scholarly journals Estimation of Heat Loss Coefficient and Thermal Demands of In-Use Building by Capturing Thermal Inertia Using LSTM Neural Networks

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 5188
Author(s):  
Martín Pensado-Mariño ◽  
Lara Febrero-Garrido ◽  
Estibaliz Pérez-Iribarren ◽  
Pablo Eguía Oller ◽  
Enrique Granada-Álvarez
Keyword(s):  
Neural Networks ◽  
Heat Loss ◽  
Short Term Memory ◽  
Basque Country ◽  
Thermal Inertia ◽  
Loss Coefficient ◽  
Time Lags ◽  
The North ◽  
The University ◽  
North Of Spain

Accurate forecasting of a building thermal performance can help to optimize its energy consumption. In addition, obtaining the Heat Loss Coefficient (HLC) allows characterizing the thermal envelope of the building under conditions of use. The aim of this work is to study the thermal inertia of a building developing a new methodology based on Long Short-Term Memory (LSTM) neural networks. This approach was applied to the Rectorate building of the University of Basque Country (UPV/EHU), located in the north of Spain. A comparison of different time-lags selected to catch the thermal inertia has been carried out using the CV(RMSE) and the MBE errors, as advised by ASHRAE. The main contribution of this work lies in the analysis of thermal inertia detection and its influence on the thermal behavior of the building, obtaining a model capable of predicting the thermal demand with an error between 12 and 21%. Moreover, the viability of LSTM neural networks to estimate the HLC of an in-use building with an error below 4% was demonstrated.

scholarly journals Prediction of Building’s Thermal Performance Using LSTM and MLP Neural Networks

2020 ◽  
Vol 10 (21) ◽  
pp. 7439 ◽  
Author(s):  
Miguel Martínez Comesaña ◽  
Lara Febrero-Garrido ◽  
Francisco Troncoso-Pastoriza ◽  
Javier Martínez-Torres
Keyword(s):  
Neural Networks ◽  
Short Term Memory ◽  
Public Library ◽  
Thermal Inertia ◽  
Energy Performance ◽  
Machine Learning Algorithms ◽  
Time Lags ◽  
Prediction Errors ◽  
The North ◽  
Complex Nonlinear Systems

Accurate prediction of building indoor temperatures and thermal demand is of great help to control and optimize the energy performance of a building. However, building thermal inertia and lag lead to complex nonlinear systems is difficult to model. In this context, the application of artificial neural networks (ANNs) in buildings has grown considerably in recent years. The aim of this work is to study the thermal inertia of a building by developing an innovative methodology using multi-layered perceptron (MLP) and long short-term memory (LSTM) neural networks. This approach was applied to a public library building located in the north of Spain. A comparison between the prediction errors according to the number of time lags introduced in the models has been carried out. Moreover, the accuracy of the models was measured using the CV(RMSE) as advised by AHSRAE. The main novelty of this work lies in the analysis of the building inertia, through machine learning algorithms, observing the information provided by the input of time lags in the models. The results of the study prove that the best models are those that consider the thermal lag. Errors below 15% for thermal demand and below 2% for indoor temperatures were achieved with the proposed methodology.

Western Pyrenees geodetic deformation study using the Guipuzcoa GNSS network

2018 ◽  
Vol 12 (3) ◽  
pp. 229-238 ◽  
Author(s):  
Adriana Martín ◽  
Miguel Sevilla ◽  
Joaquín Zurutuza
Keyword(s):  
Basque Country ◽  
The North ◽  
Study Results ◽  
Double Differences ◽  
Processing Module ◽  
Gnss Network ◽  
North Of Spain ◽  
Processing Engine ◽  
Basque Cantabrian Basin ◽  
Western Pyrenees

Abstract The Basque Country in the north of Spain is located inside the Basque-Cantabrian basin of the western Pyrenees which remarkable seismic-tectonic implications justify the need of geodetic control in the area. In order to perform a crustal deformation study we have analysed all daily observations from the GNSS permanent network of Guipuzcoa and external IGS stations, from January 2007 to November 2011. We have carried out the data processing applying double differences methodology in the automatic processing module BPE (Bernese Processing Engine) from Bernese GNSS software version 5.0. Solution was aligned to geodetic reference framework ITRF2008, by using the IGS08 solution and updated satellite and terrestrial antennas calibration. This five years network study results: Coordinate time series, velocities and baseline lengths variations show internal stability among inner stations and from them with respect to outer IGS stations, concluding that no deformations have been observed.

