Advanced and novel modeling techniques for simulation, optimization and monitoring chemical engineering tasks with refinery and petrochemical unit applications

Engineers predict, optimize, and monitor processes to improve safety and profitability. Models automate these tasks and determine precise solutions. This research studies and applies advanced and novel modeling techniques to automate and aid engineering decision-making. Advancements in computational ability have improved modeling software’s ability to mimic industrial problems. Simulations are increasingly used to explore new operating regimes and design new processes. In this work, we present a methodology for creating structured mathematical models, useful tips to simplify models, and a novel repair method to improve convergence by populating quality initial conditions for the simulation’s solver. A crude oil refinery application is presented including simulation, simplification tips, and the repair strategy implementation. A crude oil scheduling problem is also presented which can be integrated with production unit models. Recently, stochastic global optimization (SGO) has shown to have success of finding global optima to complex nonlinear processes. When performing SGO on simulations, model convergence can become an issue. The computational load can be decreased by 1) simplifying the model and 2) finding a synergy between the model solver repair strategy and optimization routine by using the initial conditions formulated as points to perturb the neighborhood being searched. Here, a simplifying technique to merging the crude oil scheduling problem and the vertically integrated online refinery production optimization is demonstrated. To optimize the refinery production a stochastic global optimization technique is employed. Process monitoring has been vastly enhanced through a data-driven modeling technique Principle Component Analysis. As opposed to first-principle models, which make assumptions about the structure of the model describing the process, data-driven techniques make no assumptions about the underlying relationships. Data-driven techniques search for a projection that displays data into a space easier to analyze. Feature extraction techniques, commonly dimensionality reduction techniques, have been explored fervidly to better capture nonlinear relationships. These techniques can extend data-driven modeling’s process-monitoring use to nonlinear processes. Here, we employ a novel nonlinear process-monitoring scheme, which utilizes Self-Organizing Maps. The novel techniques and implementation methodology are applied and implemented to a publically studied Tennessee Eastman Process and an industrial polymerization unit

A complex speciation-richness relationship in a simple neutral model

Speciation is the "elephant in the room" of community ecology. As the ultimate source of biodiversity, its integration in ecology's theoretical corpus is necessary to understand community assembly. Yet, speciation is often completely ignored or stripped of its spatial dimension. Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes. In this study, we use this framework to model allopatric and parapatric speciation in networks of communities and focus on the relationship between speciation, richness, and the spatial structure of communities. We find a strong opposition between speciation and local richness, with speciation being more common in isolated communities and local richness being higher in more connected communities. Unlike previous models, we also find a transition to a positive relationship between speciation and local richness when dispersal is low and the number of communities is small. Also, we use several measures of centrality to characterize the effect of network structure on diversity. The degree, the simplest measure of centrality, is found to be the best predictor of local richness and speciation, although it loses some of its predictive power as connectivity grows. Our framework shows how a simple neutral model can be combined with network theory to reveal complex relationships between speciation, richness, and the spatial organization of populations.Comment: 9 pages, 5 figures, 1 table, 50 reference

Phosphorus and Nitrogen Transport in the Binational Great Lakes Basin Estimated Using SPARROW Watershed Models

AbstractEutrophication problems in the Great Lakes are caused by excessive nutrient inputs (primarily phosphorus, P, and nitrogen, N) from various sources throughout its basin. In developing protection and restoration plans, it is important to know where and from what sources the nutrients originate. As part of a binational effort, Midcontinent SPARROW (SPAtially Referenced Regression On Watershed attributes) models were developed and used to estimate P and N loading from throughout the entire basin based on nutrient inputs similar to 2002; previous SPARROW models only estimated U.S. contributions. The new models have a higher resolution (~2‐km2 catchments) enabling improved descriptions of where nutrients originate and the sources at various spatial scales. The models were developed using harmonized geospatial datasets describing the stream network, nutrient sources, and environmental characteristics affecting P and N delivery. The models were calibrated using loads from sites estimated with ratio estimator and regression techniques and additional statistical approaches to reduce spatial correlation in the residuals and have all monitoring sites equally influence model development. SPARROW results, along with interlake transfers and direct atmospheric inputs, were used to quantify the entire P and N input to each lake and describe the importance of each nutrient source. Model results can be used to compare loading and yields from various tributaries and jurisdictions

