Search results for: optimization algorithm

Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Minjeong Kim, Seungchul Lee, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

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A trajectory of set-point of ventilation control systems plays an important role for efficient ventilation inside subway stations since it affects the level of indoor air pollutants and ventilation energy consumption. To maintain indoor air quality (IAQ) at a comfortable range with lower ventilation energy consumption, the optimal trajectory of the ventilation control system needs to be determined. The concentration of air pollutants inside the station shows a diurnal variation in accordance with the variations in the number of passengers and subway frequency. To consider the diurnal variation of IAQ, an iterative dynamic programming (IDP) that searches for a piecewise control policy by separating whole duration into several stages is used. When outdoor air is contaminated by pollutants, it enters the subway station through the ventilation system, which results in the deteriorated IAQ and adverse effects on passenger health. In this study, to consider the influence of outdoor air quality (OAQ), a new performance index of the IDP with the passenger health risk and OAQ is proposed. This study was carried out for an underground subway station at Seoul Metro, Korea. The optimal set-points of the ventilation control system are determined every 3 hours, then, the ventilation controller adjusts the ventilation fan speed according to the optimal set-point changes. Compared to manual ventilation system which is operated irrespective of the OAQ, the IDP-based ventilation control system saves 3.7% of the energy consumption. Compared to the fixed set-point controller which is operated irrespective of the IAQ diurnal variation, the IDP-based controller shows better performance with a 2% decrease in energy consumption, maintaining the comfortable IAQ range inside the station.

Keywords: indoor air quality, iterative dynamic algorithm, outdoor air information, ventilation control system

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Authors: Magu Raam Prasaad R., Venkatramani Jagadish

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Recent studies in the literature have shown that randomly fluctuating wind flows can give rise to a distinct regime of pre-flutter oscillations called intermittency. Intermittency is characterized by the presence of sporadic bursts of high amplitude oscillations interspersed amidst low-amplitude aperiodic fluctuations. The focus of this study is on investigating the energy harvesting potential of these intermittent oscillations. Available literature has by and large devoted its attention on extracting energy from flutter oscillations. The possibility of harvesting energy from pre-flutter regimes have remained largely unexplored. However, extracting energy from violent flutter oscillations can be severely detrimental to the structural integrity of airfoil structures. Consequently, investigating the relatively stable pre-flutter responses for energy extraction applications is of practical importance. The present study is devoted towards addressing these concerns. A pitch-plunge airfoil with cubic hardening nonlinearity in the plunge and pitch degree of freedom is considered. The input flow fluctuations are modelled using a sinusoidal term with randomly perturbed frequencies. An electromagnetic coupling is provided to the pitch-plunge equations, such that, energy from the wind induced vibrations of the structural response are extracted. With the mean flow speed as the bifurcation parameter, a fourth order Runge-Kutta based time marching algorithm is used to solve the governing aeroelastic equations with electro-magnetic coupling. The harnessed energy from the intermittency regime is presented and the results are discussed in comparison to that obtained from the flutter regime. The insights from this study could be useful in health monitoring of aeroelastic structures.

Keywords: aeroelasticity, energy harvesting, intermittency, randomly fluctuating flows

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Authors: Ayshan Gurbanova

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Despite based on the fact that drill bit which is the smallest part of bottom hole assembly costs only in between 10% and 15% of the total expenses made, they are the first equipment that is in contact with the formation itself. Hence, it is consequential to choose the appropriate type and dimension of drilling bit, which will prevent majority of problems by not demanding many tripping procedure. However, within the advance in technology, it is now seamless to be beneficial in the terms of many concepts such as subsequent time of operation, energy, expenditure, power and so forth. With the intention of applying the method to Azerbaijan, the field of Shallow Water Absheron Peninsula has been suggested, where the mainland has been located 15 km away from the wildcat wells, named as “NKX01”. It has the water depth of 22 m as indicated. In 2015 and 2016, the seismic survey analysis of 2D and 3D have been conducted in contract area as well as onshore shallow water depth locations. With the aim of indicating clear elucidation, soil stability, possible submersible dangerous scenarios, geohazards and bathymetry surveys have been carried out as well. Within the seismic analysis results, the exact location of exploration wells have been determined and along with this, the correct measurement decisions have been made to divide the land into three productive zones. In the term of the method, Electric Impulse Technology (EIT) is based on discharge energies of electricity within the corrosivity in rock. Take it simply, the highest value of voltages could be created in the less range of nano time, where it is sent to the rock through electrodes’ baring as demonstrated below. These electrodes- higher voltage powered and grounded are placed on the formation which could be obscured in liquid. With the design, it is more seamless to drill horizontal well based on the advantage of loose contact of formation. There is also no chance of worn ability as there are no combustion, mechanical power exist. In the case of energy, the usage of conventional drilling accounts for 1000 𝐽/𝑐𝑚3 , where this value accounts for between 100 and 200 𝐽/𝑐𝑚3 in EIT. Last but not the least, from the test analysis, it has been yielded that it achieves the value of ROP more than 2 𝑚/ℎ𝑟 throughout 15 days. Taking everything into consideration, it is such a fact that with the comparison of data analysis, this method is highly applicable to the fields of Azerbaijan.

