Database Of Physical Properties Research Articles

Basis Set Requirements of σ-Functionals for Gaussian- and Slater-Type Basis Functions and Comparison with Range-Separated Hybrid and Double Hybrid Functionals.

σ-Functionals belong to the class of Kohn-Sham (KS) correlation functionals based on the adiabatic-connection fluctuation-dissipation theorem and are technically closely related to the random phase approximation (RPA). They have the same computational demand as the latter, with the computational effort of an energy evaluation for both methods being lower than that of a preceding hybrid DFT calculation for typical systems but yield much higher accuracy, reaching chemical accuracy of 1 kcal/mol for quantities such as reactions and transition energies in main group chemistry. In previous work on σ-functionals, rather large Gaussian basis sets have been used. Here, we investigate the actual basis set requirements of σ-functionals and present three setups that employ smaller Gaussian basis sets ranging from quadruple-ζ (QZ) to triple-ζ (TZ) quality and represent a good compromise between accuracy and computational efficiency. Furthermore, we introduce an implementation of σ-functionals based on Slater-type basis sets and present two setups of QZ and TZ quality for this implementation. We test the accuracy of these setups on a large database of various physical properties and types of reactions, as well as equilibrium geometries and vibrational frequencies. As expected, the accuracy of σ-functional calculations becomes somewhat lower with a decreasing basis set size. However, for all setups considered here, calculations with σ-functionals are clearly more accurate than those within the RPA and even more so than those of the conventional KS methods. For the smallest setup using Gaussian-type basis functions and Slater-type basis functions, we introduce a reparametrization that reduces the loss in accuracy due to the basis set error to some extent. A comparison with the range-separated hybrid ωB97X-V and the double hybrid DSD-BLYP-D3 shows that σ functionals outperform in accuracy both of these accurate and, for their class, representative functionals.

CLSoilMaps: A national soil gridded database of physical and hydraulic soil properties for Chile

Spatially explicit soil information is crucial for comprehending and managing many of Earth´s processes related to carbon, water, and other biogeochemical cycles. We introduced a gridded database of soil physical properties and hydraulic parameters at 100 meters spatial resolution. It covers the continental area of Chile and binational basins shared with Argentina for six standardized depths following the specifications of the GlobalSoilMap project. We generated soil maps based on digital soil mapping techniques based on more than 4000 observations, including unpublished data from remote areas. These maps were used as input for the pedotransfer function Rosetta V3 to obtain predictions of soil hydraulic properties, such as field capacity, permanent wilting point, total available water capacity, and other parameters of the water retention curve. The trained models outperformed several other DSM studies applied at the national and regional scale for soil physical properties (nRMSE ranging from 6.93% to 15.7%) and delivered acceptable predictions (nRMSE ranging from 10.4% to 15.6%) for soil hydraulic properties, making them suitable for countless environmental studies.

Effects of High Temperature Tempering on Microstructure and Hardness Distribution on 18Cr2Ni4WA Alloy Steel Heavy-duty Gears: Numerical Simulation and Experiments

In the present work, simulations of gas carburizing heat treatment of heavy-duty gears on a coal-cutting machine fabricated by a 18Cr2Ni4WA alloy steel were carried out by using a finite element method software. The physical property database of the 18Cr2Ni4WA alloy steel was constructed in the software. The effects of the high temperature tempering process on the microstructure and hardness distributions were simulated and studied. The hardness distribution results obtained by simulation are in good agreement with the experimental results, which verifies the accuracy of the simulation. The evolution of the volume fractions of the austenite, martensite, and bainite microstructure after high temperature tempering was simulated, while the change of the retained austenite varying with the number of high temperature tempering was studied. The results show that with the increase of the number of high-temperature tempering, the content of retained austenite in the gear decreases, and it could reduce the surface carbon concentration. The hardness variation, calculated by the Maynier equation through secondary development, is shown to be governed by the joint influence of carbon concentration and microstructure distribution. The hardness distribution from the surface layer to the core is 62HRC-32HRC after the heat treatment process with twice high tempering, which meets the needs of the practical application of the gears.

