2023 – a Year of Magnitude and Direction

2023 marked year 15 for Endurica.  If I had to pick one word to describe the past year, that word would be “vector”.  Because magnitude and direction.  😊

We updated our core value statement this year.  The first one I ever wrote as part of Endurica’s original business plan listed 3 values: technical leadership, customer focus, and trustworthiness.  Those values served us well for many years and in many ways shaped who we have become.  But it was important this year to take stock again.  We’ve grown 8-fold since I wrote those down!  So our team spent many hours revisiting our shared values and deliberating over which will best define our culture and steer us right going forward.  In the end, we decided to keep the first 3, and we added 3 more:  embrace the grit, make an impact, and better every day.

We also completed an exercise to articulate what makes Endurica truly unique in the CAE / durability simulation space.  The 3 words we chose are… Accurate, Complete, and Scalable.

  • Accurate refers to the accurate material models that capture rubber’s many “special effects”, the accurate critical plane analysis method for analyzing multiaxial history, the accurate handling of nonlinear relationships between global input load channels and local crack experiences, and the extensive set of validation cases that have demonstrated our accuracy over the years. Nobody offers a more accurate solution for rubber durability.
  • Complete refers to our complete coverage of infinite life, safe life and damage tolerant approaches to testing and simulation. It refers to feature completeness that enables users to account for nearly any material behavior under nearly any service conditions.  Finally, it refers to the documentation, the materials database, and the examples we distribute with the software and with our webinar series.  Nobody offers a more complete solution for rubber durability.
  • Scalable refers to our capacity to apply our solutions efficiently in all circumstances. Scalability is the training we provide so that users can learn our tools quickly.  Scalability is access to powerful, ready-to-use workflows right when you need them.  Scalability is the modular approach we take to material testing and modeling so that simple problems can be solved cheaply and complex problems can be solved accurately in the same framework.  Scalability is our multi-threading that allows job execution time to be accelerated to complete impactful analysis on tough deadlines.  Nobody offers a more scalable solution for rubber durability.

2023 was not all navel-gazing and new marketing.  We also had magnitude and direction in other areas.

Top 10 Code Developments:

  1. New Endurica Architecture: After several years of development and a soft launch under the Katana project name, we finally completed our migration to the new architecture.  The new architecture provides a huge speed advantage for single thread and now for multithread execution. It uses a new input file format (.json). The json format makes it easier than ever for users to build customized and automated workflows via Python scripting.
  2. Sequence Effects: Sometimes the order of events matters to durability, and sometimes it doesn’t. We introduced Steps and Blocks to our input file, giving users complete control over the specification of multi-block, multi-step scheduling of load cases.  There is also a new output request that came out of this work: residual strength.
  3. EIE: 6 channels and support for RPC: Support for 6 channels of load input was one of our most highly requested new features.  Fast growing use of this feature led to further enhancements of the workflow (support for rpc file format, studies of map building techniques), and new recommendations on how to implement boundary conditions for specified rotation histories in explicit and implicit finite element models.
  4. Queuing: Design optimization studies need efficient management and execution of multiple jobs. Endurica’s software license manager now supports queueing for licenses. Queuing allows a submitted job to automatically wait to start until a license is available, instead of the prior behavior of exiting with a license error. Now you can submit many jobs without worrying about license availability.
  5. Haigh Diagram Improvements: We implemented an improved discretization of the Haigh diagram, and parallelized its evaluation. Now you get much nicer looking results in a fraction of the time. For details, check out our blog post on Haigh diagrams and also read about other improvements like axis limit setting and smoother contour plots.
  6. Viewer image copy: There is now a button! Its easier than ever to get your images into reports.
  7. Documentation Updates: We have been focusing on improving documentation this year. There are many new sections in the theory manual and user guide, as well as a getting started guide and more examples.  Stay tuned for many more examples coming in 2024!
  8. User Defined Planes: It is now possible to define your own set of planes for the critical plane search. One example where you might want to do this would be the situation where you would like to refine the critical plane search on a limited domain of the life sphere.
  9. New Database Materials: We added 7 new carbon black and silica filled EPDM compounds to the database. We are now up to 42 unique rubber compounds in the database.
  10. Uhyper Support: The new architecture now supports user-defined hyperelasticity. If you have a Uhyper subroutine for your finite element analysis, you can use it directly with Endurica.

