Modelling techniques for biological systems

The objective of this investigation has been to develop and evaluate techniques which are appropriate to the modelling and simulation of biological reaction system behaviour. The model used as the basis for analysis of modelling and simulation techniques is a reduced version of the biological model proposed by the IAWPRC Task Group for mathematical modell ing in wastewater treatment design. This limited model has the advantage of being easily manageable in terms of analysis and presentation of the simulation techniQues whilst at the same time incorporating a range of features encountered with biological growth applications in general. Because a model may incorporate a number of different components and large number of biological conversion processes, a convenient method of presentation was found to be a matrix format. The matrix representation ensures clarity as to what compounds, processes and react ion terms are to be incorporated and allows easy comparison of different models. In addition, it facilitates transforming the model into a computer program. Simulation of the system response first involves specifying the reactor configuration and flow patterns. With this information fixed, mass balances for each compound in each reactor can be completed. These mass balances constitute a set of simultaneous non-linear differential and algebraic eQuations which, when solved, characterise the system behaviour

Implicit Runge-Kutta formulae for the numerical integration of ODEs

Imperial Users onl

CLASSIFICATION OF T\TEUROMUSCIILAR DISORDERSI BASED ON ELECTROMYOGRAPTTY (EMG) SIGNALS

Electromyography (EMG) signals are the measune of activity in the muscles. The motion of the muscles will be generated and recorded using skin surface electrodes. EMG signals can be found from anywhere on the exterior of human's body such as biceps, triceps, shoulder, arm, hand, leg. The aim of this project is to identifr the neuromuscular diseases based on EMG signals by means of classification. The ncuromuscular diseases that have been identified are healthy, myopathy and neuropathy. The signals weIE taken and analyzed from EMG lab database to become datasets for classification system. The classification was carried out using Artilicial Neural Network. In this project, there are two techniques that used to classifr three different types of muscular disorders such as Multilayer Perceptron (MLP) and Wavelet Neural Network (WlIhI). And the input that applied to these systems using feature extraction from EMC signals. In time domain, five feature extraction techniques that used to exmct the sample of signal such as Autoregressive (AR), Root mean square (RMS), Zero crossing (zc), waveform length (wL) and Mean Absolute Value (MA$. The comparison between different techniques will be included based on the accuracy of the result. The input data has been used in Multilayer Perceptron (MtP) to train the classification system. Besides that, frequency domain was used for extracting the useful information from EMG signal for Wavelet neural network (wl[Nr) such as Power Spectrum Density (pSD), both systems were hained and the test performances were examined after training to provide the best result

The Telecommunications and Data Acquisition Report

This publication, one of a series formerly titled The Deep Space Network (DSN) Progress Report, documents DSN progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics, and the radio search for extraterrestrial intelligence are reported

Reducing Uncertainties in the Velocities Determined by Inversion of Phase Velocity Dispersion Curves Using Synthetic Seismograms

Characterizing the near-surface shear-wave velocity structure using Rayleigh-wave phase velocity dispersion curves is widespread in the context of reservoir characterization, exploration seismology, earthquake engineering, and geotechnical engineering. This surface seismic approach provides a feasible and low-cost alternative to the borehole measurements. Phase velocity dispersion curves from Rayleigh surface waves are inverted to yield the vertical shear-wave velocity profile. A significant problem with the surface wave inversion is its intrinsic non-uniqueness, and although this problem is widely recognized, there have not been systematic efforts to develop approaches to reduce the pervasive uncertainty that affects the velocity profiles determined by the inversion. Non-uniqueness cannot be easily studied in a nonlinear inverse problem such as Rayleigh-wave inversion and the only way to understand its nature is by numerical investigation which can get computationally expensive and inevitably time consuming. Regarding the variety of the parameters affecting the surface wave inversion and possible non-uniqueness induced by them, a technique should be established which is not controlled by the non-uniqueness that is already affecting the surface wave inversion. An efficient and repeatable technique is proposed and tested to overcome the non-uniqueness problem; multiple inverted shear-wave velocity profiles are used in a wavenumber integration technique to generate synthetic time series resembling the geophone recordings. The similarity between synthetic and observed time series is used as an additional tool along with the similarity between the theoretical and experimental dispersion curves. The proposed method is proven to be effective through synthetic and real world examples. In these examples, the nature of the non-uniqueness is discussed and its existence is shown. Using the proposed technique, inverted velocity profiles are estimated and effectiveness of this technique is evaluated; in the synthetic example, final inverted velocity profile is compared with the initial target velocity model, and in the real world example, final inverted shear-wave velocity profile is compared with the velocity model from independent measurements in a nearby borehole. Real world example shows that it is possible to overcome the non-uniqueness and distinguish the representative velocity profile for the site that also matches well with the borehole measurements

