Quantifying and Enhancing Puncture Resistance 

in Railroad Tank Cars Carrying Hazardous 

Materials

Phase I: Preliminary Study

Prepared for

Transportation Issues Team

The Chlorine Institute

Arlington, VA

Prepared by

Ted L. Anderson, Ph.D., P.E.

Structural Reliability Technology, Inc.

Boulder, CO

Steven W. Kirkpatrick, Ph.D.

Applied Research Associates, Inc.

Mountain View, CA

September 1, 2006

2465 Central Avenue, Suite 110 2672 Bayshore Parkway, Suite 1035

Boulder, CO 80301 Mountain View, CA 94043

(303) 415-1475 (Ph) (650) 625 8150 (Ph)

(303) 415-1847 (fax) (650) 625-8145 (fax)

www.srt-boulder.com www.arasvo.com
1

EXECUTIVE SUMMARY

This report is a critical assessment of puncture resistance and the potential for lading loss 

in tank cars. The effect of material properties and tank car design on puncture resistance 

is examined.

An overview of the fracture behavior of steels is presented, followed by a discussion on 

possible improvements in tank car materials. Much of the previous work on 

improvements in steel for tank car applications has focused on low-temperature 

toughness properties. However it is the resistance to ductile fracture that is the most 

important factor in lading loss because most punctures occur by ductile rupture. The 

authors recommend that the next generation of tank car steel have very low sulfur content

and sulfide shape control to provide superior upper-shelf toughness. Further work is 

necessary to determine whether a carbon-manganese steel or a microalloyed steel would 

be better suited for tank car applications.

An examination of trends from prior accident data led to the development of a predictive 

model that quantifies the effect of design modification and material properties. For 

existing chlorine tank cars, the model and prior accident data indicate that a total of 44 

punctures through the head and shell (combined) are expected for every 1000 cars 

involved in a mainline accident. If the proposed design modifications for chlorine cars 

(i.e., increased wall thicknesses, addition of head shields) are adopted, but tank car steel 

quality is unchanged, the model predicts 12 punctures per 1000 cars. However, if a new

steel with, hypothetically, twice the puncture resistance is adopted, the predicted 

punctures decrease from 44 to 2 per 1000 cars if the design remains unchanged. If both

the steel and design are improved, the model predicts 2 punctures per 10,000 cars.

To validate the conclusions of the puncture model, a puncture resistance test for tank car 

materials is desirable. As part of a preliminary effort to develop a puncture test, a series 

of computer simulations of fracture and puncture were performed. These analyses were 

restricted to relatively small-scale laboratory experiments. Full-scale simulations of tank 

car punctures are recommended for a subsequent phase.

This report includes previously unpublished work performed by the authors as part of 

their investigation of the recent derailment near Minot, ND. This work includes 

experimental data and detailed nonlinear dynamic computer simulations. Many of the 

computational procedures developed in the Minot investigation will be applicable to fullscale puncture simulations, which will be undertaken in a future study.
2

TABLE OF CONTENTS

1 BACKGROUND ........................................................................................................ 3

2 EFFECT OF MATERIAL PROPERTIES ON PUNCTURE RESISTANCE............ 4

2.1 Fracture Mechanisms in Steel............................................................................. 4

2.1.1 Cleavage (Brittle) Fracture.......................................................................... 5

2.1.2 Ductile Rupture (Microvoid Coalescence) ................................................. 7

2.1.3 The Ductile-Brittle Transition................................................................... 10

2.2 Effect of Steel Chemistry and Microstructure .................................................. 10

2.3 Steels for Improved Tank Car Performance ..................................................... 20

3 EFFECT OF TANK CAR DESIGN ON PUNCTURE RESISTANCE................... 30

3.1 Inferring Trends from Prior Accident Data....................................................... 30

3.2 Development of a Predictive Model................................................................. 35

4 DYNAMIC COLLISION SIMULATION ............................................................... 43

4.1 Material Model for Ductile Fracture ................................................................. 43

4.2 Calibration of Material Model with Charpy Impact Tests................................ 44

4.3 Full-Scale Simulation of Tank Car Collisions and Rupture ............................. 47

5 DYNAMIC PUNCTURE SIMULATION ............................................................... 57

5.1 Charpy Calibration............................................................................................ 57

5.2 Fracture Simulation of Unnotched Bars........................................................... 59

5.3 Puncture of a Flat Plate ..................................................................................... 63

6 CONCLUSIONS AND RECOMMENDATIONS ................................................... 71

7 REFERENCES ......................................................................................................... 73
3

1 BACKGROUND

When a derailment or other rail accident occurs, the resulting collision forces can lead to 

a loss of lading from tank cars. While such an event is always undesirable, it is 

particularly damaging when the cars contain a hazardous material. Two relatively recent 

derailments in Minot, ND [1,2] and Graniteville, SC [3] that resulted in significant 

releases of hazardous materials have heightened the concern over lading loss during rail 

accidents. There is a strong desire in the rail industry to develop a new generation of tank 

cars that are more resistant to puncture in the event of an accident. 

In recent years, normalization of steels for tank cars carrying gases has become 

mandatory. The requirement reduces the incidence of brittle failures during rail accidents. 

However, the accident data has shown that the normalization requirement has had a 

negligible effect on the frequency of lading loss. The overwhelming majority of lading 

loss incidents are ductile failures [4, 5]. Normalization provides no significant protection 

against ductile puncture or ductile fracture.

There are a number of ways to increase the puncture resistance of tank cars, including:

1. Increasing the thickness of the shell and head.

2. Adding head shields and jackets.

3. Using modern high-toughness steels in place of traditional carbon steels.

Other possible remedies have been proposed, such as honeycomb and crumble zones. A 

major difficulty is that there is presently no recognized method to quantify the 

improvement in puncture resistance of a proposed design. Past accident data can be used 

to infer the relative benefits of increases in plate thickness, but there are practical limits to 

section thickness. Tougher steel should result in an improvement in puncture resistance, 

but quantifying this benefit is difficult.

This report takes a critical look at the issue of puncture resistance. There is an extensive 

discussion of the effect of material properties on puncture resistance, and we offer 

recommendations on potential next-generation steels. A database of previous rail 

accidents is used to assess the effect of tank car design features such as wall thickness, 

jackets, and head shields. A model is developed to explain the trends in previous 

accident data and to predict the effect of design modifications. Finally, some preliminary 

computer simulations of fracture and puncture are performed.

This report includes previously unpublished experimental and computational results from 

the investigation of the Minot, ND derailment.
4

2 EFFECT OF MATERIAL PROPERTIES ON PUNCTURE 

RESISTANCE

This chapter begins with a brief review of the microscopic mechanisms of fracture in 

ferritic steel (Section 2.1), followed by a discussion of the effect of chemistry and 

microstructure on fracture resistance (Section 2.2). These fundamental principles lead 

directly to the authors’ recommendations for steels with improved puncture resistance, 

which are presented in Section 2.3.

2.1 Fracture Mechanisms in Steel

The two fracture mechanisms that are of primary interest in tank car steels are illustrated 

in Figure 2.1 [6]. Cleavage fracture is characterized by rapid transgranular crack 

propagation. It is referred to as brittle fracture, but it can be preceded by significant 

plastic deformation. Ductile fracture occurs through the nucleation and growth of 

microscopic voids at nonmetallic inclusions, usually manganese sulfide (MnS). These 

two mechanisms are described further below.

a) Brittle fracture (cleavage).

b) Ductile fracture (microvoid coalescence).

FIGURE 2.1 Fracture mechanism in steel [6].
5

2.1.1 Cleavage (Brittle) Fracture

A photograph of a brittle fracture in a tank car is shown in Figure 2.2 [1]. The fracture 

surface in a typical brittle failure is flat and is perpendicular to the principal stress 

direction. In coarse-grained steels, shiny facets can be seen at low magnifications. 

Higher magnifications are necessary to discern cleavage facets in fine-grained steels. 

Figure 2.3 is a scanning electron microscope (SEM) photograph of cleavage in a lowalloy steel. The lines on each facet are called river patterns.

In body-centered cubic (BCC) metals such as ferritic iron, cleavage fracture occurs on the 

cube faces of the unit cell, which have the lowest packing density in the crystal. That is, 

there are fewer bonds to break per unit area on preferred cleavage planes than on other 

planes in the crystal. In polycrystalline metals with randomly oriented grains, a cleavage 

crack must change directions each time it crosses a grain boundary. 

The formation of river patterns as a result of the twist angle between cleavage planes in 

adjoining grains is illustrated in Figure 2.4. When the crack reaches a grain boundary, it 

must immediately change orientations to accommodate the nearest cleavage plane on the 

adjoining grain. This causes the crack to split into a number of parallel fracture planes. 

These parallel planes link up by tearing. As the fracture propagates across the grain, the 

parallel fracture planes merge. This process is repeated when the cleavage crack reaches 

another grain boundary. The river patterns can be used to infer the crack propagation 

direction on the microscopic scale. Figure 2.5 is an SEM photograph that shows a closeup of river patterns in a low-alloy steel. The resistance to cleavage fracture increases

with decreasing grain size, due in large part to the energy dissipation that occurs when 

cleavage cracks cross grain boundaries.

FIGURE 2.2 Brittle fracture in an anhydrous ammonia tank car that derailed near Minot, ND [1].
6

FIGURE 2.3 SEM photograph of transgranular cleavage fracture in steel [6].

FIGURE 2.4 Formation of river patterns as a result of cleavage fracture crossing a twist boundary 

[6].
7

FIGURE 2.5 SEM photograph of river patterns in steel [6]. The light areas correspond to tearing 

between parallel cleavage planes.

2.1.2 Ductile Rupture (Microvoid Coalescence)

The microscopic processes that result in ductile fracture are illustrated in Figure 2.6 [6]. 

Microvoids that nucleate at inclusions grow as a result of plastic strain. Plastic strain 

concentrates between voids, resulting in local necking and coalescence (fracture). Figure 

2.7 is an SEM photograph of the fracture surface of a material that failed by microvoid 

coalescence.