 

Testing Hardware

We completed the acquisition and installation at ACE labs of a Coesfeld Instrumented Cut and Chip Analyser (ICCA).  The ICCA provides unmatched measurement and control of impact conditions, and provides a way to evaluate rubber compounds for their resistance to cutting and chipping.

 

Applications, Case Studies, Webinars

Never underestimate the students! We were blown away by the work of undergraduates at the University of Calgary with our tools and Ansys.  The students designed an airless tire, completing durability simulations using Endurica software within the scope of a senior design project. They were able to Get Durability Right on a short timeline and a student budget. Check out their multi-objective, high-performance design project here.

Analyzing what happens to tires as they take on the most celebrated testing track in the world might have been the funnest project Endurica’s engineers tackled in 2023. We presented the technical details at The Tire Society annual meeting and more in a followup webinar. An extensive Q&A session followed, and I loved the final question: “So, how long before we have a dashboard display of ‘miles to tire failure’ in our cars?”  Bring it.  We are ready!

Our Winning on Durability webinar series hit a nerve with the Metal Fatigue DOES NOT EQUAL Rubber Fatigue episodes on mean strain (the tendency of larger mean strains to significantly INCREASE the fatigue life of some rubbers!) and linear superposition (for converting applied load inputs to corresponding stress/strain responses). The great response has lead to our third installment on the differences between rubber and metal fatigue with an upcoming presentation on temperature effects.

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Latest Addition: the Coesfeld Instrumented Chip & Cut Analyser

When there is rolling or sliding contact of a rubber surface over a second hard surface of sufficient roughness, localized cutting and damage of the rubber surface sometimes becomes a problem.  It occurs in off-road tires operating on stony surfaces, for example, and it can severely limit the useful life of a tire.  In order to study this “cutting and chipping” failure mode, Endurica last month acquired a new testing instrument: the Coesfeld Instrumented Chip & Cut Analyser (or ICCA).  It has been set up at partner lab ACE Laboratories, commissioned, and it is now ready for running tests.

The ICCA test uses a solid rubber wheel specimen.  These are molded from uncured rubber compound supplied by the client.  Alternatively, the mold can be rented if the client prefers to produce their own specimens.  The ICCA test offers direct control and measurement of the following key parameters

  • Wheel revolution speed
  • Overall impact period, tP
  • Peak impact force, FD
  • Contact duration of impact, tD

Figure 1.  Contact force control signal (left).  Coesfeld ICCA impactor tool actuation (right).

It also records the following measurements

  • Normal force
  • Normal displacement
  • Friction force
  • Friction displacement (i.e. wheel rotation)
  • Abrasion depth

Figure 2.  Normal and friction impact forces and displacements during a single impact.

The Coesfeld ICCA instrument improves on J. R. Beatty’s 1979 “BF Goodrich Cut and Chip” (BFG) test in several ways.  Perhaps the chief improvement is that the force and duration of the impact are accurately controlled and measured.  The BFG test suffers from two major problems: 1) that the impact is passively applied by means of a weighted beam whose natural impact frequency is influenced by the stiffness of the rubber compound, and 2) that the impact forces and displacement are not measured and not easily relatable to applications.  By quantifying the impact conditions of the test, the Coesfeld ICCA offers the opportunity to match those of the actual application.

As the Americas distributor for Coesfeld testing instruments, Endurica is proud and excited to add the Coesfeld ICCA to our portfolio of testing services and testing instruments.  Reach out to us today if you have a need for testing services on the ICCA, or if you would like to bring the Coesfeld ICCA to your lab.

Figure 3.  Endurica President Will Mars and Vice President Tom Ebbott with the newly installed Coesfeld ICCA at partner ACE Laboratories.

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Tolerances in Fatigue Life Prediction with Endurica

I get this question a lot: how well can the Endurica software predict fatigue life?  Is it as good as a metal fatigue code, where a factor of 2x is often quoted as a target tolerance?

