Application of Robust Model Predictive Control to a Renewable Hydrogen-based Microgrid

In order to cope with uncertainties present in the renewable energy generation, as well as in the demand consumer, we propose in this paper the formulation and comparison of three robust model predictive control techniques, i. i. e., multi-scenario, tree-based, and chance-constrained model predictive control, which are applied to a nonlinear plant-replacement model that corresponds to a real laboratory-scale plant located in the facilities of the University of Seville. Results show the effectiveness of these three techniques considering the stochastic nature, proper of these systems

The procurement and evaluation of a prototype laser satellite-tracking system Final report, 1 Jan. 1967 - 30 Sep. 1968

Pulsed ruby laser satellite tracking syste

Phase diagrams of Janus fluids with up-down constrained orientations

A class of binary mixtures of Janus fluids formed by colloidal spheres with the hydrophobic hemispheres constrained to point either up or down are studied by means of Gibbs ensemble Monte Carlo simulations and simple analytical approximations. These fluids can be experimentally realized by the application of an external static electrical field. The gas-liquid and demixing phase transitions in five specific models with different patch-patch affinities are analyzed. It is found that a gas-liquid transition is present in all the models, even if only one of the four possible patch-patch interactions is attractive. Moreover, provided the attraction between like particles is stronger than between unlike particles, the system demixes into two subsystems with different composition at sufficiently low temperatures and high densities.Comment: 10 pages, 6 figure

Virtual acoustic rendering by state wave synthesis

International audienceIn the context of the class of virtual acoustic simulation techniques that rely on traveling wave rendering as dictated by path-tracing methods (e.g, image-source, ray-tracing, beam-tracing) we introduce State Wave Synthesis (SWS), a novel framework for the efficient rendering of sound traveling waves as exchanged between multiple directional sound sources and multiple directional sound receivers in time-varying conditions.The proposed virtual acoustic rendering framework represents sound-emitting and sound-receiving objects as multiple-input, multiple-output dynamical systems. Each input or output corresponds to a sound traveling wave received or emitted by the object from/to different orientations or at/from different positions of the object. To allow for multiple arriving/departing waves from/to different orientations and/or positions of an object in dynamic conditions, we introduce a discrete-time state-space system formulation that allows the inputs or the outputs of a system to mutate dynamically. The SWS framework treats virtual source or receiver objects as time-varying dynamical systems in state-space modal form, each allowing for an unlimited number of sound traveling wave inputs and outputs.To model the sound emission and/or reception behavior of an object, data may be collected from measurements. These measurements, which may comprise real or virtual impulse or frequency responses from a real physical object or a numerical physical model of an object, are jointly processed to design a multiple-input, multiple-output state-space model with mutable inputs and/or outputs. This mutable state-space model enables the simulation of direction- and/or position-dependent, frequency-dependent sound wave emission or reception of the object. At run-time, each of the mutable state-space object models may present any number of inputs or outputs, with each input or output associated to a received/emitted sound traveling wave from/to specific arrival/departure position or orientation. In a first formulation, the sound wave form, the traveling of sound waves between object models is simulated by means of delay lines of time-varying length. In a second formulation, the state wave form, the traveling of sound waves between object models is simulated by way of propagating the state variables of source objects along delay lines of time-varying length. SWS allows the accurate simulation of frequency-dependent source directivity and receiver directivity in time-varying conditions without any time-domain or frequency-domain explicit convolution processing. In addition, the framework enables time-varying, obstacle-induced frequency-dependent attenuation of traveling waves without any dedicated digital filters. SWS facilitates the implementation of efficient virtual acoustic rendering engines either as software or in dedicated hardware, allowing realizations in which the number of delay lines is independent of the number of traveling wave paths being simulated. Moreover, the method enables a straightforward dynamic coupling between virtual acoustic objects and their physics-based simulation counterparts as performed by computer for animation, virtual reality, video-games, music synthesis, or other applications.In this presentation we will introduce the foundations of SWS and employ a real acoustic violin and a real human head as illustrative examples for a source object and a receiver object respectively. In light of available implementation possibilities, we will examine the basic memory requirements and computational cost of the rendering framework and suggest how to conveniently include minimum-phase diffusive elements to procure additional diffuse field contributions if necessary. Finally, we will expose limitations and discuss future opportunities for development

Photographic measurements of the energy distribution in the beam of a ruby laser

Photographic measurement of energy distribution in beam of Q-switched ruby lase

Measurements of satellite range with a ruby laser

Range measurements of GEOS-I and BE-C satellites with ruby lase

Use of a laser for satellite-range measurement

Optical laser satellite range measuring syste

Distribution of SARS-CoV-2 RNA Signal in a Home with COVID-19 Positive Occupants

Although many COVID-19 patients quarantine and recover at home, the dispersal of SARS-CoV-2 onto surfaces and dust within the home environment remains poorly understood. To investigate the distribution and persistence of SARS-CoV-2 in a quarantine home, samples were collected from a household with two confirmed COVID-19 cases (one adult and one child). Home surface swab and dust samples were collected two months after symptom onset (and one month after symptom resolution) in the household. The strength of the SARS-CoV-2 molecular signal in fomites varied as a function of sample location, surface material and cleaning practices. Notably, the SARS-CoV-2 RNA signal was detected at several locations throughout the household although cleaning appears to have attenuated the signal on many surfaces. Of the 24 surfaces sampled, 46% were SARS-CoV-2 positive at the time of sampling. The SARS-CoV-2 concentrations in dust recovered from floor and HVAC filter samples ranged from 104-105 N2 gene copies/g dust. While detection of viral RNA does not imply infectivity, this study confirms that the SARS-CoV-2 RNA signal can be detected at several locations within a COVID-19 quarantine home and can persist after symptoms have resolved. In addition, the concentration of SARS-CoV-2 (normalized per unit mass of dust) recovered in home HVAC filters may prove useful for estimating SARS-CoV-2 airborne levels in homes.This work was supported by Whole Communities-Whole Health, a research grand challenge at the University of Texas at Austin. In addition, the work that provided the basis for this publication was also supported by funding under an award TXHHU0046-18 with the U.S. Department of Housing and Urban Development.Office of the VP for Researc

Opioid pain medication prescription for chronic pain in primary care centers: the roles of pain acceptance, pain intensity, depressive symptoms, pain catastrophizing, sex, and age

Background: Psychological factors of patients may influence physicians’ decisions on prescribing opioid analgesics. However, few studies have sought to identify these factors. The present study had a double objective: (1) To identify the individual factors that differentiate patients who had been prescribed opioids for the management of chronic back pain from those who had not been prescribed opioids and (2) to determine which factors make significant and independent contributions to the prediction of opioid prescribing. Methods: A total of 675 patients from four primary care centers were included in the sample. Variables included sex, age, pain intensity, depressive symptoms, pain catastrophizing, and pain acceptance. Results: Although no differences were found between men and women, participants with chronic noncancer pain who were prescribed opioids were older, reported higher levels of pain intensity and depressive symptoms, and reported lower levels of pain-acceptance. An independent association was found between pain intensity and depressive symptoms and opioid prescribing. Conclusions: The findings suggest that patient factors influence physicians’ decisions on prescribing opioids. It may be useful for primary care physicians to be aware of the potential of these factors to bias their treatment decisions.info:eu-repo/semantics/publishedVersio