Macroscopically, ductile fracture tends to have a dull appearance, compared to the shiny 

faceted surface that is characteristic of cleavage fracture. In some instances, the fracture 

surface of a ductile failure is oriented approximately 45 degrees from the applied stress. 

Figure 2.8 is a photograph of a 45-degree ductile fracture in the head of an ammonia tank 

car that derailed near Minot, ND [1].
8

(a) Inclusions in a ductile matrix. (b) Void nucleation.

(c) Void growth (inclusions omitted for clarity). (d) Strain localization between voids

(e) Necking between voids. (f) Void coalescence.

FIGURE 2.6 Void nucleation, growth, and coalescence in metals [6].
9

FIGURE 2.7 SEM photograph of microvoid coalescence in steel.

FIGURE 2.8 Ductile fracture in an anhydrous ammonia tank car that derailed near Minot, ND [1].
10

2.1.3 The Ductile-Brittle Transition

Carbon steels exhibit a transition from to ductile to brittle behavior as temperature 

decreases. Figure 2.9 illustrates the temperature dependence of toughness in steels. At 

high temperatures, the material is on the upper shelf, where the fracture mechanism is 

microvoid coalescence. On the lower shelf, the toughness is low and the fracture 

mechanism is cleavage. A mixture of cleavage and microvoid coalescence is typically 

observed in the transition region between the lower and upper shelves.

2.2 Effect of Steel Chemistry and Microstructure

A number of metallurgical variables affect a steel’s resistance to cleavage fracture and 

microvoid coalescence. Figure 2.10 illustrates the most important parameters that 

influence toughness. Beginning with a baseline steel, its toughness properties can be 

improved through a variety of means. Refinement of ferrite grain size results in a 

downward shift in the ductile-brittle transition curve. Desulfurization and sulfide shape 

control increase the upper shelf toughness relative to the baseline. 

Ferrite grain size refinement, which results in improved cleavage resistance and a 

downward shift in the transition temperature, can be achieved through a variety of means. 

Normalization, where steel is air cooled from approximately 1700

o

F, is the traditional 

method for grain refinement. Modern steelmaking procedures such as microalloying and 

thermomechanical controlled processing (TMCP) can produce ultra-fine grain structures 

with excellent strength and low-temperature toughness.

TEMPERATURE

Upper Shelf

(Microvoid Coalescence)

Lower Shelf

(Cleavage)

TOUGHNESS

FIGURE 2.9 The ductile-brittle transition in steels.
11

TEMPERATURE

TOUGHNESS

Desulfurization

Sulfide

Shape

Control

Ferrite Grain

Refinement

Baseline

Toughness

Improved

Toughness

FIGURE 2.10 Effect of microstructure on the toughness of steel.

Over the past 30 years, efforts to improve the toughness of tank car steels have focused 

almost exclusively on low-temperature properties (i.e., downward shifts in the transition 

temperature) [7-10]. However, it is the upper shelf toughness that dictates puncture 

resistance, as discussed in Section 2.3 below. In steels, microvoid coalescence nucleates 

predominately at MnS inclusions. Therefore, reductions in sulfur content directly 

translate to increased upper-shelf toughness. Moreover, the shape of MnS inclusions has 

a pronounced effect on ductile fracture behavior.

Figure 2.11 illustrates two inclusion morphologies in steel. When a steel plate is hot 

rolled, inclusions tend to elongate into sulfide stringers, as the upper sketch in Fig. 2.11 

illustrates. The goal of sulfide shape control is to create spherical inclusions, as 

illustrated in the lower sketch. In the past, sulfide shape control was accomplished by 

adding small amounts of rare earth metals to the molten steel. This practice tended to 

result in weldability problems, however. More recently, sulfide shape control has 

typically been achieved through CaSi additions, which have the added benefit of reducing 

the sulfur content in the steel.

In the absence of sulfide shape control, the upper shelf toughness can be highly 

anisotropic. That is, the Charpy V-notch (CVN) energy is affected by the notch 

orientation relative to the rolling direction. Figure 2.12 illustrates CVN specimens with 

longitudinal and transverse orientation. Figure 2.13 compares the transverse and 

longitudinal CVN transition curves for an anhydrous ammonia car that sustained a 360-

degree shell fracture during the Minot derailment [2]. Figure 2.14 is a photograph of the 

fracture surface from this car. The crack propagated circumferentially in the shell, which 

corresponds to the rolling direction. This low-energy ductile fracture has a “woody”
12

appearance because the crack ran along sulfide stringers. A wood analogy is apt here: 

just as it is easier to split wood along the grain than against the grain, less energy is 

required to propagate a crack in the longitudinal direction in a steel plate with sulfide 

stringers.

As a result of the Minot derailment, a total of 7 anhydrous ammonia cars lost all of their 

lading due to punctures and fractures through the head and/or shell. Each of these cars 

was built in the 1970s. Testing on head and shell samples extracted from the damaged 

cars indicated that the steel met the tensile and chemistry requirements of the TC 128B 

specification that existed at the time of construction [1, 2]. The current TC 128B 

specification limits the sulfur content to 0.015%, while the limit was 0.040% when the 

Minot cars were built. Another substantial change in the specification for tank car steels 

over this period occurred in 1989, when a requirement to normalize the head and shell 

steel was introduced. To this day, the TC 128B specification does not require sulfide 

shape control in the steelmaking process.

Rolling

Direction

Sulfide

Stringers

Spherical

Inclusions

FIGURE 2.11 Sulfide shape control results in spherical inclusions instead of sulfide stringers.
13

Transverse

Longitudinal

Rolling

Direction

FIGURE 2.12 Orientation of Charpy specimens relative to the rolling direction.

0

10

20

30

40

50

60

-150 -100 -50 0 50 100

Transverse

Longitudinal

Absorbed Energy, ft-lb

Temperature, oF

Minot Car 19

Shell Material

FIGURE 2.13 Effect of CVN specimen orientation on toughness in an ammonia tank car 

that derailed near Minot, ND [2].
14

FIGURE 2.14 Low-energy ductile fracture in Minot Car 19 [1]. The fracture propagated in the 

longitudinal direction, along sulfide stringers, which resulted in a “woody” appearance.

During the Minot investigation, various tests were performed on steels from the subject 

cars, as well as on exemplar tank car steels. One of the exemplar materials was a 1999

vintage normalized TC 128B plate. Figures 2.15 and 2.16 compare the microstructures of 

a 1970s vintage steel from the Minot derailment with the modern steel plate. The most 

obvious difference is that the modern normalized plate has a finer ferrite grain size than 

the older steel, as expected. The modern plate also has a lower sulfur content than the 

older steel. Apparently, neither plate was manufactured with sulfide shape control, as 

discussed below.

The Minot testing program included high-rate fracture mechanics tests, which were 

performed at Southwest Research Institute in San Antonio [11]. Figures 2.17 and 2.18 

compare the fracture surfaces of specimens extracted from the two plates whose 

microstructures are shown in Figs. 2.15 and 2.16, respectively. The crack propagation 

direction was longitudinal in both cases. The fracture surface in Fig. 2.17 has a 

“corrugated roof” appearance. Fracture along sulfide stringers created troughs, which 

reflect the light in the photograph. The fracture surface of the modern plate (Fig. 2.18) 

also shows troughs, which are indicative of sulfide stringers. There are fewer such 

features on Fig. 2.18 than on Fig. 2.17, which is due to lower sulfur content in the former 

case. Nevertheless, the upper-shelf toughness of modern tank car steels could be 

significantly improved through sulfide shape control.

In order to demonstrate the effect of normalization on toughness, the NTSB heat treated a 

sample extracted from one of the cars damaged in the Minot derailment [1, 2]. The 

resulting toughness comparison is plotted in Fig. 2.19. There is a difference in uppershelf toughness between longitudinal and transverse CVN specimens, as was the case in 

Fig. 2.13. When this plate was subject to a normalizing heat treatment, the expected 

leftward shift in the transition curve occurred. Moreover, there was a slight improvement 
15

in the upper shelf toughness. Since normalization does not affect MnS inclusions, this 

improvement in upper shelf toughness is likely due to a grain size strengthening effect, 

which is described below.

Figure 2.20 schematically illustrates the effect of grain refinement on a material’s stressstrain curve. Assuming ductility remains constant, the fracture energy, which is 

proportional to the area under the stress-strain curve, would be higher for the fine-grained 

material. However, the trend in Fig. 2.19 does not prove that normalized TC 128 B has 

better upper shelf toughness than as-rolled TC 128 B plates in general. The strength 

requirements for both normalized and as-rolled plates are the same, and steelmakers are 

given substantial latitude in how they meet the minimum tensile properties. In 

normalized plate, a steelmaker can take advantage of grain size strengthening by reducing 

the amount of certain alloying elements that contribute to strength. Given the same sulfur 

content and tensile properties, there should be no systematic difference in the upper-shelf 

toughness of as-rolled versus normalized TC 128 B plates. Normalization per se does not 

result in improved upper shelf toughness.

FIGURE 2.15 Microstructure of a 1970s vintage TC 128 B steel sample taken from the shell of Minot 

Car 22 [11].
16

FIGURE 2.16 Microstructure of a 1999 vintage normalized plate of TC 128B steel [11].
17

FIGURE 2.17 Fracture surface from a high-rate toughness test on the shell steel from Minot Car 22 

(Fig. 2.15), tested at 37oF [11]. The shiny areas correspond to troughs that formerly contained sulfide 

stringers.
18

FIGURE 2.18 Fracture surface from a high-rate toughness test on a modern normalized TC 128B 

plate (Fig. 2.16), tested at ambient temperature [11]. Although the sulfur content is lower than in the 

1970s vintage steel from Minot Car 22, numerous sulfide stringers are evident. Currently, the TC 

128 B specification does not require sulfide shape control.
19

0

10

20

30

40

50

60

70

80

-150 -100 -50 0 50 100 150 200

Transverse

Longitudinal

Longitudinal, Normalized

Absorbed Energy, ft-lb

Temperature, oF

Minot Car 22

Shell Material

FIGURE 2.19 Effect of specimen orientation and normalization on impact toughness in a 1970s 

vintage TC 128B steel from an ammonia tank car that derailed near Minot, ND [1].

