Search results for: parameter

Authors: Zhaoyang Liu, Detao Qin, Darren Delai Sun

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The onshore production of oil and gas (for example, shale gas) generates large quantities of wastewater, referred to be ‘produced water’, which contains high contents of oils and salts. The direct discharge of produced water, if not appropriately treated, can be toxic to the environment and human health. Membrane filtration has been deemed as an environmental-friendly and cost-effective technology for treating oily wastewater. However, conventional polymeric membranes have their drawbacks of either low salt rejection rate or high membrane fouling tendency when treating oily wastewater. Recent years, forward osmosis (FO) membrane filtration has emerged as a promising technology with its unique advantages of low operation pressure and less membrane fouling tendency. However, until now there is still no report about FO membranes specially designed and fabricated for treating the oily and salty produced water. In this study, a novel nanocomposite FO membrane was developed specially for treating oil- and salt-polluted produced water. By leveraging the recent advance of nanomaterials and nanotechnology, this nanocomposite FO membrane was designed to be made of double layers: an underwater oleophobic selective layer on top of a nanomaterial infused polymeric support layer. Wherein, graphene oxide (GO) nanosheets were selected to add into the polymeric support layer because adding GO nanosheets can optimize the pore structures of the support layer, thus potentially leading to high water flux for FO membranes. In addition, polyvinyl alcohol (PVA) hydrogel was selected as the selective layer because hydrated and chemically-crosslinked PVA hydrogel is capable of simultaneously rejecting oil and salt. After nanocomposite FO membranes were fabricated, the membrane structures were systematically characterized with the instruments of TEM, FESEM, XRD, ATR-FTIR, surface zeta-potential and Contact angles (CA). The membrane performances for treating produced waters were tested with the instruments of TOC, COD and Ion chromatography. The working mechanism of this new membrane was also analyzed. Very promising experimental results have been obtained. The incorporation of GO nanosheets can reduce internal concentration polarization (ICP) effect in the polymeric support layer. The structural parameter (S value) of the new FO membrane is reduced by 23% from 265 ± 31 μm to 205 ± 23 μm. The membrane tortuosity (τ value) is decreased by 20% from 2.55 ± 0.19 to 2.02 ± 0.13 μm, which contributes to the decrease of S value. Moreover, the highly-hydrophilic and chemically-cross-linked hydrogel selective layer present high antifouling property under saline oil/water emulsions. Compared with commercial FO membrane, this new FO membrane possesses three times higher water flux, higher removal efficiencies for oil (>99.9%) and salts (>99.7% for multivalent ions), and significantly lower membrane fouling tendency (<10%). To our knowledge, this is the first report of a nanocomposite FO membrane with the combined merits of high salt rejection, high oil repellency and high water flux for treating onshore oil/gas produced waters. Due to its outstanding performance and ease of fabrication, this novel nanocomposite FO membrane possesses great application potential in wastewater treatment industry.

Keywords: nanocomposite, membrane, polymer, graphene oxide

Procedia PDF Downloads 227

Authors: Piyush Sharma, Laltu Chandra, P. S. Ghoshdastidar, Rajiv Shekhar

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Metals processing operations such as melting and heat treatment of metals are energy-intensive, requiring temperatures greater than 500oC. The desired temperature in these industrial furnaces is attained by circulating electrically-heated air. In most of these furnaces, electricity produced from captive coal-based thermal power plants is used. Solar thermal energy could be a viable heat source in these furnaces. A retrofitted solar convective furnace (SCF) concept, which uses solar thermal generated hot air, has been proposed. Critical to the success of a SCF is the design of an open volumetric air receiver (OVAR), which can heat air in excess of 800oC. The OVAR is placed on top of a tower and receives concentrated solar radiation from a heliostat field. Absorbers, mixer assembly, and the return air flow chamber (RAFC) are the major components of an OVAR. The absorber is a porous structure that transfers heat from concentrated solar radiation to ambient air, referred to as primary air. The mixer ensures uniform air temperature at the receiver exit. Flow of the relatively cooler return air in the RAFC ensures that the absorbers do not fail by overheating. In an earlier publication, the detailed design basis, fabrication, and characterization of a 2 kWth open volumetric air receiver (OVAR) based laboratory solar air tower simulator was presented. Development of an experimentally-validated, CFD based mathematical model which can ultimately be used for the design and scale-up of an OVAR has been the major objective of this investigation. In contrast to the published literature, where flow and heat transfer have been modeled primarily in a single absorber module, the present study has modeled the entire receiver assembly, including the RAFC. Flow and heat transfer calculations have been carried out in ANSYS using the LTNE model. The complex return air flow pattern in the RAFC requires complicated meshes and is computational and time intensive. Hence a simple, realistic 1-D mathematical model, which circumvents the need for carrying out detailed flow and heat transfer calculations, has also been proposed. Several important results have emerged from this investigation. Circumferential electrical heating of absorbers can mimic frontal heating by concentrated solar radiation reasonably well in testing and characterizing the performance of an OVAR. Circumferential heating, therefore, obviates the need for expensive high solar concentration simulators. Predictions suggest that the ratio of power on aperture (POA) and mass flow rate of air (MFR) is a normalizing parameter for characterizing the thermal performance of an OVAR. Increasing POA/MFR increases the maximum temperature of air, but decreases the thermal efficiency of an OVAR. Predictions of the 1-D mathematical are within 5% of ANSYS predictions and computation time is reduced from ~ 5 hours to a few seconds.

Keywords: absorbers, mixer assembly, open volumetric air receiver, return air flow chamber, solar thermal energy

Procedia PDF Downloads 168

Authors: Marcel Meinhardt, Manfred Keuser, Thomas Braml

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Cracking of reinforced concrete is a complex phenomenon induced by direct loads or restraints affecting reinforced concrete structures as soon as the tensile strength of the concrete is exceeded. Hence it is important to predict where cracks will be located and how they will propagate. The bond theory and the crack formulas in the actual design codes, for example, DIN EN 1992-1-1, are all based on the assumption that the reinforcement bars are embedded in homogeneous concrete without taking into account the influence of transverse reinforcement and the real stress situation. However, it can often be observed that real structures such as walls, slabs or beams show a crack spacing that is orientated to the transverse reinforcement bars or to the stirrups. In most Finite Element Analysis studies, the smeared crack approach is used for crack prediction. The disadvantage of this model is that the typical strain localization of a crack on element level can’t be seen. The crack propagation in concrete is a discontinuous process characterized by different factors such as the initial random distribution of defects or the scatter of material properties. Such behavior presupposes the elaboration of adequate models and methods of simulation because traditional mechanical approaches deal mainly with average material parameters. This paper concerned with the modelling of the initiation and the propagation of cracks in reinforced concrete structures considering the influence of transverse reinforcement and the real stress distribution in reinforced concrete (R/C) beams/plates in bending action. Therefore, a parameter study was carried out to investigate: (I) the influence of the transversal reinforcement to the stress distribution in concrete in bending mode and (II) the crack initiation in dependence of the diameter and distance of the transversal reinforcement to each other. The numerical investigations on the crack initiation and propagation were carried out with a 2D reinforced concrete structure subjected to quasi static loading and given boundary conditions. To model the uncertainty in the tensile strength of concrete in the Finite Element Analysis correlated normally and lognormally distributed random filed with different correlation lengths were generated. The paper also presents and discuss different methods to generate random fields, e.g. the Covariance Matrix Decomposition Method. For all computations, a plastic constitutive law with softening was used to model the crack initiation and the damage of the concrete in tension. It was found that the distributions of crack spacing and crack widths are highly dependent of the used random field. These distributions are validated to experimental studies on R/C panels which were carried out at the Laboratory for Structural Engineering at the University of the German Armed Forces in Munich. Also, a recommendation for parameters of the random field for realistic modelling the uncertainty of the tensile strength is given. The aim of this research was to show a method in which the localization of strains and cracks as well as the influence of transverse reinforcement on the crack initiation and propagation in Finite Element Analysis can be seen.

