Hello, everyone. Thank you for joining us today for our virtual meeting on the Extremely Low Probability of Rupture or XLPR Probabilistic Fraction Mechanics Code, Advanced Methods. My name is Matthew Homiak. I am the NRC's lead in the Office of Nuclear Regulatory Research for the XLPR program. And I'm joined by my counterpart today, Craig Harrington, from the Electric Power Research Institute. Purpose of today's meeting is to help new XLPR users by showing them some advanced methods. The meeting today is the last in the four-part technical seminar series that we've been sponsoring surrounding public release of XLPR version 2.1. In the first seminar, we reviewed all the models that are programmed into XLPR. In the second seminar, we showed how to set up the inputs directly using the input set file and using the companion submitter. In the third seminar, we showed you how to run an XLPR simulation and look at the results. In today's seminar, we will be covering a range of what we would consider to be more advanced methods. This will be an extension of the prior seminars on inputs running the simulation and reviewing results. These will be some additional tools that you want to keep in mind as you progress beyond initial training and familiarization with the code and into running your own analyses for your problems. If you're not yet there yet, then no worries. You can consider these topics for awareness and later review when you're ready. Here's our agenda for today, currently in the introduction and opening remarks portion. We'll talk about some advanced methods related to inputs, cover sampling strategies, look at some advanced ways to extract results and look at the outputs, and then we'll cover ways you can run your simulations more efficiently, primarily using multiprocessing. And throughout, we'll have questions and remarks, and then we'll end the meeting with a few closing remarks. We're recording all these seminars for later reviewing, so don't worry if you missed the detail. You can watch it again. You can view those by going to youtube.com and searching for XLPR and looking for our logo. You can also find them through the NRC's YouTube channel. The videos for the first two seminars are posted, and we've also posted the video from our public release meeting that was held back in April. I'd expect us to have the last two videos up within the next few weeks or so, and I'll send an announcement to all the XLPR users when that happens. This is an NRC category three public meeting, which means the public is invited to participate by providing comments and asking questions throughout. We're using the WebEx platform to deliver the meeting today, and this is how we plan to take your questions. You can submit your questions and comments at any time using the Q&A feature. Shown here on the slide is a short review on how you can display that feature, depending on whether you're using WebEx in your internet browser or through your desktop client. At designated points, we may also invite you to ask questions verbally. If you'd like to ask a question then, please use the raise hand feature. We'll call on you and unmute your line. Today, our main presenter is Marcus Burkhart from Dominion Engineering. He was also a presenter on the XLPR model seminar, and backing him up is our usual team of experts. That includes Craig and myself, Cedric Salibary from Engineering Mechanics Corporation of Columbus, Nathan Glunt from the EPRI staff, and Margerix from Phoenix Engineering Associates. Giovanni Facco from the NRC staff is our WebEx host. Can reach out to them through the chat feature if you're having any difficulties with your WebEx setup. Right now, Giovanni is going to share a short poll with you all. This is the same poll as we shared last time, and it's just to help the presentation team here gauge where you're at at this point. So, please take a minute or so to complete that. We'd appreciate it very much, and don't forget to hit the submit button at the very end to enter your responses. Craig, while everyone is completing that poll, would you like to add anything? Thanks, Matt. I just want to express my appreciation to this team that has put these training sessions together. Emphasize the fact that they will be available as all of our users work through the process of understanding XLPR how to run it. Hopefully, these will provide useful guidance and input on that journey through this code. And as we've said many times, please, if you have issues or general questions, as you use the code, please reach out to us. Let us know how it's going, what your experience has been, challenges and opportunities. We want to keep up with what you're doing and how it's going for you. So, we appreciate everyone joining the call today, and turn it back to you, Matt. All right. Thank you, Craig, and thanks for everyone for responding to our poll. Just to have a few references here in the beginning. These are pertinent to today's webinar, and we've shown these to you in the past, so that's really nothing new. With that, I'm just going to turn it over to Marcus to do the presentations. Thanks, everybody. So, now I'm going to go through an assortment of topics that are various different advanced methods, and I'm kind of grouping them by category. This first category will be focused on inputs related topics. So, the first item is related to log normal distributions. And so, one item that has led to some confusion in the use of XLPR is the definition of log normal distributions within Golbson. Typically, log normal distributions are defined by mu, or the mean of the log transform data, and sigma, or the standard deviation of the log transpose data. These are sometimes also referred to as log mean or log sigma. Instead, Golbson defines the log normal distribution either based on the true arithmetic mean and standard deviation, or the geometric mean and standard deviation. In the XLPR input set, there's a flag with a value of zero or one that is used to select if the true arithmetic or geometric mean and standard deviations are input to define the log normal distribution. So, on the slide, I show how the true arithmetic or geometric mean and standard deviation can be calculated in more classical log mu and log sigma. These are the equations you see on the left. In the figures on the right, you can see how the probability density function for a log normal distribution changes. If you switch from true to geometric, believe the mean standard deviation inputs unchanged. XLPR also gives the user the option to pairwise correlate sample values for several of the inputs. Inputs that can be correlated include several probability detection model parameters on the properties tab, as well as a few general material properties, initiation model parameters and growth model parameters, which are on the left pipe, right pipe, welds, and mitigation tabs of the input set. At the bottom of these tabs, there's a box labeled correlations, which identifies which pairs of inputs can be correlated. The user can specify the strength of the correlation by inputting a ranked correlation coefficient, which can have a value ranging between negative one and one. Automated error checking for input values is also performed by the input set. The allowable range of input values is shown in the leftmost column of the input set. This generally ensures that input values are physical, so for example, ensuring that the wall thickness is positive. Any values that are outside of the allowable range are then automatically highlighted in red in the input set. You see an example of that below. Some of these ranges are set up to be dynamic and can be changed based on other inputs. So for example, the allowable range for values in the ESGY input can be no greater than the value of the plant operation time input. So in the example below, you see that you get the laser. Here the range is from 0 to 60 since the plant operation time is set to 60 and then the EFPY deterministic value, you know, not be greater than that value. However, if he set the plant operation time to 80 years, then this would be an acceptable input value. The SIM editor also performs similar input range checks as those performed by the input set. This was demonstrated in seminar number two, which was focused on the inputs. In addition to checks for physical values, models implemented in XLPR may have additional ranges of validity or applicability. To check over which ranges the models are defined, you can look at appendix E of the XLPR user manual. Here, specific input limits are provided for each model. If any of these input ranges are violated, that module will lose an error that's captured in the run log. Details on model specific errors are also provided in the user manual. Furthermore, module subgroup reports provide documentation on the range over which a given model is validated, as well as further details on the model validation itself. Although module subgroup reports are currently not available, they will be released to users at a later date. There are also several tools available for comparing input sets. You may want to use such tools to determine what changes have been made to a given input set or to compare two different cases that you've run. Some Microsoft Office licenses include a Microsoft spreadsheet repair program, which is a separate program from XL, and I've included a link here that gives a description of that program. There's also XL Compare, which offers a 30-day free trial version. Again, I've included a link so you can look into that program further if you're interested. You can also use conditional formatting or Boolean logic within Excel to identify any differences in input values between two different input sets. There are also many other options. For example, you could write a script that reads in values from two Excel files and then identifies any differences between the two. I'll now jump into a couple of sort of topics related to sampling. There are several sampling methods available within Excel at the RC Plan 1. These sampling options are available for the user for both epistemic outer and aleatory interweaves. So first, the user chooses between single random sampling and line-hypercute sampling. Then the user can decide if they want to apply importance to one or several of the inputs. Additionally, the user has the option to decide if they want to apply a discrete probability distribution. So as the name implies, simple random sampling is the simplest of the sampling options. It is the easiest method to analyze, compare results across plans, and calculate sampling uncertainty. Latin hypercube sampling improves sample space coverage versus simple random sampling, without increasing computation time or complexity of the processing. Important sampling can be used to target tails of distributions, helping estimate very small probabilities in a reasonable computing time. You won't typically start off running simulations with important sampling enables, but it may be activated after some preliminary sensitivity studies have been deployed. Finally, discrete probability distribution results in samples that are always uniformly distributed over the sample