Keywords: drilling, drill bit cost, efficiency, cost

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Authors: Aadila Cayenne, Hinrich Uellendahl

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Optimization of the anaerobic digestion (AD) process of halophytic plants is essential as the biomass contains a high salt content that can inhibit the AD process. Anaerobic co-digestion, together with manure, can resolve the inhibitory effects of saline biomass in order to dilute the salt concentration and establish favorable conditions for the microbial consortia of the AD process. The present laboratory study investigated the co-digestion of S. ramosissima (Sram), and pig manure (PM) in batch and semi-continuous stirred tank reactors (CSTR) under mesophilic (38oC) conditions. The 0.5L batch reactor experiments were in mono- and co-digestion of Sram: PM using different percent volatile solid (VS) based ratios (0:100, 15:85, 25:75, 35:65, 50:50, 100:0) with an inoculum to substate (I/R) ratio of 2. Two 5L CSTR systems (R1 and R2) were operated for 133 days with a feed of PM in a control reactor (R1) and with a co-digestion feed in an increasing Sram VS ratio of Sram: PM of 15:85, 25:75, 35:65 in reactor R2 at an organic loading rate (OLR) of 2 gVS/L/d and hydraulic retention time (HRT) of 20 days. After a start-up phase of 8 weeks for both reactors R1 and R2 with PM feed alone, the halophyte biomass Sram was added to the feed of R2 in an increasing ratio of 15 – 35 %VS Sram over an 11-week period. The process performance was monitored by pH, total solid (TS), VS, total nitrogen (TN), ammonium-nitrogen (NH4 – N), volatile fatty acids (VFA), and biomethane production. In the batch experiments, biomethane yields of 423, 418, 392, 365, 315, and 214 mL-CH4/gVS were achieved for mixtures of 0:100, 15:85, 25:75, 35:65, 50:50, 100:0 %VS Sram: PM, respectively. In the semi-continuous reactor processes, the average biomethane yields were 235, 387, and 365 mL-CH4/gVS for the phase of a co-digestion feed ratio in R2 of 15:85, 25:75, and 35:65 %VS Sram: PM, respectively. The methane yield of PM alone in R1 was in the corresponding phases on average 260, 388, and 446 mL-CH4/gVS. Accordingly, in the continuous AD process, the methane yield of the halophyte Sram was highest at 386 mL-CH4/gVS in the co-digestion ratio of 25:75%VS Sram: PM and significantly lower at 15:85 %VS Sram: PM (100 mL-CH4/gVS) and at 35:65 %VS Sram (214 mL-CH4/gVS). The co-digestion process showed no signs of inhibition at 2 – 4 g/L NH4 – N, 3.5 – 4.5 g/L TN, and total VFA of 0.45 – 2.6 g/L (based on Acetic, Propionic, Butyric and Valeric acid). This study demonstrates that a stable co-digestion process of S. ramosissima and pig manure can be achieved with a feed of 25%VS Sram at HRT of 20 d and OLR of 2 gVS/L/d.

Keywords: anaerobic co-digestion, biomethane production, halophytes, pig manure, salicornia ramosissima

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Authors: S. Sreeja, Radhakrishnan R. Nair, Noble Gracious, Sreeja S. Nair, M. Radhakrishna Pillai

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Background: Tacrolimus is a potent immunosuppressant clinically used for the long term treatment of antirejection of transplanted organs in liver and kidney transplant recipients though dose optimization is poorly managed. However, So far no study has been carried out on the South Indian kidney transplant patients. The objective of this study is to evaluate the potential influence of a functional polymorphism in CYP3A5*3 gene on tacrolimus physiological availability/dose ratio in South Indian renal transplant patients. Materials and Methods: Twenty five renal transplant recipients receiving tacrolimus were enrolled in this study. Their body weight, drug dosage, and therapeutic concentration of Tacrolimus were observed. All patients were on standard immunosuppressive regime of Tacrolimus-Mycophenolate mofetil along with steroids on a starting dose of Tac 0.1 mg/kg/day. CYP3A5 genotyping was performed by PCR followed with RFLP. Conformation of RFLP analysis and variation in the nucleotide sequence of CYP3A5*3 gene were determined by direct sequencing using a validated automated generic analyzer. Results: A significant association was found between tacrolimus per dose/kg/d and CYP3A5 gene (A6986G) polymorphism in the study population. The CYP3A5 *1/*1, *1/*3 and *3/*3 genotypes were detected in 5 (20 %), 5 (20 %) and 15 (60 %) of the 25 graft recipients, respectively. CYP3A5*3 genotypes were found to be a good predictor of tacrolimus Concentration/Dose ratio in kidney transplant recipients. Significantly higher L/D was observed among non-expressors 9.483 ng/mL(4.5- 14.1) as compared with the expressors 5.154 ng/mL (4.42-6.5 ) of CYP3A5. Acute rejection episodes were significantly higher for CYP3A5*1 homozygotes compared to patients with CYP3A5*1/*3 and CYP3A5*3/*3 genotypes (40 % versus 20 % and 13 %, respectively ). The dose normalized TAC concentration (ng/ml/mg/kg) was significantly lower in patients having CYP3A5*1/*3 polymorphism. Conclusion: This is the first study to extensively determine the effect of CYP3A5*3 genetic polymorphism on tacrolimus pharmacokinetics in South Indian renal transplant recipients and also shows that majority of our patients carry mutant allele A6986G in CYP3A5*3 gene. Identification of CYP3A5 polymorphism prior to transplantation could contribute to evaluate the appropriate initial dosage of tacrolimus for each patient.

