Sour water stripper unit 1

[ReemaK]

Hello

I am trying to simulate a 2-stage sour water unit using Aspen Hysys...I have used sour PR package...There is no access to other simulation software like protreat/promax

Both the stripper columns have pumparounds..The number of trays in each column are 47...The pumparound draw is taken at tray no 41 and returned back at 47 (topmost tray) in both the columns

For column 1:
PA Drawoff temperature : 130 C ; PA return temperature : 90 C ; Column overhead temperature : 108 C

For column 2 :
PA drawoff temperature : 115 C; PA return temperature : 70 C ; Column overhead temperature : 90 C

Can there be a difference of 18-20 C between PA return temperature and column overhead ?? The overhead vapor flow is around 8000kg/hr for column-1 and around 5000 for column 2

I am new to SWS units...so looking forward to any guidance

Any books on sour water stripping process chemistry and unit operation are available..please share them

Thanks in advance !!!

 

[georgeverghese]

Of course it can.
Strange you need a 2 stage stripper with a total of 94trays to strip this sour water stream ! You should be able to get this done with a single column with less than half the trays you have now - refer to your applications case manual for SWS simulation for example simulations. There is a case simulation for SWS in Pro II - Simsci applications manual.

 

[ReemaK]

Thank you for your prompt response !!

The unit has already been designed and is under commissioning...I am simulating it because i need to see the change in reboiler duty, Pa duty, when another waste stream containing ammonia and h2s is also sent to this unit..if the existing unit can handle it without significant modifications

I dont have the simulation model of the existing unit as it was provided by the contractor..so have to build it from scratch

I have access only to Aspen suite...no other softwares

Thank You !!

 

[shvet]

My first case when I came into process engineering was related to a 25 t/h sour water stripping unit. It was initially engineered by a EU division of Koch-Glitsch and worked not as planned although it had been modelled by an experienced and motivated persons involved. Total remodelling, reengineering, and rebuilt had been required to provide intended capacity and products purity.

We used GPSA system (default setup) in Pro/II and provided remodelling adjusting step-by-step model results with series of test runs of the real process unit in close collaboration of engineering and operating teams.

My personal experience is that sour water is a challenging issue especially when more than 1 of ions are involved, let's say S and NH4 both. Reliable modelling becomes impossible when soluble hydrocarbons and and other ions are involved, let's say Na, Ca2, CO2. This is the reason why so many thermodynamic systems have been created.

Seems an insurmountable task for a newcomer.

 

[ReemaK]

Yes @shvet

I am trying to get the test run data so that I can compare and model it better.

Any reading material on sour water stripper process chemistry ??

Thank You !!

 

[shvet]

Start with actual composition and flowrate of all streams in/outcoming to/from columns. We had lost several months till obtained correct results. The most challenging issue for a process team.
Then check condition of packing, we have encountered fouling of lower packing layers by a catalyst dust.
Then provide in laboratory a visual check of foaming dendency of pump-around streams samples.

 

[ReemaK]

Ok

We are using a trayed column.

 

[PaoloPemi]

>>Any books on sour water stripping process chemistry and unit operation are available..please share them

many books available but you may start from original paper : "A New Correlationof NH3, CO2, and H2S Volatility Data from Aqueous Sour Water Systems" which includes a discussion on the limits of the model vs. measured data and application examples...

Said that, I agree with others that this may be a challenging issue... probably related to the limits of these (empirical) models and the difficult to fit a suitable design within these limits...
Rate based models (i.e. solving phase equilibria with reactions) could represent an alternative but Wilson's model is available in many applications (I have it in my copy of Prode Properties..) and it has been well tested...

 

[georgeverghese]

There is a special sour water thermodynamics package in Pro/II - Simsci which accommodates both H2S and NH3.
Pump around coolers are usually done when you want to reduce the duty of the condensor, but this comes at the expense of stripping efficiency. IN SWS, typically there is adequate cooling water for overheads condensors, and cooling water temp is also adequate, so why the pump around cooler ? In your case, you are basically losing the rectification duty possible for 6 trays in each of these 2 columns.