space. But results in fewer unique sampled values. This may be useful if the simulation sample size is formulated. However, adding additional realizations may not improve estimates impacted by the distribution tails. Over the next few slides, I'll go over each of these sampling schemes in a little bit more detail and show you how to activate them in XLDR. For simple random sampling, all inputs are randomly sampled from their distributions. This makes simple random sampling easy to implement, easy to explain, and easy to analyze. However, also greater number of realizations are needed to achieve reasonably low sampling uncertainty. Latin hypercube sampling forces the sampled values to be spread out across an input distribution. For the same number of realizations, Latin hypercube sampling results in a lower sampling uncertainty than simple random sampling. It's also fairly easily analyzed. However, estimating sampling uncertainty is also a bit more difficult than for simple random sampling. Generally, we recommend using Latin hypercube sample for a majority of simulations XLDR. Latin hypercube sampling better covers the distribution tails, which may have a more significant impact for low probability events. However, if you're using 10,000 realizations, the difference between simple random sampling and Latin hypercube sampling can be very significant. These differences tend to be more significant for smaller numbers of realizations. As you can see in the figure below, for an example of 100 realizations, Latin hypercube sampling more consistently covers a sample space than simple random sampling. This results in a more converged result for the same number of realizations. So how do you switch between simple random sampling and Latin hypercube sampling? There are two sets of simulation settings, one for the epistemic outer loop and the other for the aleatory inner loop. To get to the epistemic outer loop simulation settings, you can click on the menu bar and then simulation settings followed by the Monte Carlo tab. Or you can click the setup epistemic sample size and random seed button on the XLDR global settings dashboard. To open up aleatory inner loop simulation settings, you go to the model root and right click main model and then go to the Monte Carlo tab. Or from the XLDR global setting dashboard, you can click setup aleatory random seed button and then go to the Monte Carlo tab. I'll go over those again in our demo shortly. You will then see a check box with an option to use Latin hypercube sampling for either of these simulation settings. The box is unchecked and simple random sampling will be used. The box is checked and Latin hypercube sampling will be applied instead. Keep in mind their inputs within the input set for the user to record whether or not Latin hypercube sampling is used for a given run. Although Goldson doesn't directly read these input values, it is good practice to record the simulation setting options for a given run within the input set. Important sampling focuses the number of samples in a specific region of interest. So this helps results in a better estimation of low probability events. For example, if you want to focus in on the tail of a given distribution. It's noted that important sampling is harder to implement and can make analysis of data more difficult. Kind of implementation can also actually increase sampling uncertainty. XLPR accounts for any bias introduced by important sampling when the final results are calculated. So that is not something that XLPR users need to worry about. So how does one turn on important sampling? The user decides whether to apply important sampling for each variable within XLPR. For each variable where you activate important sampling, half of the samples for that variable are concentrated within a region about a user-specific quantile. This quantile can be different for each important sample variable. The exact width of this region depends on the number of inputs that are selected for important sampling. In general, we recommend that if important sampling is performed, it's only important sample one or perhaps a few inputs. The more inputs that are selected for important sampling, the more the impact of important sampling for a given variable is diminished. And I'll show you how to activate important sampling for a given input. First on the use for options tab, you need to activate important sampling either for the epistemic loop, the aleatorial loop, or both. Then for the specific input you want to important sample, you need to switch the important sampling input from no to yes and then specify a region of importance. So for the example I'm showing here, important sampling on input 2543, which is a multiplier on the probability constant A for direct model one. And I'm applying the important sampling around the quantile 0.995. So as this variable is set to be sampled in the epistemic loop, I've also activated important sampling for the epistemic loop. Discrete probability distribution discretizes the domain in a number of equal probable strata. The number of strata is a user-specified input. You have a separate input for both the epistemic and aleatorial loops. After the sample space is partitioned, the simulation is executed by applying the conditional mean of that stratum. So if five levels are defined, the quantiles are split into 0 to 0.2, 0.2 to 0.4, 0.4 to 0.6, and so on. Any sampled value within the quantile 0 to 0.2 will then be set to the distribution mean over that range. If DPD is turned on for either the epistemic outer or aleatory inner loop, discretization is applied to all variables within that loop. So for example, if you wanted to turn on DPD for the aleatory loop, you would set input 0111 to 1, and then set input 0112 equal to the number of strata you'd want to use to partition the sample space for inputs within that loop. Note that the number of strata must be greater than 1 and less than the sample size for that loop. Although XLPR includes both epistemic outer and aleatory inner loops, it is also possible to run a more classical single loop monocarlous inflation. If you want to sample all variables in the epistemic outer loop, first in the inputs set, you need to change all sampled value variables to epistemic. You then need to adjust the monocarlo simulation settings to the aleatory inner loop. However, simulation settings can be adjusted to run only one realization. This is done by checking the run one realization only box and specifying the realization number. If using Latin hypercube sampling, running a single loop monocarlo simulation in the epistemic outer loop allows for larger sample sizes than doing so in the aleatory inner loop. If you want to sample all variables in the aleatory inner loop, first you need to change all sampled variables to aleatory in the input set. Then in the monocarlo simulation settings for the aleatory inner loop, you check the box, use a different random speed for each realization of the parent model. You can then use any number of samples in the epistemic outer and aleatory inner loops to run the simulation. For example, setting the number of epistemic realizations to 100 and the number of aleatory realizations to 100 would then result in a total of 10,000 realizations, all of which are sampled in the aleatory inner loop. Thus, if using simple random sampling, the aleatory inner loop allows for larger sample sizes in a given run. For a deterministic single realization run, you want to run only one realization in both the epistemic outer and aleatory inner loops. This is done by changing monocarlo settings for both the epistemic and aleatory loops. For the epistemic loop shown on the left, you'll want to set the number of realizations to one. For the aleatory loop shown on the right, you'll want to check to run the following realization only box. Furthermore, so that you know which input values are being used in your deterministic run, all inputs should also be set to constant within the input set. Keep in mind, there are inputs within the input set for the user to record the number of realizations which should also be updated. For the aleatory number of realizations, setting this to two, which is enforced by the inputs at error checking, but then running only one realization is considered okay. Now, I'll jump into a quick demo within XLTR on the simulation settings. So first, I'll show you how to modify the monocarlo settings for the epistemic. One way to reach those is by going to the set the epistemic sample size and random seed button on the colo setting dashboard. You then go to the monocarlo tab. We always execute runs using the probabilistic simulation option. Below that, you see the input for the number of realizations to the epistemic outer loop. If you'd like to run only one of those realizations, for example, if looking into specific results or debugging, you can then specify below that which realization you would love to run. So for example, if I have 100 realizations and then I want to run realization number 10, I can do so that way. You then have the option to switch back and forth between Latin hypercube sampling and simple random sampling. As I mentioned, when this box is unchecked, simple random sampling is applied. And when the box is checked, Latin hypercube sampling is applied. You then have a dropdown to select whether to use random points in the strata or midpoints in the strata. I always use the random points within the strata when applying Latin hypercube sampling. You can then also specify if sampling sequences should be defined using a specific random seed or not. If you specify the random seed, then the results are repeatable and can be recreated. At the bottom of the window, you see an estimate of the result size for the loop. You also see this number goes up and down as you increase or decrease the number of realizations. So as I take the number of realizations from 100 to 1000, you can see that size increase because we're running only one realization. So if you run more than one realization, you see the size increase and decrease. So there are two ways to get to the epistemic loop settings. Either through the button I showed you here or through run and then simulation settings and then going to the Monte Carlo stand. For the aleatory loop settings, you can either go to the setup aleatory random seed button and then Monte Carlo. Or from the main model, you can right click the main model, go to properties and then Monte Carlo. The settings in the aleatory inner loop look very similar to those in the epistemic outer loop. Again, there are two ways to get to these settings as I already showed you. Here, the number of realizations is tied to input 0107 in the input set. Again, you can specify a specific realization should be run. You can specify a simple random sampling or a Latin hyper key sampling should be applied. And you can specify the random seed for that set of realizations. One additional option that is available to use is a different random seed for each realization of the parent model. This means that for each epistemic realization, a new random seed is selected for the aleatory loop within the epistemic realization. So I will