The answer is yes, fatigue life predictions can reach and beat this level of accuracy. But as always, knowledge and control of the problem at hand is key.  We must keep in mind that fatigue behavior varies on a logarithmic scale.  It depends on many variables.  It depends on how failure is defined in the simulation and in the test.  Small variations of an input may lead to large variations of the fatigue life.  So, to achieve the best tolerances, careful specification, measurement, and control are required of both simulation and test.

Analysis tolerances depend on whether the analysis workflow is “open loop” or “closed loop”.  In an open loop workflow, the analyst is typically in the position of having to accept without question the as-given material properties, geometry, boundary conditions and load history.  The analysis is completed and reported.  Decisions are made and life goes on.  In a closed loop workflow, there are additional steps.  These include a careful review of differences between the test and the simulation, as well as identification and correction of any erroneous assumptions (about material properties, geometry, boundary conditions, and load history).

Open loop workflows produce larger tolerances.  Every situation is different, but do not expect tolerances tighter than perhaps a factor of 3x-10x in life, when working in open loop mode.  There is just too much sensitivity, too many variables, and too little control in this mode.  The open loop mode does have a few advantages though.  It takes less work, less time, less cost.  And it is often useful for ranking alternatives (ie A vs. B comparisons).

For high accuracy, a closed loop workflow is required.  It is rarely the case that initial assumptions are sufficiently error-free to support tight tolerances on fatigue life prediction.  Therefore, careful measurement and validation of material property inputs, part dimensions, load-deflection behavior, pre-stresses, etc. should be made.  Where gaps are found between test and simulation, appropriate amendments to the test and/or to the simulation should be adopted.  This approach yields high confidence in the simulation results, and good accuracy in fatigue life predictions.  We have seen users hit life predictions to better than a factor of 1.1x with this approach!  Although this approach requires more effort, it results in more complete mastery of part design, and it yields a much stronger starting position for subsequent products.

While “right the first time” engineering is possible with either open or closed loop, the closed loop approach benefits from progressive refinement of the analysis inputs and it ultimately gives the highest success rate.

 

 

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The New Endurica Architecture – It’s Time to Migrate

Our transition to a new software architecture is a vital move in navigating the dynamic technological landscape. In a recent webinar, we discussed the aspects of this transition, providing insights into the why and how of adopting a new architectural approach despite having a functional existing one. This post will highlight the motivations behind the shift, the present status of feature migration, alterations in the latest software release, and an overview of projects within this new framework.

The Rationale and Benefits

Why Overhaul?

The complete rewrite of our software’s architecture was not a decision made lightly. The reasoning extends beyond merely wanting a refresh; it was driven by pivotal motivations, primarily surrounding the necessity for speed and efficiency in executing computing processes. Speed is invariably tied to productivity and operational fluency in software and technology. The plot below illustrates a compelling story: the old architecture (represented by the blue line), exhibited a static runtime, regardless of the number of threads engaged, revealing its inability to utilize parallel processing. Contrastingly, the new architecture demonstrates a significant speed-up, even with just a single thread, and scales to allow an increase in speed by many multiples, contingent on thread capacity.

Solving Larger Problems

The pursuit of faster execution isn’t arbitrary; it is intrinsically linked to our objective of solving larger problems. With larger tasks and projects on the horizon, scaling up and utilizing more CPU threads became essential. Exemplified through a job run on a virtual machine with 96 available CPU threads, the linear decrease in runtime with increasing threads (until certain hardware limitations are met) exhibits the new architecture’s adept handling of larger jobs (see plot below). The capability to scale and manage tasks of escalating complexity and size was a crucial driver for our transition.

Enhancing Integrations and Streamlining Workflows

Then, we turned our attention toward improving the user experience in interfacing with our software. Our prior use of the HFI and HFO file formats, while functional, presented numerous challenges regarding modification and integration, particularly when scripted modifications were necessary. The new architecture employs the JSON file format, widely recognized for its robustness and versatility across various industries and applications. With JSON, modifying job inputs and managing data become significantly simplified, as illustrated by a Python script example, wherein the entirety of job modifications, inputs, and submissions can be seamlessly handled with a handful of lines of code.

Improved Usability and Real-Time Error Checking

In an effort to enhance usability and mitigate the common issue of erroneous entries and syntax use, the new architecture, especially when utilized with a text editor like VS Code, offers real-time checking and syntax suggestions. This not only makes job submission more precise but also substantially reduces the trial-and-error cycle, saving valuable time. Additionally, upon job submission, the new architecture performs rigorous error and syntax checks, ensuring smooth execution and user experience.

