Combining simulation techniques and design expertise in a renewable energy system design package, RESSAD

Computer simulation is an increasingly popular tool for determining the most suitable renewable energy system type, design and control for an isolated community or homestead. However for the user without any expertise in system design, the complicated process of system component and control selection using computer simulation takes on a trial and error approach. Our renewable energy system design package, RESSAD, has been developed to simulate a wide range of renewable power supply systems, and to go beyond system simulation, by combining design expertise with the simulation model. The knowledge of the system designer is incorporated into the package through a range of analysis tools that assist in the selection process, without removing or restricting individual choices. The system selection process is analysed from the early stages of renewable resource assessment to the final evaluation of the results from a simulation of the chosen system. The approach of the RESSAD package in this selection process is described and its use is illustrated by two case studies in Western Australia.     

Engineering improvement of NaAlH4 system

The significant engineering challenges associated with developing lower-pressure, materials-based, hydrogen storage systems for hydrogen fuel cell light-duty vehicles are being addressed by focusing on the role that powder consolidation can play. NaAlH₄ with 4 mol % TiCl₃ was selected as the model material. We focused on the changes in the physical (density and thermal conductivity) and mechanical properties (biaxial flexure strength) and on how these impacted the volumetric capacity of the hydrogen storage system. Both the thermal conductivity and the density of the ball milled material improved with applied pressure in a uniaxial press over the range of 14 MPa–281 MPa. The thermal conductivity reached a value of (1.64 ± 0.02) W/m/K, which was a factor seven higher than that of the unconsolidated powder. The volume of the material was reduced by 42% at the highest applied pressure. A method was developed for determining the strength of NaAlH₄ pellets before and after hydrogen absorption and desorption cycles. It is based on a biaxial flexure test that was originally designed for determining the strength of green ceramic materials. The tests showed that the pellets were strong with biaxial flexure strength of 1.4 kpsi which was unaltered over three studied hydrogen absorption/desorption cycles. The increased materials density did not affect the hydrogen absorption and desorption kinetics, which is important in order to benefit from the improved volumetric capacity. The new material properties of the compacted NaAlH₄ were used in finite element modeling of a hydrogen storage system that targeted a fast refueling time. The results clearly show an improvement of the volumetric capacity of the system by powder consolidation but the gravimetric capacity remains below target, as expected. A system level study of a light-duty vehicle with such a hydrogen storage system is required in order to determine whether the amount of hydrogen stored in the pore volume of the sodium alanate will still be enough to enable one cold start from room temperature to its operating temperature (120–140 °C) or that a buffer volume needs to be installed. While it is recognized that a sodium alanate based hydrogen storage system has its limitations, it has been demonstrated that powder consolidation can address some of those limitations by improving the thermal conductivity and volumetric capacity.     

Field and laboratory studies of the stability of amorphous silicon solar cells and modules

If photovoltaic solar cells and modules are to be used as a major source of power generation it is important to have a good knowledge and understanding of their long-term performance under different climatic and operating conditions. A number of studies of the long-term performance of commercially available photovoltaic modules manufactured using different technologies have now been reported in the literature. These have shown clear differences in the seasonal and long term performance and stability of different solar cell techniques. In addition to general module engineering factors that result in a loss of performance in all modules some types of solar cells, such as those made from thin film amorphous silicon (a-Si:H), also suffer specific losses in performance due to fundamental material changes, such as photodegradation or the Staebler–Wronski effect (SWE). A field evaluation of the long term performance of state-of-the-art crystalline and amorphous silicon photovoltaic modules in Australian conditions is currently being undertaken at Murdoch University. The initial results from this monitoring program are reported. This paper also reports on laboratory and field studies being undertaken on the nature of the Staebler–Wronski effect in amorphous silicon solar cells and how the stability of these cells is affected by different operating conditions. Based on a mechanism for the SWE in a-Si:H solar cells developed as a result of our research we propose a number of possible ways to reduce the Staebler–Wronski effect in a-Si:H solar cells.     