briefly pause for questions. Do you have any questions? Please feel free to submit them. You can use your raise your hand here. We'll just take a short break to get everybody caught up. Of course, if you have a question that's not related to the presentation today, we could entertain that as well. Again, I'm now catching up on the Q&A and it looks like all of the written questions so far have been responded to. Okay, I think I will go ahead and proceed in the presentation. There will be several additional points where we'll pause for questions. And so at those points, we'll go ahead and catch up to anything that we haven't responded to yet in the chat. So the next set of topics is focused on the results and outputs and advanced methods related to those. After each run, the Bolton environment creates the run log. The user should inspect the run log for warnings and error messages. Warnings are also printed when the model is activated. The user should just be aware of these. If there are any errors that are reported, the user should look at the run log to obtain more information. After a run is completed, PapaBucks asks the user if they want to view the run log. Another way to view the run log is to go to the run in the menu bar and then select view run log. It has been also saved in the same directory as the Bolton file and it is named GoldSimRunLog.txt. The run log captures a few other pieces of information in addition to warnings and errors. These include file name, simulation start time, simulation run time, the number of epistemic outer loop realizations, and the epistemic outer loop random seed. In the prior seminar on running the simulation, Cedric talked about exporting results from GoldSim. In addition to using copy paste to specific results, you can also export results to a specific Excel or a text file. This is not done by default but can be activated in the properties for time history result elements located in the model loop. To do so, use the export results to drop down menu to select if you'd like to export to Excel or text file. In the export tab, you can then specify the file name, when to export, and for the case of Excel files, where in the Excel file the results are exported to. You can either use this to export results after completing a run or you can set this up prior to a run and then have the results exported when the simulation completes. Conditional results can also be generated by creating new results elements. Add a new result element is only possible within GoldSim Pro. However, once results elements have been created, GoldSim model file can be saved in player format and then viewed and run with GoldSim Player. New results elements can be inserted by right clicking and selecting insert element and then results. Then you select the desired result type. Of these shown in the figure, the time history result, distribution result, and array result are the ones most commonly used in Excel PR. Note that the saved results in any GoldSim element can be displayed by left clicking on the green output port. This causes an output interface to pop up which displays the outputs of that element. If you then right click on a given output, you can then view those as a time history result or a distribution result. It is noted that these outputs, if within the main model, only represent the last value that is calculated. So it is for the aleatory realizations of the last executed epistemic loop. If you want an added output to be calculated for all epistemic and aleatory realizations, you need to first get the calculated results out of the main model. This is something you need to do before running a simulation. Again, it is only possible to make these changes in GoldSim Pro. Once completed, the file can also be saved in the player format. To get the results out of the main model, you have to add that result to the main model interface. I'll go over this again in a demo shortly. From the model route, you right click main model, then go to properties, and then the interface tab. Additional output variables can then be added using the green plus sign under the output interface definition. From here, you can then browse to select which output to export as well as what format that output should be used for. To view the time history, where the options are statistic history or realization history, or final value, where the options are statistic or distribution. So if you're running a simulation with a large sample size, it may be difficult to extract all of the results. In some cases, viewing results on a realization by realization basis. GoldSim may display values only from the first thousand realizations at a time. However, a screening feature exists that allows you to view realization-specific results for other realizations. Screenings performed at the epistemic or outer loop level. A description of how to perform such screening is provided in volume two of Zibble's user manual. And I'll go over this in the demo as well. There are several ways to access the result screening options. One is by going to run and simulation settings, Monte Carlo, and then selecting results options. Alternatively, in a results element, you can click the edit properties option, and then Monte Carlo results options. You can also right click the results element, select properties, and then Monte Carlo results options. Once in the Monte Carlo result display properties, you can change settings for realization classification and screening. By default, screening is set to include all realizations. Additional conditions can be added and applied for screening. This is done by clicking on add, and then to add a new category. When you do so, a new category pops up, but first does not have any conditioning. The condition fields can then be edited by double clicking on the corresponding cells in the new category. So in the example here, I've entered a condition to include only epistemic realizations less than 30. I then unchecked the all realizations category to exclude any other realizations. The gross percent and net percent numbers on the right tell you what percentage of the realizations fall within each category. So then if you open up a results element, it will only show you the results for the first 29 epistemic realizations, if that's all that you have screened in using these conditions. When it comes to screening of results, there are a few important things to note. Conditions can also be used to screen out results. So for example, here by checking category one and unchecking category two, only results with epistemic realizations greater than equal to 30 will be displayed. When screening is activated, it is applied to the entire Goldson plot. So as a reminder, the stats text in the lower right corner, the main Goldson window is changed from result mode to result mode screened. Unchecking all categories may lead to Goldson crashing, and so it is recommended to always save once a simulation has been run prior to doing any screening. Multiple conditions can also be applied combined using operators such as and. An example shown here, I've screened in realizations greater than 10 and less than 31. So now I'll walk through an example for if you wanted to screen results based on realizations that have had cracks initiate. In this example, I will work through again as part of a demo. So first, we would add an additional output to the main model interface. We right click the main model and select properties to go to the interface tab. Then we use the green plus sign under the output interface definition to add an additional output variable. We then point that new output variable to the occurrence of crack output, which is located in Excel care model, post processing occurrence of crack and occurrence of crack. And we'll call this new variable is cracked. We then need to set the output type to final value and the output definition to statistic and mean at the model root, we then add a datum element that links to main model dot is cracked. So we do this by right clicking the background and selecting insert element inputs and data. We then change the element ID to is cracked and the data definition to main model dot is cracked. Then when we set up the screening, we can access this newly added variable as cracks. We can using this, we can now screen in or out epistemic realizations that have had cracking by screening based on the values of this variable that are non-sterile. Note that if you're using multiple alitory realizations with an epistemic realization, if any one alitory realization associated with an epistemic realization is cracking, then all alitory realizations associated with that epistemic screened in. And so all, as I mentioned, I'll go over all these steps again in the demo. So once you've extracted results from Golbson into your desired format, you can then perform post-processing to calculate any outputs not directly calculated in XLPR. For example, some outputs that were considered as part of the NRC and EPRI typing system analyses included the leak before break ratio, which was defined as the ratio between critical crack size and crack size at detectable leakage, as well as the time from detectable leakage to rupture. For the post-processing, any desired software to look and be applied. So some examples that have been used in the past include XLPR or Python. Other examples of post-processing that have been performed are sensitivity analyses. Sensitivity analyses can be used to better understand the relationship between model inputs and outputs. For example, sensitivity analyses can be used to identify the inputs out of the most significant impact on the results of the given model. The knowledge of the most important results can be used to identify inputs where more information collection could decrease uncertainty, or it could help inform additional simulations with important sampling active on the inputs which drive the model results. Many statistical methodologies exist to determine which sample inputs have the greatest influence on outputs of interest. Some include regression techniques, bottom modeling techniques, or adjoint methods. So keep in mind in order to apply these sorts of methodologies, sample values for all inputs as well as the outputs of interest need to be saved. The figures on the right show an example of two sampled inputs, one of which is highly correlated with the occurrence of crack output, the other of which which is not highly correlated with the occurrence of crack output. Now I will jump into the demo on how to set up screening for results. So first, we would need to set up a file that adds additional output that we'll use for the screening. And this is something that we need to do before a simulation is run. So we'll go to the main model, right click, select properties, and we'll go to the interface tab. Then under the output interface definition, we'll press the green plus button to add an additional output variable. So the value for occurrence of crack can be found under XLPR model and post-processing. And under occurrence of crack, we select occurrence of crack and press OK. We'll rename the output to is cracked. And then we verify that the output type is