Accelerated high-cycle phase field fatigue predictions

Phase field fracture models have seen widespread application in the last decade. Among these applications, its use to model the evolution of fatigue cracks has attracted particular interest, as fatigue damage behaviour can be predicted for arbitrary loading histories, dimensions and complexity of the cracking phenomena at play. However, while cycle-by-cycle calculations are remarkably flexible, they are also computationally expensive, hindering the applicability of phase field fatigue models for technologically-relevant problems. In this work, a computational framework for accelerating phase field fatigue calculations is presented. Two novel acceleration strategies are proposed, which can be used in tandem and together with other existing acceleration schemes from the literature. The computational performance of the proposed methods is documented through a series of 2D and 3D boundary value problems, highlighting the robustness and efficiency of the framework even in complex fatigue problems. The observed reduction in computation time using both of the proposed methods in tandem is shown to reach a speed-up factor of 32, with a scaling trend enabling even greater reductions in problems with more load cycles

Mean exit times from submanifolds with bounded mean curvature

We show that submanifolds with infinite mean exit time can not be isometrically and minimally immersed into cylinders, horocylinders, cones, and wedges of some product spaces. Our approach is not based on the weak maximum principle at infinity, and thus it permits us to generalize previous results concerning non-immersibility of stochastically complete submanifolds. We also produce estimates for the complete tower of moments for submanifolds with small mean curvature immersed into cylinders

Hygrothermal Assessment of Internally Insulation for Historic Half-Timbered Outer Wall

Internal insulation is generally considered a risky solution regarding the risk of moisture-induced damage such as mould growth and wood decay, and this might particularly be problematic for half-timbered buildings due to the extensive use of wooden elements in the walls. These would be particularly exposed in the case of internal insulation. This study investigates the hygrothermal performance and the theoretical risk of mould growth in critical locations in half-timbered walls fitted with internal insulation through 2D-dimensional hygrothermal simulations. Sev-eral types of insulation systems were investigated, including diffusion-open and diffusion-tight systems. Moreover, the effect of exterior plaster to reduce rain in-trusion was investigated. The results showed potentially critical relative humidity levels at several places inside the half-timbered walls, mainly when using diffu-sion-tight systems. However, the combination with exterior plaster positively af-fected the hygrothermal performance. The direction of the wall is important, as wind-driven rain influences the performance more than the possibility of drying out inwards

Microgel-Extracellular Matrix Composite Support for the Embedded 3D Printing of Human Neural Constructs

The embedded 3D printing of cells inside a granular support medium has emerged in the past decade as a powerful approach for the freeform biofabrication of soft tissue constructs. However, granular gel formulations have been restricted to a limited number of biomaterials that allow for the cost-effective generation of large amounts of hydrogel microparticles. Therefore, granular gel support media have generally lacked the cell-adhesive and cell-instructive functions found in the native extracellular matrix (ECM). To address this, a methodology has been developed for the generation of self-healing annealable particle-extracellular matrix (SHAPE) composites. SHAPE composites consist of a granular phase (microgels) and a continuous phase (viscous ECM solution) that, together, allow for both programmable high-fidelity printing and an adjustable biofunctional extracellular environment. This work describes how the developed methodology can be utilized for the precise biofabrication of human neural constructs. First, alginate microparticles, which serve as the granular component in the SHAPE composites, are fabricated and combined with a collagen-based continuous component. Then, human neural stem cells are printed inside the support material, followed by the annealing of the support. The printed constructs can be maintained for weeks to allow the differentiation of the printed cells into neurons. Simultaneously, the collagen continuous phase allows for axonal outgrowth and the interconnection of regions. Finally, this works provides information on how to perform live-cell fluorescence imaging and immunocytochemistry to characterize the 3D-printed human neural constructs

Feasibility analysis of clean utilization of kitchen waste oil and lignite by co-fermentation treatment

In order to improve the efficiency of biomethane production through lignite anaerobic fermentation and perform the treatment and application of kitchen waste oil (KWO), different KWO to lignite ratios were used for combined anaerobic fermentation of biomethane. Biogas production characteristics, fermentation broth, and solid residue utilization properties of co-fermentation were analyzed using liquid fatty acid, thermogravimetric (TG), and combustion flue gas tests. The experimental results show that the co-anaerobic fermentation of KWO and lignite can improve the biogenic methane production, and the ratio of the two will also affect the biogenic methane production. Among them, the biogenic methane production by the co-anaerobic fermentation of 1.2 g KWO and 20 g of lignite is the largest, which is 377.86% higher than that by the anaerobic fermentation of single lignite. According to the three-dimensional fluorescence spectrum analysis, the fermentation substrate with the highest biogenic methane production contains more fulvic acid, tryptophan, lysine, phenol hydroxyl, ketone carbonyl, carbonyl, and other groups. In the change of fatty acid content before and after anaerobic fermentation, the content of palmitic acid, stearic acid, oleic acid, and other non-degradable fatty acids contained in KWO significantly decreased, and the volatile fatty acids significantly increased. After anaerobic fermentation, the volatilization analysis temperature, ignition point, and combustion temperature of residual coal are advanced, and the combustion is more stable. At the same time, the emission of combustion pollution gas of residual coal after fermentation is significantly reduced, which is conducive to the clean utilization of lignite

Constituents of Human Particle, Microbial and Chemical Emissions and Exposures in Indoor Environments: An experimental overview

