Monday, 31 July 2017

The importance of characterizing your random inputs and their influence in your probabilistic process.

Hi everyone,

So its time for a new message in the blog about work.

I told you before that I was looking at these very cool models called Kriging models. Well, I m still looking at them, but now I have been inveting some time on the analysis if their design of experiments, or, the variables that are used to create the model that, lets say, stay on our x axis (y axis will give the output, just imagine a 2D curve).

Why is it important to look at these variables before any further progress? I have the surrogate model, I have the means to compute the results, why spend some time doing tests with these variables?

Well, maybe you don't need, but lets see why it is important.

When you run an experiment some variables affect much more the output of your experiment than the other. So, if a variable is 98% responsible for the variations in your output why should you consume your time looking at the other variables. You just do it once, you quantify these relations between variables and then in future experiments you now "whats happening". This is of particular interest in the case where you're going to repeat your experiments a lot!

But do not forget, this preliminary analysis, usually called, sensitivity analysis, needs to be very well done. Otherwise you may neglect important effects. Like coupled effects or similar.

So, you spend some more time in this and in the future you just save some time. We just need to believe that the balance will be positive. And it is very likely to be.

In cases where budget and time is a limited resource (in other words, always), this can be very interesting.

I believe and I heard it many times before from big scientists that, no additional complexity should be added to the analysis if it is not needed. Or, that "simple is beautiful".

In the case of Offshore Wind Turbine Towers there are many many variables that affect the behaviour of the turbine. As a very complex technology, its analysis is time consuming, so, characterizing well the different variables that affect the turbine is important before going on loops trying to do new things. Basically, before trying intensive research !
Even more when you work on probailistic research, quantifiying uncertainty adds a new layer of complexity and effort, so this is even more important.

To analyse the influence of the different variables there are many different techniques, Screening, Sobol, Anova, KL divergence, you can find many in the literature. Also, different techniques exist to simulate experiments, as the simple Monte Carlo or the Latin Hypercube Sampling. If variables ar correlated it gets a bit more complex, but still feasible.  You can find many of them in literature.

Well, all this just to tell you that despite looking a secndary task from your main topic, or boring in some way, sensitivity analysis are very relevant and they can be a milestone when you're doing research in terms of saving time and resource and in the end your skin. Its like that subject that you're never into during the university but suddendly when you start working you realise it is much harder than it looks and much more important.

I know I know, some of you will now say....I didn't need 95% of the university courses.... bu this one for sure you needed and for sure it was diluted in the many different courses and you probably never had it to its full extent.

I recomend some reaidng on the topic. Very interesting indeed!

See you soon!

Monday, 10 July 2017

ESREL2017 Conference and Renewable Energy

Hi everyone! 

Just last month was the ESREL conference and I had the opportunity to participate and present some of the work that I have been developing on OWT reliability. 

ESREL its quite a big conference, probably the biggest or one of the biggest in Europe about reliability. 
I have to say that it was an interesting experience, met lots of interesting people. Other ITN students  (working on wind, which makes me happy to see such an interest in reliability and addressing uncertainty for OWT. But mostly, the opportunity to interact in an international conference and present some work, reuniting some good comments, good contacts, that was great.

 Here I am doing the presentation, still need to train a bit more to lose some stiffness in the stage :) 

Next I will be at home, Madeira, for a Conference in September called ICSI2017. I hope at least so interesting as this one.

Okay okay, these things of conference and all is interesting, but... More than important to get yourself and your "brand" known...

It looks like in renewable energy we are going back in time (in fact in everything not only renewable energy) and we need to work together to fight some of these ideas/seeds that are being implemented slowly on people heads. 

Some time ago I saw this amazing video by Neil deGrasse Tyson (below), one of the most outreaching persons in science that always has one of those arguments in the sleeve. I think it mirrors how surprising in a negative sense is this discussion over science, global warming and everything. 

I believe, and believe well applied here, that it really looks silly when you hear all these arguments that contradict some scientific facts. 

It is true that science can be wrong, and it happens, but just the fact that people identify patterns in their studies, that means that something is happening there and it does not matter if it is important or not on a first phase.  

Some people criticize how science is made, and on how some studies are accepted with low confidence and all that but in fact that is not true. 

But be aware, things are published when patterns and occurrences show that something that is widely correlated is happening. The results show it. You, that have access the data, may be interpreting the results on your own way, maybe wrong, but the truth is that something that is widely correlated is happening. It is not just something that happened by luck in one experiment. It can start like that, but then you repeat and repeat ... and if the pattern is there...its just not a matter of luck...

Then, your results go to be reviewed by other scientits...and believe is a competitive world...
It is like you work for a company, lets say for example McRui, and someones presents you a burger from Burger Rui that is undoubtedly good. Well, you will try to say that it is no good because its painful to believe that burgers better than yours may exist. But if it really is, you don't have other choice than accept it and try to improve your own burgers. Remember, science is supported on quality, not on anything else...   

