Tag Archives: corrosion

Preventing corrosion in oil pipelines at the nanoscale

A June 7, 2019 news item on Azonano announces research into the process of oil pipeline corrosion at the nanoscale (Note: A link has been removed),

Steel pipes tend to rust and sooner or later fail. To anticipate disasters, oil companies and others have developed computer models to foretell when replacement is necessary. However, if the models themselves are incorrect, they can be amended only through experience, an expensive problem if detection happens too late.

Currently, scientists at Sandia National Laboratories, the Department of Energy’s Center for Integrated Nanotechnologies and the Aramco Research Center in Boston, have discovered that a specific form of nanoscale corrosion is responsible for suddenly diminishing the working life of steel pipes, according to a paper recently published in Nature’s Materials Degradation journal.

A June 6, 2019 Sandia National Laboratories news release (also on EurekAlert), which originated the news item, provides more technical detail,

Using transmission electron microscopes, which shoot electrons through targets to take pictures, the researchers were able to pin the root of the problem on a triple junction formed by a grain of cementite — a compound of carbon and iron — and two grains of ferrite, a type of iron. This junction forms frequently during most methods of fashioning steel pipe.

Iron atoms slip-sliding away

The researchers found that disorder in the atomic structure of those triple junctions made it easier for the corrosive solution to remove iron atoms along that interface.
In the experiment, the corrosive process stopped when the triple junction had been consumed by corrosion, but the crevice left behind allowed the corrosive solution to attack the interior of the steel.

“We thought of a possible solution for forming new pipe, based on changing the microstructure of the steel surface during forging, but it still needs to be tested and have a patent filed if it works,” said Sandia’s principle investigator Katherine Jungjohann, a paper author and lead microscopist. “But now we think we know where the major problem is.”

Aramco senior research scientist Steven Hayden added, “This was the world’s first real-time observation of nanoscale corrosion in a real-world material — carbon steel — which is the most prevalent type of steel used in infrastructure worldwide. Through it, we identified the types of interfaces and mechanisms that play a role in the initiation and progression of localized steel corrosion. The work is already being translated into models used to prevent corrosion-related catastrophes like infrastructure collapse and pipeline breaks.”

To mimic the chemical exposure of pipe in the field, where the expensive, delicate microscopes could not be moved, very thin pipe samples were exposed at Sandia to a variety of chemicals known to pass through oil pipelines.

Sandia researcher and paper author Khalid Hattar put a dry sample in a vacuum and used a transmission electron microscope to create maps of the steel grain types and their orientation, much as a pilot in a plane might use a camera to create area maps of farmland and roads, except that Hattar’s maps had approximately 6 nanometers resolution. (A nanometer is one-billionth of a meter.)

“By comparing these maps before and after the liquid corrosion experiments, a direct identification of the first phase that fell out of the samples could be identified, essentially identifying the weakest link in the internal microstructure,” Hattar said.

Sandia researcher and paper author Paul Kotula said, “The sample we analyzed was considered a low-carbon steel, but it has relatively high-carbon inclusions of cementite which are the sites of localized corrosion attacks.

“Our transmission electron microscopes were a key piece of this work, allowing us to image the sample, observe the corrosion process, and do microanalysis before and after the corrosion occurred to identify the part played by the ferrite and cementite grains and the corrosion product.”

When Hayden first started working in corrosion research, he said, “I was daunted at how complex and poorly understood corrosion is. This is largely because realistic experiments would involve observing complex materials like steel in liquid environments and with nanoscale resolution, and the technology to accomplish such a feat had only recently been developed and yet to be applied to corrosion. Now we are optimistic that further work at Sandia and the Center for Integrated Nanotechnologies will allow us to rethink manufacturing processes to minimize the expression of the susceptible nanostructures that render the steel vulnerable to accelerated decay mechanisms.”

Invisible path of localized corrosion

Localized corrosion is different from uniform corrosion. The latter occurs in bulk form and is highly predictable. The former is invisible, creating a pathway observable only at its endpoint and increasing bulk corrosion rates by making it easier for corrosion to spread.

“A better understanding of the mechanisms by which corrosion initiates and progresses at these types of interfaces in steel will be key to mitigating corrosion-related losses,” according to the paper.

