does it mean to people on the west coast of the united states? for specific u.s. interests there were a lot of questions that we cared about quite a bit. what are dose rates? which isotopes and things of higher degree refinement. the initial estimate was from the simulations that were done were that tokyo was not at risk and we did not have to worry about that. i had to say it's not easy to do these kinds of scientific problems to the conventional way of peer review. you can't pull together the team of your best people in the middle of the night in say hey you haven't met each other before but one of you work together and answer this question in an hour. the question is how do we do that? how do we become more responsive to harvesting the skills we have in this country in a way that can address these questions

which seem to come up almost annually? there is always something that comes up where science can likely inform and i think this was the case where we did quite a bit of air sampling and air modeling. we did really quite a bit of support for japan and i think there was a very positive story that came out of this understanding, what happened at the site and what it means to japan and u.s. citizens as well or to the continental united states. there are other places. we have been working for a good year or so on trying to look at governance models. how we work, how many agencies can, and partner with us at our national laboratories to solve some of their interesting

problems. what is the way we can engage other agencies to answer their strategic issues using the tools we have like oak ridge or other national laboratories. we had a conversation with janet napolitano on december 18 on this, saying that a partnership model as part of our effort to develop a stronger strategic relationship between agencies which turned out to be timely in a number of ways. one week later on december 25, 2009 there was mr. abdulmutallab the underwear bomber who was stopped from igniting his petn but he kept in his underwear during the flight. it started a relationship between the department of energy

and the department of homeland security and aviation security to try and answer some of these questions of how do we protect events and could this happen again? what are really the risks of this happening? it was an interesting problem. it's really for this particular type of issue it's a competition of different effects going on of all the elastic energy stored in the airplane and whether you can dissipate it before a catastrophic? propagate through the skin and the ribs of the aircraft. we worked on this with them for some time. i would have to say it has been valuable. i can't say too much more about this other than there are a lot of interesting issues in aircraft security here and there

was quite a bit learned from this but it was a place where again we had to become aviation experts to answer a number of these questions because it was time urgent to figure out what the risks are out there. we have to protect against different kinds of threats on airplanes. i have a few other examples but let me perhaps go towards simulation. i want to say a couple of things about the tools here before i get to some summary points. the tools we use, we talk about simulation is something simple but those certainly here at the laboratories that program on these it's a tour de force. maybe 100 or 200 racks with each

rack weighing more than a car. they up remarkable amounts of energy. they have millions of processors that you have to somehow work across to solve a single problem it takes teams of experts and people to attack these from a broad set of disciplines. extremely nontrivial to deliver any of these kinds of simulations or products. these systems take megawatts of power. i remember at livermore when we were starting up a think it was the white supercomputer. it runs at about 4.7 megawatts when it's working and when it's idling it's about 2.5. when they were running the first simulation and the first benchmarks, something that jack

likes very much, the linpack benchmark that his organization tracks annually and has done for many years. it started and suddenly there was 2.5 megawatt spike in the local power grid which is equivalent to a couple thousand homes. there was a call from the local power company trying to figure out what was going on because someone started a calculation. these are not just computers. they are very complex things that you really have to think about in different ways. when we have the first large system at sandia up there in the top corner 10,000 processors, i think the was about the size of a basketball court. there was a chip by intel which effectively has the same power.

the equivalent power from this machine in 1996. we are looking ahead at the technology, keeping in mind that portable electronics and basically a 600 plus billion dollar portable electronics market camp he steered very much by federal investment but perhaps strategic investment on the margins could still derive quality computers for the problems that we need to solve in the years to come. it is a challenge. it makes the scale of initiatives a code word for what the department has struggled with right now but the system we are looking at what probably be in the best case a 20-megawatt type of system. tented 18 calculations operations per second are notional goals for this but we

need them to be functional and useful. let's see. i think since i have a tendency to talk a little bit too long let me go to thinking a little bit about the future. so going back to where i started there isn't a natural place where anyone stops to say what is simulation and what can it do for us? who should be working on this? off the wind up in crises in and of places where we are responding to something and doing the best we can with what we have. it's important to start looking ahead in asking where could we add value? i picked a couple of things that the president has mentioned recently, the climate action plan and his nuclear security agenda from a number of speeches

and nuclear posture review, places we could imagine there could be a role for simulation in a substantive way. the question is how do we do that? who is going to do it? it's one thing to say that but the question is who does what? if there isn't a central place to think about this it's incumbent on those invested in the outcomes to think about that and try and make things happen. decisions are typically not made by scientists. i don't say that is good or bad. i simply observed that the kinds of questions we are faced with often are not scientific and the problems are often not well defined. we want to know what it means to people. we want to know what it needs to the economy and we want to know big societally based questions. when you try and dissect these they typically cover a number of