And that thing of fake results does not exist. See the example, one of the most prominent guys of anti-vaccination was caught in the past because of its biased results...and lost his degree. So that myth does not exist. Lie has short legs. And shorter than usual in science. 

Well, there is lot to be said, but remember :
You cannot say that you do not believe on a scientific fact. That just does not make sense. You can choose to believe or not in many thing, just not on science. Its not a matter of whether you believe or not. Please stop that. 
If you really don't "believe" in the global warming by human hands (apart from other effects we are indeed accelerating it) or vaccines or whatever and on the importance of the renewable energy, please go read a bit about it. 

I challenge you to do some science to prove the contrary. And make it accepted by a renowned entity ! 

See you soon, 

Monday, 29 May 2017

Applying the Kriging Models in Structural Reliability

Hi all,

I will then, as promised, talk a bit today about the Kriging surface models.
These models are nothing more than surrogate models that account for a certain level of uncertainty. They are widely used for many fields, but their initial application goes back to geostatistics.

They are an interesting tool that we don't hear much about when learning Engineering. On the other hand, if you talk with a Geologist they will know for sure about what you're talking. I share my office with some people from Geology, and they do. They are all happy when they see me working with it... it's like... "look at this Engineer in trouble with these simple Kriging" haha

Well, as I told before these are nothing more than interpolators. The image below will help you understand (courtesy of Wikipedia):

Kriging interpolation example (courtesy of Wikipedia)

The idea of the Kriging surrogate model is to approximate a group of points in a N-dimensional space with a curve. Like you would do with a 2nd, 3nd or n degree polynomial. But in this case, we assume that the space between the points we do not know as an error which is Gaussian distributed.
Let's see, you see the red dots, these are the points that we know. If we assume a deterministic interpolation scheme we will have the red line or another line (depending on the order of the approximation) that will in the limit be the same as the trimmed blue line. For such a complex model it's hard to have exactly the blue trimmed line if we use a reasonable amount of points, so we are very likely to be induce in some kind of error in our prediction of the variation of z with x.

Where does the Kriging surface comes into play then? Well, if you assume the Kriging surface for the same set of points you will have the gray area, mixed with the red line. This means that you know that your blue trimmed lined will be, with 95% confidence, inside that area. (!! but it can be out! The Gaussian distribution tails are not bounded). So, let's say it is like a model, that fits infinite curves to a certain group of points.
With one single sample of points for all the domain of x from the Kriging:
If you're lucky you will have the exact same blue curve...well....very very lucky....
If you're not, you will end up with an approximation that is worst than the red line (which is the expected curve). If you take many many "samples of this curve" you will end with the red line, the expected curve.

Can you see the interest now? They are indeed an amazing piece of math. You can tell, well, whats the point? It's all left to the luck? Or, I'll end up with a red curve anyway?

Well, do not forget that so many things in this world follow a Gaussian distribution... and a tool like this one, which is simple and beautiful, can be widely implemented in this world for much more than just approximating curves or a couple of points.

If you have a system's output that is Gaussian distributed and depends on many variables you can use this, like I am doing. If you're not sure about your curve and you want some degrees of uncertainty, here we are :) etc etc...

I am pretty sure that you're amazed, because the first time I saw this I was like: "This is way I am not going anywhere, such a simple and beautiful tool and I couldn't even think remotely on this existing inside my ignorance" :)

It was nice to write to you all.
For those who know me... I know I know...lately it's Kriging for this, Kriging for that... Kriging for beers... Kriging tatoo...I can't avoid it. I love the concept hehe
But I know I know, extra care in the application of them, as good-sense is needed.

See you soon and I hope you find the post interesting,

Monday, 24 April 2017

Update on research - Prologue to the probabilistic analysis of Offshore Wind Turbines (OWT)

Hello !

Here we are again, this time to talk a bit about work.

As you may know from previous posts I have been working on characterizing probabilistically the OWT towers, specifically for the fatigue analysis.

The fatigue analysis recomended for the design of OWT towers usually involves a very high number of simulations and some statistical distributions.
What is done is to run multiple simulations that reproduce the loads on the OWT; apply a methodology to count the loads that happen in every simulation; use the well know fatigue curves and linear damage sumation and then work on reproducing the best the complete lifetime of the turbine.
Obviously, it is quite unfeasible to make simulations for the full 10, 20 or many L years of simulations. So, what is usually done is to, using all the loads the we can obtain, extrapolate the loads for the period of time we want to design. This is assuming that the high load ranges will have the most impact on the fatigue life.