TRUE STRESS

TRUE STRAIN

Grain Refinement

FIGURE 2.20 Strengthening due to grain refinement, which can also improve upper shelf toughness.
20

2.3 Steels for Improved Tank Car Performance

Given the desire of the rail industry to reduce the frequency of lading loss resulting from

accidents, it is useful to consider which material properties are most important in 

reducing lading loss through head and shell failures. This then leads to a discussion of 

possible replacements for the current TC 128B steel specification in future tank car 

construction.

Figure 2.21 is a schematic plot of the energy required to puncture or fracture a steel plate 

as a function of temperature. The fracture energy is substantially reduced when there is a 

pre-existing notch-like feature. Moreover, the fracture mode transitions from ductile to 

brittle at much lower temperatures for the unnotched case. Therefore, failure in 

unnotched steel plates is initiated through ductile puncture over a wide temperature range, 

including temperatures where notched plates exhibit lower-shelf behavior.

The effect of a pre-existing notch on fracture behavior is demonstrated in Figs. 2.22 and 

2.23. During the Minot investigation conducted by the authors, Charpy testing was 

performed on exemplar steels taken from two retired tank cars that were built in 1967 and 

1971 [11]. Standard CVN specimens tested at -36oF absorbed energies ranging from 3 to 

6 ft-lb, and all fracture surfaces were 100% brittle. Figure 2.22 is a photograph of the 

broken specimens. Figure 2.23 is a photograph of two unnotched specimens impact 

tested at -36oF in a Charpy machine with a 300-ft-lb capacity. Both specimens bent but 

did not break, which indicates that the fracture energy for the unnotched specimens is at 

least two orders of magnitude higher than for notched specimens at this temperature. 

These specimens absorbed a significant amount of energy without fracturing, despite 

being at a temperature that is on the lower shelf of the CVN toughness curve.

When a tank car is subject to an impact load during a rail accident, the head and shell are 

analogous to the unnotched condition in Figs. 2.21 and 2.23, aside from the rare instances 

where the impact occurs at a significant pre-existing weld flaw. In the absence of a preexisting notch, a puncture must form at a smooth surface. This requires a substantial

amount of energy concentrated over a small area. Moreover, the puncture will form by 

ductile rupture (microvoid coalescence) unless the steel is at a very low temperature (i.e., 

cryogenic conditions well below ambient temperatures in Antarctica). 

Once a ductile puncture forms, one or more cracks may emanate from the puncture if 

sufficient kinetic energy remains from the impact event. Such a crack may be ductile or 

brittle, depending on the metal temperature relative to its transition region (in the 

presence of a notch or crack). Figures 2.24 and 2.25 are photographs of a puncture and 

subsequent brittle crack propagation that occurred in an anhydrous ammonia tank car as a 

result of the Minot derailment. Figure 2.26 is a photograph of another anhydrous 

ammonia car that was taken at the site of the Minot derailment. In this case, a 360-degree 

shell fracture initiated from a puncture. Figure 2.14 is a photograph of the fracture 

surface of the car in shown Fig. 2.26. Recall from the previous section that this failure 

propagated as a low-energy ductile fracture. The woody appearance of the fracture 

surface is due to a significant number of sulfide stringers.
21

TEMPERATURE

FRACTURE

ENERGY

Pre-Existing

Notch

No Notch Ductile Puncture

FIGURE 2.21 Effect of a pre-existing notch on fracture energy.

FIGURE 2.22 Charpy specimens tested at -36oF, where the fracture is 100% brittle. Coupons 7AS 

and 8BS were taken from retired tank cars built in 1967 and 1971, respectively.
22

FIGURE 2.23 Unnotched Charpy specimens for Coupons 7AS and 8BS tested at -36oF. The Charpy 

test machine has a 300 ft-lb capacity.
23

FIGURE 2.24 Puncture and brittle fracture in an anhydrous ammonia tank car that derailed near 

Minot, ND [1].

FIGURE 2.25 Close-up of the puncture in Fig. 2.24.
24

FIGURE 2.26 Puncture and 360-degree shell fracture in an anhydrous ammonia car, which derailed 

near Minot, ND. Crack propagation from the puncture was by a low-energy ductile fracture 

mechanism (Fig. 2.14).

Over the past 30 years, nearly all research and discussion about improving the toughness 

of tank car steels has focused on brittle fracture resistance [7-10]. The 1989 requirement 

to construct tank car shells from normalized TC 128B plate was intended to reduce or 

eliminate brittle fracture during accidents. Studies of modern microalloying steels as 

possible replacements to TC 128B have largely been motivated by the superior lowtemperature toughness properties that can, in theory, be achieved in these materials.

We contend that the preoccupation with brittle fracture avoidance has not resulted in the 

most prudent use of time and resources. Our reasoning is as follows:

• Two separate studies of past accident data [4, 5] indicated that brittle fracture 

comprises a small fraction of total lading loss incidents. Moreover, these studies 

concluded that preventing brittle fracture would have a very small effect on the 

overall probability of lading loss because in most cases where brittle fracture 

occurs, derailment forces were sufficient to cause ductile failure.

• In order for brittle fracture to occur in a tank car, it must initiate from a notch-like 

feature. Aside from the rare cases where there is a significant pre-existing flaw at 
25

the impact location, brittle fracture must be preceded by ductile puncture. 

Prevention of brittle fracture is, at best, a second line of defense. Preventing the 

puncture that initiated brittle failure would seem to be a more sensible goal.

• The 1989 requirement to use normalized TC 128 B steel tank car shells has 

largely eliminated the risk of brittle fracture in tank cars built since this 

requirement went into effect. Therefore, pursuing even better low temperature 

properties that are potentially available in microalloyed steels does not appear to 

make sense. If improved low-temperature toughness is the only reason for 

considering microalloyed steels, then this is an option with a high cost and 

virtually no benefit.

That is not to say that modern microalloyed steels should not be considered for use in 

future tank car construction, but the low-temperature toughness properties should not be 

the primary motivation. The real potential benefit in certain modern grades of steel lies 

in their superior upper shelf toughness, which is achieved largely through desulfurization 

and sulfide shape control.

Given that making tank cars more puncture resistant is a desirable goal, improved steel 

properties must play a crucial role in achieving that goal. Design modifications such as 

increased wall thickness can be beneficial (Chapter 3), but are not sufficient to prevent 

major releases such as occurred at Minot and Graniteville. Another suggested remedy 

entails accelerating the retirement of pre-1989 tank cars and replacing them with 

normalized TC 128B steel cars. Normalization does not affect the resistance to ductile 

puncture, so such a massive capital investment would produce a minimal benefit. 

Moreover, an accelerated replacement program using current steel specifications would 

result in a missed opportunity. If a large number of TC 128B cars are built in the next 

few years, these new cars will not be replaced for a long time. When and if the industry 

decides that improved steel properties are beneficial, they will be not be in a position to 

take advantage of new steels if they have already spent substantial sums to replace the 

pre-1989 fleet with cars made from TC 128B.

There are two options for improving the properties of steel for tank car construction:

1. Modify the TC 128B or other C-Mn steel specification to reduce the maximum 

allowable sulfur content and require sulfide shape control.

2. Adopt a microalloyed steel with superior upper shelf toughness as well as 

acceptable formability and weldability.

The first option is worth considering. Conventional carbon-manganese steels are capable 

of very high upper shelf toughness (> 200 ft-lb CVN) when sulfur levels are very low and 

sulfide shape control is part of the melting practice [12]. Desulfurization through the 

addition of calcium compounds is commonplace in the steel industry. Sulfur levels have 

declined over the years despite the fact that many steel specifications still allow relatively 

high amounts. For example, the A 516-70 specification currently allows 0.035%. Sulfur

contents of 0.008% or lower are readily attainable with current melting practices. Sulfide 

shape control must also be applied along with desulfurization in order to obtain the 
26

maximum benefit in upper shelf toughness, and hence puncture resistance. The current 

TC 128B specification limits sulfur to 0.015%, but this limit could be reduced to 0.010% 

or below. Apparently, Mittal steel currently manufactures TC 128 B steel with sulfide 

shape control [13], but it is not part of the AAR requirement. Further work is necessary 

to quantify the upper shelf toughness levels that are achievable in TC 128B steel, both 

with the current specification and the proposed refinements.

An ongoing project at Southwest Research Institute [14] is eva luating the properties of 

various generations of tank car steels. Figure 2.27 is a plot of transverse Charpy energy 

at +50oF as a function of sulfur content. There is considerable scatter, and a well-defined 

trend in the data is not readily apparent. However, the data for pre-1989 shells 

correspond to steels that have not been normalized, so the Charpy energies do not 

necessarily reflect upper shelf behavior. Figure 2.28 is a re-plot of the data with these 

points removed. The trend of increasing upper shelf toughness with decreasing sulfur 

content is much clearer, although there is still significant scatter. Two data points for 

pre-1989 heads have Charpy energies below 25 ft-lb, so these materials are probably not 

on the upper shelf at +50oF. Much of the scatter in upper-shelf transverse toughness is 

likely caused by variability in the sulfide stringer shape. Sulfide shape control should 

reduce this scatter and improve the toughness in the transverse orientation.

FIGURE 2.27 Charpy energy at +50oF versus sulfur content for tank car steels [14].
27

FIGURE 2.28 Same as Fig. 2.27 but with data points removed for non-normalized shell material [14].

