scholarly journals Development of a Decisional Procedure Based on Fuzzy Logic for the Energy Retrofitting of Buildings

2021 ◽  
Vol 13 (16) ◽  
pp. 9318
Author(s):  
Linda Barelli ◽  
Elisa Belloni ◽  
Gianni Bidini ◽  
Cinzia Buratti ◽  
Emilia Maria Pinchi
Keyword(s):  
Fuzzy Logic ◽  
Energy Savings ◽  
Building Energy ◽  
Linguistic Rules ◽  
Before And After ◽  
Automatic Tool ◽  
Few Data ◽  
Building Heat ◽  
Fuzzy Logic Expert System ◽  
Good Agreement

This paper concerns the development of an automatic tool, based on Fuzzy Logic, which is able to identify the proper solutions for the energy retrofitting of existing buildings. Regarding winter heating, opaque and glazing surfaces are considered in order to reduce building heat dispersions. Starting from energy diagnosis, it is possible to formulate retrofitting proposals and to evaluate the effectiveness of the intervention considering several aspects (energy savings, costs, intervention typology). The innovation of this work is represented by the application of a fuzzy logic expert system to obtain an indication about the proper interventions for building energy retrofitting, providing as inputs only few parameters, with a strong reduction in time and effort with respect to the software tools and methodologies currently applied by experts. The novelty of the paper is the easy handling properties of the developed tool, which requires only a few data about the buildings: not many such methods were developed in the last years. The energy requirements for winter heating before and after particular interventions were evaluated for a consistent set of buildings in order to produce the required knowledge base for the tool’s development. The identified appropriate inputs and outputs, their domains of discretization, the membership functions associated to each fuzzy set, and the linguistic rules were deduced on the basis of the knowledge determined in this was. Therefore, the system was successfully validated with reference to further buildings characterized by different design and architecture features, showing a good agreement with the intervention opportunities evaluated.

scholarly journals Impedance Spectroscopy of Lead-Free Ferroelectric Coatings

Coatings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 221
Author(s):  
Mariya Aleksandrova ◽  
Ivailo Pandiev
Keyword(s):  
Composite Coatings ◽  
Electrical Circuit ◽  
Ferroelectric Materials ◽  
Piezoelectric Transducers ◽  
Lead Free ◽  
Electrical Behavior ◽  
Oxide Composite ◽  
Before And After ◽  
Frequency Dependences ◽  
Good Agreement

This paper presents impedance measurements of ferroelectric structures involving lead-free oxide and polymer-oxide composite coatings for sensing and energy harvesting applications. Three different ferroelectric materials grown by conventional microfabrication technologies on solid or flexible substrates are investigated for their basic resonant characteristics. Equivalent electrical circuit models are applied to all cases to explain the electrical behavior of the structures, according to the materials type and thickness. The analytical results show good agreement with the experiments carried out on a basic types of excited thin-film piezoelectric transducers. Additionally, temperature and frequency dependences of the dielectric permittivity and losses are measured for the polymer-oxide composite device in relation with the surface morphology before and after introduction of the polymer to the functional film.

scholarly journals Energy and Greenhouse Gas Savings for LEED-Certified U.S. Office Buildings

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 749
Author(s):  
John H. Scofield ◽  
Susannah Brodnitz ◽  
Jakob Cornell ◽  
Tian Liang ◽  
Thomas Scofield
Keyword(s):  
Greenhouse Gas ◽  
Energy Use ◽  
Energy Savings ◽  
Electric Energy ◽  
Building Energy ◽  
Energy Performance ◽  
Office Buildings ◽  
Ghg Emission ◽  
Site Energy ◽  
New Construction

In this work, we present results from the largest study of measured, whole-building energy performance for commercial LEED-certified buildings, using 2016 energy use data that were obtained for 4417 commercial office buildings (114 million m2) from municipal energy benchmarking disclosures for 10 major U.S. cities. The properties included 551 buildings (31 million m2) that we identified as LEED-certified. Annual energy use and greenhouse gas (GHG) emission were compared between LEED and non-LEED offices on a city-by-city basis and in aggregate. In aggregate, LEED offices demonstrated 11% site energy savings but only 7% savings in source energy and GHG emission. LEED offices saved 26% in non-electric energy but demonstrated no significant savings in electric energy. LEED savings in GHG and source energy increased to 10% when compared with newer, non-LEED offices. We also compared the measured energy savings for individual buildings with their projected savings, as determined by LEED points awarded for energy optimization. This analysis uncovered minimal correlation, i.e., an R2 < 1% for New Construction (NC) and Core and Shell (CS), and 8% for Existing Euildings (EB). The total measured site energy savings for LEED-NC and LEED-CS was 11% lower than projected while the total measured source energy savings for LEED-EB was 81% lower than projected. Only LEED offices certified at the gold level demonstrated statistically significant savings in source energy and greenhouse gas emissions as compared with non-LEED offices.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

scholarly journals Modeling the seam strength of denim garments by using fuzzy expert system