Prevalence and Genetic Diversity of Arcobacter in Food Products in the North of Spain

2013 ◽  
Vol 76 (8) ◽  
pp. 1447-1450 ◽  
Author(s):  
BARBARA NIEVA-ECHEVARRIA ◽  
IRATI MARTINEZ-MALAXETXEBARRIA ◽  
CECILIA GIRBAU ◽  
RODRIGO ALONSO ◽  
AURORA FERNÁNDEZ-ASTORGA
Keyword(s):  
Public Health ◽  
Genetic Diversity ◽  
Basque Country ◽  
Food Products ◽  
High Genetic Diversity ◽  
The North ◽  
Arcobacter Butzleri ◽  
North Of Spain ◽  
The Impact ◽  
The Relationship

The bacterial contamination of food products can cause serious public health problems. Interest in Arcobacter contamination has increased due to the relationship between these bacteria and human enteritis. We studied the prevalence and genetic diversity of Arcobacter species at the retail level in the province of Alava in Basque Country, Spain. The results showed a high genetic diversity and indicated the regular presence of the main Arcobacter spp. associated with human enteric illness in food products. Arcobacter butzleri, Arcobacter cryaerophilus, and Arcobacter skirrowii were detected with an overall prevalence close to 40% and were isolated from 15 (42.8%) fresh cow's milk samples, 12 (73.3%) shellfish samples, 11 (55%) chicken samples, 2 (10%) pork samples, and 1 (5%) beef sample. The results indicate the need to investigate the impact of Arcobacter spp. on public health.

scholarly journals Injection Treatment for Tunneling Excavation in Sandy Soils with High Fines Content

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6930
Author(s):  
Johnatan González-García ◽  
Celestino González-Nicieza ◽  
Martina-Inmaculada Álvarez-Fernández ◽  
María-Belén Prendes-Gero
Keyword(s):  
Setting Time ◽  
Injection Pressure ◽  
High Permeability ◽  
Test Device ◽  
Fines Content ◽  
The North ◽  
Injection Treatment ◽  
The Stability ◽  
The University ◽  
North Of Spain

Instability and high permeability are two of the problems facing tunnelling excavations in soils with high fines content. Among the different techniques used to improve these soils, the injection of cement grouts stands out. In this work, a grouting treatment is designed to ensure the stability of the ground during the construction of two tunnels linking two municipalities in the north of Spain in Biscay, and to reduce the inflow of water from the aquifer located in the vicinity of these tunnels. First of all, the rock mass is analysed and the material to be injected is selected on the basis of the authors’ experience as well as setting time and compressive strength. Subsequently, with a test device designed by the DinRock research group of the University of Oviedo, two types of laboratory tests are carried out in order to analyse the effect of fines migration and washing on the water flows and the effect of re-injections of grouts with different densities on the permeability value. The results show that, in sandy materials, obtaining high degrees of waterproofing together with large stable zones can only be achieved by a combination of treatments and stages with different materials and densities. In addition, maximum values for both injection pressure and flow rate must be established depending on the type of grout and the permeability of the soil. Once the problem has been analysed, the injection treatment is designed and executed. The treatment consists of one pre-injection in four stages with 30 boreholes drilled in the top heading, 19–20 boreholes drilled in the bench, and one post-injection with boreholes drilled around the perimeter of the tunnel in those areas where the pre-injection does not achieve the desired degree of waterproofing.