different disciplines in a number of skills, many fields of specialty. rallying the right people to address them could be somewhat unnatural. it doesn't overlay university structures very well either. there isn't a natural place to go to try and address some of these questions. peer review is typically not available. we don't have time to sit back with a team of experts and have your panel together and go through and figure out if what you have done is right. if you are trying to understand what you need to do to evacuate people you just don't have time for that's the question is how do you build in a sense of pedigree and quality prediction so we don't end up doing something foolish. i think that's very nontrivial and i think it's a real problem and it requires scientific attention. we typically don't -- we typically stop on a number of

interest to us and it doesn't translate to the average person and the kind of meta-questions that are emerging now. simulation is certainly showing its value. we find it in more and more places largely because there are champions out there who pull it along and know when to inject it but it isn't still a natural place to go. many of the problems we don't have oil spill simulation experts that we call on for underwater crises. we don't have the experts for pick your topic and we can't afford to constitute them for every thing we have so we have to figure out how to create a more responsive infrastructure for the tools and people we have. so i think there's a lot to offer. i think there is a lot of

promise but we are going to have to figure out again how to transmit the degree of confidence in anything we do. perhaps understanding how we can be more responsive. there are washington issues there i'm sure but there are are places where university can see themselves the national labs can see themselves. when you know when to inject this into a conversation and how you do it. even asking are these the right questions to be asking. progress here success against the next set of threats, emergencies i think will require communication and greater partnership among the different entities. among broader set of scientists

among social scientists to health, to physical and mathematics. certainly industry and labs in government. i don't see the number of issues diminishing. i see it growing. i see the complexity increasing. i see the kinds of things that where expecting people to answer becoming a little more refined and i think we have to be prepared for that. i think there is a very positive story like what this country doesn't simulation and how we turn it to these problems. i hope i made at least some impression that this is of interest. thank you again for your time and i'm happy to take questions. [applause] >> we are recording these presentations and we would like the questions and answers to be done through the mic funds. we have microphones and we can pass around. we are also going to have a

reception after the question-and-answer period so you can ask your questions at the reception if you would like. if you have a question. tony do you want to go first? do you have a question? please. >> i enjoyed the presentation and especially the dash since i was working there. do you think we could have saved columbia? >> that i don't know. i wouldn't consider myself qualified to answer that. i think we have had in a timely way discovered but the issue was mitigation is an entirely different problem and i couldn't answer that with any confidence.

this is the right next question to ask but i don't have anything in there that's going to help you with that. >> coming back to one of the interesting pieces there was you talked about the crater code being used outside of its valid parameter site but you also raise the point that there is a human factor piece associated with that and the skill set or the knowledge or the depth of knowledge actually in that code and how it was developed was lost. as we move now into a realm where we are no longer talking about codes that are thousands of lines long but codes that are millions if not trillions of lines long how do we deal with that problem? >> yeah, so this is really at the heart of the field called

uncertainty quantification. there isn't a good answer. it is a place we are working with universities around the country to try and understand. certainly there is work at our laboratories but you are exactly right. i think an experienced code writer maybe will remember where all the right of jewish and is in the code for 50,000 lines of code. when you have 100 million lines of code it is harder to figure out what is really in there. there are all kinds of sources that come into a complicated code from the use of material properties are data to assumptions and models to places where there is a mix of empiricism and calibration. there is no methodology to propagate uncertainty through the entire spectrum of sources

of uncertainty. i think even qualifying although the potential source of uncertainty is hard. so it's a place where we need to work. i don't think there's a good answer for that but it's really where we have to look. because ultimately someone is going to make a decision. you have to have a simple distilled amount of information on the degree of trust you have in what came out. some of these simulations look progressively -- convincingly great. great color detail and so forth but it's a cartoon and so the question as to what extent is their confidence and knowledge behind it? i would say it's still an open scientific question and that is a problem that needs to be worked on in the years to come. it's really at the heart of

complex simulation. oh good. >> demetria said something earlier that really affected me and i'm sure it did everyone here when you said these things happen annually so obviously there is a pressing need to look ahead. with regard to how we set things up to better prepare to respond as opposed to calling up in the middle of the night what are your thoughts on that and how can can we setup a better framework to respond to these things given as you said we can expect these things to happen unfortunately yearly. >> yeah. that is an important question. building in a responsiveness is hard because of how we support people and fund people. everyone is busy and it requires

people who want to be involved in this. we need to know who is out there and whether they are willing and at the ready to help. when something urgent happens you go to the short list. who comes to your mind? it's kind of human nature. who do we have and we have to get a little bit better than that and think broadly about the tools and the experts in this country. there is probably a next step there in understanding what that means and whether there are e-readers in funding or regulations that we would have to change. i don't know. with the oil spill the lab director from sandia tom hunter, really left his job for about four months.

we had laboratory people for months doing only that. it was a nontrivial commitment so the question is would you be ready to leave what you are doing today if we say i really need you? can you afford that? it's not for everybody and so finding the subset of those who are inclined to dedicate themselves to some of these problems which might be short or long term is part of that, but understanding what assets we have is another and we do need it did have an inventory so that we can be more responsive and understand whether there are e-readers that have to be changed in legislation or policy changes or simply communication. wikileaks was another great example and i skipped over it.

