Introduction

In the fast-paced world of engineering simulations, Ansys Rocky stands out as a game-changer for particle dynamics. Whether you’re working in mining, pharmaceuticals, agriculture, or any industry that deals with bulk materials, Ansys Rocky provides unmatched accuracy, speed, and scalability in Discrete Element Method (DEM) simulations.

As industries push the boundaries of digital engineering, integrating Ansys Rocky with CFD (Computational Fluid Dynamics), FEA (Finite Element Analysis), and Multiphysics solutions ensures a comprehensive approach to real-world problem-solving. In this blog, we’ll explore how Ansys Rocky is reshaping engineering design and how you can leverage it for optimized results.

What Makes Ansys Rocky Stand Out?

1. Advanced Particle Shapes and Breakage Modeling

Unlike traditional DEM tools that rely on spherical approximations, Ansys Rocky allows for realistic particle shapes, including clusters, fibers, and shells. This results in highly accurate predictions of bulk material behavior, leading to more reliable product designs and operational insights.

2. Seamless Multiphysics Integration

By integrating with Ansys Fluent and Ansys Mechanical, Ansys Rocky enables users to study:

• Fluid-particle interactions (ideal for industries like pharmaceuticals and food processing)
• Structural loads due to bulk materials (important in conveyor and mining applications)
• Thermal effects on particle flow This synergy provides engineers with a holistic understanding of how materials behave under various conditions.

3. GPU Acceleration for Faster Simulations

Time is money, and Ansys Rocky ensures maximum efficiency with its GPU-accelerated solver. Users experience up to 50x faster computation speeds compared to traditional CPU-based solvers, significantly reducing simulation time and enabling rapid design iterations.

4. Realistic Conveyor and Comminution Analysis

For industries dealing with bulk material transport, Ansys Rocky provides detailed conveyor belt wear analysis and crusher/grinder efficiency predictions. These insights help manufacturers optimize equipment lifespan, reduce downtime, and improve overall productivity.

Our exclusive webinar will walk through real-world case studies, demonstrate simulation workflows, and show how Rocky integrates with other Ansys tools effectively. 

Industry Applications

1. Mining and Material Handling

• Predict and mitigate conveyor belt wear and tear
• Optimize grinding and crushing efficiency
• Reduce maintenance costs and improve operational reliability

2. Pharmaceuticals and Food Processing

• Model tablet coating and powder mixing
• Improve granulation and capsule filling processes
• Enhance product uniformity and reduce waste

3. Agriculture and Fertilizer Production

• Simulate grain flow and storage behavior
• Optimize fertilizer blending and application processes
• Reduce handling losses and ensure product consistence

How to Get Started with Ansys Rocky

Step 1: Define Your Simulation Objectives

Identify what you want to achieve—whether it’s reducing equipment wear, optimizing material flow, or improving product consistency.

Step 2: Import and Set Up Geometry

Ansys Rocky allows direct CAD imports, making it easy to create accurate simulations with real-world geometries.

Step 3: Select the Right Particle Model

Choose from a variety of particle shapes and material properties to best represent your system.

Step 4: Run GPU-Accelerated Simulations

Leverage parallel processing for faster and more detailed results.

Step 5: Analyze and Optimize

Use Ansys Rocky’s visualization tools to interpret results and refine designs for maximum efficiency.

Conclusion: Why Ansys Rocky is a Must-Have for Engineers

Ansys Rocky is more than just a DEM tool—it’s a simulation powerhouse that bridges the gap between physics-based modeling and real-world applications. With advanced particle modeling, seamless multiphysics integration, and high-speed processing, it is a must-have solution for industries looking to innovate and optimize their bulk material handling processes.

If you’re ready to take your simulations to the next level, contact us today for a demo or trial of Ansys Rocky and see how it can transform your engineering workflow! Our upcoming webinar showcases the advanced simulation tool designed for modeling granular and discontinuous materials across industries like pharmaceuticals, mining, food processing, and manufacturing.

ANsIntroduction

In modern electrical engineering, circuit simulation tools play a crucial role in designing and verifying circuits before physical implementation. LTspice and Ansys Nexxim Circuit are two widely used simulation tools, each offering unique advantages for engineers. This blog explores their features, compares their performance, and highlights the best use cases for each.