Miniaturized data loggers and computer programming improve seabird risk and damage assessments for marine oil spills in Atlantic Canada

Obtaining useful information on marine birds that can aid in oil spill (and other hydrocarbon release) risk and damage assessments in offshore environments is challenging. Technological innovations in miniaturization have allowed archival data loggers to be deployed successfully on marine birds vulnerable to hydrocarbons on water. A number of species, including murres (both Common, Uria aalge, and Thick-billed, U. lomvia) have been tracked using geolocation devices in eastern Canada, increasing our knowledge of the seasonality and colony-specific nature of their susceptibility to oil on water in offshore hydrocarbon production areas and major shipping lanes. Archival data tags are starting to resolve questions around behaviour of vulnerable seabirds at small spatial scales relevant to oil spill impact modelling, specifically to determine the duration and frequency at which birds fly at sea. Advances in data capture methods using voice activated software have eased the burden on seabird observers who are collecting increasingly more detailed information on seabirds during ship-board and aerial transects. Computer programs that integrate seabird density and bird behaviour have been constructed, all with a goal of creating more credible seabird oil spill risk and damage assessments. In this paper, we discuss how each of these technological and computing innovations can help define critical inputs into seabird risk and damage assessments, and when combined, can provide a more realistic understanding of the impacts to seabirds from any hydrocarbon release

A Synthesis of Human-related Avian Mortality in Canada

Many human activities in Canada kill wild birds, yet the relative magnitude of mortality from different sources and the consequent effects on bird populations have not been systematically evaluated. We synthesize recent estimates of avian mortality in Canada from a range of industrial and other human activities, to provide context for the estimates from individual sources presented in this special feature. We assessed the geographic, seasonal, and taxonomic variation in the magnitude of national-scale mortality and in population-level effects on species or groups across Canada, by combining these estimates into a stochastic model of stage-specific mortality. The range of estimates of avian mortality from each source covers several orders of magnitude, and, numerically, landbirds were the most affected group. In total, we estimate that approximately 269 million birds and 2 million nests are destroyed annually in Canada, the equivalent of over 186 million breeding individuals. Combined, cat predation and collisions with windows, vehicles, and transmission lines caused > 95% of all mortality; the highest industrial causes of mortality were the electrical power and agriculture sectors. Other mortality sources such as fisheries bycatch can have important local or species-specific impacts, but are relatively small at a national scale. Mortality rates differed across species and families within major bird groups, highlighting that mortality is not simply proportional to abundance. We also found that mortality is not evenly spread across the country; the largest mortality sources are coincident with human population distribution, while industrial sources are concentrated in southern Ontario, Alberta, and southwestern British Columbia. Many species are therefore likely to be vulnerable to cumulative effects of multiple human-related impacts. This assessment also confirms the high uncertainty in estimating human-related avian mortality in terms of species involved, potential for population-level effects, and the cumulative effects of mortality across the landscape. Effort is still required to improve these estimates, and to guide conservation efforts to minimize direct mortality caused by human activities on Canada's wild bird populations. As avian mortality represents only a portion of the overall impact to avifauna, indirect effects such as habitat fragmentation and alteration, site avoidance, disturbance, and related issues must also be carefully considered

Diversity and Keratin Degrading Ability of Fungi Isolated from Canadian Arctic Marine Bird Feathers

