Efficient computational techniques for modeling of transient releases following pipeline failures

This thesis describes the development and extensive testing of a numerical CFD model and a semi-analytical homogenous flow model for simulating the transient outflow following the failure of pressurised pipelines transporting hydrocarbon mixtures. This is important because these pipelines mainly convey highly flammable pressurised and hazardous inventories and their failure can be catastrophic. Therefore an accurate modelling of the discharge rate is of paramount importance to pipeline operators for safety and consequence analysis. The CFD model involves the development of a Pressure-Entropy (P-S) interpolation scheme followed by its coupling with the fluid flow conservation equations using Pressure (P), Entropy (S), Velocity (U) as the primitive variables, herewith termed as the PSUC. The Method of Characteristics along with the Peng Robinson Equation of State are in turn employed for the numerical solution of the conservation equations. The performance of the PSUC is tested against available experimental data as well as hypothetical test cases involving the failure of realistic pipelines containing gas, two-phase and flashing hydrocarbons. In all cases the PSUC predictions are found to produce reasonably good agreement with the published experimental data, remaining in excellent accord with the previously developed but computationally demanding PHU based CFD model predictions employing Pressure (P), Enthalpy (H) and Velocity (U) as the primitive variables. For all the cases presented, PSUC consistently produces significant saving in CPU run-time with average reduction of ca. 84% as compared to the previously developed PHU based CFD model. The development and extensive testing of a semi-analytical Vessel Blowdown Model (VBM) aimed at reducing the computational run-time to negligible levels is presented next. This model, based on approximation of the pipeline as a vessel discharging through an orifice, handles both isolated flows as well as un-isolated flows where the flow in the pipeline is terminated upon puncture failure or at any time thereafter. The range of applicability of the VBM is investigated based on the comparison of its predictions against those obtained using the established but computationally demanding PHU based numerical simulation. The parameters studied to perform testing the applicability of the VBM include the ratio of the puncture to pipe diameter (0.1 – 0.4), initial line pressure (21 bara, 50 bara and 100 bara) and pipeline length (100 m, 1 km and 5 km). The simulation results reveal that the accuracy of the VBM improves with increasing pipeline length and decreasing line pressure and puncture to pipe diameter ratio. Surprisingly the VBM produces closer agreement with the PHU based CFD predictions for two-phase mixtures as compared to permanent gases. This is shown to be a consequence of the depressurisation induced cooling of the bulk fluid which is not accounted for in the VBM. Finally, development and testing of the Un-isolated Vessel Blowdown Model (UVBM), as an extension of the VBM accounting for the impact of initial feed flow and fluid/wall heat transfer during puncture is presented. The performance of the UVBM is tested using a 10 km pipeline following a puncture along its length considering three failure scenarios. These include no initial feed flow, cessation of feed flow upon failure and its termination at any set time thereafter. For the ranges tested, the VBM and UVBM are shown to present considerable promise given their significantly shorter computational run-time compared to the PHU based numerical technique whilst maintaining the same level of accuracy

Short communication: optimization of semi-quantitative RT PCR analysis for CPT I gene expression in rainbow trout (Oncorhynchus mykiss)

A key enzyme in mitochondrial β¬oxidation, carnitine palmitoyltransferase (CPT) I, is transcriptionally regulated in mammals, but this enzyme also experiences allosteric modulations (Harano et al., 1985; Murthy and Pande, 1987; Bezaire et al., 2004). CPT I is located on the inner side of the outer mitochondrial membrane and catalyses the conversion of acyl-CoA to fatty acylcarnitine (Kerner and Hoppel, 2000; Price et al., 2000). Quantitative RT-PCR is a reliable technique for measuring transcripts in small amounts of tissue (Spriewald et al., 2000). With this technique, multiple mRNAs can be assayed simultaneously in a relatively short period of time. Here we describe the standard procedure, optimized in our laboratory, to assess CPT I levels with β¬actin as an internal control in rainbow trout, and all the necessary controls to ensure a quantitative analysis. RNA Extraction and Reverse Transcription Total cellular RNA was isolated from liver of rainbow trout using RNX reagent (Cinnagen-Iran). To obtain cDNA, 1 µg of total RNA was subjected to reverse transcription polymerase chain reaction (RT-PCR) with MuLV reverse transcriptase using the RevertAidTM M¬MuLV Reverse Transcriptase Kit (Fermentase Life Science, Germany) and random hexamer primer. Reaction conditions in the reverse transcription step are mostly dependent on the enzyme and the primers of choice. Whereas other protocols to require the use of specific primers, we prefer to reverse transcribe the total RNA population with random hexamers so that different PCR analyses could be performed on the same cDNA sample

Interpretable Per Case Weighted Ensemble Method for Cancer Associations

BACKGROUND: Molecular measurements from cancer patients such as gene expression and DNA methylation can be influenced by several external factors. This makes it harder to reproduce the exact values of measurements coming from different laboratories. Furthermore, some cancer types are very heterogeneous, meaning that there might be different underlying causes for the same type of cancer among different individuals. If a model does not take potential biases in the data into account, this can lead to problems when trying to predict the stage of a certain cancer type. This is especially true when these biases differ between the training and test set. RESULTS: We introduce a method that can estimate this bias on a per-feature level and incorporate calculated feature confidences into a weighted combination of classifiers with disjoint feature sets. In this way, the method provides a prediction that is adjusted for the potential biases on a per-patient basis, providing a personalized prediction for each test patient. The new method achieves state-of-the-art performance on many different cancer data sets with measured DNA methylation or gene expression. Moreover, we show how to visualize the learned classifiers to display interesting associations with the target label. Applied to a leukemia data set, our method finds several ribosomal proteins associated with the risk group, which might be interesting targets for follow-up studies. This discovery supports the hypothesis that the ribosomes are a new frontier in genadaptivelearninge regulation. CONCLUSION: We introduce a new method for robust prediction of phenotypes from molecular measurements such as DNA methylation or gene expression. Furthermore, the visualization capabilities enable exploratory analysis on the learnt dependencies and pave the way for a personalized prediction of phenotypes. The software is available under GPL2+ from https://github.com/adrinjalali/Network-Classifier/tree/v1.0. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2647-9) contains supplementary material, which is available to authorized users