Keywords: kidney transplant patients, CYP3A5 genotype, tacrolimus, RFLP

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Authors: Faris Tarlochan, Siva Mahesh Tangutooru

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Lateral Geniculate Nucleus (LGN) is the relay center in the visual pathway as it receives most of the input information from retinal ganglion cells (RGC) and sends to visual cortex. Low threshold calcium currents (IT) at the membrane are the unique indicator to characterize this firing functionality of the LGN neurons gained by the RGC input. According to the LGN functional requirements such as functional mapping of RGC to LGN, the morphologies of the LGN neurons were developed. During the neurological disorders like glaucoma, the mapping between RGC and LGN is disconnected and hence stimulating LGN electrically using deep brain electrodes can restore the functionalities of LGN. A computational model was developed for simulating the LGN neurons with three predominant morphologies, each representing different functional mapping of RGC to LGN. The firings of action potentials at LGN neuron due to IT were characterized by varying the stimulation parameters, morphological parameters and orientation. A wide range of stimulation parameters (stimulus amplitude, duration and frequency) represents the various strengths of the electrical stimulation with different morphological parameters (soma size, dendrites size and structure). The orientation (0-1800) of LGN neuron with respect to the stimulating electrode represents the angle at which the extracellular deep brain stimulation towards LGN neuron is performed. A reduced dendrite structure was used in the model using Bush–Sejnowski algorithm to decrease the computational time while conserving its input resistance and total surface area. The major finding is that an input potential of 0.4 V is required to produce the action potential in the LGN neuron which is placed at 100 µm distance from the electrode. From this study, it can be concluded that the neuroprostheses under design would need to consider the capability of inducing at least 0.4V to produce action potentials in LGN.

Keywords: Lateral Geniculate Nucleus, visual cortex, finite element, glaucoma, neuroprostheses

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Authors: Othman Maklouf, Abdunnaser Tresh

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Land vehicle navigation is subject of great interest today. Global Positioning System (GPS) is the main navigation system for positioning in such systems. GPS alone is incapable of providing continuous and reliable positioning, because of its inherent dependency on external electromagnetic signals. Inertial Navigation (INS) is the implementation of inertial sensors to determine the position and orientation of a vehicle. The availability of low-cost Micro-Electro-Mechanical-System (MEMS) inertial sensors is now making it feasible to develop INS using an inertial measurement unit (IMU). INS has unbounded error growth since the error accumulates at each step. Usually, GPS and INS are integrated with a loosely coupled scheme. With the development of low-cost, MEMS inertial sensors and GPS technology, integrated INS/GPS systems are beginning to meet the growing demands of lower cost, smaller size, and seamless navigation solutions for land vehicles. Although MEMS inertial sensors are very inexpensive compared to conventional sensors, their cost (especially MEMS gyros) is still not acceptable for many low-end civilian applications (for example, commercial car navigation or personal location systems). An efficient way to reduce the expense of these systems is to reduce the number of gyros and accelerometers, therefore, to use a partial IMU (ParIMU) configuration. For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a field experiment for a low-cost strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach, we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of our low-cost IMU (Inertial Measurement Unit) and because of the relatively small area of the trajectory.

Keywords: GPS, IMU, Kalman filter, materials engineering

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: Kaiwen Zheng, Wanting Zhou, Nan Tang, Lei Li, Yuanhang He

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The integrated circuit industry has become a cornerstone of the information society, finding widespread application in areas such as industry, communication, medicine, and aerospace. However, with the increasing complexity of integrated circuits, Hardware Trojans (HTs) implanted by attackers have become a significant threat to their security. In this paper, we proposed a hardware trojan detection method for large-scale circuits. As HTs introduce physical characteristic changes such as structure, area, and power consumption as additional redundant circuits, we proposed a machine-learning-based hardware trojan detection method based on the physical characteristics of gate-level netlists. This method transforms the hardware trojan detection problem into a machine-learning binary classification problem based on physical characteristics, greatly improving detection speed. To address the problem of imbalanced data, where the number of pure circuit samples is far less than that of HTs circuit samples, we used the SMOTETomek algorithm to expand the dataset and further improve the performance of the classifier. We used three machine learning algorithms, K-Nearest Neighbors, Random Forest, and Support Vector Machine, to train and validate benchmark circuits on Trust-Hub, and all achieved good results. In our case studies based on AES encryption circuits provided by trust-hub, the test results showed the effectiveness of the proposed method. To further validate the method’s effectiveness for detecting variant HTs, we designed variant HTs using open-source HTs. The proposed method can guarantee robust detection accuracy in the millisecond level detection time for IC, and FPGA design flows and has good detection performance for library variant HTs.

Keywords: hardware trojans, physical properties, machine learning, hardware security

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Authors: F. Murilo T. Luna, Vanessa F. Oliveira, Alysson Rocha, Expedito J. S. Parente, Andre V. Bueno, Matheus C. M. Farias, Celio L. Cavalcante Jr.

