Benchmarking energy performance of building envelopes through a selective residual-clustering approach using high dimensional dataset

2014 ◽  
Vol 75 ◽  
pp. 10-22 ◽  
Author(s):  
Endong Wang ◽  
Zhigang Shen ◽  
Kevin Grosskopf
Keyword(s):  
Energy Performance ◽  
High Dimensional ◽  
Building Envelopes ◽  
Clustering Approach

Recommended angle of a modular dynamic façade in hot-arid climate: daylighting and energy simulation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Seyedeh Samaneh Golzan ◽  
Mina Pouyanmehr ◽  
Hassan Sadeghi Naeini
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Performance ◽  
Arid Climate ◽  
Visual Comfort ◽  
Building Envelopes ◽  
Content Type ◽  
Optimum Angle ◽  
Energy Efficient Buildings ◽  
Hot Arid Climate

PurposeThe modular dynamic façade (MDF) concept could be an approach in a comfort-centric design through proper integration with energy-efficient buildings. This study focuses on obtaining and/or calculating an efficient angle of the MDF, which would lead to the optimum performance in daylight availability and energy consumption in a single south-faced official space located in the hot-arid climate of Yazd, Iran.Design/methodology/approachThe methodology consists of three fundamental parts: (1) based on previous related studies, a diamond-based dynamic skin façade was applied to a south-faced office building in a hot-arid climate; (2) the daylighting and energy performance of the model were simulated annually; and (3) the data obtained from the simulation were compared to reach the optimum angle of the MDF.FindingsThe results showed that when the angle of the MDF openings was set at 30°, it could decrease energy consumption by 41.32% annually, while daylight simulation pointed that the space experienced the minimum possible glare at this angle. Therefore, the angle of 30° was established as the optimum angle, which could be the basis for future investment in responsive building envelopes.Originality/valueThis angular study simultaneously assesses the daylight availability, visual comfort and energy consumption on a MDF in a hot-arid climate.

scholarly journals On Innovative Cool-Colored Materials for Building Envelopes: Balancing the Architectural Appearance and the Thermal-Energy Performance in Historical Districts

2017 ◽  
Vol 9 (12) ◽  
pp. 2319 ◽  
Author(s):  
Federica Rosso ◽  
Anna Pisello ◽  
Veronica Castaldo ◽  
Marco Ferrero ◽  
Franco Cotana
Keyword(s):  
Thermal Energy ◽  
Energy Performance ◽  
Building Envelopes

Energy capable clustering method for extend the duration of IoT based mobile wireless sensor network with remote nodes

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Giji Kiruba ◽  
Benita
Keyword(s):  
Cluster Formation ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Average Energy ◽  
Energy Performance ◽  
Residual Energy ◽  
Clustering Approach ◽  
Study Methodology ◽  
Mobile Wireless Sensor ◽  
Local Average

Abstract The energy performance of IoT-MWSNs may be augmented by using a suitable clustering technique for integrating IoT sensors. Clustering, on the other hand, requires additional overhead, such as determining the cluster head and cluster formation. Environmental Energy Attentive Clustering with Remote Nodes is a unique environmental energy attentive clustering approach for IoT-MWSNs proposed in this study methodology (E2ACRN). Cluster head (CH) in E2ACRN is entirely determined by weight. The residual energy of each IoT sensor and the local average energy of all IoT sensors in the cluster are used to calculate the weight. Inappropriately planned allocated clustering techniques might result in nodes being too far away from CH. These distant nodes communicate with the sink by using more energy. The ambient average energy, remoteness among IoT sensors, and sink are used to determine whether a distant node transmits its information to a CH in the previous cycle or to sink in order to lengthen lifetime. The simulation results of the current technique revealed that E2ACRN performs better than previous clustering algorithms.

scholarly journals A Grid-Density Based Algorithm by Weighted Spiking Neural P Systems with Anti-Spikes and Astrocytes in Spatial Cluster Analysis

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1132
Author(s):  
Deting Kong ◽  
Yuan Wang ◽  
Xinyan Wu ◽  
Xiyu Liu ◽  
Jianhua Qu ◽  
...  
Keyword(s):  
Dimensional Space ◽  
P Systems ◽  
High Dimensional ◽  
P System ◽  
Inhibitory Influence ◽  
Spiking Neural P Systems ◽  
Clustering Approach ◽  
Spatial Cluster Analysis ◽  
Effectiveness And Efficiency ◽  
Real World Datasets

In this paper, we propose a novel clustering approach based on P systems and grid- density strategy. We present grid-density based approach for clustering high dimensional data, which first projects the data patterns on a two-dimensional space to overcome the curse of dimensionality problem. Then, through meshing the plane with grid lines and deleting sparse grids, clusters are found out. In particular, we present weighted spiking neural P systems with anti-spikes and astrocyte (WSNPA2 in short) to implement grid-density based approach in parallel. Each neuron in weighted SN P system contains a spike, which can be expressed by a computable real number. Spikes and anti-spikes are inspired by neurons communicating through excitatory and inhibitory impulses. Astrocytes have excitatory and inhibitory influence on synapses. Experimental results on multiple real-world datasets demonstrate the effectiveness and efficiency of our approach.

