Div. 8000 uses fuze expertise for Air Force ICBMs
by Holly Larsen
If the term “fuze” seems more prevalent around Sandia these days, it’s no accident. Technical staff and managers, systems engineers, flight test specialists, and project managers across the Labs are actively engaged in the Mark (Mk) 21 Fuze Replacement program for the W87 warhead on the US Air Force Minuteman III intercontinental ballistic missile (ICBM), an engineering development effort that promises to remain a key activity for Sandia’s nuclear weapons mission for years to come.
Mounted at the forward end of the warhead, the fuze tracks the path of the warhead and gives the signal to detonate. To fulfill this role, many intricate components must operate perfectly in challenging environments, which in turn calls for very careful engineering. Sandia has been providing such engineering for decades for the arming, fuzing, and firing (AF&F) sets of several US Navy submarine-launched ballistic missile warheads.
The Mk21 Fuze program — led by Dept. 8242 in California and drawing on extensive engineering from New Mexico teams in Divisions 2000 and 5000 — leverages and consolidates Sandia’s proficiency. “Sandia has provided fuzing systems for the Navy for more than 40 years,” says Curt Nilsen (8242), manager of the ICBM Fuze Systems Engineering Group. “We’re now proud to bring our expertise to the Air Force.”
Sandia’s long-standing and productive working relationship with the Navy was a strong factor in the Air Force selection of Sandia to design the replacement Mk21 fuzes. Contracting with Sandia also created the opportunity to gain efficiencies by leveraging commonalities between the Air Force and Navy fuzes through the W88 ALT 370 program.
“The two fuzes themselves won’t be identical, but several of the key components will be the same,” Curt says. “Other parts will use similar technologies, but will be modified to meet unique Air Force needs. Both the Navy and the Air Force have been actively supporting efforts to optimize this integration,” he adds.
Sandia started work on the project in November 2011 with the goal of creating the first production units in the early 2020s. Production is expected to continue through 2029.
The Sandia teams have been busy refining product requirements, creating and prototyping their designs, and planning for qualification. Still to come is more detailed component design that will further specify the form and function of elements — and show how these specifications allow the elements to meet all requirements. Qualification activities will demonstrate component and system performance and robustness and will include a series of system-level ground and flight tests.
Top-of-the-line program management
In embarking on the Mk21 project, Sandia and the Air Force recognized the challenges created by a decision to apply the NNSA Phase 6.X NW development process, rather than the Defense Acquisition Process (known as the DoD 5000 process) historically used by the Air Force.
“Both processes are thorough, but it isn’t possible to map every step in one process to a step in the other,” says Curt. “So to gain the customer’s confidence that Phase 6.X would fulfill the letter and spirit of DoD 5000 and ensure that all project requirements would be met, we knew top-of-the-line project management processes would be required.”
As a first step, project leaders built a team of technical project managers that included several hires with extensive DoD 5000 experience. Because of customer needs, leaders also decided to implement an earned-value management (EVM) system — a highly structured way to assess work completed and budget spent against a plan. They then fostered an environment that enabled the project managers to work as peers with their R&D counterparts in implementing EVM.
Curt says that EVM increases the rigor of project management and offers the team an accurate picture of the status of the project and progress against plans and budgets.
Coordination is key
The project relies heavily on teams from across all of Sandia. In broad strokes, Dept. 2135, led by Ron Franco, is responsible for engineering the fuze hardware, while Dept. 8242 is taking the lead on systems engineering, flight tests, and project management. All these activities must take place in tandem and drive toward the common goal of ensuring that the fuze meets all of its customer requirements, on time, and within budget.
Curt says the need for close coordination has required an extra emphasis on communications between the two sites, a message seconded by Ron. “This project is exceptional in bringing people together across the sites and ensuring that we are aware of the work of other teams and actively contributing across sites as needed,” he says.
Other key California organizations working on the project include W87 Systems Engineering (8231) and Telemetry and Stockpile Support (8135). Fuze component development is provided by Nuclear Weapon Arming & Fuzing Systems (5350), Firing & Embedded Systems (2620), Advanced Mechanical Design (2610), and Power Sources & Metrology (2540). Centers 1700, 1500, 1300, and 1800 also play important roles.
