As more companies aim to reduce their product’s time to market, research and design engineers have begun integrating predictive modeling into their process. These models, whether finite element based or artificial intelligence based, all rely on quality mechanical testing results. Companies within the automotive industry have seen that accurately predicting large scale tests such as crashworthiness trials can greatly expedite the time it takes to get their products to market. One of the more important details in predicting these expensive and time-consuming tests is to understand how the materials within the design are affected by the higher rates of deformation or their strain rates.
Traditional standardized tensile tests have been used for over a century – ASTM E8 was first approved in 1924. Testing laboratories using standards like ASTM E8, ISO 6892-1, and JIS Z-2241 produce repeatable and reproducible mechanical properties for metals undergoing tensile deformation, but each of these standards requires the test to be run at a speed orders of magnitude lower than those occurring during events like sheet metal forming and automotive crash. A tensile test run according to ASTM E8 to obtain the yield properties of a metal is run at a strain rate of 0.00035 strain per second (0.00035/s). For comparison, a stamping process has strain rates on the order of 1 to 10 strain per second, and an automotive crash can have strain rates up to 1,000 strain per second (Figure 1).
Figure 1. Strain rates of different events.
Historically, no guidelines have been available as to the testing method to obtain high strain rate mechanical properties. Decisions on specimen dimensions, measurement devices, and other important issues which are critical to the quality of testing results were made within each individual laboratory. As a result, data from different laboratories were often not directly comparable. A WorldAutoSteel committee evaluated various procedures, conducted several round-robins, and developed a recommended procedure, which evolved into what are now the first two parts of ISO 26203, linked below.
Published standards addressing tensile testing at high strain rates include:
Steel alloys typically possess positive strain rate sensitivity, or m-value when tested at ambient temperature, meaning that strength increases with strain rate. This has benefits related to improved crash energy absorption.
The specific response as a function of strain rate is grade dependent. Some grades get stronger and more ductile as the strain rate increases (left image in Figure 2), while other grades see primarily a strength increase (right image in Figure 2). Increases are not linear or consistent with strain rate, so simply scaling the response from conventional quasi-static testing does not work well. Strain hardening (n-value) also changes with speed in some grades, as suggested by the different slopes in the right image of Figure 2. Accurate crash models must also consider how strain rate sensitivity impacts bake hardenability and the magnitude of the TRIP effect, both of which are further complicated by the strain levels in the part from stamping.
Figure 2: Two steels with different strength/ductility response to increasing strain rate.A-7
Importance of Proper Testing Equipment
Knowing that the strain rate directly affects mechanical properties, many research test laboratories have run tensile tests using the same specimen geometry and machine as standardized but have increased the speed the machine runs during the test. This typically allows for tests to be performed at strain rates of up to 0.1 strain per second. From this data, an extrapolated curve can be fit to approximate the properties of the materials at higher strain rates. One model used to predict the increase in strength of a material deformed at a higher strain rate is the Cowper-Symonds model:
Equation 1
where σd is the strength of the material at a strain rate έ, σs is the strength of the material at a theoretical strain rate of zero strain per second, and C and p are model parameters.
Figure 3 shows two best fit curves for this Cowper-Symonds model to the tensile strengths of a cold rolled steel across a range of strain rates. The first considers only data that can be obtained using traditional tensile testing machines (strain rates less than 0.1 strain per second) while the second uses data up to 2,000 strain per second. Both models have minimal errors at strain rates below 0.1 strain per second, but as the limited model begins to extrapolate data beyond this strain rate regime, the associated error begins to grow exponentially causing large errors at the strain rates typical in crashes.
Figure 3. Example of extrapolation of tensile strength vs strain rate data using a Cowper-Symonds model. The dashed curve is an extrapolation based only on data acquired using traditional tensile testing machines, where strain rates are less than 0.1 strain per second. The solid curve is the extrapolation when considering data from equipment capable of achieving 2,000 strain per second.
