750 research outputs found
Comparing water treatment topologies in Recirculating Aquaculture Plants
No full textAquaculture, the farming of fish and aquatic crops such askelp and algae, is traditionally carried out in natural bod-ies of water. An alternative is land-based farming in tanksor raceways, which is particularly attractive when coupledwith water treatment to form a recirculating aquaculturesystem (RAS). Benefits compared to traditional farming inopen cages include reduced emissions of nutrients, small orno risk of escapes, and control of pathogens (Thorarensenand Farrell, 2011).Water treatment takes place in a series of mechanicalfilters and biological reactors, where particulate and dis-solved matter is degraded by microorganisms similarly tohow municipal sewage is treated. The biological natureof recirculating aquaculture systems makes experimentalprocess development troublesome. Contributing factors in-clude very long time constants, biological variations, andconcerns for animal welfare. This strongly motivates theuse of dynamic simulations, and for that purpose a RASsimulator – called FishSim – was developed (Wik et al.,2009). However, the capabilities of that implementationwere limited by numerical problems.Using Modelica, a high-level object-oriented language fordynamic systems modeling (Modelica Association, 2012),we have developed a new simulation tool for recirculatingaquaculture. Like FishSim, it is based on Activated SludgeModel 1 (Henze et al., 2000), but this implementationis numerically well-behaved and robust which allows amuch greater variety in the simulated systems. It is alsosignificantly faster, even after the models have been ex-panded with many more features, such as energy balances,different feeding options, and a separation of autotrophicbacteria into ammonia-oxidizing and nitrite-oxidizing bac-teria. Since open-source Modelica tools are available, thesoftware is also free to use.Water treatment is central in recirculating aquaculture.Fish excrete ammonia, which is toxic to them. Aeratedbioreactors are typically employed to remove ammoniaand ammonium via nitrifying autotrophs, which requirelow levels of biodegradable organics to thrive. Nitrifica-tion creates nitrite (also toxic to fish at low levels) andnitrate, the latter which is removed by water exchangeor denitrification. Denitrifcation conversely requires highavailability of biodegradable organics, but only progressesrapidly in the absence of oxygen. The treatment systemsoften further contain particle filters and UV and/or ozonetreatment against pathogens.While it is reasonably clear to the industry which compo-nents should be present in the treatment system, the orderin which they are best employed is still an open question.In the literature and supplier information material thereis a large number of suggested configurations, but fewstudies comparing them. Some guesses can be made basedon elementary chemical reaction engineering, but the verycomplex dynamics of the biological treatment leads to highuncertainty.Using the simulator, we have investigated and comparedseveral treatment topologies. Through parameter opti-mization based on a genetic algorithm (Haupt and Haupt,2003) the minimal reactor sizes in each configuration wasfound which could maintain acceptable levels of ammoniaand nitrate. The resulting sizes are an indicator of whichtopology is the most effective
Light spectrum optimization for plant growth using biological feedback
No full textThe use of light emitting diods (LEDs) as greenhouse illumination is increasingly common. When each LED color is individually dimmable both light spectrum and light intensity can be tuned, which opens up for optimisation of photosynthesis through automatic control of light quality and quantity. However, this requires a non-destructive biological growth signal that can be measured fast, remotely and preferably without interacting with the plants. A potential candidate signal is steady-state chlorophyll a fluorescence gain at 740 nm, defined as dF740/dq, i.e. the difference in fluorescence at 740 nm divided by the difference in incident light quanta caused by a (small) change in intensity of each individual LED color in the lamp (Ahlman et al., 2017). By automatically adjusting the spectrum, to aim for equal fluorescence gains for all LED colors (Wik et al., 2014), the instant photosynthetic rate can be optimised given a preset electric power input to the lamp. When implementing such a controller though, constraints on the\ua0spectral distribution are needed to minimise a negative impact on plant morphology.\ua0In this study measurements were conducted (on cucumber and lettuce) under different background light, and at each setting excitation signals were sequentially added by each of six different LED colors (peak wavelength at 400, 420, 450, 530, 630 and 660 nm). The corresponding changes in steady-state fluorescence were measured with a spectrometer and the fluorescence gain (dF740/dq) was calculated for each LED color and at each background light setting. These fluorescence gains were compared in order to evaluate the different LEDs\u27 relative effect on photosynthesis under each of the different background light settings
