ESSS Rocky DEM Activation key

tional N-body code pkdgrav, a well-tested simulation pack- age that has been used to provide The discrete element method (DEM), which. Key Take-Aways · Detailed simulation techniques like DEM, CFD provide critical insights on the process. · Advanced artificial intelligence techniques are now. डाउनलोड ESSS Rocky DEM Crack [Full Latest] आप मदद कर सकतेहैंकेव्यवहार Noted: Version is inconsistent with.

: ESSS Rocky DEM Activation key

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ESSS Rocky DEM Activation key -

ESSS Rocky DEM Model material ESSS Rocky DEM

Download ESSS Rocky DEM 4 - Help you can simulate the behavior of materials and the flow of them with speed and accuracy


ESSS Rocky DEM is the name of a software engineer specializing in simulation the small particles. In fact, with this product, you will be able to model the volume of the material. In fact, you can simulate the behavior of materials and the flow of them with speed and precision. With the help of the simulation is done by this software, you can predict the behavior of the particles very accurately. It predicts the behavior such as energy absorption and percentage of fractured particles and flow analysis material by this software.



You can also use multiple graphics cards at the same time in the simulation ESSS Rocky DEM his. This will make your simulation run faster and operate on large volumes of data than in the shorter time. You can also perform a particle simulation in two-dimensional mode and three-dimensional. Apply the features of flexibility or hardness for the particles, the other features of this powerful software.

The ability to activate the particle motion simulation freely react with the other forces as exposed particles, gravity, etc. is a very useful feature of this software. With such capabilities, you can model reality better than ever. The result of this software is very accurate and you can leave the analysis of the motion of the particles and the change of them with respect to this program.

The features of ESSS Rocky DEM

  • Capable of handling multiple simultaneous graphics card
  • You will simulate the complex motions of particles with changes in it
  • Allows you to modeling the fluid flow in different
  • Provides statistics of particle impact accurate and useful
  • Benefits from the optimization tools and modeling capabilities of heat


Free Download ESSS Rocky DEM 4 full version standalone offline installer for Windows is an effective software for modeling granular media by discrete elements. It allows you to quickly and as realistic as possible to model ix bulk material particles flow with the necessary properties in any process and apparatus.

You can also FREE download Freeplane.

Overview of ESSS Rocky DEM 4 Benefits

ROCKY is a modern software for modeling processes with bulk materials and related equipment. The software product uses the Discrete Element Method (DEM), which allows you to quickly and accurately calculate the behavior of a stream of particles of various shapes and sizes when moving along conveyor lines.

Furthermore, ROCKY differs from other software solutions using the DEM method primarily in the possibilities of using fundamental nonspherical particles, simulating their destruction without loss of mass and volume, and calculating and visualizing abrasive wear working surfaces of equipment elements.

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However, due to the ability to create realistic particle shapes that behave the same as fundamental particles, taking into account various “flow” conditions in ROCKY, one can simulate the operation of almost any installation.

Overview of ESSS Rocky DEM 4 Features

  • Efficient computing;
  • Double precision calculations (using the corresponding GPU function);
  • A wide range of job granulometric composition;
  • Non-spherical particles;
  • Consideration of the rheology of dry and wet materials;
  • Calculation and three-dimensional visualization of abrasive wear of surfaces;
  • The task of rotation, translational and vibrational movement of equipment elements;
  • Integration with ANSYS finite element solvers;
  • Manage the animation of simulation results and create panoramic video reports.

Technical Details and System Requirements

  • Supported OS: Windows 10, Windows , Windows 7
  • RAM (Memory): 2 GB RAM (4 GB recommended)
  • Free Hard Disk Space: 2 GB or more




Next generation DEM Particle Simulator

ROCKY is a 3D Discrete Element Method (DEM) code that simulates the granular flow behavior of different shaped and sized particles, with varying levels of moisture (adhesion), friction and impact restitution along the handling chain of the granular material itself.
Therefore ROCKY is used all over the world by manufacturing and mining companies, to quickly and accurately analyze their bulk material handling systems. The software consists of a single working environment which is accessed by a simple and user-friendly graphical interface, which allows to create the mathematical model, to run the simulation and to evaluate all results necessary for the analysis.

Why ROCKY is different apart from other DEM codes?
ROCKY is the only commercial code that uses an accurate particle shape representation (not cluster of spheres), advanced breakage and fragmentation models, visualization of boundary surface reduction due to wear, complex geometry motion, double precision solver that uses Share-parallel memory with CPU or Multi GPU, extensive code validation and calibration. ROCKY is fully integrated with ANSYS Workbench with Structural and Fluid analysis coupling.

Rocky is a product of ESSS


Fluidized bed simulation (2-way coupling with ANSYS Fluent)

Rocky DEM accurately replicates many types of materials — such as ore, grain, plastic, and metal — and can do so with varying levels of moisture (adhesion).

With Rocky DEM you can mix and match different shape, size, and adhesion combinations to create your own unique particle set.