Here’s a link to and a citation for the paper,

Localized corrosion of low-carbon steel at the nanoscale by Steven C. Hayden, Claire Chisholm, Rachael O. Grudt, Jeffery A. Aguiar, William M. Mook, Paul G. Kotula, Tatiana S. Pilyugina, Daniel C. Bufford, Khalid Hattar, Timothy J. Kucharski, Ihsan M. Taie, Michele L. Ostraat & Katherine L. Jungjohann. npj Materials Degradation volume 3, Article number: 17 (2019) DOI: https://doi.org/10.1038/s41529-019-0078-1 Published 12 April 2019

This paper is open access.

Artificial intelligence and industrial applications

This is take on artificial intelligence that I haven’t encountered before. Sean Captain’s Nov. 15, 2016 article for Fast Company profiles industry giant GE (General Electric) and its foray into that world (Note: Links have been removed),

When you hear the term “artificial intelligence,” you may think of tech giants Amazon, Google, IBM, Microsoft, or Facebook. Industrial powerhouse General Electric is now aiming to be included on that short list. It may not have a chipper digital assistant like Cortana or Alexa. It won’t sort through selfies, but it will look through X-rays. It won’t recommend movies, but it will suggest how to care for a diesel locomotive. Today, GE announced a pair of acquisitions and new services that will bring machine learning AI to the kinds of products it’s known for, including planes, trains, X-ray machines, and power plants.

The effort started in 2015 when GE announced Predix Cloud—an online platform to network and collect data from sensors on industrial machinery such as gas turbines or windmills. At the time, GE touted the benefits of using machine learning to find patterns in sensor data that could lead to energy savings or preventative maintenance before a breakdown. Predix Cloud opened up to customers in February [2016?], but GE is still building up the AI capabilities to fulfill the promise. “We were using machine learning, but I would call it in a custom way,” says Bill Ruh, GE’s chief digital officer and CEO of its GE Digital business (GE calls its division heads CEOs). “And we hadn’t gotten to a general-purpose framework in machine learning.”

Today [Nov. 15, 2016] GE revealed the purchase of two AI companies that Ruh says will get them there. Bit Stew Systems, founded in 2005, was already doing much of what Predix Cloud promises—collecting and analyzing sensor data from power utilities, oil and gas companies, aviation, and factories. (GE Ventures has funded the company.) Customers include BC Hydro, Pacific Gas & Electric, and Scottish & Southern Energy.

The second purchase, Wise.io is a less obvious purchase. Founded by astrophysics and AI experts using machine learning to study the heavens, the company reapplied the tech to streamlining a company’s customer support systems, picking up clients like Pinterest, Twilio, and TaskRabbit. GE believes the technology will transfer yet again, to managing industrial machines. “I think by the middle of next year we will have a full machine learning stack,” says Ruh.

Though young, Predix is growing fast, with 270 partner companies using the platform, according to GE, which expects revenue on software and services to grow over 25% this year, to more than $7 billion. Ruh calls Predix a “significant part” of that extra money. And he’s ready to brag, taking a jab at IBM Watson for being a “general-purpose” machine-learning provider without the deep knowledge of the industries it serves. “We have domain algorithms, on machine learning, that’ll know what a power plant is and all the depth of that, that a general-purpose machine learning will never really understand,” he says.

One especially dull-sounding new Predix service—Predictive Corrosion Management—touches on a very hot political issue: giant oil and gas pipeline projects. Over 400 people have been arrested in months of protests against the Dakota Access Pipeline, which would carry crude oil from North Dakota to Illinois. The issue is very complicated, but one concern of protestors is that a pipeline rupture would contaminate drinking water for the Standing Rock Sioux reservation.

“I think absolutely this is aimed at that problem. If you look at why pipelines spill, it’s corrosion,” says Ruh. “We believe that 10 years from now, we can detect a leak before it occurs and fix it before you see it happen.” Given how political battles over pipelines drag on, 10 years might not be so long to wait.

I recommend reading the article in its entirety if you have the time. And, for those of us in British Columbia, Canada, it was a surprise to see BC Hydro on the list of customers for one of GE’s new acquisitions. As well, that business about the pipelines hits home hard given the current debates (Enbridge Northern Gateway Pipelines) here. *ETA Dec. 27, 2016: This was originally edited just prior to publication to include information about the announcement by the Trudeau cabinet approving two pipelines for TransMountain  and Enbridge respectively while rejecting the Northern Gateway pipeline (Canadian Broadcasting Corporation [CBC] online news Nov. 29, 2016).  I trust this second edit will stick.*

It seems GE is splashing out in a big way. There’s a second piece on Fast Company, a Nov. 16, 2016 article by Sean Captain (again) this time featuring a chat between an engineer and a robotic power plant,

