DEM, will undoubtedly be invaluable.

Read more:

Little P.Eng. for Discrete Element Modeling (DEM) Services: Unveiling the Power of Simulation

The Importance of Discrete Element Modeling (DEM) Studies and What Problems It Can Solve

Tags:

Little P.Eng.

Discrete Element Modeling

Mixing

Granular systems

Particle behavior

EDEM

PFC (Particle Flow Code)

LIGGGHTS

Rocky DEM

Yade

Abaqus

Ansys Rocky

Barracuda Virtual Reactor

Calculation-based modeling

Particle velocity

Shear forces

Normal forces

Bending moments

Torsional moments

Acceleration

Material scatter

Flow simulation

Wear patterns

Center loading

Equipment design

Production line optimization

Safety protocols

Computational simulations

Input parameters

Simulation accuracy

Bulk Material Handling & Processing

Engineering Services

Located in Calgary, Alberta; Vancouver, BC; Toronto, Ontario; Edmonton, Alberta; Houston Texas; Torrance, California; El Segundo, CA; Manhattan Beach, CA; Concord, CA; We offer our engineering consultancy services across Canada and United States. Meena Rezkallah.

[littlepeng1]

Little P.Eng. for Engineering Services

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Little P.Eng. Engineering delivers expert engineering services across North America. We specialize in Bulk Material Handling Engineering, Seismic Hazards Analysis & Bracing Design, and Structural Engineering, ensuring safe and efficient industrial systems. Our team excels in Piping Stress Analysis, Above-Ground Tank Design, and Pressure Vessel Design, adhering to leading industry codes. We also offer CRN Registration support for Canadian compliance. With advanced Discrete Element Modeling (DEM), we optimize bulk flow systems, and our CIPP Liner solutions provide reliable Pipeline Rehabilitation. Trust Little P.Eng. for innovative, code-compliant, and cost-effective engineering services.

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[govindhtech]

EDEM Altair on Google Cloud Unlock Billion-Particle Models

Google Cloud and Altair EDEM

An essential skill for manufacturing, industrial, and life science companies is modelling the interactions between bulk and granular materials and containers, machinery, and each other. The more realistic these simulations get, the less time and money businesses need to spend refining their designs and prototypes. Recently, Altair and Google Cloud worked together to see how big of a simulation EDEM Altair could run on a single Google Cloud virtual machine. The outcomes were revolutionary.

Software for the Discrete Element Method (DEM) High-performance software for simulating both bulk and granular materials is called EDEM. Equipped with DEM, EDEM simulates and analyses a wide range of materials’ behaviours, including coal, mined ores, soils, fibres, grains, tablets, powders, and more, with speed and accuracy.

Engineers may get vital insight into how those materials will behave with their equipment under various operating and process settings by using EDEM modelling. It may be used in conjunction with other CAE tools or on its own.

Using EDEM, top businesses in the heavy equipment, off-road, mining, steel, and process manufacturing sectors can assess equipment performance, optimise workflows, and comprehend and forecast granular material behaviours.

GPUs drive simulations for EDEM A high-performance software programme for simulating bulk and granular materials is called EDEM Altair. Discrete element method (DEM) simulations and analysis of the behaviour of mined ores, soils, fibres, grains, tablets, powders, and more are performed fast and precisely thanks to EDEM calculations.

Several advancements in model size have been made as a result of industry demands for EDEM to operate at even larger scale. The maximum two decades ago was 200,000 particles, requiring up to ten days to generate in a simulation. That increased swiftly to one million particles, ten million, and finally twenty million. Today, completing a simulation with one billion particles in a few days is the holy grail.

Since these simulations necessitate a significant amount of processing power, as one might anticipate, the use of graphics processing units (GPUs) has significantly increased simulation speed and efficiency. GPUs are extremely effective at handling the massive volumes of data and intricate computations required for EDEM simulations because they are specifically made to handle parallel processing tasks.

The EDEM Altair experiment running on Google Cloud EDEM was initially intended to be a desktop application and has only ever worked with shared-memory architectures that are hosted on a single host. Unlike distributed memory, which can scale across multiple hosts, this restricts access to processors. EDEM is unable to benefit from the scalability and flexibility of distributed memory without a significant rebuild. On the other hand, multi-GPU systems provide a way to boost processing capacity without switching to distributed memory programming models.

The partnership between Altair and Google Cloud had two objectives: to simulate the largest system that could be created, with one billion particles, and to collect data in order to create estimates for mapping a specific type of hardware to a potential simulation scale. Google Cloud made the announcement that its A3 virtual machines (VMs) with NVIDIA H100 GPUs were now available in May 2023. This level of simulation is made feasible by the A3 VMs, which combine modern CPUs with NVIDIA H100 Tensor Core GPUs and also provide significant network upgrades and enhanced host memory.

Two simulation scenarios were conducted by Altair and Google Cloud on a single A3 virtual machine (VM) equipped with eight NVIDIA H100 GPUs, each having 80 GB of GPU memory and 3.6 TB/s of bisectional bandwidth. A 4th Generation Intel Xeon Scalable processor and 2 TB of host memory were also included in the system.

The filling test was selected as the test scenario. This useful simulation examines the effects of particle behaviour in an actual industrial environment, where particles are dropped into a container from a moving plate. In this simulation, single- and multi-sphere particles were employed.

As previously shown, the combined filing test simulation with single- and multi-sphere EDEM Altair simulations scales well across the eight NVIDIA H100 GPUs that are available, reaching a total particle count of one billion.

The manufacturing industries can now assess equipment performance, optimise processes on a never-before-seen scale, and better understand and predict granular material behaviours thanks to this new breakthrough in simulation technology billion particles which will enable future simulations with greater fidelity and larger scale.

Key points are summarised below: Importance of Bulk Material Simulation The behaviour of these materials must be simulated in bulk because it affects many different industries, including manufacturing, life sciences, and industrial processes.

Software called Altair EDEM Software called EDEM Altair was created especially for high-performance simulation of granular and bulk materials.

Need for Greater Scale The industry has been requesting that EDEM be able to manage even bigger and more intricate simulations.

Cooperation Goal Two primary objectives drove the collaboration between Altair EDEM and Google Cloud

Run the biggest simulation you can, aiming for a billion particles as a benchmark. Collect information to determine the possible simulation scale that can be reached with various hardware setups. Making Use of Google Cloud Hardware The secret to the success was to leverage the A3 virtual machines (VMs) on Google Cloud, which were outfitted with potent NVIDIA H100 GPUs.

A3 virtual machines offer the base for general-purpose computing. The processing power for high-performance computations is provided by H100 GPUs. The article discusses utilising eight H100 GPUs, but it makes no mention of the precise A3 VM configuration.

Read more on Govindhtech.com

[talktomanojpachaury]

Surface Mining

Surface mining, including strip mining, open-pit mining and mountaintop removal mining, is a broad category of mining in which soil and rock overlying the mineral deposit are removed, in contrast to underground mining, in which the overlying rock is left in place, and the mineral is removed through shafts or tunnels.

The Main Difference between  Surface mining &  Underground mining is that :  Surface mining is suitable for large, low-grade ore deposits which occur below a thin layer of rock or sand. Underground mining is used for small, high-grade deposits covered with a thick soil or rock above the ore.

Surface mining began in the mid-16th century and is practiced throughout the world, although the majority of surface coal mining occurs in North America. It gained popularity throughout the 20th century, and surface mines now produce most of the coal mined in the United States.

In most forms of surface mining, heavy equipment, such as earthmovers, first remove the overburden. Next, large machines, such as dragline excavators or bucket wheel excavators, extract the mineral.

Image above shows the methods of surface mining.

There are five main methods of surface mining, detailed below.

1. Strip mining

2. Open-pit mining

3.  Mountaintop removal

4.  Dredging

5.  Highwall mining

1.  Strip mining

"Strip mining" is the practice of mining a seam of mineral, by first removing a long strip of overlying soil and rock (the overburden); this activity is also referred to as "overburden removal". It is most commonly used to mine coal and lignite (brown coal). Strip mining is only practical when the ore body to be excavated is relatively near the surface. This type of mining uses some of the largest machines on earth, including bucket-wheel excavators which can move as much as 12,000 cubic metres of earth per hour.