Keywords: crack initiation, crack modelling, crack propagation, cracks, numerical simulation, random fields, reinforced concrete, stochastic

Procedia PDF Downloads 117

Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

Procedia PDF Downloads 112

Authors: Leo Nnamdi Ozurumba-Dwight

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Single-cell genomic analytical systems have proved to be a platform to isolate bulk cells into selected single cells for genomic, proteomic, and related metabolomic studies. This is enabling systematic investigations of the level of heterogeneity in a diverse and wide pool of cell populations. Single cell technologies, embracing techniques such as high parameter flow cytometry, single-cell sequencing, and high-resolution images are playing vital roles in these investigations on messenger ribonucleic acid (mRNA) molecules and related gene expressions in tracking the nature and course of disease conditions. This entails targeted molecular investigations on unit cells that help us understand cell behavoiur and expressions, which can be examined for their health implications on the health state of patients. One of the vital good sides of single-cell RNA sequencing (scRNA seq) is its probing capacity to detect deranged or abnormal cell populations present within homogenously perceived pooled cells, which would have evaded cursory screening on the pooled cell populations of biological samples obtained as part of diagnostic procedures. Despite conduction of just single-cell transcriptome analysis, scRNAseq now permits comparison of the transcriptome of the individual cells, which can be evaluated for gene expressional patterns that depict areas of heterogeneity with pharmaceutical drug discovery and clinical treatment applications. It is vital to strictly work through the tools of investigations from wet lab to bioinformatics and computational tooled analyses. In the precise steps for scRNAseq, it is critical to do thorough and effective isolation of viable single cells from the tissues of interest using dependable techniques (such as FACS) before proceeding to lysis, as this enhances the appropriate picking of quality mRNA molecules for subsequent sequencing (such as by the use of Polymerase Chain Reaction machine). Interestingly, scRNAseq can be deployed to analyze various types of biological samples such as embryos, nervous systems, tumour cells, stem cells, lymphocytes, and haematopoietic cells. In haematopoietic cells, it can be used to stratify acute myeloid leukemia patterns in patients, sorting them out into cohorts that enable re-modeling of treatment regimens based on stratified presentations. In immunotherapy, it can furnish specialist clinician-immunologist with tools to re-model treatment for each patient, an attribute of precision medicine. Finally, the good predictive attribute of scRNAseq can help reduce the cost of treatment for patients, thus attracting more patients who would have otherwise been discouraged from seeking quality clinical consultation help due to perceived high cost. This is a positive paradigm shift for patients’ attitudes primed towards seeking treatment.

Keywords: immunotherapy, transcriptome, re-modeling, mRNA, scRNA-seq

Procedia PDF Downloads 144

Authors: Kamal Agrawal, Ved Prakash Nayak, Akshay Patil

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Raipur is known as a city of water bodies. The city had around 200 man-made and natural lakes of varying sizes. These structures were constructed to collect rainwater and control flooding in the city. Due to the transition from community participation to state government, as well as rapid urbanisation, Raipur now has only about 80 lakes left. Rapid and unplanned growth has resulted in pollution, encroachment, and eutrophication of the city's lakes. The state government keeps these lakes in good condition by cleaning them and proposing lakefront developments. However, maintaining individual lakes is insufficient because urban lakes are not distinct entities. It is a system comprised of the lake, shore, catchment, and other components. While Urban lake system (ULS) is a combination of multiple such lake systems interacting in a complex urban setting. Thus, the project aims to propose a co-evolution model for urban lake systems (ULS) and rapid urbanization in Raipur. The goals are to comprehend the ULS and to identify elements and dimensions of urbanization that influence the ULS. Evaluate the impact of rapid urbanization on the ULS & vice versa in the study area. Determine how to maximize the positive impact while minimizing the negative impact identified in the study area. Propose short-, medium-, and long-term planning interventions to support the ULS's co-evolution with rapid urbanization. A complexity approach is used to investigate the ULS. It is a technique for understanding large, complex systems. A complex system is one with many interconnected and interdependent elements and dimensions. Thus, elements of ULS and rapid urbanization are identified through a literature study to evaluate statements of their impacts (Beneficial/ Adverse) on one another. Rapid urbanization has been identified as having elements such as demography, urban legislation, informal settlement, urban infrastructure, and tourism. Similarly, the catchment area of the lake, the lake's water quality, the water spread area, and lakefront developments are all being impacted by rapid urbanisation. These nine elements serve as parameters for the subsequent analysis. Elements are limited to physical parameters only. The city has designated a study area based on the definition provided by the National Plan for the Conservation of Aquatic Ecosystems. Three lakes are discovered within a one-kilometer radius, establishing a tiny urban lake system. Because the condition of a lake is directly related to the condition of its catchment area, the catchment area of these three lakes is delineated as the study area. Data is collected to identify impact statements, and the interdependence diagram generated between the parameters yields results in terms of interlinking between each parameter and their impact on the system as a whole. The planning interventions proposed for the ULS and rapid urbanisation co-evolution model include spatial proposals as well as policy recommendations for the short, medium, and long term. This study's next step will be to determine how to implement the proposed interventions based on the availability of resources, funds, and governance patterns.

Keywords: urban lake system, co-evolution, rapid urbanization, complex system

Procedia PDF Downloads 48

Authors: Francesca Marsili

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The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

Procedia PDF Downloads 314

Authors: Fatih Kılıç, Burak Birol, Necmettin Maraşlı

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The directional solidification process is generally used for homogeneous compound production, single crystal growth, and refining (zone refining), etc. processes. The most important two parameters that control eutectic structures are temperature gradient and grain growth rate which are called as solidification parameters The solidification behavior and microstructure characteristics is an interesting topic due to their effects on the properties and performance of the alloys containing eutectic compositions. The solidification behavior of multicomponent and multiphase systems is an important parameter for determining various properties of these materials. The researches have been conducted mostly on the solidification of pure materials or alloys containing two phases. However, there are very few studies on the literature about multiphase reactions and microstructure formation of multicomponent alloys during solidification. Because of this situation, it is important to study the microstructure formation and the thermodynamical, thermophysical and microstructural properties of these alloys. The production process is difficult due to easy oxidation of magnesium and therefore, there is not a comprehensive study concerning alloys containing high Mg (> 30 wt.% Mg). With the increasing amount of Mg inside Al alloys, the specific weight decreases, and the strength shows a slight increase, while due to formation of β-Al8Mg5 phase, ductility lowers. For this reason, production, examination and development of high Mg containing alloys will initiate the production of new advanced engineering materials. The original value of this research can be described as obtaining high Mg containing (> 30% Mg) Al based multicomponent alloys by melting under vacuum; controlled directional solidification with various growth rates at a constant temperature gradient; and establishing relationship between solidification rate and microstructural, mechanical, electrical and thermal properties. Therefore, within the scope of this research, some > 30% Mg containing ternary or quaternary Al alloy compositions were determined, and it was planned to investigate the effects of directional solidification rate on the mechanical, electrical and thermal properties of these alloys. Within the scope of the research, the influence of the growth rate on microstructure parameters, microhardness, tensile strength, electrical conductivity and thermal conductivity of directionally solidified high Mg containing Al-32,2Mg-0,37Si; Al-30Mg-12Zn; Al-32Mg-1,7Ni; Al-32,2Mg-0,37Fe; Al-32Mg-1,7Ni-0,4Si; Al-33,3Mg-0,35Si-0,11Fe (wt.%) alloys with wide range of growth rate (50-2500 µm/s) and fixed temperature gradient, will be investigated. The work can be planned as; (a) directional solidification of Al-Mg based Al-Mg-Si, Al-Mg-Zn, Al-Mg-Ni, Al-Mg-Fe, Al-Mg-Ni-Si, Al-Mg-Si-Fe within wide range of growth rates (50-2500 µm/s) at a constant temperature gradient by Bridgman type solidification system, (b) analysis of microstructure parameters of directionally solidified alloys by using an optical light microscopy and Scanning Electron Microscopy (SEM), (c) measurement of microhardness and tensile strength of directionally solidified alloys, (d) measurement of electrical conductivity by four point probe technique at room temperature (e) measurement of thermal conductivity by linear heat flow method at room temperature.

