I'm using the Aconcagua measurement library in Pharo. I've had a lot of success using it to model things like days and kilometers, but have encountered an interesting problem where converting between units requires information on the underlying substance being measured. The formula for expressing the amount of a substance in air in parts per million, given the amount in milligrams per cubic meter is:
; where mw is the molecular weight of the material.
I'm envisioning usage like:
tlvCO := carbonMonoxide tlv. "returns the Threshold limit Value as 29 mg/m3"
...
tlvCO convertTo: PPM "where PPM is an Aconcagua unit"
The problem is that, while the examples I've seen of measurements in Aconcagua are contain in themselves all the info you need for conversion, in this case, you have to know the molecular weight of the underlying substance being measured. Thus mg/m3 -> ppm is not inherently meaningful. A properly formed question would be mg/m3 of ammonia -> ppm.
My instinct is to either:
create a new class like MaterialQuantity which has a material and a measure, or
create a special unit subclass that has a material
But I'm not 100% sold and would like some input...
I don't think that molecular weight is part of the unit, but part of a calculation, like the 24.45 (which is not clear, but it seems that is an average you consider for air molecular mass).
I am not sure that ppm is a unit that you can convert to a density unit, because they belong in different domains.
As far as i understand, you need to reify tlv as a compound unit or formula, which you can ask for the element. Then you could simply do something like [:tlv | tlv * ( 24.45 / tlv element) ]
Related
I am new to modelica, and i don't have this much experience in it, but i got the basics of course. I am trying to model a micrfluidic network. The network consists of two sources of water and oil, controlled by two valves. The flow of the two mediums interact at a Tjunction and then into a tank or chamber. I don't care about the fluid properties of the mixture because its not my purpose. My question is how do redeclare two medium packages (water and oil) in one system component such as the Tjunction or a tank in order to simulate the system. In my real model, the two mediums doesn't meet, becuase every medium passes through the channels at a different time.
I attached the model with this message. Here's the link.
https://www.dropbox.com/s/yq6lg9la8z211uc/twomediumsv2.zip?dl=0
Thanks for the help .
I don't think you can redeclare a medium during simulation. In your case (where you don't need the mixing of the two fluids) you could create a new medium, for instance called OilWaterMixture, extending from Modelica.Media.Interfaces.PartialMedium.
If you look into the code of PartialMedium you'll see that it contains a lot of partial ("empty") functions that you should fill in in your new medium model. For example, in OilWaterMixture you should extend the function specificEnthalpy_pTX to return the specific enthalpy of your water/oil mixture, for a certain water/oil mixture (given by the mass fraction vector X). This could be done by adding the following model to the OilWaterMixture package:
redeclare function extends specificEnthalpy_pTX "Return specific enthalpy"
Oil = Modelica.Media.Incompressible.Examples.Essotherm650;
Water = Modelica.Media.Water.StandardWater;
algorithm
h_oil := Oil.h_pT(p,T);
h_water := Water.specificEnthalpy_pT(p,T);
h := X[0]*h_oil + X[1]*h_water;
end specificEnthalpy_pTX;
The mass fraction vector X is defined in PartialMedium and in OilWaterMixture you must define that it has two elements.
Again, since you are not going to actually use the mixing properties but only mass fraction vectors {0,1} or {1,0} the simple linear mixing equation should be adequate.
When you use OilWaterMixture in the various components, the error log will tell you which medium functions they need. So you probably don't need to extend all the partial functions in PartialMedium.
I wish to create efficient frontiers for portfolios with bounds on both weights and costs. The following code provides the frontiers for portfolios in which the underlying assets are bounded with minimum and maximum weights. How do I add to this a secondary constraint in which the combined annual charges of the underlying assets do not exceed a maximum? Assume each asset has an annual cost which is applied as a percentage. As such the combined weights*charges should not exceed x%.
lb=Bounds(:,1);
ub=Bounds(:,2);
P = Portfolio('AssetList', AssetList,'LowerBound', lb, 'UpperBound', ub, 'Budget', 1);
P = P.estimateAssetMoments(AssetReturns);
[Passetmean, Passetcovar] = P.getAssetMoments;
Correlations=corrcoef(AssetReturns);
% Estimate Frontier
pwgt = P.estimateFrontier(20);
[prsk, pret] = P.estimatePortMoments(pwgt);
Mary,
having entered another set of constraint principles into the model, kindly notice, that the modified efficient frontier problem is out of the grounds of a guaranteed convex-optimisation problem.
