Homayoun Najjaran

Microfluidics Integrated Biosensors: A Leading Technology towards Lab-on-a-Chip and Sensing Applications

A biosensor can be defined as a compact analytical device or unit incorporating a biological or biologically derived sensitive recognition element immobilized on a physicochemical transducer to measure one or more analytes. Microfluidic systems, on the other hand, provide throughput processing, enhance transport for controlling the flow conditions, increase the mixing rate of different reagents, reduce sample and reagents volume (down to nanoliter), increase sensitivity of detection, and utilize the same platform for both sample preparation and detection. In view of these advantages, the integration of microfluidic and biosensor technologies provides the ability to merge chemical and biological components into a single platform and offers new opportunities for future biosensing applications including portability, disposability, real-time detection, unprecedented accuracies, and simultaneous analysis of different analytes in a single device. This review aims at representing advances and achievements in the field of microfluidic-based biosensing. The review also presents examples extracted from the literature to demonstrate the advantages of merging microfluidic and biosensing technologies and illustrate the versatility that such integration promises in the future biosensing for emerging areas of biological engineering, biomedical studies, point-of-care diagnostics, environmental monitoring, and precision agriculture.

Fuzzy Expert System to Assess Corrosion of Cast/Ductile Iron Pipes from Backfill Properties

: Several factors may contribute to the structural failure of cast and ductile iron water mains, the most important of which is considered to be corrosion. The ANSI/AWWA C105/A21.5-99 10-point scoring (10-P) method is commonly used to predict the corrosivity potential of a given soil sample using certain soil properties. The 10-P and other scoring methods use binary logic to classify the soil as either corrosive or noncorrosive. Fuzzy logic extends binary logic in this context as it recognizes the real world phenomena using a certain degree of membership between 0 and 1. This article presents a fuzzy logic expert system capable of predicting the deterioration of cast and ductile iron water mains based on surrounding soil properties. The proposed model consists of two modules: a knowledge base and an inference mechanism. The knowledge base provides information for better decision making and is developed in a two-tier fuzzy modeling process. First in direct approach, the expert knowledge generates a subjective model to describe the characteristics of the system using fuzzy linguistic variables. Later in system identification, the field data are used to develop an objective model, which is eventually used in conjunction with the subjective model to provide a more reliable knowledge base for the expert system. The inference mechanism uses fuzzy approximate reasoning methods to process the encoded information of the knowledge base.

Online Drinking Water Quality Monitoring: Review on Available and Emerging Technologies

Online drinking water quality monitoring technologies have made significant progress for source water surveillance and water treatment plant operation. The use of these technologies in the distribution system has not been favorable due to the high costs associated with installation, maintenance, and calibration of a large distributed array of monitoring sensors. This has led to a search for newer technologies that can be economically deployed on a large scale. This paper includes a brief description of important parameters for drinking water and current available technologies used in the field. The paper also provides a thorough review of the advances in sensor technology for measurement of common water quality parameters (pH, turbidity, free chlorine, dissolved oxygen, and conductivity) in drinking water distribution systems.

Leakage detection and location in water distribution systems using a fuzzy-based methodology

Loss of water due to leakage is a common phenomenon observed practically in all water distribution systems (WDS). However, the leakage volume can be reduced significantly if the occurrence of leakage is detected within minimal time after its occurrence. This paper proposes a novel methodology to detect and diagnose leakage in WDS. In the proposed methodology, a fuzzy-based algorithm has been employed that incorporates various uncertainties into different WDS parameters such as roughness, nodal demands, and water reservoir levels. Monitored pressure in different nodes and flow in different pipes have been used to estimate the degree of membership of leakage and its severity in terms of index of leakage propensity (ILP). Based on the degrees of leakage memberships and the ILPs, the location of the nearest leaky node or leaky pipe has been identified. To demonstrate the effectiveness of the proposed methodology, a small distribution network was investigated which showed very encouraging results. The proposed methodology has a significant potential to help water utility managers to detect and locate leakage in WDS within a minimal time after its occurrence and can help to prioritise leakage management strategies.

Dynamic analysis and human analogous control of a pipe crawling robot

In this paper the design and development of a crawling robot for inspection of live water pipes are addressed. The mechanical design of the robot is described in detail. The governing dynamics equations of the robot moving against water flow as well as gravity in a straight pipe are also derived. Specifically, the hydrodynamic forces exerted on the robot when moving in a live pressurized pipe are taken into account. Two fuzzy-logic based control strategies are adopted. The first one is to maintain a constant translational speed in robots motion when subjected to flow disturbances that are numerically modeled using step changes in flow velocity within a human-in-the-loop real-time simulation environment, and the second is to steer the real robot inside the pipe while following a numerically modeled time-varying velocity set point with no fluid present in the pipe. The controller parameters were tuned based on data obtained from a human-in-the-loop control system via an artificial neural network.