Comprehensive Feature Migration: A Successful Transition

Reflecting on the past two years, we have accomplished a near-complete feature migration to the new software architecture, with 99% of features now successfully transitioned. This includes all outlined output requests, material models, history types, and various procedures.
Our commitment to supporting multiple interfaces remains, with support for Abaqus, Ansys, and Marc using the new architecture. Furthermore, Endurica Viewer is fully compatible, providing enhanced visualization capabilities under the new system.
The comprehensive migration and the incorporation of new functionalities marks the new architecture as fully operational and ready for use across all undertakings.

Implementation of Directory and Execution Changes in Endurica Software

Refined Directory Structure

In efforts to provide a seamless transition and user experience with the upgraded Endurica software, modifications have been made to the directory structure. The new architecture, once labeled “Katana” during its development phase, has now been ubiquitously integrated into the top-level Endurica directory. With the most recent software installation, users will observe the top-level CL and DT directories contain the new architecture, and the Katana directory has been removed.

Consequently, when we refer to Endurica CL and Endurica DT moving forward, it denotes reference to the new architecture.

Accommodating Transition: The Legacy Folder

Acknowledging that the transition to the new architecture may not be instantaneous for all users, the old architecture will still be available and designated within a “Legacy” folder. Though it requires navigation into subfolders, we ensure its accessibility for users who need more time to transition fully into the new structure.

Executable Naming Conventions

In tandem with the directory adjustments, executable naming conventions have been revised to be more intuitive. Previously, “endurica” was employed to submit fatigue analyses in the old architecture, while “katana” pertained to the new. To streamline, “katana” has been rebranded as “endurica” for submitting the JSON input file, with the legacy version adopting the name “endurica-legacy.” It is crucial to note that users accustomed to utilizing “katana” may continue to do so — “endurica” and “katana” will run the same executable. However, usage of the old architecture requires invoking a new “endurica-legacy” command.

Delivering the Unattainable with Endurica’s New Software Architecture

Embarking upon two recent projects with our new computational architecture, we explored the realms of virtual simulation and data management in tire durability and elastomeric mount durability performance.

Project 1: Tire Durability with Dassault Systems

In collaboration with Dassault Systems, a multi-body dynamic simulation was conducted to compute tire durability at the Nurburgring circuit. Utilizing SIMPACK for generating virtual road load data and employing Endurica EIE and Abaqus to establish a workspace map of driving conditions, the endeavor yielded significant data, processed through 176,000 time steps to evaluate the tire’s fatigue life. After a meticulous analysis, the results spotlighted the fatigue life to be 214 laps, pinpointing the most critical point around the tire bead edge.

Project 2: Durability of an Elastomeric Mount with Ford

Undertaken with Ford, the second project navigated through the durability performance of an elastomeric mount, involving a behemoth of data from 144 load history files, each load file containing tens or hundreds of thousands of time points, accumulating to over 15 million total time points. Utilizing a similar approach as the Nurburgring project, Endurica EIE and Abaqus were used together to generate the strain history data. The analysis focused on membrane elements on the mount’s free surfaces to precisely gauge surface strains. Culminating the analysis, the project succeeded in qualifying the part with a fatigue life of 9.4 repeats of the entire schedule, wherein the requisite was just one repeat.

These projects underscored the capabilities of our new architecture, navigating through large data sets and providing tangible insights in significantly reduced timeframes compared to the old architecture. In essence, the implementation of the new architecture has not only streamlined our processes but also expanded our horizons in handling large data and achieving nuanced analyses in our projects.

Summary

The new Endurica CL and Endurica DT architectures have now fully replaced our old system, maintaining the accuracy our users expect while introducing an easier, more powerful, and scalable solution. Everything has been successfully migrated over to this complete solution. With its enhanced capabilities, it addresses problems that were previously too large or took too long to solve, enabling our customers to tackle challenges they might not have considered before. The ability to solve unprecedented problems is just one more example of our steadfast commitment to providing accurate, complete, and scalable solutions.

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Crack Growth or Continuum Damage?

