Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Design of healthy, comfortable, and energy-efficient buildings

The HOPE European research project aimed to look at a possible relationship between the energy performance of a building and the well-being (health and comfort) of their occupants. An interdisciplinary survey resulted in guidelines to increase the number of energy-efficient buildings that are at the same time healthy and comfortable. These guidelines are presented, together with experimental evidence for their reliability. © Springer Science+Business Media, LLC 2012

Methodology for the Evaluation of Thermal Comfort in Office Buildings

The comfort standards define a methodology for the evaluation of thermal comfort for design purposes. Compared to this, a standardized evaluation of measurement campaigns should apply some constraints: The applied comfort approach need to be adapted for the cooling concept. Monitored room temperatures are evaluated on an hourly basis for both the upper and lower limits during occupancy only. The evaluation is carried out for 84 % of the building area. The deviation from the comfort temperature and its tolerance band is limited to 5 % and is determined for the entire summer period. A summer day is a day with a mean running temperature higher than 15 °C. Results should be illustrated in a comfort figure and as a thermal-comfort footprint

Standards on Thermal Comfort

International standards give criteria for thermal comfort based on the evaluation of room temperatures and their deviation from the comfort temperature. The static approach to thermal comfort is derived from the physics of heat transfer and combined with an empirical fit to sensation. It defines constant comfort temperatures for the summer and winter period considering different clothing. The adaptive comfort model considers the thermal sensation of the occupants and different actions in order to adapt to the thermal environment as well as variable expectations with respect to outdoor and indoor climate. The comfort temperature is dependent on the outdoor temperature. Though standards clearly define the static approach as general criterion and the adaptive approach as optional approach for naturally ventilated buildings only, the application in buildings with lowenergy cooling and strong users’ impact on the indoor environment is critically reviewed

Heat recovery unit failure detection in air handling unit

| openaire: EC/H2020/688203/EU//BIoTopeMaintenance is a complicated task that encompasses various activities including fault detection, fault diagnosis, and fault reparation. The advancement of Computer Aided Engineering (CAE) has increased challenges in maintenance as modern assets have became complex mixes of systems and sub systems with complex interaction. Among maintenance activities, fault diagnosis is particularly cumbersome as the reason of failures on the system is often neither obvious in terms of their source nor unique. Early detection and diagnosis of such faults is turning to one of the key requirements for economical and functional asset efficiency. Several methods have been investigated to detect machine faults for a number of years that are relevant for many application domains. In this paper, we present the process history-based method adopting nominal efficiency of Air Handling Unit (AHU) to detect heat recovery failure using Principle Component Analysis (PCA) in combination of the logistic regression method.Peer reviewe