On the existence of chaotic circumferential waves in spinning disks

We use a third-order perturbation theory and Melnikov's method to prove the existence of chaos in spinning circular disks subject to a lateral point load. We show that the emergence of transverse homoclinic and heteroclinic points respectively lead to a random reversal in the traveling direction of circumferential waves and a random phase shift of magnitude $\pi$ for both forward and backward wave components. These long-term phenomena occur in imperfect low-speed disks sufficiently far from fundamental resonances.Comment: 8 pages, 5 figures, to appear in CHAOS (Volume 17, Issue 2, June 2007

An Investigation of High Performance Heterojunction Silicon Solar Cell Based on n-type Si Substrate

In this study, high efficient heterojunction crystalline silicon solar cells without using an intrinsic layer were systematically investigated. The effect of various parameters such as work function of transparent conductive oxide (ϕTCO), density of interface defects, emitter and crystalline silicon thickness on heterojunction silicon solar cell performance was studied. In addition, the effect of band bending and internal electric field on solar cell performance together with the dependency of cell performance on work function and reflectance of the back contact were investigated in full details. The optimum values of the solar cell properties for the highest efficiency are presented based on the results of the current study. The results represent a complete set of optimum values for a heterojunction solar cell with high efficiency up to the 24.1 % with VOC = 0.87 V and JSC =32.69 mA⋅cm – 2

An Investigation of High Performance Heterojunction Silicon Solar Cell Based on n-type Si Substrate

In this study, high efficient heterojunction crystalline silicon solar cells without using an intrinsic layer were systematically investigated. The effect of various parameters such as work function of transparent conductive oxide (ϕTCO), density of interface defects, emitter and crystalline silicon thickness on heterojunction silicon solar cell performance was studied. In addition, the effect of band bending and internal electric field on solar cell performance together with the dependency of cell performance on work function and reflectance of the back contact were investigated in full details. The optimum values of the solar cell properties for the highest efficiency are presented based on the results of the current study. The results represent a complete set of optimum values for a heterojunction solar cell with high efficiency up to the 24.1 % with VOC = 0.87 V and JSC =32.69 mA⋅cm – 2

Partially Blind Domain Adaptation for Age Prediction from {DNA} Methylation Data

Over the last years, huge resources of biological and medical data have become available for research. This data offers great chances for machine learning applications in health care, e.g. for precision medicine, but is also challenging to analyze. Typical challenges include a large number of possibly correlated features and heterogeneity in the data. One flourishing field of biological research in which this is relevant is epigenetics. Here, especially large amounts of DNA methylation data have emerged. This epigenetic mark has been used to predict a donor's 'epigenetic age' and increased epigenetic aging has been linked to lifestyle and disease history. In this paper we propose an adaptive model which performs feature selection for each test sample individually based on the distribution of the input data. The method can be seen as partially blind domain adaptation. We apply the model to the problem of age prediction based on DNA methylation data from a variety of tissues, and compare it to a standard model, which does not take heterogeneity into account. The standard approach has particularly bad performance on one tissue type on which we show substantial improvement with our new adaptive approach even though no samples of that tissue were part of the training data

An investigation on fish parasites in Hanna Wetland, Semirom, Isfahan Province

As a part of a major ecological study of Hanna Wetland, Semirum Region, Isfahan Province, parasitic infestation of 3 native and one introduced fish species were investigated. A total of 120 fish specimens were collected by both cast net and a series of gillnets between fall and winter 2007, and spring and summer 2008. Some of the observed parasites are reported for the first time as new host records of: Trichodina perforata on gill and skin of Carassius auratus auratus and three species of leeches namely: Glossiphonia heteroclite, Thromyzon tessulatum and Hemiclepsis marginata on the skin and fin bases of Capoeta damascina. Moreover, 14 internal and external parasites including: one protozoan; Ichthyophthirius multifiliis and two myxosporeans; Myxobolus varicorhini, Myxobolus sp., three monogeneans; Dactylogyrus lenkoran, Dactylogyrus intermedius and Gyrodactylus sp., two immature digeneans; Diplostomum spathaceum, Tylodephys sp., two mature digeneans; Allocreadium isoporum and A. layman, one unknown cyst, one Acanthocephalan; Acanthocephalorhynchoides sp., one cestoda; Khawia armeniaca. The highest prevalence of Diplostomum spathaceum (100%) was observed in Aphanius isfahanensis and Alburnus sp. However, the lowest prevalence was related to A. layman in Capoeta damascina in winter (0%), and autumn and spring (11%). Leeches infections were only observed in Capoeta damascina and Alburnus sp. in winter and summer, respectively. The maximum average (±SD) infection intensity belonged to K. armeniaca in intestine of C. damascina in spring (12.50±3.40, range: 8-16). Among the parasites identified in the region, D. spathaceum showed the highest mean (±SD) abundance (41.67±11.79) in C. auratus auratus in spring. In general, a relatively high diversity of fish parasitic fauna exists in this water body which could jeopardize fish populations and the whole ecosystem if the ecological status of the Hanna Wetland is neglected