Reflections on preserving the state of new media art

As part of its work to explore emerging issues associated with characterisation of digital materials, Planets has explored vocabularies and information structures for expressing the properties integral to the value of digital art. Value encompasses those qualities that must be understood and captured in order to ensure that art works’ sensory, emotional, mental and spiritual resonance remain. Facets of interactivity, modularity and temporality associated with digital art present some critical questions that the preservation community must increasingly be equipped to answer. Because digital art materials exhibit fundamental multidimensionality, validating the successful preservation of creative experience demands the explication of more than just file characteristics. Understanding relationships between objects also implies an understanding of their respective functional qualities. This paper presents a Planets’ vocabulary for encapsulating contextual and implicit characteristics of digital art, optimised for preservation planning and validation

Entropy scaling based viscosity predictions for hydrocarbon mixtures and diesel fuels up to extreme conditions

An entropy scaling based technique using the Perturbed-Chain Statistical Associating Fluid Theory is described for predicting the viscosity of hydrocarbon mixtures and diesel fuels up to high temperatures and high pressures. The compounds found in diesel fuels or hydrocarbon mixtures are represented as a single pseudo-component. The model is not fit to viscosity data but is predictive up to high temperatures and pressures with input of only two calculated or measured mixture properties: the number averaged molecular weight and hydrogen to carbon ratio. Viscosity is predicted less accurately when the mixture contains high concentrations of iso-alkanes and cyclohexanes. However, it is shown that predictions for these mixtures are improved by fitting a third parameter to a single viscosity data point at a chosen reference state. For hydrocarbon mixtures, viscosity is predicted with average mean absolute percent deviations (MAPDs) of 12.2% using the two-parameter model and 7.3% using the three-parameter model from 293 to 353 K and up to 1000 bar. For two different diesel fuels, viscosity is predicted with an average MAPD of 21.4% using the two-parameter model and 9.4% using the three-parameter model from 323 to 423 K and up to 3500 bar

Engage - Using Data About Research Clusters to Enhance Collaboration

This project explored different classifications of research and ideas for implementing these in University systems to facilitate publicity of research

Modelling of Diesel fuel properties through its surrogates using Perturbed-Chain, Statistical Associating Fluid Theory

The Perturbed-Chain, Statistical Associating Fluid Theory equation of state is utilised to model the effect of pressure and temperature on the density, volatility and viscosity of four Diesel surrogates; these calculated properties are then compared to the properties of several Diesel fuels. Perturbed-Chain, Statistical Associating Fluid Theory calculations are performed using different sources for the pure component parameters. One source utilises literature values obtained from fitting vapour pressure and saturated liquid density data or from correlations based on these parameters. The second source utilises a group contribution method based on the chemical structure of each compound. Both modelling methods deliver similar estimations for surrogate density and volatility that are in close agreement with experimental results obtained at ambient pressure. Surrogate viscosity is calculated using the entropy scaling model with a new mixing rule for calculating mixture model parameters. The closest match of the surrogates to Diesel fuel properties provides mean deviations of 1.7% in density, 2.9% in volatility and 8.3% in viscosity. The Perturbed-Chain, Statistical Associating Fluid Theory results are compared to calculations using the Peng–Robinson equation of state; the greater performance of the Perturbed-Chain, Statistical Associating Fluid Theory approach for calculating fluid properties is demonstrated. Finally, an eight-component surrogate, with properties at high pressure and temperature predicted with the group contribution Perturbed-Chain, Statistical Associating Fluid Theory method, yields the best match for Diesel properties with a combined mean absolute deviation of 7.1% from experimental data found in the literature for conditions up to 373°K and 500 MPa. These results demonstrate the predictive capability of a state-of-the-art equation of state for Diesel fuels at extreme engine operating conditions

High-Temperature, High-Pressure Viscosities and Densities of n-Hexadecane, 2,2,4,4,6,8,8-Heptamethylnonane, and Squalane Measured Using a Universal Calibration for a Rolling-Ball Viscometer/Densimeter