final value, statistic, and mean. Again, there are several options for output type. So the spinal value or time history, and for the output definition, you can select last calculated statistic or distribution. And then you can either specify mean or some other specific percentile. One press OK and close. So at the model root, we now add a data element that links to the main model that is cracked, item that we just added to the interface. We do this by right clicking the background, selecting insert element, inputs, and data. We'll then change the element ID to is cracked. And then data definition will point it to main model that is cracked. Once the variable is a valid variable name, it turns to green. We then press OK. So now we can perform screening on the newly added output is cracked. So for an output, we go to properties, monocular results options. And then now we have access to the realization classification and screening. So we can add that new output for screening by pressing add. And double clicking here and selecting is cracked, there's a zero. We can then uncheck all realizations to only screen in realizations where cracking has occurred. Or you can run with all realizations being shown. And then when you investigate the results, you can then perform screening at that time. So to save time for the demo, I'll now switch to another GoldSim file where I've already completed these steps and run the simulation and save the results. So just take a moment to open. Since GoldSim saves all results within the GoldSim file, if you run larger realization numbers or save a lot of the inputs and outputs, doing certain operations on the file can take a little bit of time. So now let's look at the comparison detection output. So currently I do not have screening applied. You can see it just says result modes. And so we should see all realizations when this result table opens up. So here you can see all individual realizations for this run. And for this run, I ran 2,500 realizations in total. So for the occurrence of crack output, if you look at the values, most of them are zero, indicating that no cracks initiated. There's a handful of them where cracks did initiate. So now let's use screening to more closely look at the realizations where cracking did initiate. We'll go to the edit properties, Monte Carlo results options. We'll uncheck all realizations to only look at the realizations where cracking occurred, which is actually the only fraction of a percent for the inputs that I used. We're going to press OK. So now it shows result mode screen. So I should just take a moment and then I'll be able to close this window. So while we're waiting for Goldson to continue thinking, I just wanted to point out that to access the export results options, you can do this do so here through the dropdown for export results too. And then under that dropdown, you can select either tasks or Excel file as options for the export and close this. The bottom right, we see that screening is now active. And now we see the six realizations where cracking has occurred. And so by scrolling here, you can more clearly see when the occurrence of crack outputs, which is from zero to one for each of those realizations, indicating when the crack has initiated. So now if we wanted to look into any further details for other values calculated in Excel PR associated with those realizations, it's a lot easier to do so. As you can see, I closed the comparison detection output and screening remained active. So now we could go to the total leak rate history output. And the screening remains active for showing those six realizations where cracking has occurred. We can then scroll down again and see where and when leakage occurred for each of these realizations as well as what the leak rate was for those realizations. So that's all for the screening demo. Open up the next file here in the background of this list for the presentation. So I'd like to pause again for questions to see if there's any additional questions that are unanswered before I jump into the next topic. Yeah, I think Marcus, we're all caught up on the Q&A questions. If anybody wanted to raise their hand right now and ask a question or the topics up until this point, please go ahead. We can take your question verbally if you'd like. I'm not seeing anything, so I'll wait for another moment. And then if not, I'll roll on to the next topic. I'll start talking about certain ways that you can improve efficiency in SLPR. So by default, time histories or final values are saved for many of the Goldstone elements. In the player version, you can disable some results elements. In Goldstone Pro, you can also edit the settings of some of the elements to disable them as well. So options for disabling look like one of these options where you have various checkboxes that allows you to determine if you want to enable or disable those elements. To see what is being saved, you go to view and highlight saved results, then check the time history results and the final value results. Any value that is being saved is then shown in bold text below. You can also look at the result size in the simulation settings for the epistemic outer and aleatory inner loops. Goldstone containers allow some settings, such as results saving, to be changed recursively. So you only need to change the settings for a container, and those settings changes are then propagated to all contents of the container. Even if elements are disabled, the calculations are still being performed. It's just the results aren't being saved directly in the Goldstone file once the simulation is complete. So Goldstone is a 32-bit program, and it retains all saved information in RAM. So this means that the 32-bit memory limitation also limits the number of realizations that can be executed in a given run. So by disabling outputs or intermediate variables, this reduces the amount of information being saved, and thus allows you to run an increased number of realizations in a given run. Now if you do exceed the Goldstone memory limits, there are several errors that might pop up. So for example, you might be warned in the simulation settings with a triangle and exclamation point. This one doesn't necessarily mean you only exceed the Goldstone memory limits, but it means that you're getting close, and you should be careful. You might also see other errors that just don't make quite as much sense, and so I've included two examples of those. One where you just get a black box error, and you can't read anything, and another where you see an application where you then need to terminate the program. Finally, Goldstone may also just crash during the run if you exceed memory limits. So Goldstone saves the results at every time step for every realization. So in addition to disabling outputs or calculating intermediate variables, you can also reduce the frequency at which values are saved. For example, you could decide to only save every other time step rather than every time step. To do so in the model root, you right click on the main model, and select properties. You go to the time tab. You can then adjust the output frequency to be every several time steps rather than every time step. Then an estimated result size is also shown at the bottom of that window to help you determine how frequently you may want to save those results. So in the main model properties, so the properties for the alliatory loop, you also have the ability to change the time step settings. So you get that here by going to set up the alliatory random CV button, then going over to the time tab, and then here under the basic step you can change the time step in months. In XLPR, the default time step is set to one month. This is where you may want to vary the time step, or if you want to investigate temporal convergence for a simulation. Another thing you can do to decrease runtime is to run XLPR in parallel. So I'll go over the steps to do this in another demo tourally. So with Goldson Pro, up to four Goldson Slate processes can be run in parallel. If you have the distributed processing module, then there is no limit to the number of slave processes that can be run. First, you'll want to run the code without distributed processing and a small number of realizations. The fastest option is to perform this on a single alliatory and single epistemic realization. I've shown here one realization for each loop. This is to confirm that all input values from the input set have been updated. Although this should have been done automatically, we've seen a bug where inputs were not updated if going directly to running XLPR in parallel. So Goldson has been made aware of this issue. Then when we're ready to run the simulation using distributed processing, we can do so on up to n minus one slave processes, where n is the number of cores in the compute processor. So for example, if you have eight cores, then you can have the distributed processing module. Then you can run up to seven slave processes. So that's what I'll be showing in the demo. The slave processes can be started using the Windows Run utility, which you access by pressing the Windows key and R on your keyboard. Inside the Run utility, you can then enter a command pointing to the location of the Goldson executable with a dash S, depending to the end, to specify that a Goldson slave process should be run. Each time this command is executed, one slave process is started. And so then these steps can be repeated for as many slave processes as you'd like to run, be it four or seven or however many. Once the slave processes have been started, we then need to connect to the master Goldson file with the slave processes. You do this by selecting Run and then Run on Network. You can then connect to the master of the slaves. For slave processes on the same computer, you can use the local host address to point to the slaves. Once all slaves have been added to the list, you can click an update status button, which is behind this text box here, to confirm the link between the master and the slaves. You can see that button here. So parallel execution is only applied to the epistemic outer loop. Another thing that you have control over is the number of epistemic realizations that are passed to a slave at a given time. Adjusting this number can also help improve runtime. So too few at a time and more processing time spent transferring data back and forth between the master and the slaves. Too many, and then you start to lose some of the benefits of parallel execution, plus data transfer takes a lot longer for each chunk of realizations. So rule of thumb that we would recommend this to be used is somewhere between a hundred and a thousand realizations per transaction. So in the example shown here, I've selected 500 realizations at a time. Then once this is all set up, to start the simulation, you press the Run Simulation button. So now go through those steps again as part of the demo. So first, we want to run the simulation without multi-processing and ensure that all inputs have been updated. In this case, I'll do a quick run with one epistemic and one alleys for realization. And in this case, we won't need to update the input side. So