Numerical Model of a Variable-Combined-Cycle Engine for Dual Subsonic and Supersonic Cruise

Efficient high speed propulsion requires exploiting the cooling capability of the cryogenic fuel in the propulsion cycle. This paper presents the numerical model of a combined cycle engine while in air turbo-rocket configuration. Specific models of the various heat exchanger modules and the turbomachinery elements were developed to represent the physical behavior at off-design operation. The dynamic nature of the model allows the introduction of the engine control logic that limits the operation of certain subcomponents and extends the overall engine operational envelope. The specific impulse and uninstalled thrust are detailed while flying a determined trajectory between Mach 2.5 and 5 for varying throttling levels throughout the operational envelope.

Two-temperature model of the coronal irradiated pellets

A two electron-temperature, quasi-steady model of the corona of a laser-ablated pellet is considered. Ablation pressure, critical radius and mass flow rate are determined. Results are close to those obtained with heat flux saturation well below the free-streaming limit.

Variable structure control with chattering elimination and guaranteed stability for a generalized T-S model

In this paper, a fuzzy based Variable Structure Control (VSC) with guaranteed stability is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. The main contribution of this work is that, firstly, new functions for chattering reduction and error convergence without sacrificing invariant properties are proposed, which is considered the main drawback of the VSC control. Secondly, the global stability of the controlled system is guaranteed.The well known weighting parameters approach, is used in this paper to optimize local and global approximation and modeling capability of T-S fuzzy model.A one link robot is chosen as a nonlinear unstable system to evaluate the robustness, effectiveness and remarkable performance of optimization approach and the high accuracy obtained in approximating nonlinear systems in comparison with the original T-S model. Simulation results indicate the potential and generality of the algorithm. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved with the proposed FLC-VSC controller. The effectiveness of the proposed controller is proven in front of disturbances and noise effects.

Variable structure control with chattering reduction of a generalized T-S model

In this paper, a fuzzy logic controller (FLC) based variable structure control (VSC) is presented. The main objective is to obtain an improved performance of highly non-linear unstable systems. New functions for chattering reduction and error convergence without sacrificing invariant properties are proposed. The main feature of the proposed method is that the switching function is added as an additional fuzzy variable and will be introduced in the premise part of the fuzzy rules; together with the state variables. In this work, a tuning of the well known weighting parameters approach is proposed to optimize local and global approximation and modelling capability of the Takagi-Sugeno (T-S) fuzzy model to improve the choice of the performance index and minimize it. The main problem encountered is that the T-S identification method can not be applied when the membership functions are overlapped by pairs. This in turn restricts the application of the T-S method because this type of membership function has been widely used in control applications. The approach developed here can be considered as a generalized version of the T-S method. An inverted pendulum mounted on a cart is chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of the proposed estimation approach in comparison with the original T-S model. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the chattering reduction algorithm. In this paper, we prove that the proposed estimation algorithm converge the very fast, thereby making it very practical to use. The application of the proposed FLC-VSC shows that both alleviation of chattering and robust performance are achieved.

A Knowledge Model for Automatic Configuration of Traffic Messages

This paper describes a knowledge model for a configuration problem in the do-main of traffic control. The goal of this model is to help traffic engineers in the dynamic selection of a set of messages to be presented to drivers on variable message signals. This selection is done in a real-time context using data recorded by traffic detectors on motorways. The system follows an advanced knowledge-based solution that implements two abstract problem solving methods according to a model-based approach recently proposed in the knowledge engineering field. Finally, the paper presents a discussion about the advantages and drawbacks found for this problem as a consequence of the applied knowledge modeling ap-proach.

Bayesian model selection methodology for road safety

Road accidents are a very relevant issue in many countries and macroeconomic models are very frequently applied by academia and administrations to reduce their frequency and consequences. The selection of explanatory variables and response transformation parameter within the Bayesian framework for the selection of the set of explanatory variables a TIM and 3IM (two input and three input models) procedures are proposed. The procedure also uses the DIC and pseudo -R2 goodness of fit criteria. The model to which the methodology is applied is a dynamic regression model with Box-Cox transformation (BCT) for the explanatory variables and autorgressive (AR) structure for the response. The initial set of 22 explanatory variables are identified. The effects of these factors on the fatal accident frequency in Spain, during 2000-2012, are estimated. The dependent variable is constructed considering the stochastic trend component.

Railway Rapid Transit timetables with variable and elastic demand.