Before discussing the merits of modern microalloying steels (Option 2 above), a brief 

overview of these material might be beneficial to the reader. Microalloyed steels, also 

known as high strength low alloy (HSLA) steels, have small additions of alloying 

elements such as columbium, vanadium, and titanium. These steels achieve high strength 

and toughness through a very fine grain structure. The microalloying elements form 

carbide and nitride precipitates, which provide additional strengthening. Some HSLA 

steels are manufactured with a thermomechanical controlled process (TMCP), which 

entails controlled rolling and accelerated cooling. The finishing temperature for rolling is 

in the austenitic range, but below the recrystallization temperature for austenite. Upon 

accelerated cooling, a very fine ferritic structure forms on deformed austenite grains. 

Some HSLA steels are normalized rather than manufactured with the TMCP method.

The AAR previously commissioned a two-part study of HSLA steels for possible tank car 

use. The reports of the Phase I and Phase II programs were issued in 1987 and 1991, 

respectively [9, 10]. A proposed steel specification, TC-135, was developed during Phase 

I. Although the test results on HSLA steels were largely encouraging, two problems were 

identified in the AAR research. First, the good toughness properties produced as a result 

of controlled rolling are lost when the material is heated to a hot-forming temperature. 

Second, the weldability of the HSLA steels considered was not as good as hoped. Both 

of these difficulties have been addressed in recent years [15]. Good formability can be 
28

achieved in normalized HSLA plates, and the weldability of HSLA steels has improved 

due to lower carbon content and other factors.

Table 2.1 lists the existing ASTM standards for HSLA steel plate. The proposed AAR 

TC-135 specification is also shown for comparison. Since upper shelf toughness is the 

key factor in puncture resistance, the steel grades that allow up to 0.035% sulfur (A 633, 

A 656, and A 737) are not ideal for future tank car construction. The only ASTM 

specifications in Table 2.1 that include low sulfur limits are A 841 and A 945. The 

former is not suitable for hot-formed heads because it is exclusively produced by the 

TMCP method. Paragraph 1.3 of A 841 limits forming and post-weld heat treatments to 

1200oF because higher temperatures adversely affect the toughness and microstructure of 

TMCP steels. The A 841 specification could, however, be considered for tank car shells 

and cold-formed heads. The A 945 specification allows plate to be produced by the 

TMCP method, but it is not a requirement. The title of A 945, “Standard Specification 

for High-Strength Low-Alloy Structural Steel Plate with Low Carbon and Restricted 

Sulfur for Improved Weldability, Formability, and Toughness”, indicates that is it is the 

best choice for hot-formed tank car heads among the available ASTM grades of 

microalloyed HSLA steel. Referring to Table 2.1, the chemical and tensile specifications 

of A 945 are similar to TC 135, but the former undoubtedly incorporates improvements 

in HSLA steelmaking technology that have occurred since 1991. Sulfide shape control is 

not specifically required by A 945, but it is routinely applied in the manufacture of this 

alloy. If an AAR specification equivalent to A 945 were developed, it should include an 

explicit requirement for sulfide shape control.

It remains to be seen whether Option 2 (microalloyed steel) is better than Option 1

(conventional normalized C-Mn steel with low sulfur and sulfide shape control) on a 

cost/benefit basis. A testing program and cost analysis is recommended to assess the 

relative merits of Options 1 and 2.
29

TABLE 2.1

Summary of chemical and strength requirements for HSLA steels.

Specification Grade % Carbon % Manganese % Sulfur

Yield Strength, 

ksi

Tensile Strength, 

ksi

A 0.18 max 1.00 – 1.35 0.035 max 42 min 63 – 83

C 0.20 max 1.15 – 1.50 0.035 max 50 min 70 – 90

D 0.20 max 0.70 – 1.35 0.035 max 50 min 70 – 90

A 633 – 01

E 0.22 max 1.15 – 1.50 0.035 max 60 min 80 – 100

50 0.18 max 1.65 max 0.035 max 50 min 60 min

60 0.18 max 1.65 max 0.035 max 60 min 70 min

70 0.18 max 1.65 max 0.035 max 70 min 80 min

A 656 – 03

80 0.18 max 1.65 max 0.035 max 80 min 90 min

A 737 – 99 B 0.22 max 1.07 – 1.62 0.035 max 50 min 70 – 90

(Reapproved 04) C 0.22 max 1.07 – 1.62 0.035 max 60 min 80 – 100

A 0.20 max 0.70 – 1.35 0.030 max

B 0.15 max 0.70 – 1.35 0.030 max

C 0.10 max 0.70 – 1.60 0.030 max

50 min (Class 1)

60 min (Class 2)

70 – 90 (Class 1)

80 – 100 (Class 2)

D 0.09 max 1.00 – 2.00 0.010 max 100 min (Class 3) 145-170 (Class 3)

E 0.07 max 0.70 – 1.60 0.015 max 70 min (Class 4)

75 min (Class 5)

84 – 104 (Class 4)

88 – 108 (Class 5)

A 841 – 03a

F 0.10 max 1.10 – 1.70 0.020 max 70 min (Class 6)

75 min (Class 7)

80 min (Class 8)

82 – 102 (Class 6)

86 – 106 (Class 7)

90 – 110 (Class 8)

A 945 – 00 50 0.10 max 1.10 – 1.65 0.010 max 50 min 70 min

65 0.10 max 1.10 – 1.65 0.010 max 65 min 78 min

A 0.12 max 1.00 – 1.75 0.010 max 50 min 70 – 90

B 0.16 max 1.00 – 1.75 0.010 max 60 min 81 – 100

TC 135

C 0.22 max 1.00 – 1.60 0.010 max 60 min 81 – 100
30

3 EFFECT OF TANK CAR DESIGN ON PUNCTURE 

RESISTANCE

3.1 Inferring Trends from Prior Accident Data

An extensive database of prior rail accidents and resulting lading loss, created and 

maintained by the RSI-AAR Railroad Tank Car Safety Research and Test Project, has 

been used in a number of projects over the years. This database has made it possible to 

correlate lading loss incidents with tank car design attributes such as wall thickness. 

Figure 3.1 was taken from a 1998 RPI-AAR report [5] in which a Monte Carlo 

probabilistic fracture model was calibrated to the accident data. There is a clear trend 

between the probability of lading loss through the head or shell and section thickness. 

Figure 3.1 has considerable scatter because the data points reflect raw data, where sample 

size is limited for a given thickness. Another limitation of this plot is that the “equivalent 

thickness” plotted on the horizontal axis corresponds to the combined thickness when a 

jacket or head shield is present. For example, a jacketed 1⁄2” shell is given an effective 

thickness of 5/8” to account for a nominally 1/8” jacket. When head shields were present, 

0.5” was added to the head thickness. Any potential differences in the rupture behavior 

between two plates of a given combined thickness and a solid plate of that same thickness 

cannot be inferred from Fig. 3.1.

0

1

2

3

4

5

6

7

6 8 10 12 14 16 18 20 22

Shell Loss Data

Head Loss Data

Monte Carlo Model

Probability of Fracture, %

Equivalent Thickness, 16ths of an Inch

FIGURE 3.1 Results of an earlier study, where a Monte Carlo fracture model was calibrated to the 

accident database. RPI-AAR Report RA-03-6-62 [5].
31

A recent RSI-AAR study [16] took a more systematic look at tank car design parameters 

that affect lading loss probability. Statisticians from the University of Illinois performed 

multi-variable regression analysis on the accident data. This ana lysis had the effect of 

smoothing the data so that trends could be more readily discerned. The analysis 

separated the data into multiple populations, including:

• Head versus shell loss.

• Jacketed versus non-jacketed cars.

• Cars with and without head shields.

The investigators did, however, lump pressure and non-pressure cars into a single 

population for head and shell loss probability because they could not detect a statistically 

significant difference between the two car types at a given wall thickness. They adjusted 

the lading loss probability values downward to account for unreported accidents. The 

number of unreported accidents is, by definition, unknown, so the adjusted probability 

values in the AAR study are subject to uncertainty and error. However, the predicted 

relative trends of lading loss probability with section thickness and other variables should 

be reliable.

The results of the regression analysis are presented in tabular form in Ref. [16]. Figures 

3.2 to 3.4 show several plots created by the present authors that were generated from this

tabular data. 

Figure 3.2 is a plot of head and shell lading loss probability versus thickness for nonjacked cars without head shields. Note that the lading loss probability through the shell is 

much more sensitive to thickness than the head loss probability.

Figure 3.3 compares the lading loss through the shell for jacketed and non-jacketed cars. 

In the former case, the jacket and shell thickness were added to obtain the combined 

thickness. The data are plotted in this manner in order to isolate the effect of the standoff 

between the jacket and shell. This plot indicates that a jacketed shell performs slightly 

better than a non-jacketed shell with the same total thickness. For example, a jacketed 

1⁄2” shell, which has a combined thickness of approximately 5/8 ”, performs slightly better 

in an accident than a non-jacketed shell that is 5/8” thick. Of course, a jacketed 1⁄2” shell 

performs significantly better than a non-jacketed 1⁄2” shell, with the benefit coming from a 

combination of the additional section thickness provided by the jacket as well as the 

standoff between the jacket and shell.

Figure 3.4 shows the relative effect of a jacket or head shield on the probability of lading 

loss through the head. As is the case in Fig. 3.3, the lading loss probability is plotted in 

terms of combined thickness. In a non-jacketed car, where the head shield is flush against 

the head, the performance for a given combined thickness is slightly better than a head 

with the same total thickness. That is, a laminated 2-piece head configuration performs 

slightly better than a 1-piece head with the same total thickness. In a jacketed car, 

however, the performance is far superior to a non-jacketed car. When there is a standoff 
32

Lading Loss Through Heads and Shells

No Jacket or Head Shield

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

0 0.2 0.4 0.6 0.8 1 1.2

Thickness, inches

Lading Loss Probability

Head Loss

Shell Loss

FIGURE 3.2 Lading loss probability curves obtained from tabular results in RSI-AAR Report RA-05-02 [16].
33

Shell Loss in Mainline Accidents

Assumed Jacket Thickness = 0.1196"

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

0 0.2 0.4 0.6 0.8 1 1.2

Total Thickness (Excluding Insulation), inches

Lading Loss Probability

Non-Jacketed

Jacketed

FIGURE 3.3 Effect of a jacket on lading loss through the shell. Data taken from RSI-AAR Report RA-05-02 [16].
34

Head Loss in Mainline Accidents

Assumed Head Shield Thickness = 0.5"

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Total Thickness (Excluding Insulation), inches

Lading Loss Probability

No Head Shield

With Head Shield

Head Shield + Insulation

No Head Shield + Jacket

FIGURE 3.4 Effect of head shields and jackets on lading loss through heads. Data taken from RSI-AAR Report RA-05-02 [16].
35

between either a head shield or jacket and the head, the lading loss probability at a given 

combined thickness is significantly lower than for a solid head with the same total 

thickness. Note that although half-height head shields are included in the regression 

analysis in RSI-AAR Report RA-05-02 [16], they are not considered in the present study.