Keywords: directional solidification, electrical conductivity, high Mg containing multicomponent Al alloys, microhardness, microstructure, tensile strength, thermal conductivity

Procedia PDF Downloads 239

Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km², 5 km² and 1 km² horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m^-3) and RMSE (20 – 30 µg.m^-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: land use, spatial resolution, WRF-Chem, air quality assessment

Procedia PDF Downloads 129

Authors: Chuyu Huang, Itsuki Minemi, Kuanlin Chen, Yuki Hirose

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It remains unclear how language speakers are able to perceive phonological contrasts that do not exist on their own. This experiment uses the vowel-length distinction in Japanese, which is phonologically contrastive and co-occurs with tonal change in some cases. For speakers whose first language does not distinguish vowel length, contrastive duration is usually misperceived, e.g., Mandarin speakers. Two alternative hypotheses for how Mandarin speakers would perceive a phonological contrast that does not exist in their language make different predictions. The stress parameter model does not have a clear prediction about the impact of tonal type. Mandarin speakers will likely be not able to perceive vowel length as well as Japanese native speakers do, but the performance might not correlate to tonal type because the prosody of their language is distinctive, which requires users to encode lexical prosody and notice subtle differences in word prosody. By contrast, cue-based phonetic models predict that Mandarin speakers may rely on pitch differences, a secondary cue, to perceive vowel length. Two groups of Mandarin speakers, including naive non-Japanese speakers and beginner learners, were recruited to participate in an AX discrimination task involving two Japanese sound stimuli that contain a phonologically contrastive environment. Participants were asked to indicate whether the two stimuli containing a vowel-length contrast (e.g., maapero vs. mapero) sound the same. The experiment was bifactorial. The first factor contrasted three syllabic positions (syllable position; initial/medial/final), as it would be likely to affect the perceptual difficulty, as seen in previous studies, and the second factor contrasted two pitch types (accent type): one with accentual change that could be distinguished with the lexical tones in Mandarin (the different condition), with the other group having no tonal distinction but only differing in vowel length (the same condition). The overall results showed that a significant main effect of accent type by applying a linear mixed-effects model (β = 1.48, SE = 0.35, p < 0.05), which implies that Mandarin speakers tend to more successfully recognize vowel-length differences when the long vowel counterpart takes on a tone that exists in Mandarin. The interaction between the accent type and the syllabic position is also significant (β = 2.30, SE = 0.91, p < 0.05), showing that vowel lengths in the different conditions are more difficult to recognize in the word-final case relative to the initial condition. The second statistical model, which compares naive speakers to beginners, was conducted with logistic regression to test the effects of the participant group. A significant difference was found between the two groups (β = 1.06, 95% CI = [0.36, 2.03], p < 0.05). This study shows that: (1) Mandarin speakers are likely to use pitch cues to perceive vowel length in a non-native language, which is consistent with the cue-based approaches; (2) an exposure effect was observed: the beginner group achieved a higher accuracy for long vowel perception, which implied the exposure effect despite the short period of language learning experience.

Keywords: cue-based perception, exposure effect, prosodic perception, vowel duration

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Authors: Zeradam Yeshiwas, A. Krishnaia

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The aim of this study is to verify the resulting surface roughness of parts formed by the Single-Point Incremental Forming (SPIF) process for an ISO 3574 Drawing Quality Cold Rolled CR2 Steel. The chemical composition of drawing quality Cold Rolled CR2 steel is comprised of 0.12 percent of carbon, 0.5 percent of manganese, 0.035 percent of sulfur, 0.04 percent phosphorous, and the remaining percentage is iron with negligible impurities. The experiments were performed on a 3-axis vertical CNC milling machining center equipped with a tool setup comprising a fixture and forming tools specifically designed and fabricated for the process. The CNC milling machine was used to transfer the tool path code generated in Mastercam 2017 environment into three-dimensional motions by the linear incremental progress of the spindle. The blanks of Drawing Quality Cold Rolled CR2 steel sheets of 1 mm of thickness have been fixed along their periphery by a fixture and hardened high-speed steel (HSS) tools with a hemispherical tip of 8, 10 and 12mm of diameter were employed to fabricate sample parts. To investigate the surface roughness, hyperbolic-cone shape specimens were fabricated based on the chosen experimental design. The effect of process parameters on the surface roughness was studied using three important process parameters, i.e., tool diameter, feed rate, and step depth. In this study, the Taylor-Hobson Surtronic 3+ surface roughness tester profilometer was used to determine the surface roughness of the parts fabricated using the arithmetic mean deviation (Rₐ). In this instrument, a small tip is dragged across a surface while its deflection is recorded. Finally, the optimum process parameters and the main factor affecting surface roughness were found using the Taguchi design of the experiment and ANOVA. A Taguchi experiment design with three factors and three levels for each factor, the standard orthogonal array L9 (3³) was selected for the study using the array selection table. The lowest value of surface roughness is significant for surface roughness improvement. For this objective, the ‘‘smaller-the-better’’ equation was used for the calculation of the S/N ratio. The finishing roughness parameter Ra has been measured for the different process combinations. The arithmetic means deviation (Rₐ) was measured via the experimental design for each combination of the control factors by using Taguchi experimental design. Four roughness measurements were taken for a single component and the average roughness was taken to optimize the surface roughness. The lowest value of Rₐ is very important for surface roughness improvement. For this reason, the ‘‘smaller-the-better’’ Equation was used for the calculation of the S/N ratio. Analysis of the effect of each control factor on the surface roughness was performed with a ‘‘S/N response table’’. Optimum surface roughness was obtained at a feed rate of 1500 mm/min, with a tool radius of 12 mm, and with a step depth of 0.5 mm. The ANOVA result shows that step depth is an essential factor affecting surface roughness (91.1 %).

Keywords: incremental forming, SPIF, drawing quality steel, surface roughness, roughness behavior