Testing Methods and Equipment
The biggest obstacle to measuring how a material responds to different strain rates is that it requires several different types of equipment. This is due to the need to run tests at up to six or seven different orders of magnitude to fully characterize the material. Figure 4 shows which mechanical testing equipment is most used to perform tensile tests based on the strain rate of the test. A broader range of testing methods for more strain rates can be found in the ASM Handbook, Volume 8: Mechanical Testing and Evaluation.A-88 The limits for the strain rate range that each type of test equipment can achieve varies based on the design and attributes of each specific machine as well as the specimen geometry used in testing. In tensile and compression testing, going from a longer specimen to a shorter specimen allows for a specific machine to increase its upper limit on strain rates.
Figure 4. Testing equipment most used to test materials at strain rates between 0.0001 strain per second and 10,000 strain per second in uniaxial tension.
Modified Servo-Hydraulic Machines
Modified servo-hydraulic testing machines are specifically engineered to characterize the dynamic mechanical properties of materials at high strain rates, often reaching strain rates up to 500 strain per second. Unlike conventional servo-hydraulic machines, which used closed-loop control for precise lower-speed testing, these modified systems incorporate design features that overcome the limitations of standard hydraulic controls at higher speeds. Many of these machines utilize extreme high flow valves along with slack adapters. The higher flow valves allow for higher accelerations while the slack adapters decouple the actuator from the specimen while the actuator accelerates to a desired test speed.
Split Hopkinson Pressure Bars
A split Hopkinson pressure bar (sometimes referred to as Kolsky bar or simply SHPB) is an impact-based device that is designed to characterize the dynamic mechanical properties of materials at strain rates above 100/s. The SHPB system uses a striker rod to generate a stress wave which induces plastic deformation in a specimen placed between two elastic bars. The stress wave generated by the striker bar in the first elastic bar (called the incident bar) is measured by a strain gauge fixed at the midpoint of the incident bar. When the stress wave reaches the specimen, part of the stress wave is transmitted through the specimen into the second elastic bar (called the transmitted bar) where it is measured by a second strain gauge. The rest of the stress wave is reflected off the specimen and returns down the incident bar to be re-measured by the strain gauge. Figure 5 shows how the stress waves propagate through a SHPB system during a compression test. There are various options to modify the compression SHPB setup to run a tensile test, but the most common is to replace the striker bar with a tube that slides on the incident bar where it impacts a flange on the end of the incident bar causing a tensile stress wave to propagate towards the specimen instead of a compression wave.
Figure 5. Animation showing how a stress wave propagates through a
split Hopkinson pressure bar system during a high strain rate compression test.
High Strain Rate Testing Challenges
Many other challenges complicate testing materials at higher strain rates. Three of the major challenges are
Challenges of measuring strain at high speeds
Challenges of accounting for inertial effects
Challenges of accounting for adiabatic heating
Strain Measurements in High Strain Rate Testing
During standardized mechanical testing, clip-on extensometers and deflectometers provide excellent extension measurements. As the speed of the test increases, the mass of the extensometer inhibits its use due to slippage of the contact points or interference with the specimen, both of which lead to erroneous test results and potential damage to the device. During high strain rate tests, the simplest means of measuring specimen displacements is to derive them based on the stress waves from the test. A detailed derivation of this method can be found here. This method works well for compression testing, but during tensile testing, events such as slippage of the specimen within the grips or deformation of the radius section of the specimen add to the displacements of the test. These additional displacements overshoot the tensile strain of a specimen during the test. This has led to the nearly universal adoption of optical strain measurements for high strain rate tension tests.
The most common optical method is digital image correlation (DIC). DIC correlates a series of images taken during the deformation of a specimen and calculates the corresponding strains of the specimen. It does this by tracking a black-and-white speckle pattern painted on the specimen’s surface which creates a series of high-contrast features as shown in Figure 6.
Figure 6. Two examples of 2D digital image correlation (DIC) showing the true equivalent strain fields during tensile tests performed at 0.1 strain per second and 1000 strain per second.
