Hierarchically porous, anisotropic, and green carbon aerogels (CAs) prepared from second most abundant and underutilized biopolymer lignin is used together with biobased epoxy resin to prepare green composite materials with superior mechanical properties. Green and facile preparation route involving ice-templating, lyophilization followed by carbonization was followed for the preparation of CAs. Ice-templating cooling rate is an important parameter in determining the porous structure of the CAs and by choosing a slower cooling rate bigger macropores can be achieved which facilitate the capillary impregnation of the epoxy resin through the CA structure. Hence in this study a cooling rate of 5 K/min was used and the CAs were prepared at 1000 °C from lignin/CNF suspensions containing 3, 5 and 7 wt% of total solid contents. Composites prepared using these CAs as reinforcements showed interesting morphologies which were analyzed using scanning electron microscopy and X-Ray microtomography. Prepared composites contained a mass fraction of 5–9 wt% of CAs. Composites showed remarkable 72 % higher dynamic mechanical properties compared to neat epoxy. Thus, this study introduces new synthesis strategy for carbon composites with completely biobased anisotropic CAs as oriented and strong reinforcements.

Despite the significance of snow in various cryospheric, polar, and construction contexts, more comprehensive studies are required on its mechanical properties. In recent years, the utilization of μ CT has yielded valuable insights into snow analysis. Our objective is to establish a methodology for mapping density-dependent material properties for dry manufactured snow within the density range of 400–600 kg/m 3 utilizing μ CT imaging and step-wise, quasi-static, mechanical loading. We also aim to investigate the variations in the structural parameters of snow during loading. The three-dimensional (3D) structure of snow is captured using μ CT with 801 projections at the beginning of the experiments and at the end of each loading step. The sample is compressed at a temperature of − 18 o C using a constant rate of deformation (0.2 mm/min) in multiple steps. The relative density of the snow is determined at each load step using binary image segmentation. It varies from 0.44 in the beginning to nearly 0.65 at the end of the loading, which corresponds to a density range of 400–600 kg/m 3 . The estimated modulus and viscosity terms, obtained from the Burger’s model, show an increasing trend with density. The values of the Maxwell and Kelvin–Voigt moduli were found to range from 60 to 320 MPa and from 6 to 40 MPa, respectively. Meanwhile, the viscosity values for the Maxwell and Kelvin–Voigt models varied from 0.4 to 3.5 GPa-s, and 0.3–3.2 GPa-s, respectively, within the considered density range. In addition, Digital Volume Correlation (DVC) was used to calculate the full-field strain distribution in the specimen at each load step. The image analysis results show that, the particle size and specific surface area (SSA) do not change significantly within the studied range of loading and densities, while the sphericity of the particles is increased. The grain diameter ranges from approximately 100 μ m to nearly 400 μ m, with a mode of nearly 200 μ m. The methodology presented in this study opens up a path for an extensive statistical analysis of the material properties by experimenting more snow samples.

The mechanical properties of natural snow play a crucial role in understanding glaciers, avalanches, polar regions, and snow-related constructions. Research has concentrated on how the mechanical properties of snow vary, primarily with its density; the integration of cutting-edge techniques like micro-tomography with traditional loading methods can enhance our comprehension of these properties in natural snow. This study employs CT imaging and uniaxial compression tests, along with the Digital Volume Correlation (DVC) to investigate the density-dependent material properties of natural snow. The data from two snow samples, one initially non-compressed (test 1) and the other initially compressed (test 2), were fed into Burger’s viscoelastic model to estimate the material properties. CT imaging with 801 projections captures the three-dimensional structure of the snow initially and after each loading step at -18C, using a constant deformation rate (0.2 mm/min). The relative density of the snow, ranging from 0.175 to 0.39 (equivalent to 160–360 kg/m), is determined at each load step through binary image segmentation. Modulus and viscosity terms, estimated from Burger’s model, exhibit a density-dependent increase. Maxwell and Kelvin–Voigt moduli range from 0.5 to 14 MPa and 0.1 to 0.8 MPa, respectively. Viscosity values for the Maxwell and Kelvin–Voigt models vary from 0.2 to 2.9 GPa-s and 0.2 to 2.3 GPa-s within the considered density range, showing an exponent between 3 and 4 when represented as power functions. Initial grain characteristics for tests 1 and 2, obtained through image segmentation, reveal an average Specific Surface Area (SSA) of around 55 1/mm and 40 1/mm, respectively. The full-field strain distribution in the specimen at each load step is calculated using the DVC, highlighting strong strain localization indicative of non-homogeneous behavior in natural snow. These findings not only contribute to our understanding of natural snow mechanics but also hold implications for applications in fields such as glacier dynamics and avalanche prediction.

This study focuses on utilizing image techniques for river velocity measurement, with a specific emphasis onnatural surface floating patterns. Employing a multi-camera system, we conducted 3D measurements on riversurfaces, including surface velocity and water surface reconstruction. A pattern-based tracking approach hasbeen adopted to improve the performance of image measurements on different types of natural floating tracers.The study employs the following approaches: 3D Lagrangian Pattern Tracking Velocimetry (3D-LPTV), 2DLagrangian Pattern Velocimetry (2D- LPTV), and Large-scale Particle Image Velocimetry (LSPIV), for surfacevelocity estimation. The outcomes revealed that all three approaches yielded consistent results in terms ofaveraged velocity. However, the LSPIV method produced about two times higher uncertainty in measured velocitiescompared to the other methods. A strategy to assess the quality of river surface patterns in velocityestimation is presented. Specifically, the sum of squared interrogation area intensity gradient (SSIAIG) was foundto be strongly correlated with measurement uncertainty. Additionally, a term related to the peak sidelobe ratio(PSR) of the cross-correlation map was found as an effective constraint, ensuring the image-tracking processachieves high reliability. The precision of measurements increases corresponding to the increase of image intensitygradient and PSR.