We present the first records of fungi associated with feathers from seabirds and sea ducks in the Canadian Arctic and sub-Arctic. Birds sampled in Nunavut and Newfoundland (Canada) included the Common Eider (Somateria mollissima), King Eider (S. spectabilis), Black-legged Kittiwake (Rissa tridactyla), Northern Fulmar (Fulmarus glacialis), Glaucous Gull (Larus hyperboreus), Black Guillemot (Cepphus grylle), and Thick-billed Murre (Uria lomvia). In total 19 fungal species were cultured from feathers, identified using ITS rDNA barcoding, and screened for their ability to degrade keratin using a keratin azure assay. Our results indicate that 1) of the 19 isolates, 74% were ascomycetes, while the remaining 26% were basidiomycetes (yeasts); 2) 21% of the ascomycete isolates demonstrated keratinolytic activity (a known pathogenicity factor for fungi that may potentially be harmful to birds); 3) the largest number of fungi were cultured from the sampled Thick-billed Murre; and 4) based on a multiple correspondence analysis, there is some indication that both the King Eider and the Thick-billed Murre collected in the low Arctic had distinct fungal communities that were different from each other and from the other birds sampled. Although our sample sizes were small, initial trends in point (4) do demonstrate that additional study is merited to assess whether the fungal community differences are influenced by variation in the known ecologies of the avian hosts and fungi identified.Nous présentons les premiers enregistrements de champignons se rapportant aux plumes d’oiseaux et de canards de mer dans l’Arctique et la région subarctique du Canada. Parmi les oiseaux échantillonnés au Nunavut et à Terre-Neuve (Canada), notons l’eider à duvet (Somateria mollissima), l’eider à tête grise (S. spectabilis), la mouette tridactyle (Rissa tridactyla), le fulmar boréal (Fulmarus glacialis), le goéland bourgmestre (Larus hyperboreus), le guillemot à miroir (Cepphus grylle) et le guillemot de Brünnich (Uria lomvia). En tout, 19 espèces de champignons ont été prélevées à partir de plumes. Elles ont été identifiées au moyen de codes à barres ITS ADNr et examinées afin de déterminer si elles sont capables de dégrader la kératine, et ce, à l’aide d’une épreuve de dégradation de la kératine au bleu azur. Nos résultats indiquent : 1) que parmi les 19 isolats, 74 % étaient des ascomycètes et que les 26 % restants étaient des basidiomycètes (levures); 2) que 21 % des isolats d’ascomycètes ont affiché une activité kératinolytique (un facteur de pathogénicité pour les champignons, facteur susceptible de nuire aux oiseaux); 3) que le plus grand nombre de cultures de champignons a été prélevé chez le guillemot de Brünnich; et 4) que d’après une analyse de correspondance multiple, il y a une certaine indication que les échantillons de l’eider à tête grise et du guillemot de Brünnich recueillis dans le Bas-Arctique comprenaient des communautés fongiques distinctes qui différaient les unes des autres ainsi que des autres oiseaux échantillonnés. Même si la taille de nos échantillons était petite, les premières tendances ressortant du point (4) démontrent qu’il y a lieu de faire des études plus poussées afin de déterminer si les différences entre les communautés fongiques sont influencées par la variation des écologies connues des hôtes aviaires et des champignons identifiés

Sympatric ecological speciation meets pyrosequencing: sampling the transcriptome of the apple maggot Rhagoletis pomonella

Background The full power of modern genetics has been applied to the study of speciation in only a small handful of genetic model species - all of which speciated allopatrically. Here we report the first large expressed sequence tag (EST) study of a candidate for ecological sympatric speciation, the apple maggot Rhagoletis pomonella, using massively parallel pyrosequencing on the Roche 454-FLX platform. To maximize transcript diversity we created and sequenced separate libraries from larvae, pupae, adult heads, and headless adult bodies. Results We obtained 239,531 sequences which assembled into 24,373 contigs. A total of 6810 unique protein coding genes were identified among the contigs and long singletons, corresponding to 48% of all known Drosophila melanogaster protein-coding genes. Their distribution across GO classes suggests that we have obtained a representative sample of the transcriptome. Among these sequences are many candidates for potential R. pomonella speciation genes (or barrier genes ) such as those controlling chemosensory and life-history timing processes. Furthermore, we identified important marker loci including more than 40,000 single nucleotide polymorphisms (SNPs) and over 100 microsatellites. An initial search for SNPs at which the apple and hawthorn host races differ suggested at least 75 loci warranting further work. We also determined that developmental expression differences remained even after normalization; transcripts expected to show different expression levels between larvae and pupae in D. melanogaster also did so in R. pomonella. Preliminary comparative analysis of transcript presences and absences revealed evidence of gene loss in Drosophila and gain in the higher dipteran clade Schizophora. Conclusions These data provide a much needed resource for exploring mechanisms of divergence in this important model for sympatric ecological speciation. Our description of ESTs from a substantial portion of the R. pomonella transcriptome will facilitate future functional studies of candidate genes for olfaction and diapause-related life history timing, and will enable large scale expression studies. Similarly, the identification of new SNP and microsatellite markers will facilitate future population and quantitative genetic studies of divergence between the apple and hawthorn-infesting host races