Search results for: linear density of reinforcement

Authors: Ines Antunes, Andrea Massari, Concetta Bartucca

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Greenhouse gasses (GHG) role in the atmosphere has been well known since the 19th century; however, researchers have begun to relate them to climate changes only in the second half of the following century. From this moment, scientists started to correlate the presence of GHG such as CO₂ with the global warming phenomena. This has raised the awareness not only of those who were experts in this field but also of public opinion, which is becoming more and more sensitive to environmental pollution and sustainability issues. Nowadays the reduction of GHG emissions is one of the principal objectives of EU nations. The target is an 80% reduction of emissions in 2050 and to reach the important goal of carbon neutrality. Road sector is responsible for an important amount of those emissions (about 20%). The most part is due to traffic, but a good contribution is also given directly or indirectly from road construction and maintenance. Raw material choice and reuse of post-consumer plastic rather than a cleverer design of roads have an important contribution to reducing carbon footprint. Bituminous membranes can be successfully used as reinforcement systems in asphalt layers to improve road pavement performance against cracking. Composite materials coupling membranes with grids and/or fabrics should be able to combine improved tensile properties of the reinforcement with stress absorbing and waterproofing effects of membranes. Polyglass, with its brand dedicated to road construction and maintenance called Polystrada, has done more than this. The company's target was not only to focus sustainability on the final application but also to implement a greener mentality from the cradle to the grave. Starting from production, Polyglass has made important improvements finalized to increase efficiency and minimize waste. The installation of a trigeneration plant and the usage of selected production scraps inside the products as well as the reduction of emissions into the environment, are one of the main efforts of the company to reduce impact during final product build-up. Moreover, the benefit given by installing Polystrada products brings a significant improvement in road lifetime. This has an impact not only on the number of maintenance or renewal that needs to be done (build less) but also on traffic density due to works and road deviation in case of operations. During the end of the life of a road, Polystrada products can be 100% recycled and milled with classical systems used without changing the normal maintenance procedures. In this work, all these contributions were quantified in terms of CO₂ emission thanks to an LCA analysis. The data obtained were compared with a classical system or a standard production of a membrane. What it is possible to see is that the usage of Polyglass products for street maintenance and building gives a significant reduction of emissions in case of membrane installation under the road wearing course.

Keywords: CO₂ emission, LCA, maintenance, sustainability

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Authors: S. Khan, A. Khan, Abdul R. Soomrani, Raja F. Zafar, A. Waqas, G. Akbar

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This paper proposes a low-complexity image interpolation method. Image interpolation is used to convert a low dimension video/image to high dimension video/image. The objective of a good interpolation method is to upscale an image in such a way that it provides better edge preservation at the cost of very low complexity so that real-time processing of video frames can be made possible. However, low complexity methods tend to provide real-time interpolation at the cost of blurring, jagging and other artifacts due to errors in slope calculation. Non-linear methods, on the other hand, provide better edge preservation, but at the cost of high complexity and hence they can be considered very far from having real-time interpolation. The proposed method is a linear method that uses gradient orientation for slope calculation, unlike conventional linear methods that uses the contrast of nearby pixels. Prewitt edge detection is applied to separate uniform regions and edges. Simple line averaging is applied to unknown uniform regions, whereas unknown edge pixels are interpolated after calculation of slopes using gradient orientations of neighboring known edge pixels. As a post-processing step, bilateral filter is applied to interpolated edge regions in order to enhance the interpolated edges.

Keywords: edge detection, gradient orientation, image upscaling, linear interpolation, slope tracing

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Authors: K. N. S. Kasi Viswanadham

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Coupled system of second order linear and nonlinear boundary value problems occur in various fields of Science and Engineering. In the formulation of the problem, any one of 81 possible types of boundary conditions may occur. These 81 possible boundary conditions are written as a combination of four boundary conditions. To solve a coupled system of boundary value problem with these converted boundary conditions, a collocation method with cubic B-splines as basis functions has been developed. In the collocation method, the mesh points of the space variable domain have been selected as the collocation points. The basis functions have been redefined into a new set of basis functions which in number match with the number of mesh points in the space variable domain. The solution of a non-linear boundary value problem has been obtained as the limit of a sequence of solutions of linear boundary value problems generated by quasilinearization technique. Several linear and nonlinear boundary value problems are presented to test the efficiency of the proposed method and found that numerical results obtained by the present method are in good agreement with the exact solutions available in the literature.

Keywords: collocation method, coupled system, cubic b-splines, mesh points

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Authors: Acumsiri Tantikarnpanit

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This paper aims to examine the relationship between urbanization and income inequality in Thailand during the period 2002–2020. Using a panel of data for 76 provinces collected from Thailand’s National Statistical Office (Labor Force Survey: LFS), as well as geospatial data from the U.S. Air Force Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite Day/Night band (VIIRS-DNB) satellite for nineteen selected years. This paper employs two different definitions to identify urban areas: 1) Urban areas defined by Thailand's National Statistical Office (Labor Force Survey: LFS), and 2) Urban areas estimated using nighttime light data from the DMSP and VIIRS-DNB satellite. The second method includes two sub-categories: 2.1) Determining urban areas by calculating nighttime light density with a population density of 300 people per square kilometer, and 2.2) Calculating urban areas based on nighttime light density corresponding to a population density of 1,500 people per square kilometer. The empirical analysis based on Ordinary Least Squares (OLS), fixed effects, and random effects models reveals a consistent U-shaped relationship between income inequality and urbanization. The findings from the econometric analysis demonstrate that urbanization or population density has a significant and negative impact on income inequality. Moreover, the square of urbanization shows a statistically significant positive impact on income inequality. Additionally, there is a negative association between logarithmically transformed income and income inequality. This paper also proposes the inclusion of satellite imagery, geospatial data, and spatial econometric techniques in future studies to conduct quantitative analysis of spatial relationships.