less than a million mixed-media kinds of things. aside from doing the key word search is our department and there? there is something a little more sophisticated you could do and there graph analysis methods and things we looked at. what is the content and what is the knowledge involves? what are the relationships of information and? what do you distilled from this when you look at it and it's in entirety. there's a complex set of problems there so sometimes you need material science and sometimes unique graph people. ultimately though you need a computer so it's kind of like the core base but then it's a mix of things or you would need at the ready for any of these. >> i'm going to take the microphone for a follow-on comment that i hope he can elaborate on. i notice that you added a

component to your presentation. i know goodyear worked with sandia at length to model the next generation tire and it reminds me that we need these computer folks increasingly with their corporate engagement strategies and involvement of their partnership which many of our corporate partners are coming to us and asking to simulate experiments i have of spending a lot of time and energy and money actually confirming the experiments. we are seeing a groundswell of interest in that and it speaks to the fact that i think this although it will not be commonplace it will be more routine in the future. do you see that coming in that realm? >> i hope so. we have a few examples of where things like that have worked where partnerships with businesses have worked. my personal characterization of the goodyear story was a

required the company to be in crisis before it forced adoption as a new paradigm. in the end it led to the top-selling tire in germany. there are a really marquee product or they think the president of north american tire was the one who finally championed this in 2004. we have found in talking with different companies you often find the people doing simulation and those engaged in thinking about the world this way often not having the top cover for their leadership. there is in the top -- pulled from the top from management saying i want you to inject his new way of thinking into our business model. typically what we hear is you know you are too expensive then what have you done for me now?

we need this by next quarter but the goodyear story was decadal. it started in 1993 and it showed value in 2004. it saved the company which was the last global u.s. tire company. but it took that long. it was beyond thinking through quarterly profits and so that is hard to do. when companies are at risk there are a few stories out there and that's what leadership looks at all the options on the table and they are willing to change the models are matter way. i don't know if too many examples where it has happened when things were going well. >> you hopefully that will change. >> capturing the roi is something we need to do more of. >> we have time for one more question. >> thank you for a very stimulating presentation. you talk much about how to

prepare in terms of the people and the science. now i think also the data and then you talked about assumptions and how much can we trust the data and the outcome of the models? the input is very important of course. if you can't trust the data that we have and of course you need to draw on data in the public sector and the private sector and the academic sector. can we do more in preparing in terms of validating existing datasets and really documenting them well enough as a computer code as you mentioned in the crater code and was it not applied for what it was intended for and we didn't know about the limitations. the nation hasn't been very successful i think and implementing metadata standards and i think there could be more.

what do you see could be done in terms of getting the datasets more useful because we can trust them better? >> so, i think one of the thingt is we need to do what is useful to do in the first place. i don't think we should have standing armies on the ready for trying to anticipate things that might happen because we will never get it right. we don't want to waste money and you don't want people idols. given that you can't anticipate what's going to happen, the move towards simply doing what we are doing better for what we need to do anyway is probably what we should be doing. if there are people -- places where we can improve standards and improve the quality of what we think we are doing, the methodologies that

should be something that we do and we tried to capture. the only other thing we can do is structure ourselves so we can then be responsive to draw upon what we have learned to throw it at the next crisis. >> thank you. before we wrap up and thank him for his excellent presentation and wanted to make a few comments. we have a number of guests from various organizations external to the university here. we have the department of energy from the national nuclear security administration one of 12 facilities that have testingg and local labs. we are glad our friends in the community they were able to join us today. we will have a reception shortly i'm very blessed with the fact that i have a wonderful colleague of mine susan who helps me organize these things.

this actual conversation was cohosted by the baker and howard paul nuclear and thanks to howard for your help with this. thank you for coming on a very cold day. it's warming up and if you would like to join us after this for some refreshments and more discussion with dimitri that would be great. please help me thank dimitri for his time and we want to give a small token of our push asian to dimitri. [applause] >> the a health care program the united states is going to continue and it's not going to go anywhere in the sense that if we do not deal with the issue of innovation, if we do not translate all of those bindings that occur at the pharmaceutical industry at the university level into health care programs which

are affordable and treat disease and cures them and as long as we do not understand their causes and how to treat or cure them there is no point really in talking about the solution of the health care problem. because health insurance coverage is what is going to provide health insurance but when it comes to drugs, when it comes to the premiums when it comes to subsidies where the subsidies going to come from? from taxpayers money. people are not going to get the dollars out of the trees. people have to pay for that. the economy is basically the science of limitations so if we don't deal with a better system on working with understanding and how we can take care of our own health there is no point in having health insurance. what is going to happen is what is happening in colombia right now.

everybody can have access to health care but what happens in europe in which people are covered when it comes to medications and when it comes to drugs than governments are having problems affording them. it's at the end of the day i think the economy is going to continue to need