Model and distribution uncertainty in multivariate GARCH estimation: a Monte Carlo analysis

Multivariate GARCH models are in principle able to accommodate the features of the dynamic conditional correlations processes, although with the drawback, when the number of financial returns series considered increases, that the parameterizations entail too many parameters.In general, the interaction between model parametrization of the second conditional moment and the conditional density of asset returns adopted in the estimation determines the fitting of such models to the observed dynamics of the data. This paper aims to evaluate the interactions between conditional second moment specifications and probability distributions adopted in the likelihood computation, in forecasting volatilities and covolatilities. We measure the relative performances of alternative conditional second moment and probability distributions specifications by means of Monte Carlo simulations, using both statistical and financial forecasting loss functions.Multivariate GARCH models; Model uncertainty; Quasi-maximum likelihood; Monte Carlo methods

Uncertainty in discrete-time integration — The case of static gas meters

We consider the evaluation of uncertainty in a particular case of discrete-time integration, i.e., that of static gas meters. We show that the current approach, which does not take correlations into account, can lead to underrating of the uncertainty associated with the estimate of the delivered volume. Now, a correct evaluation of uncertainty in the case e.g. of online measurements along large offshore pipelines is important in order to remove technical barriers to international trade. We focus our discussion on the practical example of gas meters, but the framework of uncertainty evaluation we provide is valid in general for all those measurements involving discrete-time integration, and has therefore a wide applicability

Performance Analysis of a Microthruster for Satellite Applications

Scientific space missions require a very high accuracy of positioning and orientation of the satellites in order to meet their objectives. Such accuracy can be obtained through a set of positioning thrusters, which need to be able to generate very low forces with high precision. This result can be obtained using cold gas thrusters. A method for the design and the forecast of the expected performance of such thrusters will be presented

intracorporeal heat Distribution from Fully implantable energy sources for Mechanical circulatory support: a computational Proof-of-concept study

Mechanical circulatory support devices, such as total artificial hearts and left ventricular assist devices, rely on external energy sources for their continuous operation. Clinically approved power supplies rely on percutaneous cables connecting an external energy source to the implanted device with the associated risk of infections. One alternative, investigated in the 70s and 80s, employs a fully implanted nuclear power source. The heat generated by the nuclear decay can be converted into electricity to power circulatory support devices. Due to the low conversion efficiencies, substantial levels of waste heat are generated and must be dissipated to avoid tissue damage, heat stroke, and death. The present work computationally evaluates the ability of the blood flow in the descending aorta to remove the locally generated waste heat for subsequent full-body distribution and dissipation, with the specific aim of investigating methods for containment of local peak temperatures within physiologically acceptable limits. To this aim, coupled fluid-solid heat transfer computational models of the blood flow in the human aorta and different heat exchanger architectures are developed. Particle tracking is used to evaluate temperature histories of cells passing through the heat exchanger region. The use of the blood flow in the descending aorta as a heat sink proves to be a viable approach for the removal of waste heat loads. With the basic heat exchanger design, blood thermal boundary layer temperatures exceed 50°C, possibly damaging blood cells and proteins. Improved designs of the heat exchanger, with the addition of fins and heat guides, allow for drastically lower blood temperatures, possibly leading to a more biocompatible implant. The ability to maintain blood temperatures at biologically compatible levels will ultimately allow for the body-wise distribution, and subsequent dissipation, of heat loads with minimum effects on the human physiology

Analysis of Flow Meters Calibration

Calibration data of flow meters are often reported using the so called calibration coefficient, i.e. the ratio between the reference flow rate (or equivalent quantity, e.g. airspeed, accumulated volume etc.) and the corresponding quantity as indicated by the instrument to be calibrated. The main reasons for this choice are twofold: - First of all, this approach is very practical for the end user of the instrument, who can get the corrected flow rate by simple multiplication of the readout times the coefficient; - Second, this representation allows to highlight the non-linearities of the instrument, which usually show up in the lower end of the range and might be hidden by a direct representation. On the other hand, this approach makes the uncertainty evaluation of the resulting data more complex, because of the correlation between the regression data. In this paper, we will perform an analysis according to such traditional approach and also according to an alternate “direct” approach, i.e., considering the reference flow rate as the dependent variable, instead of the calibration coefficient. In both cases the regression will be performed by a specific software for calibration curves (CCC software, developed at INRIM in the framework of the EMRP NEW04 Project). Fig. 1 shows, as a case example, the scatter plot and the relevant regression curve for the two data representations. A procedural approach for correctly performing regression and uncertainty evaluation will be derived for both methods, and the results obtained will be compared. Specific attention will be devoted to the non-linear response region of the instrument range, since this part of the range is the more delicate and often the one where the instrument is used for a significant fraction of its operational life

