Individual Security and Network Design with Malicious Nodes

Networks are beneficial to those being connected but can also be used as carriers of contagious hostile attacks. These attacks are often facilitated by exploiting corrupt network users. To protect against the attacks, users can resort to costly defense. The decentralized nature of such protection is known to be inefficient but the inefficiencies can be mitigated by a careful network design. Is network design still effective when not all users can be trusted? We propose a model of network design and defense with byzantine nodes to address this question. We study the optimal defended networks in the case of centralized defense and, for the case of decentralized defense, we show that the inefficiencies due to decentralization can be fully mitigated, despite the presence of the byzantine nodes.Comment: 19 pages, 3 figure

Improving Stability of Electronically Controlled Pressure 1 Reducing Valves

The file attached to this record is the author's final peer reviewed version.9 This paper explains the root cause of instabilities which tend to arise in pressure reducing 10 valves (PRVs) under low flow conditions. It was found that the loss of stability in PRVs is a direct 11 result of an increase in the static valve/network gain as the valve position gets smaller, thus making 12 pressure changes more sensitive to valve position adjustments. If the valve controller is tuned at 13 medium valve openings characteristic of normal operating conditions, the increased gain at low 14 valve openings can cause the control system to be too aggressive in its valve position adjustments 15 leading to oscillations. The manuscript provides a mathematical derivation of the gain equation 16 for a simplified pipe-PRV-pipe model. The obtained gain equation curve is then used to derive the 17 formula for a gain compensator whose purpose is to keep the static gain constant across an entire 18 range of permitted valve openings. A simplified network transient model is then used to recreate a 19 real-life PRV instability event and show the remedial effects of the gain compensator

Integrated benchmark simulation model of an immersed membrane bioreactor

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper presents a new integrated model of an immersed membrane bioreactor (iMBR)for wastewater treatment. The model is constructed out of three previously published sub-models describing the bioreactor, the membrane, and the interface between them. Thebioreactor submodel extends a conventional activated sludge model with soluble and boundbiopolymers which have been found to cause irreversible and reversible fouling. The mem-brane model describes fouling as a function of biopolymer concentrations, permeate flow,and shear stresses on the membrane surface. The interface describes the dependency ofoxygen transfer rate on suspended solids concentrations and calculates shear stresses onthe membrane surface from air-scour rates. The paper serves three purposes. First, the inte-grated model is simulated on a plant layout of a previously published MBR benchmark modelwhich did not consider any interactions between the submodels. Hence, this paper presentsa new and upgraded MBR benchmark model. Secondly, the simulation results showcase howsimulations with an integrated model can be used to optimise plant performance and min-imise energy consumption. Finally, the paper introduces new measures of fouling whichcan be used for benchmarking different MBR plant layouts and control strategies

Interface model between the bioreactor and the membrane in a membrane bioreactor for wastewater treatment.

This paper proposes a structure of an integrated mathematical model of a membrane bioreactor (MBR) and describes the links between two main parts of a MBR model: the bioreactor and the membrane. In case of an immersed MBR three types of links are considered: a relationship between specific cake resistance (SCR) and extracellular polymeric substances (EPS) in the bioreactor, a relationship between air scour rate and shear stresses on the membrane surface, and a relationship between concentration of soluble microbial products (SMP) in the bioreactor and rate of pore constriction. While SMP concentration features directly in the equations of pore constriction, EPS are assumed to affect SCR which in turn has an effect on cake filtration. The relationship between EPS and SCR is described with a linear algebraic equation. Shear stresses on the membrane surface are calculated as a function of air scour rate with a one- imensional slug flow model

