Alle Veröf­fentlichun­gen zu unseren The­menge­bi­eten find­est Du hier zum Down­load als PDF-Datei bzw. einen Ref­eren­zlink zur Down­load­seite der Gesamt­pub­lika­tion. Bei Rück­fra­gen ste­hen wir Dir gerne über unser Kon­tak­t­for­mu­lar zur Ver­fü­gung.


Aquaponics Systems Modelling

Karel J. Keesman, Oliv­er Körn­er, Kai Wag­n­er, Jan Urban, Divas Kari­manzi­ra, Thomas Rauschen­bach, and Simon God­dek

Math­e­mat­i­cal mod­els can take very dif­fer­ent forms and very dif­fer­ent lev­els of com­plex­i­ty. A sys­tem­at­ic way to pos­tu­late, cal­i­brate and val­i­date, as pro­vid­ed by sys­tems the­o­ry, can there­fore be very help­ful. In this chap­ter, dynam­ic sys­tems mod­el­ling of aquapon­ic (AP) sys­tems, from a sys­tems the­o­ret­i­cal per­spec­tive, is con­sid­ered and demon­strat­ed to each of the sub­sys­tems of the AP sys­tem, such as fish tanks, anaer­o­bic digester and hydro­pon­ic (HP) green­house. It fur­ther shows the links between the sub­sys­tems, so that in prin­ci­ple a com­plete AP sys­tems mod­el can be built and inte­grat­ed into dai­ly prac­tice with respect to man­age­ment and con­trol of AP sys­tems. The main chal­lenge is to choose an appro­pri­ate mod­el com­plex­i­ty that meets the exper­i­men­tal data for esti­ma­tion of para­me­ters and states and allows us to answer ques­tions relat­ed to the mod­el­ling objec­tive, such as sim­u­la­tion, exper­i­ment design, pre­dic­tion and con­trol.

Down­load­link zum Buch

Development of denitrification in semi-automated moving bed biofilm reactors operated in a marine recirculating aquaculture system

Orestis Stavrakidis-Zachou, Anneliese Ernst, Chris­t­ian Stein­bach, Kai Wag­n­er, Uwe Waller

This study exam­ined the per­for­mance of three inde­pen­dent­ly oper­at­ed den­i­tri­fy­ing mov­ing bed biofilm reac­tors (MBBRs) in a zero-exchange marine recir­cu­lat­ing aqua­cul­ture sys­tem (RAS) stocked with Euro­pean seabass (Dicen­trar­chus labrax). A semi-auto­mat­ed con­trol strat­e­gy was applied to fos­ter spon­ta­neous den­i­tri­fi­ca­tion. Process automa­tion con­sist­ed of a pulsed car­bon sup­ply and an inflow of nitrate-rich, aer­at­ed process water con­trolled by the oxi­da­tion-reduc­tion poten­tial (ORP) in the MBBR. Car­bon dos­ing fre­quen­cy was adjust­ed man­u­al­ly if the process pro­duced unwant­ed prod­ucts (i.e., nitrite or ammo­nia). OPR-con­trolled inflow stim­u­lat­ed bac­te­r­i­al activ­i­ties in the MBBRs until inflow reached the pre-set max­i­mum at a hydraulic reten­tion time (HRT) of 0.75 h. This allowed for a quick start-up of the den­i­tri­fi­ca­tion process­es in spite of high ini­tial vari­abil­i­ty of process water inflow and of nitrate removal effi­cien­cy (NRE). A start-up with glyc­erol did not induce a sta­ble den­i­tri­fi­ca­tion process; how­ev­er, after the process had been estab­lished with acetate, glyc­erol pro­mot­ed effi­cient den­i­tri­fi­ca­tion with NRE close to one. The suc­ces­sive appli­ca­tion of the two car­bon sources result­ed in a high nitrate removal rate (NRR) of 2 kg nitrate‑N m−3 day−1 in the biofil­ters. This dimin­ished the con­cen­tra­tion of nitrate-nitro­gen (nitrate‑N) in the RAS (vol­ume 9 m³) from176 to 36g m−3 in 42 days with biofil­ters com­pris­ing only 1% of the RAS vol­ume. The impli­ca­tions for the devel­op­ment of an auto­mat­ed den­i­tri­fi­ca­tion process are dis­cussed.

Artikel kaufen

Call Now ButtonJetzt anrufen