Effective R-value of enclosed reflective space for different building applications

2019 ◽  
Vol 43 (5) ◽  
pp. 398-427 ◽  
Author(s):  
Hamed H Saber ◽  
Wahid Maref ◽  
Ali E Hajiah
Keyword(s):  
Heat Flow ◽  
Thermal Performance ◽  
Accurate Determination ◽  
Energy Performance ◽  
Climatic Conditions ◽  
Operating Conditions ◽  
Building Envelopes ◽  
Inclination Angles ◽  
R Value ◽  
Enclosed Space

Many parts of the building envelopes contain enclosed airspaces. Also, the insulating glass units in fenestration systems, such as curtain walls, windows, and skylight devices, contain enclosed spaces that are normally filled with air or heavy gas such as argon, xenon, or krypton. The thermal resistance (R-value) of an enclosed space depends mainly on the type of the filling gas, emissivity of all surfaces that bound the space, the size and orientation of the space, the direction of heat flow through the space, and the respective temperatures of all surfaces that define the space. Assessing the energy performance of building envelopes and fenestration systems, subjected to different climatic conditions, requires accurate determination of the R-values of the enclosed spaces. In this study, a comprehensive review is conducted on the thermal performance of enclosed airspaces for different building applications. This review includes the computational and experimental methods for determining the effective R-value of enclosed reflective airspaces. Also, the different parameters that affect the thermal performance of enclosed airspaces are discussed. These parameters include the following: (a) dimensions, (b) inclination angles, (c) directions of heat flow, (d) emissivity of all surfaces that bound the space, and (e) operating conditions. Moreover, numerical simulations are conducted using a previously developed and validated model to investigate the effect of the inclination angle, direction of heat transfer, and the coating emissivity on the R-values of enclosed spaces when they are filled with different types of gases.

scholarly journals Cool Marble Building Envelopes: The Effect of Aging on Energy Performance and Aesthetics

2016 ◽  
Vol 8 (8) ◽  
pp. 753 ◽  
Author(s):  
Federica Rosso ◽  
Anna Pisello ◽  
Weihua Jin ◽  
Masoud Ghandehari ◽  
Franco Cotana ◽  
...  
Keyword(s):  
Energy Performance ◽  
Building Envelopes

scholarly journals Selecting Insulating Materials for Building Envelope: A Life Cycle Approach

2021 ◽  
Vol 65 (2-4) ◽  
pp. 312-316
Author(s):  
Surnam Sonia Longo ◽  
Maurizio Cellura ◽  
Maria Anna Cusenza ◽  
Francesco Guarino ◽  
Ilaria Marotta
Keyword(s):  
Life Cycle ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Cellulose Fibers ◽  
Energy Performance ◽  
Embodied Energy ◽  
Life Cycle Approach ◽  
Insulation Material ◽  
Gas Emissions ◽  
Building Envelopes

This paper aims at assessing the embodied energy and greenhouse gas emissions (GHGs) of two building envelopes, designed for a two floors semi-detached house located in the Central Italy. The analysis is performed by applying the Life Cycle Assessment methodology, following a from cradle-to-gate approach. Fixtures (windows and doors), external and internal opaque walls, roof and floors (including interstorey floors) make the building envelopes. Their stratigraphy allows for achieving the thermal transmittance values established in the Italian Decree on energy performance of buildings. The two examined envelopes differ only for the insulation material: extruded expanded polystyrene (XPS) or cellulose fibers. The results shows that the envelope using cellulose fibers has better performance than that using XPS: it allows for reducing the embodied energy and the GHGs of about 13% and 9.3%, respectively. A dominance analysis allows to identify the envelope components responsible of the higher impacts and the contribution of the insulating material to the impacts. The study is part of the Italian research “Analysis of the energy impacts and greenhouse gas emissions of technologies and components for the energy efficiency of buildings from a life cycle perspective” funded by the Three-year Research Plan within the National Electricity System 2019-2021.

scholarly journals A Clustering Approach for Characterizing Voter Types: An Application to High-Dimensional Ballot and Survey Data

2020 ◽  
Author(s):  
Shiro Kuriwaki
Keyword(s):  
Survey Data ◽  
Large Scale ◽  
Clustering Algorithm ◽  
High Dimensional ◽  
Palm Beach County ◽  
Spatial Voting ◽  
Clustering Approach ◽  
Swing Voters ◽  
State And Local ◽  
Spatial Voting Model

Large-scale ballot and survey data hold the potential to uncover the prevalence of swing voters and strong partisans in the electorate. However, existing approaches either employ exploratory analyses that fail to fully leverage the information available in high-dimensional data, or impose a one-dimensional spatial voting model. I derive a clustering algorithm which better captures the probabilistic way in which theories of political behavior conceptualize the swing voter. Building from the canonical finite mixture model, I tailor the model to vote data, for example by allowing uncontested races. I apply this algorithm to actual ballots in the Florida 2000 election and a multi-state survey in 2018. In Palm Beach County, I find that up to 60 percent of voters were straight ticket voters; in the 2018 survey, even higher. The remaining groups of the electorate were likely to cross the party line and split their ticket, but not monolithically: swing voters were more likely to swing for state and local candidates and popular incumbents.

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