I go to the epistemic sample size and random seed. I verify that one realization is set. So we're good there. Press OK. Then for the alliatory random seed, go to Monte Carlo. And then I only want to run one simulation or one realization. So I select one here and then press OK. We then go to run model. I'm going to run and then run model. Use the run controller. Now it's importing data from the input set and gives us the option to display the run log file. For this case, I'm not going to bother with opening that up. But if you wanted to, you would press yes. If you close out of this and then do want to look at the run log file later, you can select run and then view run log. All right. So now that we've done this, we're certain that the inputs have been updated correctly. And we will go ahead and clear the results return to edit mode. So now we'll update the input set with the number of realizations that we want to run. In this case, we'll do 2,500 epistemic realizations. An epistemic random seed of one, two, three. We'll do one alliatory realization. I need to enter two in the input set. I set this to one. The dynamic highlighting shows this as red and a valid value. So we'll go ahead and change this back to two. And then the alliatory random seed will set to four class types. Once we've met these changes, we'll go ahead and hit save. Now we need to update our simulation settings for both the epistemic and alliatory routes. So first, for the epistemic loop, we'll do 2,500 realizations. And we'll use Latin hyperheat sampling. We'll use one, two, three, alliatory loop. We just want to run the one alliatory realization. And for that one, we'll use a sampling sequence four, five, six, and press OK. So at this point, I like to save the model to ensure that all of my changes to the simulation settings have been saved. I go to save. Then I want to spin up the number of Goldson slaves that I want to run. I'll just move Goldson here.  So here you have the path, the Goldson file, executable with a dash s for slave. And press OK. And that starts up one Goldson slave. So I'll then repeat that process until I have a total of seven Goldson slaves start up. Two, three, four, five, six, seven. Since you can see the communication output from each of these slaves, I usually like to tile them so that I can see the output from each one, or at least partially see it. Then we go to run, run on network to set up the settings for the multi-processing. So if you haven't already added the addresses for the slave processes, you can do so by pressing the add button. I'll remove one of these and then demonstrate. First add. And then for slaves that are on the computer that you're running Goldson on, you can use the local post address. To connect to the slaves, you can click one of these check boxes. So each time I connect to a check box, I connect to an additional slave. And then the status, it tells me which slave I've connected to. I can then press update status to make sure that the status for each of the slaves is up to date. I can then set the number of realizations to process for the slave transaction. So for this example, we'll just use 100. Then here you have a drop list option to save files on the slave computer. You can either save all files, auxiliary files or not. So I'm going to go ahead and press none. Once you've done that, you're ready to start the start the simulation.  You can then see that the slaves start receiving files and start loading the model files. And here you can also see that the connections have been established and files are being transferred. You then see which realization each slave is working on. And then when the simulation starts running, the simulation timer will also start up, as shown here. And you can also see the gears turning to help verify that the slave is in performing calculations. So that's that's pretty much it for distributed processing. Now I'm going to switch back to the presentation. That's it for the match topics. So I'm going to go ahead and turn it back over to Matt. All right. Thank you, Marcus. Did anybody have any questions there on the last portion about efficiency gains in XLPR or any of the topics actually? We can do Q&A. I know we're all cut up on the question here. All right. So the houses are run with larger sample sizes with some modifications. So I went over those modifications as part of the presentation. They were focused on the enabling and disabling specific outputs and intermediate variables as well as adjusting how frequently certain values are saved. And so by reducing the number of elements that are saved per run, you can then execute greater numbers and realizations in an XLPR. Thank you, David, for your question. Anybody else have any other questions about presentations today or any of our webinars? Or just general questions about the XLPR code? Yeah, certainly the presentations today being on more advanced methods. Most folks, I would guess, probably haven't gotten that far yet. So I'm not surprised we don't have a ton of questions on the presentations today. And we've also provided a lot of information over the last couple of weeks now. So it's a lot of information to take in. By the way, we've gone through it here and we're recording this. So you can have it handy for later viewing to re-review any of those topics. All right. I'm not seeing any other questions come in. So I'll go ahead and take us to the closing remarks. So in today's meeting, we covered some of the advanced features for the XLPR code and these built upon topics introduced at our previous seminars. Specifically, we covered advanced topics related to setting up the inputs, selecting appropriate sampling strategies, screening and creating custom results, and maximizing the efficiency of the XLPR simulations by altering the outputs saved and using multi-processing. So with this being our last seminar, you may seem like it's the end, but I think we're late from NRC at every perspective. This is just the beginning. We are currently working on setting up an XLPR user group and some of that framework for the user group has already been established. And I'll give you a few details here. It will be fee-based and offered under a separate license agreement and it will provide access to things like the source code, our entire library of the XLPR software quality assurance documentation, which is north of 3,000 pages. It's going to also allow for external uses of the code, meaning you can use it to do consulting for others. And the other features as well that we haven't determined yet, but some things we have in mind are like real-time bug reporting, other services like maybe user support, you know, training like we've been doing in these meetings, access to beta releases, user form, those kind of things. So those are all in the works right now and we're going to use some of the feedback we've been getting in these webinars to help establish that. And we'd also like to send a survey the next month or two here to all our XLPR users to get some feedback on those kind of things and features we may want to have included in the users group. So please look out for that survey. It will be coming soon as well as we'll be doing other XLPR communications as well. So look out for that. Greg, did you want to add anything else on that? No, I think you've covered that well. We were working to put that together and have it available and we'll try to structure it in a way that will most appropriately suit the needs and interests of our audience of users. So we'll look forward to continuing to interact with everyone and using XLPR. Okay, am I posited? Are there any questions on the user group before we take us to the end? Yeah, okay. Well, if you have any questions, of course, you can reach out to us here at the usual contact information. I want to thank everyone again for their time and after the meeting ends, if you'd like to provide feedback to the NRC on this meeting, how it went, you can go to the nrc.gov public meeting schedule, find this meeting listed there and you can click on a feedback form and submit that to us. We'd appreciate it. So just some final reminders for you. Again, I suggest that you complete the introductory training, which is available in the training materials included in the XLPR version 2.1 release package. You're welcome to re-watch, of course, any of these videos that we're posting up on YouTube. And then, of course, like we said, look for our future announcements and information on the user group. I want to thank everyone again for staying with us in these webinars and we look forward very much to engaging with you in the future on XLPR. Thanks again and with that we'll adjourn.


Good evening. I'm very pleased to see the considerable number of you with the stamina to be with us for today's program to its conclusion I Invite my colleague professor Claire McRosty to Introduce Barron Stigrall Some considerable number of months before the United States entered World War two John Maynard Keynes was in our country Concerned about the economic dimensions of assistance for Britain At an evening meeting with some American Keynesian economists He urged that the United States should set up step up its preparations for war and Terminate its efforts to end the Great Depression When some of the American Keynesians protested that he was that what he was urging was not Keynesian Keynes is reported to have responded in that case. I am no longer a Keynesian The debate about who is a Keynesian and What economic policies are Keynesian? Will not be resolved here nor in the near future Nor can the legacy of Keynes be adequately appraised at this conference By examination of theory and the experience most familiar to us It is fitting and right That the Swedish experience be scrutinized at this conference entitled Nobel and In this place which claims Swedish heritage Barron Stigrall is uniquely qualified for this assignment He is a practicing economist in the service of his country He has had long experience in the Ministry of Foreign Affairs in transport and in export He is the chairman vice chairman or member of the boards of Swedish and international companies and organizations You know of this college's commitment to the examination of the legacy of Nobel and of science Stig Rommel the president of the Nobel foundation Joins us in the investigation of the legacy of Keynes in the science and art of economics applied in Sweden Please welcome Stig Rommel to tell us about the Swedish model Keynesian policies put into practice Thank you so much for That very nice introduction and for your kind reception. I was a little scared when I listened to the music The title of the music was the end of the world or end of time and I can assure you that that's not the Swedish model Before during dinner I and my colleagues were had the privilege of Meeting Some 17 years old voice and girls and We were asked to give advice What they should do now when they were 17 and With all these 17 years old people present here some of them gray-haired I'm sorry that you would not all were there to listen because there was a lot of fine advice given by Those wise men present I was not asked of course, but