Modelling and Simulation of Membrane Bioreactors for Wastewater Treatment

The work presented in this thesis leads to the formulation of a dynamic mathematical model of an immersed membrane bioreactor (iMBR) for wastewater treatment. This thesis is organised into three parts, each one describing a different set of tasks associated with model development and simulation. In the first part, the Author qualitatively and quantitatively compares various published activated sludge models, i.e. models of biochemical processes associated with bacterial growth, decay, lysis and substrate utilisation in activated sludge systems. As the thesis is focused on modelling membrane bioreactors (MBRs) which are known to experience membrane fouling as a result of adsorption of biopolymers present in the bulk liquid onto and within the membrane, all activated sludge models considered in this thesis are able to predict, with various levels of accuracy, the concentrations of biopolymeric substances, namely soluble microbial products (SMP) and extracellular polymeric substances (EPS). Some of the published activated sludge models dedicated to modelling SMP and EPS kinetics in MBR systems were unable to predict the SMP and EPS concentrations with adequate levels of accuracy, without compromising the predictions of other sludge and wastewater constituents. In other cases, the model equations and the assumptions made by their authors were questionable. Hence, two new activated sludge models with SMP and EPS as additional components have been formulated, described, and simulated. The first model is based on the Activated Sludge Model No. 1 (ASM1) whereas the second model is based on the Activated Sludge Model No. 3 (ASM3). Both models are calibrated on two sets of data obtained from a laboratory-scale system and a full-scale system and prove to be in very good agreement with the measurements. The second part of this thesis explains the development of two membrane fouling models. These models are set to describe the loss of membrane permeability during filtration of various solutions and suspensions. The main emphasis is placed on filtration of activated sludge mixtures, however the models are designed to be as general as feasibly possible. As fouling is found to be caused by a large number of often very complex processes which occur at different spatial as well as temporal scales, the two fouling models developed here have to consider a number of significant simplifications and assumptions. These simplifications are required to balance the model’s accuracy, generality and completeness with its usability in terms of execution times, identifiability of parameters and ease of implementation in general purpose simulators. These requirements are necessary to ascertain that long term simulations as well as optimisation and sensitivity studies performed in this thesis either individually on fouling models or on the complete model of a MBR can be carried out within realistic time-scales. The first fouling model is based on an idea that fouling can be subdivided into just two processes: short-term reversible fouling and long-term irreversible fouling. These two processes are described with two first order ordinary differential equations (ODEs). Whilst the first model characterises the membrane filtration process from an observer’s input-output point of view without any rigorous deterministic description of the underlying mechanisms of membrane fouling, the second model provides a more theoretical and in-depth description of membrane fouling by incorporating and combining three classical macroscopic mechanistic fouling equations within a single simulation framework. Both models are calibrated on a number of experimental data and show good levels of accuracy for their designated applications and within the intended ranges of operating conditions. In the third part, the first developed biological model (CES-ASM1) is combined with the behavioural fouling model and the links between these two models are formulated to allow complete simulation of a hollow fibre (HF) immersed membrane bioreactor (iMBR). It is assumed that biological processes affect the membrane through production of mixed liquor suspended solids (MLSS), SMP and EPS which cause pore blockage, cake formation, pore diameter constriction, and affect the specific cake resistance (SCR). The membrane, on the other hand, has a direct effect on the bulk liquid SMP concentration due to its SMP rejection properties. SMP are assumed to be solely responsible for irreversible fouling, MLSS is directly linked to the amount of cake depositing on the membrane surface, whereas EPS content in activated sludge affects the cake’s SCR. Other links provided in the integrated MBR model include the effects of air scouring on the rate of particle back-transport from the membrane surface and the effects of MLSS concentration on oxygen mass transfer. Although backwashing is not described in great detail, its effects are represented in the model by resetting the initial condition in the cake deposition equation after each backwash period. The MBR model was implemented in Simulink® using the plant layout adopted in the MBR benchmark model of Maere et al. [160]. The model was then simulated with the inputs and operational parameters defined in [36, 160]. The results were compared against the MBR benchmark model of Maere et al. [160] which, contrary to this work, does not take into account the production of biopolymers, the membrane fouling, nor any interactions between the biological and the membrane parts of an MBR system

Optimal Scheduling of Variable Speed Pumps Using Mixed Integer Linear Programming -- Towards An Automated Approach

This article describes the methodology for formulating and solving optimal pump scheduling problems with variable-speed pumps (VSPs) as mixed integer linear programs (MILPs) using piece-linear approximations of the network components. The water distribution network (WDN) is simulated with an initial pump schedule for a defined time horizon, e.g. 24 hours, using a nonlinear algebraic solver. Next, the network element equations including VSPs are approximated with linear and piece-linear functions around chosen operating point(s). Finally, a fully parameterized MILP is formulated in which the objective is the total pumping cost. The method was used to solve a pump scheduling problem on a a simple two variable speed pump single-tank network that allows the reader to easily understand how the methodology works and how it is applied in practice. The obtained results showed that the formulation is robust and the optimizer is able to return global optimal result in a reliable manner for a range of operating points.Comment: Presented at 19th Computing and Control for the Water Industry Conference, CCWI 202

Proteomic patterns analysis with multivariate calculations as a promising tool for prompt differentiation of early stage lung tissue with cancer and unchanged tissue material

