Dissolved oxygen concentration control and prediction modelling for liquid LBE loop: UPBEAT loop

Greenhouse cultivation is an important technique for producing high-quality crops with a high profit margin. Fuzzy inference systems have been effectively utilized in prediction and control models to enable good management of environmental factors. The aim of this review is to determine the different relationships in the fuzzy inference systems currently used for modelling, prediction and humidity control in greenhouses and their evolution over time in order to develop more robust and reliable models easy to understand. The main objective is to identify the different relationships within fuzzy inference systems their configurations and models through optimization algorithms currently used for prediction, control and humidity modelling in greenhouses. The methodology follows the PRISMA working guide. A total of 93 surveys were reviewed in 4 academic databases; its bibliometric aspects have been extracted and analysed, which contributes to the objective of the survey. Finally, it was determined that using Mamdani's fuzzy inference systems in conjunction with optimization and fuzzy clustering approaches, as well as strategies like model-based predictive control, ensures high levels of accuracy and interpretability.

QFT Control of Dissolved Oxygen Concentration in a Wastewater Treatment Pilot Plant

This paper presents a control-oriented model describing the dynamics of oxygen concentration through a Diesel engine aftertreatment system that includes a Diesel oxidation catalyst (DOC) and a Diesel particulate filter (DPF). Exhaust gas oxygen concentration is important for catalysts such as NOx conversion efficiencies of selective catalytic reduction (SCR) systems and lean NOx traps (LNT). In the presence of low-pressure loop exhaust gas recirculation (EGR), the exhaust gas oxygen concentration after-DPF also influences combustion. Due to the chemical reactions occurring inside DOC and DPF, the exhaust gas oxygen concentration considerably varies through the aftertreatment systems. Directly measuring the exhaust gas oxygen concentrations at different locations through the exhaust gas aftertreatment system is costly and unreliable. A dynamic model is thus needed in order to design model-based observers to estimate the exhaust gas oxygen concentrations at various locations. The oxygen-related reactions within a DOC and a DPF are investigated in this study. A lumped-parameter, control-oriented DOC-DPF oxygen concentration dynamic model was developed by a multi-objective optimization method and validated with experimental data obtained on a medium-duty Diesel engine equipped with full aftertreatment systems. Experimental results show that the model can well capture the oxygen dynamics across the Diesel engine aftertreatment systems.

The effect of microbes and dissolved oxygen concentration on inorganic and organic substances elimination in a climate changing environment: The aerobic bioreactor

A simple approach was developed to determine the half-saturation coefficient for dissolved oxygen (K(DO)) for three bacteria by maintaining a constant oxygen concentration in continuous culture, and employing a dynamic method to obtain the specific growth rate (mu) for each species. Measurement of mu at selected dissolved oxygen concentrations (DO) resulted in a typical Monod curve for a plot of mu vs. DO. Values for K(DO) and mu(max) were obtained from the Lineweaver-Burk reciprocal plot. The bacteria studied included representative strains of three microorganisms isolated in pure culture from poorly settling activated sludge: two filamentous microorganisms, Sphaerotilus natans and a second Sphaerotilus sp., and an unidentified floc-forming microorganism. The K(DO) values obtained for Sphaerotilus sp., S. natans, and the floc former were 0.014, 0.033, and 0.073 mg/L, respectively. Dual species competition experiments were conducted in continuous culture under low and high DO conditions. Successful growth competition by these microorganisms under DO-limiting conditions was consistent with experimentally determined K(DO) values. The finding of lower K(DO) values for the two Sphaerotilus species, compared to the floc former, confirmed the hypothesis that these filamentous microorganisms can outgrow floc-forming microorganisms in activated sludge when DO in the aeration basin is low.

Dissolved oxygen concentration (DO) is one of the main factors limiting benthic species distribution. Due to ocean warming and eutrophication, the ocean is deoxygenating. In the Eastern Tropical Pacific (ETP), deep waters with low DO (<1 mg L-1) may reach coral reefs, because upwelling will likely intensify due to climate change. To understand oxygen variability and its effects on corals, we characterize the Spatio-temporal changes of DO in coral reefs of Gorgona Island and calculate the critical oxygen tension (P crit) to identify the DO concentration that could represent a hypoxic condition for Pocillopora capitata, one of the main reef-building species in the ETP. The mean (±SD) DO concentration in the coral reefs of Gorgona Island was 4.6 ± 0.89 mg L-1. Low DO conditions were due to upwelling, but hypoxia (<3.71 mg L-1, defined as a DO value 1 SD lower than the Mean) down to 3.0 mg O2 L-1 sporadically occurred at 10 m depth. The P crit of P. capitata was 3.7 mg L-1 and lies close to the hypoxic condition recorded on coral reefs during the upwelling season at 10 m depth. At Gorgona Island oxygen conditions lower than 2.3 mg L-1 occur at >20 m depth and coincide with the deepest bathymetric distribution of scattered colonies of Pocillopora. Because DO concentrations in coral reefs of Gorgona Island were comparably low to other coral reefs in the Eastern Tropical Pacific, and the hypoxic threshold of P. capitata was close to the minimum DO record on reefs, hypoxic events could represent a threat if conditions that promote eutrophication (and consequently hypoxia) increase.