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Aviation jetfuel used in aircraft gas-turbine engines is customarily obtained from the kerosene distillation fraction of petroleum (150-275°C). Mineral jetfuel consists of a hydrocarbon mixture containing paraffins, naphthenes and aromatics, with low olefins content. In order to ensure their safety, several stringent requirements must be met by jetfuels, such as: high energy density, low risk of explosion, physicochemical stability and low pour point. In this context, aviation fuels eventually obtained from biofeedstocks (which have been coined as ‘biojetfuel’), must be used as ‘drop in’, since adaptations in aircraft engines are not desirable, to avoid problems with their operation reliability. Thus, potential aviation biofuels must present the same composition and physicochemical properties of conventional jetfuel. Among the potential feedtstocks for aviation biofuel, the babaçu oil, extracted from a palm tree extensively found in some regions of Brazil, contains expressive quantities of short chain saturated fatty acids and may be an interesting choice for biojetfuel production. In this study, biojetfuel was synthesized through homogeneous transesterification of babaçu oil using methanol and its properties were compared with petroleum-based jetfuel through measurements of oxidative stability, physicochemical properties and low temperature properties. The transesterification reactions were carried out using methanol and after decantation/wash procedures, the methyl esters were purified by molecular distillation under high vacuum at different temperatures. The results indicate significant improvement in oxidative stability and pour point of the products when compared to the fresh oil. After optimization of operational conditions, potential biojetfuel samples were obtained, consisting mainly of C8 esters, showing low pour point and high oxidative stability. Jet engine tests are being conducted in an automated test bed equipped with pollutant emissions analysers to study the operational performance of the biojetfuel that was obtained and compare with a mineral commercial jetfuel.

Keywords: biojetfuel, babaçu oil, oxidative stability, engine tests

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Authors: Tooba Aslam, Efthalia Chatzisymeon

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UV-assisted irradiation technologies are well-established for water and wastewater treatment. UVC treatments are widely used at large-scale, while UVA irradiation has more often been applied in combination with a catalyst (e.g. TiO₂ or FeSO₄) in smaller-scale systems. A technical issue of these systems is the formation of fouling on the quartz sleeves that houses the lamps. This fouling can prevent complete irradiation, therefore reducing the efficiency of the process. This paper investigates the effects of operational parameters, such as the type of wastewater, irradiation source, H₂O₂ addition, and water pH on fouling formation and, ultimately, the treatment of municipal wastewater. Batch experiments have been performed at lab-scale while monitoring water quality parameters including: COD, TS, TSS, TDS, temperature, pH, hardness, alkalinity, turbidity, TOC, UV transmission, UV₂₅₄ absorbance, and metal concentrations. The residence time of the wastewater in the reactor was 5 days in order to observe any fouling formation on the quartz surface. Over this period, it was observed that chemical oxygen demand (COD) decreased by 30% and 59% during photolysis (Ultraviolet A) and photo-catalysis (UVA/Fe/H₂O₂), respectively. Higher fouling formation was observed with iron-rich and phosphorous-rich wastewater. The highest rate of fouling was developed with phosphorous-rich wastewater, followed by the iron-rich wastewater. Photo-catalysis (UVA/Fe/H₂O₂) had better removal efficiency than photolysis (UVA). This was attributed to the Photo-Fenton reaction, which was initiated under these operational conditions. Scanning electron microscope (SEM) measurements of fouling formed on the quartz sleeves showed that particles vary in size, shape, and structure; some have more distinct structures and are generally larger and have less compact structure than the others. Energy-dispersive X-ray spectroscopy (EDX) results showed that the major metals present in the fouling cake were iron, phosphorous, and calcium. In conclusion, iron-rich wastewaters are more suitable for UV-assisted treatment since fouling formation on quartz sleeves can be minimized by the formation of oxidizing agents during treatment, such as hydroxyl radicals.

Keywords: advanced oxidation processes, photo-fenton treatment, photo-catalysis, wastewater treatment

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Authors: Navpreet Kaur, Himkusha Thakur, Nirmal Prabhakar

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The most controversial issue in crop production is the use of Organophosphate insecticides. This is evident in many reports that Organophosphate (OP) insecticides, among the broad range of pesticides are mainly involved in acute and chronic poisoning cases. OPs detection is of crucial importance for health protection, food and environmental safety. In our study, a nanocomposite of poly (3,4 ethylenedioxythiophene) (PEDOT) and multi-walled carbon nanotubes (MWCNTs) has been deposited electrochemically onto the surface of fluorine doped tin oxide sheets (FTO) for the analysis of malathion OP. The -COOH functionalization of MWCNTs has been done for the covalent binding with amino groups of AChE enzyme. The use of PEDOT-MWCNT films exhibited an excellent conductivity, enables fast transfer kinetics and provided a favourable biocompatible microenvironment for AChE, for the significant malathion OP detection. The prepared biosensors were characterized by Fourier transform infrared spectrometry (FTIR), Field emission-scanning electron microscopy (FE-SEM) and electrochemical studies. Various optimization studies were done for different parameters including pH (7.5), AChE concentration (50 mU), substrate concentration (0.3 mM) and inhibition time (10 min). Substrate kinetics has been performed and studied for the determination of Michaelis Menten constant. The detection limit for malathion OP was calculated to be 1 fM within the linear range 1 fM to 1 µM. The activity of inhibited AChE enzyme was restored to 98% of its original value by 2-pyridine aldoxime methiodide (2-PAM) (5 mM) treatment for 11 min. The oxime 2-PAM is able to remove malathion from the active site of AChE by means of trans-esterification reaction. The storage stability and reusability of the prepared biosensor is observed to be 30 days and seven times, respectively. The application of the developed biosensor has also been evaluated for spiked lettuce sample. Recoveries of malathion from the spiked lettuce sample ranged between 96-98%. The low detection limit obtained by the developed biosensor made them reliable, sensitive and a low cost process.