The influence of spatial distribution and work organization on the effectiveness of teamwork in an innovative multidisciplinary project

The aim of this paper is to investigate and define the type of teamwork that best fits along various phases of innovation projects based on design thinking process.Within the context of Innovation 4 Change program, the typical phases of a design thinking project havebeen analysedby means of a macro methodology matrix based on twocore variables: spatial distribution and internal organization of team members. Every single team member was asked, based on his experience, what is the most effective combination for teamwork

Model and distribution uncertainty in multivariate GARCH estimation: a Monte Carlo analysis

Multivariate GARCH models are in principle able to accommodate the features of the dynamic conditional correlations processes, although with the drawback, when the number of financial returns series considered increases, that the parameterizations entail too many parameters.In general, the interaction between model parametrization of the second conditional moment and the conditional density of asset returns adopted in the estimation determines the fitting of such models to the observed dynamics of the data. This paper aims to evaluate the interactions between conditional second moment specifications and probability distributions adopted in the likelihood computation, in forecasting volatilities and covolatilities. We measure the relative performances of alternative conditional second moment and probability distributions specifications by means of Monte Carlo simulations, using both statistical and financial forecasting loss functions

Flow leaks normalization

Flow leaks are small devices generating a well-determined flow when subject to a pressure differential (feed pressure). Though, they need to be calibrated against a reference flow based on the feed pressure and fluid density through a complex relation derived from the modified Darcy law, therefore results of a calibration performed in a given condition are not necessarily valid when the leak is used in different conditions. In this paper we will describe a correct renormalization of the calibration results allowing to compute precisely the actual flow rate generated by the leak. A mathematical description of the renormalization will be presented and a method for the experimental determination of the permeability will be discussed. It will be shown that the calibration uncertainty can be reduced by applying the correct normalization, and that the in-use uncertainty can be brought to be of the same order of magnitude as the calibration uncertainty

A non-linear observer for unsteady three-dimensional flows

A method is proposed to estimate the velocity field of an unsteady flow using a limited number of flow measurements. The method is based on a non-linear low-dimensional model of the flow and on expanding the velocity field in terms of empirical basis functions. The main idea is to impose that the coefficients of the modal expansion of the velocity field give the best approximation to the available measurements and that at the same time they satisfy as close as possible the non-linear low-order model. The practical use may range from feedback flow control to monitoring of the flow in non-accessible regions. The proposed technique is applied to the flow around a confined square cylinder, both in two- and three-dimensional laminar flow regimes. Comparisons are provided. with existing linear and non-linear estimation techniques

Generation of CO2 gas mixtures by dynamic dilution for the development of gaseous certified reference materials

The use of Certified Reference Materials (CRMs) is of utmost importance to achieve the comparability and traceability of data, which are essential features of measurement results in environmental and climate fields. The present paper focuses on the generation of gas mixtures at known composition of carbon dioxide at atmospheric amount-of-substance fraction in synthetic air by means of a dynamic dilution system, designed and implemented at the Istituto Nazionale di Ricerca Metrologica (INRiM). The validation of the dynamic system in terms of amount-of-substance fraction is presented. The system was also used to verify the carbon dioxide amount-ofsubstance fraction of a suite of gas mixtures gravimetrically prepared at INRiM in the framework of the EMPIR Joint Research Project 19ENV05 – STELLAR. Dynamic dilution proved to be an effective tool for the preparation and certification of CRMs for gaseous pollutants (i.e. carbon dioxide, nitrogen oxides) relevant for monitoring environmental pollution and climate changes