Clearly, the behavior of heads and shells in accidents are significantly different from one 

another. This behavior is explored further below.

3.2 Development of a Predictive Model

What follows is the presentation of a simple model that is intended to explain the trends 

in Figs. 3.2 to 3.4, as well as predict the effect of possible changes to the design and/or 

material properties.

Every rail accident is unique. A major derailment may result in multiple collisions, each 

of which is itself unique and highly complex. Let us assume that the complexities of a 

collision event can be captured with a single driving force parameter, which we will call 

puncture intensity:

Puncture Intensity (I) = × Impact Energy ,,, fGGG ( 123 L) (3.1)

where Gi are geometry factors, which could include the size and shape of the object that 

collides with the tank car, as well as the location and angle of the collision. Developing a 

detailed mathematical description of the function f(Gi) is beyond the scope of this project, 

and may be not be feasible in any case. It is sufficient for our purposes to assume that I

scales with the available impact energy.

Let us now define a puncture resistance index, IR, which is a function of section thickness 

and material properties. Puncture will occur when the driving force exceeds the material 

resistance. That is,

R

I I ≥ (3.2)

The absolute values of I and IR are arbitrary, so we can set IR = 1 for a 7/16” shell made 

from traditional tank car steel. Assuming the puncture resistance index exhibits a powerlaw dependence on shell thickness results in the following expression:

0.4375

n

R

t

I

 

=    (3.3)

Now suppose that we decide to increase the shell thickness by Δt. The new puncture 

resistance index is given by
36

0.4375

n

R

t t I

  + Δ

=    (3.4)

assuming the power-law dependence in Eq. (3.3). On the other hand, suppose that instead 

of increasing the shell thickness, we add a jacket of thickness Δt. If there is a significant

standoff between the jacket and shell, they should each respond to the impact event 

independently1, so the respective puncture resistance values would be additive:

0.4375 0.4375

n n

R

t t I

    Δ

= +        (3.5)

For the special case of n = 1, both of the above examples will result in the same puncture 

resistance. The physical significance of an exponent of unity is that the puncture energy 

of the shell plate scales linearly with thickness. If this were the case, there would be no 

net benefit of a jacket relative to a increasing the shell thickness by the amount of the 

jacket thickness. In reality, there is a modest benefit to the standoff between the jacket 

and shell, as Fig. 3.3 illustrates. Therefore, n must be slightly less than 1 for the shell.

The effect of the jacket on puncture resistance can be predicted from Eq. (3.5) if n is 

known. However, in order to translate puncture resistance into lading loss probability 

(Fig. 3.3), a statistical distribution function for the puncture intensity is needed.

The lading loss probabilities for the shell can be used to infer a statistical distribution of 

the puncture intensity in past mainline accidents. For example, the probability of lading 

loss through the shell is approximately 11% for 7/16” wall thickness, where IR = 1. In 

order for puncture to occur, I must reach or exceed IR. Therefore, an impact event where 

I = 1 is in the 89th percentile, meaning that I ≤ 1 in 89% of accidents. For shell 

thicknesses greater than 7/16”, IR was computed from Eq.(3.3) assuming n = 0.95. This 

exponent was arrived at through trial and error. The cumulative probability of the I values 

corresponding to the various shell thicknesses were determined in the same manner as the 

7

/16” case. The results of this exercise are listed in Table 3.1

The data in Table 3.1 were fit to a Weibull distribution:

1 exp

I

F

b

q

       

= − −               (3.6)

where F is the cumulative probability, and b & q are fitting constants. For the purpose of 

curve fitting, Eq. (3.6) can be linearized:

 

1

 That is, if the jacket and shell do not interact with one another during impact, the total puncture resistance 

is equal to the sum of the respective puncture resistances of the two plates. For example, if a projectile is 

fired at a pair of parallel plates of equal thickness, where there is significant gap between the plates, the 

energy required to penetrate both plates would be twice the energy necessary to penetrate a single plate.
37

TABLE 3.1

Puncture resistance and lading loss probability as a function of shell thickness. The puncture 

resistance index was computed from Eq. (3.3) assuming n = 0.95.

Shell Thickness, 

inches

Puncture Resistance 

Index (IR)

Lading Loss 

Probability

Cumulative 

Probability on I

0.4375 1.000 10.92% 89.08%

0.5 1.135 8.86% 91.14%

0.5625 1.270 7.12% 92.88%

0.625 1.403 5.68% 94.32%

0.6875 1.536 4.50% 95.50%

0.75 1.669 3.55% 96.45%

0.8125 1.801 2.79% 97.21%

0.875 1.932 2.18% 97.82%

0.9375 2.063 1.70% 98.30%

1 2.193 1.33% 98.67%

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

-0.2 0 0.2 0.4 0.6 0.8

Ln[-Ln(1-F)]

Ln (I)

FIGURE 3.5 Weibull fit of the puncture intensity at tank car shells for mainline accidents.
38

ln   − − ln (1 F I ) = − b ln ( ) b q ln( )   (3.7)

Figure 3.5 shows the fit of the data in Table 3.1 to Eq. (3.7). The data points follow a 

linear trend, which indicates that the Weibull distribution provides a good fit. The 

following constants were obtained from the curve fit:

β = 0.858

q = 0.405

In order to compute the lading loss probability for a jacketed shell, the combined 

puncture resistance index as a function of shell thickness was inferred from Eq. (3.5). 

These IR values were substituted into Eq. (3.6) to obtain the cumulative probability of the 

puncture intensity, F. Note that the probability of lading loss = 1 – F.

Figure 3.6 compares the predicted and actual lading loss probabilities for jacketed shells. 

Note the value of n was chosen such that the prediction would match the curve inferred 

from the regression analysis of accident data.

The behavior of tank car heads during accidents is clearly different than for shells, as Figs. 

3.2 and 3.4 illustrate. Heads and shells exhibit a different thickness dependence, and the 

relative benefits of a jacket are much greater for a head than for a shell. Given the simple 

model for the shell outlined above, there are two ways to handle the head:

1. Assume the same thickness dependence for IR in both the head and shell, and infer

the puncture intensity distribution for the head.

2. Assume the same puncture intensity distribution for the head and shell and infer IR

versus thickness for the head.

The first approach is not consistent with the observed trends. For example, the behavior 

of jacketed heads cannot be explained in terms of a different distribution of puncture 

intensity. Heads and shells definitely exhibit different relationships between puncture 

resistance and thickness. Some might quibble with the assumption that heads and shells 

are subject to identical populations of impact events, but we believe that this assumption 

is a reasonable approximation of reality. Overall, the rate of head and shell punctures are 

comparable in cars that do not have head shields. If there was a systematic difference 

between impact events for heads and shells, we would expect to see significantly more 

losses in one than the other.

Figure 3.7 compares the puncture resistance index of heads and shells based on 

Assumption #2 above. The IR values for the shell were computed from Eq. (3.3) 

assuming n = 0.95. The head puncture resistance was inferred from the lading loss 

probabilities in Fig. 3.2 along with Eq. (3.6). The data point for the thickness of 0.112 

inch corresponds to the jacket puncture resistance on the head. This data point was 

inferred from the analysis described below.

The inferred puncture resistance for a tank car head does not follow a simple power-law 

dependence on thickness, as Fig 3.7 indicates. However, it is still possible to predict the 
39

relative effect of head shields and jackets. For example, when the head and head shield 

are separated by a layer of insulation, they should behave independently of one another, 

in which case the total puncture resistance is additive:

Rto( t) Rhea ( d ) R(shield )

I = + I I (3.8)

At the other extreme, suppose that the head shield is completely fused to the head, such 

that the head is now thicker by 0.5 inch. In this case, the head and head shield are 

completely interdependent, and the puncture resistance corresponds to that of the 

combined thickness:

( )

I

Rtot = + I R (t t head shield ) (3.9)

Equations (3.8) and (3.9) are generalizations of Eqs. (3.5) and (3.4), respectively.

Figure 3.8 shows the actual and predicted lading loss for heads with head shields or 

jackets. In jacketed cars with head shields, there is a standoff between the head and head 

shield. In this case the head and head shield appear to behave independently, and Eq. 

(3.8) accurately predicts the puncture resistance. In non-jacketed cars where the head 

shield is flush against the head, the behavior falls somewhere between independent and 

completely interdependent (Eqs. (3.8) and (3.9), respectively). There is definitely some 

interaction between the head and head shield in this case, but the performance in an 

accident is slightly better than would be achieved by increasing the head thickness by 0.5 

inch. 

When the head is protected by a thin jacket and a layer of insulation, there is a significant 

improvement in puncture resistance. A puncture resistance index of 0.49 was inferred for 

the jacket head using Eq. (3.8). This value is plotted on Fig. 3.7

This model can be used to predict the impact of proposed tank car design changes. For 

example, the proposed 600-lb chlorine car has a shell thickness of 0.981 inch and a head 

thickness of 1.136 inches. The current nominal shell and head thicknesses in chlorine 

cars is 0.777 and 0.81 inch, respectively. Both car designs are jacketed and insulated, but 

the proposed design includes a 0.5-inch head shield. Using the above model and 

regression fits, the current chlorine car design has a lading loss probability of 1.9% due to 

shell puncture and 2.5% due to head puncture. This translates to 19 shell punctures and 

25 head punctures for every 1000 cars involved in a mainline accident, or a total of 44 

punctures per 1000 cars. The proposed design modification would reduce this number to 

12 punctures per 1000 cars, which is a 73% decrease. However, improving the material 

properties can have an even greater effect than increasing thicknesses. Suppose, for 

example, that improved upper shelf toughness in the next generation of tank car steels 

results in a doubling of the puncture resistance index. That is, assume that the puncture 

energy for a given tank car geometry doubles compared to traditional tank car steels. 