A comparison of cabbage crop growth parameters and harvest maturity indices under different planting methods, with an emphasis on mechanical harvesting

The predominant method of cabbage harvesting in India is manual labor, which is both time-consuming and physically demanding. However, the introduction of mechanical harvesting could offer a viable solution to this problem. A plant physical properties database is needed before the developing mechanical harvesting system design. In view of this, a study was conducted to examine the effect of planting methods (flat, ridge-furrow and ridge-furrow with plastic mulch) on physical growth and harvesting age of crop and thereby find out the most suitable planting method for mechanical harvesting. For two cabbage cultivars (Syngenta BC-79 and S-996), the effect of planting methods on physical growth parameters (plant height, plant diameter, length of leaf stem, length of stem, stem diameter, head diameter, and head weight) and harvest maturity indices (compactness, specific gravity, total soluble solids, pH, and pattern of wrapper leaves) was studied. The planting methods had shown a significant effect on growth parameters such as plant height (270.56 mm), plant diameter (549.39 mm), stem length (58.61 mm), stem diameter (34.58 mm), head diameter (144.89 mm) and head weight (1.12 kg) at harvest. The maximum number of matured heads (83.66%) was recorded in ridge-furrow with mulch planting. The interaction effect of planting methods and cultivars was found to be non-significant for all physical growth indicators. The findings of this study provide a valuable planting method for cabbage growers from the perspective of mechanical harvesting.

Estimating WEPP Cropland Erodibility Values From Soil Properties

Highlights Very fine sand is the single most important variable for predicting rill and interrill erodibility values. Slope steepness is the most important property for predicting critical shear for rill erosion. Erodibility prediction equations with the best goodness-of-fits have both soil texture and mineralogy terms. Equations to predict erodibility from texture, organic carbon, cation exchange, slope, and taxonomy are proposed. Abstract. In the late 1980s, the USDA Agricultural Research Service, along with other federal agencies and multiple universities, collaborated to develop a new physically based soil erosion model, the Water Erosion Prediction Project (WEPP) Model. The WEPP model was intended to replace the Universal Soil Loss Equation and was to include estimates for upland runoff and erosion, sediment delivery to first order channels, and runoff and sediment routing through a downstream channel network. The WEPP technology estimated erosion from raindrop splash and sheet flow (interrill erosion) and concentrated channel flow (rill erosion). To make these erosion estimates, WEPP required new soil erodibility values for interrill erodibility (Ki). rill erodibility (Kr), and critical shear (𝜏c) for concentrated flow erosion. The WEPP Core team determined that they needed to estimate these three erodibility values from measurable soil properties for a wide range of soil conditions. To develop relationships between WEPP soil erodibility variables and other soil properties, a field study was carried out using rainfall and runoff simulation to measure the three erodibility values for 36 soils. Sites were identified on croplands from Washington to Georgia and Maine to California, USA for erodibility measurement. Concurrently, the USDA Soil Conservation Service (SCS) carried out detailed soil surveys and laboratory analyses for all sites to provide a large database of soil physical, chemical, and engineering properties. Correlation and regression analyses were carried out to develop relationships between SCS measurable soil properties and WEPP soil erodibility values. This article provides a summary of the field procedures, data analyses, and subsequent predictive equations that were developed. The predictive equations that were finalized in the WEPP User Summary used sand, very fine sand, clay, and organic carbon contents to predict cropland soil erodibility, but the Coefficient of Determination (r2) values were 0.55 or less. More complex predictive equations were developed with soil physical, chemical, mineralogical, and geomorphic properties, with r2 values up to 0.81. Most of the better predictive equations included terms for soil texture and clay mineralogy, often with additional chemical properties. A set of simplified erodibility equations using only the readily available properties of soil texture, organic carbon, cation exchange capacity, slope steepness, and taxonomic order were derived for use within the WEPP Model, with r2 values greater than 0.5 for all three equations for estimating soil erodibility from measurable soil properties. Keywords: Critical Shear, Interrill Erodibility, Rill Erodibility, Soil Properties, WEPP.