Maintaining a cutting-edge NW workforce
Besides extending Sandia’s fuze expertise to a new system, the Mk21 program is significant because it is one of three Sandia programs — along with the B61-12 Life Extension Program (LEP) and W88 Alteration (ALT) 370 effort — that are in “Phase 6.3” or full-scale engineering development.
Sandia activity in weapons modernization has not been this high since the early 1990s, a fact highlighted by Labs Director Paul Hommert in his testimony to the US House Armed Services Subcommittee on Strategic Forces, provided in October 2013.
Cutting-edge projects such as the Mk21 Fuze Replacement Program keep Sandia employees at the forefront of a wide range of technology advances, from electronics to environmental testing. The fuze project also gives employees opportunities to develop and work with hardware — work that many find deeply satisfying.
In testifying to the House subcommittee, Paul noted that 500 of Sandia’s new hires, many in the early stages of their careers, are working on new weapon projects. Said Paul: “The modernization program provides opportunities for these new technical staff to work closely with our experienced designers: from advanced concept development to component design and qualification, and ultimately to the production and fielding of nuclear weapon systems.”
In turn, this provides new technical staff with “the multiyear learning it takes to technically steward the nation’s nuclear stockpile now and into the future, after the modernized warheads are in the stockpile.”
Put simply, programs such as these are critical to building the skilled technical workforce Sandia needs to execute its mission and ensure an effective nuclear deterrent for decades to come.
-- Holly Larsen
Sandia researchers find clues to superbug evolution
by Patti Koning
Imagine going to the hospital with one disease and coming home with something much worse, or not coming home at all.
With the spread of antibiotic resistance, healthcare-associated infections have become a serious threat. In fact, on any given day about one in 25 hospital patients has at least one such infection and as many as one in nine of those die as a result, according to the Centers for Disease Control.
Consider Klebsiella pneumoniae, not typically a ferocious pathogen, but now armed with resistance to virtually all antibiotics in clinical use; it is the most common species of carbapenem-resistant Enterobacteriaceae (CRE) in the United States. Carbapenems are considered the antibiotic of last resort.
But there is hope — a team of Sandia microbiologists recently sequenced the entire genome of a Klebsiella pneumoniae strain encoding New Delhi Metallo-beta-lactamase (NDM-1), an enzyme that breaks down carbapenems and renders them ineffective.
CREs are a wholly different group of antibiotic-resistant bacteria than the better-known methicillin-resistant Staphylococcus aureus (MRSA). CREs are considered a “triple threat” because of their resistance to nearly all antibiotics, high mortality rates, and ability to spread their resistance to other bacteria.
Having sequenced the entire genome of the NDM-1 strain Klebsiella pneumoniae for the first time, the Sandia team of Corey Hudson (8623), Zach Bent (8623), Robert Meagher (8621) and Kelly Williams (8623) are beginning to understand the bacteria’s multifaceted mechanisms for resistance. They presented their findings in a paper recently published in PLOS One, “Resistance Determinants and Mobile Genetic Elements of an NDM-1 Encoding Klebsiella pneumoniae Strain.”
“Once we had the entire genome sequenced, it was a real eye-opener to see the concentration of so many antibiotic-resistant genes and so many different mechanisms for accumulating them,” says Kelly, a bioinformaticist. “Just sequencing this genome unlocked a vault of information about how genes move between bacteria and how DNA moves within the chromosome.”
Robert first worked with Klebsiella pneumoniae ATCC BAA-2146 (Kpn2146), the first US isolate found to encode NDM-1, last year. Along with E.coli, it was used to test an automatic DNA sequencing preparation platform for the RapTOR Grand Challenge, a project that developed techniques to allow discovery of pathogens in clinical samples.
“I’ve been interested in multi-drug resistant organisms for some time. The NDM-1 drug resistance trait is spreading rapidly worldwide, so there is a great need for diagnostic tools,” says Robert. “This particular strain of Klebsiella pneumoniae is fascinating and terrifying because it’s resistant to practically everything. Some of that you can explain on the basis on NDM-1, but it’s also resistant to other classes of antibiotics that NDM-1 has no bearing on.”
Unlocking Klebsiella pneumoniae
Assembling an entire genome is like putting together a puzzle. The researchers needed two genomic datasets, Illumina and Pacific Biosciences (PacBio), to assemble Klebsiella pneumoniae. The Illumina pair-end genomic sequence dataset, done at Sandia, provided accurate but short reads. The PacBio dataset contained much longer reads with less accuracy.