Given the current chlorine car design, the predicted number of punctures per 1000 cars 

involved in a mainline accident would decrease from 44 to 2, which is a 95% reduction.

If the improved material properties are combined with the proposed design modification, 

the number of predicted punctures would decrease to 2 per 10,000 cars.
40

Shell Loss in Mainline Accidents

Assumed Jacket Thickness = 0.1196"

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

0 0.2 0.4 0.6 0.8 1 1.2

Total Thickness (Excluding Insulation), inches

Lading Loss Probability

Non-Jacketed

Jacketed

Predicted Jacket,

n = 0.95

FIGURE 3.6 Prediction of the effects of a jacket on lading loss through the shell. Data taken from RSI-AAR Report RA-05-02 [16].
41

0

0.5

1

1.5

2

2.5

0 0.2 0.4 0.6 0.8 1 1.2

Thickness, inches

Puncture Resistance Index

Shell, n = 0.95

Head (Inferred)

FIGURE 3.7 Puncture resistance index versus thickness for heads and shells.
42

Head Loss in Mainline Accidents

Assumed Head Shield Thickness = 0.5"

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

9.00%

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Total Thickness (Excluding Insulation), inches

Lading Loss Probability

No Head Shield

With Head Shield

Head Shield + Insulation

No Head Shield + Jacket

Predicted Head Shield + Insul.

Predicted Jacket

FIGURE 3.8 Predicted effect of head shields and jackets on lading loss through heads. Data taken from RSI-AAR Report RA-05-02 [16].
43

4 DYNAMIC COLLISION SIMULATION

During the Minot investigation, the present authors performed a series of computer 

simulations that were geared toward understanding the relationship between material 

properties and catastrophic rupture of tank cars [11]. These analyses combined detailed

nonlinear dynamic collision simulation with a material model that incorporates ductile 

fracture. This work is summarized here because much of the computer modeling 

methodology developed in the Minot investigation can be used to study the effect of tank 

car design and material properties on puncture resistance.

4.1 Material Model for Ductile Fracture

The Gurson-Tvergaard model [17-20] simulates void growth and ductile fracture through 

a strain-softening constitutive law. Strain softening is captured through a void volume 

fraction, which increases with plastic flow. Fracture occurs when the void volume 

fraction reaches a critical value. This material model is implemented in some commercial 

finite element codes, including ABAQUS Explicit and LS-DYNA, both of which were 

used in the Minot investigation.

The Gurson-Tvergaard yield condition is given by:

( )

2

2

1 2 3

3

2 cosh 1 0

2 y y

q p

q f q q f

s s

   

Φ =   +   − − + =  

   

(4.1)

where q is the effective Mises stress, p is the hydrostatic pressure, σy is the yield stress of 

the fully dense material, q1, q2, q3 are porosity material parameters, and f is the void 

fraction.

The void growth and void nucleation rate gives the total change in the void volume 

fraction, f

&

:

gr nucl f = + f f & & & (4.2)

where gr f

&

 is from the existing void growth, and nucl f

&

 is from the nucleation of new voids. 

The growth of existing voids is given by:

(1 )

pl

gr f f = − e

&

& (4.3)

and the growth of new voids due to nucleation is given by:
44

2

1

exp

2 2

pl

nucl m

pl

N m N

N N

f A

f

A

s s

e

e e

p

=

    −

= −         

& &

(4.4)

The nucleation strain is assumed to follow a normal distribution with a mean value of εN, 

and a standard deviation sN. fN is the void volume fraction of the new voids; which are 

nucleated only in tension. 

For a numerical analysis, the initial void volume fraction, f0, is defined for the material. 

The porous failure criteria is given by the critical void volume fraction, fc. When cf f ≥

at all the material points (integration points) of a finite element, the stress carrying 

capacity of the material is reduced to zero and the finite element is removed from the 

model. The progressive failure of elements results in crack growth across the mesh. 

4.2 Calibration of Material Model with Charpy Impact Tests

In order to apply the Gurson-Tvergaard model to a particular problem, the model must 

first be calibrated to experimental results. In this instance, we chose to calibrate the 

material model to Charpy impact results. A series of finite element simulation of Charpy

tests were performed, and the material model was adjusted to achieve various values of 

absorbed energy.

Figure 4.1 shows the finite element model used for Charpy simulations, which were 

performed with ABAQUS Explicit. The anvil and striker were treated as contact surfaces, 

so the specimen is free to move relative to the test machine during fracture. The initial 

velocity of the striker was 235.9 in/sec (13.4 mph), which is equivalent to being dropped 

from a height of 6 ft. The velocity of the striker decreased as it imparted its kinetic 

energy to the specimen. This effect is handled automatically in the analysis through 

energy conservation. The weight of the striker was 49.15 lb, so the total available energy 

was 295 ft-lb. The fracture energy is equal to the total internal energy absorbed by the 

specimen. This quantity is output by ABAQUS Explicit.
45

X

Y

Z

FIGURE 4.1 Finite element model for simulation of the Charpy test.

The stress-strain curve used in the analysis is shown in Fig. 4.2 and Table 4.1. This curve 

is representative of TC 128 B steel at 37oF, which is the estimated metal temperature at 

the time of the Minot derailment. The following Gurson parameters were assumed, based 

on the published literature:

Gurson parameter q1 = 1.81

Gurson parameter q2 = 0.82

Gurson parameter q3 = 3.2761

Nucleation strain mean value εN = 0.30

Nucleation strain standard deviation sN = 0.10

Void nucleation initial void volume fraction fN = f0

Critical void fracture fc = 0.15

The initial void fraction, fo, was used as a fitting parameter in the model

Figure 4.3 is a plot of absorbed energy versus initial porosity. It was decided to perform 

the full-scale collision simulations with a Charpy energy of 100 ft-lb, which corresponds 

to an initial porosity of 0.0144. Figure 4.4 shows the specimen near the end of the test 

for a 100 ft-lb material.
46

FIGURE 4.2 Stress-strain curve used for all finite element analyses.

TABLE 4.1

Tabular TC128B stress-strain curve values (37oF)

Point No. Plastic Strain (in/in) True Stress (ksi)

1 0.00E+00 56.6

2 4.37E-03 57.9

3 1.37E-02 69.2

4 3.22E-02 83.4

5 5.69E-02 94.3

6 9.26E-02 102.0

7 1.36E-01 107.0

8 5.96E-01 124.0

The material parameters determined from the Charpy simulation cannot be used directly 

in a full-scale simulation. The appropriate material parameters for a given toughness 

value are mesh sensitive. That is, the results change as the element size changes. The 

reason for this is that fracture in real materials is governed by microstructural length 

scales such as grain size and inclusion spacing. Finite element analysis is based on 

continuum theory, so the element size becomes the de facto material length scale.
47

Charpy bar total absorbed energy vs. initial porosity for 

Gurson material

0

20

40

60

80

100

120

140

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

initial porosity, f_0

Absorbed Energy (ft*lb)

Charpy energy from analysis (ft*lb) Target Charpy energy (ft*lb)

FIGURE 4.3 Effect of initial porosity on Charpy energy. Element size = 0.01 inch.

The simulation of tank car failures used shell elements in the collision zone with a 2-inch 

length in each direction in the plane of the tank wall. The Charpy simulation used 0.01-

inch elements in the fracture zone. Refinement of the full-scale tank car to the level of 

the Charpy model is impossible with existing computational resources. Consequently, 

the material parameters for a 100 ft-lb steel had to be adjusted for the 2-inch element size. 

This was accomplished by gradually increasing element size in a benchmark problem and 

re-calibrating the material model at each step.

4.3 Full-Scale Simulation of Tank Car Collisions and Rupture

A series of tank car impact analyses were performed to analyze the conditions for which 

a puncture or rupture response is obtained. The tank car model used in these analyses 

was based on a previous finite element model of a DOT 112A340W pressure tank car 

was generated to analyze the loads and stresses in the tank car as a result of service and 

salvage operating conditions [21-23]. The LS-DYNA finite element code was used for 

the tank car modeling [24]. LS-DYNA is developed and maintained by the Livermore 

Software Technology Corporation (LSTC). LS-DYNA is an explicit nonlinear three-
48

dimensional finite element code for analyzing the large deformation dynamic response of 

solids and structures. It has many features ideally suited to analysis of vehicle collisions. 

As a result, LS-DYNA is widely used and well accepted in the crashworthiness 

community as a state-of-the-art code. Equipment manufacturers commonly use LSDYNA in the design of passenger rail car and automotive crash safety. The model for the 

tank car was developed using the TrueGrid preprocessor code [25]. 

FIGURE 4.4 Simulated Charpy test on a 100 ft-lb material.

Two external views of the original DOT 112A340W tank car model are shown in Fig. 4.5. 

The structure includes the tank with ellipsoidal heads, manway, stub sill, bolster, and 

bogie structures. The geometry of the tank car structures in the model were based on a 

design originally developed by Union Tank Car. Figure 4.5(b) gives a detailed view of 

the original model car end structures and the associated model mesh resolution.

For the impact analyses described here, the model was modified to include greater 

fidelity in the modeling of the draft gear and stub sill geometry as well as improved mesh 

refinement. In addition, the tank wall thickness was modified to 0.6875 inch, 

corresponding to the values measured and reported in the NTSB Materials Laboratory 

Factual Report [2]. The external insulation and jacket were not included in the model. 

