Kinetic Study of Gluconic Acid Batch Fermentation by Aspergillus niger

Gluconic acid is one of interesting chemical products in industries such as detergents, leather, photographic, textile, and especially in food and pharmaceutical industries. Fermentation is an advantageous process to produce gluconic acid. Mathematical modeling is important in the design and operation of fermentation process. In fact, kinetic data must be available for modeling. The kinetic parameters of gluconic acid production by Aspergillus niger in batch culture was studied in this research at initial substrate concentration of 150, 200 and 250 g/l. The kinetic models used were logistic equation for growth, Luedeking-Piret equation for gluconic acid formation, and Luedeking-Piret-like equation for glucose consumption. The Kinetic parameters in the model were obtained by minimizing non linear least squares curve fitting.

New Technologies for Modeling of Gas Turbine Cooled Blades

In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade

Mathematical Approach towards Fault Detection and Isolation of Linear Dynamical Systems

The main objective of this work is to provide a fault detection and isolation based on Markov parameters for residual generation and a neural network for fault classification. The diagnostic approach is accomplished in two steps: In step 1, the system is identified using a series of input / output variables through an identification algorithm. In step 2, the fault is diagnosed comparing the Markov parameters of faulty and non faulty systems. The Artificial Neural Network is trained using predetermined faulty conditions serves to classify the unknown fault. In step 1, the identification is done by first formulating a Hankel matrix out of Input/ output variables and then decomposing the matrix via singular value decomposition technique. For identifying the system online sliding window approach is adopted wherein an open slit slides over a subset of 'n' input/output variables. The faults are introduced at arbitrary instances and the identification is carried out in online. Fault residues are extracted making a comparison of the first five Markov parameters of faulty and non faulty systems. The proposed diagnostic approach is illustrated on benchmark problems with encouraging results.

Autonomous Underwater Vehicle (AUV) Dynamics Modeling and Performance Evaluation

A sophisticated simulator provides a cost-effective measure to carry out preliminary mission testing and diagnostic while reducing potential failures for real life at sea trials. The presented simulation framework covers three key areas: AUV modeling, sensor modeling, and environment modeling. AUV modeling mainly covers the area of AUV dynamics. Sensor modeling deals with physics and mathematical models that govern each sensor installed onto the AUV. Environment model incorporates the hydrostatic, hydrodynamics, and ocean currents that will affect the AUV in a real-time mission. Based on this designed simulation framework, custom scenarios provided by the user can be modeled and its corresponding behaviors can be observed. This paper focuses on the accuracy of the simulated data from AUV model and environmental model derived from a developed AUV test-bed which was jointly upgraded by DSTO and the University of Adelaide. The main contribution of this paper is to experimentally verify the accuracy of the proposed simulation framework.

Thermal and Visual Performance of Solar Control Film

The use of solar control film on windows as one of solar passive strategies for building have becoming important and is gaining recognition. Malaysia located close to equator is having warm humid climate with long sunshine hours and abundant solar radiation throughout the year. Hence, befitting solar control on windows is absolutely necessary to capture the daylight whilst moderating thermal impact and eliminating glare problems. This is one of the energy efficient strategies to achieve thermal and visual comfort in buildings. Therefore, this study was carried out to investigate the effect of window solar controls on thermal and visual performance of naturally ventilated buildings. This was conducted via field data monitoring using a test building facility. Four types of window glazing systems were used with three types of solar control films. Data were analysed for thermal and visual impact with reference to thermal and optical characteristics of the films. Results show that for each glazing system, the surface temperature of windows are influenced by the Solar Energy Absorption property, the indoor air temperature are influenced by the Solar Energy Transmittance and Solar Energy Reflectance, and the daylighting by Visible Light Transmission and Shading Coefficient. Further investigations are underway to determine the mathematical relation between thermal energy and visual performance with the thermal and optical characteristics of solar control films.

A Shallow Water Model for Computing Inland Inundation Due to Indonesian Tsunami 2004 Using a Moving Coastal Boundary

In this paper, a two-dimensional mathematical model is developed for estimating the extent of inland inundation due to Indonesian tsunami of 2004 along the coastal belts of Peninsular Malaysia and Thailand. The model consists of the shallow water equations together with open and coastal boundary conditions. In order to route the water wave towards the land, the coastal boundary is treated as a time dependent moving boundary. For computation of tsunami inundation, the initial tsunami wave is generated in the deep ocean with the strength of the Indonesian tsunami of 2004. Several numerical experiments are carried out by changing the slope of the beach to examine the extent of inundation with slope. The simulated inundation is found to decrease with the increase of the slope of the orography. Correlation between inundation / recession and run-up are found to be directly proportional to each other.

