Blog

REDRUM 251 – New EP on Spotify

A short collection of soundtracks for Fabrizio Borgio’s crime stories, settled among Piedmont’s wine hills and featuring Detective Giorgio Martinengo. Inspired by psychological horror and by the movie The Shining (1980).

https://open.spotify.com/embed/album/5Xj7F4ULGVnfG2uCxsNHbW?utm_source=generator

You can also listen to the EP on Soundcloud:

I am featured also on Apple Music: https://music.apple.com/us/artist/quantum-prana/1400222239

Video – Covering Bauhaus well masked

From last Friday’s gig, here I am playing our own cover of Bauhaus’ Stigmata Martyr…wearing The Old Man’s mask. This is only the intro, full video link in the description. #bauhaus #postpunk #avantgarde #experimental #mask

Gear and tone matter – Know Your Gear! (cit.)

What a nice gig yesterday! Investing time, thought and money in quality equipment and effects layering (besides lots of practice!) does make a difference, performance- as well as tone-wise.

#Fender #Markbass #Two notes Audio Engineering #Walrus Audio #Darkglass Electronics #Phillip McKnight

Attached, a close-up of the accidental star of the evening.

Special Issue on HVAC and Sustainability

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Submissions are welcome for the new Special Issue at Energies MDPI where I am guest editor.

Topics: #energyefficiency #HVAC# Sustainability #IEQ #thermalcomfort and many others.

Deadline: April, 27th 2022. https://www.mdpi.com/…/Building_Sustainable_District

Demogorgon, a new song.

“Ήτοι μεν πρώτιστα χάος γένετο.” (“Verily at the first Chaos came to be.”)
Hesiod (ca.750 BC), Theogonia, 116.

The opening tune of my dark progressive album “Quantum Arkanum”, featuring stoner, sludge and psychedelic elements, with some classical flavour.

Quantum Prana: guitars, bass, voices, drum programming, mixing & mastering.

Cover illustration by Gustave Doré (1832-1883).

New paper on energy data mining now published

Office Building Tenants’ Electricity Use Model for Building Performance Simulations
https://www.mdpi.com/1996-1073/13/21/5541

Abstract

Large office buildings are responsible for a substantial portion of energy consumption in urban districts. However, thorough assessments regarding the Nordic countries are still lacking. In this paper we analyse the largest dataset to date for a Nordic office building, by considering a case study located in Stockholm, Sweden, that is occupied by nearly a thousand employees. Distinguishing the lighting and occupants’ appliances energy use from heating and cooling, we can estimate the impact of occupancy without any schedule data. A standard frequentist analysis is compared with Bayesian inference, and the according regression formulas are listed in tables that are easy to implement into building performance simulations (BPS). Monthly as well as seasonal correlations are addressed, showing the critical importance of occupancy. A simple method, grounded on the power drain measurements aimed at generating boundary conditions for the BPS, is also introduced; it shows how, for this type of data and number of occupants, no more complexities are needed in order to obtain reliable predictions. For an average year, we overestimate the measured cumulative consumption by only 4.7%. The model can be easily generalised to a variety of datasets.
Keywords: building simulationoffice buildingsenergy performanceenergy modellingHVACanalytical modellingstatistical analysis