A gravimetric assessment of the Gotthard Base Tunnel geological model: insights from a novel gravity terrain-adaptation correction and rock physics data

The Gotthard Base Tunnel (GBT) is a 57 km long railway tunnel, constructed in the Central Alps in Switzerland and extending mainly North–South across numerous geological units. We acquired 80 new gravity data points at the surface along the GBT profile and used 77 gravity measurements in the tunnel to test and constrain the shallow crustal, km-scale geological model established during the tunnel construction. To this end, we developed a novel processing scheme, which computes a fully 3D, density-dependent gravity terrain-adaptation correction (TAC), to consistently compare the gravity observations with the 2D geological model structure; the latter converted into a density model. This approach allowed to explore and quantify candidate rock density distributions along the GBT modelled profile in a computationally-efficient manner, and to test whether a reasonable fit can be found without structural modification of the geological model. The tested density data for the various lithologies were compiled from the SAPHYR rock physical property database. The tested models were evaluated both in terms of misfit between observed and synthetic gravity data, and also in terms of correlation between misfit trend and topography of the target profile. The results indicate that the locally sampled densities provide a better fit to the data for the considered lithologies, rather than density data averaged over a wider set of Alpine rock samples for the same lithology. Furthermore, using one homogeneous and constant density value for all the topographic corrections does not provide an optimal fit to the data, which instead confirms density variations along the profile. Structurally, a satisfactory fit could be found without modifying the 2D geological model, which thus can be considered gravimetry-proof. From a more general perspective, the gravity data processing routines and the density-dependent corrections developed in this case study represent a remarkable potential for further high-resolution gravity investigations of geological structures.

Study on the Preparation of GeoWEPP Model Input Data for Erosion Prediction in Cikeruh-Citarik Sub-watershed

Cikeruh-Citarik sub-watershed is a part of the upstream zone of the Citarum watershed which is classified as a watershed with critical conditions in West Java. The change in land use as a side effect of the increasing population causes a degradation of the watershed. Land-use change in a watershed without considering any conservation rules leads to erosion, becoming a watershed criticality indicator. Erosion can be minimized by using a prediction model to predict the amount of erosion that might happen, for the result could help to decide which conservation action is needed in the watershed rehabilitation. GeoWEPP is one of the prediction models that is suitable for predicting the amount of erosion on a watershed scale. This research aims to study the preparation of the input data needed in the GeoWEPP model to predict the amount of erosion, especially in the Cikeruh-Citarik sub-watershed. The methodologies that were used in this research are literature study and field survey. According to the research results, the input data needed for GeoWEPP are DEM (Digital Elevation Model) data of the research area, climate database, soil type and soil physical properties database, land use and landcover data, and bridge files for soil, land cover data, and evapotranspiration calculation.

A database of soil physical properties for the Kansas Mesonet

AbstractThis study developed a comprehensive database of soil physical properties to expand the potential applications of soil moisture observations across the Kansas Mesonet environmental monitoring network. The database comprises 14 site‐ and depth‐specific soil hydraulic properties for 40 stations monitoring soil water content. The measured soil hydraulic properties include sand, clay, and silt contents; bulk density; particle density; total porosity; effective saturation; saturated hydraulic conductivity; and water retention at six matric potentials. The soil database spans eight soil textural classes, with silty clay loam, silt loam, and silty clay soils dominating the fine‐textured soils, and sandy loam and sandy clay loam soils comprising the only coarse‐textured soils. All the measured soil hydraulic properties showed low coefficient of variation (CV ≤10%) within soil textural classes, except for the saturated hydraulic conductivity, which varied from a median of 0.520 ± 308 cm d–1 in the clay soils to 47.1 ± 119 cm d–1 in the sandy loam soils. The uncertainty of the Kansas Mesonet soil water content observations was reduced by at least 29% using laboratory sensor calibration equations instead of the factory default sensor equation. Our soil physical property database offers new prospects to use historical and near real‐time in situ soil water content observations across the Kansas Mesonet for diverse agricultural and hydrological applications, including drought monitoring, wildfire preparedness, and estimating potential drainage and groundwater recharge rates.

MesoSoil v2.0: An updated soil physical property database for the Oklahoma Mesonet

AbstractSoil moisture data from the Oklahoma Mesonet have been used in numerous fields within the Earth sciences, including agriculture, hydrology, and meteorology. Soil matric potentials measured by heat dissipation sensors at Oklahoma Mesonet stations have been converted to soil volumetric water content estimates using soil water retention curve parameters estimated by the Rosetta pedotransfer function. Recently, an improved version of Rosetta, Rosetta3, was released. Informed by this new pedotransfer function and soil sampling at additional locations, an improved version of the Oklahoma Mesonet soil physical property database, MesoSoil v2.0, has been created. This article presents this new soil database, compares soil water retention parameters estimated using Rosetta3 with those derived from the original Rosetta model, and describes the effects of changes in those parameters on estimated volumetric water content. Using the Rosetta3 model led to changes in the estimated water retention parameters, most notably decreases in the parameter α, which is related to the inverse of the air‐entry potential. These changes resulted in volumetric water content estimates that differed from those based on Rosetta1, with mean absolute differences averaging 0.02 cm3 cm–3 across all site‐years and the greatest differences occurring during wet periods. The mean volumetric water content estimated using the Rosetta3 parameters across more than 100 sites was not significantly different from that determined by soil sampling. The updated database is publicly available and may be found here: http://soilphysics.okstate.edu/data.

