Physics-informed deep learning for one-dimensional consolidation

Neural networks with physical governing equations as constraints have recently created a new trend in machine learning research.In this context,a review of related research is first presented and discussed.The potential offered by such physics-informed deep learning models for computations in geomechanics is demonstrated by application to one-dimensional(1D)consolidation.The governing equation for 1D problems is applied as a constraint in the deep learning model.The deep learning model relies on automatic differentiation for applying the governing equation as a constraint,based on the mathematical approximations established by the neural network.The total loss is measured as a combination of the training loss(based on analytical and model predicted solutions)and the constraint loss(a requirement to satisfy the governing equation).Two classes of problems are considered:forward and inverse problems.The forward problems demonstrate the performance of a physically constrained neural network model in predicting solutions for 1D consolidation problems.Inverse problems show prediction of the coefficient of consolidation.Terzaghi’s problem,with varying boundary conditions,is used as a numerical example and the deep learning model shows a remarkable performance in both the forward and inverse problems.While the application demonstrated here is a simple 1D consolidation problem,such a deep learning model integrated with a physical law has significant implications for use in,such as,faster realtime numerical prediction for digital twins,numerical model reproducibility and constitutive model parameter optimization.     

Hierarchical approach for fatigue cracking performance evaluation in asphalt pavements

In this paper, a hierarchical approach is proposed for the evaluation of fatigue cracking in asphalt concrete pavements considering three different levels of complexities in the representation of the material behaviour, design parameters characterization and the determination of the pavement response as well as damage computation. Based on the developed hierarchical approach, three damage computation levels are identified and proposed. The levels of fatigue damage analysis provides pavement engineers a variety of tools that can be used for pavement analysis depending on the availability of data, required level of prediction accuracy and computational power at their disposal. The hierarchical approach also provides a systematic approach for the understanding of the fundamental mechanisms of pavement deterioration, the elimination of the empiricism associated with pavement design today and the transition towards the use of sound principles of mechanics in pavement analysis and design.     

SnO<Subscript>2</Subscript>-core/SiO<Subscript>x</Subscript>-shell coaxial whiskers with a needle-like morphology

Needle-shaped structures of tin oxide (SnO₂) were coated with a shell layer of SiO_x via a sputtering method. The diameters of the SiO_x-coated structures gradually became thinner, leading to the formation of sharp tips. The whiskers consisted of a crystalline SnO₂ core surrounded by an amorphous SiO_x shell. The photoluminescence (PL) spectrum with a Gaussian fitting exhibited yellow-green and orange light emission bands, and the overall shape and intensity of the PL spectrum were not changed by the SiO_xcoating. The results of this study suggest that sputtering can be employed to achieve the layered growth of shell layers on a variety of nanostructures.     

Habitat quality–physicochemical water quality–littoral macroinvertebrate community nexus in Lugo Lake (Ethiopia): Priorities for sustainable water resources management

The integration of water quality characteristics with habplot-based habitat quality assessment score (HabQA) has received little attention in ecological quality assessment studies. This study investigated the macroinvertebrate community structure in relation with lake habitat quality and physicochemical water quality variables in Lugo Lake (Ethiopia). Twelve sampling sites (eight agricultural and four recreational) were included. The variation among macroinvertebrates data was significantly explained by HabQA score and soluble reactive phosphorus. The study revealed the greater importance of habitat quality characteristics in comparison with the other conventional physicochemical characteristics on macroinvertebrate community structure. We strongly recommend the use of HabQA system while studying macroinvertebrate community structure for a deeper understanding of the environmental functioning of tropical lakes. The results suggested the need to apply integrated and sustainable protection and management of the lake catchment (including wetlands) to enhance the ecological integrity and hence biodiversity of lakes.     

Predicting Acute Renal Failure after Cardiac Surgery: Validation and Re‐definition of a Risk‐Stratification Algorithm