We are entering the era of talking machines—and it’s about more than just asking Amazon’s Alexa to turn down the music. General Electric has built a digital assistant into its cloud service for managing power plants, jet engines, locomotives, and the other heavy equipment it builds. Over the internet, an engineer can ask a machine—even one hundreds of miles away—how it’s doing and what it needs. …

Voice controls are built on top of GE’s Digital Twin program, which uses sensor readings from machinery to create virtual models in cyberspace. “That model is constantly getting a stream of data, both operational and environmental,” says Colin Parris, VP at GE Software Research. “So it’s adapting itself to that type of data.” The machines live virtual lives online, allowing engineers to see how efficiently each is running and if they are wearing down.

GE partnered with Microsoft on the interface, using the Bing Speech API (the same tech powering the Cortana digital assistant), with special training on key terms like “rotor.” The twin had little trouble understanding the Mandarin Chinese accent of Bo Yu, one of the researchers who built the system; nor did it stumble on Parris’s Trinidad accent. Digital Twin will also work with Microsoft’s HoloLens mixed reality goggles, allowing someone to step into a 3D image of the equipment.

I can’t help wondering if there are some jobs that were eliminated with this technology.

Studying corrosion from the other side

Corrosion can be beautiful as well as destructive,

Typically, the process of corrosion has been studied from the metal side of the equation - See more at: http://www.anl.gov/articles/core-corrosion#sthash.ZPqFF13I.dpuf. Courtesy of the Argonne National Laboratory

Typically, the process of corrosion has been studied from the metal side of the equation – See more at: http://www.anl.gov/articles/core-corrosion#sthash.ZPqFF13I.dpuf. Courtesy of the Argonne National Laboratory

A Feb. 18, 2014 news item on Nanowerk expands on the theme of corrosion as destruction (Note: Links have been removed),

Anyone who has ever owned a car in a snowy town – or a boat in a salty sea – can tell you just how expensive corrosion can be.

One of the world’s most common and costly chemical reactions, corrosion happens frequently at the boundaries between water and metal surfaces. In the past, the process of corrosion has mostly been studied from the metal side of the equation.

However, in a new study (“Chloride ions induce order-disorder transition at water-oxide interfaces”), scientists at the Center for Nanoscale Materials at the U.S. Department of Energy’s Argonne National Laboratory investigated the problem from the other side, looking at the dynamics of water containing dissolved ions located in the regions near a metal surface.

The Feb. 14, 2014 Argonne National Laboratory news release by Jared Sagoff, which originated the news item, describes how the scientists conducted their research,

A team of researchers led by Argonne materials scientist Subramanian Sankaranarayanan simulated the physical and chemical dynamics of dissolved ions in water at the atomic level as it corrodes metal oxide surfaces. “Water-based solutions behave quite differently near a metal or oxide surface than they do by themselves,” Sankaranarayanan said. “But just how the chemical ions in the water interact with a surface has been an area of intense debate.”

Under low-chlorine conditions, water tends to form two-dimensional ordered layers near solid interfaces because of the influence of its strong hydrogen bonds. However, the researchers found that increasing the proportion of chlorine ions above a certain threshold causes a change in which the solution loses its ordered nature near the surface and begins to act similar to water away from the surface. This transition, in turn, can increase the rate at which materials corrode as well as the freezing temperature of the solution.

This switch between an ordered and a disordered structure near the metal surface happens incredibly quickly, in just fractions of a nanosecond. The speed of the chemical reaction necessitates the use of high-performance computers like Argonne’s Blue/Gene Q supercomputer, Mira.

To further explore these electrochemical oxide interfaces with high-performance computers, Sankaranarayanan and his colleagues from Argonne, Harvard University and the University of Missouri have also been awarded 40 million processor-hours of time on Mira.

“Having the ability to look at these reactions in a more powerful simulation will give us the opportunity to make a more educated guess of the rates of corrosion for different scenarios,” Sankaranarayanan said. Such studies will open up for the first time fundamental studies of corrosion behavior and will allow scientists to tailor materials surfaces to improve the stability and lifetime of materials.

Here’s a link to and a citation for the paper,

Chloride ions induce order-disorder transition at water-oxide interfaces by Sanket Deshmukh, Ganesh Kamath, Shriram Ramanathan, and Subramanian K. R. S. Sankaranarayanan. Phys. Rev. E 88 (6), 062119 (2013) [5 pages]

This article is behind a paywall on both the primary site and the beta site (the American Physical Society is testing a new website for its publications).