The topic of whether to use a crack growth method or a continuum damage method for product fatigue and durability assessment has long been debated. Oftentimes, experts will recommend using a continuum damage approach in the initial phase, when no noticeable cracks are present, and then transition to a crack growth analysis when damage has reached a certain level where cracks are likely to appear.  In other applications, most of the product’s life is consumed in the crack or crack growth initiation phase, so a continuum damage method is deemed most appropriate.  There are also cases where products are in service with known detectable cracks; in this case fracture mechanics and crack growth analysis is employed to predict how fast the crack will propagate and when it will reach a critical size.

The simplest continuum damage analysis uses Wöhler curves, or S-N diagrams and Palmgren-Miner’s rule.  The S-N diagrams are built by running fatigue tests on un-cracked dumbbell specimens at various stress amplitudes, S, and measuring the number of cycles to failure, Nf. Typical S-N diagrams are shown in Figure 1 [1].  The quantity Sf is the Endurance Limit (or Fatigue Limit), below which no failure is predicted to occur.

 

Figure 1. Typicaly S-N Diagrams [1]

A linear damage rule like the Palmgren-Miner rule states that the amount of damage due to a certain number of cycles, ni, at a certain stress amplitude, Si, is a simple linear ratio compared to the number of cycles to cause failure at that stress amplitude, or

(1)

The incremental amount of damage can then be summed over different blocks of cycles at different stress amplitudes to predict failure when

(2)

One of the limitations of this approach is that sequence effects, for example going from a high-to-low stress amplitude vs. going from a low-to-high stress amplitude is not accounted for. Stated another way, the rate of damage accumulation does not depend on the current state of damage. There also tends to be a large amount of scatter in the results.  In finite element implementations, the amount of damage is tracked towards failure, and damage can be included as a state variable in the constitutive law to allow the stiffness to evolve as a function of damage.

The Endurica methods of fatigue analysis combine fracture mechanics, crack growth, and continuum damage methods. In most materials, there are crack precursors on the micron, or sub-micron level that serve as crack growth initiators. Filled elastomers are known to have many discontinuities at the micron level due to, for example, voids filled with air, agglomeration of fillers or clumps of additives.  These are treated as an initial “pre-cursor” crack with the size c0 with typical values between 10 and 100 microns. Crack growth analysis is used to predict the number of cycles, or number of repeats of a block of cycles until the crack reaches a length indicative of the end of life of the product or component.

Rather than using stress as the driver for damage as in the SN diagram, a fracture parameter called Energy Release Rate, or Tearing Energy is used as the driver for crack growth rate.  An example plot is shown in Figure 2.

The analogy to the Endurance Limit in the S-N diagram is the Intrinsic Strength, T0, below which no crack growth is predicted.  The power-law portion of the plot with slope “F” can be expressed as

(3)

 

where rc is the crack growth rate when T = Tc, the Critical Tearing Energy.   In metals, this is termed a Paris Law, in elastomers, it is the Thomas Law [2].

The damage rate in this case is the crack growth rate, dc/dN. Also, the “damage” is tracked as the predicted length of a growing crack.  The summation of the damage over a given set of cycles can be written as

 

(4)

 

The Tearing Energy in a single edge cracked tension specimen is given by

 (5)

 

where W is the strain energy density far from the crack and k is a constant depending on strain level. In a general three-dimensional state of deformation, Endurica uses the Cracking Energy Density, Wc such that,

(6)

In each of these cases, the Tearing Energy, and thus the crack growth rate is predicted to depend on the crack length, c.

Combining equations 6 and 3, we see that the damage rate, dc/dN, in this analysis, will depend on the current state of damage, c, and thus be able to represent sequence effects as part of the analysis.

In the finite element implementation with the Endurica software, there is typically no explicit crack in the FEA model. Thus the calculation of damage in the form of a growing crack is like a continuum damage approach on the macro-scale.  A co-simulation workflow is also available where the stiffness of each element in the FEA model evolves with the calculation of crack length in each element.

The Endurica analysis methods can be viewed as a continuum damage method on the macro-scale, while using fracture mechanics and crack-growth analysis on the micro-scale.  The use of fracture mechanics provides many advantages including a well-developed and validated theory for elastomers, less scatter in fatigue experiments, nonlinear damage evolution and sequence effects, and the easy ability to include many other aspects such as temperature, aging, and strain crystallization.