Background:  Acute renal failure (ARF) after cardiac surgery is associated with significant morbidity and mortality, irrespective of the need for dialysis. Previous studies have attempted to identify predictors of ARF and develop risk stratification algorithms. This study aims to validate the algorithm in an independent cohort of patients that includes a significant proportion of female and black patients and compares two different definitions of renal outcome.
Methods:  A large single center cardiac surgery database was examined (n, 24,660; 1993–2000) which included 29.9% females and 3.7% black patients. Post‐operative ARF was defined as: a) ARF requiring dialysis, b) > 50% reduction in creatinine clearance relative to baseline or requiring dialysis. Clinical variables related to baseline renal function and cardiovascular disease were used in recursive partitioning analysis for both outcome definitions. Chi‐square goodness of fit analysis was performed to validate the algorithm.
Results:  The frequency of post‐operative ARF requiring dialysis ranged between 0.5 and 15.5% based on the risk categories with the area under the receiver operating characteristic (ROC) curve of 0.78. Using the more inclusive definition of ARF, the frequency was significantly higher ranging from 2.6 to 25%(P < 0.001) with an area under ROC curve of 0.65.
Conclusions:  The renal risk stratification algorithm is valid in predicting post‐operative ARF in an independent cohort of patients, well represented by differences in gender and race. Since the need for dialysis remains subjective, a more objective and inclusive definition of ARF may help in identifying a larger number of patients 'at‐risk'.     

The effect of diet changes and food loss reduction in reducing the water footprint of an average American

ABSTRACT

We analyzed the consumptive water reduction of diet shifting along with food waste reductions in the case of the United States. We find that a dietary shift to healthy diet will not always lead to reduced water footprint. Dietary shifts to vegan and vegetarian diets provide larger reduction in the consumptive water footprint. Reducing food loss and waste produced the largest potential water footprint reduction in our analysis of the US food system. Our findings suggest that a combination of measures that include dietary shift, reducing caloric intake, and reducing food waste result in a significant decline in water footprint.     

Alcohol Determination in Distilled Alcoholic Beverages by Liquid Phase Fourier Transform Mid-Infrared and Near-Infrared Spectrophotometries

Fourier transform mid-infrared spectrophotometry (FT-MIR), 1180–950 cm^?1, and near-infrared spectrophotometry (NIR), 1720–1660 nm, have been used complementarily for the direct determination of ethanol and methanol in distilled alcoholic beverages. In mid-infrared ethanol and methanol identified separately, hence, it has been used to confirm the absence or presence of methanol. In the absence of methanol, both were used to determine the alcoholic strength independently; however, near-infrared was used without diluting the samples. Ethanol and methanol contents were evaluated using the calibration curves established by a plot of peak height or peak area versus concentration % (w/w). The linearity range for ethanol was up to 15 and 50 % (w/w) for mid- and near-infrared, respectively. The developed methods are simple, fast, precise, and accurate. Moreover, the results obtained were in excellent agreement with the results obtained from gas chromatographic measurements. No sample preparation was required at all, and in all samples, methanol was not detected.     

Using a silanized silica nanofiller to reduce excessive amount of rubber curatives in styrene‐butadiene rubber

In recent years, the rubber industry has come under pressure to improve health and safety at work, minimize damage to the environment, reduce costs, and increase competitiveness. Rubber compounds contain additives including curing chemicals, which are hazardous and harmful. Reducing their use or eliminating them altogether will be beneficial to rubber compounders and manufacturers of rubber articles. A styrene‐butadiene rubber (SBR) was cured and reinforced with a high loading of precipitated amorphous white silica nanofiller. The silica surfaces were pretreated with bis(3‐triethoxysilylpropyl) tetrasulfide (TESPT), which is a sulfur‐bearing bifunctional organosilane to chemically adhere silica to the rubber. The chemical bonding between the filler and rubber was optimized via the tetrasulfane groups of TESPT by adding accelerator and activator. The rubbers were subsequently cured and their hardness, tensile strength, elongation at break, stored energy density at break, tearing energy, tensile modulus, Young's modulus, and bound rubber content were measured. This study showed that using the filler in combination with a sulfur‐donor accelerator was the most efficient method for curing and reinforcing the rubber. This led to a significant reduction in the use of the curing chemicals, a faster curing cycle, and very good mechanical properties for the rubber vulcanizate. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

ZnO sputter coating on SnO2 nanowires: Effects of thin coating and subsequent thermal annealing

The structural and optical properties of SnO₂–ZnO core–shell nanowires were studied and the effects of thermal annealing were investigated. As-prepared SnO₂–ZnO core–shell nanowires exhibited a smooth and continuous shell layer along the nanowire, with a thickness in the range of 5–10 nm. While the thin ZnO shell layer disappeared after annealing at 800 °C, this did not occur after annealing at 600 °C. The as-fabricated SnO₂–ZnO core–shell nanowires exhibited yellow emission, presumably from the core SnO₂ nanowires. The UV emission from ZnO shell layer was obtained by annealing at 600 °C, whereas it was removed by annealing at 800 °C.