There are two forms of strip mining. The more common method is "area stripping", which is used on fairly flat terrain, to extract deposits over a large area. As each long strip is excavated, the overburden is placed in the excavation produced by the previous strip.

"Contour mining" involves removing the overburden above the mineral seam near the outcrop in hilly terrain, where the mineral outcrop usually follows the contour of the land. Contour stripping is often followed by auger mining into the hillside, to remove more of the mineral. This method commonly leaves behind terraces in mountainsides.

2.  Open-pit mining

"Open-pit mining" refers to a method of extracting rock or minerals from the earth through their removal from an open pit or borrow. Although open-pit mining is sometimes mistakenly referred to as "strip mining", the two methods are different.

The El Chino mine located near Silver City, New Mexico is an open-pit copper mine.

3.  Mountaintop removal

"Mountaintop removal mining" (MTR) is a form of coal mining that mines coal seams beneath mountaintops by first removing the mountaintop overlying the coal seam. Explosives are used to break up the rock layers above the seam, which are then removed. Excess mining waste or "overburden" is dumped by large trucks into fills in nearby hollow or valley fills. MTR involves the mass restructuring of earth in order to reach the coal seam as deep as 400 feet (120 m) below the surface. Mountaintop removal replaces the original steep landscape with a much flatter topography. Economic development attempts on reclaimed mine sites include prisons such the Big Sandy Federal Penitentiary in Martin County, Kentucky, small town airports, golf courses such as Twisted Gun in Mingo County, West Virginia and Stonecrest Golf Course in Floyd County, Kentucky, as well as industrial scrubber sludge disposal sites, solid waste landfills, trailer parks, explosive manufacturers, and storage rental lockers.

The technique has been used increasingly in recent years in the Appalachian coal fields of West Virginia, Kentucky, Virginia and Tennessee in the United States. The profound changes in topography and disturbance of pre-existing ecosystems have made mountaintop removal highly controversial.

4.  Dredging

"Dredging" is a method for mining below the water table. It is mostly associated with gold mining. Small dredges often use suction to bring the mined material up from the bottom of a water body. Historically, large-scale dredging often used a floating dredge, a barge-like vessel which scooped material up on a conveyor belt in front, removed the desirable component on board, and returned the unwanted material via another conveyor belt in back. In gravel-filled river valleys with shallow water tables, a floating dredge could work its way through the loose sediment in a pond of its own making.

5.  Highwall mining

Highwall mining is another form of mining sometimes conducted to recover additional coal adjacent to a surface mined area. The method evolved from auger mining but does not meet the definition of surface mining since it does not involve the removal of overburden to expose the coal seam.

CERB final report No. 2014-004 "Highwall Mining: Design Methodology, Safety, and Suitability" by Yi Luo characterizes it as a "relatively new semi-surface and semi-underground coal mining method that evolved from auger mining".

In Highwall mining, the coal seam is penetrated by a continuous miner propelled by a hydraulic Pushbeam Transfer Mechanism (PTM). A typical cycle includes sumping (launch-pushing forward) and shearing (raising and lowering the cutterhead boom to cut the entire height of the coal seam). As the coal recovery cycle continues, the cutterhead is progressively launched into the coal seam for 19.72 feet (6.01 m). 

Then, the Pushbeam Transfer Mechanism (PTM) automatically inserts a 19.72-foot (6.01 m) long rectangular Pushbeam (Screw-Conveyor Segment) into the center section of the machine between the Powerhead and the cutterhead. The Pushbeam system can penetrate nearly 1,200 feet (366 m) into the coal seam.

One patented Highwall mining systems use augers enclosed inside the Pushbeam that prevent the mined coal from being contaminated by rock debris during the conveyance process. Using a video imaging and/or a gamma ray sensor and/or other Geo-Radar systems like a coal-rock interface detection sensor (CID), the operator can see ahead projection of the seam-rock interface and guide the continuous miner's progress. 

Highwall mining can produce thousands of tons of coal in contour-strip operations with narrow benches, previously mined areas, trench mine applications and steep-dip seams with controlled water-inflow pump system and/or a gas (inert) venting system.

Recovery with tunneling shape of Drives are much better than round Augering Holes, but the mapping of areas that have been developed by a Highwall miner are not mapped as rigorously as deep mined areas. 

Very little soil is displaced in contrast with mountain top removal; however a large amount of capital is required to operate and own a Highwall miner. But then this Highwall mining system is the innovative roadmap future potential and stay or being better competitive in the area of environmental friendly non mountain-top (overburden) removal operated by only 4 crew members.

Mapping of the outcrop as well as core hole data and samples taken during the bench making process are taken into account to best project the panels that the Highwall miner will cut. 

Obstacles that could be potentially damaged by subsidence and the natural contour of the Highwall are taken into account, and a surveyor points the Highwall miner in a line (Theoretical Survey Plot-Line) mostly perpendicular to the Highwall. 

Parallel lines represent the drive cut into the mountain (up to 1,200 feet (366 m) deep - 2015 records), without heading or corrective steering actuation on a navigation Azimuth during mining results in missing a portion of the coal seam and is a potential danger of cutting in pillars from previous mined drives due to horizontal drift (Roll) of the Pushbeam-Cuttermodule string.

Recently Highwall miners have penetrated more than 1200 feet (366 m) [2015 ongoing records] into the coal seam, and today's models are capable of going farther, with the support of gyro navigation and not limited anymore by the amount of cable stored on the machine. 

The maximum depth would be determined by the stress of further penetration and associated specific-power draw, ("Torsion and Tension" in Screw-Transporters String) but today's optimized Screw-Transporters Conveying Embodiments (called: Pushbeams) with Visual Product Development and Flow Simulation Behavior software "Discrete Element Modeling" (DEM) shows smart-drive extended penetrations are possible, even so under steep inclined angles from horizontal to more than 30 degree downhole.

In case of significant steep mining the new mining method phrase should be "Directional Mining" [Commonly Used Technologies as valuable synergy Directional Drilling and Directional Mining are categorized in "Surface to In-Seam" (SIS) Techniques], dry or wet, Dewatering is developed or Cutting & Dredging through Screw-Transporters are proactive in developing roadmap of the leading global Highwall mining engineering company.

[testmyinternetspeed]

EPB Speed Test

This study demonstrates a three-dimensional numerical EPB Speed Test simulation of earth pressure balance shield tunneling using a coupled discrete element method and a finite difference method. The analysis adopted the actual size of a spoke-type EPB shield tunnel boring machine consisting of a cutter head with cutting tools, working chamber, screw conveyor, and shield. testmyinternetspeed.org,For the coupled model to reproduce the in situ ground condition, the ground formation was generated partially using the DEM, with the rest of the domain being composed. https://7smabu.com/read-blog/288837_epb-speed-test.html

[rahima3432]

ESSS Rocky DEM 2021 Free Download

ESSS Rocky DEM 2021 Free Download

ESSS Rocky DEM 2021 Overview ESSS Rocky DEM 2021 is a reliable and powerful 3D Discrete Element Modeling (DEM) system which accurately and quickly simulates the granular flow conduct of various shaped and sized particles.This is an intelligent application that truly provides exact prediction of the actions of particles as energy absorption rate as well as particle fracture as well as material…

[automaticwastelandllama]

ESSS Rocky DEM Crack is an efficient granular material modeling software using the discrete element method.

[architectnews]

Striatus Masonry Footbridge, Venice

Zaha Hadid Architects Venice, Striatus Masonry Footbridge, Italy Architeture Images

Striatus Masonry Footbridge in Venice: Zaha Hadid Architects

19 Jul 2021

Architect: Zaha Hadid Architects

Location: Venice, Italy

photo © Naaro

Striatus Masonry Footbridge

Striatus is an arched masonry footbridge composed of 3D-printed concrete blocks assembled without mortar or reinforcement. The 16 x 12 metre footbridge is the first of its kind, combining traditional techniques of master builders with advanced computational design, engineering and robotic manufacturing technologies.

photo © Naaro

Exhibited at the Giardini della Marinaressa during the Venice Architecture Biennale until November 2021, Striatus has been developed by the Block Research Group (BRG) at ETH Zurich and Zaha Hadid Architects Computation and Design Group (ZHACODE), in collaboration with incremental3D (in3D) and made possible by Holcim.

photos © Naaro

Proposing a new language for concrete that is structurally informed, fabrication aware, ecologically responsible and precisely placed to build more with less, Striatus optimises the properties of masonry structures, 3D concrete printing (3DCP) and contemporary design; presenting an alternative to traditional concrete construction.

photo © Naaro

The name “Striatus” reflects its structural logic and fabrication process. Concrete is precisely printed in layers orthogonal to the main structural forces to create a “striated” compression-only structure that requires no mortar or reinforcement.