Udkm1Dsim – a Python toolbox for simulating 1D ultrafast dynamics in condensed matter

The udkm1Dsim toolbox is a collection of Python classes and routines to simulate the thermal, structural, and magnetic dynamics after laser excitation as well as the corresponding X-ray scattering response in one-dimensional samples, such as multilayers. The toolbox provides the capabilities to define arbitrary layered structures on the atomic level including a rich database of element-specific physical properties. The excitation of dynamics is represented by an N-temperature-model which is commonly applied in ultrafast physics. Structural dynamics due to thermal stresses are calculated by a linear-chain model of masses and springs. The implementation of specific magnetic dynamics can be easily accomplished by the user employing a generalized magnetization interface class. The resulting X-ray diffraction response is computed by kinematical or dynamical X-ray theory which can also include polarization-dependent magnetic scattering. The udkm1Dsim toolbox is highly modular and allows for injecting user-defined inputs at any step within the simulation procedure. New version program summaryProgram Title: udkm1DsimCPC Library link to program files:https://doi.org/10.17632/bnzw823v6y.1Developer's repository link:https://github.com/dschick/udkm1DsimCode Ocean capsule:https://codeocean.com/capsule/8131941Licensing provisions: MITProgramming language: PythonJournal reference of previous version: Comput. Phys. Commun. 185 (2) (February 2014) 651–660Does the new version supersede the previous version?: YesReasons for the new version: The toolbox has been ported from MATLAB (MathWorks Inc.) to Python and is based exclusively on free and open-source components. Moreover, new features have been added that allow for a broader applicability of the toolbox.Summary of revisions: Porting to Python.Introduction of amorphous layers in the sample structures.Add magnetization property to atoms and layers.Multilayer formalism to calculate laser absorption.New magnetization class to allow for user-defined magnetization dynamics.New resonant magnetic X-ray scattering employing dynamical X-ray theory.Calculation of X-ray scattering as function of photon energy and scattering vector.Nature of problem: Simulate the thermal, structural, and magnetic dynamics of 1D layered sample structures due to an ultrafast laser excitation and compute the corresponding transient (magnetic) X-ray scattering response.Solution method: The program provides an object-oriented toolbox for building arbitrary layered 1D crystalline/amorphous sample structures including a rich database of element-specific parameters. The excitation, thermal transport, and lattice dynamics are simulated utilizing SciPy's ODE solver. Magnetization dynamics can be introduced by the user employing a magnetization interface class. The dynamical (magnetic) X-ray scattering is computed by a matrix formalism that can be parallelized.Additional comments including restrictions and unusual features: The program is restricted to 1D layered sample structures. Phonon dynamics only include longitudinal acoustic phonons (sound waves). Magnetization dynamics have to be defined by the user. X-ray scattering only allows for symmetrical and co-planar geometries due to the 1D nature of the toolbox. The program is highly modular and allows the inclusion of user-defined inputs at any time of the simulation procedure.

A practical method for estimating specific refractive index increments for flexible non-electrolyte polymers and copolymers in pure and mixed solvents using the Gladstone-Dale and Lorentz-Lorenz equations in conjunction with molar refraction structural constants, and solvent physical property databases

Equations for calculating the specific refractive index increment, ∂n/∂c, for polymer/solvent systems have been developed starting with either the Gladstone-Dale equation or the Lorentz-Lorenz equation for the refractive index of a dielectric medium. The resulting equations can be used to estimate ∂n/∂c as a function of polymer concentration, temperature, solvent composition, and, for copolymers, monomer composition. Simplifying assumptions have been made to generalize these equations and make them more usable: 1) molar refractions are treated as constants, 2) the density of the polymer solution, in the limit of low polymer concentration, can be approximated via the additivity of volumes approach; the densities of polymer-free solvents and solvent mixtures are not necessarily subject to this approximation, 3) the mass density of solvents and solvent mixtures can be estimated by any one of several models developed specifically for this purpose; we will consider the Rackett equation, the COSTALD equation, and the standard assumption of mass and volume additivity, and 4) the mass density of a copolymer can be obtained from a weight fraction average of the mass densities of the homopolymers from which it is comprised. Comparisons to experimental data show that (∂n/∂c)GD and (∂n/∂c)LL both yield average absolute deviations of approximately 0.009 ml/gm.

