That sounds reasonable, it also seems to me that this might be the best place to start implementing the adjoints since the linearized residuals are already implemented.
On 20 April 2015 at 09:05, Alf Birger Rustad <[email protected]> wrote: > Hi Tobias, > > Access to adjoints is interesting for more of us. We have not been able to > prioritise it, but getting adjoint output is quickly moving up the list. > However, I would be most interested in seeing the functionality in our most > capable simulator, which today is flow (found within the opm-autodiff > repository). > > Cheers, > Alf > > ------------------------------ > *From:* Opm [[email protected]] on behalf of Tobias Ritschel [ > [email protected]] > *Sent:* Sunday, April 19, 2015 1:08 PM > *To:* [email protected] > *Subject:* Re: [OPM] Opm Digest, Vol 31, Issue 5 > > Alright, I'll continue with the sim_example.cpp, I just wanted to make > sure. I think I'll have a look at the MRST code, I guess it should be a > good starting point. Some of my fellow students are using MRST for > optimization and it seems to work quite well, but my master thesis (which I > am currently working on) is concerned with high performance computing so > I'll stick to OPM and use PETSc/TAO for the optimization. For now I am only > concerned with two-phase immiscible flow but I'll let you know of my > progress. > > Kind Regards > > On 19 April 2015 at 12:00, <[email protected]> wrote: > >> Send Opm mailing list submissions to >> [email protected] >> >> To subscribe or unsubscribe via the World Wide Web, visit >> http://www.opm-project.org/mailman/listinfo/opm >> or, via email, send a message with subject or body 'help' to >> [email protected] >> >> You can reach the person managing the list at >> [email protected] >> >> When replying, please edit your Subject line so it is more specific >> than "Re: Contents of Opm digest..." >> >> >> Today's Topics: >> >> 1. Derivatives from solvers in opm-autodiff (Tobias Ritschel) >> 2. Re: Derivatives from solvers in opm-autodiff (Atgeirr Rasmussen) >> >> >> ---------------------------------------------------------------------- >> >> Message: 1 >> Date: Sat, 18 Apr 2015 15:11:26 +0200 >> From: Tobias Ritschel <[email protected]> >> To: [email protected] >> Subject: [OPM] Derivatives from solvers in opm-autodiff >> Message-ID: >> <CAJcuCB34EoqUw6c8-10_W= >> [email protected]> >> Content-Type: text/plain; charset="utf-8" >> >> Hi >> >> I would like to use OPM for optimal control of injection and production. >> As >> such I need the derivatives/sensitivities of the a given objective >> function >> with respect to controls. This can be calculated using the discrete >> adjoint >> method which in turn requires derivatives of the residuals with respect to >> the dynamic variables and controls. >> >> I can see that there are some solvers such as SimulatorIncompTwophaseAd >> and >> ImpesTPFAAD, which I guess uses Automatic Differentiation. Is it possible >> to extract relevant derivatives from these functions, e.g. by using the >> function LinearizedBlackoilResidual and FullyImplicitBlackoilSolver? >> >> I am currently modifying the sim_simple.cpp example but if the >> functionality is implemented in one of the solvers in any way, I would >> prefer to use them. >> >> Kind Regards >> Tobias >> -------------- next part -------------- >> An HTML attachment was scrubbed... >> URL: < >> http://www.opm-project.org/pipermail/opm/attachments/20150418/5a19d9f9/attachment-0001.html >> > >> >> ------------------------------ >> >> Message: 2 >> Date: Sun, 19 Apr 2015 08:18:25 +0000 >> From: Atgeirr Rasmussen <[email protected]> >> To: OPM Mailing List <[email protected]> >> Subject: Re: [OPM] Derivatives from solvers in opm-autodiff >> Message-ID: <[email protected]> >> Content-Type: text/plain; charset="us-ascii" >> >> Hi! >> >> We have not yet implemented the adjoint method in OPM. >> We do indeed use Automatic Differentiation (AD) which should make it >> relatively easy (compared to without AD) to implement adjoints. If you'd >> implement this I would certainly be interested! >> >> It should also be noted that if you have access to Matlab, there are >> adjoint implementations in MRST's solvers. >> >> Atgeirr >> >> >> 18. apr. 2015 kl. 15:11 skrev Tobias Ritschel <[email protected]>: >> >> > Hi >> > >> > I would like to use OPM for optimal control of injection and >> production. As such I need the derivatives/sensitivities of the a given >> objective function with respect to controls. This can be calculated using >> the discrete adjoint method which in turn requires derivatives of the >> residuals with respect to the dynamic variables and controls. >> > >> > I can see that there are some solvers such as SimulatorIncompTwophaseAd >> and ImpesTPFAAD, which I guess uses Automatic Differentiation. Is it >> possible to extract relevant derivatives from these functions, e.g. by >> using the function LinearizedBlackoilResidual and >> FullyImplicitBlackoilSolver? >> > >> > I am currently modifying the sim_simple.cpp example but if the >> functionality is implemented in one of the solvers in any way, I would >> prefer to use them. >> > >> > Kind Regards >> > Tobias >> > _______________________________________________ >> > Opm mailing list >> > [email protected] >> > http://www.opm-project.org/mailman/listinfo/opm >> >> >> >> >> ------------------------------ >> >> Subject: Digest Footer >> >> _______________________________________________ >> Opm mailing list >> [email protected] >> http://www.opm-project.org/mailman/listinfo/opm >> >> >> ------------------------------ >> >> End of Opm Digest, Vol 31, Issue 5 >> ********************************** >> > > > > ------------------------------------------------------------------- > The information contained in this message may be CONFIDENTIAL and is > intended for the addressee only. Any unauthorised use, dissemination of the > information or copying of this message is prohibited. If you are not the > addressee, please notify the sender immediately by return e-mail and delete > this message. > Thank you >
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