Quality Factor Variation with Transform Order in Fractional Fourier Domain

Fractional Fourier Transform is a powerful tool, which is a generalization of the classical Fourier Transform. This paper provides a mathematical relation relating the span in Fractional Fourier domain with the amplitude and phase functions of the signal, which is further used to study the variation of quality factor with different values of the transform order. It is seen that with the increase in the number of transients in the signal, the deviation of average Fractional Fourier span from the frequency bandwidth increases. Also, with the increase in the transient nature of the signal, the optimum value of transform order can be estimated based on the quality factor variation, and this value is found to be very close to that for which one can obtain the most compact representation. With the entire mathematical analysis and experimentation, we consolidate the fact that Fractional Fourier Transform gives more optimal representations for a number of transform orders than Fourier transform.

Futures Trading: Design of a Strategy

The paper describes the futures trading and aims to design the speculators trading strategy. The problem is formulated as the decision making task and such as is solved. The solution of the task leads to complex mathematical problems and the approximations of the decision making is demanded. Two kind of approximation are used in the paper: Monte Carlo for the multi-step prediction and iteration spread in time for the optimization. The solution is applied to the real-market data and the results of the off-line experiments are presented.

A Forecast Model for Projecting the Amount of Hazardous Waste

The objective of the paper is to develop the forecast model for the HW flows. The methodology of the research included 6 modules: historical data, assumptions, choose of indicators, data processing, and data analysis with STATGRAPHICS, and forecast models. The proposed methodology was validated for the case study for Latvia. Hypothesis on the changes in HW for time period of 2010-2020 have been developed and mathematically described with confidence level of 95.0% and 50.0%. Sensitivity analysis for the analyzed scenarios was done. The results show that the growth of GDP affects the total amount of HW in the country. The total amount of the HW is projected to be within the corridor of – 27.7% in the optimistic scenario up to +87.8% in the pessimistic scenario with confidence level of 50.0% for period of 2010-2020. The optimistic scenario has shown to be the least flexible to the changes in the GDP growth.

Modeling and Parametric Study for CO2/CH4 Separation Using Membrane Processes

The upgrading of low quality crude natural gas (NG) is attracting interest due to high demand of pipeline-grade gas in recent years. Membrane processes are commercially proven technology for the removal of impurities like carbon dioxide from NG. In this work, cross flow mathematical model has been suggested to be incorporated with ASPEN HYSYS as a user defined unit operation in order to design the membrane system for CO2/CH4 separation. The effect of operating conditions (such as feed composition and pressure) and membrane selectivity on the design parameters (methane recovery and total membrane area required for the separation) has been studied for different design configurations. These configurations include single stage (with and without recycle) and double stage membrane systems (with and without permeate or retentate recycle). It is shown that methane recovery can be improved by recycling permeate or retentate stream as well as by using double stage membrane systems. The ASPEN HYSYS user defined unit operation proposed in the study has potential to be applied for complex membrane system design and optimization.

On Leak Localization in the Main Branched and Simple Inclined Gas Pipelines

In this paper two mathematical models for definition of gas accidental escape localization in the gas pipelines are suggested. The first model was created for leak localization in the horizontal branched pipeline and second one for leak detection in inclined section of the main gas pipeline. The algorithm of leak localization in the branched pipeline did not demand on knowledge of corresponding initial hydraulic parameters at entrance and ending points of each sections of pipeline. For detection of the damaged section and then leak localization in this section special functions and equations have been constructed. Some results of calculations for compound pipelines having two, four and five sections are presented. Also a method and formula for the leak localization in the simple inclined section of the main gas pipeline are suggested. Some results of numerical calculations defining localization of gas escape for the inclined pipeline are presented.

Mixture Design Experiment on Flow Behaviour of O/W Emulsions as Affected by Polysaccharide Interactions

Interaction effects of xanthan gum (XG), carboxymethyl cellulose (CMC), and locust bean gum (LBG) on the flow properties of oil-in-water emulsions were investigated by a mixture design experiment. Blends of XG, CMC and LBG were prepared according to an augmented simplex-centroid mixture design (10 points) and used at 0.5% (wt/wt) in the emulsion formulations. An appropriate mathematical model was fitted to express each response as a function of the proportions of the blend components that are able to empirically predict the response to any blend of combination of the components. The synergistic interaction effect of the ternary XG:CMC:LBG blends at approximately 33-67% XG levels was shown to be much stronger than that of the binary XG:LBG blend at 50% XG level (p < 0.05). Nevertheless, an antagonistic interaction effect became significant as CMC level in blends was more than 33% (p < 0.05). Yield stress and apparent viscosity (at 10 s-1) responses were successfully fitted with a special quartic model while flow behaviour index and consistency coefficient were fitted with a full quartic model (R2 adjusted ≥ 0.90). This study found that a mixture design approach could serve as a valuable tool in better elucidating and predicting the interaction effects beyond the conventional twocomponent blends.

