scholarly journals Occupant comfort in Nearly Zero Energy Buildings (nZEB) by using the building structure for demand side management (DMS)

2020 ◽  
Vol 172 ◽  
pp. 06011
Author(s):  
Ferdinand Sigg ◽  
Harald Krause

This research project aims to increase the application range of Thermally Activated Building Systems (TABS). Usually TABS are used for heating and cooling purpose of buildings. The application range of the usage as energy storage element is limited by the surface temperature of the element to avoid overheating. Via a thermal decoupling of the thermal activated part with insulation from the building structure, it is possible to use TABS as an thermal energy storage. The results show a significant opportunity to time-shift the purchase of energy. The results show that it is possible to use TABS as a thermal energy storage element. It’s shown that the purchase of electrician energy for heating purpose can be shifted to economical or ecological optimal time points, for example if renewable energy is abundant in the electrical grid. The heating demand, covered by thermally charged TABS elements can be supplied by a fraction of 95%. Common TABS with a limited surface temperature can reach a coverage rate of 64 %. Nevertheless, the mean air temperature increases for this task by 1.1 K and the heat demand by 15.0 %.

2019 ◽  
Vol 665 ◽  
pp. 1-10 ◽  
Author(s):  
M. Pellegrini ◽  
M. Bloemendal ◽  
N. Hoekstra ◽  
G. Spaak ◽  
A. Andreu Gallego ◽  
...  

Author(s):  
Shuoyu Wang ◽  
Ahmed Abdulridha ◽  
Spencer Quiel ◽  
Clay Naito ◽  
Muhannad Sulieman ◽  
...  

Abstract This paper presents a lab-scale investigation of the use of structural concrete for sensible heat storage in power plants. Transient thermal and mechanical analyses are simulated via coupled finite element models to study the thermo-mechanical performance of a cylindrical concrete block with 4-in diameter and 8-in length under thermal loading. The model is validated by performing experiments on high strength concrete (HSC) cylinders with this geometry in an oven, which heats the specimens from the outside. The models are then modified to simulate thermal energy storage (TES) application with thermal loading applied at the interior surface of a hole running through the longitudinal center of the cylinder. Thermal cycles have a varying heating rate (5, 10, or 24 hours) followed by consistent durations of soaking (2 hours) and cooling (13 hours). In the TES simulations, a steel jacket is also applied to the external surface of the concrete cylinder to provide confinement. The resulting thermal distribution and maximum principal stresses during heating and cooling are observed as a function of time. This study provides insight into the mechanical requirements and impact on material integrity for concrete modules subjected to representative TES heating regimes.


2019 ◽  
Vol 250 ◽  
pp. 593-604 ◽  
Author(s):  
Matthew Fong ◽  
Mahmoud A. Alzoubi ◽  
Jundika C. Kurnia ◽  
Agus P. Sasmito

Author(s):  
Aditya Jayakumar Chuttar ◽  
Debjyoti Banerjee

Miniaturization of electronics devices is often limited by the concomitant high heat fluxes (cooling load) and maldistribution of temperature profiles (hot spots). Thermal energy storage (TES) platforms providing supplemental cooling can be a cost-effective solution, that often leverages phase change materials (PCM). Although salt hydrates provide higher storage capacities and power ratings (as compared to that of the organic PCMs), they suffer from reliability issues (e.g., supercooling). ‘Cold Finger Technique (CFT)’ can obviate supercooling by maintaining a small mass fraction of the PCM in solid state for enabling spontaneous nucleation. Optimization of CFT necessitates real-time forecasting of the transient values of the melt-fraction. In this study artificial neural network (ANN) is explored for real-time prediction of the time remaining to reach a target value of melt-fraction based on the prior history of the spatial distribution of the surface temperature transients. Two different approaches were explored for training the ANN model, using: (1) transient PCM-temperature data; or (2) transient surface-temperature data. When deployed in a heat sink that leverages PCM based passive thermal management systems for cooling of electronic chips and packages, this maverick approach (using the second method) affords cheaper costs, better sustainability, higher reliability and resilience.


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