This paper focuses on the design of railway timetables considering a variable elastic demand profile along a whole design day. Timetabling is the third stage in the classical hierarchical railway planning process. Most of previous works on this topic consider a uniform demand behavior for short planning intervals. In this paper, we propose a MINLP model for designing non-periodic timetables on a railway corridor where demand is dependent on waiting times. In the elastic demand case, long waiting times lead to a loss of passengers, who may select an alternative transportation mode. The mode choice is modeled using two alternative methods. The first one is based on a sigmoid function and can be used in case of absence of information for competitor modes. In the second one, the mode choice probability is obtained using a Logit model that explicitly considers the existence of a main alternative mode. With the purpose of obtaining optimal departure times, in both cases, a minimization of the loss of passengers is used as objective function. Finally, as illustration, the timetabling MINLP model with both mode choice methods is applied to a real case and computational results are shown.

Comparison of the seismic behaviour between three building tests, all based on a two storey model house

Integral Masonry System consisting of intersecting steel trusses alo ng each of the three dimensional directions of space on walls and slabs using any masonry material, had yet been backed up by the previous adobe test for seismic areas. This paper presents the comparison this last test and the adaptation of the IMS using h ollow brick. A prototype based on a two storey model house (6mx6mx6m) has being also built in two different scales in order to maximize the load and size of the shake table: the first one half size the whole building (3mx3mx3m) and the second, a quarter of the real size (3mx3mx6m). Both tests have suffered some mild to moderate damages while supporting the higher seismic action subjected by the shake table, without even fissuring the first test and with very few damages the second one. The thickness of the hollow brick wall and the diameter of the tree - dimensional truss reinforcement were scaled to the real size test in order to ascertain its great structural behaviour in relation to the previous structural model calculations. The aim of this study is to sum marize the results of the research collaboration between the ETSAM - UPM and the PUCP in whose laboratory these tests were carried out.

A neuronal model of a global workspace in effortful cognitive tasks

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

A general two-process model describes the hydrogen exchange behavior of RNase A in unfolding conditions.

When NMR hydrogen exchange was used previously to monitor the kinetics of RNase A unfolding, some peptide NH protons were found to show EX2 exchange (detected by base catalysis) in addition to the expected EX1 exchange, whose rate is limited by the kinetic unfolding process. In earlier work, two groups showed independently that a restricted two-process model successfully fits published hydrogen exchange rates of native RNase A in the range 0-0.7 M guanidinium chloride. We find that this model predicts properties that are very different from the observed properties of the EX2 exchange reactions of RNase A in conditions where guanidine-induced unfolding takes place. The model predicts that EX2 exchange should be too fast to measure by the technique used, whereas it is readily measurable. Possible explanations for the contradiction are considered here, and we show that removing the restriction from the earlier two-process model is sufficient to resolve the contradiction; instead of specifying that exchange caused by global unfolding occurs by the EX2 mechanism, we allow it to occur by the general mechanism, which includes both the EX1 and EX2 cases. It is logical to remove this restriction because global unfolding of RNase A is known to give rise to EX1 exchange in these unfolding conditions. Resolving the contradiction makes it possible to determine whether populated unfolding intermediates contribute to the EX2 exchange, and this question is considered elsewhere. The results and simulations indicate that moderate or high denaturant concentrations readily give rise to EX1 exchange in native proteins. Earlier studies showed that hydrogen exchange in native proteins typically occurs by the EX2 mechanism but that high temperatures or pH values above 7 may give rise to EX1 exchange. High denaturant concentrations should be added to the list of variables likely to cause EX1 exchange.

Two-hybrid system as a model to study the interaction of beta-amyloid peptide monomers.

The kinetics of amyloid fibril formation by beta-amyloid peptide (Abeta) are typical of a nucleation-dependent polymerization mechanism. This type of mechanism suggests that the study of the interaction of Abeta with itself can provide some valuable insights into Alzheimer disease amyloidosis. Interaction of Abeta with itself was explored with the yeast two-hybrid system. Fusion proteins were created by linking the Abeta fragment to a LexA DNA-binding domain (bait) and also to a B42 transactivation domain (prey). Protein-protein interactions were measured by expression of these fusion proteins in Saccharomyces cerevisiae harboring lacZ (beta-galactosidase) and LEU2 (leucine utilization) genes under the control of LexA-dependent operators. This approach suggests that the Abeta molecule is capable of interacting with itself in vivo in the yeast cell nucleus. LexA protein fused to the Drosophila protein bicoid (LexA-bicoid) failed to interact with the B42 fragment fused to Abeta, indicating that the observed Abeta-Abeta interaction was specific. Specificity was further shown by the finding that no significant interaction was observed in yeast expressing LexA-Abeta bait when the B42 transactivation domain was fused to an Abeta fragment with Phe-Phe at residues 19 and 20 replaced by Thr-Thr (AbetaTT), a finding that is consistent with in vitro observations made by others. Moreover, when a peptide fragment bearing this substitution was mixed with native Abeta-(1-40), it inhibited formation of fibrils in vitro as examined by electron microscopy. The findings presented in this paper suggest that the two-hybrid system can be used to study the interaction of Abeta monomers and to define the peptide sequences that may be important in nucleation-dependent aggregation.