if I had been asked I would my advice to Then would be keep good company and I would With that refer to a story that was told by our president the president of Gustavus Adolphus young Kendall he referred to a story about the price winner in physics in 1983 of Fowler Who had Had been unlucky We had an accident with his knee and it was a very nice story. I shouldn't steal your story You should tell it the story yourself, but I I found a strain that you forgot to tell what happened then Because Fowler told me that That follow up perhaps he spared you Because what happened then was after the young 17 years old Fowler had Had got had this accident He he got too many bottles of beer And he was carried home by two of his friends and Those two and he told this story the day before he got the Nobel Prize In seeing us by the king and he told us then that the two other fellows who carried him home also got the Nobel Prize and one of one of them was Was That famous physicist Glenn Seaboy so there you see keep good company I think That John Maynard Keynes is good company and I I hope that all those who have been here today Followed for many hours All these lectures about him will not leave St. Peter with the impression that John Maynard Keynes was A brilliant just a brilliant economist with a general theory He was much so much more He was for young people I think especially it's they should learn more about him The tremendous moral courage John Maynard showed John Maynard Keynes showed when he as a member of the British Delegation to the peace conference in Versailles He decided to break with the British government because he Thought that he found out that the political game played in Versailles by Lord George President Wilson and Clemenceau was deadly game that would harm The word and harm humanity and he had them the moral courage to to leave a government and Publish that famous book the economic consequences of the peace I Think the moral courage he showed is a stirring example for all the young people to not to be too impressed by authorities so Don't give a damn what presidents and premiers think stand up for what you believe is important I think this is something The young people should remember when they listen to what has been told here about Keynes They should also learn more about him The his broad interest he was interested. He was Tremendously interested in art ballet had played a very important role in the in the British The the Bloomsbury group Fascinating man putting his economic theories aside. He also worked Very very successfully on the British stock market to make him himself a Fortune Fascinating man a good company. I hope that you will decide after having attended this conference to learn more about him I will Start my lecture here By quoting Keynes In the following way the ideas of economists and political philosophers Both when they are right and when they are wrong Are more powerful that is commonly understood Indeed the world is ruled by little else Practical men Who believe themselves to be quite exempt from any intellectual influences are usually the slaves of some defunct? Economist for more than 50 years Sweden has been governed by practical men Who have been slaves of that defunct economist John Mayard Keynes? They have however been fully aware of the intellectual influence and they have indeed been very proud of it I venture to say That there are few countries in the world where Keynes and his economic theories Have influenced the shaping of economic policies as much as in Sweden That does not mean that Keynes would have approved of us all the time. I Think he would have been quite content how things were handled in the 30s and Quite proud of his disciples in the 50s and the 60s. I Beloves by believes strongly however That he could he would have criticized our government severely for following Keynesian policies too long Long after the prerequisites had ceased to exist. In fact, I believe That lord Keynes would have stopped being Keynesian long before the Swedish government did In my lecture, I will review Swedish economic policies from 32 up to now And I will do so by describing Our policies during six different periods that is first between 32 and 1940 the end of the depression and beginning of the war boom second period 1940 to 48 the war years years of national otter key that is natural self-sufficiency Temptations of a planned economy And then the third period 48 to 68 the welfare state based on a healthy market economy came into being and Then the fourth period 68 to 76 the Indian summer of socialism and the temptations of a planned economy The fifth period 76 to 82 and non socialist government pursues social democratic policies and then finally From 1982 up to now a socialist government a social democratic government pursues non socialist policies And the rebirth of the market economy The first period the end of the depression year and the beginning of the war boom The depression did not hit Sweden as hard as other countries in particular United States even if unemployment increased considerably and The Kruger crash that was the match King Eva Kruger's bankruptcy after his suicide in 1932 Which was a Catastrophe it looked upon it was looked upon at a catastrophe at that time It made also the stock on stock exchange impotent for many years But with Sweden as a country was out of depression as early as in 1936 The social democratic government we came into power in 32 With Mr. Pierre Albin Hansen as premier was clearly inspired by the ideas of young men main arcades They put into practice His ideas about the wisdom of an expansionist policy in times of depression They invested in public works and in a way their predecessors had not dare to do The public sector in Sweden was at that time Very small and there was ample room for expansion Certainly these Keynesian policies had positive effects on the economy But much more important was the devaluation of the crown which took place in 1932 That devaluation Gave a strong shot in the arm to Swedish export industry for the rest of the 30s the undervalued crown Made Swedish exports very competitive on world markets with healthy effects on the economy as a whole Unlike the United States where higher unemployment still lingered well into 38 39 Sweden enjoyed a boom of its own industrial investment increased Unemployment dropped and the cornerstones of the new welfare state were laid The legendary American journalist Marcus Childs Told sweden's success story of the 30s in his book sweden the middle way The story of a country following its own Keynesian path Between the extremes of old-fashioned capitalism and totalitarian socialism This book was a bestseller in america of the new deal Let me add That sweden of the middle way Was a country dominated by private enterprise and with only a small public sector The second period of 40 to 48 the war years Isolated sweden from its trading partners And circled by nazi occupied countries sweden was forced to adopt the rules of a war economy strict retching Of food clothes and fuel and with industry and trade under strong And determined governmental control The national coalition government that ruled sweden during the war years was dominated by the social democrats And its leader pair are bin hansom In the election of 1940 they gained more than 50 percent of the votes Votes of confidence not only in the economic policies of the pre-war pre-war years, but also of The the prime minister as a leader of the country in wartime But it clearly was a vote of confidence in the policies the Keynesian policies of the 30s The wartime government succeeded not only in keeping the country free of war and german occupation But it was also successful in keeping down inflation and unemployment And making industry and agriculture produce the goods that were needed to keep the country going In 1945 the coalition government fell apart and the social democrats continued alone The undisputed success of the planned economy of the war years And the prestige socialist as in ideology Had gained because of the successful soviet resistance to the nazis Encouraged the new government The new the one party government of social Social democrats to adopt a much more radical leftist path than they had followed in the 30s In 1944 The party had adopted a platform The so-called the post war program In that program economic planning was a keyword and there was a blueprint In 27 points of a planned economy with strict regulation of industry and commerce And governmental control of all foreign trade The program also promised an egalitarian society achieving equality and social justice through increased taxes The program was inspired not only by the ideological fervor of the minister of finance But also inspired by fear of a new economic depression Like the one that had followed the end of world war one Professor gunna myrdal The economist who lived in the u.s. During the war was one of the leading Proponents of that pessimistic school of thought myrdal's book a warning against after-war optimism Became a bestseller in sweden and had a strong impact on the social democratic government thinking Myrdal was appointed minister of commerce in 45 And the new policy adopted was inspired by myrdal rather than by canes In the following three years 46 to 48 the new socialist program became the focus of an intense political debate sweden stood at crossroads The new leader of the liberal party professor bertel olien A true caneson became leader of the opposition And his hard-hitting criticism of the socialist policies of the post war program Which was very much these criticisms were very much respected because of olien's position as a leading economist Came to play a very important role In putting to an end the idea of a socialist experiment in sweden It should be added That the short-term economic policy of the government Also turned to a failure An appreciation of the swedish crown Had a disastrous effect on exports and wartime Rationing had to be reintroduced In the general election of 48 the social democratic party experienced heavy losses and could only retain a majority in parliament With a very narrow margin Myrdal left sweden and became head of the european economic commission in geneva The american economy had shown its vitality Flexibility and strength As and no post war post war depression came about Instead there was a powerful investment boom And international trade came to life in a way myrdal had not expected The swedish export industry throw A dominant factor In this development was of course The marshal plan which received which revived wartime war ravaged europe The marshal plan was bold and inspiring Exactly the kind of medicine that john canes had prescribed in his famous book Which i just mentioned the economic consequences of the peace published in 1919 Let me add In my view If canes advice had been followed then No one would ever have heard of Ardolf hitler Thus 48 1948 became a watershed in swedish economic policies The new prime minister targi allander Abandoned the party platform or 44 orthodox socialist was out Instead the social democratic government went back to a canesian policy With strong roots