Lagrange-s Inversion Theorem and Infiltration

Implicit equations play a crucial role in Engineering. Based on this importance, several techniques have been applied to solve this particular class of equations. When it comes to practical applications, in general, iterative procedures are taken into account. On the other hand, with the improvement of computers, other numerical methods have been developed to provide a more straightforward methodology of solution. Analytical exact approaches seem to have been continuously neglected due to the difficulty inherent in their application; notwithstanding, they are indispensable to validate numerical routines. Lagrange-s Inversion Theorem is a simple mathematical tool which has proved to be widely applicable to engineering problems. In short, it provides the solution to implicit equations by means of an infinite series. To show the validity of this method, the tree-parameter infiltration equation is, for the first time, analytically and exactly solved. After manipulating these series, closed-form solutions are presented as H-functions.

Study of Damage in Beams with Different Boundary Conditions

–In this paper the damage in clamped-free, clampedclamped and free-free beam are analyzed considering samples without and with structural modifications. The damage location is investigated by the use of the bispectrum and wavelet analysis. The mathematical models are obtained using 2D elasticity theory and the Finite Element Method (FEM). The numerical and experimental data are approximated using the Particle Swarm Optimizer (PSO) method and this way is possible to adjust the localization and the severity of the damage. The experimental data are obtained through accelerometers placed along the sample. The system is excited using impact hammer.

Analysis of Self Excited Induction Generator using Particle Swarm Optimization

In this paper, Novel method, Particle Swarm Optimization (PSO) algorithm, based technique is proposed to estimate and analyze the steady state performance of self-excited induction generator (SEIG). In this novel method the tedious job of deriving the complex coefficients of a polynomial equation and solving it, as in previous methods, is not required. By comparing the simulation results obtained by the proposed method with those obtained by the well known mathematical methods, a good agreement between these results is obtained. The comparison validates the effectiveness of the proposed technique.

Bridging the Mental Gap between Convolution Approach and Compartmental Modeling in Functional Imaging: Typical Embedding of an Open Two-Compartment Model into the Systems Theory Approach of Indicator Dilution Theory

Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.

Application of Ant Colony Optimization for Multi-objective Production Problems

This paper proposes a meta-heuristic called Ant Colony Optimization to solve multi-objective production problems. The multi-objective function is to minimize lead time and work in process. The problem is related to the decision variables, i.e.; distance and process time. According to decision criteria, the mathematical model is formulated. In order to solve the model an ant colony optimization approach has been developed. The proposed algorithm is parameterized by the number of ant colonies and the number of pheromone trails. One example is given to illustrate the effectiveness of the proposed model. The proposed formulations; Max-Min Ant system are then used to solve the problem and the results evaluate the performance and efficiency of the proposed algorithm using simulation.

Cost and Profit Analysis of Markovian Queuing System with Two Priority Classes: A Computational Approach

This paper focuses on cost and profit analysis of single-server Markovian queuing system with two priority classes. In this paper, functions of total expected cost, revenue and profit of the system are constructed and subjected to optimization with respect to its service rates of lower and higher priority classes. A computing algorithm has been developed on the basis of fast converging numerical method to solve the system of non linear equations formed out of the mathematical analysis. A novel performance measure of cost and profit analysis in view of its economic interpretation for the system with priority classes is attempted to discuss in this paper. On the basis of computed tables observations are also drawn to enlighten the variational-effect of the model on the parameters involved therein.

A Method for 3D Mesh Adaptation in FEA

The use of the mechanical simulation (in particular the finite element analysis) requires the management of assumptions in order to analyse a real complex system. In finite element analysis (FEA), two modeling steps require assumptions to be able to carry out the computations and to obtain some results: the building of the physical model and the building of the simulation model. The simplification assumptions made on the analysed system in these two steps can generate two kinds of errors: the physical modeling errors (mathematical model, domain simplifications, materials properties, boundary conditions and loads) and the mesh discretization errors. This paper proposes a mesh adaptive method based on the use of an h-adaptive scheme in combination with an error estimator in order to choose the mesh of the simulation model. This method allows us to choose the mesh of the simulation model in order to control the cost and the quality of the finite element analysis.

Symbolic Analysis of Large Circuits Using Discrete Wavelet Transform

Symbolic Circuit Analysis (SCA) is a technique used to generate the symbolic expression of a network. It has become a well-established technique in circuit analysis and design. The symbolic expression of networks offers excellent way to perform frequency response analysis, sensitivity computation, stability measurements, performance optimization, and fault diagnosis. Many approaches have been proposed in the area of SCA offering different features and capabilities. Numerical Interpolation methods are very common in this context, especially by using the Fast Fourier Transform (FFT). The aim of this paper is to present a method for SCA that depends on the use of Wavelet Transform (WT) as a mathematical tool to generate the symbolic expression for large circuits with minimizing the analysis time by reducing the number of computations.