2021 ◽  
Vol 16 ◽  
pp. 155892502198897
Author(s):  
Joy Sarkar ◽  
Md Abdullah Al Faruque ◽  
Moni Sankar Mondal
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Linear Density ◽  
Unit Length ◽  
Coefficient Of Determination ◽  
Sewing Thread ◽  
External Forces ◽  
Fuzzy Logic Expert System ◽  
The Relationship ◽  
Sufficient Strength

The main purpose of this study is to predict and develop a model for forecasting the Seam Strength (SS) of denim garments with respect to the thread linear density (tex) and Stitches Per Inch (SPI) by using a Fuzzy Logic Expert System (FLES). The seam strength is an important factor for the serviceability of any garments. As seams bound the fabric pieces together in a garment, the seams must have sufficient strength to execute this property even in the unexpected severe conditions where the garments are subjected to loads or any additional internal or external forces. Sewing thread linear density and number of stitches in a unit length of the seam are the two of the most important factors that affect the seam strength of any garments. But the relationship among these two specific variables and the seam strength is complex and non-linear. As a result, a fuzzy logic based model has been developed to demonstrate the relationship among these parameters and the developed model has been validated by the experimental trial. The coefficient of determination ( R2) was found to be 0.98. The mean relative error also lies withing acceptable limit. The results have suggested a very good performance of the model in the case of the prediction of the seam strength of the denim garments.

scholarly journals Measurements of urban traffic parameters before and after road reconstruction

2021 ◽  
Vol 11 (1) ◽  
pp. 365-376
Author(s):  
Andrzej Bąkowski ◽  
Leszek Radziszewski
Keyword(s):  
Urban Traffic ◽  
Noise Model ◽  
Vehicle Traffic ◽  
The Road ◽  
Passenger Vehicles ◽  
Before And After ◽  
Traffic Volumes ◽  
National Road ◽  
The City ◽  
Good Agreement

Abstract The study analyzed the parameters of vehicle traffic and noise on the national road in the section in the city from 2011 to 2016. In 2013–2014 this road was reconstructed. It was found that in most cases, the distribution of the tested variable was not normal. The median and selected percentiles of vehicle traffic parameters and noise were examined. The variability and type A uncertainty of the results were described and evaluated. The results obtained for the data recorded on working and non-working days were compared. The vehicle cumulative speed distributions, for two-way four-lane road segments in both directions were analyzed. A mathematical model of normalized traffic flow has been proposed. Fit factor R2 of the proposed equations to the experimental data for passenger vehicles ranges from 0.93 to 0.99. It has been shown that two years after the road reconstruction, the median noise level did not increase even though traffic volumes and vehicle speeds increased. The Cnossos noise model was validated for data recorded over a period of 6 years. A very good agreement of the medians determined according to the Cnossos-EU model and the measured ones was obtained. It should be noted, however, that for the other analyzed percentiles, e.g. 95%, the discrepancies are larger.

scholarly journals Influence of Lightweight Aggregate Concrete Materials on Building Energy Performance

Buildings ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 94
Author(s):  
Tara L. Cavalline ◽  
Jorge Gallegos ◽  
Reid W. Castrodale ◽  
Charles Freeman ◽  
Jerry Liner ◽  
...  
Keyword(s):  
Thermal Properties ◽  
Building Materials ◽  
Energy Savings ◽  
Lightweight Concrete ◽  
Lightweight Aggregate ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Building Energy Performance

