Grading of recovered Norway spruce (Picea abies) timber for structural purposes

Llana, Daniel F.; Íñiguez-González, Guillermo; Plos, Mitja; Turk, Goran

doi:10.1016/j.conbuildmat.2023.132440

Cited by 2 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The oldest known technique for NDT is the visual inspection technique starting with the naked eye, but with the advent of technology, the visual inspection technique is augmented with the power of strong microscopes and high-resolution camera lens setups [4]. Vibration-based methods have also been used in the industry for defect detection; however, they are limited by their low sensitivity and accuracy, especially for small subjects [5]. Electromagnetic (EM) techniques offer a vital contribution in the field of NDT, utilizing techniques like eddy current testing, electromagnetic induction, and the sweep frequency technique [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

In-Depth Steel Crack Analysis Using Photoacoustic Imaging (PAI) with Machine Learning-Based Image Processing Techniques and Evaluating PAI-Based Internal Steel Crack Feasibility

Akbar,

Lee,

Kim

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

Steel plays an indispensable role in our daily lives, permeating various products ranging from essential commodities and recreational gears to information technology devices and general household items. The meticulous evaluation of steel defects holds paramount importance to ensure the secure and dependable operation of the end products. Photoacoustic imaging (PAI) emerges as a promising modality for structural inspection in the realm of health monitoring applications. This study incorporates PAI experimentation to generate an image dataset and employs machine learning techniques to estimate the length and width of surface cracks. Furthermore, the research delves into the feasibility assessment of employing PAI to investigate internal cracks within a steel sample through a numerical simulation-based study. The study’s findings underscore the efficacy of the PAI in achieving precise surface crack detection, with an acceptable root mean square error (RMSE) of 0.63 ± 0.03. The simulation results undergo statistical analysis techniques, including the analysis of variance (ANOVA) test, to discern disparities between pristine samples and those featuring internal cracks at different locations. The results discern statistically significant distinctions in the simulated acoustic responses for samples with internal cracks of varying sizes at identical/different locations (p < 0.001). These results validate the capability of the proposed technique to differentiate between internal crack sizes and positions, establishing it as a viable method for internal crack detection in steel.

show abstract

Section: Introductionmentioning

confidence: 99%

In-Depth Steel Crack Analysis Using Photoacoustic Imaging (PAI) with Machine Learning-Based Image Processing Techniques and Evaluating PAI-Based Internal Steel Crack Feasibility

Akbar,

Lee,

Kim

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

Evaluation of the Carbon Footprint of Wooden Glamping Structures by Life Cycle Assessment

Sebestyén

2024

Sustainability

View full text Add to dashboard Cite

Despite the increasing popularity of glamping structures, empirical studies often overlook the carbon impact of wood in these constructions, creating a significant research gap. Understanding the net carbon effect of wood in glamping structures is crucial for informing sustainable building practices. This paper aims to quantitatively compare the net carbon impact of wood in glamping structures, filling a notable gap in the current research literature. The investigation undertakes a thorough evaluation employing a life cycle methodology, appraising the emissions linked with the complete glamping life span. Seven Romanian companies are examined vertically within the glamping production chain and horizontally across the supply value chain. The investigation unveils a notable discovery: the integration of wood within glamping yields considerable carbon sequestration, wherein the wood employed sequesters 36.83 metric tons of CO2 per glamping unit. This surpasses the carbon emissions entailed throughout the entirety of the glamping life cycle, ranging from 9.97 to 11.72 metric tons of carbon. Remarkably, a single wood-incorporated glamping structure has the capacity to sequester approximately 25 metric tons of carbon within a span of 50 years. In summary, the investigation underscores the capacity of responsibly sourced timber to function as a carbon reservoir, proficiently counterbalancing emissions across the entirety of the construction life cycle. The findings underscore the importance of sustainably sourced wood in achieving carbon neutrality and provide valuable insights for promoting sustainable building practices. This methodology has broad applicability beyond glamping structures, holding potential for replication and scalability across various sectors and regions, thereby contributing to global efforts towards mitigating climate change and fostering positive environmental change.

show abstract

Grading of recovered Norway spruce (Picea abies) timber for structural purposes

Cited by 2 publications

References 36 publications

In-Depth Steel Crack Analysis Using Photoacoustic Imaging (PAI) with Machine Learning-Based Image Processing Techniques and Evaluating PAI-Based Internal Steel Crack Feasibility

In-Depth Steel Crack Analysis Using Photoacoustic Imaging (PAI) with Machine Learning-Based Image Processing Techniques and Evaluating PAI-Based Internal Steel Crack Feasibility

Evaluation of the Carbon Footprint of Wooden Glamping Structures by Life Cycle Assessment

Contact Info

Product

Resources

About