Background: The Importance of Circuit Simulation

SPICE (Simulation Program with Integrated Circuit Emphasis) has been a cornerstone in circuit analysis since its inception. Over the years, multiple variations of SPICE have emerged, including ISPICE, HSPICE, PSPICE, and LTspice, each catering to different needs. Almost all electrical engineers have used SPICE-based tools for verifying circuit designs, debugging performance issues, and optimizing circuit parameters.

Project Overview: Comparing LTspice and Ansys Nexxim Circuit

For this study, a two-stage operational amplifier (op-amp) was simulated using both LTspice and Ansys Nexxim Circuit. The key design specifications included:

• Gain @ 1kHz > 40dB
• Unity Gain Frequency > 50kHz
• Phase Margin > 45˚
• Gain Margin > 10dB
• Quiescent Current ≅ 100µA
• Compensation Capacitor < 30pF
• Compensation Resistor < 1000kΩ
• MOSFET Model: 0.18µm CMOS

The primary goal was to determine how each tool handled the circuit simulation process, from defining models and parameters to analyzing compensated and uncompensated results.

LTspice: Strengths and Workflow

LTspice is a widely used, free circuit simulation tool developed by Analog Devices. It allows engineers to:

• Define subcircuits using .model for MOSFETs
• Assign design parameters (W/L ratios, bias voltages) using .param definitions
• Use hierarchical subcircuits for modular design
• Perform transient and frequency-domain analysis
• Visualize circuit behavior with node plotting

LTspice is known for its simplicity and efficiency, making it an excellent choice for small-to-medium-sized analog circuit designs.

Ansys Nexxim Circuit: Advanced Features and Workflow

Nexxim Circuit, a part of Ansys’ circuit simulation suite, offers all the capabilities of LTspice with additional advanced analysis features. Key capabilities include:

• Defining model blocks for MOSFETs
• Using project variables for W/L ratios and bias voltages
• Performing transient, frequency-domain, and DC sweep analysis
• Conducting signal integrity, resonant, and time-varying noise analysis
• Using structure blocks for trace and via modeling
• Co-simulating with FEM (Finite Element Method) analysis
• Parameterizing and optimizing circuit designs

Results: LTspice vs. Nexxim Circuit Performance

The two tools were used to simulate both uncompensated and compensated versions of the op-amp. The results showed that both LTspice and Nexxim Circuit provided comparable basic simulation accuracy. However, Nexxim’s Optimetrics feature allowed advanced optimization of the circuit parameters, leading to an improved design with minimized component values while maintaining target performance.

Conclusion: Which Tool Should You Use?

• Use LTspice if you need a free, straightforward SPICE simulation tool for basic analog circuit design and debugging.
• Use Ansys Nexxim Circuit if you require advanced analysis, signal integrity testing, co-simulation with FEM, and automated circuit optimization for high-performance applications.

For engineers working on high-speed digital circuits, RF applications, or signal integrity-focused designs, Nexxim Circuit is the superior choice due to its extended analysis capabilities and optimization features. However, LTspice remains a go-to tool for quick, effective circuit verification in analog and power electronics design. Want to see LTspice and Nexxim Circuit in action? Watch our detailed breakdown and simulation walkthrough on YouTube! If you’re interested in learning more about circuit simulation techniques and best practices, don’t miss our upcoming webinar on LTspice vs. Ansys Nexxim Circuit: Advanced Simulation Techniques.

Introduction

Torque is a fundamental aspect of fastening technology, ensuring that components remain securely connected under various loads and operating conditions. In threaded fastener assemblies, torque application must be carefully analyzed and controlled to prevent issues such as joint loosening, fatigue failure, or excessive stress on the materials involved. Engineers rely on torque analysis to optimize design, improve reliability, and enhance performance in mechanical assemblies ranging from automotive applications to aerospace and heavy machinery.

Understanding how torque is absorbed and distributed within a threaded assembly is essential for accurate predictions of joint behavior. This blog explores the three primary areas where torque is absorbed, introduces different simulation techniques available in Ansys Mechanical, and explains methods for validating torque using both traditional analytical approaches and modern computational tools. By leveraging these methodologies, engineers can make informed decisions that enhance the efficiency and safety of fastener assemblies.

Torque Distribution in Fastener Assemblies

Torque applied to a threaded fastener assembly is primarily absorbed in three main areas:

1. Underhead Friction
2. Thread Friction
3. Developing Clamping Force that holds components together

The net distribution of torque among these areas plays a crucial role in fastening integrity and performance.