As the construction does not need mortar, the blocks can be dismantled, and the bridge reassembled at different location. If the construction is no longer needed, the materials can simply be separated and recycled.

photo © Naaro

Strength through geometry Striatus is an unreinforced concrete structure that achieves strength through geometry. Concrete can be considered an artificial stone that performs best in compression. In arched and vaulted structures, material can be placed precisely so that forces can travel to the supports in pure compression. Strength is created through geometry, rather than an inefficient accumulation of materials as in conventional concrete beams and flat floor slabs. This presents opportunities to significantly reduce the amount of material needed to span space as well as the possibility to build with lower-strength, less-polluting alternatives.

Striatus’ bifurcating deck geometry responds to its site conditions. The funicular shape of its structural arches has been defined by limit analysis techniques and equilibrium methods, such as thrust network analysis, originally developed for the structural assessment of historic masonry vaults; its crescent profile encompasses the thrust lines that trace compressive forces through the structure for all loading cases.

Steel tension ties absorb the horizontal thrust of the arches. Neoprene pads placed in between the dry-assembled blocks avoid stress concentrations and control the friction properties of the interfaces, echoing the use of lead sheets or soft mortar in historical masonry construction.

photo © Naaro

In plan, the boundaries of the structure form deep arches that transfer horizontal loads (for example, from visitors leaning against the balustrades) to the supports in pure compression. Advanced discrete element modelling (DEM) was used to refine and optimise the blocks’ stereotomy and to check stability of the entire assembly under extreme loading cases or differential settlements of the supports.

The bridge’s 53 3DCP voussoirs have been produced using non-parallel print layers that are orthogonal to the dominant flow of forces. This avoids delamination between the print layers as they are held together in compression. The additive manufacturing process ensures the structural depth of the components can be achieved without producing blocks with a solid section, hence reducing the amount of material needed compared to subtractive fabrication methods or casting.

Striatus follows masonry structural logic on two levels. As a whole, the bridge behaves as a series of leaning unreinforced voussoir arches, with discretisations orthogonal to the dominant flow of compressive forces, following the same structural principles as arched Roman bridges in stone. Locally, on the level of the voussoir, the 3DCP layers behave as traditional brick masonry evident in the inclined rows of bricks within Nubian or Mexican vaulting.

photo © Naaro

Circular by design Circular by design, Striatus places material only where needed, significantly reducing its environmental footprint. Built without reinforcement and using dry assembly without binders, Striatus can be installed, dismantled, reassembled and repurposed repeatedly; demonstrating how the three R’s of sustainability (Reduce, Reuse, Recycle) can be applied to concrete structures.

Reduce: – Lowering embodied emissions through structural geometry and additive manufacturing that minimises the consumption of resources and eliminates construction waste. – Placing concrete only there where needed, 3DCP minimises the amount of material required, while the low-stress, compression-only funicular geometry of Striatus proposes the further development of 3DCP that will enable the use of much lower-strength, less-polluting printable materials. – Compared to embedded reinforcement in concrete, Striatus uses external ties to absorb the thrust of its arched shape and dramatically reduce the amount of steel required. A high carbon-intense material, steel reinforcement (100% recycled) per unit mass is more than ten times that of a standard concrete.

Reuse: – Improving circularity and longevity. Unlike conventional reinforced concrete structures, Striatus is designed to be dry assembled without any binder or glue, enabling the bridge to be dismantled and reused in other locations. Its funicular design ensures the 3DCP blocks experience low stresses throughout their use, resulting in no loss of structural integrity. Striatus separates components in compression and tension, ensuring external ties can be easily accessed and maintained, resulting in a longer lifespan for the entire structure.

Recycle: – By ensuring different materials are separated and separable, each component of Striatus can easily be recycled with minimal energy and cost. 3D printing also avoids the waste and costs associated with single-use moulds. Additionally, the component materials within Striatus remain separate and separable with the use of mechanical connections such as simple dry contacts between the voussoirs rather than chemical glues or binders, ensuring a simple, low-energy recycling process at the end of the elements’ life, potentially after multiple cycles of reuse.

photo © Naaro

Robotic 3D concrete printing Unlike typical extrusion 3D printing in simple horizontal layers, Striatus uses a two-component (2K) concrete ink with corresponding printing head and pumping arrangement to precisely print non-uniform and non-parallel layers via a 6-axis, multi-DOF robotic arm. This new generation of 3D concrete printing in combination with the arched masonry design allows the resulting components to be used structurally without any reinforcement or post-tensioning.

To prevent misalignment between the direction of structural forces and the orientation of material layers that arises from typical shape-agnostic slicing of explicitly modelled geometry, a custom-developed design pipeline was formulated for Striatus to ensure that its printed layers are wholly aligned with the direction of compression forces throughout the entire bridge and also locally through each 3D-printed block. To address issues and challenges that could prevent in-between stability during printing, the coherence and feasibility of the gradually evolving print paths have been modelled using a Functional Representation (FRep) process.

photo © Naaro

This process encodes and continuously checks rules of minimum overlap, maximum cantilever between print layers and print length, print speed and the volume of wet concrete extruded. These measures, typically used in horizontally layered 3DCP, have been advanced and refined to work on an inclined-plane setting:

– The angular differences between start and end planes of all 53 printed blocks have been simultaneously adjusted to meet multiple criteria such as an appropriate structural contact and angle between adjacent blocks, and maximum print inclination. – The careful design and iterative refinement of the hollow cross sections and infill triangulation have ensured that material is placed corresponding to the precisely analysed, local structural performance of each block. This design and optimisation has been applied to each individual layer of every block (with 500 print layers on average per block), ensuring that all blocks are as hollow and light as possible, and consequently use the least amount of material possible, while maintaining structural integrity under all loading conditions. – The resulting intricate cross-sectional design has been processed into a single, continuous print path meeting various criteria that include appropriate print speed and turning radii, structurally required material width and thickness, and controlled expression of naturally occurring printing artefacts.

photo © Tom van Mele

A nuanced aspect of robotic 3DCP masonry is the re-introduction of intelligence and highly skilled labour into the manufacturing and construction industry. The digitisation of fabrication and digital augmentation of skilled assembly and construction techniques makes historically-accrued knowledge accessible to younger generations and enables its systematic upgrade towards industrialised construction through the use of computational and robotic technologies. In stark contrast to a brute force, and often materially wasteful economy biased towards automation and assembly line production, 3DCP masonry introduces possibilities of a symbiotic human-machine economy. This promises an environmentally, socio-culturally and economically sustainable alternative to its 20th-century predecessor.

photo © Tom van Mele

Computational design-to-construction integration Integrating design, engineering, fabrication and construction, Striatus redefines conventional interdisciplinary relations. The precise manufacturing of the blocks was enabled by well-defined data exchange between the various domain-specific software toolchains involved in the process. This co-development approach was facilitated through the use of COMPAS, an open-source computational framework for collaboration and research in the AEC industry, which enabled the fluent interaction among the key players of the project, working together in five different countries, under a very tight schedule and budget, at a time in which travelling was not possible.

photo © Tom van Mele

Disruptive outlook Striatus offers a blueprint for building more with less. Created with the same structural principles and a similar fully-integrated computational design-to-fabrication approach that form the basis of the vaulted, rib-stiffened, unreinforced concrete floors being developed by the Block Research Group in partnership with Holcim, Striatus proposes an alternative to the standard inefficient floor slabs within any building.

