Mohammad Rajabi

Bio: Mohammad Rajabi is an academic researcher from Katholieke Universiteit Leuven. The author has contributed to research in topics: Materials science & Wireless power transfer. The author has an hindex of 10, co-authored 30 publications receiving 323 citations. Previous affiliations of Mohammad Rajabi include Tarbiat Modares University & Babol Noshirvani University of Technology.

Optimal Management of a Freshwater Lens in a Small Island Using Surrogate Models and Evolutionary Algorithms

Abstract: This paper examines a linked simulation-optimization procedure based on the combined application of an artificial neural network (ANN) and genetic algorithm (GA) with the aim of developing an efficient model for the multiobjective management of groundwater lenses in small islands. The simulation-optimization methodology is applied to a real aquifer in Kish Island of the Persian Gulf to determine the optimal groundwater-extraction while protecting the freshwater lens from seawater intrusion. The initial simulations are based on the application of SUTRA, a variable-density groundwater numerical model. The numerical model parameters are calibrated through automated parameter estimation. To make the optimization process computationally feasible, the numerical model is subsequently replaced by a trained ANN model as an approximate simulator. Even with a moderate number of input data sets based on the numerical simulations, the ANN metamodel can be efficiently trained. The ANN model is subsequently linked with GA to identify the nondominated or Pareto-optimal solutions. To provide flexibility in the implementation of the management plan, the model is built upon optimizing extraction from a number of zones instead of point-well locations. Two issues are of particular interest to the research reported in this paper are: (1) how the general idea of minimizing seawater intrusion can be effectively represented by objective functions within the framework of the simulation-optimization paradigm, and (2) the implications of applying the methodology to a real-world small-island groundwater lens. Four different models have been compared within the framework of multiobjective optimization, including (1) minimization of maximum salinity at observation wells, (2) minimization of the root mean square (RMS) change in concentrations over the planning period, (3) minimization of the arithmetic mean, and (4) minimization of the trimmed arithmetic mean of concentration in the observation wells. The latter model can provide a more effective framework to incorporate the general objective of minimizing seawater intrusion. This paper shows that integration of the latest innovative tools can provide the ability to solve complex real-world optimization problems in an effective way. DOI: 10.1061/(ASCE)HE.1943-5584 .0000809. © 2014 American Society of Civil Engineers.

Bandwidth Analysis of RF-DC Converters Under Multisine Excitation

Abstract: The use of multisine signals to improve the efficiency of wireless power transfer (WPT) for low average received power was proposed recently. Several measurement-based studies illustrated the gain that can be achieved for different circuit or waveform instances, focusing on the impact of a time-varying amplitude on the rectifying efficiency. This paper first establishes a model enabling a thorough analysis of the multisine-based WPT system focusing on the bandwidth of the signal and the rectifier. This model enables a codesign of signal and rectifier for optimal WPT. The proposed model provides insight into the output voltage and power, as a function of the input waveform for different circuit models. By including the input matching and the clamper, our model is generic and can include a wide range of rectifiers with different voltage multiplication approaches. The key insight gained from our analysis is that there is a tradeoff between the frequency spacing of the tones of the multisine signal and the cut-off frequency of the low-pass RC filter, as a main property of the rectifier circuit. Our model predicts the measured power conversion efficiency and voltage with an error below 0.1 and 0.2 V, respectively.

Enhanced Biased ASK Modulation Performance for SWIPT With AWGN Channel and Dual-Purpose Hardware

Abstract: A lot of small sensors are deployed in Internet of Things applications. Simultaneous wireless information and power transfer (SWIPT) is a solution to avoid a large amount of batteries, while exchanging information with the sensors. Combining both energy harvesting and information receiving in dual-purpose hardware lowers power consumption while also decreasing sensor size. Biased amplitude shift keying (ASK) is introduced as a solution for the SWIPT modulation technique. In particular, the design of enhanced biased ASK modulation in case of an additive white Gaussian noise channel is analyzed in this paper. Novel formulas for symbol error rate are derived, while improvements of the modulation scheme are proposed based on measurements, taking rectifier nonlinearity into account and resulting in reducing the transmitted power by 14 dB for fixed error rate.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

