Jesús Zambrano

Steady-state analysis of activated sludge processes with a settler model including sludge compression

A reduced model of a completely stirred-tank bioreactor coupled to a settling tank with recycle is analyzed in its steady states. In the reactor, the concentrations of one dominant particulate biomass and one soluble substrate component are modelled. While the biomass decay rate is assumed to be constant, growth kinetics can depend on both substrate and biomass concentrations, and optionally model substrate inhibition. Compressive and hindered settling phenomena are included using the Bürger-Diehl settler model, which consists of a partial differential equation. Steady-state solutions of this partial differential equation are obtained from an ordinary differential equation, making steady-state analysis of the entire plant difficult. A key result showing that the ordinary differential equation can be replaced with an approximate algebraic equation simplifies model analysis. This algebraic equation takes the location of the sludge-blanket during normal operation into account, allowing for the limiting flux capacity caused by compressive settling to easily be included in the steady-state mass balance equations for the entire plant system. This novel approach grants the possibility of more realistic solutions than other previously published reduced models, comprised of yet simpler settler assumptions. The steady-state concentrations, solids residence time, and the wastage flow ratio are functions of the recycle ratio. Solutions are shown for various growth kinetics; with different values of biomass decay rate, influent volumetric flow, and substrate concentration.

Gaussian process regression for monitoring and fault detection of wastewater treatment processes

Monitoring and fault detection methods are increasingly important to achieve a robust and resource efficient operation of wastewater treatment plants (WWTPs). The purpose of this paper was to evaluate a promising machine learning method, Gaussian process regression (GPR), for WWTP monitoring applications. We evaluated GPR at two WWTP monitoring problems: estimate missing data in a flow rate signal (simulated data), and detect a drift in an ammonium sensor (real data). We showed that GPR with the standard estimation method, maximum likelihood estimation (GPR-MLE), suffered from local optima during estimation of kernel parameters, and did not give satisfactory results in a simulated case study. However, GPR with a state-of-the-art estimation method based on sequential Monte Carlo estimation (GPR-SMC) gave good predictions and did not suffer from local optima. Comparisons with simple standard methods revealed that GPR-SMC performed better than linear interpolation in estimating missing data in a noisy flow rate signal. We conclude that GPR-SMC is both a general and powerful method for monitoring full-scale WWTPs. However, this paper also shows that it does not always pay off to use more sophisticated methods. New methods should be critically compared against simpler methods, which might be good enough for some scenarios.

ATAD control goals through the analysis of process variables and evaluation of quality, production and cost

The aim of this paper is to establish and quantify different operational goals and control strategies in autothermal thermophilic aerobic digestion (ATAD). This technology appears as an alternative to conventional sludge digestion systems. During the batch-mode reaction, high temperatures promote sludge stabilization and pasteurization. The digester temperature is usually the only online, robust, measurable variable. The average temperature can be regulated by manipulating both the air injection and the sludge retention time. An improved performance of diverse biochemical variables can be achieved through proper manipulation of these inputs. However, a better quality of treated sludge usually implies major operating costs or a lower production rate. Thus, quality, production and cost indices are defined to quantify the outcomes of the treatment. Based on these, tradeoff control strategies are proposed and illustrated through some examples. This papers results are relevant to guide plant operators, to design automatic control systems and to compare or evaluate the control performance on ATAD systems.

Robust tuning of bending-points detection algorithms in-batch-operated processes

The literature shows a diversity of real-time algorithms for automatic detection of bending-points in batch-operated waste treatment systems. In this study a new methodology is proposed for tuning the parameters of these algorithms when uncertainty specifications are considered at the outset. In this method the effects of slow and fast dynamic responses on the shape of signal trajectories were treated separately in order to cover via simulation all possible operating scenarios for a real situation. Long-term uncertainty and steady-state simulations were combined to derive probability distributions for biomasses. These probability distributions were then merged with short-term uncertainty to run one-cycle random simulations with which to reproduce the entire diversity of signal trajectories. Finally, an optimisation problem was formulated in terms of the algorithm parameters. The methodology was satisfactorily applied to tune an algorithm for detection of bending-points in an Autothermal Thermophilic Aerobic Digestion (ATAD) process. Methodology for tuning of bending-point detection algorithms in batch-operated systems.Application of the method to a specific bending-point detection algorithm for ATAD technology.Short and long-term uncertainty to describe the population of both slow and fast response states.Steady-state and one-cycle simulations to generate realistic signal trajectories.