Simulating Tissues with 3D-Printed and Castable Materials.

Manufacturing technologies continue to be developed and utilized in medical prototyping, simulations, and imaging phantom production. For radiologic image-guided simulation and instruction, models should ideally have similar imaging characteristics and physical properties to the tissues they replicate. Due to the proliferation of different printing technologies and materials, there is a diverse and broad range of approaches and materials to consider before embarking on a project. Although many printed materials' biomechanical parameters have been reported, no manufacturer includes medical imaging properties that are essential for realistic phantom production. We hypothesize that there are now ample materials available to create high-fidelity imaging anthropomorphic phantoms using 3D printing and casting of common commercially available materials. A material database of radiological, physical, manufacturing, and economic properties for 29 castable and 68 printable materials was generated from samples fabricated by the authors or obtained from the manufacturer and scanned with CT at multiple tube voltages. This is the largest study assessing multiple different parameters associated with 3D printing to date. These data are being made freely available on GitHub, thus affording medical simulation experts access to a database of relevant imaging characteristics of common printable and castable materials. Full data available at: https://github.com/nmcross/Material-Imaging-Characteristics .

Inertial properties of a living population for the development of biofidelic headforms

The aim of this study is to create a new database of human head physical properties based on a living adult population that can be used to inform the development of future biofidelic headforms. Relationships between head circumference and mass, as well as head moments of inertia and mass, are sufficiently linear to provide simple yet accurate values for the mass and inertia properties of differently sized heads. Physical data regarding the dimensions, mass, moments of inertia and centre of gravity location for the heads of 56 living adults were obtained using a non-invasive method based on computed tomography-based finite element models. The computed tomography data showed good agreement with published cadaver data and significantly less variation. The data set presented in this article provides an important basis for more biofidelic future headform designs. The linear equations associated with this new primary data set relate head circumference to head mass and moments of inertia: Head Mass = 0.18 × Head Circumference – 6.08, where mass is in kg and circumference is in cm, while Ixx = 79.88 × Head Mass – 132.88, Iyy = 81.70 × Head Mass – 128.38 and Izz = 53.88 × Head Mass – 86.66, where I is the moment of inertia in kg/cm2 and mass is in kg. The X, Y and Z axes correspond to forward, lateral and vertical directions and the XZ plane corresponds to the mid-sagittal plane. These results represent the first published human head physical property data that are based on a living population, rather than cadaver data. These data are freely available to all and should serve to improve the biofidelity of standard headforms in terms of their mass and moments of inertia.

3D geophysical modeling of the Alberton-Mathinna section of the “Main Slide,” northeast Tasmania

We have developed a high-resolution 3D model of the Alberton-Mathinna section of the “Main Slide,” northeast Tasmania. This geological model expresses a new synthesis based on mapping and structural interpretation on multiple cross sections. We have refined this model by 3D geophysical inversion constrained by gravity and magnetic survey data coupled with drilling and rock physical property databases. Our modeling incorporates statistically generated sensitivity characterization metrics into 3D model products that map confidence in the geometry of geological units at depth. The results include a granitoid surface that is considerably more detailed than earlier versions based on 2D modeling. Among the new features to emerge is a cupola 1.6 km below and slightly west of the Mathinna goldfield. At the Ringarooma United deposit located within the Alberton goldfield, we seethat the fault network underpinning the deposit was intruded by granite to a depth of approximately 400 m. Ore-forming solutions for both deposits have been interpreted as metamorphic in origin, but our results suggest the possibility of a role for magmatic fluids (i.e., granite related) in the gold-mineralizing system, particularly for the Ringarooma United deposit.

