Framework for Combined Life Cycle Environmental, Economic, and Social Assessment of Reclaimed Construction Products

A relevant approach to limit virgin materials consumption and waste in the construction industry is to use reclaimed construction products. Their sustainability performance depends on various parameters, including the activities needed to reuse them. Currently, the life cycle sustainability assessment (LCSA) of reclaimed products is conducted following various methods and assumptions, which are not always transparently communicated. There is also limited consideration of other sustainability indicators beyond initial cost and greenhouse gas (GHG) emissions. Therefore, we developed a harmonized Excel-based LCSA framework for evaluating and comparing side-by-side the life cycle environmental (LCA), economic (LCC), and social (S-LCA) impacts of reclaimed and new construction products. This chapter presents the LCSA framework and how it can be applied in practice, with the comparative evaluation of a pavement in Oslo, Norway, with new and reclaimed paving stones. The LCSA framework shows it is possible to harmonize the various assessment methods and expand the scope of product assessment from purely GHG emissions to overall sustainability. The results of the pavement assessment show that reuse can bring lower environmental and social impacts, although it currently costs more to the user. The LCSA framework can be tested by experts in one or more life cycle approaches to guide different actors in the reuse value chain (e.g., product resellers and architects).publishedVersio

Non-contact interactance NIR spectroscopy for estimating TSS and sensory sweetness in conveyor-belt transported cherry tomatoes (Lycopersicon esculentum ’Piccolo’)

Sweetness in tomatoes is a crucial quality feature, especially for high-cost varieties. Without efficient measurements, producers cannot guarantee sweetness, which may lead to low repurchase rates and increased food waste. In this article we report how total soluble solids (TSS), a measure for total sugar content, can be measured in cherry tomatoes using non-contact near-infrared (NIR) interactance spectroscopy. A prototype system working in the wavelength range 760–1080 nm was tested and compared with a commercial handheld NIR reflection instrument operating in the range of 909–1676 nm. The instruments were calibrated using data collected from 200 tomatoes and tested on 5 independent sets harvested over the next 14 months, a total of 611 single tomatoes and 22 tomato trusses. TSS for single tomatoes was in the range 5.3–14 %. NIR interaction obtained typical standard errors of prediction in the range 0.38–0.52 %, significantly lower (p < 0.05) compared to NIR reflection (0.70–0.98 %). Approximately the same accuracy was obtained by interaction measurements on tomatoes moving on a conveyor belt, both in lab (0.47–0.53 %) and in industry (0.39 %). Whole tomato trusses were measured in movement, and TSS could successfully be measured in each tomato on the truss. Three of the test sets were subjected to sensory analysis performed by a trained panel of 10 assessors, revealing high correlations (0.88 – 0.99) between sensory sweetness and NIR estimated TSS. The results demonstrate that a carefully designed NIR interaction instrument can be used for rapid and non-contact monitoring and sorting of cherry tomatoes according to sweetness.publishedVersio

SnowPole Detection: A comprehensive dataset for detection and localization using LiDAR imaging in Nordic winter conditions

The SnowPole Detection dataset is a comprehensive collection of labeled LiDAR images, specifically designed for snow pole detection in road environments. This dataset was collected using a high-resolution OS2-128 LiDAR sensor mounted on an autonomous vehicle research platform, covering diverse environments such as mountainous, open, and forested areas. The SnowPole Detection dataset supports applications in computer vision, with a particular focus on snow pole detection and localization. he OS2-128 LiDAR sensor captures point clouds, which are processed using the Ouster SDK to generate 360-degree images in four modalities: Near-IR, Signal, Reflectivity, and Range. To enhance usability, color images were generated by assigning the first three modalities (Near-IR, Signal, and Reflectivity) to the blue, green, and red channels, respectively, excluding the Range modality. Initial labeling was conducted using Roboflow, with further refinement in CVAT, resulting in high-quality annotations. The dataset comprises a total of 1,954 manually labeled images, divided into 1,367 training images, 390 validation images, and 197 test images, following a 70/20/10 split. Since the images across all modalities are pixel-aligned, the labels for the color images are also applicable to each modality individually. This structure allows researchers to directly use the dataset for snow pole detection tasks, whether focusing on color or individual LiDAR modalities. The SnowPole Detection dataset is publicly available at Mendeley1.publishedVersio

Ultrasonic pulse-echo dataset from numerical modelling for oil and gas well integrity investigations