Procedia PDF Downloads 38

Authors: Mohammed Makha, Jakob Heier, Frank Nüesch, Roland Hany

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Organic solar cells (OSCs) have made rapid progress and currently achieve power conversion efficiencies (PCE) of over 10%. OSCs have several merits over other direct light-to-electricity generating cells and can be processed at low cost from solution on flexible substrates over large areas. Moreover, combining organic semiconductors with transparent and conductive electrodes allows for the fabrication of semitransparent OSCs (SM-OSCs). For SM-OSCs the challenge is to achieve a high average visible transmission (AVT) while maintaining a high short circuit current (Jsc). Typically, Jsc of SM-OSCs is smaller than when using an opaque metal top electrode. This is because the non-absorbed light during the first transit through the active layer and the transparent electrode is forward-transmitted out of the device. Recently, OSCs using a ternary blend of organic materials have received attention. This strategy was pursued to extend the light harvesting over the visible range. However, it is a general challenge to manipulate the performance of ternary OSCs in a predictable way, because many key factors affect the charge generation and extraction in ternary solar cells. Consequently, the device performance is affected by the compatibility between the blend components and the resulting film morphology, the energy levels and bandgaps, the concentration of the guest material and its location in the active layer. In this work, we report on a solvent-free lamination process for the fabrication of efficient and semitransparent ternary blend OSCs. The ternary blend was composed of PC70BM and the electron donors PBDTTT-C and an NIR cyanine absorbing dye (Cy7T). Using an opaque metal top electrode, a PCE of 6% was achieved for the optimized binary polymer: fullerene blend (AVT = 56%). However, the PCE dropped to ~2% when decreasing (to 30 nm) the active film thickness to increase the AVT value (75%). Therefore we resorted to the ternary blend and measured for non-transparent cells a PCE of 5.5% when using an active polymer: dye: fullerene (0.7: 0.3: 1.5 wt:wt:wt) film of 95 nm thickness (AVT = 65% when omitting the top electrode). In a second step, the optimized ternary blend was used of the fabrication of SM-OSCs. We used a plastic/metal substrate with a light transmission of over 90% as a transparent electrode that was applied via a lamination process. The interfacial layer between the active layer and the top electrode was optimized in order to improve the charge collection and the contact with the laminated top electrode. We demonstrated a PCE of 3% with AVT of 51%. The parameter space for ternary OSCs is large and it is difficult to find the best concentration ratios by trial and error. A rational approach for device optimization is the construction of a ternary blend phase diagram. We discuss our attempts to construct such a phase diagram for the PBDTTT-C: Cy7T: PC70BM system via a combination of using selective Cy7T selective solvents and atomic force microscopy. From the ternary diagram suitable morphologies for efficient light-to-current conversion can be identified. We compare experimental OSC data with these predictions.

Keywords: organic photovoltaics, ternary phase diagram, ternary organic solar cells, transparent solar cell, lamination

Procedia PDF Downloads 241

Authors: K. C. Sharda

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Introduction: In the world, almost half of the population are lacking proper access to improved sanitation services. In Nepal, large number of people are living without access to any sanitation facility. Ecological sanitation toilet which is defined as water conserving and nutrient recycling system for use of human urine and excreta in agriculture would count a lot to utilize locally available resources, to regenerate soil fertility, to save national currency and to achieve the goal of elimination open defecation in country like Nepal. The objectives of the research were to test the efficacy of human urine for improving crop performance and to evaluate the feasibility of ecological sanitation in rural area of Central Nepal. Materials and Methods: The field investigation was carried out at Palung Village Development Committee (VDC) of Makawanpur District, Nepal from March – August, 2016. Five eco-san toilets in two villages (Angare and Bhot Khoriya) were constructed and questionnaire survey was carried out. During the questionnaire survey, respondents were asked about socio-economic parameters, farming practices, awareness of ecological sanitation and fertilizer value of human urine and excreta in agriculture. In prior to a field experiment, soil was sampled for analysis of basic characteristics. In the field experiment, cauliflower was cultivated for a month in the two sites to compare the fertilizer value of urine with chemical fertilizer and no fertilizer with three replications. The harvested plant samples were analyzed to understand the nutrient content in plant with different treatments. Results and Discussion: Eighty three percent respondents were engaged in agriculture growing mainly vegetables, which may raise the feasibility of ecological sanitation. In the study area, water deficiencies in dry season, high demand of chemical fertilizer, lack of sanitation awareness were found to be solved. The soil at Angare has sandier texture and lower nitrogen content compared to that in Bhot Khoriya. While the field experiment in Angare showed that the aboveground biomass of cauliflower in the urine fertilized plot were similar with that in the chemically fertilized plot and higher than those in the non-fertilized plots, no significant difference among the treatments were found in Bhot Khoriya. The more distinctive response of crop growth to the three treatments in the former might be attributed to the poorer soil productivity, which in turn could be caused by the poorer inherent soil fertility and the poorer past management by the farmer in Angare. Thus, use of urine as fertilizer could help poor farmers with low quality soil. The significantly different content of nitrogen and potassium in the plant samples among three treatments in Bhot Khoriya would require further investigation. When urine is utilized as a fertilizer, the productivity could be increased and the money to buy chemical fertilizer would be utilized in other livelihood activities. Ecological sanitation is feasible in the area with similar socio-economic parameter.

Keywords: cauliflower, chemical fertilizer, ecological sanitation, Nepal, urine

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Authors: Zulkifli, I. W. Eltara, Anawati

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Understanding the complementary roles of surface energy and roughness on natural nonwetting surfaces has led to the development of a number of biomimetic superhydrophobic surfaces, which exhibit apparent contact angles with water greater than 150 degrees and low contact angle hysteresis. However, superoleophobic surfaces—those that display contact angles greater than 150 degrees with organic liquids having appreciably lower surface tensions than that of water—are extremely rare. In addition to chemical composition and roughened texture, a third parameter is essential to achieve superoleophobicity, namely, re-entrant surface curvature in the form of overhang structures. The overhangs can be realized as fibers. Superoleophobic surfaces are appealing for example, antifouling, since purely superhydrophobic surfaces are easily contaminated by oily substances in practical applications, which in turn will impair the liquid repellency. On the other studied have demonstrate that such aqueous nanofibrillar gels are unexpectedly robust to allow formation of highly porous aerogels by direct water removal by freeze-drying, they are flexible, unlike most aerogels that suffer from brittleness, and they allow flexible hierarchically porous templates for functionalities, e.g. for electrical conductivity. No crosslinking, solvent exchange nor supercritical drying are required to suppress the collapse during the aerogel preparation, unlike in typical aerogel preparations. The aerogel used in current work is an ultralight weight solid material composed of native cellulose nanofibers. The native cellulose nanofibers are cleaved from the self-assembled hierarchy of macroscopic cellulose fibers. They have become highly topical, as they are proposed to show extraordinary mechanical properties due to their parallel and grossly hydrogen bonded polysaccharide chains. We demonstrate that superoleophobic nanocellulose aerogels coating by sol-gel method, the aerogel is capable of supporting a weight nearly 3 orders of magnitude larger than the weight of the aerogel itself. The load support is achieved by surface tension acting at different length scales: at the macroscopic scale along the perimeter of the carrier, and at the microscopic scale along the cellulose nanofibers by preventing soaking of the aerogel thus ensuring buoyancy. Superoleophobic nanocellulose aerogels have recently been achieved using unmodified cellulose nanofibers and using carboxy methylated, negatively charged cellulose nanofibers as starting materials. In this work, the aerogels made from unmodified cellulose nanofibers were subsequently treated with fluorosilanes. To complement previous work on superoleophobic aerogels, we demonstrate their application as cargo carriers on oil, gas permeability, plastrons, and drag reduction, and we show that fluorinated nanocellulose aerogels are high-adhesive superoleophobic surfaces. We foresee applications including buoyant, gas permeable, dirt-repellent coatings for miniature sensors and other devices floating on generic liquid surfaces.

Keywords: superoleophobic, nanocellulose, aerogel, sol-gel

Procedia PDF Downloads 319

Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: A. Rahim Baharudin, Nor Arinee binti Mat Saaud, Muhammad Afiq Azman, Farah Adiba A. Sani