Klebsiella pneumoniae turned out to have one large chromosome and four plasmids, smaller DNA circles physically separate from and able to replicate independently of a cell’s chromosomal DNA. Plasmids often carry antibiotic-resistant genes and other defense mechanisms.
The researchers discovered that their Klebsiella pneumoniae bacteria encoded 34 separate enzymes of antibiotic resistance, as well as efflux pumps that move compounds out of cells and mutations in chromosomal genes that are expected to confer resistance.
“Each one of those genes has a story. How it got into this bacteria, where it has been, and how it has evolved,” says Kelly.
The researchers also identified several mechanisms that mobilize resistance genes: acquisition of plasmids and genomic islands; integron cassette swapping; transposition events from chromosome to plasmid and vice versa; and homologous recombination at high copy repeats.
Necessity leads to development of new tools
In the course of mapping out the many tricks and weapons of Klebsiella pneumoniae, the research team developed several new bioinformatics tools for identifying established mechanisms of genetic movement.
Kelly and Corey detected circular forms of transposons, or “jumping genes,” in movement, which has never before been shown this way, and discovered sites within the genome undergoing homologous recombination. By applying two existing bioinformatics methods for detecting genomic islands, they found a third class of islands that neither method alone could have detected.
“To some extent, every extra piece of DNA that a bacteria acquires comes at some cost, so the bacteria doesn’t usually hang onto traits it doesn’t need,” says Corey. “The further we dug down into the genome, the more stories we found about movement within the organism and from other organisms and the history of insults, like antibiotics, that it has faced. This particular bacteria is just getting nastier over time.”
Translating findings to diagnostics
The researchers are now applying their understanding of Klebsiella pneumoniae’s mechanisms of resistance and their new bioinformatics tools to develop diagnostic tools to detect bioengineering. Looking across 10 related but distinct strains of Klebsiella pneumoniae, they pinpointed regions that were new to their strain, and so indicate genetic movement.
“By studying the pattern of movement, we can better characterize a natural genomic island,” says Corey. “We are now using that knowledge to characterize unnatural islands, which would be an indication of bioengineering.”
The findings are also being applied to another Laboratory Directed Research and Development project led by Eric Carnes (8635) that is examining alternative approaches for treating drug resistant organisms. “Instead of traditional antibiotics, we use a sequence-based approach to silence expression of drug resistant genes,” explains Meagher.
The importance of this research can be summed up nicely by an oft-quoted line from Sun Tzu’s Art of War — know the enemy.
-- Patti Koning
Can there be too much data?
by Patti Koning
Knowledge is power, but too much knowledge — in the form of data — can be a bad thing. “More information doesn’t always lead to better decisions,” says Philip Kegelmeyer (8900). “In fact, sometimes the two can be anti-correlated.”
An expert in machine learning, Philip has spent a lot of time pondering dangers and opportunities in “big data” — essentially, large and complex data sets that can only be processed on a supercomputer. He’s given numerous presentations to answer questions related to the use of personal data to enhance national security data analysis.
“Does all that data make a difference? Is it worth the privacy concerns?” he asks. “Big data is tricky. It can help or hurt your analysis, depending on how you use it.”
To understand these issues, Philip says you first have to appreciate how data can influence, or fail to influence, human decision-making. “The leading theory in evolutionary psychology is that intelligence evolved to win arguments, not to arrive at the truth. So in a roomful of people, the opinion of the most charismatic person often wins out,” he says. “That’s fairly depressing, and a good argument for thinking carefully about how data and judgment interact.”
The base rate fallacy
One way data can lead us astray is the base rate fallacy — an error in thinking in which we fail to take into account how likely things are to happen, or not to happen.
Philip gives the example of a bozometer that can accurately detect bozos 99.99 percent of the time. “I point it at you and it says you are a bozo. But are you really? The very counterintuitive answer depends on who else I test. This is not solely about you and the accuracy of the instrument,” he says.
On a pre-selected group of 2,000, of whom 1,000 are known bozos, the device will accurately find 999 bozos with one false alarm. But add a lot of untargeted data — the rest of the US population of approximately 300 million people — and you now have 300,000 false alarms.
“If you know there are only about 2,000 bozos in the entire data set, 99.99 percent accuracy isn’t so great,” says Philip. “The chances that you are really a bozo become quite small. This is the danger of adding untargeted data to any analytic.”