When testing round or more complex specimens, two cameras are required to track the surface of the specimen in three-dimensional space. This is referred to as 3D DIC, and it often requires more rigorous calibration for use in testing due to its multi-camera complexity. Alternatively, there are a series of one-dimensional options for strain measurements. The simplest utilizes a high-speed line scan camera to measure the displacement of a specimen along the test direction. While the two- and three-dimensional approaches bring in more data, the one-dimensional approach has been shown to provide excellent resolution at a lower adoption cost.Z-16
Accounting for Inertia in High Strain Rate Testing
At strain rates around one to ten strain per second, inertial effects can begin to complicate the interpretation of test results. These effects can be broken into two varieties: inertia of the specimen being tested and inertia of the equipment being used. Both directly affect the load values measured during a given test. In a modified servo-hydraulic load frame, large grips can create a large difference in stiffness (known more specifically as mechanical impedance) between each grip and the specimen. This difference causes more of any generated stress wave to be reflected at the interface as opposed to transmitting through; thus, as the wave travels back-and-forth through the specimen, the load it experiences “rings up”. This is sometimes referred to as “load ringing”. During this transient period of ring-up, the wave is amplifying or changing shape each time it reaches an end of the specimen. From this, the specimen experiences a load gradient across its gauge section depending on where the wave is at that point. After a certain number of reflections have occurred, the stress wave within the specimen becomes uniform and the specimen is determined to be in stress equilibrium. The number of oscillations it takes for this to occur is greatly dependent on the maximum frequency of the stress wave that enters the specimen and the ratio of mechanical impedances between the specimen and its grips. The lower the difference in impedances, the lower the energy that is reflected back into the specimen. The overall time of this period is not affected by the strain rate of the test being performed. This is because the phenomenon is based more so on the number of times the wave traverses the specimen which is solely dependent on the wave speed and length of the specimen. The wave speed of a material (assuming one—dimensional wave propagation) is calculated by:
Equation 2
Where c is the wave speed of the material, E is the Young’s modulus of the material, and ρ is its density. When viewing test results, the load ringing can be seen as a decaying sinusoidal that begins when the specimen is first loaded. Figure 7 shows an example of how this could look across various strain rates. Each data set shares the same decay time constant, frequency, and magnitude of oscillations. Holding these three as constant simulates running tensile tests using the same specimen geometry, machine, and grips but varying the strain rate of the test. In the data set at lower strain rates, the effect of load ringing is minor with no notable difference between the actual response and the measured response at 10 strain per second. At 30 and 100 strain per second, the yield portions of the stress-strain curves are noisy, but the overall hardening profile is still clean. At 300 strain per second, the oscillations affect most of the hardening potion of the stress-strain curve. At 1000 strain per second, the overall profile of the stress-strain curve can be made out including strain to failure, but no details regarding hardening, uniform elongation, or tensile strength can be stated without large error bands. At 3000 strain per second, very little can be discerned from the data.
Figure 7. Illustration of theoretical frequency responses of dynamic tensile tests performed at various strain rates. All tests share the same decaying time constant, frequency, and magnitude of oscillations.
Some laboratories have adopted an inverse method that takes data with excessive load ringing and derives a stress-strain model. This is done by simulating the equipment used to perform the test along with the specimen tested in a finite element model. Then, repeated iterations of the stress-strain profile are sequentially optimized until the simulation best fits the data read from the test which includes the load oscillations. While this method has shown great potential, it is often too time intensive and expensive to justify in most industrial applications.
Adiabatic Heating in High Strain Rate Testing
The final challenge when testing materials at high strain rates comes from a by-product of plastic deformation of materials: adiabatic heating. Quasi-static tests allow for iso-thermal testing where the rate of heat being generated from plastically deforming the specimen is exceeded by the rate that heat is lost to the surrounding environment. As the strain rate of the test is increased, so too does the rate of plastic work and heat generation within the specimen. This internal heating is also compounded with the need for high intensity lighting to illuminate any high-speed optical methods for measuring strain of specimens. Because of these heat sources without equivalent cooling, the material response as measured by a high strain rate test is jointly affected by the higher strain rate as well as the elevated temperature of the specimen. These two effects have been shown experimentally to not be independent of one another, further complicating the analysis and interpretation of these tests. More complex multi-physics material models are often employed to account for these coupled effects in finite element model simulations.
