A Non‐Gaussian Spatio‐Temporal Model for Daily Wind Speeds Based on a Multi‐Variate Skew‐t Distribution

Facing increasing domestic energy consumption from population growth and industrialization, Saudi Arabia is aiming to reduce its reliance on fossil fuels and to broaden its energy mix by expanding investment in renewable energy sources, including wind energy. A preliminary task in the development of wind energy infrastructure is the assessment of wind energy potential, a key aspect of which is the characterization of its spatio‐temporal behavior. In this study we examine the impact of internal climate variability on seasonal wind power density fluctuations over Saudi Arabia using 30 simulations from the Large Ensemble Project (LENS) developed at the National Center for Atmospheric Research. Furthermore, a spatio‐temporal model for daily wind speed is proposed with neighbor‐based cross‐temporal dependence, and a multi‐variate skew‐t distribution to capture the spatial patterns of higher‐order moments. The model can be used to generate synthetic time series over the entire spatial domain that adequately reproduce the internal variability of the LENS dataset.     

Long-term performance of BHE (borehole heat exchanger) fields with negligible groundwater movement

The long-term performance of double U-tube BHE (borehole heat exchanger) fields is investigated by finite element simulations, performed through the software package COMSOL Multiphysics (^©COMSOL, Inc.), for grounds in which the effects of groundwater movement are negligible. Six time periodic heat loads with period of 1 year are examined, with either full compensation, or partial compensation or no compensation of winter heating with summer cooling. A single BHE surrounded by infinite ground and the following BHE field configurations are analyzed: a single line of infinite BHEs, two staggered lines of infinite BHEs, a square field of infinite BHEs. For each BHE field configuration, four different distances between adjacent BHEs and two values of the ground thermal conductivity are considered. The undisturbed ground temperature is assumed equal to 14 °C, and −5 °C is prescribed as the lowest allowed temperature for the working fluid. For each BHE field geometry, heat load and ground thermal conductivity, plots of the minimum annual value of the fluid temperature for a period of 50 years are reported, and the pairs “distance – heat load” which keep the fluid temperature above the prescribed limit are evidenced.     

Hafnium binary alloys from experiments and first principles

Despite the increasing importance of hafnium in numerous technological applications, experimental and computational data on its binary alloys is sparse. In particular, data is scant on those binary systems believed to be phase-separating. We performed a comprehensive study of hafnium binary systems with alkali metals, alkaline earths, transition metals and metals, using high-throughput first-principles calculations. These computations predict novel unsuspected compounds in six binary systems previously believed to be phase-separating. They also predict a few unreported compounds in additional systems and indicate that some reported compounds may actually be unstable at low temperatures. We report the results for the following systems: AgHf, AlHf, AuHf, BaHf, BeHf, BiHf, CaHf, CdHf, CoHf, CrHf, CuHf, FeHf, GaHf, HfHg, HfIn, HfIr, HfK, HfLa, HfLi, HfMg, HfMn, HfMo,HfNa, HfNb, HfNi, HfOs, HfPb, HfPd, HfPt, HfRe, HfRh, HfRu, HfSc, HfSn, HfSr, HfTa, HfTc, HfTi, HfTl, HfV, HfW, HfY, HfZn and HfZr ( = systems in which the ab initio method predicts that no compounds are stable).     

Heavy metals in sediments from canals for water supplying and drainage: mobilization and control strategies

One of the most critical aspects of the maintenance of canals for water supplying and drainage is the managing of deposited sediments, which must be periodically removed. Deposited sediments, if containing anthropogenic pollutants with a concentration exceeding specific law limits, must be stored as industrial wastes, thus raising additional economic and logistic problems to deal with. Our research considers polluted sediments from an area close to the south side of Po river, in order to characterize heavy metals associated with different mineral species, thus defining effective treatments for their inertization, and suggesting a possible process for their recycle. Our results demonstrate that the composition of these sediments is suitable for the production of tiles and bricks. Several tests were thus performed to optimize sample treatment and other process parameters, finally giving very encouraging results. Releasing tests on fired products reveal that all the heavy metals are well retained.     