A survey of free and conjugated deoxynivalenol in the 2008 corn crop in Ontario, Canada

BACKGROUND: Deoxynivalenol (DON, vomitoxin), one of the most important mycotoxins produced by many Fusarium species, is found as a common contaminant of crops worldwide. Recent studies have described the presence of conjugated forms of DON (glycosides and fatty acid). The aim of the current study was therefore to investigate the natural occurrence of free and conjugated DON in Canadian corn. RESULTS: Free and conjugated DON was determined by gas chromatography‐mass spectrometry (GC‐MS) and enzyme‐linked immunosorbent assay (ELISA) in 86 corn samples collected from the 2008 crop in Ontario, Canada. Free DON concentrations determined by ELISA were similar to values determined in most samples using GC‐MS. Conjugated DON was detected in 72 samples. Levels of free DON ranged from 0.17 to 14.00 µg g^?1 using GC‐MS. The highest levels of free DON were found in corn samples from the southern and southwestern regions of Ontario, while samples from eastern regions were less contaminated. Conjugated DON was found mainly in corn from the east‐central region, with five of six samples showing high levels of conjugated DON (up to 43% increase in DON following acid hydrolysis). Low levels of conjugated DON (≤10% increase in DON following acid hydrolysis) were detected in the majority of corn samples from the southwestern region (nine of 19 samples) and from the central region (16 of 36 samples). CONCLUSION: The current survey emphasizes the frequency of conjugated DON in Ontario grown corn and the potential challenges in understanding the hazard posed by DON‐contaminated foodstuffs and feedstuffs. Copyright © 2011 Society of Chemical Industry     

Reduction by gaseous ozone of Salmonella and microbial flora associated with fresh-cut cantaloupe

This research investigates the efficacy of gaseous ozone, applied under partial vacuum in a controlled reaction chamber, for the elimination of Salmonella inoculated on melon rind. The performance of high dose, short duration treatment with gaseous ozone, in this pilot system, on the microbial and sensory quality of fresh-cut cantaloupes was also evaluated. Gaseous ozone (10,000 ppm for 30 min under vacuum) reduced viable, recoverable Salmonella from inoculated physiologically mature non-ripe and ripe melons with a maximum reduction of 4.2 and 2.8 log CFU/rind-disk (12.6 cm(2)), respectively. The efficacy of ozone exposure was influenced by carrier matrix. Salmonella adhering to cantaloupe was more resistant to ozone treatment when suspended in skim-milk powder before aqueous inoculation to the rind. This indicated that organic matter interferes with the contact efficiency and resultant antimicrobial activity of gaseous ozone applied as a surface disinfectant. Conversely, in the absence of an organic carrier, Salmonella viability loss was greater on dry exocarp surfaces than in the wetted surfaces, during ozone treatment, achieving reductions of 2.8 and 1.4 initial log CFU/rind-disk, respectively. Gaseous ozone treatment of 5000 and 20,000 ppm for 30 min reduced total coliforms, Pseudomonas fluorescens, yeast and lactic acid bacteria recovery from fresh-cut cantaloupe. A dose Ct-value (concentration x exposure time) of 600,000 ppm min achieved maximal log CFU/melon-cube reduction, under the test conditions. Finally, fresh-cut cantaloupe treated with gaseous ozone, maintained an acceptable visual quality, aroma and firmness during 7-day storage at 5 degrees C. Conclusions derived from this study illustrate that gaseous ozone is an effective option to risk reduction and spoilage control of fresh and fresh-cut melon. Moreover, depending on the timing of contamination and post-contamination conditions, rapid drying combined with gaseous ozone exposure may be successful as combined or sequential disinfection steps to minimize persistence of Salmonella on the surface of cantaloupe melons and transference during fresh-cut processing of home preparation. Based on these results, greater efficacy would be anticipated with mature but non-ripe melons while ripe tissues reduce the efficacy of these gaseous ozone treatments, potentially by oxidative reaction with soluble refractive solids.     

Meat quality comparison between fresh and frozen/thawed ostrich M. iliofibularis

A pairwise comparison of the meat quality between fresh and frozen/thawed Musculus iliofibularis was conducted. Thirty-two (16 left; 16 right) muscles were collected and allocated to two treatments: fresh and frozen/thawed. Frozen vacuum-packed samples were stored for 1 month at -20°C before thawing. The fresh samples had higher pH (P<0.05), water binding capacity (P<0.05), CIE L* (P<0.0001), CIE a* (P<0.05) and Chroma values (P<0.05) than the frozen/thawed samples, indicating the fresh samples were bright red in appearance and had minimal exudate. The frozen/thawed samples lost 5.09±0.21% moisture during thawing and had a greater drip loss (P<0.0001) and shear force (P<0.001). No differences were obtained with regard to cooking loss, CIE b*, hue and TBARS. Protein oxidation (mM carbonyls/mg protein) was lower (P<0.05) in the frozen/thawed samples, which was attributed to the higher (P<0.0001) protein concentration negating the higher (P<0.001) carbonyl content. Industrial freezing and thawing regimes negatively affected the quality of ostrich meat.     