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Objectives: This paper shares the case study on the engineering analysis, data analysis, and real-time data comparison for qualifying the stand wires' minimum breaking load and safe working load upon loadout operation for a new project and, at the same time, eliminate the risk due to discrepancies and unalignment of COMPANY Technical Standards to Industry Standards and Practices. This paper demonstrates “Lean Construction” for COMPANY’s Project by sustaining fit-for-purpose Technical Requirements of Loadout Strand Wire Factor of Safety (F.S). The case study utilizes historical engineering data from a few loadout operations by skidding methods from different projects. It is also demonstrating and qualifying the skidding wires' minimum breaking load and safe working load used for loadout operation for substructure and other facilities for the future. Methods: Engineering analysis and comparison of data were taken as referred to the international standard and internal COMPANY standard requirements. Data was taken from nine (9) previous projects for both topsides and jacket facilities executed at the several local fabrication yards where load out was conducted by three (3) different service providers with emphasis on four (4) basic elements: i) Industry Standards for Loadout Engineering and Operation Reference: COMPANY internal standard was referred to superseded documents of DNV-OS-H201 and DNV/GL 0013/ND. DNV/GL 0013/ND and DNVGL-ST-N001 do not mention any requirements of Strand Wire F.S of 4.0 for Skidding / Pulling Operations. ii) Reference to past Loadout Engineering and Execution Package: Reference was made to projects delivered by three (3) major offshore facilities operators. Strand Wire F.S observed ranges from 2.0 MBL (Min) to 2.5 MBL (Max). No Loadout Operation using the requirements of 4.0 MBL was sighted from the reference. iii) Strand Jack Equipment Manufacturer Datasheet Reference: Referring to Strand Jack Equipment Manufactured Datasheet by different loadout service providers, it is shown that the Designed F.S for the equipment is also ranging between 2.0 ~ 2.5. Eight (8) Strand Jack Datasheet Model was referred to, ranging from 15 Mt to 850 Mt Capacity; however, there are NO observations of designed F.S 4.0 sighted. iv) Site Monitoring on Actual Loadout Data and Parameter: Max Load on Strand Wire was captured during 2nd Breakout, which is during Static Condition of 12.9 MT / Strand Wire (67.9% Utilization). Max Load on Strand Wire for Dynamic Conditions during Step 8 and Step 12 is 9.4 Mt / Strand Wire (49.5% Utilization). Conclusion: This analysis and study demonstrated the adequacy of strand wires supplied by the service provider were technically sufficient in terms of strength, and via engineering analysis conducted, the minimum breaking load and safe working load utilized and calculated for the projects were satisfied and operated safely for the projects. It is recommended from this study that COMPANY’s technical requirements are to be revised for future projects’ utilization.

Keywords: construction, load out, minimum breaking load, safe working load, strand jacking, skidding

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Authors: Gopalasingam Daisan

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Landmines and ammunitions have been creating a significant threat to the people and animals, after the war, the landmines remain in the land and it plays a vital role in civilian’s security. Especially the Children are at the highest risk because they are curious. After all, an unexploded bomb can look like a tempting toy to an inquisitive child. The initial step of designing the UAS (Unmanned Aircraft Systems) for landmine detection is to choose an appropriate and effective sensor to locate the landmines and other unexploded ammunitions. The sensor weight and other components related to the sensor supporting device’s weight are taken as a payload weight. The mission requirement is to find the landmines in a particular area by making a proper path that will cover all the vicinity in the desired area. The weight estimation of the UAV (Unmanned Aerial Vehicle) can be estimated by various techniques discovered previously with good accuracy at the first phase of the design. The next crucial part of the design is to calculate the power requirement and the wing loading calculations. The matching plot techniques are used to determine the thrust-to-weight ratio, and this technique makes this process not only easiest but also precisely. The wing loading can be calculated easily from the stall equation. After these calculations, the wing area is determined from the wing loading equation and the required power is calculated from the thrust to weight ratio calculations. According to the power requirement, an appropriate engine can be selected from the available engine from the market. And the wing geometric parameter is chosen based on the conceptual sketch. The important steps in the wing design to choose proper aerofoil and which will ensure to create sufficient lift coefficient to satisfy the requirements. The next component is the tail; the tail area and other related parameters can be estimated or calculated to counteract the effect of the wing pitching moment. As the vertical tail design depends on many parameters, the initial sizing only can be done in this phase. The fuselage is another major component, which is selected based on the slenderness ratio, and also the shape is determined on the sensor size to fit it under the fuselage. The landing gear is one of the important components which is selected based on the controllability and stability requirements. The minimum and maximum wheel track and wheelbase can be determined based on the crosswind and overturn angle requirements. The minor components of the landing gear design and estimation are not the focus of this project. Another important task is to calculate the weight of the major components and it is going to be estimated using empirical relations and also the mass is added to each such component. The CG and moment of inertia are also determined to each component separately. The sensitivity of the weight calculation is taken into consideration to avoid extra material requirements and also reduce the cost of the design. Finally, the aircraft performance is calculated, especially the V-n (velocity and load factor) diagram for different flight conditions such as not disturbed and with gust velocity.

Keywords: landmine, UAS, matching plot, optimization

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Authors: Emily Rowe

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Introduction: Balance assessments can be used to help evaluate a person’s risk of falls, determine causes of balance deficits and inform intervention decisions. It is widely accepted that instrumented quantitative analysis can be more reliable and specific than semi-qualitative ordinal scales or itemised scoring methods. However, the uptake of quantitative methods is hindered by expense, lack of portability, and set-up requirements. During stepping, foot placement is actively coordinated with the body centre of mass (COM) kinematics during pre-initiation. Based on this, the potential to use COM velocity just prior to foot off and foot placement error as an outcome measure of dynamic balance is currently being explored using complex 3D motion capture. Inertial sensors and pressure mats might be more practical technologies for measuring these parameters in clinical settings. Objective: The aim of this study was to test the criterion validity and test-retest reliability of a synchronised inertial sensor and pressure mat-based approach to measure foot placement error and COM velocity while stepping. Methods: Trials were held with 15 healthy participants who each attended for two sessions. The trial task was to step onto one of 4 targets (2 for each foot) multiple times in a random, unpredictable order. The stepping target was cued using an auditory prompt and electroluminescent panel illumination. Data was collected using 3D motion capture and a combined inertial sensor-pressure mat system simultaneously in both sessions. To assess the reliability of each system, ICC estimates and their 95% confident intervals were calculated based on a mean-rating (k = 2), absolute-agreement, 2-way mixed-effects model. To test the criterion validity of the combined inertial sensor-pressure mat system against the motion capture system multi-factorial two-way repeated measures ANOVAs were carried out. Results: It was found that foot placement error was not reliably measured between sessions by either system (ICC 95% CIs; motion capture: 0 to >0.87 and pressure mat: <0.53 to >0.90). This could be due to genuine within-subject variability given the nature of the stepping task and brings into question the suitability of average foot placement error as an outcome measure. Additionally, results suggest the pressure mat is not a valid measure of this parameter since it was statistically significantly different from and much less precise than the motion capture system (p=0.003). The inertial sensor was found to be a moderately reliable (ICC 95% CIs >0.46 to >0.95) but not valid measure for anteroposterior and mediolateral COM velocities (AP velocity: p=0.000, ML velocity target 1 to 4: p=0.734, 0.001, 0.000 & 0.376). However, it is thought that with further development, the COM velocity measure validity could be improved. Possible options which could be investigated include whether there is an effect of inertial sensor placement with respect to pelvic marker placement or implementing more complex methods of data processing to manage inherent accelerometer and gyroscope limitations. Conclusion: The pressure mat is not a suitable alternative for measuring foot placement errors. The inertial sensors have the potential for measuring COM velocity; however, further development work is needed.