Due to their porous nature, lightweight aggregates have been shown to exhibit thermal properties that are advantageous when used in building materials such as lightweight concrete, grout, mortar, and concrete masonry units. Limited data exist on the thermal properties of materials that incorporate lightweight aggregate where the pore system has not been altered, and very few studies have been performed to quantify the building energy performance of structures constructed using lightweight building materials in commonly utilized structural and building envelope components. In this study, several lightweight concrete and masonry building materials were tested to determine the thermal properties of the bulk materials, providing more accurate inputs to building energy simulation than have previously been used. These properties were used in EnergyPlus building energy simulation models for several types of commercial structures for which materials containing lightweight aggregates are an alternative commonly considered for economic and aesthetic reasons. In a simple model, use of sand lightweight concrete resulted in prediction of 15–17% heating energy savings and 10% cooling energy savings, while use of all lightweight concrete resulted in prediction of approximately 35–40% heating energy savings and 30% cooling energy savings. In more complex EnergyPlus reference models, results indicated superior thermal performance of lightweight aggregate building materials in 48 of 50 building energy simulations. Predicted energy savings for the five models ranged from 0.2% to 6.4%.

scholarly journals A Study of Optimal Specifications for Light Shelves with Photovoltaic Modules to Improve Indoor Comfort and Save Building Energy

2021 ◽  
Vol 18 (5) ◽  
pp. 2574
Author(s):  
Heangwoo Lee ◽  
Xiaolong Zhao ◽  
Janghoo Seo
Keyword(s):  
Energy Savings ◽  
Building Energy ◽  
Energy Performance ◽  
Building Energy Efficiency ◽  
Efficiency Change ◽  
Photovoltaic Modules ◽  
Heating And Cooling ◽  
Pv Module ◽  
Pv Modules ◽  
Indoor Comfort

Recent studies on light shelves found that building energy efficiency could be maximized by applying photovoltaic (PV) modules to light shelf reflectors. Although PV modules generate a substantial amount of heat and change the consumption of indoor heating and cooling energy, performance evaluations carried out thus far have not considered these factors. This study validated the effectiveness of PV module light shelves and determined optimal specifications while considering heating and cooling energy savings. A full-scale testbed was built to evaluate performance according to light shelf variables. The uniformity ratio was found to improve according to the light shelf angle value and decreased as the PV module installation area increased. It was determined that PV modules should be considered in the design of light shelves as their daylighting and concentration efficiency change according to their angles. PV modules installed on light shelves were also found to change the indoor cooling and heating environment; the degree of such change increased as the area of the PV module increased. Lastly, light shelf specifications for reducing building energy, including heating and cooling energy, were not found to apply to PV modules since PV modules on light shelf reflectors increase building energy consumption.

Discontinuation of Medication Overuse in Headache Patients: Recovery of Therapeutic Responsiveness

Cephalalgia ◽  
2006 ◽  
Vol 26 (10) ◽  
pp. 1192-1198 ◽  
Author(s):  
P Zeeberg ◽  
J Olesen ◽  
R Jensen
Keyword(s):  
Drug Withdrawal ◽  
Medication Overuse ◽  
Medication Overuse Headache ◽  
Headache Frequency ◽  
Female Ratio ◽  
Headache Centre ◽  
Before And After ◽  
Male Female Ratio ◽  
Few Data ◽  
Almost All

It is generally accepted that ongoing medication overuse nullifies the effect of prophylactic treatment, although few data support this contention. We set out to describe the treatment outcome in patients withdrawn from medication overuse and relate any improvement to a renewed effect of prophylaxis. For patients with probable medication-overuse headache (pMOH), treated and dismissed from the Danish Headache Centre in 2002 and 2003, we assed, from prospective headache diaries, the headache frequency before and after withdrawal of offending drugs and compared these frequencies with the headache frequency at dismissal. Among 1326 patients, 337 had pMOH. Eligible were 175, mean age 49 years, male/female ratio 1: 2.7. Overall, there was a 46% decrease in headache frequency from the first visit to dismissal ( P < 0.0001). Patients with no improvement 2 months after complete drug withdrawal ( N = 88) subsequently responded to pharmacological and/or non-pharmacological prophylaxis with a 26% decrease in headache frequency as measured from the end of withdrawal to dismissal ( P < 0.0001). At dismissal, 47% were on prophylaxis. Former non-responders to medical prophylaxis had a 49% decrease in headache frequency from first visit to dismissal ( P < 0.0001), whereas those who had never received prophylaxis had a 56% reduction ( P < 0.0001). This difference was not statistically significant ( P = 0.22). Almost all MOH patients benefit from drug withdrawal, either just from the withdrawal or by transformation from therapeutic non-responsiveness to responsiveness. According to the International Classification of Headache Disorders, 2nd edn, the MOH diagnosis requires improvement after drug withdrawal. Our data suggest that these diagnostic criteria are too strict.

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