Real-time motion planning of an autonomous mobile manipulator using a fuzzy adaptive Kalman filter

This paper presents the real-time motion planning i.e., map building and path planning of an autonomous mobile manipulator capable of scanning natural terrain using a detector e.g., a landmine detector. Map building generates a terrain map using the measurements of laser and ultrasonic rangefinders, and path planning uses the map to define an obstacle-free path for the detector. Map building involves sensor fusion to tackle the uncertainties associated with range measurement. Fusion takes place in a hierarchical filtering process that updates the map in real time and also optimizes the scanning process based on the terrain type. The filtering process includes a proposed fuzzy adaptive Kalman filter in which the gain of the filter is adapted using a fuzzy model that characterizes the terrain. The efficiency of the proposed map building and path planning methods has been verified by experiments on a prototype mine detector robot.

Exploring the Relationship between Soil Properties and Deterioration of Metallic Pipes Using Predictive Data Mining Methods

Soil corrosivity is considered to be a major factor for the deterioration of metallic water mains. Using a 10-point scoring method as suggested by the American Water Works Association, soil corrosivity potential can be estimated by five soil properties: (1) resistivity; (2) pH value; (3) redox potential; (4) sulfide; and (5) percentage of clay fines. However, the relationship between soil corrosivity and pipe deterioration is often ambiguous and not well-defined. In order to identify the direct relationship between soil properties and pipe deterioration, which is defined as the ratio of the maximum pit depth to pipe age, predictive data mining approaches are investigated in this study. Both single- and multipredictor based approaches are employed to model such relationship. The advantage of combining multiple predictors is also demonstrated. Among all approaches, rotation forest achieves the best result in terms of the prediction error to estimate pipe deterioration rate. Compared to the random forest method, which is next to the best, the normalized mean square error decreased 50%. With the proposed approaches, the assessment of pipe condition can be achieved by analyzing soil properties. This study also highlights the importance for collecting more reliable soil properties data.

Two-dimensional flow dynamics in digital microfluidic systems

A two-dimensional model for the fluid flow in a digital microfluidic system is introduced, and the results are compared to experimental data. Resistive flow effects based upon contact line forces, filler effects and shear forces are applied in the model. It is found that the induced vertical velocity components are critical to the overall motion, as velocity and pressure gradients, together with microdroplet surface deformations, can limit the desired horizontal velocity. These effects are particularly important for digital microfluidic systems characterized by higher Reynolds numbers.

Development of Visual Simultaneous Localization and Mapping (VSLAM) for a Pipe Inspection Robot

This paper describes a visual simultaneous localization and mapping (VSLAM) method for a pipe inspection robot that can serve as a carrier for nondestructive testing (NDT) sensors inside in-service water mains. The proposed method features a multi-sensor fusion system that simultaneously executes two important functions of the robot: construct a global image of the internal surface of the pipe and provide the location of the NDT sensors. The fusion involves a synergy between image mosaicing and dead reckoning. More precisely, the sequential images of a digital camera are stitched together with the help of an inertial navigation system (INS). In the proposed model, the processing load of image mosaicing is reduced significantly, and at the same time the accumulation of error of the INS is prevented. The functionality of the model is verified using a simulator that mimics the motion of a pipe inspection robot inside a water main.

Fabrication of digital microfluidic devices on flexible paper-based and rigid substrates via screen printing

In this work, a new fabrication method is presented for digital microfluidic (DMF) devices in which the electrodes are generated using the screen printing technique. This method is applicable to both rigid and flexible substrates. The proposed screen printing approach, as a batch printing technique, is advantageous to the widely reported DMF fabrication methods in terms of fabrication time, cost and capability of mass production. Screen printing provides an effective means for printing different types of conductive materials on a variety of substrates. Specifically, screen printing of conductive silver and carbon based inks is performed on paper, glass and wax paper. As a result, the fabricated DMF devices are characterized by being flexible, disposable and incinerable. Hence, the main advantage of screen printing carbon based inks on paper substrates is more pronounced for point-of-care applications that require a large number of low cost DMF chips, and laboratory setups that lack sophisticated microfabrication facilities. The resolution of the printed DMF electrodes generated by this technique is examined for proof of concept using manual screen printing, but higher resolution screens and automated machines are available off-the-shelf, if needed. Another contribution of this research is the improved actuation techniques that facilitate droplet transport in electrode configurations with relatively large electrode spacing to alleviate the disadvantage of lower resolution screens. Thus, we were able to reduce the cost of fabrication significantly without compromising the DMF performance. The paper-based devices have already shown to be effective in continuous microfluidics domain, so the investigation of their applicability in DMF systems is worthwhile. With this in mind, successful integration of a paper-based microchannel with paper-based digital microfluidic chip is demonstrated in this work.