Compared to typical reinforced-concrete flat floor slabs, this new floor system uses only 30% of the volume of concrete and just 10% of the amount of steel. The very low stresses within the funicular structure also enable the use of low-embodied-carbon concrete that incorporates high percentages of recycled construction waste. Prefabricated and dry-assembled, and therefore fully demountable and reusable, this floor system is easily and cleanly recyclable at end-of-life.

photo © in3d

With an estimated 300 billion square metres of floor area to be constructed worldwide over the next 30 years, and floors comprising more than 40% of the weight of most high-rise buildings (10+ storeys), introducing the principles demonstrated by Striatus would truly disrupt the construction industry — transforming how we design and construct our built environment to address the defining challenges of our era.

photo © in3d

Architect: Zaha Hadid Architects

Photography: Naaro, Tom van Mele and ©in3d

Zaha Hadid

Striatus Masonry Footbridge, Venice images / information received 190721

Location: Venezia, Italia

Installation by Alison Brooks Architects at 16th International Architecture Exhibition photo © Luke Hayes ReCasting by Alison Brooks Architects

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Japan Pavilion Venice Biennale 2021

Young Talent Architecture Award 2020 picture Courtesy Fundació Mies van der Rohe Young Talent Architecture Award 2020

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[juniperpublishers-ttsr]

Practical Approach for Elements within Incorporated Charged Zinc Particles in an Anode Zinc Reactor of a Fabricated Zinc Bromine Battery Cell System (ZnBr2) with Fitting Materials

Abstract

Batteries with different chemistries and designs encounters various (redox reactions) to store energy through applying charges and discharges rates. Redox flow batteries systems such as zinc bromine batteries cells systems (ZnBr2) can be enclosed with high surface area anode electrodes (reactors) and charged with some amount of added carbon particles for zinc deposition. The electrochemical reactions within a fabricated ZnBr2 battery cell system have been investigated with the coupled inlets and outlet brass fitting materials (15mm and 30mm) of different anode and cathode electrolyte compositions. SEM analysis was explored on some charged particles collected from the anode reactor to identify all the existing elements within the deposited charged zinc particles after several charges. The investigated zinc particles were between 254 microns to 354 microns. The electrolyte composition includes 3 moles of KBr (535.51 grams), 1 mole of KCl (111.89 grams) as the cathode side electrolyte and 3 moles of ZnBr2 (675 grams), 1 mole of ZnCl2 (205 grams), and 1M of KCl (111.826 grams) as the anode electrolyte solution. Originally, this journal paper has discovered the importance of coupling chemically resistance materials to ZnBr2 cells as investigated on the fabricated ZnBr2 cell that was initially converted to a CuZn2 battery cell system and reverted to the ideal ZnBr2 cell system before using an SEM technique to identify separately the present elements.

Keywords: SEM Analysis on Elements; Flow Rate; Reverting Battery Cell System

    Introduction

As previously presented in a journal titled (Practical Development of a ZnBr2 Flow Battery with a Fluidized Bed Anode Zinc-Electrode), Journal of the Electrochemical Society, Volume 167, Number 5, various categories of anode reactors designed in solidwork were numerically examined before choosing the best candidate reactor and later passed different coulombs of charges and discharges to the fabricated ZnBr2 battery cell after the incorporated chosen reactor to the cell anode side and later explored the presented SEM analysis carried out in this paper on some particles collected from the anode reactor [1].

The fluent version in Ansys has assisted to successfully modelled a fluidized bed to address problems facing zinc-bromine battery cells systems. Such as dendrites problems within the cell; puncturing membranes of these cells systems and thereby resulting to cut off voltages, short circuits that also reduces their life span. Introducing and modelling a fluidized bed zinc electrode has demonstrated fast deposition of zinc ions within the battery system zinc electrode and serve as an incorporated alternative electrode to prevent depositing zinc ions onto a solid electrode previously making ZnBr2 cells to encounter mechanical abrasion and deteriorating the electrodes as zinc ions stays longer on them than the expected time [1-3]. See the presented schematic diagram in Figure 1.

    Introduction to SEM and Fluidized Bed Reactors

SEM (scanning electrons microscopy) and fluidized bed zinc anode reactors has several benefits. Some of these benefits include using SEM to examine electrode sample homogeneity and fluidized bed reactors for multiphase mixing purposes etc. Elements present within injected particles to zinc bromine batteries cells systems; anode zinc electrode can be examined using SEM analysis. Redox flow batteries cells systems (RFB’s) such as zinc bromine batteries cells systems enclosed with high surface area zinc electrodes are capable to prevent the issue of dendrite formation within these batteries cells systems.

By means of SEM, scanning of electrons microscopy, samples images sample can be produced through focusing on the beam of electrons [4]. Anode zinc reactors of ZnBr2 batteries cells systems are usually in liquid and solid phases. Both the two phases, liquid and solid are common in petrochemical industries, biological industries in chemical industries and particularity for adsorption, cracking (catalytic), crystallization and for ion exchange [5] etc. Particles sizes and shapes within anode reactors has huge impact to achieve fluidization and prevent dendrite formation in ZnBr2 cells. However, majority of these fluidized beds are not always designed properly before fabrication and to tailoring them to the mean particle size; especially for those in use for particle size distributions [6-18].

Particles behaviour are now usually modelled using the DEM technique, (discrete element method). DEM approaches are used to represent particles numerically and individually by identifying them with their specific properties (shapes, magnitude, properties of their material and the original velocity) [19-21]. The geometry interior shape accommodating all the injected particles are the domain for the simulation. Designed reactors can be separated by grids to identify the positions of particles prior to modelling and simulating.

Based on Newton’s laws, injected particles in reactors are subjected to have good contacts and can be exposed to a small motion during the iteration process [22-24]. Contacts among injected particles in a ZnBr2 anode reactor can be monitored throughout discrete reactions, modelling stages and to determine the particles contact forces ad magnitude through a spring dashpot model. The acceleration of drag forces on fluid and particles, total forces and summation can be computationally balanced before determining individually the parameters and particles motion [25].

Particles properties, such as structure can differently be observed using SEM, scanning of electrons microscopy and their sample compositions, and any interacted atoms within the provided sample [26,27]. In most application, over the surface of samples, data collections are possible within the selected area and spatially displayed variances in their properties. Areas in between 1 cm to 5 microns can be imaged using such technique and within a spatial resolution of 50 to 100nm through using conventional scanning electrons microscopy method [28-31].

Suitable qualitative approaches, semi-quantitative, structural crystal or using EBSD to observe the orientation of the crystal and selecting point on samples are possible on SEM to determine chemically various compositions by means of an energy dispersive x-ray spectroscopy (EDS) [29,32]. Typically, scanning electron microscopy, as probes electrons micro-analyzer, EPMA, has considerably several existing designed functions of overlapped capabilities among other analytical instruments.

Backscattered electrons can be standardly collected using an SEM and electrons sources are the basic part of SEM. Through SEM analysis, electron’s properties, electrodes dispersion and their homogeneity can also be observed [33,34]. The sources of electrons, high voltages encountered across them, electrons accelerating toward the samples, electromagnetic lenses, temperatures, detectors, and data systems collections are diffractions of samples usually at high incidence angles [35-40]. Within a user interface, SEM does not rely on a 2θ angle, rather to act marginally and similarly to a light microscope [41]. Some SEMs are equipped to count samples, detect, and analyze off a scattered x-ray. Through such type of detectors, the elemental composition of a sample can possibly be determined [42-44]. Table 1 has further presented other advantages and disadvantages of scanning electrons microscopy, SEM.

    Materials and Suppliers

Materials and Method

SEM Preparation

By exploring scanning of electrons microscopy (SEM) on some of the collected charged particles from the anode zinc reactor was to discover all the enclosed various elements after charging and discharging the zinc bromine battery cell at different charge rates. Before exploring SEM analyses on the charged deposited zinc morphology collected from the anode reactor were dried in an oven at a temperature of 50°C to prevent these particles from agglomerating together.

The investigated particles sizes were in between (254 microns to 354 microns). Some of these particles from the anode-side zinc electrode after charging the cell were viewed at different microns (100 microns, 50 microns, 10 microns and 5 microns) by using the JEOL JSM-6010 PLUS/LA (SEM) scanning electron microscope machine.