Tertiary structure of an amyloid immunoglobulin light chain protein: a proposed model for amyloid fibril formation.

An immunoglobulin light chain protein was isolated from the urine of an individual (BRE) with systemic amyloidosis. Complete amino acid sequence of the variable region of the light chain (VL) protein established it as a kappa I, which when compared with other kappa I amyloid associated proteins had unique residues, including Ile-34, Leu-40, and Tyr-71. To study the tertiary structure, BRE VL was expressed in Escherichia coli by using a PCR product amplified from the patient BRE's bone marrow DNA. The PCR product was ligated into pCZ11, a thermal-inducible replication vector. Recombinant BRE VL was isolated, purified to homogeneity, and crystallized by using ammonium sulfate as the precipitant. Two crystal forms were obtained. In crystal form I the BRE VL kappa domain crystallizes as a dimer with unit cell constants isomorphous to previously published kappa protein structures. Comparison with a nonamyloid VL kappa domain from patient REI, identified significant differences in position of residues in the hypervariable segments plus variations in framework region (FR) segments 40-46 (FR2) and 66-67 (FR3). In addition, positional differences can be seen along the two types of local diads, corresponding to the monomer-monomer and dimer-dimer interfaces. From the packing diagram, a model for the amyloid light chain (AL) fibril is proposed based on a pseudohexagonal spiral structure with a rise of approximately the width of two dimers per 360 degree turn. This spiral structure could be consistent with the dimensions of amyloid fibrils as determined by electron microscopy.

Microevolutionary responses in experimental populations of plants to CO2-enriched environments: parallel results from two model systems.

Despite the critical role that terrestrial vegetation plays in the Earth's carbon cycle, very little is known about the potential evolutionary responses of plants to anthropogenically induced increases in concentrations of atmospheric CO2. We present experimental evidence that rising CO2 concentration may have a direct impact on the genetic composition and diversity of plant populations but is unlikely to result in selection favoring genotypes that exhibit increased productivity in a CO2-enriched atmosphere. Experimental populations of an annual plant (Abutilon theophrasti, velvetleaf) and a temperate forest tree (Betula alleghaniensis, yellow birch) displayed responses to increased CO2 that were both strongly density-dependent and genotype-specific. In competitive stands, a higher concentration of CO2 resulted in pronounced shifts in genetic composition, even though overall CO2-induced productivity enhancements were small. For the annual species, quantitative estimates of response to selection under competition were 3 times higher at the elevated CO2 level. However, genotypes that displayed the highest growth responses to CO2 when grown in the absence of competition did not have the highest fitness in competitive stands. We suggest that increased CO2 intensified interplant competition and that selection favored genotypes with a greater ability to compete for resources other than CO2. Thus, while increased CO2 may enhance rates of selection in populations of competing plants, it is unlikely to result in the evolution of increased CO2 responsiveness or to operate as an important feedback in the global carbon cycle. However, the increased intensity of selection and drift driven by rising CO2 levels may have an impact on the genetic diversity in plant populations.

Two helices plus a linker: a small model substrate for eukaryotic RNase P.

Using precursor tRNA molecules to study RNA-protein interactions, we have identified an RNA motif recognized by eukaryotic RNase P (EC 3.1.26.5). Analysis of circularly permuted precursors indicates that interruptions in the sugar-phosphate backbone are not tolerated in the acceptor stem, in the T stem-loop, or between residues A-9 and G-10. Prokaryotic RNase P will function with a minihelix consisting of the acceptor stem connected directly to the T stem-loop. Eukaryotic RNase P cannot use such a minimal substrate unless a linker sequence is added in the gap where the D stem and anticodon stem-loop were deleted.

A structural model of cognitive-motivational variables as explanatory factors of academic achievement in Spanish Language and Mathematics

In recent years, several explanatory models have been developed which attempt to analyse the predictive worth of various factors in relation to academic achievement, as well as the direct and indirect effects that they produce. The aim of this study was to examine a structural model incorporating various cognitive and motivational variables which influence student achievement in the two basic core skills in the Spanish curriculum: Spanish Language and Mathematics. These variables included differential aptitudes, specific self-concept, goal orientations, effort and learning strategies. The sample comprised 341 Spanish students in their first year of Compulsory Secondary Education. Various tests and questionnaires were used to assess each student, and Structural Equation Modelling (SEM) was employed to study the relationships in the initial model. The proposed model obtained a satisfactory fit for the two subjects studied, and all the relationships hypothesised were significant. The variable with the most explanatory power regarding academic achievement was mathematical and verbal aptitude. Also notable was the direct influence of specific self-concept on achievement, goal-orientation and effort, as was the mediatory effect that effort and learning strategies had between academic goals and final achievement.