Browsing TKD - Institutt for bygg- og energiteknikk by Title
Now showing items 354-373 of 464
-
Post-COVID ventilation design: Infection risk-based target ventilation rates and point source ventilation effectiveness
(Peer reviewed; Journal article, 2023)Ventilation, air filtration and disinfection have been found to be the main engineering measures to control the airborne respiratory infection transmission in shared indoor spaces. Wells-Riley model modifications allow to ... -
Pozzolanisk høyfast betong med tilgjengelige materialer
(Bachelor thesis, 2019)Denne bacheloroppgaven omhandler muligheten for å produsere pozzolanisk høyfast betong, med tilstrekkelig støpelighet, trykkfasthet innenfor definisjonsområdet gitt i Eurokode 2, og som utnytter tilgjengelige materialer ... -
Pre-code RC bare frame: Seismic retrofit with alternative strategies
(AIP Conference Proceedings; Volume 2293, Issue 1, Journal article; Peer reviewed, 2020-11-25)In the last fifty years, a significant number of earthquakes that caused great economic losses and casualties have been recorded. In particular, in the last ten years, many seismic events occurred, and their medium magnitude ... -
Predicting Compressive Strength of Concrete Containing Recycled Aggregate Using Modified ANN with Different Optimization Algorithms
(Applied Sciences;Volume 11, Issue 2, Journal article; Peer reviewed, 2021-01-06)Using recycled aggregate in concrete is one of the best ways to reduce construction pollu- tion and prevent the exploitation of natural resources to provide the needed aggregate. However, recycled aggregates affect the ... -
Predicting compressive strength of CRM samples using Image processing and ANN
(IOP Conference Series: Materials Science and Engineering;volume 899, Peer reviewed; Journal article, 2020)Quality of concrete is majorly ascertained through its compressive strength which has a significant role in the stability of concrete structures. In this study, artificial neural network (ANN) and image processing (IP) ... -
Predicting moisture condensation risk on the radiant cooling floor of an office using integration of a genetic algorithm-back-propagation neural network with sensitivity analysis
(Journal article; Peer reviewed, 2022)Pre-dehumidification time (𝜏�pre ) and pre-dehumidification energy consumption (Epre ) play important roles in preventing the condensation of moisture on the floors of rooms that use a radiant floor cooling (RFC) ... -
Predicting the shear capacity of composite steel plate shear wall with the application of RSM
(Peer reviewed; Journal article, 2024)This research aims to predict the maximum shear capacity of Composite Steel Plate Shear Walls (CSPSWs) through nonlinear Finite Element (NLFE) analyses and Response Surface Method (RSM). The variables are concrete thickness ... -
Prediction and correlation analysis of ventilation performance in a residential building using artificial neural network models based on data-driven analysis
(Sustainable Cities and Society (SCS);Volume 83, August 2022, 103981, Peer reviewed; Journal article, 2022-06-14)This study investigates approaches to evaluate prediction and correlation how significantly mechanical and natural ventilation rate and local weather conditions affect the actual ventilation performance of a residential ... -
Prediction models for bond strength of steel reinforcement with consideration of corrosion
(Materials Today: Proceedings;Volume 45, Part 6, Peer reviewed; Journal article, 2021-04-02)Corrosion phenomena is one of the main deterioration causes, which remarkably affects the behavior of structural reinforced concrete (RC) members in seismic regions. Researches on reducing rehabilitation cost, performance ... -
Prediction Models for Thermal Conductivity of Cement-based Composites
(Nordic Concrete Research;No. 58 – 1/2018, Journal article; Journal article; Peer reviewed, 2018-10-25)Cement-based materials are the most consumed materials in the construction industry. Low or high thermal conductive cement-based materials are of interest in applications such as embedded floor heating systems, building ... -
Prediction of properties of FRP-confined concrete cylinders based on artificial neural networks
(Crystals;Volume 10, Issue 9, Journal article; Peer reviewed, 2020-09-14)Recently, the use of fiber-reinforced polymers (FRP)-confinement has increased due to its various favorable effects on concrete structures, such as an increase in strength and ductility. Therefore, researchers have been ... -
Prediction of seismic damage spectra using computational intelligence methods
(Computers & structures;, Peer reviewed; Journal article, 2021)Predicting seismic damage spectra, capturing both structural and earthquake features, is useful in performance-based seismic design and quantifying the potential seismic damage of structures. The objective of this paper ... -
Prediction of the Eigenperiods of MDOF Shear Buildings Using Neural Networks
(International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering;8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, Conference object, 2021)The study of multi-degree of freedom (MDOF) systems is essential to evaluate and understand the seismic response of buildings. Through a MDOF idealization, the dynamic properties of the building such as its natural frequencies ... -
Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network
(Applied Sciences;Volume 10 / Issue 3: Special Issue - Soft Computing Techniques in Structural Engineering and Materials, Journal article; Peer reviewed, 2020-02-10)As a lateral load-bearing system, the steel plate shear wall (SPSW) is utilized in different structural systems that are susceptible to seismic risk and because of functional reasons SPSWs may need openings. In this ... -
Predictions of electricity consumption in a campus building using occupant rates and weather elements with sensitivity analysis: Artificial neural network vs. linear regression
(Peer reviewed; Journal article, 2020)This study compares building electric energy prediction approaches that use a traditional statistical method (linear regression) and artificial neural network (ANN) algorithms. We investigate how significantly occupancy ... -
A Preliminary Structural Survey of Heritage Timber Log Houses in Tønsberg, Norway
(Conference object, 2021-11-29)The formulation of a multi-hazard loss model for a given structure is not only of interest for predicting the economic impact of future damage but it can also be of importance for risk mitigation. A methodology that can ... -
Probabilistic approach to assess URM walls with openings using discrete rigid block analysis (D-RBA)
(Journal article; Peer reviewed, 2022)This study aims to improve our current understanding of the seismic assessment of load-bearing unreinforced masonry (URM) systems by proposing a probabilistic computational modeling framework using the discrete element ... -
Probabilistic Assessment of RC Piers Considering Vertical Seismic Excitation Based on Damage Indices
(RILEM Bookseries;, Chapter; Peer reviewed; Conference object; Journal article, 2023)Bridges play a vital role in highway transportation systems and damage to bridges may cause impaired emergency response and economic loss and interrupt the functionality of the systems. Damage to bridge during the last ... -
Probabilistic models of marine environmental variables and their impact on dynamic responses of a sea-crossing suspension bridge
(Ocean Engineering;, Peer reviewed; Journal article, 2024)Advancing the Qiongzhou Strait Sea-crossing Bridge program is crucial for regional integration and economic development, yet the intricate coupling effects between environmental variables and structures pose significant ... -
Pros and cons of various equivalent frame models for nonlinear analysis of URM buildings
(ECCOMAS Congress;8th European Congress on Computational Methods in Applied Sciences and Engineering, Conference object, 2022)Brick masonry is considered as one of the old construction materials, and several cultural heritage assets are made of unreinforced masonry (URM), which is susceptible to earthquakes due to its brittle behavior. The ...