<p>Abstract</p> <p>Background</p> <p>Lung cancer diagnosis in tissue material with commonly used histological techniques is sometimes inconvenient and in a number of cases leads to ambiguous conclusions. Frequently advanced immunostaining techniques have to be employed, yet they are both time consuming and limited. In this study a proteomic approach is presented which may help provide unambiguous pathologic diagnosis of tissue material.</p> <p>Methods</p> <p>Lung tissue material found to be pathologically changed was prepared to isolate proteome with fast and non selective procedure. Isolated peptides and proteins in ranging from 3.5 to 20 kDa were analysed directly using high resolution mass spectrometer (MALDI-TOF/TOF) with sinapic acid as a matrix. Recorded complex spectra of a single run were then analyzed with multivariate statistical analysis algorithms (principle component analysis, classification methods). In the applied protocol we focused on obtaining the spectra richest in protein signals constituting a pattern of change within the sample containing detailed information about its protein composition. Advanced statistical methods were to indicate differences between examined groups.</p> <p>Results</p> <p>Obtained results indicate changes in proteome profiles of changed tissues in comparison to physiologically unchanged material (control group) which were reflected in the result of principle component analysis (PCA). Points representing spectra of control group were located in different areas of multidimensional space and were less diffused in comparison to cancer tissues. Three different classification algorithms showed recognition capability of 100% regarding classification of examined material into an appropriate group.</p> <p>Conclusion</p> <p>The application of the presented protocol and method enabled finding pathological changes in tissue material regardless of localization and size of abnormalities in the sample volume. Proteomic profile as a complex, rich in signals spectrum of proteins can be expressed as a single point in multidimensional space and than analysed using advanced statistical methods. This approach seems to provide more precise information about a pathology and may be considered in futer evaluation of biomarkers for clinical applications in different pathology. Multiparameter statistical methods may be helpful in elucidation of newly expressed sensitive biomarkers defined as many factors "in one point".</p

On strong equilibria and improvement dynamics in network creation games

We study strong equilibria in network creation games. These form a classical and well-studied class of games where a set of players form a network by buying edges to their neighbors at a cost of a fixed parameter \xce\xb1. The cost of a player is defined to be the cost of the bought edges plus the sum of distances to all the players in the resulting graph. We identify and characterize various structural properties of strong equilibria, which lead to a characterization of the set of strong equilibria for all \xce\xb1 in the range (0, 2). For \xce\xb1> 2, Andelman et al. [4] prove that a star graph in which every leaf buys one edge to the center node is a strong equilibrium, and conjecture that in fact any star is a strong equilibrium. We resolve this conjecture in the affirmative. Additionally, we show that when \xce\xb1 is large enough (\xe2\x89\xa5 2 n) there exist non-star trees that are strong equilibria. For the strong price of anarchy, we provide precise expressions when \xce\xb1 is in the range (0, 2), and we prove a lower bound of 3/2 when \xce\xb1\xe2\x89\xa5 2. Lastly, we aim to characterize under which conditions (coalitional) improvement dynamics may converge to a strong equilibrium. To this end, we study the (coalitional) finite improvement property and (coalitional) weak acyclicity property. We prove various conditions under which these properties do and do not hold. Some of these results also hold for the class of pure Nash equilibria

Hydraulic modelling for pressure reducing valve controller design addressing disturbance rejection and stability properties

Open Access articlePressure reducing valves (PRVs) are widely used in water distribution systems to reduce excess pressure caused by variations in terrain elevation or by excessive pumping. The fundamental role of a PRV is to maintain a desired outlet pressure irrespectively of hydraulic conditions in the water distribution network (WDN). Unfortunately, even a stable PRV can exhibit poor disturbance rejection resulting in variations of outlet pressure around the setpoint due to randomly varying demands. The aim of this paper is to better understand this phenomenon and to develop models which would facilitate designing effective controllers considering the stability and disturbance rejection issue

ASM1-based activated sludge model with biopolymer kinetics for integrated simulation of membrane bioreactors for wastewater treatment

This paper presents an activated sludge model suitable for modelling membrane bioreactors (MBRs) for wastewater treatment. The model, later referred to as combined EPS and SMP production ASM1-based model (CES-ASM1), extends Activated Sludge Model No. 1 (ASM1) with biokinetics of two types of bacterial biopolymers: soluble microbial products (SMP) and extracellular polymeric substances (EPS). The biopolymer kinetics in CES-ASM1 are, in their majority, borrowed from Laspidou and Rittmann[1] although, as shall be explained in the article, with one conceptual correction a kinetic pathway of biomass associated products (BAP). CES-ASM1 was calibrated on published experimental results from batch and continuous flow laboratory and pilot plant experiments and proved to be in good agreement with measurements. Standard set of parameters was then proposed as a combination of empirically identified and literature values. The model was then used to predict SMP and EPS production in an activated sludge system under various operating conditions