Torque-Angle Relationship

The torque-angle of turn relationship is a valuable method for determining torque using traditional techniques, such as hand calculations. This approach helps engineers estimate torque with reasonable accuracy, ensuring secure fastener connections.

The net distribution of the torque in these 3 main areas is given as below:

Method 1: Helical Thread Trajectory Simulation

There are several techniques to simulate geometric interference from torque. One approach involves driving the parts in Ansys Discovery along the helical thread trajectory. This method simulates both rotational and axial movement due to torque, creating geometric overlap. To achieve accurate results, the contact offset is set to zero, allowing the actual geometric interference to represent torque application.

Method 2: Contact-Based Interference Simulation

Second method involves simulating applied torque through contact-based interference. This technique models torque effects by defining contact conditions where the original geometry shows parts merely touching. The simulation then resolves the resulting interference forces.

There are couple of different ways to validate torque; one is using traditional method such as hand calculations and second method is to use CAE, in this case, using Ansys.

Traditional Methods to determine torque:

Method 1 is to use the torque-angle of turn relationship as shown below.

Method 2 is to take the contact element data and output via ETABLE, and the contact pressure is multiplied with contact elements to contact normal force which is then multiplied by friction coefficient to get shear force on each contact element. The shear force is then multiplied with distance of contact element (Centroid) from axis to get torque on contact element and then it’s summed from all contact elements to get overall torque.

Methods to Validate Torque

The Ansys methodology also offers several options. One way is to output solution result tracker as shown illustrated below:

Second way would be to use an MAPDL macro that will deliver the results automatically.

Summary

The difference in the two ways demonstrated here; using the result tracker, Ansys is assuming unity friction coefficient, so user would need to scale the results with appropriate friction coefficient as demonstrated here. For the MAPDL macro, it’s fully automated, the user plugs in the friction coefficient and the total torque is delivered.

The techniques presented here provide ample options for the user to determine total torque; the automated ways using Ansys are accurate and the traditional methods provide quick and dirty answer that gives us a ballpark estimate for a good sanity check. One can use this technique to not only validate torque, but also calibrate the torque if actual angle of turn is unknown through couple of design iteration runs.

The techniques discussed provide engineers with multiple options for torque validation:

• Ansys-based automated methods offer high accuracy and efficiency.
• Traditional hand calculations serve as quick, approximate checks.

Beyond torque validation, these approaches can also help calibrate torque in cases where the actual angle of turn is unknown. By performing multiple design iterations, engineers can refine torque estimates and optimize fastener performance in real-world applications.

Additional Resources

For more insights, check out the following resources:

• Watch a detailed video on torque analysis on YouTube
• Watch full webinar on evaluating torque values on threaded fasterners 

Recently I had an amazing reunion with my friends and mentors, Dwight Yoder and Steve Jordan, in Sanibel Island, FL. Our wives, Carolyn, Donna, and Anne joined us in this remarkable event. Steve and Dwight have been my friends and mentors my entire professional life.

In 1977 Steve and his business partners, Mike Apostal and Chuck Ritter, founded Jordan, Apostal, Ritter Associates Engineering Mechanics Consultants in Davisville, RI.  JAR began to do engineering mechanics consulting for the AMOCO Research Center in Tulsa, OK. JAR and AMOCO were two of the first companies to utilize the finite element method to model the lower part of the drill string, called the bottom hole assembly, to predict directional drilling for the oil and gas industry. JAR’s work with AMOCO led to Steve, Mike and Chuck creating Drilling Resources Development Corporation in Tulsa, now DRD Technology, to work with AMOCO to develop a drilling simulator to model the entire drilling process in real time. Steve hired Dwight and me in 1981 to join DRD, and our work with AMOCO led to software development for other oil and gas companies. Ultimately DRD developed its own commercial suite of software tools for the oil and gas industry, Wellplan™, which we sold worldwide.

Because of a relationship with John Swanson, founder of Ansys, JAR and Drilling Resources Development Corporation became Ansys Support Distributors in 1984. JAR later became Ansys East in the 1990’s. Steve, Mike and Chuck also founded Concurrent Engineering Corporation in Minneapolis, MN in the 1990’s, which later became Ansys Minneapolis. Earlier in his career Steve worked with several of the pioneers of the early finite element industry including Richard Gallagher of Bell Aerosystems, Cornell University and University of AZ; Richard MacNeal of MSC (NASTRAN); Pedro Marcal and Bob Melosh of MARC Analysis; and David Hibbitt of Hibbitt, Karlsson, and Sorenson, developer of ABAQUS. Steve offered me the opportunity to have a career in the field of engineering simulation, and he mentored me closely my first two decades at DRD.