The SEM characterization of the zinc electrodeposits were examined after charging the cell at a charge rate of 0.27 amps and 0.3 amps. The anode-electrolyte composition includes 3 moles of ZnBr2 (675 grams) Solution, 1 mole of ZnCl2 (205 grams), and 1 mole of KCl (111.826 grams). The cathode electrolyte solution includes 3 moles of KBr (535 grams) and 1 mole of KCl (111.897 grams). The anode electrolyte solution density was 1.47g cm-3 which was used to gauge the cathode-electrolyte. A flow rate of (166.7cm3/ min) was maintained throughout the experiment. The used JSM-6010LA/JSM-6010LV equipment for the scanning process was a compact mobile SEMs device with high performance and suitable for research use (Figure 2). The surface structures are observed by secondary electrons, the distribution of materials in a specimen was observed by backscattering the electrons and analysing the elements by EDS (energy dispersive X-ray analyser). All the necessary functions are available in the all-in-one mobile multi-touch-panel SEM [45-49].

    Results Analysis and Discussion

Examined Particles

Particles collected from the anode zinc reactor in the lab for SEM analysis (scanning of electrons image) occupied some white edges after the charge and discharge experiments according to the colour mapping. (Figures 3a-3c) for the decoupled anode and cathode cell reactor, the anode zinc reactor incorporating charged zinc particles, the collected and prepared charged electrodeposited zinc morphology enclosed within the small glass coin beaker for SEM analysis. Encountered degasification, the removal of dissolved gases from the anode and cathode electrolyte solution was due to the solid and liquid interfaces enclosing some formed bubbles during the experimental work. The observed degasification was concluded to have originated from particles that were not properly dried before removing them from the oven and before the SEM process. Particles not properly dried before the SEM analysis were expected to have strangely behaved and changed the zinc morphology (shape and structure) due to the observed gasification.

The dried and examined zinc morphologies presented in Figures 4-6 were studied using the scanning of electron microscopy, SEM characterization to observe elements enclosed within these particles after the redox reaction (charged and discharged) to store and discharge the stored energy by the fabricated zinc bromine battery cell and after observing copper deposits at the cathode-side electrolyte due to the brass fittings that were not chemically resistance that initially changed the battery to a copper-zinc RFB cell before it was reverted back to a zinc-bromine battery cell by changing some of the materials. See the two graphical peak plots in Figure 7a & 7b for the identified copper showing the presence of copper at a wavelength of 740nm and at a wavelength of 900nm with a UV-visible spectrophotometer device (Table 2).

As presented in Tables 3-5, the images of the mapped elements during the SEI, scanning of electrons images showed no hydrogen traces subsequently after charging the ZnBr2 battery cell at various charged and discharged amperes.

Zinc deposited within the anode reactor via SEM were viewed using different microns. Picture 1, observed as 100 microns has a sedimentary rock shape, photo 3, viewed in 10 microns has high mossy deposits that look like zinc clusters. Picture 2 of 50 microns resemble silt sand that was sticky together, and photo 4, was observed in 5 microns. Particles collected after discharging the stored energy by the battery cell were like the charged particles examined via SEM. Furthermore, the carbon fibre feeder electrode materials also contributed to the low current in between (-300 mA to 300 mA) that was observed continuously when the fabricated battery cell was charged and throughout its mode of operation. In the past, a similar magnificently SEM results have been achieved despite using the appropriate working electrodes materials, primary and secondary supporting electrolyte which also enhanced a good electrochemical behaviour [50].

Charged and Dried Particles

Discharged and Dried Particles

Cu Electrodeposition at Charge and Discharge

UV-Visible Spectrometer Device and Peak Plots

As presented in Figure 8, a UV-Vis spectroscopy laboratory device is a simple, quick, and not expensive measurable technique for measuring the amount of light absorbs by a chemical substance. See also Figure 7a-7c and Figure 9 for other results. The process can be carried out by gaging the light intensity passing through a sample in relation to the light intensity through a blank reference or sample. Multiple techniques can measure types of multiple samples, either in thin film, glass, liquids, or solids. UV-Vis Spectroscopy as a measuring device is suitable to know the transmitting, absorption and the functioning reflection of a material wavelength in the range of 190 nanometers to 1,100 manometers [51,52].

With a UV-Vis spectroscopy device, it was possible the observed brown deposits within the cathode electrolyte solution as copper by collecting some of this electrolyte solution in a small glass bottle after passing these charges to the cell: (1) 0.1 amps and -0.1 amps for 3600 secs and 800 secs (2) At 0.1 amps and -0.1 amps for 3500 secs and 200 secs and (3) At 0.25 amps for 3600 secs and -0.25 amps for 100 secs with 3 moles of KBr (535.51 grams), 1 mole of KCl (111.89 grams) as the cathode-side electrolyte solution and 3 moles of ZnBr2 (675 grams), 1M of ZnCl2 (205 grams), and 1 mole of KCl (111.826 grams) as the anode electrolyte solution [53,54].

The cathode electrolyte solution contains 3 moles of KBr (535.51g), 1 mole of KCl (111.89g). The anode electrolyte solution contains 3 moles of ZnBr2, 1 mole of KCl and 1 mole of ZnCl2. Both electrolytes solution contained 24.1g of Sodium Bromoacetate acid and Bromoacetic acid and 240g of MEM-Sequestering agent.

    Conclusion and Future Work

The fabricated ZnBr2 cell chemically converted to a CuZn2battery cell due to the non-chemically fitted brass materials coupled to the fabricated battery cell according to the investigated brown deposits within the cathode-side electrolyte observed to be copper and further to the explored SEM analysis on some of the electrodeposited charged zinc particles incorporated within the anode-reactor. The outcome of the results encouraged interrupting the cell from operating further and led to pulling apart the cell components to be properly cleaned and the sieving separation technique carried out on the cathode and anode electrolyte solution due the escaped charged zinc-particles.

Furthermore, as previously mentioned the possibility to revert the cell back to a zinc-bromine battery cell from a copper-zinc battery cell had occurred by changing the brass fitting materials (BFM) to a plastic fitting material (PFM). The observed brown deposits which had converted the zinc-bromine batteries cell to a copper-zinc battery cell was only possible to be reverted to a zinc-bromine battery cells by carrying out repeatedly a filtration process to separate the sediments observed from the anode and cathode electrolyte solution.

Initially by not fabricating the Nafion membrane size to the actual length and cell breadth size (190mm*190mm), had supported allowing the anode and cathode electrolyte to mix. Therefore, fabricating the membrane size to a cell shape will prevent any future occurrence from allowing any cross-mixing of any anode-side and cathode-side electrolyte.

By using a UV-visible spectrophotometer device to detect why the cathode-side electrolyte did not change to a reddish brown or yellow colour during the charge rate and discharged rate after identifying a dark green coloured electrolyte at the cathode-side cell; which was recognized as copper at a wavelength of 900nm and with two peaks (see Figure 7a & 7b) had also supported having the establishment of a good redox reaction according to the electrochemical results according to the experimental observation. Furthermore, see Figures 1 & 7b. Therefore, identifying the chemistry behind the electrolyte colour had further helped.

The presence of oxygen (O2) was agreed to have occurred because the cell was exposed before coupling it and due to the presence of H2O. Silicon has originated due to the applied adhesive glue to prevent leakages. Chromium (Cr), Iron (Fe) and carbon (C) were both produced due to the coupled anode-inlet and anode-outlet pipe steel materials and brass fittings that were not chemical resistance. The anode and cathode inlets and outlets brass fittings materials had supported the origination of the identified selenium element during the chemical reaction. Selenium as non-metallic chemical elements in the group xvi of the periodic table could conducts electricity better in the light than in the dark and used in photocells. It was not peculiar by identifying some potassium elements during the SEM since the cell electrolytes consisted of some added salt.

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[biotechtimes]

IIT Mandi Summer Internship 2020

New Post has been published on https://biotechtimes.org/2020/02/18/iit-mandi-summer-internship-2020/

IIT Mandi Summer Internship 2020

IIT Mandi Summer Internship

IIT Mandi has released the official notification for its summer internship 2020. Students interested in IIT Mandi Summer Internship may go through the details given below. IIT Mandi Summer Internship.

