Effects of heating in air and chlorine atmosphere on the crystalline structure of pure Ta2O5 or mixed with carbon

Structure changes undergone by pure amorphous hydrated tantalum oxide mixed with different types of carbon when heated in air or chlorine atmospheres were monitored by X-ray diffraction (XRD) and scanning electronic microscopy (SEM). Heating in air of pure Ta2O5 causes the appearance of the hexagonal structure -Ta2O5 at 973 K and the ortho-rhombic structure -Ta2O5 at 1173 K. Heating in chlorine atmosphere markedly lowers the temperature at which transformation to the orthorhombic phase occurs. This effect is attributed to recrystallization of tantalum oxide from tantalum chloride and oxygen, both in gaseous phase, formed in a previous chlorination step of the amorphous oxide. When the thermal treatment is performed in chlorine atmosphere the presence of carbon permits the detection of the hexagonal form at 753 K; this temperature varies with the type of carbon and the oxide : carbon ration. © 1998 Kluwer Academic Publishers     

Staphylococcal growth and enterotoxin production in the presence of meat cultures (non LAB)

The effect of meat cultures (non lactic acid bacteria) on the growth and production of enterotoxins and thermonuclease by Staphylococcus aureus was studied. Micrococcus varians did not affect growth nor the synthesis of metabolites. Levels of enterotoxins A, B and D produced by the respective S. aureus strains were reduced by S. xylosus, S. saprophyticus and S. carnosus. The two latter species prevented production of enterotoxin C₁ and S. xylosus markedly reduced the amount produced. The three coagulase-negative staphylococci showed little inhibitory effect on the growth of S. aureus. Penicillium nalgiovense did not show inhibitory activity against the four S. aureus strains. Debaryomyces hansenii slightly inhibited growth of the enterotoxin A-producing strain, but reduced enterotoxin synthesis at 30 °C. Thermonuclease was detected whenever enterotoxins were detected though the influence of the effector organism was dependent on the test strain.     

Some questions on the corrosion of steel in concrete—Part I: when,how and how much steel corrodes

It is widely accepted that concrete-embedded steel is in a passive state. However, there are some exceptional circumstances that induce corosion in an active state within concrete structures, thereby severely reducing their durability. This two-part paper analyses some major questions which, however elementary they may be, are still controversial in scientific, technical and economic terms. The first part provides answers to the following questions on the steel/concrete/environment system:

1. How does steel in concrete normally behave?
2. What are the initiating factors for depassivation?
3. What are the effects of corrosion?
4. What is the morphology of corrosion in the active state? and
5. What is the corrosion rate threshold above which the durability of reinforced concrete structures is impaired? The answers to these questions are provided in light of experimental results, most of which were obtained by the authors themselves.

     

Partitioned formulation of internal and gravity waves interacting with flexible structures

This paper presents a partitioned modeling of internal and gravity fluid waves that interact with flexible structures. The governing interaction model consists of three completely partitioned entities: fluid model, structural model, and interface model that acts as an internal constraint on the fluid–structure interface boundary. Thus, the proposed partitioned multi-physics modeling can employ two completely modular fluid and structure software modules plus an interface solver, hence amenable to partitioned solution algorithms. The interface discretization can exploit the nonmatching interface algorithm previously developed via the method of localized Lagrange multipliers. Also noted is that the present fluid model can make use of widely available finite element software for standard Poisson-type problems.     

Optimization of biochemical systems through mathematical programming: Methods and applications

In this work we present a general (mono and multiobjective) optimization framework for the technological improvement of biochemical systems. The starting point of the method is a mathematical model in ordinary differential equations (ODEs) of the investigated system, based on qualitative biological knowledge and quantitative experimental data. In the method we take advantage of the special structural features of a family of ODEs called power-law models to reduce the computational complexity of the optimization program. In this way, the genetic manipulation of a biochemical system to meet a certain biotechnological goal can be expressed as an optimization program with some desired properties such as linearity or convexity.The general method of optimization is presented and discussed in its linear and geometric programming versions. We furthermore illustrate the use of the method by several real case studies. We conclude that the technological improvement of microorganisms can be afforded using the combination of mathematical modelling and optimization. The systematic nature of this approach facilitates the redesign of biochemical systems and makes this a predictive exercise rather than a trial-and-error procedure.     

A genetic solution based on lexicographical goal programming for a multiobjective job shop with uncertainty

In this work we consider a multiobjective job shop problem with uncertain durations and crisp due dates. Ill-known durations are modelled as fuzzy numbers. We take a fuzzy goal programming approach to propose a generic multiobjective model based on lexicographical minimisation of expected values. To solve the resulting problem, we propose a genetic algorithm searching in the space of possibly active schedules. Experimental results are presented for several problem instances, solved by the GA according to the proposed model, considering three objectives: makespan, tardiness and idleness. The results illustrate the potential of the proposed multiobjective model and genetic algorithm.     

A technique for defining agent-oriented engineering processes with tool support

The formalization of engineering processes is necessary for guaranteeing the quality and cost of the products involved. Agent-oriented engineering has already proposed development processes that still need to be further formalized to be applicable by non-researchers. This paper proposes a technique to instantiate processes for specific agent-oriented methodologies. This technique is based on three orthogonal views that are respectively related with lifecycles, disciplines and guidances. In addition, processes are modeled with a tool, which is automatically generated from a process metamodel inspired by the software & systems process engineering metamodel. Accordingly, engineers can choose the methodology–process pair best-suited for the characteristics of their project. The paper illustrates the approach based on the unified development process and the scrum process for the INGENIAS methodology and compares the results with other existing alternatives.     

Efficient coupling of multibody software with numerical computing environments and block diagram simulators

Simulation of complex mechatronic systems like an automobile, involving mechanical components as well as actuators and active electronic control devices, can be accomplished by combining tools that deal with the simulation of the different subsystems. In this sense, it is often desirable to couple a multibody simulation software (for the mechanical simulation) with external numerical computing environments and block diagram simulators (for the modeling and simulation of nonmechanical components).     

Hybrid learning for interval type-2 fuzzy logic systems based on orthogonal least-squares and back-propagation methods

This paper presents a novel learning methodology based on a hybrid algorithm for interval type-2 fuzzy logic systems. Since only the back-propagation method has been proposed in the literature for the tuning of both the antecedent and the consequent parameters of type-2 fuzzy logic systems, a hybrid learning algorithm has been developed. The hybrid method uses a recursive orthogonal least-squares method for tuning the consequent parameters and the back-propagation method for tuning the antecedent parameters. Systems were tested for three types of inputs: (a) interval singleton, (b) interval type-1 non-singleton, and (c) interval type-2 non-singleton. Experiments were carried out on the application of hybrid interval type-2 fuzzy logic systems for prediction of the scale breaker entry temperature in a real hot strip mill for three different types of coil. The results proved the feasibility of the systems developed here for scale breaker entry temperature prediction. Comparison with type-1 fuzzy logic systems shows that hybrid learning interval type-2 fuzzy logic systems provide improved performance under the conditions tested.