Dwight has also been my friend and mentor my entire career. In 1995 DRD sold Wellplan to Landmark Graphics, a division of Halliburton. Dwight and I were colleagues at DRD until 1995 when Dwight left DRD to become a Vice President at Landmark Graphics. Dwight later returned to work at DRD before leaving DRD a second time to pursue other interests. Dwight remains a minority owner of DRD. Dwight and Carolyn are god parents to Anne’s and my daughters, Renee and Morgan.

This Sanibel reunion was the first in-person one for Dwight, Steve, and me in 26 years, and the experience was as if we had never been apart.  What a reunion!

The development of modern firearms and ammunition presents significant challenges. Engineers must balance performance, reliability, and safety while keeping costs and production efficiency in check. Traditional methods rely heavily on physical prototyping, which can be time-consuming and expensive. Additionally, factors such as barrel dynamics, bullet drag, thermal effects, and recoil must be optimized to ensure a firearm function effectively under various conditions.

Accuracy is one of the most critical factors in firearm performance. Barrel vibrations, thermal expansion, and rifling design all influence how precisely a bullet reaches its target. Likewise, excessive recoil can reduce shooter comfort and control, while poor thermal management in high-rate firing scenarios can cause overheating, leading to component degradation or even catastrophic failures. Understanding and mitigating these issues is essential for advancing firearm technology. This blog explores the role of physics-based simulation in firearm development and how it contributes to cutting-edge advancements in the industry.

To dive deeper into these challenges and explore solutions, join our exclusive webinar and watch our in-depth video demonstration on firearm simulation techniques.

What is Physics-Based Simulation?

Physics-based simulation involves four critical steps:

1. Providing CAD Geometry – Creating a digital model of the firearm or ammunition component.
2. Generating a Computational Mesh – Breaking down the model into smaller elements for analysis.
3. Setting Up Physics Parameters – Incorporating factors such as sliding friction, pressure, heat transfer, and material properties.
4. Post-Processing Results – Analyzing the simulation output to make simulation-driven design decisions.

Each type of physics—mechanical, fluid dynamics, and electromagnetics—has its own set of constitutive equations, allowing for quantitative predictions of firearm behavior.

The Role of Simulation in Firearm Development

Engineers can conduct virtual prototyping and design verification, accelerating the product development process. Simulation helps solve fundamental laws of physics, including mass, momentum, and force balances, providing insights that enhance accuracy, durability, and safety. The following are key applications of Ansys in firearm engineering.

• Barrel Dynamics and Accuracy
  

Barrel dynamics significantly impact firearm accuracy. Simulation enables engineers to tune barrel dynamics by analyzing vibrations and harmonic frequencies, ensuring minimal muzzle movement.

• Bullet Drag Prediction and Optimization
  

Predicting aerodynamic drag is crucial for improving projectile performance. Ansys simulations analyze bullet shape, rifling effects, and gas dynamics to minimize drag and enhance accuracy. By optimizing groove length and depth, engineers can achieve better flight stability and range.

• Thermal Management for High Firing Rates

Excessive heat buildup in barrels and suppressors can lead to safety risks, including accidental cook-off. Ansys simulations evaluate thermal distribution in rapid-fire scenarios, helping to mitigate overheating and structural deformation. Thermodynamics, such as non-uniform barrel heating, can also be assessed to optimize material selection and structural integrity.

• Reducing and Predicting Felt Recoil

Recoil affects shooter comfort and accuracy. Simulation allows for ergonomic analysis, studying the effects of force distribution, action delay, and muzzle devices like barrel porting or brakes to reduce perceived recoil.

• Suppressor and Muzzle Blast Characterization

Suppressors are designed to dissipate pressure waves and reduce noise. Ansys simulations predict gas expansion and pressure variations, optimizing suppressor efficiency while maintaining firearm performance.

• Functional Testing

Mechanical components such as triggers, bolts, and actions require precise tolerances for smooth operation. Simulations assess tolerance stacking, material properties, and wear characteristics to ensure reliable firearm functionality before physical prototyping.