Summer Internship at IIT Mandi

Each year various Departments/Schools accept a huge number of interns during the summer (typically May/June). The interns are supposed to work under the guidance of IIT Mandi faculty member(s) broadly in the following areas:

Biosensors Material and properties, Photocatalysis

Biomedical Engineering

Hydraulics, Environmental, Water resources

Host-Pathogen Interaction, Soil microbiology and its application in landslide mitigation

Gene Regulation

NanoBiotechnology

Physical Chemistry, Nanotechnology, Fluorescence Spectroscopy, Bioimaging, Microscopy

Protein folding and Aggregation

Solid Mechanics; Mechanical Design; Biomechanics

Deep Learning application in biometrics and medical imaging

Computational Chemistry, Theoretical Chemistry

Condensed Matter Physics/Materials Science

CMOS Analog IC design

Controllability of Differential Equations with Applications in Engineering and fluid-solid interaction problems

Computational Fluid Dynamics

Control Systems

Discrete element modeling (DEM) of granular flows

Differential Equations, Mathematical Modelling

Earthquake Engineering

Energy Conversion and storage

Electrodynamics

Experimental Physics and Nanosciences

Experimental Condensed Matter Physics, Fluid and Thermal Science

Financial Inclusion, Financial Literacy, Business Correspondent Model of Banking, Digital Identity (Aadhaar)

Fluid Mechanics and Solid Mechanics

Geotechnical Engineering

Geotechnical Engineering, Sensors in Geotechnical engineering

Investigations of drop impact onto a liquid pool

Landslide study

Power Electronic Applications

RF and Microwave propagation and device design

Semiconductor Devices

Structural Mechanics

Thermal management of microelectronics

Wireless networks and IoT

Eligibility and Support

Second-year of B.Tech. / B.E. students and 1st year PG or Masters Students.

Only students having a minimum CGPA of 7.5/10 or equivalent percentage of marks are considered.

The duration of the summer internship is eight weeks.

Interns will be supported financially for Rs.10,000/- for the entire 8 weeks.

Travel and living expenses should be borne by the intern.

The screening of interns will be done by the faculty members based on the credentials of applicants.

Selected candidates will have to arrange letters of recommendation from their Institute.

Selected students will be informed through e-mail.

How to apply:

Interested candidates should apply through an online application

Tentative Dates:

Start and Last Date for submission of Application form 10th April 2020 to 30th April 2020 Joining of Interns 11th June 2020 Duration of Internship Eight weeks from joining

Officiala Notification

[little-p-eng-engineering]

The Importance of Discrete Element Modeling (DEM) Studies and What Problems It Can Solve

In today's rapidly advancing world of science and engineering, the need for accurate and efficient simulation tools has never been greater. One such tool that has gained significant prominence in recent years is Discrete Element Modeling (DEM). DEM is a numerical technique used to simulate the behavior of granular materials, such as powders, grains, and particles, on a microscale level. This modeling approach has proven to be invaluable in a wide range of industries, from pharmaceuticals to civil engineering. In this article, we will explore the importance of DEM studies and delve into the various problems it can solve, demonstrating its versatility and impact across diverse fields.

I. Understanding Discrete Element Modeling (DEM)

Before we dive into the importance of DEM studies, it's essential to grasp the fundamentals of Discrete Element Modeling itself. DEM is a computational technique that simulates the behavior of a large number of individual particles. Each particle is treated as a discrete entity and follows specific rules and interactions with other particles. These interactions are governed by various force laws, including contact forces, friction, and collision dynamics. By tracking the motion and interactions of these particles over time, DEM can provide valuable insights into the behavior of granular materials.

DEM Fundamentals

At the core of DEM lies the discrete nature of particles. Unlike continuum-based methods, DEM models materials as a collection of individual particles, each with its own properties and interactions. These particles move within a virtual space and collide with one another, creating complex dynamics that mirror real-world granular materials.

The essential components of a DEM simulation include:

Particles: These represent the individual grains or particles within the material.

Interactions: DEM defines the rules governing how particles interact with each other, including contact forces, friction, and restitution coefficients.

Time Integration: DEM calculates the motion of particles over discrete time steps, accounting for forces and interactions at each step.

Boundaries and Constraints: The simulation environment often includes boundaries and constraints to model specific scenarios accurately.

DEM Applications

The versatility of DEM has led to its adoption in various fields and industries. Some notable applications of DEM include:

Geotechnical Engineering: DEM is used to study soil mechanics, soil-structure interactions, and landslide prediction.

Pharmaceutical Manufacturing: DEM helps optimize drug formulation, tablet compression, and powder flow in pharmaceutical processes.

Mining and Minerals Processing: DEM is employed to understand the behavior of ore materials during crushing, grinding, and transport.

Food Processing: DEM studies can improve the design of food processing equipment and optimize the handling of food particles.

Civil Engineering: DEM is applied to simulate granular materials in construction, such as concrete mixing and soil compaction.

Powder Technology: In industries like powder metallurgy and ceramics, DEM assists in optimizing powder compaction and sintering processes.

Now that we have a fundamental understanding of DEM, let's explore the significance of DEM studies and the diverse range of problems it can solve across these industries.

II. The Importance of DEM Studies

DEM studies have become increasingly important in various fields, offering valuable insights, solutions, and advancements. Here, we will delve into the significance of DEM studies by examining the critical problems it addresses across industries.

Geotechnical Engineering

a. Soil Mechanics

In geotechnical engineering, understanding the behavior of soils is paramount for infrastructure design and construction. DEM studies provide insights into soil mechanics by simulating the interaction between soil particles under various loading conditions. This allows engineers to predict soil settlement, shear strength, and bearing capacity, all of which are crucial for designing stable foundations for buildings, bridges, and other structures.

b. Landslide Prediction

Landslides pose a significant threat in hilly and mountainous regions. DEM can simulate the movement of soil and rocks on slopes, aiding in landslide prediction and risk assessment. By analyzing factors like particle size, shape, and cohesion, DEM models can help identify areas prone to landslides and develop mitigation strategies.

Pharmaceutical Manufacturing

a. Tablet Compression

In the pharmaceutical industry, tablet compression is a critical process in drug manufacturing. DEM studies help optimize tablet formulation by simulating the compaction of powder blends. By varying particle properties and compaction conditions, researchers can predict tablet properties like hardness, friability, and dissolution rate, leading to improved drug formulations and reduced development costs.

b. Powder Flow and Mixing

Powder flow and mixing are crucial steps in pharmaceutical manufacturing. DEM models can simulate the flow of powders through equipment like hoppers, silos, and blenders. This enables the identification of potential flow problems, such as segregation or arching, and the design of equipment modifications to enhance powder handling and mixing efficiency.

Mining and Minerals Processing

a. Crushing and Grinding

In mining and minerals processing, the efficient comminution of ore materials is essential for resource extraction. DEM studies simulate the crushing and grinding of ore particles in crushers and mills, allowing engineers to optimize equipment design and operating conditions. This leads to improved energy efficiency and increased mineral recovery rates.

b. Material Handling

The transport of bulk materials within mining and processing facilities can be challenging. DEM helps analyze conveyor belt behavior, chute design, and transfer point performance. By studying particle trajectories and interaction forces, engineers can minimize material spillage, dust generation, and equipment wear, ultimately reducing operational costs.

Food Processing

a. Mixing and Blending

In the food processing industry, achieving uniform mixing and blending of ingredients is critical for product quality. DEM simulations of mixing processes help optimize equipment design and operating parameters. By visualizing particle distribution and movement, manufacturers can ensure consistent product quality and reduce waste.

b. Powder Handling

Powder handling in the food industry can be complex due to the diverse properties of food powders. DEM studies assist in designing equipment such as pneumatic conveyors and feeders. By predicting powder flow behavior and potential issues like segregation, DEM helps ensure the efficient and hygienic handling of food ingredients.

Civil Engineering

a. Concrete Mixing and Placement

In civil engineering, the proper mixing and placement of concrete are essential for constructing durable structures. DEM can model the behavior of concrete constituents, such as aggregates and cement particles, during mixing and placement processes. This allows engineers to optimize concrete mix designs and construction techniques, leading to improved performance and longevity of concrete structures.

b. Soil Compaction

Achieving adequate soil compaction is crucial for road construction, embankment construction, and foundation preparation. DEM simulations can replicate the compaction process, considering factors like soil particle properties, compactor geometry, and dynamic loading. Engineers can use DEM to optimize compaction equipment and procedures, ensuring the desired level of soil compaction is achieved.