scholarly journals Single and Multi-Sequence Deep Learning Models for Short and Medium Term Electric Load Forecasting

Energies ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 149 ◽  
Author(s):  
Salah Bouktif ◽  
Ali Fiaz ◽  
Ali Ouni ◽  
Mohamed Adel Serhani
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Deep Learning ◽  
Short Term Memory ◽  
Load Forecasting ◽  
Forecasting Model ◽  
Time Lags ◽  
Electric Load ◽  
Learning Approaches ◽  
Electric Load Forecasting

Time series analysis using long short term memory (LSTM) deep learning is a very attractive strategy to achieve accurate electric load forecasting. Although it outperforms most machine learning approaches, the LSTM forecasting model still reveals a lack of validity because it neglects several characteristics of the electric load exhibited by time series. In this work, we propose a load-forecasting model based on enhanced-LSTM that explicitly considers the periodicity characteristic of the electric load by using multiple sequences of inputs time lags. An autoregressive model is developed together with an autocorrelation function (ACF) to regress consumption and identify the most relevant time lags to feed the multi-sequence LSTM. Two variations of deep neural networks, LSTM and gated recurrent unit (GRU) are developed for both single and multi-sequence time-lagged features. These models are compared to each other and to a spectrum of data mining benchmark techniques including artificial neural networks (ANN), boosting, and bagging ensemble trees. France Metropolitan’s electricity consumption data is used to train and validate our models. The obtained results show that GRU- and LSTM-based deep learning model with multi-sequence time lags achieve higher performance than other alternatives including the single-sequence LSTM. It is demonstrated that the new models can capture critical characteristics of complex time series (i.e., periodicity) by encompassing past information from multiple timescale sequences. These models subsequently achieve predictions that are more accurate.

First report of Mycosphaerella dearnessii Rostrup, teleomorph of Lecanosticta acicola (Thüm.) Syd., in Europe

2021 ◽  
Author(s):  
Nebai Mesanza ◽  
Mónica Hernández ◽  
Rosa Raposo ◽  
Eugenia Iturritxa
Keyword(s):  
Pinus Radiata ◽  
Basque Country ◽  
First Report ◽  
The North ◽  
Lecanosticta Acicola ◽  
Blight Disease ◽  
North Of Spain ◽  
Needle Blight

Conifers severely affected by brown needle blight disease caused by the ascomycete Lecanosticta acicola (Thüm.) Syd. show defoliation, reduced growth and death. Although L. acicola is known in Europe since 1942, its teleomorph, Mycosphaerella dearnessii Rostrup, has not yet been found. In this brief, we address the occurrence of Mycosphaerella dearnessii in Pinus radiata D. Don cast dead needles collected in the north of Spain (Basque country). To our knowledge, this is the first report of Mycosphaerella dearnessii Rostrup, teleomorph of Lecanosticta acicola (Thüm.) Syd., in Europe.

scholarly journals Analysis of an Attached Sunspace with a Thermal Inertia Floor

Energies ◽  
2018 ◽  
Vol 11 (5) ◽  
pp. 1136 ◽  
Author(s):  
María Suárez López ◽  
Antonio Gutiérrez Trashorras ◽  
Jorge Parrondo Gayo ◽  
Eduardo Blanco Marigorta
Keyword(s):  
Thermal Energy ◽  
Three Dimensional ◽  
Thermal Inertia ◽  
Thick Layer ◽  
Solar Irradiation ◽  
Thermal Mass ◽  
Intermediate Space ◽  
The North ◽  
Clear Glass ◽  
North Of Spain

An attached sunspace is a partially or fully glazed enclosure, usually located on the first floor, facing south (in the Northern Hemisphere) and adjacent to a conditioned room. Because of the length and orientation of the glazed area, the temperature in the sunspace is usually higher than outside the building. As a Trombe–Mitchel wall, the sunspace has a considerable mass that accumulates thermal energy, but in this case the thermal mass is located in the floor. This capacity to accumulate thermal energy confers the attached sunspace features beyond passive insulation. The sunspace studied in this paper is part of an experimental building located in the North of Spain that was built in the frame of the so-called ARFRISOL project. It consists of a south-facing glazed exterior wall with both clear glass and semi-transparent photovoltaic panels, an intermediate space with a thick layer of sand over a concrete floor, and a partially glazed interior wall. In this paper, a three-dimensional computational model has been implemented to analyse the thermal behaviour inside the sunspace. This analysis takes into account, among other factors, the effects of sun position, incident solar irradiation and temperature both inside and outside.

