Publicacións

@article{martinez-garcia_assessment_2021,

title = {Assessment of mussel shells building solutions: A real-scale application},

author = {Carolina Martínez-García and Belén González-Fonteboa and Diego Carro-López and Juan Luis Pérez-Ordóñez},

url = {https://www.sciencedirect.com/science/article/pii/S2352710221004939},

doi = {10.1016/j.jobe.2021.102635},

issn = {2352-7102},

year  = {2021},

date = {2021-12-01},

urldate = {2026-08-06},

journal = {Journal of Building Engineering},

volume = {44},

pages = {102635},

abstract = {The construction sector is a key generator of greenhouse emissions, so the use of alternative low-emission building materials is a growing tendency. This work describes and analyses an innovative sustainable building that includes mussel shells in all its constructive elements. This material is a by-product of the canning industry that is nowadays landfilled. Mussel shells were used as aggregate in the concrete strip footing (foundation) and in the exterior and interior coating mortars (walls), and as loose-fill material for the whole envelope insulation (floor, walls, and roof). The results from both the laboratory and the constructive process were useful to improve the solutions and to develop a building with low energy consumption. Finally, the energy demand of the building was assessed using the Passive House Planning Package (PHPP) software and the blower door test was carried out to measured air tightness. It can be concluded that mussel shell materials meet the requirements of Passive House standard for energy efficient buildings: simulation results showed a primary energy consumption of 86 kWh/(m2yr), that is a 28.3% lower than the value fixed by the standard.},

keywords = {Coating mortars, Energy efficiency, Loose-fill insulation, Recycled mussel shells, Thermal transmittance, Wood structure},

pubstate = {published},

tppubtype = {article}

}

@article{bienvenido-huertas_automation_2020,

title = {Automation and optimization of in-situ assessment of wall thermal transmittance using a Random Forest algorithm},

author = {David Bienvenido-Huertas and Carlos Rubio-Bellido and Juan Luis Pérez-Ordóñez and Miguel José Oliveira},

url = {https://www.sciencedirect.com/science/article/pii/S0360132319306912},

doi = {10.1016/j.buildenv.2019.106479},

issn = {0360-1323},

year  = {2020},

date = {2020-01-01},

urldate = {2026-08-06},

journal = {Building and Environment},

volume = {168},

pages = {106479},

abstract = {Reducing energy consumption and greenhouse gases emissions is among the main challenges of building sector. It is therefore crucial to know the characteristics of envelopes. There are experimental methods to determine thermal transmittance, but limitations are presented. By using techniques of artificial intelligence, this article solves the limitations of current methods by predicting correctly the thermal transmittance value of ISO 6946 and the building period of a wall with monitored data. The methodology used is extrapolated to any country: 163 real monitorings and 140 different typologies of walls have been combined to generate the dataset (22,820 items). The results show the optimal operation of the Random Forest algorithm because both the thermal transmittance of ISO 6946 and the building period are determined by using the most common methods: the heat flow meter method and the thermometric method. This study makes progress towards more automatized processes to characterize thermal transmittance.},

keywords = {Artificial intelligence, Building period, In-situ, ISO 6946, Random forests, Thermal transmittance},

pubstate = {published},

tppubtype = {article}

}

@article{bienvenido-huertas_optimizing_2019,

title = {Optimizing the evaluation of thermal transmittance with the thermometric method using multilayer perceptrons},

author = {David Bienvenido-Huertas and Carlos Rubio-Bellido and Juan Luis Pérez-Ordóñez and Juan Moyano},

url = {https://www.sciencedirect.com/science/article/pii/S0378778819310941},

doi = {10.1016/j.enbuild.2019.06.040},

issn = {0378-7788},

year  = {2019},

date = {2019-09-01},

urldate = {2026-08-06},

journal = {Energy and Buildings},

volume = {198},

pages = {395–411},

abstract = {The characterization of building thermal behaviour is crucial to achieve the low-carbon objectives of the European Union by 2050. In this way, the knowledge of the thermal transmittance is being developed as a significant factor of the thermophysical properties of the envelope. In the existing building, the theoretical calculation has several limitations with non-destructive techniques typical of the deterioration of the elements. Many experimental methods obtain therefore more representative results. The experimental method developed in ISO 9869–1 is the most standardized, although it presents limitations in the heat flux measurement. However, the thermometric method obtains the thermal transmittance with the surface temperature. This research is focused on the evaluation of the thermal transmittance based on ISO 9869–1 (average method and average method with correction for storage effects), but using variables measured with the thermometric method. For this purpose, multilayer perceptrons were used as post-processing techniques. The models were trained by using a dataset of 22,820 simulated tests of representative walls of the building stock in Spain. The determination coefficient was greater than 98% in both analysis approaches. Individual models were also generated for each building period because they significantly influenced the input variables. The results showed that thermal transmittance values can be obtained without measuring the heat flux, and the error associated with the use of tabulated values for the total internal heat transfer can be removed. This research would guarantee a high assessment tax of buildings establishing adequate energy conservation measures to improve their energy performance.},

keywords = {ISO 9869–1, Multilayer perceptrons, Thermal transmittance, Thermometric method},

pubstate = {published},

tppubtype = {article}

}