Assessment of cocoa input needs using soil types and soil spectral analysis

AbstractIn this study, diffuse reflectance spectroscopy (DRS) approach was examined for making input recommendations in the smallholder cocoa farms of Papua New Guinea (PNG). Soil samples were collected from four provinces of PNG. Soil samples from four different depths (0–10, 10–30, 30–60 and 60–90 cm) of 32 profiles in each of these site were used to create a database of soil chemical and physical properties. Spectral reflectance values at 1 nm interval covering visible to shortwave‐infrared (350–2,500 nm) were collected for each of these soil samples to develop partial least squares regression models. Soil textural fractions, soil organic carbon contents and available N were well predicted by the DRS approach with R2 values larger than 0.75. Moderate to poor estimation efficiencies were observed for remaining parameters. Nevertheless, the estimated soil attributes and their corresponding measured soil parameters were used as inputs to an input recommendation model of soil diagnosis to create input recommendation for a targeted cocoa yield of 1,000 kg dry cocoa beans ha‐1 Resulting input recommendations were similar for both of these input sources (measured and DRS‐estimated) suggesting that the DRS approach may provide an easy way to create input recommendations.

Exploration of the importance of physical properties of Indonesian peatlands to assess critical groundwater table depths, associated drought and fire hazard

Widespread degradation of Indonesian peatlands by deforestation and excessive drainage results into more frequent fires, particularly in El Niño years, which causes: (i) release of enormous amounts of peat soil carbon to the atmosphere, impacting climate, (ii) severe air pollution, affecting human health and air traffic, and (iii) decreased ecosystem services through loss of biodiversity. Groundwater table decline is the main driver of these negative processes and, therefore restoration of peatland hydrology is essential. Although groundwater table depth is critical to counteract peatland degradation, optimal depths are not generic for all peatlands, but depend on peat physical properties (i.e. water retention, unsaturated conductivity), which are related to the degree of peat humification (Fibric, Hemic, Sapric). Unfortunately only few of these peat physical properties are available while they are essential input data in hydrological models required to extend the usually short observed groundwater hydrographs. An experiment with the Soil-Water-Atmosphere-Plant model (SWAP) for two locations in Indonesian peatlands illustrates the impact of the degree of peat humification on physical properties and thereby on calculated groundwater table depth, hydrological drought and associated fires hazards. The Variable Threshold Method is applied to convert groundwater table depths into hydrological drought, and next the modified Keetch-Byram Drought Index (mKBDI) is used to assess wildfire hazard. Peat physical properties that reflect higher peat humification (Hemic and Sapric) result into lower water tables during dry periods, in particular during El Niño years, more severe hydrological drought, and an earlier and longer fire season. Using the limited available peat physical properties the importance is demonstrated of initiating a comprehensive programme to build a database of peat physical properties covering different environmental conditions in which tropical peatlands occur. Availability of such a database connected to a long-term monitoring programme, will support the ongoing rewetting, revegetation and revitalisation programme for Indonesian peatlands, which eventually will contribute to sustainable livelihoods for local people and reduce impact on the regional climate.

Flash‐point prediction of fragrances or flavours accounting for non‐ideality of the liquid phase

AbstractThe flammability classifications of flavour and fragrance oils are determined from their flash‐point temperatures, which are of critical importance for safety and regulatory considerations. The reliable prediction of flash points for our products is a business need challenged by the sheer number of ingredients present in a typical formulation, ranging from dozens to hundreds of ingredients, and their chemical diversity. To assess the predictability of flash points for the complex mixtures relevant to our industry, we consider five model mixtures of 15 perfume and flavour raw materials, with a variety of chemical functionalities, and apply Le Chatelier('s rule together with vapour pressure curves from the Design Institute for Physical Properties (DIPPR) database and activity coefficients predicted from the Modified UNIFAC (Dortmund 1993) group contribution model. Flash‐point temperatures of the 15‐compound model mixtures were predicted with an accuracy of ±2°C, compared with experimental data, when taking into account the non‐ideality of the liquid phase.