References

[1]        Stephens, R. I., Fatemi, A., Stephens, R.R., and Fuchs, H.O., Metal Fatigue in Engineering, 2nd edition, John Wiley & Sons, 2001.

[2]        Thomas, A.G., “Rupture of Rubber  IV. Cut Growth in Natural Rubber Vulcanizates,” Journal of Polymer Science, Vol 31, pp 467-480, 1958.

 

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License Queueing

Design optimization studies are driving a need to support the efficient management and execution of many jobs.  This is why we are announcing that Endurica’s software license manager now supports queueing for licenses. This allows a submitted job to automatically wait to start until enough licenses are available, instead of the prior behavior of exiting with a license error. Now you can submit many jobs without worrying about license availability.

License queueing is only available for network licenses (not node-locked). It is currently supported for Katana CL/DT jobs and EIE jobs submitted from a command prompt.

To enable queueing, set the environment variable RLM_QUEUE to any value. This environment variable must be set on the client machine (not the license server).

To learn more about license queueing, search for “How to Queue for Licenses” in the RLM License Administration documentation here: https://www.reprisesoftware.com/RLM_License_Administration.pdf

 

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Defining the Temperature Dependence of Strain Crystallization in Endurica

Crystallization requires the suppression of molecular mobility, which in natural rubber can happen either by reducing the temperature or by increasing the strain.  Crystallization of natural rubber can be extremely beneficial to durability.  Nonrelaxing conditions (ie R>0) can increase life by factors of more than 100!  So, what happens if you have both high mean strain and high temperature?

This was the question studied in 2019 by Ruellan et al.  They constructed Haigh diagrams for a filled natural rubber at 3 temperatures: 23 degC, 90 degC and 110 degC.  They completed a large experimental study using dumbbell shaped specimens with a matrix consisting of approximately 4 R ratios x 4 amplitudes x 3 temperatures = 48 conditions.  Their results show that the increase of fatigue life with increasing mean strain at constant amplitude disappears as temperature is increased.  In particular, notice how at 23 degC each life contour (shown in red) has a strongly defined minimum force amplitude that lies near the R=0 line.  Also notice how, at higher temperatures, the life contours start to reflect a decrease of life with increasing mean strain.

This interesting effect can easily by replicated in the Endurica fatigue solver by letting the strain crystallization effect depend on temperature.  The material definition we have used in this quick demo is given below in both the old hfi format and the new Katana json format.  I have highlighted in yellow those parts of the definition which reflect the temperature dependence.

In the material definition, we have reflected two behaviors:

  1. the increase of crack growth rate with temperature (ie the RC parameter), and
  2. the decrease of strain crystallization with temperature (ie the Mars-Fatemi exponential strain crystallization parameter FEXP).

We have plotted the resulting Haigh diagrams in the Endurica viewer, and directly overlaid Ruellan’s results for comparison.  Although the x and y scales in Ruellan’s results are shown in terms of total specimen force and ours are shown in terms of strain, a quite satisfying match is nonetheless achieved for the interaction of temperature with the mean strain effect.  It is especially satisfying that such rich behavior is so compactly and so accurately described by means of the Mars-Fatemi crystallization parameter.

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What is the Price of Standing Still?

What if we don't change at all and something magical just happens? Technical equation for entropy

“We have always done it this way.” No longer simply a hated phrase, this statement is a warning of impending disaster. Entropy – the disorder that happens when energy disperses and systems simply fall into chaos – happens when things do not change. But it’s a slow process you don’t see day-to-day. Continuing with traditional “build and break” development methods instead of embracing CAE and simulation has many long-term risks but it will only be after stagnating for some time that rubber parts manufacturing firms, and even the entire rubber industry, will realize the pitfalls:

Talent Loss
People are the key to it all and we start here since intelligent, hard-working, productive people are the fundamental reason any business succeeds. When the best and brightest employees leave a company, the fundamental reasons often include the lack of opportunity, learning, and career development. When not allowed to work with emerging technologies and are no longer challenged to grow, top performers find new opportunities taking not only raw potential but also institutional memory with them. And if they don’t see the industry as a viable long-term option, switching companies can also mean leaving the sector completely.