Thus one may forget about a comfort of all the popular fmicg(), l-bgfs et al solvers.
This will not simply have a SLOC one-liner to get answer(s) out of the box.
Non-linear problems will require ( the wilder, the more ... ) you to assemble another optimisation function, be it either
a brute-force based scanner,
with a fully orthogonal mesh scanned, with "utility function" defined so that, as the given requirement states, it incorporates also the add-on cost-of-beholding a Portfolio item
or
a genetic-algorithm based approach,
in a belief, the brute-force one might become as time-extensive as to cease to be a feasible approach and a GA-evolution may yield acceptable sub-optimal (local optima) outputs
Is there a method of using the exponent properties of LabView units for carrying custom units? For example I would find it convenient to use milli-Amperes instead of Amperes in my data wires.
My first attempt at doing so looks like this, but trying to get the value out at the end gives me nothing.
I would find it convenient to use milli-Amperes instead of Amperes in my data wires
For a wire, it's not possible, and it's not a problem, here's why:
I'm afraid what you want make little sense, since you're milli-Amperes instead of Amperes refers to representing your data, while a wire is just raw data. Adding the milli- to a floating point changes the exponent, not the mantissa, so there's no loss or gain of precision in the value that your number carries.
Now if we talk about an indicator which is technically a display of the wire value, you change the unit from "A" to "mA" to have the display you want.
Finally, in your attempt with "set numeric info", the -3 factor added next to Amperes means the unit is A^-3, not mA.
You can use data that don't use units, however than you will loose your automatic check of the units.
For display properties you can tweak the display format to show different outputs:
This format string is constructed as following:
% numeric
^ engineering notation, exponents in multiples of three
# no trailing zeros
_6 six significat digits
e scientific notation (1e1 for instance)
The prefix is the best way to affect the presentation of the value on a specific front panel.
When passing data from VI to VI, the prefix is not passed, and the data uses the base ( Amps, Volts, etc...)
In my example below, the unitless value 3 is assigned units of Amp in mA.vi. The front panel indicator is set to show units of mA.
In Watts.vi I multiply the Amps OUT of mA.vi by a constant of 9V and the result is wired to the indicator x*y.
x*y has units of W and I changed the prefix to k for presentation.
The NI forums have several threads that report certain functions (square and square root specifically) can cause unit errors or broken wires. Most folks don't even know the units capability exists, and most that do have tried and abandoned them. :)
I am running a wavelet transform (cmor) to estimate damping and frequencies that exists in a signal.cmor has 2 parameters that I can change them to get more accurate results. center frequency(Fc) and bandwidth frequency(Fb). If I construct a signal with few freqs and damping then I can measure the error of my estimation(fig 2). but in actual case I have a signal and I don't know its freqs and dampings so I can't measure the error.so a friend in here suggested me to reconstruct the signal and find error by measuring the difference between the original and reconstructed signal e(t)=|x(t)−x^(t)|.
so my question is:
Does anyone know a better function to find the error between reconstructed and original signal,rather than e(t)=|x(t)−x^(t)|.
can I use GA to search for Fb and Fc? or do you know a better search method?
Hope this picture shows what I mean, the actual case is last one. others are for explanations
Thanks in advance
You say you don't know the error until after running the wavelet transform, but that's fine. You just run a wavelet transform for every individual the GA produces. Those individuals with lower errors are considered fitter and survive with greater probability. This may be very slow, but conceptually at least, that's the idea.
Let's define a Chromosome datatype containing an encoded pair of values, one for the frequency and another for the damping parameter. Don't worry too much about how their encoded for now, just assume it's an array of two doubles if you like. All that's important is that you have a way to get the values out of the chromosome. For now, I'll just refer to them by name, but you could represent them in binary, as an array of doubles, etc. The other member of the Chromosome type is a double storing its fitness.
We can obviously generate random frequency and damping values, so let's create say 100 random Chromosomes. We don't know how to set their fitness yet, but that's fine. Just set it to zero at first. To set the real fitness value, we're going to have to run the wavelet transform once for each of our 100 parameter settings.
for Chromosome chr in population
chr.fitness = run_wavelet_transform(chr.frequency, chr.damping)
end
Now we have 100 possible wavelet transforms, each with a computed error, stored in our set called population. What's left is to select fitter members of the population, breed them, and allow the fitter members of the population and offspring to survive into the next generation.
while not done
offspring = new_population()
while count(offspring) < N
parent1, parent2 = select_parents(population)
child1, child2 = do_crossover(parent1, parent2)
mutate(child1)
mutate(child2)
child1.fitness = run_wavelet_transform(child1.frequency, child1.damping)
child2.fitness = run_wavelet_transform(child2.frequency, child2.damping)
offspring.add(child1)
offspring.add(child2)
end while
population = merge(population, offspring)
end while
There are a bunch of different ways to do the individual steps like select_parents, do_crossover, mutate, and merge here, but the basic structure of the GA stays pretty much the same. You just have to run a brand new wavelet decomposition for every new offspring.
