Civil Structural & Environ Eng: Recent submissions
Now showing items 81-100 of 1410
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Alkali fusion of bauxite refining residue (red mud-RM) to produce low carbon cements
(2023)This paper creates hydraulic binders using waste and a low energy input. Cements are produced with a bauxite refining residue (red mud-RM), blended with limestone and lime, and fused at temperatures from 600 to 1200 °C. ... -
Appraisal of Alum Sludge Waste for Low-Carbon, Calcium Aluminate Cement Production
(ISBN: 978-989-54499-3-4, 2023)Calcium aluminate cement (CAC) is the most used non-Portland cement, known for its rapid hardening and high thermal resistance. The difficulty in obtaining raw materials, mainly bauxite, has resulted in the current high ... -
Properties of Alkali Activated Materials made with bauxite refining residue (red mud-RM) and blends of RM with fly ash (FA)
(ISBN: 978-989-54499-3-4, 2023)A bauxite refining residue (RM), both alone and blended with FA at 30% and 50%, is activated with alkalis (Na2SiO3 and Na2SiO3/NaOH) to produce geopolymer cements. Alkali-activated materials (AAMs)/geopolymers are a more ... -
Measuring the design of empathetic buildings: a review of universal design evaluation methods
(2016)Purpose: Universal design (UD) provides an explanation of good design based on the user perspective, which are outlined through its principles, goals, and related frameworks. The aim of this paper is to provide an overview ... -
Potential of spent fluid cracking catalyst (FCC) waste for low-carbon cement production
(2023)Spent fluid cracking catalyst (FCC) waste is produced to convert petroleum crude oil into gasoline, and its main component is a reactive zeolite known as faujasite. This paper studies low-energy treatments to enhance ... -
Hot-lime-mixed hemp concretes
(2023)Hemp-lime composites are sustainable, low-carbon, non-loadbearing materials with outstanding thermal properties and high vapour permeability, used in new construction or thermal upgrades. The abundant pores in the hemp ... -
Reverse extrusion test for fine-grained soil characterisation: internal flow pattern with ANN-enhanced particle tracking
(2023)The reverse extrusion test involves one-dimensionally (1D) compressing a fine-grained soil sample contained in a cup container of cross-sectional area A. The force Fe applied by the loading platen causes extrusion of the ... -
Converting optimum compaction properties of fine-grained soils between rational energy levels
(2023)This study introduces a practical energy conversion (EC)-type modeling framework capable of converting the optimum compaction properties of fine-grained soils between any two rational compaction energy levels (CELs). Model ... -
Pre and post Covid preferences for working from home
(2024)Working from home (WFH) is being seen as a potential solution to many contemporary problems from congestion to global warming and work-life balance. Since the 1970 s, it was assumed that when information technology ... -
Large scale compound parabolic concentrator for building integrated façade
(Trinity College Dublin. School of Engineering. Disc of Civil Structural & Environmental Eng, 2023)This thesis presents the design, fabrication, performance and analysis of two façade integrated compound parabolic concentrator (CPC) for two different locations: Ferrara, Italy and Mayo Ireland. The research involves ... -
Damping Ratio Estimation for a Slender Modular Building from Full Scale Ambient Response Monitoring
(2023)The application of modular construction in tall slender structures is a relatively novel concept. Modular buildings with heights exceeding 130m have been successfully constructed by combining reinforced concrete cores with ... -
Critical Infrastructure Resilience in the PRECINCT Project
(2023)The PRECINCT project brings together Critical Infrastructure owners and authorities from four �Living Lab� cities throughout Europe. These Living Labs then operate as a coordinated precinct responding to the various ... -
Engineering Risk Analysis and Decision for Communities Facing Natural Hazards: A Talk in Four Parts
(2023)This presentation is the culmination of a decade of research on the technological and social aspects of decision-making for the consideration of natural hazards in communities. It covers four different aspects, and as such, ... -
Physically driven full probabilistic uncertainty propagation in complex nonlinear structures
(2023)The safety and reliability evaluation of complex engineering structures under dynamic loading conditions has long been a challenging problem. The coupling of nonlinearity and randomness in high-dimensional or large-degre ... -
Disaster Resilience Management of Civil Infrastructure Systems based on Reliability, Redundancy, and Recoverability
(2023)As the complexity of civil infrastructure systems is ever-increasing amid various uncertainties, their resilience against natural and human-made disasters should be managed based on a holistic understanding of the systemsﾒ ... -
New insights for chemical-physical processes from analysis of observations using extreme value probability distributions
(2023)Conventional extreme value (EV) theory has the Gumbel EV distribution as the theoretically correct distribution to represent the maximum depth of corrosion pits. It has long been used for prediction of the probability of ... -
Empirical distributions of traffic loads from one year of weigh-in-motion data
(2023)In the state-of-the-art of structural engineering the actions for design or assessment of bridges should derive from a probabilistic (i.e., frequentist) characterization of the loads. Data from weigh-in-motion (WIM) systems ... -
Structural management and Value of Information analysis accounting for sensor data quality
(2023)Structural health monitoring (SHM) can be used to assess the state of health of civil structures and infrastructures and acquire information that can support maintenance-related activities and post-disaster emergency ... -
Bayesian Neural Networks for Probabilistic Surrogate Models ﾖ Uncertainty Quantification, Propagation, and Sensitivity Analysis
(2023)Neural networks are powerful function approximators which scale to problems having large input dimensionality. Bayesian neural networks are an interesting choice for surrogate models as they (1) natively enable performing ...