Thanks are given to Trey Leonard, for his contributions to this page. Trey is the founder and CEO of Standard Mechanics, LLC, where he delivers advanced mechanical testing services and solutions across a wide range of applications, from automotive design to consumer electronics. His expertise spans formability, fatigue, and strain rate sensitivity testing. Beyond conducting tests, he partners with customers to ensure the development of high-quality, calibrated material cards and models for accurate finite element simulations. Dr. Leonard earned his Ph.D. in Mechanical Engineering from Mississippi State University, where he pioneered and licensed technologies in dynamic material testing and characterization. Building on this foundation, he continues to develop innovative testing methods and technologies that advance the field of dynamic mechanical testing. He also contributes to the broader engineering community through his work with ASTM International, where he serves on the E28 Committee on Mechanical Testing, regularly reviewing and improving industry standards.
All metals strengthen as they are deformed through a process called work hardening. However, the degree of strengthening may change as a function of the speed at which they are tested. In these cases, when local necking starts, the strain rate in the necked area is different in the surrounding non-necking region.
With negative strain-rate sensitivity, as is the case with many aluminium alloys, the necked region is weaker than the surrounding area. Fracture occurs with very little additional strain after necking initiation.
With positive strain-rate sensitivity, the necked region is stronger than the surrounding area. This is the basis for many steel alloys having a total elongation to fracture that is nearly double that of uniform elongation.
This strain-rate sensitivity is described by the exponent, m, in the modified power law equation:
Equation 1
where έ is the strain rate and m is the strain rate sensitivity.
To characterize the strain rate sensitivity, medium strain rate tests were conducted at strain rates ranging from 10-3/sec (commonly found in tensile tests) to 103/sec. For reference, 101/sec approximates the strain rate observed in a typical stamping. Both yield strength and tensile strength increase with increasing strain rate, as indicated Figures 1 and 2.
Figure 1: Influence of Strain Rate on Yield Strength.Y-1
Figure 2: Influence of Strain Rate on Tensile Strength.Y-1
Up to a strain rate of 101/sec, both the YS and UTS only increased about 16-20 MPa per order of magnitude increase in strain rate. These increases are less than those measured for low strength steels. This means the YS and UTS values active in the sheet metal are somewhat greater than the reported quasi-static values traditionally reported. However, the change in YS and UTS from small changes in press strokes per minute are very small and are less than the changes experienced from one coil to another.
The change in n-value with increase in strain rate is shown in Figure 3. Steels with YS greater than 300 MPa have an almost constant n-value over the full strain rate range, although some variation from one strain rate to another is possible.
Similar behavior was noted in another studyB-22 that included one TRIP steel and three DP steels. Here, DP1000 showed a 50% increase in yield strength when tested at 200/sec compared with conventional tensile test speeds. Strain rate has little influence on the elongation of AHSS at strain rates under 100/sec.
Figure 4: Relationship between strain rate and yield strength (left) and elongation (right). Citation B-22, as reproduced in Citation D-44
Figure 5 shows the true stress-true strain curves for a processed Press Hardened Steel tested at different strain rates. The yield stress increases approximately five MPa for one order of magnitude increase in strain rate.
Figure 5: True stress-strain curves at different strain rates for 1mm thick Press Hardening Steel (PHS) after heat treatment and quenching.V-1
The tensile and fracture response of different grades is a function of the strain rate and cannot be generalized from conventional tensile tests. This has significant implications when it comes to predicting deformation behavior during the high speeds seen in automotive crash events. See our page on high speed testing for more details.
In addition to enhanced formability, Advanced High-Strength Steels (AHSS) provide crash energy management benefits over their conventional High-Strength Steel (HSS) counterparts at similar strength levels. Higher levels of work hardening and bake hardening at a given strength level contribute to this improvement in crash performance.
The energy required for plastically deforming a material (force times distance) has the same units as the area under the true stress-true strain curve. This applies to all types of plastic deformation – from that which occurs during tensile testing, stamping, and crash. The major difference between these is the speed at which the deformation takes place.
As an example, consider the press energy requirements of two grades by comparing the respective areas under their true stress – true strain curves. The shape and magnitude of these curves are a function of the yield strength and work hardening behavior as characterized by the n-value when tested at conventional tensile testing speeds. At the same yield strength, a grade with higher n-value will require greater press energy capability, as highlighted in Figure 1 which compares HSLA 350/450 and DP 350/600. For these specific tensile test results, there is approximately 30% greater area under the DP curve compared with the HSLA curve, suggesting that forming the DP grade requires 30% more energy than required to form a part using the HSLA grade.