Vorticity structure and evolution in a transverse jet with new algorithms for scalable particle simulation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.Includes bibliographical references (p. 188-200).Transverse jets arise in many applications, including propulsion, effluent dispersion, oil field flows, V/STOL aerodynamics, and drug delivery. Furthermore, they exemplify flows dominated by coherent structures that cascade into smaller scales, a source of many current challenges in fluid dynamics. This study seeks a fundamental, mechanistic understanding of the relationship between the dispersion of jet fluid and the underlying vortical structures of the transverse jet-and of how to develop actuation that optimally manipulates their dynamics to affect mixing. We develop a massively parallel 3-D vortex simulation of a high-momentum transverse jet at large Reynolds number, featuring a discrete filament representation of the vorticity field with local mesh refinement to capture stretching and folding and hair-pin removal to regularize the formation of small scales. A novel formulation of the vorticity flux boundary conditions rigorously accounts for the interaction of channel vorticity with the jet boundary layer. This formulation yields analytical expressions for vortex lines in near field of the jet and suggests effective modes of unsteady actuation at the nozzle. The present computational approach requires hierarchical N-body methods for velocity evaluation at each timestep, as direct summation is prohibitively expensive. We introduce new clustering algorithms for parallel domain decomposition of N-body interactions and demonstrate the optimality of the resulting cluster geometries. We also develop compatible techniques for dynamic load balancing, including adaptive scaling of cluster metrics and adaptive redistribution of their centroids. These tools extend to parallel hierarchical simulation of N-body problems in gravitational astrophysics,(cont.) molecular dynamics, and other fields. Simulations reveal the mechanisms by which vortical structures evolve; previous computational and experimental investigations of these processes have been incomplete at best, limited to low Reynolds numbers, transient early-stage dynamics, or Eulerian diagnostics of essentially Lagrangian phenomena. Transformation of the cylindrical shear layer emanating from the nozzle, initially dominated by azimuthal vorticity, begins with axial elongation of its lee side to form sections of counter-rotating vorticity aligned with the jet trajectory. Periodic rollup of the shear layer accompanies this deformation, creating arcs carrying azimuthal vorticity of alternating signs, curved toward the windward side of the jet. Following the pronounced bending of the trajectory into the crossflow, we observe a catastrophic breakdown of these sparse periodic structures into a dense distribution of smaller scales, with an attendant complexity of tangled vortex filaments. Nonetheless, spatial filtering of this region reveals the persistence of counter-rotating streamwise vorticity. We further characterize the flow by calculating maximum direct Lyapunov exponents of particle trajectories, identifying repelling material surfaces that organize finite-time mixing.by Youssef Mohamed Marzouk.Ph.D

Tractable multi-product pricing under discrete choice models

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 199-204).We consider a retailer offering an assortment of differentiated substitutable products to price-sensitive customers. Prices are chosen to maximize profit, subject to inventory/ capacity constraints, as well as more general constraints. The profit is not even a quasi-concave function of the prices under the basic multinomial logit (MNL) demand model. Linear constraints can induce a non-convex feasible region. Nevertheless, we show how to efficiently solve the pricing problem under three important, more general families of demand models. Generalized attraction (GA) models broaden the range of nonlinear responses to changes in price. We propose a reformulation of the pricing problem over demands (instead of prices) which is convex. We show that the constrained problem under MNL models can be solved in a polynomial number of Newton iterations. In experiments, our reformulation is solved in seconds rather than days by commercial software. For nested-logit (NL) demand models, we show that the profit is concave in the demands (market shares) when all the price-sensitivity parameters are sufficiently close. The closed-form expressions for the Hessian of the profit that we derive can be used with general-purpose nonlinear solvers. For the special (unconstrained) case already considered in the literature, we devise an algorithm that requires no assumptions on the problem parameters. The class of generalized extreme value (GEV) models includes the NL as well as the cross-nested logit (CNL) model. There is generally no closed form expression for the profit in terms of the demands. We nevertheless how the gradient and Hessian can be computed for use with general-purpose solvers. We show that the objective of a transformed problem is nearly concave when all the price sensitivities are close. For the unconstrained case, we develop a simple and surprisingly efficient first-order method. Our experiments suggest that it always finds a global optimum, for any model parameters. We apply the method to mixed logit (MMNL) models, by showing that they can be approximated with CNL models. With an appropriate sequence of parameter scalings, we conjecture that the solution found is also globally optimal.by Philipp Wilhelm Keller.Ph.D

Modeling the internal combustion engine

A flexible and computationally economical model of the internal combustion engine was developed for use on large digital computer systems. It is based on a system of ordinary differential equations for cylinder-averaged properties. The computer program is capable of multicycle calculations, with some parameters varying from cycle to cycle, and has restart capabilities. It can accommodate a broad spectrum of reactants, permits changes in physical properties, and offers a wide selection of alternative modeling functions without any reprogramming. It readily adapts to the amount of information available in a particular case because the model is in fact a hierarchy of five models. The models range from a simple model requiring only thermodynamic properties to a complex model demanding full combustion kinetics, transport properties, and poppet valve flow characteristics. Among its many features the model includes heat transfer, valve timing, supercharging, motoring, finite burning rates, cycle-to-cycle variations in air-fuel ratio, humid air, residual and recirculated exhaust gas, and full combustion kinetics

Space programs summary no. 37-27, volume IV for the period April 1, 1964 to May 31, 1964. Supporting research and advanced development

Space exploration programs - systems analysis - spacecraft power and guidance systems - propellant engineering and communications system