III. Challenges and Advances in DEM Studies

While DEM has proven to be a valuable tool in addressing various problems, it is not without its challenges and limitations. Researchers continue to work on improving DEM techniques and expanding their capabilities. Let's explore some of the challenges and recent advances in DEM studies:

Computational Intensity

DEM simulations involving a large number of particles can be computationally intensive and time-consuming. To address this challenge, researchers have developed parallel algorithms and utilized high-performance computing clusters to accelerate simulations. Additionally, advancements in graphics processing units (GPUs) have significantly improved the efficiency of DEM simulations.

Particle-Particle Interactions

Accurately modeling complex particle-particle interactions, including adhesive forces and agglomeration, remains a challenge in DEM. Recent research has focused on refining contact models to better capture these interactions, allowing for more realistic simulations of cohesive and adhesive materials.

Scale-Up and Scale-Down

Scaling DEM simulations from laboratory-scale experiments to real-world applications can be challenging due to differences in length and time scales. Researchers are developing multiscale modeling approaches to bridge this gap, enabling more accurate predictions in practical engineering applications.

Integration with Other Simulation Techniques

In some cases, it is necessary to combine DEM with other simulation techniques, such as Computational Fluid Dynamics (CFD) or Finite Element Analysis (FEA), to study complex multiphysics problems. Integrating DEM with these techniques and developing robust coupling methods are active areas of research.

Calibration and Validation

Calibrating DEM models to match real-world behavior and validating simulations against experimental data are crucial for model accuracy. Researchers are developing techniques for parameter calibration and validation, including advanced imaging and tracking technologies for particle characterization.

GPU Acceleration and Cloud Computing

As computing power continues to advance, the use of GPUs and cloud computing resources has become more accessible for DEM simulations. These technologies enable researchers and engineers to perform more extensive and detailed simulations, opening new possibilities for problem-solving and optimization.

Machine Learning and AI Integration

The integration of machine learning and artificial intelligence (AI) with DEM is a promising avenue for advancing the field. These techniques can aid in data analysis, model parameterization, and real-time decision-making in DEM simulations.

IV. Conclusion

Discrete Element Modeling (DEM) has emerged as a powerful and versatile tool for simulating the behavior of granular materials in various industries. Its ability to address critical problems in geotechnical engineering, pharmaceutical manufacturing, mining, food processing, and civil engineering has led to its widespread adoption and continued development.

DEM studies have provided engineers and researchers with valuable insights into the behavior of granular materials, enabling them to optimize processes, design equipment, and make informed decisions. Despite its challenges, ongoing advancements in computational methods, particle interactions, and multiscale modeling are expanding the capabilities of DEM and enhancing its accuracy.

As industries continue to evolve and face new challenges, DEM will likely play an increasingly vital role in solving complex problems and driving innovation. Its integration with emerging technologies like machine learning and AI holds promise for further enhancing its capabilities and broadening its application areas.

In conclusion, Discrete Element Modeling stands as a testament to the power of computational simulations in shaping the future of science and engineering. Its importance in solving real-world problems cannot be overstated, and its continued development promises to revolutionize the way we understand and manipulate granular materials in the years to come.

V. The Capabilities of Newton DEM Software

In the realm of Discrete Element Modeling (DEM), the choice of software is paramount to achieving accurate and insightful simulations. One software package that has gained recognition for its capabilities and versatility in solving complex granular material problems is Newton DEM Software. In this section, we will explore the unique features and advantages that Newton DEM Software offers in the context of DEM studies.

High-Performance Simulations

Newton DEM Software is renowned for its high-performance capabilities. It leverages advanced algorithms and efficient parallel processing to handle simulations involving a vast number of particles seamlessly. This makes it suitable for tackling large-scale industrial problems, such as those encountered in mining, pharmaceuticals, and construction.

Comprehensive Material Models

One of the standout features of Newton DEM Software is its extensive library of material models. It provides users with the flexibility to simulate a wide range of granular materials, including various shapes, sizes, and properties. This enables researchers and engineers to model materials accurately, whether they are dealing with cohesive powders, irregularly shaped particles, or even mixtures of different materials.

Advanced Contact Mechanics

Accurate modeling of particle-particle interactions is crucial for DEM simulations. Newton DEM Software employs advanced contact mechanics algorithms to precisely capture complex interactions, such as rolling, sliding, and friction. Additionally, it allows users to define custom contact models, ensuring that simulations closely mirror real-world behavior.

Multiscale Modeling Capabilities

Newton DEM Software recognizes the importance of bridging the gap between laboratory-scale experiments and practical engineering applications. It offers multiscale modeling capabilities that enable users to perform simulations at various length and time scales. This flexibility is particularly valuable when dealing with materials that exhibit different behaviors under different conditions.

Coupling with Other Simulation Techniques

Many real-world problems require a multiphysics approach, combining DEM with other simulation techniques like Computational Fluid Dynamics (CFD) or Finite Element Analysis (FEA). Newton DEM Software supports seamless coupling with these techniques, allowing users to investigate complex interactions between granular materials and fluid flows or structural elements.

User-Friendly Interface

Usability is a key consideration in software tools, and Newton DEM Software excels in this regard. Its user-friendly interface streamlines the simulation setup and visualization processes, making it accessible to both seasoned researchers and newcomers to DEM. The software provides an intuitive environment for defining particle properties, boundary conditions, and analysis parameters.

Visualization and Data Analysis

Newton DEM Software offers robust visualization and data analysis tools. Users can visualize simulation results in real-time, enabling immediate insights into particle behavior. Additionally, the software provides tools for post-processing and data analysis, allowing users to extract valuable information from their simulations and make informed decisions.

Integration with Machine Learning and AI

To stay at the forefront of technological advancements, Newton DEM Software has embraced the integration of machine learning and artificial intelligence (AI). Users can leverage these capabilities to enhance their DEM simulations, from automating parameter tuning to making real-time predictions based on simulation data.

Scalability and Cloud Computing

Recognizing the growing demand for scalability and accessibility, Newton DEM Software is compatible with cloud computing platforms. This facilitates the execution of resource-intensive simulations on remote clusters, reducing computational bottlenecks and accelerating research and development efforts.

Comprehensive Support and Training

Effective use of DEM software requires proper training and support. Newton DEM Software provides comprehensive training materials, documentation, and customer support to assist users at every stage of their simulations. This ensures that users can leverage the full potential of the software and achieve meaningful results.

Incorporating Newton DEM Software into DEM studies enhances the capabilities of researchers and engineers, enabling them to tackle increasingly complex granular material problems across a spectrum of industries. Its combination of high-performance simulations, advanced contact mechanics, multiscale modeling, and integration with other simulation techniques makes it a valuable asset for those seeking to push the boundaries of DEM.

In conclusion, the capabilities of Newton DEM Software exemplify the ongoing evolution of computational tools in solving real-world problems. Its user-friendly interface, extensive material models, and support for multiscale modeling and coupling with other simulation techniques empower researchers and engineers to explore the behavior of granular materials with unparalleled accuracy and efficiency. As industries continue to advance, Newton DEM Software stands as a reliable and indispensable tool in the realm of Discrete Element Modeling.

Read more about:

Little P.Eng. for Discrete Element Modeling (DEM) Services: Unveiling the Power of Simulation

Little P.Eng. for Discrete Element Modeling (DEM) Services

Tags:

Artificial Intelligence

Discrete Element Modeling

Mixing

Geotechnical Engineering

Granular Materials

DEM Studies

Simulation

Particle Interaction

Pharmaceutical Manufacturing

Mining

Food Processing

Civil Engineering

Soil Mechanics

Landslide Prediction

Tablet Compression

Powder Flow

Crushing

Material Handling

Concrete Mixing

Soil Compaction

Computational Intensity

Particle-Particle Interactions

Multiscale Modeling

Machine Learning

GPU Acceleration

High-Performance Computing

Newton DEM Software

Contact Mechanics

Cloud Computing

Validation

Bulk Material Handling & Processing

Engineering Services

Located in Calgary, Alberta; Vancouver, BC; Toronto, Ontario; Edmonton, Alberta; Houston Texas; Torrance, California; El Segundo, CA; Manhattan Beach, CA; Concord, CA; We offer our engineering consultancy services across Canada and United States. Meena Rezkallah.