Figure 1: True stress-strain curves for two materials with equal yield strength.T-3
The high degree of work hardening exhibited by DP and TRIP steels results in higher ultimate tensile strength than that exhibited by conventional HSS of similar yield strength. This provides for a larger area under the true stress-strain curve. Similarly, when panels are formed from these grades, the work hardening during forming leads to higher in-panel strength than panels from HSS of comparable yield strength, further increasing the area under the stress-strain curve, ultimately resulting in greater absorption of crash energy.
Finally, the high work-hardening rate better distributes strain during crash deformation, providing for more stable, predictable axial crush that is crucial for maximizing energy absorption during a front or rear crash event.
Many AHSS are bake hardenable. The relatively large BH effect also increases the energy absorption capacity of these grades by further increasing the area under the stress-strain curve. The BH effect adds to the work hardening imparted by the forming operation. Conventional HSS do not exhibit a strong BH effect and therefore do not benefit from this strengthening mechanism.
Figure 2 illustrates the difference in energy absorption between DP and TRIP steels as a function of their yield strength determined at quasi-static tensile testing speeds.
Figure 2: Absorbed energy for square tube as function of quasi-static yield strength.T-2
Figure 3 shows calculated absorbed energy plotted against total elongation for a square tube component. The absorbed energy remains constant for the DP and TRIP steels but the increase in total elongation allows for formation into complex shapes.
Figure 3: Calculated absorbed energy for a square tube as a function of total elongation.T-2
For certain parts, conventional steels may have sufficient formability for stamping, yet lack the required ductility for the desired crash failure mode and will split prematurely rather than collapsing in a controlled manner. AHSS grades improve energy absorption by restoring a stable crush mode, permitting more material to absorb the crash energy. The increased ductility of AHSS grades permit the use of higher strength steels with greater energy absorbing capacity in complex geometries that could not otherwise be formed from conventional HSS alloys.
Stable and predictable deformation during a crash event is key to optimizing the steel alloy selection. The ideal profile is a uniform folding pattern showing progressive buckling with no cracks (Figure 4).
Figure 5: Three-point bend testing of two DP980 products having different folding and cracking behavior resulting from different microstructures and alloying approaches.B-12
High Strain Rate Property Test Methods
for Steel and Competing Materials
Tensile testing occurs at speeds that are 1000x slower than typical automotive stamping rates. Furthermore, automotive stamping is done at speeds that are 100x to 1000x slower than crash events. Stress-strain responses change with test speed – sometimes quite dramatically.
The m-value is one parameter to characterize this effect, since it is a measure of strain rate sensitivity. Generally, steel has more favorable strain rate effect properties compared with aluminum, but this is also a function of alloy, test temperature, selected strain range, and test speed. L-20
TWinning Induced Plasticity (TWIP) steels have the highest strength-ductility combination of any steel used in automotive applications, with tensile strength typically exceeding 1000 MPa and elongation typically greater than 50%.
TWIP steels are alloyed with 12% to 30% manganese that causes the steel to be fully austenitic even at room temperature. Other common alloying additions include up to 3% silicon, up to 3% aluminum, and up to 1% carbon. Secondary alloying additions include chromium, copper, nitrogen, niobium, titanium, and/or vanadium.D-29 The high alloying levels and substantially greater levels of strength and ductility place these into the 2nd Generation of Advanced High Strength Steels. Furthermore, due to the density of the major alloying additions relative to iron, TWIP steels have a density which is about 5% lower than most other steels.
Calling this type of steel TWIP originates from the characteristic deformation mode known as twinning. Deformation twins produced during sheet forming leads to microstructural refinement and high values of the instantaneous hardening rate (n-value). The resultant twin boundaries act like grain boundaries and strengthen the steel. On either side of a twin boundary, atoms are located in mirror image positions as indicated in the schematic microstructure shown in Figure 1. Figure 2 highlights the microstructure of TWIP steel after annealing and after deformation.
Figure 1: Schematic of TWIP steel microstructure.
