Evaluating Simplifications of Subsurface Process Representations for Field-scale Permafrost Hydrology Models

Permafrost degradation within a warming climate poses a significant environmental threat through both the permafrost carbon feedback and damage to human communities and infrastructure. Understanding this threat relies on better understanding and numerical representation of thermo-hydrological permafrost processes, and the subsequent accurate prediction of permafrost dynamics. All models include simplified assumptions, implying a tradeoff between model complexity and prediction accuracy. The main purpose of this work is to investigate this tradeoff when applying the following commonly made assumptions: (1) assuming equal density of ice and liquid water in frozen soil; (2) neglecting the effect of cryosuction in unsaturated freezing soil; and (3) neglecting advective heat transport during soil freezing and thaw. This study designed a set of 62 numerical experiments using the Advanced Terrestrial Simulator (ATS v1.2) to evaluate the effects of these choices on permafrost hydrological outputs, including both integrated and pointwise quantities. Simulations were conducted under different climate conditions and soil properties from three different sites in both column- and hillslope-scale configurations. Results showed that amongst the three physical assumptions, soil cryosuction is the most crucial yet commonly ignored process. Neglecting cryosuction, on average, can cause 10 % ~ 20 % error in predicting evaporation, 50 % ~ 60 % error in discharge, 10 % ~ 30 % error in thaw depth, and 10 % ~ 30 % error in soil temperature at 1 m beneath surface. The prediction error for subsurface temperature and water saturation is more obvious at hillslope scales due to the presence of lateral flux. By comparison, using equal ice-liquid density has a minor impact on most hydrological variables, but significantly affects soil water saturation with an averaged 5 % ~ 15 % error. Neglecting advective heat transport presents the least error, 5 % or even much lower, in most variables for a general Arctic tundra system, and can decrease the simulation time at hillslope scales by 40 % ~ 80 %. By challenging these commonly made assumptions, this work provides permafrost hydrology modelers important context for better choosing the appropriate process representation for a given modeling experiment.

Vortex Flow on the Surface Generated by the Onset of a Buoyancy-Induced Non-Boussinesq Convection in the Bulk of a Normal Liquid Helium

The onset of the Rayleigh–Benard convection (RBC) in a heated from above normal He-I layer in a cylindrical vessel in the temperature range Tλ < T ≤ Tm (RBC in non-Oberbeck–Boussinesq approximation) is attended by the emergence of a number of vortices on the free liquid surface. Here, Tλ = 2.1768 K is the temperature of the superfluid He-II–normal He-I phase transition, and the liquid density passes through a well-pronounced maximum at Tm ≈ Tλ + 6 mK. The inner vessel diameter was D = 12.4 cm, and the helium layer thickness was h ≈ 2.5 cm. The mutual interaction of the vortices between each other and their interaction with turbulent structures appeared in the layer volume during the RBC development gave rise to the formation of a vortex dipole (two large-scale vortices) on the surface. Characteristic sizes of the vortices were limited by the vessel diameter. The formation of large-scale vortices with characteristic sizes twice larger than the layer thickness can be attributed to the arising an inverse vortex cascade on the two-dimensional layer surface. Moreover, when the layer temperature exceeds Tm, convective flows in the volume decay. In the absence of the energy pumping from the bulk, the total energy of the vortex system on the surface decreases with time according to a power law.

Development of a microcontroller-based instrument for measuring liquid density

The purpose of this research was to develop a practical tool to measure the density of liquids. This research was a research and development research that referred to the development model of Borg and Gall. The research instrument used was a questionnaire with a 4-Likert scale. Evaluation phase included the assessment of media validator, students’ responses, and laboratory test. The product quality data obtained were analyzed using descriptive analysis. The quality of the product based on the analysis of the media expert’s assessment obtained a value of 3.30 which was in very good category. Meanwhile, the results of student responses in the limited-testing obtained a value of 3.30 which showed that they strongly agree with the product’s usability. The test results and questionnaire analysis indicated that the microcontroller-based density determination practicum tool developed was feasible to use. From the experimental results, the density value of water was 0.95 gr/cm3 with a standard deviation of ±0.044 and a relative uncertainty value of 0.22%. The density value for salt water was 1.04 gr/cm3 with a standard deviation of ±0.011, compared with the literature which is 1.10 gr/cm3. Moreover, the density of coconut oil measured was 0.76 gr/cm3 with a standard deviation of ±0.045, while the literature is 0.84.

