Application of 3D Roughness Parameters for Wear Intensity Calculations

In this paper, calculations of 3D parameter Vm (material volume) of surfaces with irregular roughness and comparison with experimental data were performed, with further application of this parameter in calculations of wear intensity. First, using Mountains Map software for profilometric measurements, 3D roughness processing and determination of material volume Vm at specific relative levels γ were performed. The next step was an additional analysis of the distribution of surface ordinates using a theoretical and experimental Laplace function. The given check confirmed that for mostly surfaces with irregular roughness the ordinate distribution corresponds to the normal Gaussian distribution law, but in cases when the asymmetry of the ordinate distribution function goes outside the permissible limits (|∆Ssk|> 10%), errors> 10 % occur. On this basis, the mathematical formula of the material volume Vm was derived, and the obtained calculations were compared with the measured values. The results showed that the calculated values of the parameter Vm were very close to the experimental data (|∆Vm|<10 %), while at the relative level γ=+3, errors occurred that was related to the deviation from the normal distribution law. It was concluded that the given parameter could be used in the calculations of linear wear intensity, knowing the relative level γ.

pyPI (v1.3): Tropical Cyclone Potential Intensity Calculations in Python

Potential intensity (PI) is the maximum speed limit of a tropical cyclone found by modeling the storm as a thermal heat engine. Because there are significant correlations between PI and actual storm wind speeds, PI is a useful diagnostic for evaluating or predicting tropical cyclone intensity climatology and variability. Previous studies have calculated PI given a set of atmospheric and oceanographic conditions, but although a PI algorithm – originally developed by Kerry Emanuel – is in widespread use, it remains under-documented. The Tropical Cyclone Potential Intensity Calculations in Python (pyPI, v1.3) package develops the PI algorithm in Python and for the first time details the full background and algorithm (line by line) used to compute tropical cyclone potential intensity constrained by thermodynamics. The pyPI package (1) provides a freely available, flexible, validated Python PI algorithm, (2) carefully documents the PI algorithm and its Python implementation, and (3) demonstrates and encourages the use of PI theory in tropical cyclone analyses. Validation shows pyPI output is nearly identical to the previous potential intensity computation but is an improvement on the algorithm's consistency and handling of missing data. Example calculations with reanalyses data demonstrate pyPI's usefulness in climatological and meteorological research. Planned future improvements will improve on pyPI's assumptions, flexibility, and range of applications and tropical cyclone thermodynamic calculations.

Vibrational Spectra of Zeolite Y as a Function of Ion Exchange

Zeolite Y is one of the earliest known and most widely used synthetic zeolites. Many experimental investigations verify the valuable ion exchange capability of this zeolite. In this study, we assessed the effects of ion exchange on its vibrational spectra. We applied classical lattice dynamics methods for IR and Raman intensity calculations. Computed spectra of optimized zeolite Y structures with different cations were compared with experimental data. The spectra obtained in this study are in agreement with previous experimental and computational studies on zeolites from the faujasite group.

pyPI (v1.3): Tropical Cyclone Potential Intensity Calculations in Python

Potential intensity (PI) is the maximum speed limit of a tropical cyclone found by modeling the storm as a thermal heat engine. Because there are significant correlations between PI and actual storm wind speeds, PI is a useful diagnostic for evaluating or predicting tropical cyclone intensity climatology and variability. Previous studies have calculated PI given a set of atmospheric and oceanographic conditions, but although a PI algorithm – originally developed by Kerry Emanuel – is in widespread use, it remains under-documented. The Tropical Cyclone Potential Intensity Calculations in Python (pyPI, v1.3) package develops the PI algorithm in Python, and for the first time details the full background and algorithm (line-by-line) used to compute tropical cyclone potential intensity constrained by thermodynamics. The pyPI package (1) provides a freely available, flexible, validated Python PI algorithm, (2) carefully documents the PI algorithm and its Python implementation, and (3) demonstrates and encourages the use of PI theory in tropical cyclone analyses. Validation shows pyPI output is nearly identical to the previous potential intensity computation, but is an improvement on the algorithm's consistency and handling of missing data. Example calculations with reanalyses data demonstrate pyPI's usefulness in climatological and meteorological research. Planned future improvements will improve on pyPI's assumptions, flexibility, and range of applications and tropical cyclone thermodynamic calculations.

Calculation of molecular line intensity in stellar atmospheres

Molecular line intensity calculations are not a straightforward task. We present a description of the basics for including molecular lines in synthetic spectra and of the input data needed. We aim both at describing ways in which molecular lines are computed in the context of photospheres of F–G–K stars, and to present a new online available version of our code for spectrum synthesis of cool stars. We apply calculations to molecular bands in the ultraviolet, visible, and near-infrared main features, and comparisons with spectra of reference stars are shown. We provide user-friendly tools for the free use of the code Pfant. The code is available at http://trevisanj.github.io/PFANT.

Structural and dielectric studies of Mg2+ substituted Ni–Zn ferrite

Polycrystalline ferrites having the chemical formula Ni0.65−xZn0.35MgxFe2O4 (0 ⩽ x ⩽ 0.2) were prepared by solid state reaction route in steps of x = 0.04. The effect of incorporation of diamagnetic divalent magnesium at expense of nickel on the structural properties of these ferrites has been studied. The proposed cation distribution was derived from theoretical X-ray diffraction intensity calculations. These intensity calculations were done by varying the concentration of magnesium ions over two sites in the lattice. For a certain amount of magnesium concentration, the calculated and observed X-ray diffraction intensities were found to be in good agreement. Site occupancy of divalent diamagnetic magnesium was established from this cation distribution. The octahedral environment facilitates magnesium to enter the B-site at about 95 % and the remaining 5 % occupy tetrahedral sites (A-sites). The movements of cations between tetrahedral and octahedral sites as a result of magnesium substitution were discussed in the view of structural parameters, such as tetrahedral and octahedral bond lengths, cation-cation and cation-anion distances, bond angles and hopping lengths, which were calculated using experimental lattice constants and oxygen parameters. All structural parameters showed slight deviations from ideal values. Among all magnesium substituted samples, the ones with x = 0.12 exhibited insignificant variation in view of structural properties. Dielectric measurements were conducted at a standard frequency of 1 kHz. Large values of the recorded dielectric constants displayed typical characteristics of bulk ferrites. Both dielectric constant and loss values showed mixed variations, attributed to the loss of zinc ions during the sintering process.