Figure 2: TWIP steel in the annealed condition (left) and after deformation (right) showing deformation twins. The number of deformation twins increases with increasing strain.K-42
EDDS or Interstitial-Free or Ultra-Low Carbon steels are different descriptions for the most formable lower-strength steel. Possible test results for this grade are 150 MPa yield strength, 300 MPa tensile strength, 22% to 25% uniform elongation, and 45% to 50% total elongation. In contrast, test results on TWIP steels may show 500 MPa yield strength, 1000 MPa tensile strength, 55% uniform elongation, and 60% total elongation.
The stress-strain curves for these two grades are compared in Figure 3. The TWIP curves show the manifestation of Dynamic Strain Aging (DSA), also known as the PLC effect, with more details to follow.
Figure 3: Uniaxial tensile stress-strain curves for an interstitial-free (IF) extra-deep-drawing steel and an austenitic Fe-18%Mn-0.6%C-1.5%Al TWIP steel. Curves are presented both terms of engineering (s,e) and true (σ,ε) stresses and strains, respectively.D-30
Figure 4 compares the results of bulge testing ferritic interstitial-free (IF) steel and austenitic Fe-18%Mn-0.6%C-1.5%Al TWIP steel. The TWIP steel is still undamaged at a dome height that is 31% larger than the IF steel dome height at failure.D-30
Figure 4: Comparison of dome testing between EDDS and TWIP.D-30
Excellent stretch formability is associated with high n-values. Shown in Figure 5 is a plot showing how the instantaneous n-value changes with applied strain. N-value increases to a value of 0.45 at an approximate true (logarithmic) strain of 0.2 and then remains relatively constant until an approximate true strain of 0.3 before increasing again. The high and uniform n-value delays necking and minimizes strain peaks. Twins continue to form at higher strains, leading to finer microstructural features and continued increases in n-value at higher strains.
Figure 5: Instantaneous n-value changes with applied strain. TWIP steels have high and uniform n-value leading to excellent stretch formability.C-30
A microstructural deformation phenomenon known as the Portevin-LeChatelier (PLC) effect occurs when deforming some TWIP steels to higher strain levels. The PLC effect is known by several other names as well, including jerky flow, discontinuous yielding, and dynamic strain aging (DSA).
The severity varies with alloy, strain rate, and deformation temperature. Figure 6 shows how DSA affects the appearance of the stress strain curve of two TWIP alloys.D-29The primary difference in the alloy design is the curves on the right are for steel containing 1.5% aluminum, with the curves on the left for a steel without aluminum. The addition of aluminum delays the serrated flow until higher levels of strain. Note that both alloys have negative strain rate sensitivity.
Figure 6: Influence of aluminum additions on serrated flow in Fe-18%Mn-0.6%C TWIP (Al-free on the left) and Fe-18%Mn-0.6%C-1.5% Al TWIP (Al-added on the right).D-29
stress-strain curve showing serrated or jerky flow, indicating non-uniform deformation. Strain localization takes place in propagating or static deformation bands.
the strain rate within a localized band is typically one order of magnitude larger, while that outside the band is one order of magnitude lower, than the applied strain rate.
limited post-uniform elongation, meaning uniform elongation is just below total elongation. Said another way, fracture occurs soon after necking initiation.
The PLC effect leads to relatively poor sheared edge expansion, as measured in a hole expansion test. Figure 7 on the left highlights the crack initiation site in a sample of highly formable EDDS-IF steel, showing the classic necking appearance with extensive thinning prior to fracture. In contrast, note the absence of necking in the TWIP steel shown in the right image in Figure 7.D-29
Figure 7: Sheared edge ductility comparison between IF (left) and TWIP (right) steel. TWIP steels lack the sheared edge expansion capability of IF steels.D-29
The stress-strain curves of several TWIP grades are compared in Figure 8.
Figure 8: Engineering stress-strain curve for several TWIP Grades.P-18
Complex-shaped parts requiring energy absorption capability are among the candidates for TWIP steel application, Figure 9.