 

[ReemaK]

Thank you @PaoloPemi..I will go through the paper

@georgeverghese..The company doesn't have a pro-II license...It was already designed a few years back.Now I have to check its adequacy if another stream of around 15m3 is also going into this stripper unit..like changes in reboiler duty, will there be any changes in number of trays required,etc

 

[shvet]

My experience with Aspen package is that it is bad in modelling a complex process scheme containing more than 1 of logic cycling. Hysys and Aspen+ both. Aspen is excellent in a rough modelling and decision making and bad in accurate modelling and detailed design you have been assigned to conduct.
Pro/II algorithms are much better and convinient and save engineer's time&nerves.

Having reliable data from a real process EOS package choice and software are not critical, any will be ok having done some adjustment.

Taking into account a new source of sour water it is critical to obtain a detailed composition with even traces of soluble matter as those will accumulate and become important in pump-arounds.

Focus on data coming out from a production site and a model adequacy. Do not trust any number you see neither in a test run report nor simulation report. Verify and reverify. This will most help to improve results, the rest issues are not so hard to overcome. Inform the managers that the task may require a lot of time&efforts&skills from engineering and production team both so they shall not expect emmidiate results.

For info
Lieberman's Troubleshooting Process Operations 4th ed. para. 26-29,37

 

[ReemaK]

Thank you @shvet

 

[pierreick]

Hi,
A good reference GPSA (gas processors suppliers association) chapter 19 section 19.32
Another one: Gas purification by Arthur Kohl, Richard Nielsen 5th edition pages 302-308
Pierre

 

[ReemaK]

thank you @pierreick

 

[georgeverghese]

Suspect the total number of trays you've quoted here = 94-12 = 82 (excluding the trays lost at pumparounds) is the actual no of trays. To get the theoretical no of trays, use the average tray efficiency for the controlling case solute. If you dont know, use the well known O'Connell graph to derive tray efficiency - see page 14-12, Fig 14-7 and worked example 4 for strippers in Perry Chem Engg Handbook 7th edn.

 

[ReemaK]

Thank you @georgeverghese...I will check the example suggested by you..

 

[shvet]

for info
Kister's Distillation Troubleshooting cases 22.13-22.15

Preface to Kister's Distillation Design

In the past, mass production of mathematical models and column design correlations was hindered by the extensive calculations involved. With the event of computers, this bottleneck has been eliminated. Flood gates have opened, and new mathematical models are pouring into the published literature at a record pace. Further growth in mathematical model production appears to be restricted only by the availability of persons willing to punch buttons on computer keyboards.
One would expect this state of art to be the heaven that column designers always dreamt of. Instead, it turned out to be the hell always feared. Few could keep up with the large influx of mass produced mathematical models. Little is known about the limitations of each new correlation or design method. Our prediction methods turned into black boxes: key in numbers, print out results. But how reliable are these results?
...
As we head into the 21 century, the above type of anecdote is becomming ancient history. The blak box in the computer has taken over. Looking for correlation limitations today becomes like looking for a needle in an ever-growing haystack.
With the busy life style and the pressure to publish papers, the problem is becoming more acute. There are deadlines to meet, technical papers need to be produced, and there is no time to explore correlation limitations. Besides, who needs to look for limitations when a computerized regression analysis (performed, of course, by one of the best regression packages in the business) shows an excellent data fit? Does it really matter if a handful of points for systems above atm pressure? In real life, no one will know, unless the designer ends up with a column that does not work. And if the errors is on the conservative side, no one will ever find out, because the column will work.
Data collection is another neglected child of the late 20th century. There are so many data around that collecting them all (or even most of them) for the sake of deriving a correlation becomes painful, mundane, and an extremely unattractive exercise. Not to mention the labor involved in reading data off plots and in the arithmetic involved in ensuring that all the data points have been correctly entered. I challenge anyone to cite a more boring task than this. An economical way of dealing with the excess data problem is by using the "ignore it and hope it goes away" principle. It will suffice that the new correlation will fit a handful of data thrown at it. And if data from other sources do not agree, that just means there is something wrong with other data.
What hope has the designer who sits at the end of the rainbow and attempts to make use of the mathematical models and design correlations?
...
Contrary to a popular belief, some distillation characteristics still cannot be satisfactorily predicted by correlation, regardless of the number of correlations available for their prediction. Data interpolation with the aid of an empirical procedure is probably the most reliable means of estimating these characteristics. ... Computers have provided distillation designers with speed, accuracy, and flexibility. Computers, however, still have a long way to go before - if ever - they are capable of replacing good engineering judgment.