Assessment of root uptake and systemic vine-transport of Salmonella enterica sv. Typhimurium by melon (Cucumis melo) during field production

Bifidobacterium adolescentis Int57 (Int57) and Propionibacterium freudenreichii subsp. shermanii ATCC 13673 (ATCC 13673) were grown either in coculture or as pure cultures in different media, such as cow's milk, soybean milk, and modified MRS medium. The viable cell counts of bacteria, changes in pH, concentrations of organic acids, and contents of various sugars were analyzed during incubation up to 7days. In soy milk, the survival of cocultured Int57 was six times higher than the monocultured cells, and ATCC 13673 cocultured with Int57 consumed 69.4% of lactic acid produced by Int57 at the end of fermentation. In cow's milk, coculture with ATCC 13673 increased the growth of Int57 from 24h until 120h by approximately tenfold and did not affect the survival of Int57 cells. After 96h of fermentation of modified MRS, the survival of ATCC 13673 cells cocultured with Int57 increased by 3.2- to 7.4-folds as compared with ATCC 13673 monoculture, whereas the growth of Int57 cells was unaffected. The growth and metabolic patterns of two strains during coculture showed noticeable differences between food grade media and laboratory media. The consumption of stachyose in soy milk during coculture of Int57 with ATCC 13673 was increased by more than twice compared with Int57 monoculture, and completed within 24h. The combinational use of Bifidobacterium and Propionibacterium could be applied to the development of fermented milk or soy milk products.     

Radiative Heat Transfer Simulation on a SPARCStation Farm

At the Supcrcomputing Research Center we have built a computing farm consisting of 16 SPARCStation. ELCs. The ELCs all support the Mother distributed shared memory, which has primitives to support efficient synchronization and use of the network and processors. Mother docs not support the traditional consistency semantics provided by, for example, Ivy or Mach external pagers. The first parallel application we ran on the farm was a Monte Carlo radiative heat transfer simulation. The performance we achieved on the farm was within an order of magnitude of the performance we would expect to achieve on a 16-processor model of the C90 supercomputer available from Cray Research. With this application we found that the use of the Mother distributed shared memory allowed us to run the same code on the Cray as we ran on the SPARCStatlons, and we did not require the complex cache-coherent memory semantics provided by, say, Ivy or Mach to run this application effectively.     

Longitudinal deep truck: Deep longitudinal model with application to sim2real deep reinforcement learning for heavy-duty truck control in the field

To develop cooperative adaptive cruise control (CACC), the choice of control approach often influences and can limit the choice of model structure, and vice versa. For heavy-duty trucks, practical application of CACC in the field is heavily influenced by the accuracy of the used model. Deep learning and deep reinforcement learning (deep-RL) have recently been used to demonstrate improved modeling and control performance for vehicles such as cars and quadrotors compared to state-of-the-art. The literature on the application of deep learning and deep-RL for heavy-duty trucks in the field, which are significantly more complex than cars, is still sparse, however. In this article, we develop a two-layer gray-box deep learning model to capture longitudinal dynamics of heavy-duty trucks while abstracting their complexity and present an approach to properly break the nested feedback loops in the model for training. We compare this model with three other alternative models and show that it achieves $~10x$ better general performance compared to a standard artificial neural network and results in $~4x$ and $~40x$ slower steady-state acceleration and speed error growth rates, respectively. We then present an architecture to utilize these deep learning models within the deep-RL framework and use it to develop baseline CACC controllers that can be zero-shot transferred to the field. To carry out the work, we present a setup of differently configured trucks along with their interface architecture and stochastic driving cycle generators for data collection. Numerical validation of the approach demonstrated stationary and bounded modeling error, and demonstrated transfer of CACC controllers with consistent overshoot bounds and a stable approximately-zero steady-state error. Validation from field experiments demonstrated similarly consistent results. Compared to a state-of-the-art benchmark, the deep-RL controller achieved lower speed and time-gap error variance but higher time-gap error offset.