[gaminghardware0]

AMD and Nvidia end 2019 going head-to-head on FEM physics

AMD and then, by way of an ‘us too’ announcement, Nvidia, have announced brand new game physics middleware to deliver unprecedented levels of physical material interaction using the finite element method (FEM), if you’re an AMD bod, or finite element model (also FEM) if you’re an Nvidia dev. The two GPU giants are chasing the same physics, they just can’t agree on the exact unpacking of the acronym. But thankfully the FEM physics thing isn’t anything as grubby as it might have sounded to an industry where the Dead or Alive franchise exists.

First off AMD announced its own FEMFX library as part of its open source GPUOpen project. That means the entire implementation source code is freely available under its existing GPUOpen licensing. That includes source for an Unreal Engine plugin to demonstrate “custom rendering and scene creation” to aid UE devs get started.

Then, to show that it was in on the FEM train too, Nvidia announced its own version that’s coming soon in the new PhysX 5.0 SDK. It also went one better, because of course it did, to announce that it was also using the discrete element model (DEM) for advanced liquid simulation in PhysX 5.0.

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RELATED LINKS: AMD Ryzen 9 3900X review, AMD Radeon RX 5700 XT review, Best CPU for gaming from https://www.pcgamesn.com/amd-nvidia-head-to-head-fem-physics

[engineercity]

Новости сайта #ENGINEERING - 工程

New Post has been published on https://engineer.city/new-report-provides-guidelines-for-powder-handling/

New report provides guidelines for powder handling

EDEM has produced a report providing a review of the latest research and advances in the field of powder calibration alongside guidelines for realistic simulations of powder behaviour using The Discrete Element Method (DEM).

  Powders are at the core of numerous applications in the pharmaceutical, food, additive manufacturing, chemicals and other process manufacturing industries. Powder handling and processing presents unique challenges to industry because of the variable physical characteristics and flow properties of powders. Understanding powders’ flow behaviour is critical to ensure manufacturing efficiency and avoid quality issues with the final product. The Discrete Element Method has proven to be a powerful tool to model and simulate a range of powder applications — providing key insights into processes such as mixing, granulation, segregation, coating, spreading, compaction and milling.   One critical aspect in powder simulations using DEM is the formation of suitable virtual materials that provide a realistic representation of the behaviour of the real material. This can be achieved by calibrating the input parameters and it is an important step towards accurate DEM simulations. However, it is also a genuine barrier for DEM applications and a challenge for many.   To help users address this challenge, EDEM worked with leading organisations and experts from industry and academia to understand common problems and practices in powder calibration and comprehend the latest research advances in the field. This included hosting a ‘DEM Powder Calibration’ meeting in Edinburgh which involved representatives from leading pharmaceutical companies, researchers from universities as well as powder testing equipment providers Freeman Technology and Granutools.   The findings and outcomes have been made available publicly by EDEM, in the form of a technical report that discusses the latest challenges and advances in powder simulation as well as providing guidelines for calibration. This comprehensive document discusses several key topics such as factors affecting particle behaviour, standard calibration methodology, criteria for designing suitable calibration tests and critical factors per application area. It also describes the most common calibration tests available such as static and dynamic angle of repose, tapped density test and also more sophisticated tests such as FT4 Freeman Rheometer and Ring Shear cell test with guidelines as to which test is most suitable depending on the application.   Dr Marina Sousani, EDEM engineer and main author of the report explained: “Many  don’t know where to get started when it comes to simulating powders and unfortunately there is not one right answer when it comes to powder calibration. We realised that the issues and challenges faced are the same for many users, therefore we wanted to use our knowledge and experience to offer practical solutions and guidelines to help them develop appropriate DEM models and have confidence in their simulation results. This report is the first step in this direction and we intend to update it as research and developments progress.”

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powder processes

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Process

[10] Materials Handling

Source: engineerlive.com

[barrylara8]

Computer-Aided Engineering for New Age Engineers

Computer-aided engineering (CAE) is an interactive and sophisticated computer software, used to solve engineering problems. Multibody Dynamics (MBD), Finite Element Analysis (FEA), optimization, and Computational Fluid Dynamics (CFD) are the chief tools used in CAE. This software improves the engineering tasks by analyzing the performance and toughness of the assemblies and their components. CAE software is extensively used in automotive, electronics, industrial equipment, and defense & aerospace among other end-use industries. Innovative Software for Material Simulation EDEM, a pioneer in Discrete Element Method (DEM) technology has launched “EDEM for” software, in 2017. This software can enable bulk material simulation with the help of FEA and MDB software. The software is designed for heavy equipment. It can extend capability of the host software. It can also provide an insight into the interaction between materials and equipment. This software can integrate with CAE software with MSC Software, ANSYS, and Siemens that do not involve DEM. Complexity of bulk material simulations is a hindrance for many design engineers. Versatile Applications This new software can be useful for the engineers working in off-highway, construction, mining, and other heavy industrial sectors. It equips them with a library of thousands of material models that represent a range of material such as ores, rocks, and soil. This can provide them with accurate and realistic information about the reaction of material loads on equipment. This analysis is carried out in an environment familiar for the engineers. This can improve accuracy and reduce expensive physical prototyping. Market Overview According to a new study by Grand View Research, Inc.; the worldwidecomputer aided engineering (CAE) market is projected to reach USD 12.8 billion by 2025. Integrated software solutions have eliminated the requirement for multiple prototypes. This can drive the market at a steady CAGR during the forecast period (2014 to 2025). High emphasis on analyzing the temperature and increasing life expectancy of the battery modules can further support the expansion. Market Competitors Major players operating in the global market for computer aided engineering are NEC Display Solutions, Ltd., BenQ Corporation, Seiko Epson Corp., and Casio Computer Co. Ltd. Most companies engage in mergers & acquisitions to obtain novel software technologies. In-Depth research report on computer aided engineering (CAE) market:http://www.grandviewresearch.com/industry-analysis/computer-aided-engineering-cae-market

[muzaffar1969]

http://ift.tt/2oX7OXk

Publication date: Available online 24 April 2017 Source:CIRP Annals - Manufacturing Technology Author(s): Young Sup Kang, Fukuo Hashimoto, Stephen P. Johnson, Jerry P. Rhodes A model has been developed to investigate the three-dimensional media motion during the vibratory finishing processes. This work presents a vibratory finishing machine model using a discrete element method (DEM) that calculates the media interactive normal and tangential contact forces among the media particles. The DEM model predicts the dynamic motion of individual particles inside the vibratory machine container based on Hertzian contact mechanics. The influence of contact parameters such as contact stiffness, friction and damping on media motion has been investigated to determine the critical operating parameters for the vibratory finishing process. The simulation results have been validated with experimental data. This model provides an understanding of vibratory finishing process fundamentals, guidelines for vibratory finishing machine design and optimal operating conditions. April 25, 2017 at 09:34AM http://ift.tt/2pfNEYP from http://ift.tt/2pfNEYP

[nnn-res-blog]

A sequential DEM-FEM coupling method for shot peening simulation

Publication date: 15 June 2017 Source:Surface and Coatings Technology, Volume 319 Author(s): Fubin Tu, Dorian Delbergue, Hongyan Miao, Thierry Klotz, Myriam Brochu, Philippe Bocher, Martin Levesque Shot peening is a cold-working process widely used to form and enhance the fatigue life of metallic components. The process consists of projecting high-velocity particles onto a metallic surface. This study introduces a new, and experimentally validated, sequentially coupled Discrete Element Model (DEM) - Finite Element Model (FEM) to predict the process' effects in terms of residual stresses and roughness. A shot stream was first simulated in DEM to obtain the velocity distribution of impacting shots. The target's progressive hardening was accounted for by adjusting the Coefficients of Restitution (CoRs) for shot-target interactions as the number of impacts evolved through a meshless method. The extracted impacting shots were then impinged onto a representative cell in a dynamic FEM model to evaluate the shot peening effects. The simulations were compared against experimentally measured roughness and residual stresses at full coverage. The study shows that using a constant average CoR yields results that are quite similar to those with an evolving CoRs, for a fraction of the computational cost. Moreover, cases where shot-shot interactions were accounted for yielded lower residual stresses and roughness than cases where such interactions were not accounted for. Nevertheless, all simulated cases delivered simulations that were in good agreement with the experiments, which validates the proposed approach. Read more from Journal of Safety Research http://ift.tt/2pkoV31