The influence of quartz bed particle surface morphology on the bed particle layer and crack layer formation process in fluidized bed combustion of woody biomass was investigated in this work. Bed material samples were collected at different sampling times from the startup with a fresh bed in industrial scale bubbling fluidized bed (BFB) and circulating fluidized bed (CFB) boilers, both utilizing woody biomass. X-ray microtomography (XMT) and scanning electron microscopy coupled with energy dispersive spectroscopy (SEM/EDS) were employed to characterize bed particle layers and crack layers in the samples. Results showed that there is a noticeable difference between the bed layer characteristics over the so-called “concave” and “convex”-shaped morphologies on the bed particle surface with respect to layer formation. The concave areas are mainly covered with a thin inner layer, whilst the convex display a comparably thick inner layer and an outer layer. In addition, 3D images of the particles revealed that the crack layers mainly originate from concave areas where the particle is less protected by an outer bed particle layer in conjunction with cracks in the inner layer.

Flow field measurements around cross-country skiers (xc skiers) are lacking in the literature to date. The aim was therefore to investigate the possibility of using particle tracking velocimetry for visualization and measurement of the flow field around xc skiers roller skiing on a treadmill in a wind tunnel. The airflow was seeded with neutrally buoyant helium-filled soap bubbles as tracer particles, following the flow without affecting it. As illumination, two different approaches were tested: first, a laser in the cameras’ line of sight (sagittal plane), then an LED unit directed vertically in a narrow slice, clearly limiting the depth of the measurement volume in the cameras’ line of sight. The flow field was studied at various speeds (3-7 m/s) around a single skier as well as around two skiers in line with the streaming airflow. It was found that the experimental approach has the potential to provide detailed insights, both qualitatively and quantitatively, into the flow field dynamics. The main challenges regarding setup, illumination, seeding, and cameras were identified, and possible improvements to streamline the experimental methodology were discussed. 

Bed particle layer and crack layer characteristics at different ages were studied for quartz and K-feldspar bed particles from a 30 MWth bubbling fluidized bed and a 90 MWth circulating fluidized bed, both using woody biomass as fuel. X-ray microtomography (XMT) was utilized to determine the bed particle layer distribution on the bed particles' surface. For each bed particle type, the average bed particle layer thickness as well as average volume fractions of the bed particle layer and crack layers to the entire bed particle volume were determined at three different bed particle ages by utilizing XMT analysis. Comparison of the two different bed particle types showed that K-feldspar retains a thinner bed particle layer in both conversion processes compared to quartz. Crack layers were observed extensively in quartz bed particles to the extent of 19.3 vol% and 32.1 vol% after 13 days in the BFB and the CFB, respectively, which could cause deposition of the bed particle fragments. On the contrary, K-feldspar has almost no tendency toward forming crack layers.

Hydraulic modelling can be an important tool to assess ecological status of rivers and to evaluate where and how measures should be implemented to maximize their impact. This is becoming increasingly important in regulated rivers since hydropower’s ability to balance intermittent electricity sources such as wind- and solar power is resulting in more frequent starts and stops of the power plants, which in turn is affecting the local environmental conditions. The resulting flow fields from the modelling can, for instance, be used to classify biologically important areas in rivers. Several relevant flow parameters can be predicted and applied, e.g., depth and water velocities can be used to estimate habitat for specific fish species or the variation in water levels can be used to evaluate the risk of stranding for fish in different life stages. This work specifically involves numerical modelling of a heavily regulated reach in the Lule River in northern Sweden. Models are created in 1D, 2D and 3D to show strengths and weaknesses in the different modelling techniques. To ensure that the models capture reality, measurements of water levels and temperatures in the reach are performed using pressure/temperature loggers for validation purposes. River velocities are also measured with an Acoustic Doppler Current Profiler which are mainly used to validate the 3D model. The results derived using the different modelling methods are all shown to be useful depending on relevant application.

Hierarchically porous carbon aerogels (CAs) were synthesized by following a green, facile preparation route involving ice-templating and lyophilization followed by carbonization. For the first time, we report CAs prepared with a cooling rate of 7.5 K/min, demonstrating a very high specific surface area (SSA) of 1260 m2 g–1 without any physical or chemical activation steps, and the electrode prepared using the latter aerogel showed superior electrochemical performance with a specific capacitance of 410 F g–1 at 2 m V s–1 with a cyclic stability of 94% after 4500 charge–discharge cycles. The effects of the ice-templating cooling rate and the solid content of lignin and cellulose nanofibers (CNFs) in the suspension on the structure and electrochemical performance of the CAs were investigated. The ice-templating process and the cooling rate were found to have a large effect on the generation of the nanoporous structure and the specific surface area of carbon aerogels, while the solid content of the lignin-nanocellulose suspension showed negligible effects. When assembled as a supercapacitor (SC), a remarkable specific capacitance of 240 F g–1 at 0.1 A g–1 was achieved. The relaxation time constant for the prepared SC was 1.3 s, which shows the fast response of these SCs. In addition, an energy density of 4.3 Wh kg–1 was also obtained at a power density of 500 W kg–1. Thus, this study opens new perspectives for the preparation of green, environment-friendly, free-standing, high-performance CA electrodes for future energy storage applications.