Abstract: The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs

Abstract: Radio waves carry both energy and information simultaneously. Nevertheless, radio-frequency (RF) transmissions of these quantities have traditionally been treated separately. Currently, the community is experiencing a paradigm shift in wireless network design, namely, unifying wireless transmission of information and power so as to make the best use of the RF spectrum and radiation as well as the network infrastructure for the dual purpose of communicating and energizing. In this paper, we review and discuss recent progress in laying the foundations of the envisioned dual purpose networks by establishing a signal theory and design for wireless information and power transmission (WIPT) and identifying the fundamental tradeoff between conveying information and power wirelessly. We start with an overview of WIPT challenges and technologies, namely, simultaneous WIPT (SWIPT), wirelessly powered communication networks (WPCNs), and wirelessly powered backscatter communication (WPBC). We then characterize energy harvesters and show how WIPT signal and system designs crucially revolve around the underlying energy harvester model. To that end, we highlight three different energy harvester models, namely, one linear model and two nonlinear models, and show how WIPT designs differ for each of them in single-user and multi-user deployments. Topics discussed include rate-energy region characterization, transmitter and receiver architectures, waveform design, modulation, beamforming and input distribution optimizations, resource allocation, and RF spectrum use. We discuss and check the validity of the different energy harvester models and the resulting signal theory and design based on circuit simulations, prototyping, and experimentation. We also point out numerous directions that are promising for future research.

A Framework for Dealing With Uncertainty due to Model Structure Error

Abstract: Although uncertainty about structures of environmental models (conceptual uncertainty) is often acknowledged to be the main source of uncertainty in model predictions, it is rarely considered in environmental modelling. Rather, formal uncertainty analyses have traditionally focused on model parameters and input data as the principal source of uncertainty in model predictions. The traditional approach to model uncertainty analysis, which considers only a single conceptual model, may fail to adequately sample the relevant space of plausible conceptual models. As such, it is prone to modelling bias and underestimation of predictive uncertainty. In this paper we review a range of strategies for assessing structural uncertainties in models. The existing strategies fall into two categories depending on whether field data are available for the predicted variable of interest. To date, most research has focussed on situations where inferences on the accuracy of a model structure can be made directly on the basis of field data. This corresponds to a situation of ‘interpolation’. However, in many cases environmental models are used for ‘extrapolation’; that is, beyond the situation and the field data available for calibration. In the present paper, a framework is presented for assessing the predictive uncertainties of environmental models used for extrapolation. It involves the use of multiple conceptual models, assessment of their pedigree and reflection on the extent to which the sampled models adequately represent the space of plausible models. � 2005 Elsevier Ltd. All rights reserved.

Global change and the groundwater management challenge

Abstract: With rivers in critical regions already exploited to capacity throughout the world and groundwater overdraft as well as large-scale contamination occurring in many areas, we have entered an era in which multiple simultaneous stresses will drive water management. Increasingly, groundwater resources are taking a more prominent role in providing freshwater supplies. We discuss the competing fresh groundwater needs for human consumption, food production, energy, and the environment, as well as physical hazards, and conflicts due to transboundary overexploitation. During the past 50 years, groundwater management modeling has focused on combining simulation with optimization methods to inspect important problems ranging from contaminant remediation to agricultural irrigation management. The compound challenges now faced by water planners require a new generation of aquifer management models that address the broad impacts of global change on aquifer storage and depletion trajectory management, land subsidence, groundwater-dependent ecosystems, seawater intrusion, anthropogenic and geogenic contamination, supply vulnerability, and long-term sustainability. The scope of research efforts is only beginning to address complex interactions using multiagent system models that are not readily formulated as optimization problems and that consider a suite of human behavioral responses.