Keywords: dynamic balance, inertial sensors, portable, pressure mat, reliability, stepping, validity, wearables

Procedia PDF Downloads 114

Authors: E. Poupelloz, S. Gauffinet

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Ettringite Ca₆Al₂(SO₄)₃(OH)₁₂26H₂O is one of the major hydrates formed during cement hydration. Ettringite forms in Portland cement from the reaction between tricalcium aluminate Ca₃Al₂O₆ and calcium sulfate. Ettringite is also present in calcium sulfoaluminate cement in which it is the major hydrate, formed by the reaction between yeelimite Ca₄(AlO₂)₆SO₄ and calcium sulfate. About the formation of ettringite, numerous results are available in the literature even if some issues are still under discussion. However, almost all published work about ettringite was done on cementitious systems. Yet in cement, hydration reactions are very complex, the result of dissolution-precipitation processes and are submitted to various interactions. Understanding the formation process of a phase alone, here ettringite, is the first step to later understand the much more complex reactions happening in cement. This study is crucial for the comprehension of early cement hydration and physical behavior. Indeed formation of hydrates, in particular, ettringite, will have an influence on the rheological properties of the cement paste and on the need for admixtures. To make progress toward the understanding of existing phenomena, a specific study of nucleation and growth processes of ettringite was conducted. First ettringite nucleation was studied in ionic aqueous solutions, with controlled but different experimental conditions, as different supersaturation degrees (β), different pH or presence of exogenous ions. Through induction time measurements, interfacial ettringite crystals solution energies (γ) were determined. Growth of ettringite in supersaturated solutions was also studied through chain crystallization reactions. Specific BET surface area measurements and Scanning Electron Microscopy observations seemed to prove that growth process is favored over the nucleation process when ettringite crystals are initially present in a solution with a low supersaturation degree. The influence of stirring on ettringite formation was also investigated. Observation was made that intensity and nature of stirring have a high influence on the size of ettringite needles formed. Needle sizes vary from less than 10µm long depending on the stirring to almost 100µm long without any stirring. During all previously mentioned experiments, initially present ions are consumed to form ettringite in such a way that the supersaturation degree with regard to ettringite is decreasing over time. To avoid this phenomenon a device compensating the drop of ion concentrations by adding some more solutions, and therefore always have constant ionic concentrations, was used. This constant β recreates the conditions of the beginning of cement paste hydration, when the dissolution of solid reagents compensates the consumption of ions to form hydrates. This device allowed the determination of the ettringite precipitation rate as a function of the supersaturation degree β. Taking samples at different time during ettringite precipitation and doing BET measurements allowed the determination of the interfacial growth rate of ettringite in m²/s. This work will lead to a better understanding and control of ettringite formation alone and thus during cements hydration. This study will also ultimately define the impact of ettringite formation process on the rheology of cement pastes at early age, which is a crucial parameter from a practical point of view.

Keywords: cement hydration, ettringite, morphology of crystals, nucleation-growth process

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: J. Gabrielczyk, J. Kluitmann, T. Dammeyer, H. J. Jördening

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High-level expression of proteins in bacteria often causes production of insoluble protein aggregates, called inclusion bodies (IB). They contain mainly one type of protein and offer an easy and efficient way to get purified protein. On the other hand, proteins in IB are normally devoid of function and therefore need a special treatment to become active. Most refolding techniques aim at diluting the solubilizing chaotropic agents. Unfortunately, optimal refolding conditions have to be found empirically for every protein. For large-scale applications, a simple refolding process with high yields and high final enzyme concentrations is still missing. The constructed plasmid pASK-IBA63b containing the sequence of fructosyltransferase (FTF, EC 2.4.1.162) from Bacillus subtilis NCIMB 11871 was transformed into E. coli BL21 (DE3) Rosetta. The bacterium was cultivated in a fed-batch bioreactor. The produced FTF was obtained mainly as IB. For refolding experiments, five different amounts of IBs were solubilized in urea buffer with protein concentration of 0.2-8.5 g/L. Solubilizates were refolded with batch or continuous dialysis. The refolding yield was determined by measuring the protein concentration of the clear supernatant before and after the dialysis. Particle size was measured by dynamic light scattering. We tested the solubilization properties of fructosyltransferase IBs. The particle size measurements revealed that the solubilization of the aggregates is achieved at urea concentration of 5M or higher and confirmed by absorption spectroscopy. All results confirm previous investigations that refolding yields are dependent upon initial protein concentration. In batch dialysis, the yields dropped from 67% to 12% and 72% to 19% for continuous dialysis, in relation to initial concentrations from 0.2 to 8.5 g/L. Often used additives such as sucrose and glycerol had no effect on refolding yields. Buffer screening indicated a significant increase in activity but also temperature stability of FTF with citrate/phosphate buffer. By adding citrate to the dialysis buffer, we were able to increase the refolding yields to 82-47% in batch and 90-74% in the continuous process. Further experiments showed that in general, higher ionic strength of buffers had major impact on refolding yields; doubling the buffer concentration increased the yields up to threefold. Finally, we achieved corresponding high refolding yields by reducing the chamber volume by 75% and the amount of buffer needed. The refolded enzyme had an optimal activity of 12.5±0.3 x104 units/g. However, detailed experiments with native FTF revealed a reaggregation of the molecules and loss in specific activity depending on the enzyme concentration and particle size. For that reason, we actually focus on developing a process of simultaneous enzyme refolding and immobilization. The results of this study show a new approach in finding optimal refolding conditions for inclusion bodies at high concentrations. Straightforward buffer screening and increase of the ionic strength can optimize the refolding yield of the target protein by 400%. Gentle removal of chaotrope with continuous dialysis increases the yields by an additional 65%, independent of the refolding buffer applied. In general time is the crucial parameter for successful refolding of solubilized proteins.

Keywords: dialysis, inclusion body, refolding, solubilization

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Authors: A. Falenski, A. Kaesbohrer, M. Filter

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Introduction: Risk assessments can be performed in various ways and in different degrees of complexity. In order to assess risks associated with imported foods additional information needs to be taken into account compared to a risk assessment on regional products. The present review is an overview on currently available best practise approaches and data sources used for food import risk assessments (IRAs). Methods: A literature review has been performed. PubMed was searched for articles about food IRAs published in the years 2004 to 2014 (English and German texts only, search string “(English [la] OR German [la]) (2004:2014 [dp]) import [ti] risk”). Titles and abstracts were screened for import risks in the context of IRAs. The finally selected publications were analysed according to a predefined questionnaire extracting the following information: risk assessment guidelines followed, modelling methods used, data and software applied, existence of an analysis of uncertainty and variability. IRAs cited in these publications were also included in the analysis. Results: The PubMed search resulted in 49 publications, 17 of which contained information about import risks and risk assessments. Within these 19 cross references were identified to be of interest for the present study. These included original articles, reviews and guidelines. At least one of the guidelines of the World Organisation for Animal Health (OIE) and the Codex Alimentarius Commission were referenced in any of the IRAs, either for import of animals or for imports concerning foods, respectively. Interestingly, also a combination of both was used to assess the risk associated with the import of live animals serving as the source of food. Methods ranged from full quantitative IRAs using probabilistic models and dose-response models to qualitative IRA in which decision trees or severity tables were set up using parameter estimations based on expert opinions. Calculations were done using @Risk, R or Excel. Most heterogeneous was the type of data used, ranging from general information on imported goods (food, live animals) to pathogen prevalence in the country of origin. These data were either publicly available in databases or lists (e.g., OIE WAHID and Handystatus II, FAOSTAT, Eurostat, TRACES), accessible on a national level (e.g., herd information) or only open to a small group of people (flight passenger import data at national airport customs office). In the IRAs, an uncertainty analysis has been mentioned in some cases, but calculations have been performed only in a few cases. Conclusion: The current state-of-the-art in the assessment of risks of imported foods is characterized by a great heterogeneity in relation to general methodology and data used. Often information is gathered on a case-by-case basis and reformatted by hand in order to perform the IRA. This analysis therefore illustrates the need for a flexible, modular framework supporting the connection of existing data sources with data analysis and modelling tools. Such an infrastructure could pave the way to IRA workflows applicable ad-hoc, e.g. in case of a crisis situation.