Large-scale simulations

Process optimization

Complex motion: free body and multi-body motions

Increase equipment life and capacity

Reduce dust, noise and equipment power

Accurate results using real shape particles

Minimize wear and maintenance

Intra-Particle Collision Statistics

Full integrated with structural and fluid analysis within ANSYS

Request a free demo

Send your technical questions to our experts!

Connect you with an EnginSoft expert who can provide a reliable answer to your technical question or recommend a proven solution.

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Improved blast furnace performance with material load optimization

Combining modeFRONTIER with Rocky DEM to design a better deflector saves up to hours of computation time

The Arvedi Group approached the University of Trieste to find a solution to the uneven distribution of material inside the hopper of their blast furnace in Trieste, Italy.

optimization modefrontier rocky mechanics

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Lime Kiln DEM Analysis with ROCKY

CAE is key to ensuring the efficiency and technical integrity of equipment and plants in the lime industry

In the lime industry, the process engineers of Cimprogretti advise on process safety, analyse and interpret laboratory and plant data and provide specialised support to ensure the technical integrity of equipment and plants.

mechanics rocky

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Machine Learning Leveraged Simulation Digital-twins Enabling Real-time Detailed Insights

Jenil Dedhia (jdedhia@homeover.usting), Anagha Consultants


Leveraging data-based/ machine learning approaches for predictive capabilities is a common theme currently in the various stages of the product/ process development life cycle. This helps with linking the relevant inputs of a process to the outputs, without necessarily understanding the underlying physics or interactions.

Figure 1

When one has enough experimental data (either from prior runs or structured analysis) on various inputs and outputs for a given process comprising a set of unit operations, such approaches can be used to develop a process model (Figure 1). Within the applicable parameter window, treating the whole process as a black box, such a model provides predictability into the outputs because of changes in any inputs. We will talk more about this in a separate post.

Focus of this post

In the specialty materials industry (like in pharma or niche materials), where getting experimental data both at the lab or a large scale can be prohibitive, physics-based process models can provide the necessary initial guidance to the practitioner for decision making. Depending on the complexity of the physics involved, such process models may require advanced computations and simulations involving computational fluid dynamics (CFD) or Discrete Element Modeling (DEM). Even with increased computational power, such process models may not meet the needs of a practitioner to get visibility and predictability for real-time decision making. With example cases, this post focuses on leveraging machine learning approaches to address such practitioner needs in providing real time guidance grounded on process physics. (Figure 2)

Figure 2

What is a Simulation?

In process industries, simulation software is traditionally used to obtain insights on the process or asset without having to do experiments. Simulations are typically used in process design and optimization to predict what may happen in the real world and run ‘what-if’ scenarios.

Why ML-leveraged simulation twins?

Detailed simulations which capture the process reasonably are generally computationally-intensive and hence time-consuming, sometimes taking hours to days to give results. This has been hampering the adoption of these tools, like CFD and DEM. AI/ML techniques can be applied on simulation data to provide the practitioner on-the-fly detailed-level insights obtained from the simulation. This enables the practitioner to play out extensive ‘what-if’ scenarios to gain detailed process understanding and to leverage such insights for real-time decision-making.

Let us look at a couple of scenarios.

Use Case (I): ‘Forward’ model

Here we present a case where the developed ML-twin can predict the outcome of a simulation by taking in the inputs which go into the simulation model.

Below is an example of DEM simulation of Powder Flowability test [1], where a bulk powder property Static Angle of Repose (SAoR) is obtained as an outcome of the simulation as shown in Figure 3. Simulations can be run over a parametric space of inputs (like coefficient of static and rolling friction, Young’s Modulus, particle size, particle cohesiveness) to generate data for the ML-model. Here, we use data of 53 simulations reported in the literature [1].

Figure 3

Once the simulation data is cleaned and pre-processed, different machine learning techniques (like Linear Regression, Random Forests, Gradient Boosting, and even Neural Networks) can be evaluated and the best model is identified. Figure 2 shows the results obtained for the model developed to predict SAoR through the above data. The accuracy of the test results indicate no significant dilution of the quality of the SAoR predicted via machine learning approach compared to the detailed simulation.

Figure 4

Hence, an initial investment of some simulations (in this case total ~ hours) can be used to build powerful ML models which can eliminate lot of simulations (in this case, each ranging from few minutes to few hours) in the future and give real-time insights to the users.

Use-Case (II): ‘Reverse’ model

Here, we present a case where the developed ML-twin can predict one of the inputs needed for the simulation for a given desired simulation outcome.

The classic case for such a model is calibration of DEM material parameters. DEM needs intrinsic powder properties as inputs, some of which are hard-to-measure (like for example particle-particle friction properties) for practitioners in the pharma or the additive manufacturing space. This limits the value add of such modeling approach for an industrial practitioner. One way this issue is currently addressed in this field, is as follows [2]. As many bulk properties of the powder (like bulk density, SAoR, dynamic angle of repose etc.) are easier to measure, the practitioner is advised to run multiple DEM simulations of these bulk property setups to identify the right combination of intrinsic properties.