SEM and TEM observations of sperm development in the testis of the freshwater fish Oreochromis mossambicus

1990 ◽  
Vol 48 (3) ◽  
pp. 58-59
Author(s):  
Daryl A. Cornish ◽  
George L. Smit
Keyword(s):  
Morphological Characteristics ◽  
Oreochromis Mossambicus ◽  
Breeding Cycle ◽  
Limited Information ◽  
North West ◽  
The North ◽  
Sem And Tem ◽  
Sperm Development ◽  
Ultrastructural Characteristics ◽  
The University

Oreochromis mossambicus is currently receiving much attention as a candidater species for aquaculture programs within Southern Africa. This has stimulated interest in its breeding cycle as well as the morphological characteristics of the gonads. Limited information is available on SEM and TEM observations of the male gonads. It is known that the testis of O. mossambicus is a paired, intra-abdominal structure of the lobular type, although further details of its characteristics are not known. Current investigations have shown that spermatids reach full maturity some two months after the female becomes gravid. Throughout the year, the testes contain spermatids at various stages of development although spermiogenesis appears to be maximal during November when spawning occurs. This paper describes the morphological and ultrastructural characteristics of the testes and spermatids.Specimens of this fish were collected at Syferkuil Dam, 8 km north- west of the University of the North over a twelve month period, sacrificed and the testes excised.

Social Responsibility Practice Diagnosis applied to the Universidad del Valle- Northern Facility. Period 2014-2015

2018 ◽  
Vol 34 (62) ◽  
pp. 66-81
Author(s):  
Adriana M. Moreno Moreno ◽  
Eduar Fernando Aguirre González
Keyword(s):  
Social Responsibility ◽  
Action Plan ◽  
Research Problem ◽  
Socially Responsible ◽  
Strategic Development ◽  
Strategic Issues ◽  
The North ◽  
The Social ◽  
The University ◽  
Social Management

Social Responsibility is a concept that has been approached from different perspectives by theoreticians and institutions. Initially, this was limited exclusively to companies, however, the creation of the Social Capital, Ethics and Development Initiative by the Inter-American Development Bank (IDB) sought to make educational institutions aware that, like any other organization, they are responsible for the externalities they generate in their environment and their stakeholders. This research approaches the concept of University Social Responsibility (USR) from the scheme proposed by the IDB, which proposes four axes of action for Universities’ CR: Responsible Campus, Professional and Citizen Training, Social Management of Knowledge and Social Participation. The Universidad del Valle has a strategic plan entitled “Universidad del Valle’s Strategic Development Plan” and Regionalization attached thereto. It has also developed its action plan and in the five strategic issues raised herein, its socially responsible approach is clearly identifiable. The North Cauca Facility wherein this study is being developed, even though it does not have a University Social Responsibility Management Model, has attempted to align its practices with its strategic affairs that broadly conform to the four axes proposed by the IDB. This research addresses a relevant and current issue inasmuch as it proposes to develop a diagnosis on the relationship between the four axes of Social Responsibility proposed by the IDB and the practice of Social Responsibility applied at the Universidad del Valle, North Cauca Facility, for the period 2014-2015. In order to answer the research problem, a qualitative, exploratory and descriptive type of study is used, given that the work was based on the documentary information available at the University, while the interviews with the directors of the Institution are used as a tool for oral history. The research method used is the case study, which allows to address a unit of analysis in depth, in this case the USR within the Universidad del Valle, North Cauca Facility.

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