• Ballistics and Body Armor

Simulation plays a key role in assessing bullet impact on composite armor. Engineers can analyze penetration power, velocity requirements, and material resistance to improve both ammunition and protective gear designs.

Conclusion

Ansys simulation tools provide a competitive edge in firearm development by enabling precise, simulation-driven design optimizations. From improving accuracy and durability to reducing recoil and optimizing thermal management, physics-based simulations empower engineers to push the boundaries of firearm innovation. As technology continues to evolve, simulation-driven development will remain at the forefront of the industry, ensuring safer and more effective weapon systems for the future.

Want to see these simulations in action? Our webinar and video dives deep on firearm development with Ansys.

Understanding stress vs. strain is fundamental for engineers working with material properties. However, a critical distinction exists between the stress-strain data obtained during tensile tests and the true stress-strain data required for accurate simulations in software like Ansys Mechanical.

In this article, we’ll uncover the essential differences, explain how to calculate true stress and strain, and explore why these concepts are indispensable for accurate elastic-plastic material simulations.

What is Measured and Calculated During Material Tensile Testing?

If you were to internet search for a material’s stress vs. strain data or look in the back of an engineering mechanics textbook, the stress vs. strain data provided is typically in the form of engineering stress and strain. Tensile testing for stress vs. strain is performed using tensile coupons like the layout shown in Figure 1.

This layout includes data that is measured as part of the test, where:

• P = the applied load
• A = the initial cross-section area
• l₀ = the initial extensometer length
• l = the new extensometer length after applying load P

The calculated stress and strain are:

σ_engineering = P / A

ε_engineering = (l – l₀) / l₀

These are engineering stress and strain because the calculation is performed using the initial cross-section area. However, as the tensile coupon is loaded the cross-section area reduces due to the Poisson Effect. For small values of stress and strain, the difference between engineering stress and strain and true stress and strain is low and approximated as equivalent.

Determining True Stress and Strain

There’s a handy pair of equations to calculate true stress and strain using the calculated values.

σ_true = σ_eng (1+ε_eng)

ε_true = ln (1+ε_eng)

These are simple to evaluate using the engineer’s second-best tool, Excel (the first being Ansys, of course).

Why is this Distinction Important?

You may be saying to yourself, “This doesn’t seem like that big a deal. Why are you telling me this?” It’s important to understand how simulation codes perform finite element calculations.

Let’s consider a hypothetical test procedure, where we take the tensile test coupon shown in Figure 1 and stretch it from 10mm to 12mm. This is a change in length, ∆l, of 2mm. Using the equation above for engineering strain, we can calculate an engineering strain value of:

ε_engineering = 2/10 = 0.2 mm/mm

Okay… straight forward. Let’s break that up into two steps on a second tensile test coupon. Step 1 will stretch the coupon from 10mm to 11mm and step 2 will stretch it from 11mm to 12mm; then we can simply add these two strain values to get the total strain. Pretty simple, eh?

ε_engineering = 1/10 + 1/11 = 0.191 mm/mm

What you should notice is that these two measurements do not produce identical strain values, despite both tests stretching the tensile coupon the same amount. So, what does this mean for simulation?

The second tensile test, where strain is calculated in incremental stages, directly resembles how strains are calculated in Ansys Mechanical simulation from incrementally applied loads. If analysts use engineering stress and strain as input to the plasticity material models in Ansys Mechanical, each additional increment in load represents error in the strain calculation.

Let’s redo the calculation above using true strain. The third tensile test coupon:

ε_true = ln (12/10) = 0.18232 mm/mm

And the fourth:

ε_true = ln (11/10) + ln (12/11) = 0.18232 mm/mm

As you can see, we calculate identical results using true strain. This behavior is desirable in Ansys simulation and is why Ansys Mechanical requires using true stress vs. strain as input for the elastic-plastic material models.

In fact, if you peruse the Ansys Help documentation you’ll find this note:

Hmmm… this just stated what I spent ~600 words saying. That’s alright; hopefully the illustrated examples with the tensile test coupons are helpful.

Where Else Can Analysts Learn About Ansys and Plasticity?

If you are interested in learning more about Ansys and plasticity in simulation, DRD has on-demand training content on our website. This particular topic is covered in our Nonlinear Structural Simulation course, in Chapter 3.