This study presents the preliminary findings on the human contribution to particle, microbe and gas-phase chemical burden of indoor air, as well as the effect of ozone on malondialdehyde (MDA) levels, a biomarker of lipid peroxidation

Validation of four resistivity mixing models on field time lapse geoelectrical measurements from fine-grained soil undergoing freeze-thaw cycles

Resistivity mixing models relate porosity, phase composition and specific resistivities of ground materials to their bulk (effective) electrical properties. These models were typically derived for calculating hydrocarbon saturation from geophysical logs. In permafrost monitoring applications, they have been used to link ground electrical response to its phase composition, with focus on unfrozen water vs. ice content, and to derive changes in ground ice content from repeated resistivity acquisitions. Such quantitative interpretations rely on validity of the mixing models in a context different from the one they were derived in. To increase the reliability of the permafrost forecasts that are based on repeated resistivity surveys, we undertook validation of four selected resistivity mixing model formulations: i) the original Archie's law, ii) the Archie's law with an ice-content dependent cementation exponent m (Archie-M), iii) a modification of the Archie's law for multiple conducting phases (Archie-N), and iv) the geometric mean model (GM). The model application context was permafrost monitoring and fate forecasting on natural fine-grained soil undergoing cycles of freezing and thawing, based on indirect (geophysical), in-situ time-lapse resistivity measurements. The purpose of the calibrated resistivity models was to derive the phase composition of the ground from in-situ resistivity measurements, with acceptable quantitative reliability, notably with respect to the amount and changes of ice and water content. In our validation framework, daily temperature-dependent soil phase distribution was converted into an effective resistivity distribution of the ground using each of the four resistivity mixing models. From the effective resistivity model, an apparent resistivity response was forward calculated and compared to time-lapse field apparent resistivity measurements from a permafrost monitoring field site. The performance metrics were i) the root mean square error between the forward-calculated and field-measured apparent resistivities throughout the freeze-thaw season, ii) the percentage of field apparent resistivity data explained by each resistivity model, and iii) the plausibility of the calibrated model parameter estimates. We found that despite different current conducting mechanisms involved in each of the resistivity mixing model formulations, the quantitative performance of the four evaluated models was very similar. The four models typically reproduced the field-measured resistivity variations within one to two standard deviations (STD) of the field measurements, depending on the time of the year and depth in the soil profile. In the active layer, the Archie-M model most consistently reproduced the field data within 1 STD throughout the freezing and frozen periods of the year (September – May). Meanwhile, the GM best matched the actual values of resistivities during freezing. The GM also recovered porosities of the three model layers close to the true values measured on borehole samples. All the tested models were challenged by accurately simulating the thawing period – overestimating resistivities in the temperature range from −5 °C to −2 °C and underestimating them between −2 °C and thawing point. Consequently, the choice between the models should depend on the specifics of a particular application, such as available calibration data, desired parameters or ground properties to resolve, sensitivity of the modeling framework etc. An application-specific validation of several resistivity mixing models and quantification of performance of the chosen resistivity model may be called for. Additionally, the possibility of using different mixing model and water content parameterizations should be investigated, to adequately address complex ground resistivity structures and phase change processes typical of permafrost ground.</p

Life cycle assessment of lithium ion battery from water-based manufacturing for electric vehicles

Lithium ion batteries produced using the water-based manufacturing processes, as a greener technology, have great potential to be used in future electric vehicles (EVs). A cradle-to-grave life cycle assessment model configured for actual EV applications has been developed for the water-based manufactured lithium nickel manganese cobalt oxide (NMC)-graphite battery pack. Experimental and modeling results cover raw material extraction and processing, water-based battery manufacturing processes, battery usage during EV driving, and direct recycling at End-of-Life. The ReCiPe method is employed to investigate the environmental impacts of the water-based battery pack and benchmark it against the impacts of a conventional N-methyl-2-pyrrolidone (NMP)-based battery pack with the same mass. The cradle-to-grave energy consumption of the studied water-based battery pack is 0.976 MJ/km EV driving, equivalent to a 4.5% reduction over the NMP-based battery pack. Aside from energy usage, we find reductions in all environmental impact categories (3.0%∼85%) compared to the conventional battery pack

Does the outside view affect the luminous and thermal perception? A preliminary study

This study explores whether differences in urban views affect thermal and visual perception. Experimental sessions were conducted in two identical office rooms with controlled temperatures, naturally lit but with different window views. Split into two groups by temperature (between subjects), the participants were exposed to two window views (within subjects). The results of this preliminary study indicate that the thermal and visual perception were not significantly different between the window views

Testing of a passive foam fractionator prototype in a commercial recirculating trout farm

Foam fractionation has emerged as a technical solution to reduce the build-up of microparticles and dissolved organic matter in recirculating aquaculture systems (RAS). However, commercial application in freshwater RAS is challenging and expensive. In the present study, a simple, low-cost passive foam fractionation (PFF) prototype was developed and tested under commercial conditions. The prototype was tested in a Model Trout Farm (MTF) in three different production raceways during winter and spring to assess the operation and removal potential. A number of different water quality parameters, including organic matter, particles, bacterial activity, and phosphorus were examined in the system water and in the removed foamate. Overall, the PFF prototype removed particles as well as particulate and dissolved organic matter, reduced the amount of bacteria and total phosphorus in the water, regardless of sampling time and place. By utilizing the existing airlifts in the MTF, the associated cost of construction and operation was kept low. Overall, the results demonstrate that the passive foam fractionation has the potential to help address some of aquaculture’s pressing issues in a cost effective manner