The stub sill geometry was also modeled in greater detail to allow for the inclusion of a 
49

model for the coupler and draft gear. The final modification made to the model was to 

significantly increase the mesh resolution in the impact zone. The model was refined to 

have approximately 2 inch elements in the impact zone to resolve the damage 

distributions caused by impact.

(a) Tank car model (b) Detail of the tank car mesh

FIGURE 4.5 Original model generated for a 112A340W pressure tank car.

A 55 psi pressure was applied on the inside of the tank to model the pressure stresses 

from the anhydrous ammonia at 37oF. The mass of the lading was included in the tank 

car model using an increased mass of the tank shell. The inertial effects of the lading 

were important for developing the full collision forces and resulting motions of the 

vehicles in the simulations. Gravitational accelerations are also significant for the 

collision behavior and were included in the simulations. The collision analyses were 

used to investigate the impact conditions that result in either a puncture or an unstable 

tank rupture. Different impact scenarios and speeds were used that are representative of 

the conditions expected from derailment kinematics analyses performed as part of the 

Minot Investigation. Two simulations are described here that are representative of the 

impact behaviors. 

The overall impact orientation used for these example impact simulations is shown in Fig. 

4.6. Two derailed tank cars are resting on their sides with the primary target tank car 

oriented at 40 degrees from normal to the original direction of travel. The second target 

tank car behind the target has an increased mass to be more representative of a set of 

equipment stacked behind the target car. The mass increase is representative of a car that 

is between 3 and 4 times the weight of a single car. Similarly, a pair of coupled tank cars 

is used as the impactor (bullet cars). Again, the trailing bullet car has an increased mass 

(3-4 X) to provide some of the inertial effects of the train cars behind the derailment. 

The calculated impact response for the above impact scenario and an impact speed of 25 

mph is shown in Fig. 4.7. The impact behavior results in a puncture of the target tank car 

by the impact of the coupler and stub sill on the side wall. The subsequent blunt impact 

by the bullet tank car head on the target tank pushes the target tank cars out of the path of 

the bullet cars. A more detailed view of the calculated impact damage (puncture) to the 

target tank is shown in Fig. 4.8.
50

FIGURE 4.6 Impact scenario used to investigate tank car response.

The corresponding calculated impact response for the above impact scenario with an 

increased impact speed of 30 mph is shown in Fig. 4.9. The impact behavior results in a 

rupture behavior of the tank where a fracture propagates around the circumference of the 

tank and the end of the tank and tank head are removed as a couple of large debris 

fragments. The fracture propagates from the site of the coupler head impact and puncture 

of the tank wall in the early stages of the impact response. A more detailed view of the 

damage to the tank during the rupture response is shown in Fig. 4.10.

During the inspection of some of the recovered tank car debris by the various parties 

involved in the Minot investigation, a concern was raised that there appeared to be an 

absence of massive collision/derailment damage in the immediate vicinity of some of the 

catastrophic ruptures. The implication was that the lack of denting or other collision 

damage was evidence of inferior material in the tank cars involved in the Minot incident. 

However, statements such as this were made without examining all of the remnants from 

a given tank car fracture. 
51

a) Initial Configuration

b) Impact Damage at 1.0 second (Punctured)

FIGURE 4.7. Impact response of the tank cars for a 30 mph impact.
52

FIGURE 4.8 Impact damage to the target tank car for the 25 mph impact.

We performed a tank impact and rupture analysis to demonstrate that observations of the 

presence or lack of collision damage on a single remnant can be misleading. The impact 

conditions were a side impact of two tank cars into two stationary tank cars. The outer 

tank cars are increased in weight to include inertial effects of multiple cars. The impact 

occurred near the center of the target tank at 20 degrees from normal as shown in Fig. 

4.11. The collision speed in this example was 25 mph and resulted in a catastrophic 

rupture. 

The calculated intermediate damage states at 0.35 seconds and 0.50 seconds are shown in 

Fig. 4.12. At 0.35 seconds the coupler head has punctured through the outer shell and by 

0.5 seconds the tank head of the bullet tank car has impacted the target car resulting in 

extensive impact damage. The subsequent catastrophic rupture behavior at a time of 1.0 

seconds is shown in Fig. 4.13. The rupture has two main circumferential fractures. The 

resulting major debris produced in the rupture are the large A-end and B-end sections 

and additional tank wall debris that is between 3 and 6 feet wide between the two 

circumferential fractures.
53

a) Initial Configuration

b) Impact damage at 0.86 second (Ruptured).

FIGURE 4.9 Impact response of the tank cars for a 30 mph impact.

The calculated final damage to one end of the tank car is shown in Fig. 4.14. The tank 

section has little residual evidence of the extensive impact damage in this section of the 

tank. Without gathering all of the debris from this tank and reconstructing the rupture 

process, much of the evidence of the original impact damage would be carried away by 

the central tank wall debris.
54

FIGURE 4.10 Impact damage to the target tank car for the 30 mph impact.

FIGURE 4.11 Impact scenario for the tank car impact and rupture analysis.
55

FIGURE 4.12 Calculated intermediate impact damage states 

(25 mph – Middle impact – 100 ft-lb shell material).

FIGURE 4.13 Calculated tank shell rupture response 

(25 mph – Middle impact – 100 ft-lb shell material).

The computational procedures described in this section will need to be modified to be 

applied to a study on puncture resistance. The mesh will need to be significantly refined 

in the impact zone in order to model puncture with sufficient resolution. The models 
56

used in the Minot analysis had relatively coarse meshes because we were analyzing 

catastrophic rupture, and the initial puncture event was less important. Although a 

puncture study will require significantly more local mesh refinement, it will not be 

necessary to model detailed collision scenarios with multiple tank cars. For example, 

puncture by a coupler can be addressed with a model of the target car and the impacting 

coupler. The mass of the cars impacting the target can be incorporated into the coupler.

FIGURE 4.14 Residual tank section with minimal evidence of impact damage 

(25 mph – Middle impact – 100 ft-lb shell material).
57

5 DYNAMIC PUNCTURE SIMULATION

The computational methods described in the previous chapter can be used to study 

puncture resistance, provided some modifications are made. The models shown in 

Chapter 4 were optimized to study catastrophic rupture due to collision forces that were 

likely present at the Minot derailment. In a puncture study, the goal would be to quantify 

the relative effect of variables such as wall thickness and material toughness on puncture 

resistance.

An earlier study [26] attempted to evaluate puncture resistance using finite element 

analysis. This study was of limited value because the finite element analyses were twodimensional, quasi-static, and assumed a very simplistic material failure criterion. 

Nevertheless, these analyses predict that puncture resistance should increase with 

thickness, which is broadly consistent with the trends shown in Chapter 3.

A major advantage of the analysis approach described in Chapter 4 is that the material 

model can quantify the effect of upper-shelf toughness on puncture resistance. Full-scale 

dynamic simulation of tank car punctures is beyond the scope of the present study, but 

should be undertaken in a follow-up phase. Some preliminary results from small-scale 

models are presented below.

Standard test methods to quantify puncture resistance of a tank car do not exist at present, 

so two candidate experiments are considered here. In the first example, an unnotched 

rectangular bar is struck by a pendulum. The second experiment involves a cylindrical 

bar with a rounded tip that pierces a plate that is clamped on its edges.

5.1 Charpy Calibration

The Gurson-Tvergaard material model, which is described in Section 4.1 above, was 

calibrated to Charpy impact toughness, as was the case in the Minot analysis. In this case, 

however, the element size was fixed at 0.0394 inch (1 mm) so that the material model did 

not have to be re-calibrated for difference element sizes. All analyses in this Chapter

used the same element size in the fracture zone.

Figure 5.1 shows the finite element model for the Charpy simulation. The same material 

properties were used in the present study as were used in the analysis described in 

Chapter 4. Figure 5.2 is a plot of initial porosity versus energy absorbed. This 

calibration differs slightly from Fig. 4.3 because of different element sizes on the notch 

plane.
58

FIGURE 5.1 Charpy simulation with 0.0394-inch (1 mm) elements on the notch plane.

Charpy V-Notch Specimen with Gurson-Tvergaard Material Model

Element Size = 0.0394 in (1 mm)

0

50

100

150

200

250

300

350

400

450

500

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Initial Porosity (fo)

Absorbed Energy, ft-lb

FIGURE 5.2 Calibration of Charpy energy with initial porosity.
59

5.2 Fracture Simulation of Unnotched Bars

An overall view of an impact test on an unnotched bar is shown in Figure 5.3. The bar is 

12-inches long and fixed at both ends. It is impacted with a Charpy striker, and the 

energy absorbed is computed. This experiment could not be performed in a standard 

Charpy machine because there is not sufficient energy available to break the sample. For 

example, refer to Fig. 2.23, which is a photograph of two unnotched Charpy specimens 

that failed to break in a 300 ft-lb machine.

Three bar sizes were considered, which are shown in Figs 5.4 to 5.6. The baseline 

geometry has a 0.394 x 0.394-inch (10 x 10 mm) square cross section, which is the same 

as an unnotched Charpy specimen. Specimens with reduced thickness were also 

considered. Figures 5.5 and 5.6 show specimens with 70% and 50% of the baseline 

thickness, respectively. The energy required to fracture these bars were computed at 

various initial porosity values, which correspond to specific Charpy toughness values.

A test such as this, whether it is a computer simulation or an actual experiment, is merely 

qualitative. However, it can be used to assess relative trends. For example, assume the 

fracture energy exhibits a power-law dependence on thickness:

n E t = l (5.1)

It should be possible to measure the exponent n by varying specimen thickness. Recall 

Section 3.2, where an n value of 0.95 for shell puncture resistance was inferred from the 

accident database.

Figure 5.7 is a plot of fracture energy versus thickness on a logarithmic scale. The 

computed n values range from 0.89 to 1.0, which is consistent with the value of 0.95 

inferred from the accident database for shell punctures.