Defining Petrophysical Properties of Ultramafic and Mafic Rocks In Terms of Alteration

The effects of talc-carbonate alteration and serpentinisation on the physical properties of ultramafic rocks are regularly presented but often as incomplete datasets, and are subsequently poorly understood. The development of integrated and more robust physical property databases is important. Consequently, two Western Australian greenstone terranes have been studied. Data from ~2,000 samples taken from the Plutonic-Marymia Greenstone Belt and the Eastern Gold Fields are presented. New p-wave velocity, magnetic susceptibility, density, apparent porosity, and natural remanent magnetisation data are examined. An integrated approach of placing empirical petrophysical data within a rigorous mineralogical and petrological framework has been undertaken. The use of Short Wave Infrared (SWIR) spectral data is investigated. SWIR data are shown to be useful for the identification and quantification of talc-carbonate mineralogy of ultramafic rocks. Similarly the identification of variable Mg-Fe chlorite is also beneficial. Petrophysical data are shown to correlate well when compared with talc-carbonate and chlorite spectral mineral data and abundances. Serpentine group mineralogy can be identified, however olivine, quartz and pyroxene minerals are unable to be resolved due poor absorption features in the SWIR. Serpentine mineral species, i.e. lizardite, antigorite, and chrysotile, are also unable to be resolved due to narrowness of wavelength absorption features. It also important to recognise that reported mineral abundances are typically normalised to SWIR active minerals. Anomalous values of reliable but limited spectrally classified serpentine data have shown two populations of serpentinised rocks within acoustic impedance plots. In particular, one population presents a high p-wave velocity, i.e. 6500-7000m/s, and ubiquitously low density and high magnetic susceptibility. These data suggest the presence of antigorite and or silicification. Consequently, although SWIR classified data have been shown to be appropriate to use for interpreting variable degrees of talc-carbonate alteration, an interpretation of serpentinised rocks should be treated with caution. Furthermore, it is recognised that the uncertainty of SWIR mineral abundance data should be evaluated where SWIR active minerals present overlapping wavelength features.

Practical Considerations & Good Protocol for the Interpretation of Ultramafic & Mafic Rock Physical Property Data

An increase in the availability of inexpensive and easy-to-use geophysical tools has led to an interest in the development of larger rock physical databases. These data are often interpreted at face value, with little consideration given to the selection of representative samples, sample preparation, or even the practical limitations of measuring tool. Consequently, wide-ranging data are often observed. This may lead to incorrect interpretation. Magnetic susceptibility and density measurements are now routinely made on drill-core specimens. These data are often amalgamated with historical measurements in an effort to make localised physical property databases more robust. Two practical considerations regarding these data are discussed: 1) The evaluation of dry bulk density data, and inherent issues with measuring dimensions or applying volume assumptions; 2) The appropriateness of using commonly employed inductive electromagnetic tools, i.e. handheld magnetic susceptibility meters, to resolve induced magnetisation.Changes in core-diameter due to coring and rock swelling are studied, as are the effects of core volume loss due to cutting. A comparison between empirical measurements and volume estimations has shown that up to 7% and 30% of variability may be attributed to changes in drill-core diameter and split-core geometry, respectively. Dry bulk density data that have been calculated using estimated volumes may be in extreme error and therefore inappropriate to use. Orientation markings or bottom-of-hole lines have shown to correlate with reduction in variability of core volume loss caused by cutting. The use of an Almonte core-holder, or similar, is shown to produce an even lower and less variable core volume loss. The reliability of historical dry bulk density values may be ranked based on the presence of orientation or bottom-of-hole line, or known implementation of a core cutting holders.Bulk magnetic susceptibility measurements made on ultramafic and mafic diamond drill-core using a handheld instrument are evaluated. Comparisons with Qmeter magnetisation data show that handheld bulk magnetic susceptibility values may be in the error of several orders of magnitude. Anisotropy is hypothesised to be the principal cause of variation. Furthermore, conductivity effects that are induced by handheld meters, e.g. frequency dependence, may contribute to an under-reporting of values.

Learning on chemical equilibrium shift assessment for membrane reactors using Gibbs free energy minimization method

This work presents how to deal with calculations of equilibrium shift in a membrane reactor using Gibbs free energy minimization method. Students are required to use the thermodynamic relations, stoichiometric table for membrane-assisted process, reliable physical property databases, optimization tools and mass balances fundamentals. As an example, catalytic dehydrogenation of cyclohexane, relevant for hydrogen storage and supply, was solved using MatLab® software. The equilibrium shift conversion as well as the influence of membrane reactor operational parameters were clearly demonstrated. Simulation results were successfully compared with the experimental data previously published in open literature. Thus, this exercise can help undergraduate students of chemical engineering to master the complex issues involved in chemical equilibrium calculations, offering them an opportunity to practice the application of modern numerical problem-solving tools for reacting systems.