Supercritical water oxidation of coal in power plants with low CO2 emissions

In this paper, the application of Super Critical Water Oxidation (SCWO) to direct combustion at low temperature of coal fine particles with pure oxygen for power generation is presented, including also a novel method for capturing and storing carbon dioxide as liquid. A detailed simulation model of a 100 MW_th coal-fired SWCO plant with low CO₂ emissions characterised by a steam cooled membraned SC reactor has been developed using Aspen Plus software. According to the well-known Semenov's thermal-ignition theory, the coal particle ignition temperature in SCW conditions has been also evaluated and the results have been integrated within the Aspen Plus model. This has been tested under different operating conditions. The simulation results are presented and the effects of the main plant operating conditions, such as ignition temperature, coal particle size and combustion pressure on the plant performances are discussed. The gross and net thermodynamic efficiencies of the power plant have been estimated to be around 44% and 28%, respectively. The pure oxygen production process results the main energy penalty.     

Quantification of uncertainty using Bayesian and bootstrap models to simulate the impact of nitrogen fertilisation on β‐glucan levels in barley

BACKGROUND: β‐Glucans have enjoyed renewed interest as a functional food ingredient, with current attention focused on optimising β‐glucan levels in finished products without compromising final product quality. In order to measure the uncertainty about the level of β‐glucans in barley, two different statistical methods (Bayesian inference and Bootstrap technique) were applied to measured levels of β‐glucan in three different varieties of barley grain (n = 83). RESULTS: The resulting probability density distributions were similar for the full data set and also when applied to smaller sample sizes, highlighting the potential for either method in quantifying the total uncertainty in β‐glucan levels. Bayesian inference was used to model the effect of nitrogen treatment on β‐glucan and protein contents in barley. The model found that a low level of fertilisation (50 kg N ha^?1) did not have a significant effect on β‐glucan or protein content. However, fertilisation above this level did result in an increase in β‐glucan and protein levels, the effect seeming to plateau at 100 kg N ha^?1. In addition, the uncertainty distributions were significantly different for two consecutive years of data, highlighting the potential environmental influence on β‐glucan content. CONCLUSION: The model developed in this study could be a useful tool for processors to quantify the uncertainty about the initial level of β‐glucan in barley and to evaluate the influence of environmental factors, thus enabling them to formulate their ingredient base to optimise levels of β‐glucan without compromising final product quality. Copyright © 2009 Society of Chemical Industry     

Production and characterization of an allergen panel for component-resolved diagnosis of celery allergy

In celery a relevant food allergen source, three allergens have been identified so far: Api g 1 and Api g 4, and one glycosylated protein, Api g 5. For component-resolved food allergy diagnosis high amounts of well-defined allergens are needed. Depending on the individual celery allergen, protocols for heterologous production and purification from natural source, respectively, were established to obtain homogenous protein batches. Afterwards the purified recombinant allergens, Api g 1, Api g 4 and natural Api g 5 were characterized regarding their structural integrity and immunological activity. Therefore, several methods were applied. Proteins were identified by partial N-terminal sequencing, protein mass was verified by MS and sequence integrity by MALDI-TOF and N-terminal sequencing after tryptic digestion. Presence of isoforms in natural allergen preparations was identified by 2-DE. Secondary and tertiary structures were evaluated by circular dichroism (CD) spectroscopy and NMR analysis. Finally, IgE binding capacity was verified using selected sera from celery allergic patients in IgE immunoblots and IgE ELISA. These well-defined celery allergens will be used to prove the concept of component-resolved diagnosis and will contribute to improve food allergy diagnosis in the future.     

Parabolic RANS solver for low‐computational‐cost simulations of wind turbine wakes

A numerical framework for simulations of wake interactions associated with a wind turbine column is presented. A Reynolds‐averaged Navier‐Stokes (RANS) solver is developed for axisymmetric wake flows using parabolic and boundary‐layer approximations to reduce computational cost while capturing the essential wake physics. Turbulence effects on downstream evolution of the time‐averaged wake velocity field are taken into account through Boussinesq hypothesis and a mixing length model, which is only a function of the streamwise location. The calibration of the turbulence closure model is performed through wake turbulence statistics obtained from large‐eddy simulations of wind turbine wakes. This strategy ensures capturing the proper wake mixing level for a given incoming turbulence and turbine operating condition and, thus, accurately estimating the wake velocity field. The power capture from turbines is mimicked as a forcing in the RANS equations through the actuator disk model with rotation. The RANS simulations of the wake velocity field associated with an isolated 5‐MW NREL wind turbine operating with different tip speed ratios and turbulence intensity of the incoming wind agree well with the analogous velocity data obtained through high‐fidelity large‐eddy simulations. Furthermore, different cases of columns of wind turbines operating with different tip speed ratios and downstream spacing are also simulated with great accuracy. Therefore, the proposed RANS solver is a powerful tool for simulations of wind turbine wakes tailored for optimization problems, where a good trade‐off between accuracy and low‐computational cost is desirable.