The ultrasonic pulse-echo (PE) measurement is a crucial measurement technique to determine the integrity of oil and gas wells. Oil companies use various analysis techniques and corrections to derive the pipe thickness and impedance of the material behind the pipe from PE measurements that are carried out inside the pipe. While some field measurements are publicly available, they have no corresponding ground truth. We therefore simulated a dataset of PE measurements with ground truth. The dataset was generated using axisymmetric models and 3D models in COMSOL Multiphysics. The base geometry was based on common parameters from the field: oil-based mud on the inside of a 9.625 in pipe and cement on the outside of the pipe. From this base geometry, variations in the model parameters were introduced, for example, plate/pipe wall thickness, different materials on both sides of the wall, different pipe diameter, different annulus thicknesses, eccentering. The generated dataset allows detailed investigations of existing PE analysis algorithms, comparison of those and development of new PE analysis techniques.publishedVersio

A new method for placental volume measurements using tracked 2D ultrasound and automatic image segmentation

Background: Placental volume measurements can potentially identify high-risk pregnancies. We aimed to develop and validate a new method for placental volume measurements using tracked 2D ultrasound and automatic image segmentation. Methods: We included 43 pregnancies at gestational week 27 and acquired placental images using a 2D ultrasound probe with position tracking, and trained a convolutional neural network (CNN) for automatic image segmentation. The automatically segmented 2D images were combined with tracking data to calculate placental volume. For 15 of the included pregnancies, placental volume was also estimated based on MRI examinations, 3D ultrasound and manually segmented 2D ultrasound images. The ultrasound methods were compared to MRI (gold standard). Results: The CNN demonstrated good performance in automatic image segmentation (F1-score 0.84). The correlation with MRI-based placental volume was similar for tracked 2D ultrasound using automatically segmented images (absolute agreement intraclass correlation coefficient [ICC] 0.58, 95% CI 0.13–0.84) and manually segmented images (ICC 0.59, 95% CI 0.13–0.84). The 3D ultrasound method showed lower ICC (0.35, 95% CI −0.11 to 0.74) than the methods based on tracked 2D ultrasound. Conclusions: Tracked 2D ultrasound with automatic image segmentation is a promising new method for placental volume measurements and has potential for further improvement.publishedVersio

FME HighEFF Final Report, Appendix 4: HighEFF innovations

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Datakilder for sporings- og aktivitetsdata fra myke trafikanter

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Hva må til for å akselerere omstilling av norsk havnesektor? Omstillingsagenda for tre norske havner Bodø, Kristiansand og Borg

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Structural Analysis of Glulam Frame of a Modular Timber–Aluminium Hybrid Façade System in Nordic Climate

This article presents the results of mechanical testing and structural analysis of the glulam frame supporting novel external façade envelope elements made of aluminium, glass, and insulation. The glulam frame forms the basic structural support for the new modular hybrid façade system, an industrial product designed by STATICUS company with an aim at reducing environmental impact. The ultimate and serviceability limit states are considered to assess the durability of the design in terms of possible deformations affecting air and moisture tightness as well as the level of stresses leading to potential damage accumulations and fatigue. The analysis combines the horizontal environmental loads, that is, wind loads over 4 years of real wind speed data in 2021–2023 together with the permanent self-weight loads for the representative mid-rise building in different characteristic coastal locations in Norway: Oslo, Trondheim, and Tromsø. The constructed load models are applied to the geometrically non-linear numerical mechanical model of the glulam frame. Explicit modelling of the screw connections in the frame was validated by static mechanical testing in a laboratory set-up. Continuum elements with an orthotropic material model are used for wood. The stress level in reference to the ultimate strength was established for all wind loads and characteristic failure mode was identified as local compression perpendicular to grain in the screw connection. The mechanical fatigue life of the glulam frame is estimated at a minimum of 32 years (Tromsø) and a maximum of over 100 years (Oslo, Trondheim) based on the calculated stress level and real expected number of cycles of loading over the service life.publishedVersio

Transition scenarios for conversion to net-carbon-neutral fishing vessels

SINTEF Ocean has conducted a review of published reports on transition scenarios for the conversion of fishing vessels to net-carbon-neutral vessels. The scenarios analysis concludes that the ultimate goal of carbon-neutral fishing vessels can be met, but that the direct use of hydrogen will play a neglectable role to obtain such ambitious targets. The memo explains basic constraints related to hydrogen properties and hydrogen fuel systems, as well as their impacts on costs and feasibility as a fuel for fishing vessels. These challenges explain why other carbon-neutral fuels are expected to be dominant in meeting future emission targets.publishedVersio