Ansys Mechanical Nonlinear Structural Simulation – DRD Technology

Released on July 23, 2024, Ansys Mechanical 2024 R2 introduces a powerful new native feature: Fluid Penetration Pressure. While this isn’t entirely new to Ansys, as it has long been part of Ansys APDL, it’s the first time this functionality is available natively in Ansys Mechanical. This feature provides engineers with an efficient way to simulate fluid interactions with structures without explicitly modeling the fluid in finite element analysis (FEA).

What is Fluid Penetration Pressure?

Fluid pressure penetration is a method to capture impinging fluid on a structure, without explicitly modeling the fluid in the finite element analysis.

The fluid penetration pressure method employs information of contact status between contacting bodies to determine where the fluid pressure is applied. The benefit is that this is determined as the contact status evolves over the simulation time, so the region where pressure is applied changes as contact between bodies changes under loading.

Users provide a contact region for the searching algorithm, a starting location for fluid impingement, and the fluid pressure; the solver does the rest. Figure 1 provides a simple view of the starting point on the exterior surface of the structure and the ‘flow’ of the fluid outward.

Figure 1: Schematic of Fluid Penetration Pressure Behavior

What is the Application of Fluid Penetration Pressure?

As you perhaps have guessed, the application of fluid penetration pressure is in seals and gaskets for valves, hydraulic cylinders, coil-overs, etc. This allows determination of sealing surface leakage as the structure is loaded and deforms, both from the fluid pressure itself and additional loads in service.

Figure 2: Examples of Gaskets

If engineers can determine seal capability before selling the product, expensive redesign can be circumvented. Seals do not need redesign, re-machining of the sealing surfaces is lessened, and a potentially hazardous leak can be avoided.

Example Simulation with Fluid Penetration Pressure

Here we have a simple representation of a tube, sleeve and O-ring seal in a vehicle strut or coil-over. During the assembly process, the tube is pushed downward to interface with the O-ring. In service, fluid is pushing against the seal from the top in the shown orientation, annotated by the blue arrows in Figure 3. The sleeve is fixed in place.

Figure 3: Layout of Simulation with Fluid Impingement Load Direction

As stated previously, analysts need to supply a contact, a starting point, and a fluid pressure magnitude. In the 2D axisymmetric representation of the structure in Figure 3, frictional contact is defined between the three bodies. The Fluid Penetration Pressure object is defined as shown in Figure 4.

Figure 4: Example Use of Fluid Penetration Pressure Feature, Details, Load, and Graphics

As you can see, we’ve applied the fluid pressure in the second load step; the first load step is moving the tube downward.

I’ll leave you with these final output animations, and a recommendation to visit our website to get access to on-demand training.

We walkthrough this simulation example as part of our Ansys Mechanical Nonlinear Structural Simulation course. Follow the link here: Ansys Mechanical Nonlinear Structural Simulation – DRD Technology.

When solving complex models in Ansys Mechanical, several common errors may arise. In this blog, we’ll explore three frequent error scenarios—DOF limit exceeded, unconverged solutions, and element formulation errors—and provide solutions for each.

Error Scenario 1: DOF Limit Exceeded

This error indicates that at least one body in the model has reached a degree of freedom (DOF) limit, often due to rigid body motion (RBM). Mechanical will prompt you to check for insufficient constraints. This situation is typically a result of rigid body motion (RBM), and Mechanical will have a message suggesting the user search for insufficient constraints.

In a static analysis, every part in the model must be constrained so it cannot freely rotate or translate. RBM is a consequence of one or more parts being insufficiently constrained. Check that there are enough external constraints on the model (i.e. supports) to prevent RBM. Here’s how to resolve this:

• Ensure that all parts are constrained or connected to supported parts.
• Be attached to supported parts using contacts, joints, or other connections. Mechanical offers a right-click menu in the graphics area with an option that can identify missing connections (below).

If you are depending on nonlinear contacts (Frictionless/Frictional/Rough) to hold the model together, make sure they are initially closed. The Contact Tool is a great help for this. Be aware that nonlinear contacts will not prevent separation, and they may not prevent sliding either.

If you are not able to identify any parts that are underconstrained, try running a Modal analysis with the same supports as your static analysis. The animated deformation plots from the Modal analysis should help you identify what parts need constraints. Pay special attention to modes at 0 Hz or very close to it. The mode animation below shows one part moving without deforming the rest of the assembly, indicating that it is underconstrained. Be aware, however, that Modal analysis forces nonlinear contacts to become linear, so it may not identify all problems with nonlinear contacts.