Ausschreibung von Post-Universaldiensten: Ausschreibungsgegenstände, Ausschreibungsverfahren und begleitender Regulierungsbedarf
No full text
Trickling filters and biofilm modelling
No full textTricking filters are biofilm reactors commonly used for biological removal of nitrogen and organic matter. A review of published and unpublished material on the function, microbiology, design and operation of trickling filters is given. This is followed by more general dynamic biofilm reactor modelling, i.e. models for rotating biological contactors, different types of biofilters, moving beds as well as trickling filters
Automatically adjusting light spectrum for optimal short term photosynthetic rate [Elektronisk resurs]
No full textThe use of light emitting diods (LEDs) as greenhouse illumination is increasingly common. When each LED color is individually dimmable both light spectrum and light intensity can be tuned, which opens up for optimisation of photosynthesis through automatic control of light quality and quantity. However, this requires a non-destructive biological growth signal that can be measured fast, remotely and preferably without interacting with the plants. A potential candidate signal is steady-state chlorophyll a fluorescence gain at 740 nm, defined as dF740/dq, i.e. the difference in fluorescence at 740 nm divided by the difference in incident light quanta caused by a (small) change in intensity of each individual LED color in the lamp (Ahlman et al., 2017). By automatically adjusting the spectrum, to aim for equal fluorescence gains for all LED colors (Wik et al., 2014), the instant photosynthetic rate can be optimised given a preset electric power input to the lamp. When implementing such a controller though, constraints on the spectral distribution are needed to minimise a negative impact on plant morphology
Entwicklung einer schnellen Pulsformanalyse für asymmetrische AGATA-Germanium-Detektoren
No full textOnTEAM metadata: GDSID: DOC-2007-May-32; Attribute ID: LIBRARY-thesis_diss-2007-005; Title: [GSI Diss 2007-05] Entwicklung einer schnellen Pulsformanalyse für asymmetrische AGATA-Germanium-Detektoren; Author(s): Beck, Torsten; Corporate author(s): ; Publication date: 20070501; Creator: manton; Creation date: 15.05.2007 16:02:12; Change date: 29.10.2008 16:29:34; Access: nur berechtigte Gruppen; Attribute type: Text.Thesis.Diss; Directory path: ['GSI Publications', 'GSI as Publisher']; Attribute path: ['Infrastructure', 'Library and Documentation', 'thesis_diss', 'Added in 2007']; File name(s): ['DOC-2007-May-32-1.pdf']; File title(s): ['']; File access: ['nur berechtigte Gruppen'
Comparing water treatment topologies in Recirculating Aquaculture Plants
No full textAquaculture, the farming of fish and aquatic crops such as kelp and algae, is traditionally carried out in natural bodies of water. An alternative is landbased farming in tanks or raceways, which is particularly attractive when coupled with water treatment to form a recirculating aquaculture system (RAS). Benefits compared to traditional farming in open cages include reduced emissions of nutrients, small or no risk of escapes, and control of pathogens (Thorarensen and Farrell, 2011). Water treatment takes place in a series of mechanical filters and biological reactors, where particulate and dissolved matter is degraded by microorganisms similarly to how municipal sewage is treated. The biological nature of recirculating aquaculture systems makes experimental process development troublesome. Contributing factors include very long time constants, biological variations, and concerns for animal welfare. This strongly motivates the use of dynamic simulations, and for that purpose a RAS simulator – called FishSim – was developed (Wik et al.,2009). However, the capabilities of that implementation were limited by numerical problems. Using Modelica, a high-level object-oriented language for dynamic systems modeling (Modelica Association, 2012), we have developed a new simulation tool for recirculating aquaculture. Like FishSim, it is based on Activated Sludge Model 1 (Henze et al., 2000), but this implementation is numerically well-behaved and robust which allows a much greater variety in the simulated systems. It is also significantly faster, even after the models have been expanded with many more features, such as energy balances, different feeding options, and a separation of autotrophic bacteria into ammonia-oxidizing and nitrite-oxidizing bacteria. Since open-source Modelica tools are available, the software is also free to use. Water treatment is central in recirculating aquaculture. Fish