Warranty Issues/Payouts
Liability issues arise when product usage, applications and environments bring risks that may not have been factored in to the original designs and/or production methods. Traditional testing methods cannot be used to investigate “what if?” scenarios the way CAE and simulation can. Recalls and litigation can be significantly more costly than new technology implementations.

Lost Opportunity Costs
While harder to measure than fixed and variable business costs, there is an expense to every choice known as opportunity cost. Refusing to enter a new business sector may result in significant loss of revenue and profit. Taking on a big client project may strain production capabilities. “Standing still” eliminates those risks, but at what potential gain? As the rubber industry wrestles to “go green” we are all weighing and measuring the opportunity costs involved. The real lost opportunity is in refusing to embrace a fundamentally better design platform.

Incompatibility or Obsolescence
At some point, everything being produced right now will become obsolete. Even if you produce the best “widgets” anywhere, the environment around that “widget” will change and will no longer be needed in its current form. The rubber industry standard procedure of building a product then breaking it in physical testing to determine the next design rendition is incompatible with the time available for new product development. It just does not work anymore.

How quickly your business can adapt to or anticipate change is a key factor in continued success. The reasons companies do not make continued progress often include:

Change is expensive
Investments in training, new production systems, updated software and computers add up, but these numbers are not insurmountable when factored against the ongoing and often increasing costs of waste, repairs and downtime associated with outdated systems and equipment.

Learning new technology is time-consuming
Remember when you were thinking about going to college and four (6-8-10) years seemed like FOREVER? What was your ROI? What will it be now? Time invested in learning reaps many rewards beyond the subject at hand and often provides renewed overall energy.

The status quo works
For today, yes. For a brighter future for you company and the industry, NO. Companies that don’t evolve face certain death. Day-to-day operations may appear stable, but firms who do not keep up with technology do not stay in business. Covid forced many to embrace technology in new ways and those firms continuing to provide progressive working arrangements are gathering more than their fair share of the best and brightest talent. Enabling people to work beyond traditional geographic boundaries requires accountability and processes for measuring valued contributions rather than simply time at a desk.  Firms embracing CAE and simulation technologies have realized this and are at the top of the leading rubber industry rankings.

 Six reasons to adopt Endurica workflows

  1. Technically superior (click for details)
  2. Save big on development out of pocket costs (click for details)
  3. Reduce the need for physical testing (see page 2, blue box on right)
  4. Speed to market (able to use the tools immediately)
  5. Accuracy in meeting client needs (click for details)
  6. Easier answers down the road (click for details)
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Introducing Tom Ebbott, the new Vice President at Endurica!

Thomas G. Ebbott, Ph.D. Vice President Endurica LLC

Hello everyone. I am really excited to be writing this as the newest member to Team Endurica! I am really enjoying my on-boarding with Will and the team thus far. I continue to learn all the capabilities that the Endurica software has to offer, along with all the services that Endurica the company offers. I’m looking forward to using my knowledge and experience with modeling and simulation combined with expertise in fatigue and fracture in polymers to bring value to Endurica’s customers.

Endurica’s software and services enable customers to monitor, predict and improve the endurance of products. This has a positive impact on many of today’s contemporary questions. For example, for sustainability, customers need to evaluate the durability impact of using a material with a more sustainable source, or one with better recyclability or re-useability in place of an existing material. Even re-designing a component to use less material, or to last longer is more sustainable. For electric vehicles, many of the elastomeric components are called on to carry higher loads and higher torques in the case of tires. And, for fleet operations, Endurica can be used to monitor the health of elastomeric systems and predict when maintenance will be needed.

I feel I have a good background to help both Will and the team at Endurica as well as Endurca’s many and wide-ranging customers. As many of you know, I recently retired from Goodyear after nearly 36 years with that great company. While I was at Goodyear, I worked with many wonderful and capable people, and I was fortunate to have many fulfilling experiences and roles. Some include developing fundamental technology, developing products–specifically Aviation Tires and Retreads, various people leadership roles, and finally a high-level technical leader role responsible for technical strategy. While at Goodyear, I was able to publish several papers on topics such as fracture mechanics of rubber in tires, temperature distribution and rolling resistance prediction for tires, crack growth in twisted rubber disks, and continuum damage analysis of cord-rubber structures. I served on The Tire Society Executive Committee for 8 years as Treasurer. One of my long-term contributions at Goodyear was to the 30-year partnership with Sandia National Laboratories.