Error Scenario 2: Unconverged Solution

In this scenario, you may see the line “Reason for Termination … Unconverged Solution” in the solution information, and there will be an Error message in Mechanical that reads, “The solver engine was unable to converge on a solution for the nonlinear problem as constrained.”

This error occurs for nonlinear models. When a model is nonlinear, the solution affects the model’s stiffness, and the solver needs to iterate on a solution until the remaining error is within tolerance. There are three main factors that can cause a model to be nonlinear: material properties like plasticity, nonlinear contact types, and the Large Deflection option under Analysis Settings. One or more of these nonlinearities is responsible for the failure to converge. You will need to identify which nonlinearities are the cause.

The most helpful tool for troubleshooting a force convergence error is Mechanical’s Newton-Raphson Residuals. In the Details of Solution Information, set this to some non-zero value (2 or 3 is usually enough). The plots will only be created if a non-zero value was set before the analysis was solved. You may need to initiate the solve and let it fail again in order to get the Newton-Raphson plots. Adjusting the time steps to ensure it fails quickly is recommended. Before re-attempting the solve, you may wish to try the other troubleshooting steps in this section.

The Newton-Raphson Residual plots will show hotspots (red color) where the residuals are highest. This means you should look for conditions that are scoped to these elements. Often you will see high residuals on elements that are participating in a nonlinear contact region. If so, this contact region needs attention.

Possible solutions to a contact region with high Newton-Raphson Residuals include:

• Mesh refinement on the faces scoped in the contact region.
• Reducing normal stiffness of the contact region to a Factor of 0.1 or 0.01.
• Using a linear contact instead of a nonlinear one if acceptable.
• Using displacement-based loading rather than force-based loading to close a contact region that is initially open.

Aside from the Newton-Raphson Residual plots, there are a few other tools that can help narrow down the reason for non-convergence. Per the last section, make sure the model is fully constrained and rigid body motion is not possible. If any substeps have solved, create True Scale deformation plots for the solved time points and look for any unexpected behavior such as large deformations or assemblies separating. Plots of plastic strain can identify regions that are collapsing due to widespread yielding.

If you’ve reviewed the Newton-Raphson Residual plots and solved timesteps but it still is not clear what is causing the analysis to fail, a useful approach is to remove all nonlinearities from the model and make sure it solves. If it does, then add nonlinearities back into the model gradually. When you reintroduce a source of nonlinearity and the solve fails again, you can be confident that this nonlinearity is what needs attention before the solve can succeed.

Error Scenario 3: Element Formulation Errors

This reason for termination is often accompanied by the error message in Mechanical: “Element N Located in Body (and maybe other elements) Has Become Highly Distorted.” The element formulation error means that certain elements fail to meet criteria that are required to obtain a meaningful solution. Most often the elements have become so distorted that the analysis cannot continue. An ideal element is a cubic hexahedron or a tetrahedron with four equal sides. When elements have high aspect ratios, have highly skewed shapes, or even begin to turn inside out, they are liable to terminate the solver with this error.

The first step is to identify the elements that have the error. Look at the error messages in Mechanical and the Solution Information worksheet for specific element numbers. Then find where these elements are located in the mesh (this video shows how; use the element option instead of the node option).

There is also an option to create Named Selections for element violations under Solution Information. Set this to a non-zero value (2 is usually fine).

Using either the Named Selections or the Select Mesh by ID tool, observe the element shapes and locations. If they are highly skewed, it may help to improve the mesh in that area to get better quality elements.

Another important step is to find out how far the solver made it before the failure occurred, as described earlier. If no substeps solved, then there was a problem applying the initial conditions. Use the Contact Tool to identify contacts that have initial penetration. If you have any nonlinear contacts with initial penetration, use the Add Offset, Ramped Effects setting for those contacts, or Adjust to Touch if you wish to ignore the penetration. Elements in contact regions can easily get distorted when the penetration is removed with the No Ramping setting.

If you do have solved substeps, use the plots of the solved substeps along with the locations of the element violations. (Note again that results set to Display Time = Last are unconverged and are not meaningful.) Are these elements starting to distort just before the failed time step? Is there a lot of plasticity on these elements? If the elements are actually becoming distorted, you may need to improve the mesh to get better initial quality. In scenarios with a lot of plasticity, you may not need to solve the whole analysis if the solved time steps already show levels of plasticity that indicate failure of the product.