Even an analytic with 99.999 percent accuracy would still turn up 30,000 false alarms. “So you either need an incredibly accurate analytic, or a situation in which a high false alarm rate is acceptable,” he says. “This can work in the medical community, when medical tests are given to a broad population to screen for critical conditions. In this situation, a high false alarm rate may be tolerable.”
On the flip side, extra untargeted data can fill in connections and help you understand the importance of those connections. Philip invents the example of Abe and Abigail, who are both people of interest and have both been seen in Damascus. With additional flight information, you’d learn that they both frequently fly into Yemen and their time in Damascus almost always overlaps by a day.
“Without broad data, that is all you have and those facts seem very suggestive,” Philip explains. “But if you look at the entire set of normal flight records for that region, you might learn, for example, that 80 percent of all travel to Yemen goes through Damascus, most of that travel requires an overnight stay for refueling, and that 90 percent of that travel happens in three months of the year. With this additional, non-specific data, the odds that any two random travelers to Yemen would be in Damascus at the same time go way up.”
This is an example of how large amounts of properly used data, even if the vast bulk of that data is about people who are not of security interest, can enhance national security data analysis. Such data, he explains, is useful in providing context for what is normal and what is truly unique, as in the case of Abe and Abigail’s travel patterns. “The human mind prefers simple stories. The value of bulk data is that it can tell us when the stories are too simple, when we should look deeper and not trust our first impressions,” he says.
Mining blog posts to predict violence
Philip led the 2008-2010 Networks Grand Challenge LDRD that demonstrates the power of big data. The project dug into the question of why certain events sparked violent protests. In 2005, the publication of editorial cartoons depicting the Islamic prophet Muhammad in the Danish newspaper Jyllands-Posten set off worldwide protests, violent demonstrations, and riots, which were blamed for the deaths of hundreds of people.
“This wasn’t the first or last time that these cartoons were published, so why such an extreme reaction that one time?” asks Philip. “We looked at blog postings and comments and how the information travels across the web and developed an algorithm that can predict, based on multilingual text analysis, if an event will spark deadly violence.”
The project took in a lot of data by continuously scanning blogs in multiple languages and analyzing the aggregated voluntarily public text for keywords, text clustering, and sentiment. “The prediction capability comes from looking at what is a ‘normal’ response to incendiary events in the news,” says Philip. “Our algorithm can tell us if the response will lead to violence, but it can’t tell us when, where, or by whom that violence will occur.”
Can you trust your data?
Philip has a complicated relationship with data — he doesn’t always trust it. “People can fall in love with their data, to the point that they are blind to the idea that an adversary can manipulate data,” he says.
He cites a major metropolitan police department that implemented a computer-based system to assign police officers to the neighborhoods with the most illegal drug activity. A college student arrested for possession of marijuana might not trigger an increase in police presence, but violence among cocaine dealers would. The program worked great, until police officers began seeing disparities between the computer program’s assessment of the neighborhoods and what they saw on the streets.
It turned out that a drug gang had started bribing a data entry clerk in the police department, a scheme that went undetected for a year before the gang got too ambitious. At first the clerk only flagged the arrests of the gang doing the bribing as less violent, but eventually they had the clerk flag the arrests of a rival gang as more violent.
So it soon all unraveled on the witness stand. “And it’s not like the tampering was subtle,” explains Philip. “They were able to track the problems with the data back to the very day the bribery started.”
Unfortunately, adversaries also have far more sophisticated methods of sapping or suborning the critical use of data analytics on which many research institutions, government agencies, and companies rely, including Sandia.
“Through understanding our methods, adversaries seek to produce data that is evolving, incomplete, deceptive, and otherwise custom-defined to defeat analysis,” he says. “We can’t prevent this. In fact, we frequently depend on data over which adversaries have extensive influence.”
To address this problem, Phil is now leading another LDRD project, Counter Adversarial Data Analysis (CADA), that seeks to develop and assess novel data analysis methods to counter that adversarial influence.
“We are trying to understand if an adversary can know how we are using data and if they can actually change our data,” Philip explains. “How paranoid should we be that this could happen, and what can we do to remediate the situation? The bottom line is that big data can be powerful, but only if you understand the inherent weaknesses and tradeoffs. You can’t just take data at face value.”-- Patti Koning