in a marketing in the market economy It is fair to say that professor bertha olin Bertil olin assumed a very important role in this development He never became prime minister But he had a strong influence on swedish economic policies during this period as a strong leader of the opposition It's interesting to note How greatly swedish policies after the war were thus influenced by two economists of international renown muhdal and olin Both received the economic price in arnaval for nobel muhdal in 74 and olin in 77 In particular olin was strongly influenced by canes Then Came the change In 1948 and we had those years 1948 to 1968 these were the 20 years I would say the golden age of the swedish model based on canesian policies The economy was stimulated in times of recession and restrained in times of boom Industry expanded as as so did g and p unemployment inflation figures were very low And using the market mechanism Uh labor was transferred from farming in industries with poor competitive advantages like textile and shoes to expanding industries like automobile and shipbuilding Especially impressive to the outside world was the cordial relationship and fruitful cooperation between the unions and the employers organizations the two leaders of the lo and South the central organizations as we call them in sweden Made a widely published speaking tool here in the united states The love duets of the two bosses As it was called That love duet between the bosses Was fascinating for americans used to a completely different relationship between labor and capital Even if no particular effort was made to increase public ownership of industry More than 95 percent Was in private hands and still are The public sector increased steadily because of the setting up of new social welfare programs and the growth of bureaucracies connected to such programs What we did in sweden that time was not to nationalize production But to socialize consumption The swedish welfare state building stood there imposing and impressive Caring for its citizens from the cradle to the grave But there was a price to be paid To be paid later and it has to be paid now But no one thought about them Once more sweden the middle way came into the international limelight Utopia seemed to be emerging in far away idyllic sweden The ideal came abruptly to an end in 1968 The waves of that ideological hurricane That of the cultural revolution Came rolling in from baying in paris Berkeley and Berlin into our placid swedish lake The once peaceful streets of Stockholm became The stage of huge demonstration Of a kind not seen there since the turbulent years of the beginning of the century The demonstrators marched against the war in vietnam, but the real target Was oppressive and exploiting capitalism The political climate changed suddenly and dramatically The social democratic party found itself accused for being bourgeois and Capitalistic and having betrayed its socialistic ideas At that time olaf palmer became prime minister And put politics to get turned to the left As the party congress of 68 in 1968 That fatal year The spirit of the radical party program of 1944 Was revived and socialism planned economy and equality became once again keywords of the labor movement The party congress adopted a new industrial policy Which aimed at increasing public ownership of industry naturalizing production And opened the door for an active government role in industry A ministry of industry was created and the new minister Indicated as a goal a public ownership of industry up to 25 percent as a beginning Industry In still in private hands should be closely watched That indian summer of socialism in sweden only lasted for a few years The new industrial policy turned out to be great failure The symbol of this era was the gigantic multi-billion steel mill project in lulio In the far north of sweden Steelwork 80 It never came about The project was put to an end by the non-socialist government, which came into power in 76 Only a vast and empty artificial peninsular Created for that mill outside lulio Still reminds us what was meant to be the crowning glory of a socialist industrial policy But let me go back a few years to the beginning of the palmer government The new prime minister stressed That sweden should continue as a mixed economy But the mixture Would change that is the socialist part would increase Instead increase of taxes made possible a continued growth of the public sector Which came close to 60 percent of g&p Education and health care Were made public monopolies and as always monopolies mean poor efficiency Reforms of the school system aiming at opening the doors for higher education For for everybody led to a lowering of tuition standards Instead of helping the young of working class origin these reformed reforms became counterproductive A change of the tax system made it attractive for women to take jobs outside the realm of children in kitchen A daycare system for children was established with the ideological aim of liberating women from that Traditional role of mothers and housewives But also of increasing equality by shielding children from the influence of their family background The costs of these programs financially and otherwise Became tremendous Also in the field of economic policy was a palmer government The palmer government wished to make a great leap forward In 74 it was decided to expand the economy to counteract a general downturn of the economy Of the economy of the ocd countries of the first oil shock of 73 The swedish government decided to stimulate industry by offering special tax breaks for increased stocks They made industry keep up production and at same time unemployment The idea was as simple as ingenious When the countries in the ocd once more enjoyed an upturn of the economy Swedish industry should profit by selling from its stocks In the first year this was a marvel Sweden had really a golden year in 74 while the rest of the ocd was sunk in gloom But the bridging of the war of the gap policy Which meant cancean policies carried to an extreme Became a great failure The big swedish industrial stocks Especially in paper and pulp kept export prices down And 75 and 76 put sweden way back in the gmp league at a much lower pace than the rest of ocd And it's interesting to remember these days in 74 when this bridging of the gap policy was hailed All over europe as exceedingly farsighted policy the economic council of ocd hailed it And i remember i was invited with some other representatives of industry to a meeting with the the minister of finance when he exposed to us this grand design About having industry building up stocks or waiting for for better times And i was sitting together with the head of the electro luxe company A very hard headed fellow from industry his name is Bertén He said to me he whispered to me They are fools they believe one can store cut flowers Sometimes governments have a tendency not listening to practical man The palmer government reached the election year of 76 in a position very much like Like that of the alanda government in 48 The socialist experiment had failed And the mistakes in the economic policy were obvious While alanda was saved with a narrow margin in 48 Palma lost this election with a big margin The defeat was made bigger by the anti nuclear mood of the swedish people Social democrats having invested heavily in nuclear power Then came something that really we thought never would happen After 44 years of social democratic government suddenly the first non-socialist government In sweden took over it was a sensation That government however inherited an economy much weakened by the bridging of the gap policy Furthermore the increase of the public sector had become self-generating The new government tried desperately to reduce the speed but they failed And the percentage of the gmp covered by the public sector went up to 70 percent They never got a chance to turn the wheel And that is why we say that we had a non-socialist government to carry on social democratic policies The most costly failures came in industrial policy True they stopped the steel mill for 80 project But they continued and even increased the social democratic governments policy or bailing out bankrupt companies in order to safeguard employment You know employment is sacred in sweden The new government naturalized steel mills and shipyards on a scale never seen before The costs were met through heavy loans abroad and the swedish natural debt skyrocket The new government was a coalition of the three non-socialist parties and they could not agree On taxes and on nuclear policy during their six years In power they were reelected in the 79 The non-socialist parties formed no less than four different governments In six years not bad None of these four governments managed to change a policy that had so obviously failed The kinship tradition of using the public sector as a lever to secure full employment was strongly ingrained If a government in sweden accepts Unemployment higher than three percent Then they reckon they will lose the next election kinship followers could not abandon the road. He had once pointed out To them in quite different circumstances in the 30s 50s and 60s They followed that road into a quagmire Not until 81 82 The last year of the no socialist socialist government. There was some sign of a change Inflation was kept down Tax reforms were initiated and efforts were made to cut down the public sector, but it was too late The social democrats won the election of 82 And url of palma came back into power And now we came into a period which Still is on a very interesting period because now we got a socialist government pursuing non-socialist policies And we were seen the rebirth of the market economy The election campaign had been savage and bitter And palma had attacked the government from the left accusing them of thatcherism And of starving the economy by their new Anti-inflation policy More elbow room and less belt tightening became his slogan Repeated every day at meetings all over sweden during that summer of summer autumn of 1982 Promises were made of increased pensions and more money to young families But there were also a few lines at the end of his speeches Saying that it would take some time to clean up the mess And there was a hint for those who listened carefully of some austerity to come The social democrats had made a thorough analysis of the state of the swedish economy And found that a dramatic change of policy had to be made They had to come they had come to the conclusion That the focus of attention had to be turned from the public sector To the private one Profits in industry had gone down dramatically at the end of the 70s And investments were low As the Over-extended public sector could not be increased further The tax burden having reached a record level of more than 50 percent In the tables which have been circulated You see the figures are not as high as that but they do not include social Security, so the figure is more than 50 percent the tax level of gmp With such a tax burden there was really no other alternative than to stimulate the private sector Nevertheless, nevertheless, that