The development of reference correlations for viscous fluids is predicated on the availability of accurate viscosity data, especially at high pressure, high temperature (HPHT) conditions. The rolling ball viscometer (RBV) is a facile technique for obtaining such HPHT viscosity data. A new, universal RBV calibration methodology is described and applied over a broad T-p region and for a wide range of viscosities. The new calibration equation is used to obtain viscosities for n-hexadecane (HXD), 2,2,4,4,6,8,8-heptamethylnonane (HMN), and 2,6,10,15,19,23-hexamethyltetracosane (squalane) from 298 – 530 K and pressures to 250 MPa. The available literature data base for HMN is expanded to 520 K and 175 MPa and for squalane to 525 K and 250 MPa. The combined expanded uncertainties are 0.6% and 2.5% for the densities and viscosities, respectively, each with a coverage factor, k = 2. The reliability of the viscosity data is validated by comparison of HXD and squalane viscosities to accepted reference correlations and HMN viscosities to available literature data. The necessity of this new calibration approach is confirmed by the large deviations observed between HXD, HMN, and squalane viscosities determined using the new, universal RBV calibration equation and viscosities determined using a quadratic polynomial calibration equation. HXD, HMN, and squalane densities are predicted with the Perturbed Chain Statistical Associating Fluid Theory using pure component parameters calculated with a previously reported group contribution (GC) method. HXD, HMN, and squalane viscosities are compared to Free Volume Theory (FVT) predictions using FVT parameters calculated from a literature correlation for nalkanes. Although the FVT predictions for HXD, a normal alkane, result in an average absolute percent deviation (∆AAD) of 3.8%, predictions for HMN and squalane, two branched alkanes, are four to 13 times larger. The fit of the FVT model for the branched alkanes is dramatically improved if the FVT parameters are allowed to vary with temperature

Purely predictive method for density, compressibility, and expansivity for hydrocarbon mixtures and diesel and jet fuels up to high temperatures and pressures

This study presents a pseudo-component method using the Perturbed-Chain Statistical Associating Fluid Theory to predict density, isothermal compressibility, and the volumetric thermal expansion coefficient (expansivity) of hydrocarbon mixtures and diesel and jet fuels. The model is not fit to experimental density data but is predictive to high temperatures and pressures using only two calculated or measured mixture properties as inputs: the number averaged molecular weight and hydrogen to carbon ratio. Mixtures are treated as a single pseudo-component; therefore binary interaction parameters are not needed. Density is predicted up to 470 K and 3,500 bar for hydrocarbon mixtures and fuels with 1% average mean absolute percent deviation (MAPD). Isothermal compressibility is predicted with 4% average MAPD for hydrocarbon mixtures and 9% for fuels. The volumetric thermal expansion coefficient is predicted with 7% average MAPD for hydrocarbon mixtures and 13% for fuels

Satellite versus ground-based estimates of burned area: a comparison between MODIS based burned area and fire agency reports over North America in 2007

North American wildfire management teams routinely assess burned area on site during firefighting campaigns; meanwhile, satellite observations provide systematic and global burned-area data. Here we compare satellite and ground-based daily burned area for wildfire events for selected large fires across North America in 2007 on daily timescales. In a sample of 26 fires across North America, we found the Global Fire Emissions Database Version 4 (GFED4) estimated about 80% of the burned area logged in ground-based Incident Status Summary (ICS-209) over 8-day analysis windows. Linear regression analysis found a slope between GFED and ICS-209 of 0.67 (with R = 0.96). The agreement between these data sets was found to degrade at short timescales (from R = 0.81 for 4-day to R = 0.55 for 2-day). Furthermore, during large burning days (> 3000 ha) GFED4 typically estimates half of the burned area logged in the ICS-209 estimates

Effect of parallel magnetic field on the Zero Differential Resistance State

The non-linear zero-differential resistance state (ZDRS) that occurs for highly mobile two-dimensional electron systems in response to a dc bias in the presence of a strong magnetic field applied perpendicular to the electron plane is suppressed and disappears gradually as the magnetic field is tilted away from the perpendicular at fixed filling factor $\nu$. Good agreement is found with a model that considers the effect of the Zeeman splitting of Landau levels enhanced by the in-plane component of the magnetic field.Comment: 4 pages, 4 figure

Vapor-liquid equilibria and mixture densities for 2,2,4,4,6,8,8-heptamethylnonane + N2 and n-hexadecane + N2 binary mixtures up to 535 K and 135 MPa

In this work, we report high-pressure, high-temperature (HPHT) mixture density and T-p isopleth (bubble (BP) and dew (DP) point) data for hexadecane (HXD) + N2 and heptamethylnonane (HMN) + N2 mixtures from ~323 to 523 K and pressures to ~100 MPa. Isothermal, mixture density data for both mixtures are measured in the single–phase region from the BP pressure to ~135 MPa and with ~ 14 to 90 mol% N2. A HPHT variable-volume, windowed view cell is used for both density and phase behavior measurements using the synthetic method. Mixture densities are correlated with the modified Tait equation and isothermal BP/DP data are correlated with an Antoine-type equation to allow for reliable interpolation of the data sets. Mixture densities and BP/DP pressures are modeled with the PC-SAFT equation coupled with pure component parameters calculated with two different group contribution methods. Although fairly reasonable predictions of liquid mixture densities are obtained when the binary interaction parameter, kij, is set to zero for both HXD + N2 and HMN + N2 mixtures, a value of kij equal to at least 0.119 is needed for both systems to obtain reasonable predictions of isothermal p-x behavior