Readers who are acquainted with DEM simulations would know this is a tiring and time-consuming exercise, requiring lot of iterations of simulations. Figure 5 depicts how ML-models can be leveraged to eliminate the calibration exercise by predicting the input property of interest for a desired simulation outcome, in this case, experimentally obtained SAoR.

Figure 5

Key Take-Aways

      • Detailed simulation techniques like DEM, CFD provide critical insights on the process. They require expert users and take long turnaround time for providing insights. This makes them less attractive to the practitioners interested in real time decision making.

      • Advanced artificial intelligence techniques are now available which can be leveraged using these simulation data to provide on-the-fly guidance for the practitioners to take real-time decisions in their routine efforts. As an example, how manual and cumbersome steps within two use cases (involving the application of DEM approaches, and calibration of material parameters) can be expedited, are presented.

      • These ML-models can be ‘Forward’ or ‘Reverse’, i.e. can predict the simulation outcome or the input parameters for obtaining a desired given simulation outcome.

      • Such approaches can help practitioners expedite their process development journey through process understanding.

We hope this article helped you understand how data-driven approaches can be combined with advanced simulation techniques to provide practitioner friendly and simulation level detailed visibility into the process. Such approaches can be leveraged over a range of complex applications, across a range of industries.

See value in this for your process needs?

Interested in exploring how to tailor such a hybrid approach to expedite your process development?

Reach us out at Jdedhia@homeover.usting

PS: These use-cases were developed on ProDTwin platform (, an offering of Anagha.


[1]. El-Kassem, B., et al, , Computational Particle Mechanics


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ESSS Rocky DEM v x64 / Description

Rocky DEM allows precise prediction of the particle behavior of granular and liquid systems by analyzing media flows, energy absorption rates and particle breakage. Wherever large quantities of particles and bodies are set into motion in bulk, mixing, slipping or flow processes regardless of their size, shape, material or adhesion, Rocky can help to understand and improve the processes. These are, on the one hand, measures for optimizing the movement of the mass, for example to minimize material losses or to prevent or suppress dust formation. On the other hand, the results provide important information for efficiently designing peripheral products, for example to increase the service life of conveyor belts and other components.

Key Features:
- Provides decisive insight into granular flow behavior with accurate particle representation
- Fully integrated with ANSYS (CFD and FEA)
- Get access to the key features for optimization of industrial equipment and processes
- Unique ability to utilize one or more GPU cards on the same motherboard
- Configure complex geometry movements by set up as many rotation, vibration, swinging and free-body motions—and combinations
- Two kinds of breakage models are The Ab-T10 model and the Tavares model
- Four unique methods for simulating the interaction between particles and the surrounding fluids (air, water, dust, etc.), known more commonly CFD
- And more

ESSS Rocky DEM v x64 / System Requirements

Please see below for minimum system requirements and optional recommendations.

- bit Windows 7; bit Windows 10
- A video card that supports OpenGL graphics
- 4 GB of free disk space
- 4 GB of RAM
- Two-button mouse with center wheel
- Screen resolution of x

- 8 GB of free disk space
- 8 GB of RAM
- Quad-core or better processor (Intel Core i5, Intel Core i7, or Intel Xeon processor)
- ANSYS SpaceClaim or other CAD software
- Microsoft Excel or other spreadsheet software
- AVI-compatible media player
Additional Requirements for GPU or Multi-GPU Processing
An NVIDIA GPU card (computing or gaming) with at least 4 GB memory and fast double-precision processing capabilities. (Required: The card must have a CUDA compute capability of or higher.)
Additional requirements for CFD coupling
You can use Rocky coupled with the following ANSYS Software versions:
- ANSYS versions to

ESSS Rocky DEM v x64 / Installation Guide

1. Software Software.
2. At the end of the installation, close the LicenseManagement window.
3. From the Crack folder create the Rocky4 folder in the software location (presumably u C: ProgramFiles ESSS) and replace the u file.
4. Run the software, place the LicenseType on the RLM and load LoadLicense in the dropdown window.
5. Paste the file into the Crack folder in the opened window.
6 - Run the related software.
7. Software is fully activated with no limitations on usability

ESSS Rocky DEM v x64 / Download Guide

If you do not have download management software, download download software such as IDM or FlashGet before downloading any files.
To download, click on the "Download" button and wait for the relevant window to appear, then select the location of the file to be saved and wait until the download ends.
In case of a problem downloading files is just enough. In the last link, download the file a question mark? Place the file to be easily downloaded.
Files downloaded to download to reduce volume and get faster compressed, to remove files from the compressed version of Winrar software or similar.
If you see the first, second, and section of the download link, all sections should be downloaded to make the file usable.
The password to open the compressed file is . All the letters should be typed in small and when typing in the EN / FA status of your keyboard note, it is also better to type a password and do not copy it from Copy-Paste.
If you encounter a CRC message during the removal process, if you have entered the password correctly. The file has been downloaded corrupted and you have to download it again.
Crack files due to the nature of the functionality when used may be detected by antivirus as a malicious file. In such cases, temporarily disable your antivirus.
See the download and troubleshooting guide for downloaded files on this page .