Evaluation of quadratic cost functionals for neutral systems: the frequency-domain approach

As shown in Grabowski (1983), the problem of evaluation of the quadratic performance index for delay-differential systems of neutral type can be effectively solved by the use of Lyapunov functionals. In this paper another solution to that problem, based on the frequency-domain approach, is proposed. With the use of Plancherel's theorem and other tools of complex analysis, this task is reduced to a Riemann-Hilbert problem, an explicit solution to which is found by elementary methods. Our results can be regarded as a generalization of those due to Walton and Marshall (1984, 1987). Two simple examples of application are also provided.     

A two-pronged approach for springback variability assessment using sparse polynomial chaos expansion and multi-level simulations

In this study, we show that stochastic analysis of metal forming process requires both a high precision and low cost numerical models in order to take into account very small perturbations on inputs (physical as well as process parameters) and to allow for numerous repeated analysis in a reasonable time. To this end, an original semi-analytical model dedicated to plain strain deep drawing based on a Bending-Under-Tension numerical model (B-U-T model) is used to accurately predict the influence of small random perturbations around a nominal solution estimated with a full scale Finite Element Model (FEM). We introduce a custom sparse variant of the Polynomial Chaos Expansion (PCE) to model the propagation of uncertainties through this model at low computational cost. Next, we apply this methodology to the deep drawing process of U-shaped metal sheet considering up to 8 random variables.     

Decision trees for uplift modeling with single and multiple treatments

Most classification approaches aim at achieving high prediction accuracy on a given dataset. However, in most practical cases, some action such as mailing an offer or treating a patient is to be taken on the classified objects, and we should model not the class probabilities themselves, but instead, the change in class probabilities caused by the action. The action should then be performed on those objects for which it will be most profitable. This problem is known as uplift modeling, differential response analysis, or true lift modeling, but has received very little attention in machine learning literature. An important modification of the problem involves several possible actions, when for each object, the model must also decide which action should be used in order to maximize profit. In this paper, we present tree-based classifiers designed for uplift modeling in both single and multiple treatment cases. To this end, we design new splitting criteria and pruning methods. The experiments confirm the usefulness of the proposed approaches and show significant improvement over previous uplift modeling techniques.     

Development of gluten-free fresh egg pasta based on oat and teff flour

Due to increased awareness of consumers about the relationship between food and health as well as the requirements of people following a gluten-free diet, the production of cereal products from raw materials other than wheat is of interest. However, the elimination of the visco-elastic gluten protein represents a technological challenge. During this study, response surface methodology was applied to determine optimal formulations for the production of egg pasta from oat and teff flour. Wheat flour was used as a control. The resulting products were characterised regarding firmness and elasticity, stickiness and cooking loss. The results showed that the mechanical texture of oat and teff pasta was comparable to wheat pasta, however, elasticity was significantly reduced. Compositional analysis was carried out on flour raw materials as well as on the final pasta products, showing that regarding fibre and mineral content, oat and teff samples are nutritionally superior to wheat. In addition, the microstructure was investigated by means of scanning electron microscopy, allowing also the observation of structural changes occurring during cooking. Upon cooking, a distinct outer layer can be observed, resulting from protein denaturation and starch gelatinisation. This structural feature is clearly visible for cooked wheat pasta and but is less apparent for teff and oat pasta.     

Optimization of reinforcement layout of scissor‐type bridge using differential evolution algorithm

Scissors mechanisms are commonly used in safety engineering during the construction of temporary structures, owing to their inherent advantages of foldability, transformability, and reusability. We effectively utilized these scissors mechanism features to develop a lightweight, deployable emergency Mobile Bridge (MB) based on optimization, and control of the folding structure. Here, we discuss the problems of optimal reinforcement layout for the MB by formulating and solving three optimization problems, namely: (a) the load capacity maximization problem, (b) the weight minimization problem, and (c) coupling the load capacity maximization problem and the weight minimization problem. The potential benefits resulting from the application of reinforcement were evaluated using a combination of finite element analysis and an optimization algorithm based on the differential evolution method. The results demonstrate the significant positive influence of the additional reinforcing members. In particular, the limit load was increased by over 10 times, while the weight was decreased to approximately half. The proposed methodology enabled the development of a substantially improved version of the MB characterized by a higher load capacity and lower weight in comparison to the initial bridge design.     

Power system stability enhancement by WAMS-based supplementary control of multi-terminal HVDC networks

This paper deals with supplementary control of a MTDC network designed for the stability enhancement of a AC power system. The proposed control is a WAMS-based control modulating the real and reactive power at the terminals of the DC network. Relevant control formulas have been derived for a linear multi-machine system model with the application of the direct Lyapunov method. Validity and robustness of the proposed control has been verified by computer simulation for a multi-machine test system using a nonlinear model and detailed modeling of power system components. The proposed control is robust and insensitive to changes in the network configuration and loading conditions in the AC power system. In the case, when more of the MTDC networks and/or the HVDC links are used in one interconnected power system the proposed stabilizing control produces additive damping i.e. each controlled network element contributes to the positive damping. Some practical aspects have also been discussed. The proposed WAMS-based stabilizing control of the MTDC network is innovative by both its main concept and the derivation of control formulas using the direct Lyapunov method.     

Long-term monitoring of natural hydrogen superficial emissions in a brazilian cratonic environment. Sporadic large pulses versus daily periodic emissions

In many basins, hydrogen-emitting structures are now observed, but the estimation of the H₂ flow leading to their formation remains poorly constrained since all data show that the H₂ emissions are variable in space and time. We present here the data of a long-term monitoring campaign with a high density of permanent hydrogen detectors installed in 2 structures in the Minas Gerais State (Brazil). Results show that two kinds of signals are recorded, large sporadic pulses that affect the H₂ content of the soil for one or two days and smaller ones, with a daily periodicity, that last 6 h and during which the near surface soil concentration usually does not exceed 200 ppm. This last signal is very regular in frequency, less in amount, and the daily maximum happens around noon or in the early afternoon. We interpret the large pulses as evidences of a deep hydrogen flux, leaking either from a reservoir located in the subsurface, from an aquifer which is degassing or, although it seems unlikely, directly from the H₂ generation area.The time correlation between the pulse and the increase of the daily signal suggests that this last one corresponds to the slow release of the gas that has been captured by the soil during its transport towards the surface. This daily signal is most likely influenced by external factors such as atmospheric pressure and sub-surface bacterial activity. In map view, the lack of correlation between the highest hydrogen concentrations over time suggests that the soil is very heterogeneous and that preferential pathways exist. The results confirm that long-term monitoring, over a few months, is mandatory to catch a certain number of high pulses and so to have a better estimation of the real flow. Data also suggests that sensors with a large concentration range should be used (from 10 to several 10⁴ ppm). Even if quantification of leakage doesn't help to quantify the subsurface reserves, these new data allow a more precise evaluation of the quantity of H₂ released in surface by these structures, few hundred of kilo per day, and confirm the high H₂ prospectivity of this basin.