It is easy to understand that ideally the L years of life should be assessed completely, but that is a hard task. Even not "running" all the L years of loads accomplishing the design to fatigue is a heavy task. Now imagine if you want to run it for a probabilistic approach? Not easy. That would mean, for instance, simulating multiple turbines and see the variations in the extrapolation if you want to focus only on the loads. Naturally, there are other uncertainties that have also some influence in the expected life.

I have been working to implement a new methodology to assess the fatigue of the OWT and that is specifically working with Kriging surrogate models. The Kriging surrogate models are an amazing tool originnally developed for  geostatistics that interpolates function in a Gaussian process. Is true, I was amazed the first time I ran into them. Of course, their Gaussian characteristic which accounts for some uncertainty and the possibility to interpolate functions made them quite popular for reliability. Therefore, recently their usage spread into the reliability world quite significantly.

As I believe they are a very interesting tool, I will keep a full post for them, and that will be the next one.  For now this was a small introduction to present them.

Regards and see you very soon. This time as the topic is already introduced I won't be able to escape ;)


Sunday, 19 March 2017

New working paradigm

So, two posts ago we started a brief discussion about how work is faced nowadays, introducing also, the fact that the working reality is (looking like) changing. 

People have been spending lots of time thinking on what is happening and I am not different. So I also brainstorm a bit about what is really happening everywhere... With so much crazy stuff happening around the world lately. 

So, the exercise is simple: Let's look around us and think on what are we seeing everywhere.

Unemployment is in fact a big problem today as the society and capitalism is quite built on work. With it comes big migrating movements, further social inequality, is deeply connected with criminality, and etc etc... 

Lots of the recent world changes, and specially the growing trends of radicalism are also connected to it. People are not happy in general and blame what they shouldn't blame, they are longing for change. Opportunists appear, as in EUA or UK appear and tell people exactly what they want to hear. In the end, you can't blame people for, in desperation or unhappiness, voting for change. 

I read recently about the election in the EUA and how the middle regions EUA contributed strongly for the election of the current president. It stated that in average a middle class worker in the primary sector in these regions earned today the same as 40 years ago. Being this fact a reality, it is normal that these people are moving for change instead of keeping the same system. 

In the UK things present the same trend. The big argument behind the Brexit was deeply connected to protectionism and work issues. 

Okay, it's happening and its here among us. Everyone is worried about work issues, the change in lifestyle and not being able to have a "home". Everyone is voting for a change, and waiting for the measures to come with people that bring new ideas, that are going to "protect" the countries and etc...

Well, in fact its not going to happen. Everyone is searching for the answers in the past, and they are not there. People still move around where the few working opportunities are but let's see: 

I always find funny when now and then Portugal presents the unemployment statistics and they are always decreasing (lately). So, let's see, world population is steadily increasing, work are decreasing due to automated work, so how can the unemployment be decreasing? Well, maybe if the population decreases... because decrease of  automated work is not happening for sure... 

It is proved that a huge share of the current work can be replaced by automats. It is proved that even the highly "thinking" jobs will be replaced in the future by machines. So, how will we be able to keep everyone occupied and earning money in the future? It is much more interesting for a business to have a machine that almost needs no attention than a person that is very demanding... 

Work is changing to the point that now, the problem is work itself. We are wasting the last moments debating redundant stuff by electing all these weirdos to conduct countries, but just to realize that they do not have the answer too....

I believe that the problem is much more on the society roots than everyone is realizing. We can be here worried and criticizing everyone and how the life turned so harsh...

In the past people lived to work, they still do. But now, we need to adapt the coming generations for the change in the work paradigm and teach these people to live in other ways. How should we do this, that is a big question. 
But for now, I believe we need to face work as the new social problem not in the sense that we need to find new works but in that they won't come again. Its a message that needs to be spread I think! 

A big text just to talk a bout a drop in the ocean of the problems we face today :)

Sorry this is not really connected to wind energy, but its a message that needs to be spread as i told. Next post, very soon, we will be talking about wind and one issue I have been working on. 


Sunday, 5 February 2017

End of secondment in Aberdeen and Training week Barcelona

Hi all ,

Sorry for the disappointing update frequency of this blog, its really a hard task a "not pure breeded social guy". That is why we all want to follow these guys that live of youtube and blogs, but almost anyone can make it :) 

Well, I will do a quick update of the things at work and talk about how was the second phase of my secondment. 

As you know I am now in Aberdeen. A city that I have to tell you is not as bad as as I thought in first place. I was thinking earlier this week, and its true, expectation is the secret for a happy life. Everyone was before, you're going to Aberdeen in Winter? Good luck! Or... you'll go crazy...etc etc 

In the end it wasn't that bad. Its a small city but very nice. Its grey, its true, but has its own spirit. The times were better before when oil was "pumping" people say, well... its the time for new clean energy...I say :) use that positive tension to foment it.

So, this is my last week here. Well, I enjoyed but its time to go back. It was a very enriching experience. 

