Sökning: "energy signature."
Visar resultat 1 - 5 av 45 uppsatser innehållade orden energy signature..
1. Analysis of Atmospheric Muon Bundles with IceCube
Master-uppsats, Uppsala universitet/HögenergifysikSammanfattning : This work is a preliminary study of the background of a search for dark, long-lived particles in the IceCube detector. The high flux of atmospheric muons in IceCube is considered background to the detector's primary science goal, which is to detect astrophysical neutrinos through the emission of Cherenkov radiation. LÄS MER
2. On The Evaluation of District Heating Load Predictions
Master-uppsats, Lunds universitet/Institutionen för energivetenskaperSammanfattning : District Heating is a technology with the potential to enable a fossil-free society. However, to realize this potential, some improvements need to be made in order to improve District Heating operation at large, decrease losses in the systems, and thus increase the competitiveness of District Heating as a technology. LÄS MER
3. Energy simulations of apartment buildings using IDA ICE
Master-uppsats, KTH/Hållbara byggnaderSammanfattning : This study presents an energy signature method for analyzing thermal inertia of apartment building located in Stockholm using IDA ICE software. The method involves analyzing the building’s consumption of energy hourly and calculating the temperature change rate of the building’s thermal mass. LÄS MER
4. Pulse Amplitude Reconstruction in the LDMX Hadronic Calorimeter Readout
Kandidat-uppsats, Lunds universitet/Fysiska institutionen; Lunds universitet/Partikel- och kärnfysikSammanfattning : The universe shows signs of containing some invisible matter, known as dark matter. There are many possible constituents for dark matter, one such being light dark matter which would interact with ordinary matter through a new mediator force and have masses in the range of a few MeV to GeV. LÄS MER
5. Dark Matter signals at the Large Hadron Collider with Deep Learning
Kandidat-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : While holding a firm position in popular culture and science fiction, Dark Matter (DM) is nonetheless a highly relevant topic at the forefront of modern particle physics. We study the applicability of characterizing DM particle candidates SUSY neutralino and sneutrino using Deep Learning (DL) methods. LÄS MER