For my formal training, I spent 10 years at the University of Wisconsin-Madison that culminated in a PhD in Engineering Mechanics. My masters work focused on structural dynamics while my PhD research was on crack growth in polyethylene. The application of my PhD work was for the durability evaluation of natural gas distribution pipelines. The crack growth evaluation in (high density, high molecular weight) polyethylene required development of viscoelastic material laws and characterization as well as crack growth measurement systems, means to measure strain distributions, and use of viscoelastic crack growth theories.

On a personal note, my wife Sheri and I have two adult children. Amanda is teaching 2nd grade at a school near Columbus, OH, and Zachary is a junior pursuing a Finance degree at Regis University in Denver. One of my passions is flying, and I’ve had my private pilot’s license for many years. One of my most memorable flying trips was to New Mexico and Colorado. The photo shows my plane with the sun rising over the Sandia mountains in Albuquerque, NM.

I’m looking forward meeting and talking with Endurica’s customers in the coming months and learning about their needs and challenges concerning the use of elastomers and polymers for component design.

 

 

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The View on ‘22 – The Top 10 Happenings for Endurica in 2022

  1. Expanded our team! We welcomed 35-year Goodyear veteran Tom Ebbott to our team as Vice President, and at one point we had 3 interns working with us this year.  It wasn’t all hard work – we enjoyed our first company canoe trip / picnic in July.
  2. Solved much bigger problems. We set a record this summer for the largest rubber fatigue analysis ever. Ford Motor Company gave us multi-channel recorded road load histories from the full schedule of 144 distinct test track events that they use to qualify a motor mount for durability. We used Endurica EIE to map the load space and generate 3.2 Terabytes of stress-strain history for fatigue analysis. The new Katana multi-threading architecture of our Endurica CL fatigue solver enabled us to process 152k elements through all 15,693,824 timesteps of the schedule.  Check out our presentation at RubberCon 23 in Edinborough UK.
  3. Made analysis of block cycles easier. The Endurica CL and DT solvers’ Katana architecture now enables multiple blocks of load history to be specified in a single analysis.WoD 6 - Strain Crystallization
  4. Added a Haigh diagram visualization to the Endurica Viewer. Use it to quickly understand your material’s dependence of fatigue life on mean strain and strain amplitude.
  5. Implemented a channel reduction algorithm to Endurica EIE. It will analyze your multi-channel loading history to check for opportunities to reduce the dimensionality of your analysis through a change of coordinate basis.  Often, a 6-channel signal can be reduced to 3, 4 or 5 channels, greatly reducing computational requirements for building the map for EIE’s interpolation process.
  6. Expanded our licensing model to offer local, regional and global options. If your organization uses Endurica at multiple sites around the world, ask us about the advantage of regional or global licenses. These licenses allow any number of users to share a pool of solver threads for maximum flexibility and compute power.
  7. Added an experimental characterization for ozone cracking. Ozone is a trace gas that strongly reacts with some rubbers to produce surface cracking. It limits useful product life, even for loads below the fatigue threshold.Ozone Module. quantify ozone attack critical energy and rate Our testing method gives you the parameters you need to set up the ozone attack model in your Endurica CL / DT analyses. Perfect for analysis of tire sidewall endurance.
  8. Were honored when our founder and president, Will Mars, received the Herzlich Medal – the highest award in the tire industry – at the International Tire Exhibition and Conference. This honor is bestowed every other year to recognize an individual whose career and accomplishments have changed the tire industry for the better and left a lasting impact on tire design, development and manufacturing.
  9. Strengthened our documentation. New and experienced users alike will find it easier than ever to find the theory, procedures and examples that will yield rapid success in applying our software workflows. Check out the new sections on Mullins Effect, Ageing, Safety Factor, and Block Cycle analysis.
  10. Celebrated our client’s success. Technetics Group (Pierrelatte, France Maestral® R&D Sealing Laboratory) and Delkor Rail (New South Wales, Australia) shared their Winning on Durability success in case studies.
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