The relative effect of toughness on puncture resistance can also be inferred from 

qualitative experiments. Let us assume a different power-law relationship between 

fracture energy in the unnotched bar and upper-shelf Charpy energy:

( )

m

E = g CVN (5.2)

Figure 5.8 is a plot of fracture energy in the unnotched bar versus absorbed energy in 

CVN specimens with the same initial porosity. The exponent m is approximately 0.5 in 

this case. Therefore, if these trends translate to tank cars, it will take a four-fold increase 

in upper-shelf toughness to double the puncture resistance. Such an increase in toughness 

is achievable with sufficient reductions in sulfur content in conjunction with sulfide shape 

control (Chapter 2).
60

FIGURE 5.3 Impact test on a 12-inch long unnotched bar using a Charpy striker.

FIGURE 5.4 Full-size specimen with a square cross section.
61

FIGURE 5.5 Bar thickness reduced to 70% of the baseline size.

FIGURE 5.6 Bar thickness reduced to 50% of the baseline size.
62

100

1000

0.1 1

30 ft-lb

48 ft-lb

59 ft-lb

75 ft-lb

Thickness, inches

n = 1.0

n = 0.91

n = 0.89

n = 0.90

E = λ tn

CVN Energy:

Fracture Energy in Unnotched Bar, ft-lb

FIGURE 5.7. Relationship between fracture energy in the unnoched bar and thickness.
63

10

100

1000

10 100

Full Thickness

70% Thickness

50% Thickness

Fracture Energy in Unnotched Bar, ft-lb

CVN Energy, ft-lb

m = 0.43

m = 0.56

m = 0.49

E = γ (CVN)m

FIGURE 5.8. Relationship between fracture energy in the unnoched bar and Charpy energy.

5.3 Puncture of a Flat Plate

The configuration for the simulated puncture test on flat plates is shown in Figures 5.9 

and 5.10. A 12-inch square plate is clamped around the edges, and a 1-inch diameter bar 

with a rounded end impacts the plate at 30 mph. The indenter was modeled with 

sufficient mass to puncture the plates. Puncture energy was measured as a function of 

plate thickness and initial porosity. The latter quantity was calibrated to Charpy energy, 

as shown in Fig. 5.2.

Figure 5.11 shows typical output from a simulated puncture analysis. At time = 0, the 

indenter contacts the plate and begins to impart its kinetic energy. The internal energy in 

the plate increases until the round indenter bar pierces through the plate, at which point 
64

the internal energy reaches a plateau. This plateau represents the energy absorbed by the 

plate during puncture. Note that the indenter velocity decreases as it loses kinetic energy.

Figure 5.12 shows the plate puncture model at various time intervals. This particular run 

assumed an initial porosity of 0.0075, which corresponds to a Charpy energy of 461 ft-lb. 

While such a toughness is unrealistic for steels, these results help to illustrate a 

phenomenon that was apparent to a lesser degree in simulations of lower toughness 

materials. Namely, the material at the puncture location necks (i.e., thins) considerably. 

This behavior is not representative of tank car punctures that occur during accidents. 

This puncture simulation differs from a tank car puncture in two important respects:

• The plate is highly constrained, so it cannot bend significantly inward.

• The indenter size is on the order of the plate thickness, while the cross section of a 

coupler is an order of magnitude greater than plate thickness.

Both of these factors likely contribute to the observed necking in the simulated smallscale puncture test. The above limitations could be overcome with a wider plate and a 

larger indenter, but such a test would be cost prohibitive for routine material 

characterization.

Figure 5.13 is a plot of absorbed energy versus plate thickness in the simulated puncture 

test. The trend is approximately linear over the range of thicknesses considered, but the 

line does not pass through the origin.

Figure 5.14 shows the relationship between absorbed energy in the puncture test and 

absorbed energy in a Charpy test. The curve appears to be asymptotically approaching a 

maximum puncture energy. This trend can be explained by the observed necking 

behavior, as discussed below.

Figure 5.15 is a schematic illustration of tensile tests on two materials that have similar 

stress-strain curves but differing ductility. Material B fractures after more reduction in 

area than Material A. Note that both materials have similar elongation at fracture despite 

significantly different true fracture strains. The total energy absorbed by a tensile 

specimen is proportional to the area under the engineering stress versus elongation curve. 

There would be little difference in the measured energy to fracture in the two materials 

because the deformation prior to fracture is concentrated in a small volume. In a similar 

manner, the puncture energy in the small-scale test is insensitive to material toughness 

when significant local necking occurs.

Unfortunately, there appears to be no small scale laboratory puncture experiment that is 

truly representative of a typical tank car puncture. Even with a 1-inch diameter indenter,

estimated puncture energies are on the order of 10,000 ft-lb, which would require a fairly 

large test rig. Performing larger-scale puncture tests with an indenter that is comparable 

in size to a coupler would probably be cost prohibitive.
65

FIGURE 5.9 Model of a clamped plate with a 1-inch diameter indenter
66

FIGURE 5.10 Half-symmetric model, which slows the finite element mesh.

0.00E+00

5.00E+03

1.00E+04

1.50E+04

2.00E+04

2.50E+04

3.00E+04

3.50E+04

4.00E+04

4.50E+04

0.00E+00 5.00E-03 1.00E-02 1.50E-02 2.00E-02

Time, seconds

Energy, ft-lb

Kinetic Energy

Internal Energy

Puncture

Penetrator Velocity

0

5

10

15

20

25

30

35

0.00E+00 5.00E-03 1.00E-02 1.50E-02 2.00E-02

Time, seconds

Velocity, miles/hr

FIGURE 5.11 Typical results from the puncture simulation of a flat plate. Once the indenter pierces 

the plate, the internal energy (i.e., the energy absorbed by the plate) remains constant.
67

 

 

FIGURE 5.12 Simulated puncture test on a material with very high toughness. Note the significant necking at the puncture.
68

Simulated Puncture Test on Clamped Plate

CVN Energy = 48 ft-lb

0

2000

4000

6000

8000

10000

12000

14000

16000

18000

0 0.2 0.4 0.6 0.8 1 1.2

Plate Thickness, inches

Puncture Energy, ft-lb

FIGURE 5.13 Puncture energy versus plate thickness in the simulated tests on clamped plates.
69

Simulated Puncture Test on Clamped Plate

5/8-inch Thick Plate

0

2000

4000

6000

8000

10000

12000

0 50 100 150 200 250 300 350 400 450 500

Charpy Energy, ft-lb

Puncture Energy, ft-lb

FIGURE 5.14 Puncture energy versus Charpy energy in the simulated tests on clamped plates.
70

Necking

MaterialA Material B

X

Engineering

Stress

Elongation

X

True

Stress

True Strain

X

X

MaterialA

Material B

FIGURE 5.15 Schematic comparison of two materials with similar stress-strain behavior but 

differing ductility. The total energy absorbed by the two tensile specimens, which is proportional to 

the area under the engineering stress versus elongation curve, is similar despite the difference in the 

true stress-strain curves.

Impact testing of unnotched bars (Section 5.2) may be the best available alternative. 

Although this is not a true puncture test, it does provide information on fracture energy in 

the absence of a notch. At the very least, this test should be useful in validating the 

material model. If the Gurson-Tvergaard model can predict the fracture energy of both 

notched and unnotched specimens, it should produce realistic results in full-scale tank car 

puncture simulations.
71

6 CONCLUSIONS AND RECOMMENDATIONS

Lading loss through the head or shell of a tank car occurs through a ductile puncture 

mechanism in the vast majority of cases. Even when brittle fracture occurs in a tank car 

during an accident, it initiates at a notch-like feature. In the absence of a pre-existing 

notch, the tank car must first experience a ductile puncture before brittle crack 

propagation is possible. Although previous efforts to improve tank car steels have 

focused on low temperature toughness properties, the accident data indicates that the 

current focus should be on upper shelf toughness. There are relatively few brittle failures 

in older tank cars, and the problem of brittle fracture is essentially non-existent in 

normalized tank cars built after 1989. We recommend that a next-generation tank car 

steel specification be developed that incorporates very low sulfur allowances and sulfide 

shape control. We do not recommend an accelerated program to replace pre-1989 tank 

cars with cars made from the current generation of tank car steels.

A model calibrated from the accident database can be used to quantify the effect of 

design modifications and material properties on puncture resistance. The model and the 

database indicate that existing chlorine cars will experience a combined total of 44 

punctures through the head and shell for every 1000 cars that are involved in an accident. 

If the proposed 600-lb car is adopted for chlorine transportation, but without 

improvements in steel properties, the number of expected punctures decreases to 12 per 

1000 cars. On the other hand, if the chlorine car design remains the same and a new 

generation of steel with double the puncture resistance is adopted, the number of 

expected punctures decreases from 44 to 2 out of 1000 cars. If both the new steel and 

600-lb car design are adopted, the predicted number of punctures is only 2 in 10,000.

Preliminary computer simulation indicates that a small-scale puncture experiment may

not produce meaningful results due to local necking effects. A pendulum impact test on 

unnotched bars may be a reasonable alternative. At the very least, this test will be useful 

for validating the material model to be used in full-scale simulations of puncture in tank 

cars.

Recommendations for future work include:

• A feasibility study for C-Mn and microalloyed steels with low sulfur and sulfide 

shape control. This study would consist of experimental work as well as a 

cost/availability assessment of candidate steels. As many steel samples as is 

practical should be collected for ambient-temperature impact testing, tensile 

testing, fractography, and metallography. Such a study will quantify the 

relationship between upper-shelf toughness, chemical composition, processing, 

and microstructure. It will also indicate what toughness levels are attainable with 

economically viable steel specifications.
72

• Impact testing of unnotched bars to compare notched versus unnotched behavior, 

and to validate the material model for ductile fracture.

• Development of alternative tests for puncture resistance. Candidate tests should 

first be evaluated with dynamic finite element simulation. The most promising 

test method(s) could then be applied to real materials.

• Full-scale simulations of tank car impacts and punctures. Key parameters to be 

studied include wall thickness and material toughness. The effect of jackets, head 

shields, crumple zones, and other potential design features should also be 

evaluated.

• Development of a performance standard for puncture resistance.
73

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