Fault signatures and bias progression in dissolved oxygen sensors

Biofilm fouling is known to impact the data quality of sensors, but little is known about the exact effects. We studied the effects of artificial and real biofilm fouling on dissolved oxygen (DO) sensors in full-scale water resource recovery facilities, and how this can automatically be detected. Biofilm fouling resulted in different drift direction and bias magnitudes for optical (OPT) and electrochemical (MEC) DO sensors. The OPT-sensor was more affected by biofilm fouling compared to the MEC-sensor, especially during summer conditions. A bias of 1 mg/L was detected by analysing the impulse response (IR) of the automatic air cleaning system in the DO sensor. The IR is an effect of a temporal increase in DO concentration during the automatic air cleaning. The IRs received distinct pattern changes that were matched with faults including: biofilm fouling, disturbances in the air supply to the cleaning system, and damaged sensor membrane, which can be used for fault diagnosis. The results highlight the importance of a condition-based sensor maintenance schedule in contrast to fixed cleaning intervals. Further, the results stress the importance of understanding and detecting bias due to biofilm fouling, in order to maintain a robust and resource-efficient process control.

Analysis of photobioreactors in series

A photobioreactor (PBR) contains microalgae which under illumination consume carbon dioxide and substrate dissolved in water, and produce oxygen. The process is used in water recovery resource facilities with a continuous flow of wastewaster through the PBR. With several PBRs in series the reduction of substrate can be improved. This paper contains a thorough analysis of a model of PBRs in series, where each PBR is modelled with a system of three ordinary differential equations for the concentrations of dissolved substrate and biomass (algae), and the internal cell quota of substrate to biomass. Each PBR has a certain volume and irradiation. The absorption rate of substrate into the cells is modelled with Monod kinetics, whereas the biomass growth rate is modelled with Droop kinetics, in which both a minimum and a maximum internal cell quota are assumed. The main result is that the model has a unique stable steady-state solution with algae in all PBRs. Another stable steady-state solution is the wash-out solution with no algae in the system. Other steady-state solutions are combinations of these two with no algae in some of the first PBRs and algae in the rest of the PBRs in the series. Conditions on the illumination, volumetric flow and volumes of the PBRs are given for the respective solution. Numerical solutions illustrate the theoretical results and indicate further properties.

Anaerobic co-digestion of sludge and microalgae grown in municipal wastewater – a feasibility study

In this study a natural mix of microalgae grown in wastewater of municipal character was co-digested with sewage sludge in mesophilic conditions, in both batch and semi-continuous modes. The semi-continuous experiment was divided into two periods with OLR1 (organic loading rate) of 2.4 kg volatile solids (VS) m-3 d-1 and HRT1 (hydraulic retention time) of 15 days, and OLR2 of 3.5 kg VS m-3 d-1 and HRT2 of 10 days, respectively. Results showed stable conditions during both periods. The methane yield was reduced when adding microalgae (from 200 ± 25 NmL CH4 g VSin-1, to 168 ± 22 NmL CH4 g VSin-1) but VS reduction was also decreased by 51%. This low digestibility was confirmed in the anaerobic batch test. However, adding microalgae improved the dewaterability of the digested sludge. The high heavy metals content in the microalgae resulted in a high heavy metals content in the digestate, making it more difficult to reuse the digestate as fertilizer on arable land. The heavy metals are thought to originate from the flue gas used as a CO2 source during the microalgae cultivation. Therefore the implementation of CO2 mitigation via algal cultivation requires careful consideration regarding the source of the CO2-rich gas.

Monitoring a Secondary Settler Using Gaussian Mixture Models

This paper presents a method for monitoring the sludge profiles of a secondary settler using a Gaussian Mixture Model (GMM). A GMM is a parametric probability density function represented as a weig ...