was a brave and orthodox unorthodox choice for socialists The new government started with a bang Devaluating the swedish crown by 16 percent They first planned to increase to make it by With 20 percent but at the last minute they had to give in for pressure from the other Nordic countries but by this One bold stroke swedish industry suddenly became highly competitive and profitable The stock market which had feared the return of palmer Went wild with joy and industries found it easy to raise investment capital on the market The new minister of industry declared that there should be no more subsidizing of industry And those companies which could not stand competition had to be weeded out Of course, that was an obvious consequence of the decision to devaluate devaluate the crown But the new signals from the ministry of industry dramatized A complete change of attitude Now after more than four years It is evident that the new economic policy has been successful Investments in industry have soared and so has employment The stock market has shown a vitality and zest that has been somewhat embarrassing to the government Increased taxes on stock market operations have had few negative effects so far The turnover of the stock on stock exchange in one day is now The same as during a whole year at the end of the 70s That is Rather remarkable change the value of stocks has increased by 300 billion swedish crowns That is 43 billion dollars True the social democratic government has had good luck The fall of all prices and of the dollar has given sweden billions in windfall profits But when they are accused of just having good luck They say that it's better to have a govern with good luck than to have one with bad luck That is an argument which is difficult to counter This is in sharp contrast To what happened To the non-socialists during their six years of government With a repeated Knockout blows of a bi-opec But sheer luck Is certainly not the only explanation The new minister of finance cellulo felt and the head of the central bank Bank danis have used the new options for bold and successful policies They have done what their predecessor did not dare to do Changed course The government has also tried hard to check inflation which is now on its way down about four to five percent But much higher than in our competitors in germany and harland and switzerland They have also succeeded in cutting down the deficits considerably Even if there are still is a long way to go to the healthy balance of the 50s and the 60s The liberal strongly market-oriented policy of the social democratic government has some has Has some similarity to the policies in the 30s When a successful devaluation of the crown also became the springboard of success But there is a big difference the public sector Had then a growth potential which was used to stimulate the economy Today that possibility does not exist Of course, it's self-evident that the new unorthodox policy has put strains on the socialist party social democratic party The true believers in socialism Wonder why they have voted for a government which carries out the policy which should Be that of their opponents The unions which form the backbone of the social democratic Movement have forced the part to introduce so-called wage earners funds Through which they want to share profits And obtain an influence on industry through ownership of shares They are also getting interested in the stock market In order to calm the party theoreticians The government has also increased taxes on the rich As i just said the new economic policy put in the market in the center of the carnawak system has been very successful but And and may i add There is a remarkable New optimist in the country But there are still However, two fundamental problems left Which the government has not yet dared to attack and which are very difficult to attack for a social democratic government first of all Our impossible tax system and secondly The overextended and inefficient public sector These two problems are of course interconnected The swedish tax system is in a mess Swedes are more heavily taxed people are the most heavily taxed people in the world And it's more and more acknowledged also by people in the social democratic party That a tax reform is absolutely necessary A few years ago gunna myrdal Characterized our tax system as corrupting the swedish people Making it a nation of small cheaters and tax evaders It's more and more understood that that our taxes are working against the government's effort to get the country moving again The one's progressive character of the tax system has become counterproductive In the sense that it is hitting low income groups harder than the more effluent As a matter of fact our enormously complicated tax system is loophole filled Somewhat like a swiss cheese and those who can afford to hire Skillful tax lawyers are having a good time. I have one The other day the minister of finance made a sensation By praising what he called the reagan tax reform A heresy Which severely shocked the socialist grassroots of the party for whom president reagan is a symbol of dark reactionism but It's impossible to cut taxes and to reform the system without Attacking the gigantic problem over the over extended and inefficient public sector absorbing now about 70 percent And within of the gmp and with an insatiable First for tax money Sweden has increasingly become a country not with a mixed economy, but with a dual economy On one side We have a private sector lean and competitive brimming with vitality Um and plans for expansion On the other there is a public sector bureaucratic in an inefficient Which cannot deliver the services its customers require As to new tax money as no new as no new tax money is flowing into the system The public sector has to cut on Has to cut down on services You know When the public sector has to cut down something it always cut down on services not on on bureaucrats That's this uh a rule Schools cannot hire the teachers they need A new device and a new device has has to had to be introduced classes without teachers That sounds nice Where are the teenagers? Uh, but to my mind This is a symbol of the failure of the whole system There is another serious effect the brain drain The best people avoid a career In the public sector and move instead To the private one The unions in the public sector are using striking as a weapon to increase salaries But the government is firmly fighting back Because raising salaries to in in the public sector means that taxes also have to be raised And today I believe I don't know if our council general is here today Is he here? No, yes, there you are did did the strike erupt? Not yet When I left Stockholm On saturday it was said that there would be a strike on on tuesday and that one would not be allowed To fly into sweden. So I might stay here as a refugee Gustavus Adolfos The government is fighting back as I said and of course The conflict between the government and the unions puts severe strains on the party This is a very serious development The uh the situation in the public sector Because the public But the services which should be produced by the public sector such as education Health and old age care Which are really what the consumers want They cannot be provided In this way The dual economy in my view corrupts the consumption pattern of the citizens As they cannot buy an eye operation for themselves Or a first class teacher for their children They buy gadgets or travel to the canary islands In this way In a strange way The public sector Has a way of of Corrupting The the consumers And making them just Aiming at buying things Exactly as the way that socialists always accuse the capitalistic system for not giving the people what they really want More and more people have come to understand That we have put to put an end to the dual economy By introducing competition and private alternatives As well as new standards of efficiency And quality also to the world of tax-fed public monopoly There is more and more talk about introducing private schools Hospitals and other social institutions in the sphere now completely dominated by government and municipalities the head of the unions Stig Malm Created headlines the other day by suggesting that the public sector should be open to private initiatives It is not only in baying things have changed dramatically The big question is however Can the social democrats forget their ideology to the extent that is required To make real reforms possible of the public sector of the taxes of the tax system The non-socialist parties claim that only they can do it In the next general election in 1988 the swedish people will decide who will do it Whatever happens In my view the dual economy must disappear To quote Lincoln no country can live half slave half free What would Keynes say about sweden if he was with us here today? I think he would give the present government high marks for what they have done Stimulating and vitalizing the weak parts of the economy In the 30s it was the public sector And in the 80s the private one He would also be pleased by seeing our low inflation figures And at the same time unemployment figures of only 2.5 to 3 percent I'm also sure he would enjoy the pleasure of operating on the Stockholm stock exchange Keynes made a fortune in the city of London in the 20s. He could have doubled or traveled it in Stockholm in the 80s But he would have been surprised I'm sure To see the tremendous comeback of the market As a basis of economic policy If you if you uh Years ago I met that famous American Multi-billionaire Arman Hammer You know One of he's the owner of occidental oil and he owns a lot of other things too And uh since many many years back he has also been a link between the Soviet Union and and the United States And I met him in Stockholm a few years ago And had a long talk with him. He's exceedingly interesting man And uh I I I must say that there is an interesting book to read and that is his self biography Uh the title of that book is very fitting for that man larger than life And he told me that uh in 1924 He had uh he was in Moscow and he got an urgent message that he should immediately come up to the Kremlin to see Lenin And he found Lenin very ill And um they talked and just before he left Lenin he took Arman Hammer's hand and and brought him close to him and then whispered in hammer's ear You know almond Socialism doesn't work This is at least what arman hammer told me I don't know if anyone was present When canes died but uh Perhaps arman hammer was there too Uh, but I think Canes would have could have said My policies work And they will work at least up to the fifties and the sixties At least in sweden And we are very proud still to be canesian in my country. Thank you We've taken a quick poll of the powers that be and decided that as late as the evening is We will conclude the program for this day Reconvening at 10 a.m. For The lecture by professor james toben Which will be preceded by the conferral of the honorary degree ceremony We hope today's activities and festivities and we look forward to seeing you tomorrow. Good evening