Liquid Density Prediction of Ethanol/Water, Using Artificial Neural Network

In this work, our objective was to get a reliable model for predicting liquid density ethanol-water and use it again later in modeling the ethanol production process from biomass. Hence, the unreliability of the Peng-Robinson equation of state to predict this property was shown. The average absolute deviation of this prediction is equal to 14.72 %. To have a reliable model, an artificial neural network (ANN) method was followed. Levenberg–Marquardt algorithm is used to choose the optimized ANN structure that has ten neurons in the hidden layer, three neurons in the input layer, and one neuron in the output layer, with a tangent-sigmoid and linear transfer functions, in the hidden and the output layers, respectively. The model training was done using 348 experimental data points from published experiments, realized at different liquid mole fraction range, pressure (0.10 to 10.00MP), and temperature (298.15 K to 476.2 K). The correlation coefficient between the experimental and liquid phase density was 0.9999 for training, validation, and testing the model. Statistical analysis is employed to evaluate the accuracy of the ANN, showing that the average absolute deviation, root mean square, and the Bias are 0.047 %, 0.003 %, and -0.004 %, respectively. So the ANN model gives a good estimation of liquid density, for mixture ethanol/water, with a relative importance of pressure, composition, and temperature equal to 41%, 34 %, and 25 %, respectively.

The Anomalies and Local Structure of Liquid Water from Many-Body Molecular Dynamics Simulations

For the last 50 years, researchers have sought molecular models that can accurately reproduce water’s microscopic structure and thermophysical properties across broad ranges of its complex phase diagram. Herein, molecular dynamics simulations with the many-body MB-pol model are performed to monitor the thermodynamic response functions and local structure of liquid water from the boiling point down to deeply supercooled temperatures at ambient pressure. The isothermal compressibility and isobaric heat capacity show maxima at ~223 K, in excellent agreement with recent experiments, and the liquid density exhibits a minimum at ~208 K. Furthermore, a local tetrahedral arrangement, where each water molecule accepts and donates two hydrogen bonds, is the most probable hydrogen-bonding topology at all temperatures. This work suggests that MB-pol may provide predictive capability for studies of liquid water’s physical properties across broad ranges of thermodynamic states.

Studying Grain Flow Immersion into Liquids of Various Densities Based on the Methods of Experiment Design

Introduction. In addition to grain, a grain heap of rye may contain poisonous ergot sclerotia. Modern grain cleaning machines do not isolate ergot sclerotia in one technological process because of the similarity of physical properties in linear dimensions. Isolation of ergot sclerotia from rye grain in one technological process is possible through the use of aqueous solutions of inorganic salts. The purpose of the study is to determine the optimum elevation of the loading hopper relative to the liquid surface. The data obtained contribute to increasing the quality of the technological process of the machine being developed. Materials and Methods. The paper considers the delivery of rye grain flow from the loading hopper outlet into the liquid by varying the specific grain load, liquid density and the delivery height. To set up the experiments, the experiment design methods have been used. The experimental data have been processed using the statistical package Statgraphics Plus 5.1. Results. The estimation of the effective elevation of the loading hopper outlet relative to the liquid surface when delivering grain flow has been carried out. There have been obtained regression models for the fraction of grains, which did not submerge and rose up to the liquid surface with air bubbles. Discussion and Conclusion. It has been found that the density of the aqueous salt solution has a significant effect on the percentage of grains, which did not submerge and rose up to the liquid surface with air bubbles. The smallest values of at different density of the liquid and specific grain load are achieved at a grain delivery height 56.0 ∙ 10–3 m.

Using an Adjustable Cone Meter to Measure Wet Gas

When the gas flow rate of a well significantly changes, the flow rate can fall below that of the operating range of a traditional fixed size Venturi meter, necessitating the replacement of the original meter with one of a smaller size. However, with an adjustable cone meter, the internal reconfiguration feature allows it to automatically switch from high operating flow range to low operating flow range and there is no requirement to disassemble the meter from the flow line assembly. Adjustable cone meters were designed, developed and tested at the wet-gas flow loop at National Engineering Laboratory in East Kilbride, Scotland. After calibrating the meter with dry nitrogen gas, the meter was tested with increasing amounts of liquid being injected into the flowline, upstream of the meter. The liquid caused the differential pressure measurement on the meter to over-read. Based on the differential pressure measurements under varying flow conditions, algorithms were developed to measure the dry gas and liquid fraction. The data obtained from the tests such as differential pressure, pressure, temperature, liquid density were used to build an over-reading model of the meter and a liquid fraction estimation model based on pressure loss ratio derived from an additional differential pressure measurement. The model was used to not only to quantify the gas and liquid flow rates but also the estimated error in each measurement. The measurements show that the Adjustable Cone meter is able to provide low uncertainty in both dry and wet gas conditions and offers a turndown ratio of up to 54:1 in dry gas conditions. In addition, the automatic adjustment of the meter from high flow to low flow positions avoids the need for manual intervention that involves additional risk and cost.