Keywords: PEDOT-MWCNT, malathion, organophosphates, acetylcholinesterase, biosensor, oxime (2-PAM)

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Authors: Chen Chuanzhi, Guo Yunyun

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The large linear array feeding parabolic cylindrical antenna of the satellite has the ability of large-area line focusing, multi-directional beam clusters simultaneously in a certain azimuth plane and elevation plane, corresponding quickly to different orientations and different directions in a wide frequency range, dual aiming of frequency and direction, and combining space power. Therefore, the large-diameter parabolic cylindrical antenna has become one of the new development directions of spaceborne antennas. Limited by the size of the rocked fairing, the large-diameter spaceborne antenna is required to be small mass and have a deployment function. After being orbited, the antenna can be deployed by expanding and be stabilized. However, few types of structures can be used to construct large cylindrical shell structures in existing structures, which greatly limits the development and application of such antennas. Aiming at high structural efficiency, the geometrical characteristics of parabolic cylinders and mechanism topological mapping law to the expandable truss are studied, and the basic configuration of deployable truss with cylindrical shell is structured. Then a modular truss parabolic cylindrical antenna is designed in this paper. The antenna has the characteristics of stable structure, high precision of reflecting surface formation, controllable motion process, high storage rate, and lightweight, etc. On the basis of the overall configuration comprehensive theory and optimization method, the structural stiffness of the modular truss parabolic cylindrical antenna is improved. And the bearing density and impact resistance of support structure are improved based on the internal tension optimal distribution method of reflector forming. Finally, a truss-type cylindrical deployable support structure with high constriction-deployment ratio, high stiffness, controllable deployment, and low mass is successfully developed, laying the foundation for the application of large-diameter parabolic cylindrical antennas in satellite antennas.

Keywords: linear array feed antenna, truss type, parabolic cylindrical antenna, spaceborne antenna

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Authors: Biruk Wolde, Atalay Ayele, Yonatan Garkabo, Trufat Hailmariam, Zemenu Germewu

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A comprehensive three-dimensional (3D) geological modeling and engineering geological characterization of shallow subsurface soils and rocks are essential for a wide range of geotechnical and seismological engineering applications, particularly in urban environments. The spatial distribution and geological variation of the shallow subsurface of Addis Ababa city have not been studied so far in terms of geological and geotechnical modeling. This study aims at the construction of a 3D geological model, as well as provides awareness into the engineering geological characteristics of shallow subsurface soil and rock of Addis Ababa city. The 3D geological model was constructed by using more than 1500 geotechnical boreholes, well-drilling data, and geological maps. A well-known geostatistical kriging 3D interpolation algorithm was applied to visualize the spatial distribution and geological variation of the shallow subsurface. Due to the complex nature of geological formations, vertical and lateral variation of the geological profiles horizons-solid command has been selected via the Groundwater Modelling System (GMS) graphical user interface software. For the engineering geological characterization of typical soils and rocks, both index and engineering laboratory tests have been used. The geotechnical properties of soil and rocks vary from place to place due to the uneven nature of subsurface formations observed in the study areas. The constructed model ascertains the thickness, extent, and 3D distribution of the important geological units of the city. This study is the first comprehensive research work on 3D geological modeling and subsurface characterization of soils and rocks in Addis Ababa city, and the outcomes will be important for further future research on subsurface conditions in the city. Furthermore, these findings provide a reference for developing a geo-database for the city.

Keywords: 3d geological modeling, addis ababa, engineering geology, geostatistics, horizons-solid

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Authors: Morteza Ghorbani, Reza Ghorbani

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Cavitation phenomenon has attracted much attention in the mechanical and biomedical technologies. Despite the simplicity and mostly low cost of the devices generating cavitation bubbles, the physics behind the generation and collapse of these bubbles particularly in micro/nano scale has still not well understood. In the chemical industry, micro/nano bubble generation is expected to be applicable to the development of porous materials such as microcellular plastic foams. Moreover, it was demonstrated that the presence of micro/nano bubbles on a surface reduced the adsorption of proteins. Thus, the micro/nano bubbles could act as antifouling agents. Micro and nano bubbles were also employed in water purification, froth floatation, even in sonofusion, which was not completely validated. Small bubbles could also be generated using micro scale hydrodynamic cavitation. In this study, compared to the studies available in the literature, we are proposing a novel approach in micro scale utilizing the energy produced during the interaction of the spray affected by the hydrodynamic cavitating flow and a thin aluminum plate. With a decrease in the size, cavitation effects become significant. It is clearly shown that with the aid of hydrodynamic cavitation generated inside the micro/mini-channels in addition to the optimization of the distance between the tip of the microchannel configuration and the solid surface, surface temperatures can be increased up to 50C under the conditions of this study. The temperature rise on the surfaces near the collapsing small bubbles was exploited for energy harvesting in small scale, in such a way that miniature, cost-effective, and environmentally friendly energy-harvesting devices can be developed. Such devices will not require any external power and moving parts in contrast to common energy-harvesting devices, such as those involving piezoelectric materials and micro engine. Energy harvesting from thermal energy has been widely exploited to achieve energy savings and clean technologies. We are proposing a cost effective and environmentally friendly solution for the growing individual energy needs thanks to the energy application of cavitating flows. The necessary power for consumer devices, such as cell phones and laptops, can be provided using this approach. Thus, this approach has the potential for solving personal energy needs in an inexpensive and environmentally friendly manner and can trigger a shift of paradigm in energy harvesting.