Keywords: import risk assessment, review, tools, food import

Procedia PDF Downloads 286

Authors: M. D. Nirmani, K. L. N. Perera, G. H. Galhena

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Dengue has become one of the most important arbo-viral disease in all tropical and subtropical regions of the world. Aedes aegypti, is the principal vector of the virus, vary in both epidemiological and behavioral characteristics, which could be finely measured through DNA sequence comparison at their population level. Such knowledge in the population differences can assist in implementation of effective vector control strategies allowing to make estimates of the gene flow and adaptive genomic changes, which are important predictors of the spread of Wolbachia infection or insecticide resistance. As such, this study was undertaken to investigate the phylogenetic relationships of Ae. aegypti from Galle and Colombo, Sri Lanka, based on the ribosomal protein region which spans between two exons, in order to understand the geographical distribution of genetically distinct mosquito clades and its impact on mosquito control measures. A 320bp DNA region spanning from 681-930 bp, corresponding to the ribosomal protein, was sequenced in 62 Ae. aegypti larvae collected from Galle (N=30) and Colombo (N=32), Sri Lanka. The sequences were aligned using ClustalW and the haplotypes were determined with DnaSP 5.10. Phylogenetic relationships among haplotypes were constructed using the maximum likelihood method under Tamura 3 parameter model in MEGA 7.0.14 including three previously reported sequences of Australian (N=2) and Brazilian (N=1) Ae. aegypti. The bootstrap support was calculated using 1000 replicates and the tree was rooted using Aedes notoscriptus (GenBank accession No. KJ194101). Among all sequences, nineteen different haplotypes were found among which five haplotypes were shared between 80% of mosquitoes in the two populations. Seven haplotypes were unique to each of the population. Phylogenetic tree revealed two basal clades and a single derived clade. All observed haplotypes of the two Ae. aegypti populations were distributed in all the three clades, indicating a lack of genetic differentiation between populations. The Brazilian Ae. aegypti haplotype and one of the Australian haplotypes were grouped together with the Sri Lankan basal haplotype in the same basal clade, whereas the other Australian haplotype was found in the derived clade. Phylogram showed that Galle and Colombo Ae. aegypti populations are highly related to each other despite the large geographic distance (129 Km) indicating a substantial genetic similarity between them. This may have probably arisen from passive migration assisted by human travelling and trade through both land and water as the two areas are bordered by the sea. In addition, studied Sri Lankan mosquito populations were closely related to Australian and Brazilian samples. Probably this might have caused by shipping industry between the three countries as all of them are fully or partially enclosed by sea. For example, illegal fishing boats migrating to Australia by sea is perhaps a good mean of transportation of all life stages of mosquitoes from Sri Lanka. These findings indicate that extensive mosquito migrations occur between populations not only within the country, but also among other countries in the world which might be a main barrier to the successful vector control measures.

Keywords: Aedes aegypti, dengue control, extensive mosquito migration, haplotypes, phylogeny, ribosomal protein

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Authors: S. J. Addinell, T. Richard, B. Evans

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The Deep Exploration Technologies Cooperative Research Centre (DET CRC) is researching and developing a new coiled tubing based greenfields mineral exploration drilling system utilising downhole water powered percussive drill tooling. This new drilling system is aimed at significantly reducing the costs associated with identifying mineral resource deposits beneath deep, barron cover. This system has shown superior rates of penetration in water-rich hard rock formations at depths exceeding 500 meters. Several key challenges exist regarding the deployment and use of these bottom hole assemblies for mineral exploration, and this paper discusses some of the key technical challenges. This paper presents experimental results obtained from the research program during laboratory and field testing of the prototype drilling system. A study of the morphological aspects of the cuttings generated during the percussive drilling process is presented and shows a strong power law relationship for particle size distributions. Several percussive drilling parameters such as RPM, applied fluid pressure and weight on bit have been shown to influence the particle size distributions of the cuttings generated. This has direct influence on other drilling parameters such as flow loop performance, cuttings dewatering, and solids control. Real-time, accurate knowledge of percussive system operating parameters will assist the driller in maximising the efficiency of the drilling process. The applied fluid flow, fluid pressure, and rock properties are known to influence the natural oscillating frequency of the percussive hammer, but this paper also shows that drill bit design, drill bit wear and the applied weight on bit can also influence the oscillation frequency. Due to the changing drilling conditions and therefore changing operating parameters, real-time understanding of the natural operating frequency is paramount to achieving system optimisation. Several techniques to understand the oscillating frequency have been investigated and presented. With a conventional top drive drilling rig, spectral analysis of applied fluid pressure, hydraulic feed force pressure, hold back pressure and drill string vibrations have shown the presence of the operating frequency of the bottom hole tooling. Unfortunately, however, with the implementation of a coiled tubing drilling rig, implementing a positive displacement downhole motor to provide drill bit rotation, these signals are not available for interrogation at the surface and therefore another method must be considered. The investigation and analysis of ground vibrations using geophone sensors, similar to seismic-while-drilling techniques have indicated the presence of the natural oscillating frequency of the percussive hammer. This method is shown to provide a robust technique for the determination of the downhole percussive oscillation frequency when used with a coiled tubing drill rig.

Keywords: cuttings characterization, drilling optimization, oscillation frequency, percussive drilling, spectral analysis

Procedia PDF Downloads 202

Authors: Aline Woine, Moïra Mikolajczak, Virginie Dardier, Isabelle Roskam

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Background information: Becoming a parent is said to be the happiest event one can ever experience in one’s life. This popular (and almost absolute) truth–which no reasonable and decent human being would ever dare question on pain of being singled out as a bad parent–contrasts with the nuances that reality offers. Indeed, while many parents do thrive in their parenting role, some others falter and become progressively overwhelmed by their parenting role, ineluctably caught in a spiral of exhaustion. Parental burnout (henceforth PB) sets in when parental demands (stressors) exceed parental resources. While it is now generally acknowledged that PB affects the parent’s behavior in terms of neglect and violence toward their offspring, little is known about the impact that the syndrome might have on the children’s internalized (anxious and depressive symptoms, somatic complaints, etc.) and/or externalized (irritability, violence, aggressiveness, conduct disorder, oppositional disorder, etc.) behaviors. Furthermore, at the time of writing, to our best knowledge, no research has yet tested the reverse effect, namely, that of the child's internalized and/or externalized behaviors on the onset and/or maintenance of parental burnout symptoms. Goals and hypotheses: The present pioneering research proposes to fill an important gap in the existing literature related to PB by investigating the bidirectional effect between PB and the child’s internalized and/or externalized behaviors. Relying on a cross-lagged longitudinal study with three waves of data collection (4 months apart), our study tests a transactional model with bidirectional and recursive relations between observed variables and at the three waves, as well as autoregressive paths and cross-sectional correlations. Methods: As we write this, wave-two data are being collected via Qualtrics, and we expect a final sample of about 600 participants composed of French-speaking (snowball sample) and English-speaking (Prolific sample) parents. Structural equation modeling is employed using Stata version 17. In order to retain as much statistical power as possible, we use all available data and therefore apply the maximum likelihood with a missing value (mlmv) as the method of estimation to compute the parameter estimates. To limit (in so far is possible) the shared method variance bias in the evaluation of the child’s behavior, the study relies on a multi-informant evaluation approach. Expected results: We expect our three-wave longitudinal study to show that PB symptoms (measured at T1) raise the occurrence/intensity of the child’s externalized and/or internalized behaviors (measured at T2 and T3). We further expect the child’s occurrence/intensity of externalized and/or internalized behaviors (measured at T1) to augment the risk for PB (measured at T2 and T3). Conclusion: Should our hypotheses be confirmed, our results will make an important contribution to the understanding of both PB and children’s behavioral issues, thereby opening interesting theoretical and clinical avenues.