I have a game I am working on that has homing missiles in it. At the moment they just turn towards their target, which produces a rather dumb looking result, with all the missiles following the target around.
I want to create a more deadly flavour of missile that will aim at the where the target "will be" by the time it gets there and I am getting a bit stuck and confused about how to do it.
I am guessing I will need to work out where my target will be at some point in the future (a guess anyway), but I can't get my head around how far ahead to look. It needs to be based on how far the missile is away from the target, but the target it also moving.
My missiles have a constant thrust, combined with a weak ability to turn. The hope is they will be fast and exciting, but steer like a cow (ie, badly, for the non HitchHiker fans out there).
Anyway, seemed like a kind of fun problem for Stack Overflow to help me solve, so any ideas, or suggestions on better or "more fun" missiles would all be gratefully received.
Next up will be AI for dodging them ...
What you are suggesting is called "Command Guidance" but there is an easier, and better way.
The way that real missiles generally do it (Not all are alike) is using a system called Proportional Navigation. This means the missile "turns" in the same direction as the line-of-sight (LOS) between the missile and the target is turning, at a turn rate "proportional" to the LOS rate... This will do what you are asking for as when the LOS rate is zero, you are on collision course.
You can calculate the LOS rate by just comparing the slopes of the line between misile and target from one second to the next. If that slope is not changing, you are on collision course. if it is changing, calculate the change and turn the missile by a proportionate angular rate... you can use any metrics that represent missile and target position.
For example, if you use a proportionality constant of 2, and the LOS is moving to the right at 2 deg/sec, turn the missile to the right at 4 deg/sec. LOS to the left at 6 deg/sec, missile to the left at 12 deg/sec...
In 3-d problem is identical except the "Change in LOS Rate", (and resultant missile turn rate) is itself a vector, i.e., it has not only a magnitude, but a direction (Do I turn the missile left, right or up or down or 30 deg above horizontal to the right, etc??... Imagine, as a missile pilot, where you would "set the wings" to apply the lift...
Radar guided missiles, which "know" the rate of closure. adjust the proportionality constant based on closure (the higher the closure the faster the missile attempts to turn), so that the missile will turn more aggressively in high closure scenarios, (when the time of flight is lower), and less aggressively in low closure (tail chases) when it needs to conserve energy.
Other missiles (like Sidewinders), which do not know the closure, use a constant pre-determined proportionality value). FWIW, Vietnam era AIM-9 sidewinders used a proportionality constant of 4.
I've used this CodeProject article before - it has some really nice animations to explain the math.
"The Mathematics of Targeting and Simulating a Missile: From Calculus to the Quartic Formula":
http://www.codeproject.com/KB/recipes/Missile_Guidance_System.aspx
(also, hidden in the comments at the bottom of that article is a reference to some C++ code that accomplishes the same task from the Unreal wiki)
Take a look at OpenSteer. It has code to solve problems like this. Look at 'steerForSeek' or 'steerForPursuit'.
Have you considered negative feedback on the recent change of bearing over change of time?
Details left as an exercise.
The suggestions is completely serious: if the target does not maneuver this should obtain a near optimal intercept. And it should converge even if the target is actively dodging.
Need more detail?
Solving in a two dimensional space for ease of notation. Take \vec{m} to be the location of the missile and vector \vec{t} To be the location of the target.
The current heading in the direction of motion over last time unit: \vec{h} = \bar{\vec{m}_i - \vec{m}_i-1}}. Let r be the normlized vector between the missile and the target: \vec{r} = \bar{\vec{t} - \vec{m}}. The bearing is b = \vec{r} \dot \vec{h} Compute the bearing at each time tick, and the change thereof, and change heading to minimize that quantity.
The math is harrier in 3d because of the need to find the plane of action at each step, but the process is the same.
You'll want to interpolate the trajectory of both the target and the missile as a function of time. Then look for the times in which the coordinates of the objects are within some acceptable error.