Keywords: cavitation, energy, harvesting, micro scale

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Authors: Chun-Min Lin, Yuh-Jen Wu, Ching-Ting Chung

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The formulation of tourism policies requires objective academic research and evidence as support, especially research from local academia. Taiwan is a small island, and its economic growth relies heavily on tourism revenue. Taiwanese government has been devoting to the promotion of the tourism industry over the past few decades. Scientific research outcomes by Taiwanese scholars may and will help lay the foundations for drafting future tourism policy by the government. In this study, a total of 120 full journal articles published between 2008 and 2016 from the Journal of Tourism and Leisure Studies (JTSL) were examined to explore the scientific research trend of tourism study in Taiwan. JTSL is one of the most important Taiwanese journals in the tourism discipline which focuses on tourism-related issues and uses traditional Chinese as the study language. The method of co-word analysis from bibliometrics approaches was employed for semantic analysis in this study. When analyzing Chinese words and phrases, word segmentation analysis is a crucial step. It must be carried out initially and precisely in order to obtain meaningful word or word chunks for further frequency calculation. A word segmentation system basing on N-gram algorithm was developed in this study to conduct semantic analysis, and 100 groups of meaningful phrases with the highest recurrent rates were located. Subsequently, co-word analysis was employed for semantic classification. The results showed that the themes of tourism research in Taiwan in recent years cover the scope of tourism education, environmental protection, hotel management, information technology, and senior tourism. The results can give insight on the related issues and serve as a reference for tourism-related policy making and follow-up research.

Keywords: bibliometrics, co-word analysis, word segmentation, tourism research, policy

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Authors: Bin Zhou, Tongli Lu, Jianwu Zhang, Hongtao Hao

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Dual clutch transmissions (DCT) offer a high comfort performance in terms of the gearshift. Hydraulic multi-disk clutches are the key components of DCT, its engagement determines the shifting comfort. The prefill of the clutches requests an initial engagement which the clutches just contact against each other but not transmit substantial torque from the engine, this initial clutch engagement point is called the touch point. Open-loop control is typically implemented for the clutch prefill, a lot of uncertainties, such as oil temperature and clutch wear, significantly affects the prefill, probably resulting in an inappropriate touch point. Underfill causes the engine flaring in gearshift while overfill arises clutch tying up, both deteriorating the shifting comfort of DCT. Therefore, it is important to enable an adaptive capacity for the clutch prefills regarding the uncertainties. In this paper, a dynamic model of the hydraulic actuator system is presented, including the variable force solenoid and clutch piston, and validated by a test. Subsequently, the open-loop clutch prefill is simulated based on the proposed model. Two control parameters of the prefill, fast fill time and stable fill pressure is analyzed with regard to the impact on the prefill. The former has great effects on the pressure transients, the latter directly influences the touch point. Finally, an adaptive method is proposed for the clutch prefill during gear shifting, in which clutch fill control parameters are adjusted adaptively and continually. The adaptive strategy is changing the stable fill pressure according to the current clutch slip during a gearshift, improving the next prefill process. The stable fill pressure is increased by means of the clutch slip while underfill and decreased with a constant value for overfill. The entire strategy is designed in the Simulink/Stateflow, and implemented in the transmission control unit with optimization. Road vehicle test results have shown the strategy realized its adaptive capability and proven it improves the shifting comfort.

Keywords: clutch prefill, clutch slip, dual clutch transmission, touch point, variable force solenoid

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Authors: Zehra Aybike Kılıç, Alpin Köknel Yener

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Daylight is a powerful driver in terms of improving human health, enhancing productivity and creating sustainable solutions by minimizing energy demand. A proper daylighting system allows not only a pleasant and attractive visual and thermal environment, but also reduces lighting energy consumption and heating/cooling energy load with the optimization of aperture size, glazing type and solar control strategy, which are the major design parameters of daylighting system design. Particularly, in high-rise buildings where large openings that allow maximum daylight and view out are preferred, evaluation of daylight performance by considering the major parameters of the building envelope design becomes crucial in terms of ensuring occupants’ comfort and improving energy efficiency. Moreover, it is increasingly necessary to examine the daylighting design of high-rise residential buildings, considering the share of residential buildings in the construction sector, the duration of occupation and the changing space requirements. This study aims to identify a proper daylighting design solution considering window area, glazing type and solar control strategy for a high-residential building in terms of visual comfort and lighting energy efficiency. The dynamic simulations are carried out/conducted by DIVA for Rhino version 4.1.0.12. The results are evaluated with Daylight Autonomy (DA) to demonstrate daylight availability in the space and Daylight Glare Probability (DGP) to describe the visual comfort conditions related to glare. Furthermore, it is also analyzed that the lighting energy consumption occurred in each scenario to determine the optimum solution reducing lighting energy consumption by optimizing daylight performance. The results revealed that it is only possible that reduction in lighting energy consumption as well as providing visual comfort conditions in buildings with the proper daylighting design decision regarding glazing type, transparency ratio and solar control device.