Keywords: exhaustion, structural equation modeling, cross-lagged longitudinal study, violence and neglect, child-parent relationship

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Authors: J. Martin, A. Nominé, T. Czerwiec, G. Henrion, T. Belmonte

Abstract:

The plasma electrolytic oxidation (PEO) is a particular electrochemical process to produce protective oxide ceramic coatings on light-weight metals (Al, Mg, Ti). When applied to aluminum alloys, the resulting PEO coating exhibit improved wear and corrosion resistance because thick, hard, compact and adherent crystalline alumina layers can be achieved. Several investigations have been carried out to improve the efficiency of the PEO process and one particular way consists in tuning the suitable electrical regime. Despite the considerable interest in this process, there is still no clear understanding of the underlying discharge mechanisms that make possible metal oxidation up to hundreds of µm through the ceramic layer. A key parameter that governs the PEO process is the numerous short-lived micro-discharges (micro-plasma in liquid) that occur continuously over the processed surface when the high applied voltage exceeds the critical dielectric breakdown value of the growing ceramic layer. By using a bipolar pulsed current to supply the electrodes, we previously observed that micro-discharges are delayed with respect to the rising edge of the anodic current. Nevertheless, explanation of the origin of such phenomena is still not clear and needs more systematic investigations. The aim of the present communication is to identify the relationship that exists between this delay and the mechanisms responsible of the oxide growth. For this purpose, the delay of micro-discharges ignition is investigated as the function of various electrical parameters such as the current density (J), the current pulse frequency (F) and the anodic to cathodic charge quantity ratio (R = Qp/Qn) delivered to the electrodes. The PEO process was conducted on Al2214 aluminum alloy substrates in a solution containing potassium hydroxide [KOH] and sodium silicate diluted in deionized water. The light emitted from micro-discharges was detected by a photomultiplier and the micro-discharge parameters (number, size, life-time) were measured during the process by means of ultra-fast video imaging (125 kfr./s). SEM observations and roughness measurements were performed to characterize the morphology of the elaborated oxide coatings while XRD was carried out to evaluate the amount of corundum -Al203 phase. Results show that whatever the applied current waveform, the delay of micro-discharge appearance increases as the process goes on. Moreover, the delay is shorter when the current density J (A/dm2), the current pulse frequency F (Hz) and the ratio of charge quantity R are high. It also appears that shorter delays are associated to stronger micro-discharges (localized, long and large micro-discharges) which have a detrimental effect on the elaborated oxide layers (thin and porous). On the basis of the results, a model for the growth of the PEO oxide layers will be presented and discussed. Experimental results support that a mechanism of electrical charge accumulation at the oxide surface / electrolyte interface takes place until the dielectric breakdown occurs and thus until micro-discharges appear.

Keywords: aluminium, micro-discharges, oxidation mechanisms, plasma electrolytic oxidation

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Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

Abstract:

Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 43

Authors: Monika Saha, A. T. M. Hasan Zobeyer, Nasreen Jahan

Abstract:

El Nino-Southern Oscillation (ENSO) is the interaction between atmosphere and ocean in tropical Pacific which causes inconsistent warm/cold weather in tropical central and eastern Pacific Ocean. Due to the impact of climate change, ENSO events are becoming stronger in recent times, and therefore it is very important to study the influence of ENSO in climate studies. Bangladesh, being in the low-lying deltaic floodplain, experiences the worst consequences due to flooding every year. To reduce the catastrophe of severe flooding events, non-structural measures such as flood forecasting can be helpful in taking adequate precautions and steps. Forecasting seasonal flood with a longer lead time of several months is a key component of flood damage control and water management. The objective of this research is to identify the possible strength of teleconnection between ENSO and river flow of Surma and examine the potential possibility of long lead flood forecasting in the wet season. Surma is one of the major rivers of Bangladesh and is a part of the Surma-Meghna river system. In this research, sea surface temperature (SST) has been considered as the ENSO index and the lead time is at least a few months which is greater than the basin response time. The teleconnection has been assessed by the correlation analysis between July-August-September (JAS) flow of Surma and SST of Nino 4 region of the corresponding months. Cumulative frequency distribution of standardized JAS flow of Surma has also been determined as part of assessing the possible teleconnection. Discharge data of Surma river from 1975 to 2015 is used in this analysis, and remarkable increased value of correlation coefficient between flow and ENSO has been observed from 1985. From the cumulative frequency distribution of the standardized JAS flow, it has been marked that in any year the JAS flow has approximately 50% probability of exceeding the long-term average JAS flow. During El Nino year (warm episode of ENSO) this probability of exceedance drops to 23% and while in La Nina year (cold episode of ENSO) it increases to 78%. Discriminant analysis which is known as 'Categoric Prediction' has been performed to identify the possibilities of long lead flood forecasting. It has helped to categorize the flow data (high, average and low) based on the classification of predicted SST (warm, normal and cold). From the discriminant analysis, it has been found that for Surma river, the probability of a high flood in the cold period is 75% and the probability of a low flood in the warm period is 33%. A synoptic parameter, forecasting index (FI) has also been calculated here to judge the forecast skill and to compare different forecasts. This study will help the concerned authorities and the stakeholders to take long-term water resources decisions and formulate policies on river basin management which will reduce possible damage of life, agriculture, and property.

Keywords: El Nino-Southern Oscillation, sea surface temperature, surma river, teleconnection, cumulative frequency distribution, discriminant analysis, forecasting index

Procedia PDF Downloads 117

Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

Abstract:

Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Jyoti Sahu, Vinay A. Juvekar

Abstract:

Electrolytes are often used to bring about salting-in and salting-out of organic molecules and polymers (e.g. polyethylene glycols/proteins) from the aqueous solutions. For quantification of these phenomena, a thermodynamic model which can accurately predict activity coefficient of electrolyte as a function of temperature is needed. The thermodynamics models available in the literature contain a large number of empirical parameters. These parameters are estimated using lower/upper critical solution temperature of the solution in the electrolyte/organic molecule at different temperatures. Since the number of parameters is large, inaccuracy can bethe creep in during their estimation, which can affect the reliability of prediction beyond the range in which these parameters are estimated. Cloud point of solution is related to its free energy through temperature and composition derivative. Hence, the Cloud point measurement can be used for accurate estimation of the temperature and composition dependence of parameters in the model for free energy. Hence, if we use a two pronged procedure in which we first use cloud point of solution to estimate some of the parameters of the thermodynamic model and determine the rest using osmotic coefficient data, we gain on two counts. First, since the parameters, estimated in each of the two steps, are fewer, we achieve higher accuracy of estimation. The second and more important gain is that the resulting model parameters are more sensitive to temperature. This is crucial when we wish to use the model outside temperatures window within which the parameter estimation is sought. The focus of the present work is to prove this proposition. We have used electrolyte (NaCl/Na2CO3)-water-organic molecule (Iso-propanol/ethanol) as the model system. The model of Robinson-Stokes-Glukauf is modified by incorporating the temperature dependent Flory-Huggins interaction parameters. The Helmholtz free energy expression contains, in addition to electrostatic and translational entropic contributions, three Flory-Huggins pairwise interaction contributions viz., and (w-water, p-polymer, s-salt). These parameters depend both on temperature and concentrations. The concentration dependence is expressed in the form of a quadratic expression involving the volume fractions of the interacting species. The temperature dependence is expressed in the form .To obtain the temperature-dependent interaction parameters for organic molecule-water and electrolyte-water systems, Critical solution temperature of electrolyte -water-organic molecules is measured using cloud point measuring apparatus The temperature and composition dependent interaction parameters for electrolyte-water-organic molecule are estimated through measurement of cloud point of solution. The model is used to estimate critical solution temperature (CST) of electrolyte water-organic molecules solution. We have experimentally determined the critical solution temperature of different compositions of electrolyte-water-organic molecule solution and compared the results with the estimates based on our model. The two sets of values show good agreement. On the other hand when only osmotic coefficients are used for estimation of the free energy model, CST predicted using the resulting model show poor agreement with the experiments. Thus, the importance of the CST data in the estimation of parameters of the thermodynamic model is confirmed through this work.

Keywords: concentrated electrolytes, Debye-Hückel theory, interaction parameters, Robinson-Stokes-Glueckauf model, Flory-Huggins model, critical solution temperature

Procedia PDF Downloads 358