Talking a bit about my work, which I rarely do but I should. 

These for months of secondment contributed for settling interesting knowledge in the analysis of offshore wind turbines, modelling them, analysing loads, getting the feeling of "something is wrong with these results" and more,  much faster than I would do anyway on my own.  This helped to boost my work a lot and I have to say, I even exceeded my expectation on how much I could get in  this 4+a bit months. Again, low expectations are the secret ! Haha 
It went great, now its time to go back, settle knowledge and return in the future. 
I have been working in applying probabilistic methodologies to Offshore wind turbines in the specific case of the fatigue. Fatigue is a very challenging topic for offshore wind turbines, it can drive the failure of towers for example but also its quite resource consuming. Its good to melt your brain ! 

Lets see, now that things are more settled in the analysis and understanding of the dynamics of the turbine, what value can be added to its probabilistic analysis. I already have very nice ideas that were submitted to a conference, but the complexity is big and I hope to talk about them here very soon. 

You know that we had a trainning week in January? Yes, I would like to leave here a special thanks to all the organisers from TRUSS and UPC. 
It was great, again, Its crazy how much you can learn when the teaching process is carefully aimed. We should really think about this...

Anyway, here we are; all happy. This is us: 

And this is us v them (some of them...): 

Well, I left a topic unfinished I hope to finish it next time. I'll also bring more news on work development too.

Tchin tchin ! New design too


Sunday, 1 January 2017

End of first phase of secondment and 2017 greetings

Hello guys,

Here I am again to tell you a bit more about my recent adventures. 

Last month I just finished the first phase of my secondment in London. What this means?! Yes, I left London...I'm now in Aberdeen, but midway I would like to share some of what I learn and how some things bother me...hmmm..

Overall the experience of the secondment in London was great! I won't say everything was a sea of wasn't. The secondment experience can be quite disruptive. Among going to a big city, changes of house, one thousand travels, etc etc your energy gets "pulled" out of you quite fast and that can be really disruptive for your day to day work. 

Fortunately, I experienced all of that, which is also an important part of the learning process, but from the work side I had a very productive learning experience that really minimised all the negative effects I mentioned.
I know I was lucky. When going on a secondment these conditions are unlikely to be found. That's why I would like to thank all the people that I worked with during these two months. (With a special thanks to my supervisor in Lloyd's from whom I learned crazy amount of stuff ). 

They didn't save me from some little positive embarrassment in the goodbye with a speech (which is traditional from long term workers)... it was funny... So, here, thank you all!

Also, some days after leaving I won there (even not being there) a bottle of wine in a raffle...its funny...I never get one win in these things....and when I get....I'm not there hahaha

Now, talking about other things... 
One of the things that I enjoyed in Lloyd's was the working culture, and with that I learned a lot! I believe is something common in the places I got to know recently. There the culture is highly focused on the worker and it's life.

This is really great and positive and I am highlighting it here because it is something that always disturbed me as someone that sees the working culture decay everyday with the current mess we have in the world (Portugal is a very good "generalized" example for instance where the culture of work being already bad has also been decaying since the economical crisis). 

I always wondered how can lots of Portuguese companies sum so many hours of work and yet we are still quite a not very rich country comparing with the European average..(there are exceptions of course)? It took me ages to understand, and I didn't yet...
We know that there are numerous macroscopic "things" that explains this. Although, from the side of the work I believe we are doing it all wrong. During these 2 months I realised that having some positive "worker" working culture is really important.

First point is, working too many hours is against your production as this usually means, for instance, having less time for yourself . And regardless of the job brainstorming or physical complexity, you need that time. I experienced both sides before, and this right balance much fomented by Lloyd's worked really well.

Second point, is imeasurable how much people can do when they are spiritually well. Okay, motivation is almos eveything but having a positive working culture really helps..its not just something adopted from the trendy IT companies out of nothing... it really works.  

Well, the negative part is that currently there's no point in adressing deeply the talk about working culture.
There are companies that always worked bad (most of them), there are companies that always worked well. Maybe in the past the divergence and discomfort of the people working didn't show as much as now and that´s not because the new people are weak (as many people say) or are used to facilitism.
It is because in the past, there was plenty to everyone, so that any discomfort was covered by this plenty of advantages and economic resources given to the workers (e.g. extra-hours paid, crazy opportunities of progressing career, etc). Today, things are really different.

Anyway, its nice to defend and  foment the working culture. We have seen lots of entities working hard on that but in reality the very short future tells us that the real challenge is what to do with people and their free time...

Starting 2017 in big style with a heavy message. Sorry! I had started this text in 2016  and in the first of the year I was lazy to start another text again...

Happy New Year !!! Enjoy 2017 and lets work together for the best success in this crazy changing world!

Ill be back soon with the continuation of my experience and reflection on working culture, or lets say, "non-working" culture !