Keywords: daylighting , glazing type, lighting energy efficiency, residential building, solar control strategy, visual comfort

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

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We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

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Authors: Katarina Rogulj, Ivana Racetin, Jelena Kilic

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In this study, the fuzzy logic approach (FLA) was developed for construction project management (CPM) under uncertainty and duality. The focus was on decision making in selecting the type of the glass facade for a residential-commercial building in the main design. The adoption of fuzzy sets was capable of reflecting construction managers’ reliability level over subjective judgments, and thus the robustness of the system can be achieved. An α-cuts method was utilized for discretizing the fuzzy sets in FLA. This method can communicate all uncertain information in the optimization process, taking into account the values of this information. Furthermore, FLA provides in-depth analyses of diverse policy scenarios that are related to various levels of economic aspects when it comes to the construction projects' valid decision making. The developed approach is applied to CPM to demonstrate its applicability. Analyzing the materials of glass facades, variants were defined. The development of the FLA for the CPM included relevant construction projec'ts stakeholders that were involved in the criteria definition to evaluate each variant. Using fuzzy Decision-Making Trial and Evaluation Laboratory Method (DEMATEL) comparison of the glass facade was conducted. This way, a rank, according to the priorities for inclusion into the main design, of variants is obtained. The concept was tested on a residential-commercial building in the city of Rijeka, Croatia. The newly developed methodology was then compared with the existing one. The aim of the research was to define an approach that will improve current judgments and decisions when it comes to the material selection of buildings facade as one of the most important architectural and engineering tasks in the main design. The advantage of the new methodology compared to the old one is that it includes the subjective side of the managers’ decisions, as an inevitable factor in each decision making. The proposed approach can help construction projects managers to identify the desired type of glass facade according to their preference and practical conditions, as well as facilitate in-depth analyses of tradeoffs between economic efficiency and architectural design.

Keywords: construction projects management, DEMATEL, fuzzy logic approach, glass façade selection

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Authors: Y. Trantafyllou, C. Alexandraki

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Music interpretation accounts to the way musicians shape their performance by deliberately deviating from composers’ intentions, which are commonly communicated via some form of music transcription, such as a music score. For transcribed and non-improvised music, music expression is manifested by introducing subtle deviations in tempo, dynamics and articulation during the evolution of performance. This paper presents an application, named FlameCens, which, given two recordings of the same piece of music, presumably performed by different musicians, allow visualising deviations in tempo and dynamics during playback. The application may also compare a certain performance to the music score of that piece (i.e. MIDI file), which may be thought of as an expression-neutral representation of that piece, hence depicting the expressive queues employed by certain performers. FlameCens uses the Dynamic Time Warping algorithm to compare two audio sequences, based on CENS (Chroma Energy distribution Normalized Statistics) audio features. Expressive deviations are illustrated in a moving flame, which is generated by an animation of particles. The length of the flame is mapped to deviations in dynamics, while the slope of the flame is mapped to tempo deviations so that faster tempo changes the slope to the right and slower tempo changes the slope to the left. Constant slope signifies no tempo deviation. The detected deviations in tempo and dynamics can be additionally recorded in a text file, which allows for offline investigation. Moreover, in the case of monophonic music, the color of particles is used to convey the pitch of the notes during performance. FlameCens has been implemented in Python and it is openly available via GitHub. The application has been experimentally validated for different music genres including classical, contemporary, jazz and popular music. These experiments revealed that FlameCens can be a valuable tool for music specialists (i.e. musicians or musicologists) to investigate the expressive performance strategies employed by different musicians, as well as for music audience to enhance their listening experience.

Keywords: audio synchronization, computational music analysis, expressive music performance, information visualization

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Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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Authors: Haobin Zheng, Xiang Zhang, Yong Shen, Hongxin Zou

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The research focuses on mode-locked fiber lasers with a non-linear amplifying loop mirror (NALM). Although these lasers have shown potential, they still have limitations in terms of low repetition rate. The self-starting of mode-locking in NALM is influenced by the cross-phase modulation (XPM) effect, which has not been thoroughly studied. The aim of this study is two-fold. First, to overcome the difficulties associated with increasing the repetition rate in mode-locked fiber lasers with NALM. Second, to analyze the influence of XPM on self-starting of mode-locking. The power distributions of two counterpropagating beams in the NALM and the differential non-linear phase shift (NPS) accumulations are calculated. The analysis is conducted from the perspective of NPS accumulation. The differential NPSs for continuous wave (CW) light and pulses in the fiber loop are compared to understand the inverse saturable absorption (ISA) mechanism during pulse formation in NALM. The study reveals a difference in differential NPSs between CW light and pulses in the fiber loop in NALM. This difference leads to an ISA mechanism, which has not been extensively studied in artificial saturable absorbers. The ISA in NALM provides an explanation for experimentally observed phenomena, such as active mode-locking initiation through tapping the fiber or fine-tuning light polarization. These findings have important implications for optimizing the design of NALM and reducing the self-starting threshold of high-repetition-rate mode-locked fiber lasers. This study contributes to the theoretical understanding of NALM mode-locked fiber lasers by exploring the ISA mechanism and its impact on self-starting of mode-locking. The research fills a gap in the existing knowledge regarding the XPM effect in NALM and its role in pulse formation. This study provides insights into the ISA mechanism in NALM mode-locked fiber lasers and its role in selfstarting of mode-locking. The findings contribute to the optimization of NALM design and the reduction of self-starting threshold, which are essential for achieving high-repetition-rate operation in fiber lasers. Further research in this area can lead to advancements in the field of mode-locked fiber lasers with NALM.