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multiphases and multifields interactions with long time delay phenomena take place during its operation. In BF operation, the molten iron temperature as well as the Si content ([Si]), the phosphorus content ([P]), and the sulfur content ([S]) is the most essential quality (MIQ) indices. The measurement, modeling, and control of these indices have always been important issues in metallurgic engineering and automation. This paper proposes a novel data-driven nonlinear state-space modeling method for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques together. First, to improve modeling efficiency, a data-driven hybrid method that combines canonical correlation analysis and correlation analysis is established to identify the most influential controllable variables as the modeling inputs from multitudinous factors. Then, a Hammerstein model for the prediction of MIQ indices is established using the Least squares support vector machine-based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method. Compared with the original Hammerstein model, it has been shown that this simplified model can not only significantly reduce the computational complexity, but can also exhibit a good reliability and accuracy for a stable prediction of MIQ indices. In order to verify the practicability of the developed model, it is applied to the design of a genetic algorithm based nonlinear predictive controller for the multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approaches.

Proportion regulation in Dictyostelium is altered by oxygen

Noninvasive in vivo monitoring of tissue implants provides important correlations between construct function and the observed physiologic effects. As oxygen is a key parameter affecting cell and tissue function, we established a monitoring method that utilizes (19) F nuclear magnetic resonance (NMR) spectroscopy, with perfluorocarbons (PFCs) as oxygen concentration markers, to noninvasively monitor dissolved oxygen concentration (DO) in tissue engineered implants. Specifically, we developed a dual PFC method capable of simultaneously measuring DO within a tissue construct and its surrounding environment, as the latter varies among animals and with physiologic conditions. In vitro studies using an NMR-compatible bioreactor demonstrated the feasibility of this method to monitor the DO within alginate beads containing metabolically active murine insulinoma βTC-tet cells, relative to the DO in the culture medium, under perfusion and static conditions. The DO profiles obtained under static conditions were supported by mathematical simulations of the system. In vivo, the dual PFC method was successful in tracking the oxygenation state of entrapped βTC-tet cells and the surrounding peritoneal DO over 16 days in normal mice. DO measurements correlated well with the extent of cell growth and host cell attachment examined postexplantation. The peritoneal oxygen environment was found to be variable and hypoxic, and significantly lower in the presence of metabolically active cells. The significance of the dual PFC system in providing critical DO measurements for entrapped cells and other tissue constructs, in vitro and in vivo, is discussed.

This paper describes a simple, analytical, control-oriented and physically-based model for prediction of combustion timing during PCCI combustion. The model includes direct dependence on in-cylinder temperature, in-cylinder pressure, and the total in-cylinder O2 mass fraction. It is extensively validated with experimental PCCI data from a multi-cylinder engine with almost exclusively stock hardware (stock pistons, injectors/nozzles, turbocharger, etc.) and variable valve actuation. The results show that across a wide range of input conditions the model predicts the start of combustion (SOC) within ±2°CA of the experimental values for all but one of the 119 data points. The experimental SOC ranges from as early as 19.3°CA to as late as +0.6°CA by heavily exercising the control authority over SOC provided by SOI ecm , IVC/ECR modulation (ECR ranges from 12:1 to 18:1), and the engine's air-handling system. This PCCI combustion timing model can be coupled with a gas exchange model for control algorithm design.

Dual-loop exhaust gas recirculation with a variable-geometry turbocharger is an effective architecture for achieving desired intake manifold conditions, such as the temperature, the pressure and the oxygen concentration of the intake manifold, which have critical roles in advanced combustion mode control. However, the widely used control-oriented model is derived on the basis that the heat transfer between the pipes and the gas is negligible, which means that it suffers from non-trivial errors. Simulation results show that other error sources, including the volumetric efficiency and the orifice equation, are difficult to calibrate accurately and also cause significant errors in the system, particularly in transient situations. Modified active disturbance rejection control with an extended state observer is utilized to deal with the non-linear, multiple-input multiple-output system in this paper. It is demonstrated that the performance of active disturbance rejection control mainly depends on the performance of the extended state observer. In this paper, an extended state observer, which is based on the sliding-mode concept rather than the conventional linear observer, is introduced. By taking advantage of its strong robustness, the system is decoupled into three loops. For each loop, the internal errors and the external errors, including the modelling error and the coupling effects, are lumped into one term; they are then actively estimated and cancelled out by the control input in real time. The proposed method was validated using calibrated GT-Power model simulations.

A glucose-insulin pharmacodynamic surface modeling validation and comparison of metabolic system models

Evaluation of the impact of dissolved oxygen concentration on biofilm microbial community in sequencing batch biofilm reactor

The dynamic response of optical oxygen sensors and voltammetric electrodes to temporal changes in dissolved oxygen concentrations

This paper aims at detecting the problems in aquaculture so that farmers can take preventive measures before things get out of control. It is designed to operate in ponds where aquatic animals are made to develop in their natural habitat. The device is provided with sensors namely Dissolved Oxygen sensor, PH sensor, Ultra Sonic Sensor, etc. which are connected to a base device called Arduino Board. The device uses the internet connectivity to regulate the works without manpower. In manmade ponds the Dissolved content of the oxygen, the PH level and the Water level varies with the density of the aquatic animals, so if the Dissolved oxygen content in the water decreases it will make the aquatic animals unable to survive in less oxygen atmosphere. The Dissolved oxygen sensor detects this and automatically switches on the aerators which then increase the content of oxygen. Similarly if the PH level of the water is below or above seven (7) the water becomes acidic or basic in nature which is not a good sign of natural habitat for animals. The PH level sensor detects this and we can take counter measures to make the PH again to 7. We can also regulate the temperature of the water using temperature sensor.