Early automotive applications included the bumper beam of the 2011 Fiat Nuova Panda (Figure 10), resulting in a 28% weight savings and 22% cost savingsN-24 over the prior model which used a combination of PHS and DP steels.D-31
Figure 10: Transitioning to a TWIP Bumper Beam Resulted in Weight and Cost Savings in the 2011 Fiat Nuova Panda. N-24,D-31
In the 2014 Jeep Renegade BU/520, a welded blank combination of 1.3 mm and 1.8 mm TWIP 450/950 (Figure 11) replaced a two-piece aluminum component, aiding front end stability while reducing weight in a vehicle marketed for off-road applications.D-31
Figure 11: A TWIP welded blank improved performance and lowered weight in the 2014 Jeep Renegade BU/520.D-31
Also in 2014, the Renault EOLAB concept car where the A-Pillar Lower and the Sill Side Outer were stamped from TWIP 980 steel.R-21 By 2014, GM Daewoo used TWIP grades for A-Pillar Lowers and Front Side Members, and Hyundai used TWIP steel in 16 underbody parts. Ssangyong and Renault Samsung Motors used TWIP for Rear Side Members.I-20
Other applications include shock absorber housings, floor cross-members, wheel disks and rims, wheelhouses, and door impact beams.
A consortium called TWIP4EU with members from steel producers, steel users, research centers, and simulation companies had the goal of developing a simulation framework to accurately model the complex deformation and forming behavior of TWIP steels. The targeted part prototype component was a backrest side member of a front seat, Figure 12. Results were published in 2015.H-58
Figure 12: TWIP4EU Prototype Component formed from TWIP Steel.H-58
In addition to a complex thermomechanical mill processing requirements and high alloying costs, producing TWIP grades is more complex than conventional grades. Contributing to the challenges of TWIP production is that steelmaking practices need to be adjusted to account for the types and amounts of alloying. For example, the typical ferromanganese grade used in the production of other grades has phosphorus levels detrimental to TWIP properties. In addition, high levels of manganese and aluminum may lead to forming MnO and Al2O3 oxides on the surface after annealing, which could influence zinc coating adhesion in a hot dip galvanizing line.D-29
Critical to the performance of TWIP steels is having a microstructure that is fully austenitic. This is achieved with relatively high carbon (C > 0.5%) and manganese (Mn > 15%). These levels put the alloy at risk for hydrogen embrittlement, otherwise known as hydrogen-induced delayed fracture. Additions of aluminum were found to be effective in improving the resistance to delayed fracture. However, the levels of aluminum needed substantially reduced the castability of the molten alloy during continuous casting due to the propensity for aluminum to oxidize, which results in nozzle blockage and slag entrapment.
To reduce the amount of Al and consequently improve the castability of TWIP steels without reducing their resistance to delayed fracture, rare earth (RE) elements can be used. Rare earth metals react with H2 and form metal hydrides that are much more stable than the ordinary types of hydrogen entrapments in steels.Z-19
During annealing, manganese diffuses to the surface and oxidizes. The enriched manganese at the surface produces an oxidized layer that reduces the zinc wettability on the steel surface, and limits the ability to achieve a continuous galvanized coating. Solely using a high dew point atmosphere, such as the production strategy with QP steels, is insufficient in these high-Mn TWIP alloys.
A surface treatment process of annealing in a +10°C dew point to promote internal oxidation rather than external oxidation, combined with a subsequent pickling operation to remove any surface manganese oxides, results in a fully austenitic substrate covered by a lean-Mn decarburized ferrite layer, Figure 13. This strategy has led to the commercialization of hot-dip galvanized TWIP steels.P-32
Figure 13: Cross sectional microstructure of TWIP steel after targeted processing to improve galvanizability.P-32
Thanks are given to Trey Leonard, for his contributions to this page. Trey is the founder and CEO of Standard Mechanics, LLC, where he delivers advanced mechanical testing services and solutions across a wide range of applications, from automotive design to consumer electronics. His expertise spans formability, fatigue, and strain rate sensitivity testing. Beyond conducting tests, he partners with customers to ensure the development of high-quality, calibrated material cards and models for accurate finite element simulations. Dr. Leonard earned his Ph.D. in Mechanical Engineering from Mississippi State University, where he pioneered and licensed technologies in dynamic material testing and characterization. Building on this foundation, he continues to develop innovative testing methods and technologies that advance the field of dynamic mechanical testing. He also contributes to the broader engineering community through his work with ASTM International, where he serves on the E28 Committee on Mechanical Testing, regularly reviewing and improving industry standards.