excrete ammonia, which is toxic to them. Aerated bioreactors are typically employed to remove ammonia and ammonium via nitrifying autotrophs, which require low levels of biodegradable organics to thrive. Nitrification creates nitrite (also toxic to fish at low levels) and nitrate, the latter which is removed by water exchange or denitrification. Denitrifcation conversely requires high availability of biodegradable organics, but only progresses rapidly in the absence of oxygen. The treatment systems often further contain particle filters and UV and/or ozone treatment against pathogens. While it is reasonably clear to the industry which components should be present in the treatment system, the order in which they are best employed is still an open question. In the literature and supplier information material there is a large number of suggested configurations, but few studies comparing them. Some guesses can be made based on elementary chemical reaction engineering, but the very complex dynamics of the biological treatment leads to high uncertainty. Using the simulator, we have investigated and compared several treatment topologies. Through parameter optimization based on a genetic algorithm (Haupt and Haupt, 2003) the minimal reactor sizes in each configuration was found which could maintain acceptable levels of ammonia and nitrate. The resulting sizes are an indicator of which topology is the most effective
Comparing water treatment topologies in Recirculating Aquaculture Plants [Elektronisk resurs]
No full textAquaculture, the farming of fish and aquatic crops such as kelp and algae, is traditionally carried out in natural bod- ies of water. An alternative is land-based farming in tanks or raceways, which is particularly attractive when coupled with water treatment to form a recirculating aquaculture system (RAS). Benefits compared to traditional farming in open cages include reduced emissions of nutrients, small or no risk of escapes, and control of pathogens (Thorarensen and Farrell, 2011). Water treatment takes place in a series of mechanical filters and biological reactors, where particulate and dis- solved matter is degraded by microorganisms similarly to how municipal sewage is treated. The biological nature of recirculating aquaculture systems makes experimental process development troublesome. Contributing factors in- clude very long time constants, biological variations, and concerns for animal welfare. This strongly motivates the use of dynamic simulations, and for that purpose a RAS simulator – called FishSim – was developed (Wik et al., 2009). However, the capabilities of that implementation were limited by numerical problems. Using Modelica, a high-level object-oriented language for dynamic systems modeling (Modelica Association, 2012), we have developed a new simulation tool for recirculating aquaculture. Like FishSim, it is based on Activated Sludge Model 1 (Henze et al., 2000), but this implementation is numerically well-behaved and robust which allows a much greater variety in the simulated systems. It is also significantly faster, even after the models have been ex- panded with many more features, such as energy balances, different feeding options, and a separation of autotrophic bacteria into ammonia-oxidizing and nitrite-oxidizing bac- teria. Since open-source Modelica tools are available, the software is also free to use. Water treatment is central in recirculating aquaculture. Fish excrete ammonia, which is toxic to them. Aerated bioreactors are typically employed to remove ammonia and ammonium via nitrifying autotrophs, which require low levels of biodegradable organics to thrive. Nitrifica- tion creates nitrite (also toxic to fish at low levels) and nitrate, the latter which is removed by water exchange or denitrification. Denitrifcation conversely requires high availability of biodegradable organics, but only progresses rapidly in the absence of oxygen. The treatment systems often further contain particle filters and UV and/or ozone treatment against pathogens. While it is reasonably clear to the industry which compo- nents should be present in the treatment system, the order in which they are best employed is still an open question. In the literature and supplier information material there is a large number of suggested configurations, but few studies comparing them. Some guesses can be made based on elementary chemical reaction engineering, but the very complex dynamics of the biological treatment leads to high uncertainty. Using the simulator, we have investigated and compared several treatment topologies. Through parameter opti- mization based on a genetic algorithm (Haupt and Haupt, 2003) the minimal reactor sizes in each configuration was found which could maintain acceptable levels of ammonia and nitrate. The resulting sizes are an indicator of which topology is the most effective
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