Sometimes the elements do not seem to be visibly distorting in the solved time steps. In that case, they may be distorting due to a load being applied too suddenly or due to insufficient constraints. Think about whether there are new loads being applied in the time step that failed, or whether there are parts about to come into contact. Consider ramping loads more slowly or using displacements rather than forces to move parts into contact.

Nonlinear modeling in FEA is a deep subject, and not every scenario or possible solution is covered here. Even so, we hope this guide will provide a starting point that will help you solve complex models in Ansys Mechanical.

Understanding error messages is crucial, but to prevent them, identifying them is key. Don’t miss our blog on how to use Ansys Mechanical’s troubleshooting tools to resolve failed solves and produce accurate results. 

When you initiate a solve in Ansys Mechanical, the program attempts to find a solution based on the boundary conditions you’ve specified. However, not all problems will solve on the first attempt. This guide will show you how to use Ansys Mechanical’s troubleshooting tools to resolve failed solves and produce accurate results. 

How to Identify a Failed Solve

A failed solve is indicated by a red lightning bolt next to the solution. When this happens, Ansys generates error messages that explain what went wrong.

By clicking the Messages button, you can view a list of these messages categorized as Info, Warning, or Error. Warning messages should be read and understood, but they do not always indicate a problem. Error messages are generated when solving (or another action) fails to complete, and these messages explain what happened. You will need to address the cause of the error message before proceeding. Later in this article, we will recommend troubleshooting steps for the most common errors.

• Warnings: Indicate potential issues but may not affect the solve.
• Errors: Must be addressed as they prevent the solve from completing.

Using the Solution Information Worksheet

To further troubleshoot, search the Solution Information worksheet for terms like “error” or “reason for termination.” These messages provide specific details on why the solve failed. Understanding when the failure occurred (e.g., which load steps were completed) is also crucial for narrowing down the issue.

Use CTRL+F to search for “error” and read any error messages you find here. Sometimes there will be more detailed messages here. The last error message is usually the ultimate reason the solve failed.

Also search for the phrase “reason for termination.” If present, this line indicates exactly why the solve failed. Recommendations for interpreting some of the common reasons for termination are described later in this article.

Next, figure out when the solve failure occurred. It is important to know what load steps, if any, were completed before the solve terminated because that will narrow down the cause. For instance, if no time points were solved, the problem may be that the model is initially underconstrained. If the solve completed two load steps and failed on the third, you should look at any changes to the boundary conditions in the third load step.

Select Solution and view the Tabular Data as shown below. This shows that two substeps were solved, and the last successful step was t = 0.45s. The third row that shows Substep = 1e+006 represents the unconverged results and does not mean that t = 1s solved successfully. It can be very informative to create result plots set to the last converged substeps (t = 0.45s in the example below). The results at unconverged substeps are not physically meaningful and should generally not be used.

Once you understand the error that terminated the solve and the load step when the solve terminated, you can take corrective action to make the solve successful. The next steps will depend on the error encountered. For detailed advice, see DRD’s blog on troubleshooting steps based on the most common error messages.

Troubleshooting Tips 

• Check constraints: Ensure all parts are sufficiently constrained to prevent rigid body motion (RBM).
• Review boundary conditions: If the solve failed after completing a load step, inspect changes in boundary conditions.
• Create result plots: Use the last converged substep to identify potential issues. Unconverged substep results are not physically meaningful and should generally be ignored.

Want to dig deeper into advanced troubleshooting? Our blog on using Ansys Mechanical diagnostic tools covers additional tips to help you streamline your solving process

Metal additive manufacturing (AM) has surged in popularity due to its ability to create both prototypes and final production parts. However, this cutting-edge technology comes with challenges, primarily related to thermal strains, part distortion, residual stresses, and build failures. These issues arise from the intense heat transfer involved during the manufacturing process. Fortunately, Ansys Workbench Additive provides a solution by simulating these processes to help manufacturers predict and resolve these problems, ensuring successful part creation without costly trial and error.

The Challenges of Metal Additive Manufacturing

The thermal dynamics of metal additive manufacturing can cause significant issues, such as:

• Part distortion: As heat is applied during production, thermal expansion and contraction can lead to deformation.
• Residual stresses: Unrelieved stress within the material can lead to fractures or failures during or after manufacturing.
• Costly build failures: Without accurate simulation, manufacturers may waste time and resources on failed builds.