Keywords: inverse saturable absorption, NALM, mode-locking, non-linear phase shift

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Authors: Aastha Paliwal, H. N. Chanakya, S. Dasappa

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Lignocellulose, as an alternate feedstock for biogas production, has been an active area of research. However, lignocellulose poses a lot of operational difficulties- widespread variation in the structural organization of lignocellulosic matrix, amenability to degradation, low bulk density, to name a few. Amongst these, the low bulk density of the lignocellulosic feedstock is crucial to the process operation and optimization. Low bulk densities render the feedstock floating in conventional liquid/wet digesters. Low bulk densities also restrict the maximum achievable organic loading rate in the reactor, decreasing the power density of the reactor. However, during digestion, lignocellulose undergoes very high compaction (up to 26 times feeding density). This first reduces the achievable OLR (because of low feeding density) and compaction during digestion, then renders the reactor space underutilized and also imposes significant mass transfer limitations. The objective of this paper was to understand the effects of compacting lignocellulose on mass transfer and the influence of loss of different components on the bulk density and hence structural integrity of the digesting lignocellulosic feedstock. 10 different lignocellulosic feedstocks (monocots and dicots) were digested anaerobically in a fed-batch, leach bed reactor -solid-state stratified bed reactor (SSBR). Percolation rates of the recycled bio-digester liquid (BDL) were also measured during the reactor run period to understand the implication of compaction on mass transfer. After 95 ds, in a destructive sampling, lignocellulosic feedstocks digested at different SRT were investigated to quantitate the weekly changes in bulk density and lignocellulosic composition. Further, percolation rate data was also compared to bulk density data. Results from the study indicate loss of hemicellulose (r²=0.76), hot water extractives (r²=0.68), and oxalate extractives (r²=0.64) had dominant influence on changing the structural integrity of the studied lignocellulose during anaerobic digestion. Further, feeding bulk density of the lignocellulose can be maintained between 300-400kg/m³ to achieve higher OLR, and bulk density of 440-500kg/m³ incurs significant mass transfer limitation for high compacting beds of dicots.

Keywords: anaerobic digestion, bulk density, feed compaction, lignocellulose, lignocellulosic matrix, cellulose, hemicellulose, lignin, extractives, mass transfer

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Authors: Sarra K. Ikhlef, Onita Basu

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Natural organic matter (NOM) removal efficiency using drinking water treatment biological filters can be highly influenced by backwashing conditions. Backwashing has the ability to remove the accumulated biomass and particles in order to regenerate the biological filters' removal capacity and prevent excessive headloss buildup. A lab scale system consisting of 3 biological filters was used in this study to examine the implications of different backwash strategies on biological filtration performance. The backwash procedures were evaluated based on their impacts on dissolved organic carbon (DOC) removals, biological filters’ biomass, backwash water volume usage, and particle removal. Results showed that under nutrient limited conditions, the simultaneous use of air and water under collapse pulsing conditions lead to a DOC removal of 22% which was significantly higher (p>0.05) than the 12% removal observed under water only backwash conditions. Employing a bed expansion of 20% under nutrient supplemented conditions compared to a 30% reference bed expansion while using the same amount of water volume lead to similar DOC removals. On the other hand, utilizing a higher bed expansion (40%) lead to significantly lower DOC removals (23%). Also, a backwash strategy that reduced the backwash water volume usage by about 20% resulted in similar DOC removals observed with the reference backwash. The backwash procedures investigated in this study showed no consistent impact on biological filters' biomass concentrations as measured by the phospholipids and the adenosine tri-phosphate (ATP) methods. Moreover, none of these two analyses showed a direct correlation with DOC removal. On the other hand, dissolved oxygen (DO) uptake showed a direct correlation with DOC removals. The addition of the extended terminal subfluidization wash (ETSW) demonstrated no apparent impact on DOC removals. ETSW also successfully eliminated the filter ripening sequence (FRS). As a result, the additional water usage resulting from implementing ETSW was compensated by water savings after restart. Results from this study provide insight to researchers and water treatment utilities on how to better optimize the backwashing procedure for the goal of optimizing the overall biological filtration process.

Keywords: biological filtration, backwashing, collapse pulsing, ETSW

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Authors: Remo Waser, Simon Maranda, Anastasia Stamatiou, Ludger J. Fischer, Joerg Worlitschek

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In latent heat storage, a phase change material (PCM) is used to store thermal energy. The heat transfer rate during solidification is limited and considered as a key challenge in the development of latent heat storages. Thus, finned heat exchangers (HEX) are often utilized to increase the heat transfer rate of the storage system. In this study, a new modeling approach to calculating the heat transfer rate in latent thermal energy storages with complex HEX geometries is presented. This model allows for an optimization of the HEX design in terms of costs and thermal performance of the system. Modeling solidification processes requires the calculation of time-dependent heat conduction with moving boundaries. Commonly used computational fluid dynamic (CFD) methods enable the analysis of the heat transfer in complex HEX geometries. If applied to the entire storage, the drawback of this approach is the high computational effort due to small time steps and fine computational grids required for accurate solutions. An alternative to describe the process of solidification is the so-called temperature-based approach. In order to minimize the computational effort, a quasi-stationary assumption can be applied. This approach provides highly accurate predictions for tube heat exchangers. However, it shows unsatisfactory results for more complex geometries such as finned tube heat exchangers. The presented simulation model uses a temporal and spatial discretization of heat exchanger tube. The spatial discretization is based on the smallest possible symmetric segment of the HEX. The heat flow in each segment is calculated using finite volume method. Since the heat transfer fluid temperature can be derived using energy conservation equations, the boundary conditions at the inner tube wall is dynamically updated for each time step and segment. The model allows a prediction of the thermal performance of latent thermal energy storage systems using complex HEX geometries with considerably low computational effort.

Keywords: modelling of solidification, finned tube heat exchanger, latent thermal energy storage

Procedia PDF Downloads 249