Keywords: income inequality, nighttime light, population density, Thailand, urbanization

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Authors: Hamid Mustafa, Huson J. Heather, Kim Eiusoo, Adeela Ajmal, Tad S. Sonstegard

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The objective of this study was to evaluate the informativeness of Bovine high density SNPs genotyping in Sahiwal cattle population. This is a first attempt to assess the Bovine HD SNP genotyping array in any Pakistani indigenous cattle population. To evaluate these SNPs on genome wide scale, we considered 777,962 SNPs spanning the whole autosomal and X chromosomes in Sahiwal cattle population. Fifteen (15) non related gDNA samples were genotyped with the bovine HD infinium. Approximately 500,939 SNPs were found polymorphic (MAF > 0.05) in Sahiwal cattle population. The results of this study indicate potential application of Bovine High Density SNP genotyping in Pakistani indigenous cattle population. The information generated from this array can be applied in genetic prediction, characterization and genome wide association studies of Pakistani Sahiwal cattle population.

Keywords: Sahiwal cattle, polymorphic SNPs, genotyping, Pakistan

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

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Authors: Boutahar Lhoucine, El Bikri Khalid, Benamar Rhali

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In this paper, the non-linear free axisymmetric vibration of a thin annular plate made of functionally graded material (FGM) has been studied by using the energy method and a multimode approach. FGM properties vary continuously as well as non-homogeneity through the thickness direction of the plate. The theoretical model is based on the classical plate theory and the Von Kármán geometrical non-linearity assumptions. An approximation has been adopted in the present work consisting of neglecting the in-plane deformation in the formulation. Hamilton’s principle is used to derive the governing equation of motion. The problem is solved by a numerical iterative procedure in order to obtain more accurate results for vibration amplitudes up to 1.5 times the plate thickness. The numerical results are given for the first axisymmetric non-linear mode shape for a wide range of vibration amplitudes and they are presented either in tabular form or in graphical form to show the effect that the vibration amplitude and the variation in material properties have significant effects on the frequencies and the bending stresses in large amplitude vibration of the functionally graded annular plate.

Keywords: non-linear vibrations, annular plates, large amplitudes, functionally graded material

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Authors: Intan Maisarah Abd Rahim, Herlina Abdul Rahim, Rashidah Ghazali

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Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.

Keywords: diabetes, glucose level, linear, near-infrared, non-invasive, prediction system

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Authors: Baghdasaryan Marinka

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Monitoring the distribution of electric power consumption in the technological process of ore grinding is conducted. As a result, the impacts of the mill filling rate, the productivity of the ore supply, the volumetric density of the grinding balls, the specific density of the ground ore, and the relative speed of the mill rotation on the specific consumption of electric power have been studied. The power and technological factors affecting the reactive power generated by the synchronous motors, operating within the technological scheme are studied. A block diagram for evaluating the power consumption modes of the technological process is presented, which includes the analysis of the technological scheme, the determination of the place and volumetric density of the ore-grinding mill, the evaluation of the technological and power factors affecting the energy saving process, as well as the assessment of the electric power standards.

Keywords: electric power standard, factor, ore grinding, power consumption, reactive power, technological

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

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Authors: Rajendra Kumar

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We study the Electronic spectral density of a double coupled quantum dots sandwich between superconducting leads, where one of the superconducting leads (QD1) are connected with left superconductor lead and (QD1) also connected right superconductor lead. (QD1) and (QD2) are coupling to each other. The electronic spectral density through a quantum dots between superconducting leads having s-wave symmetry of the superconducting order parameter. Such junction is called superconducting –quantum dot (S-QD-S) junction. For this purpose, we have considered a renormalized Anderson model that includes the double coupled of the superconducting leads with the quantum dots level and an attractive BCS-type effective interaction in superconducting leads. We employed the Green’s function technique to obtain superconducting order parameter with the BCS framework and Ambegaoker-Baratoff formalism to analyze the electronic spectral density through such (S-QD-S) junction. It has been pointed out that electronic spectral density through such a junction is dominated by the attractive the paring interaction in the leads, energy of the level on the dot with respect to Fermi energy and also on the coupling parameter of the two in an essential way. On the basis of numerical analysis we have compared the theoretical results of electronic spectral density with the recent transport existing theoretical analysis. QDs is the charging energy that may give rise to effects based on the interplay of Coulomb repulsion and superconducting correlations. It is, therefore, an interesting question to ask how the discrete level spectrum and the charging energy affect the DC and AC Josephson transport between two superconductors coupled via a QD. In the absence of a bias voltage, a finite DC current can be sustained in such an S-QD-S by the DC Josephson effect.

Keywords: quantum dots, S-QD-S junction, BCS superconductors, Anderson model

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Authors: B. Bouadjemi, S. Bentata, W. Benstaali, A. Souidi, A. Abbad, T. Lantri, Z. Aziz, A. Zitouni

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The electronic and magnetic structures of double perovskite Ba2MnMoO6 are systematically investigated using the first principle method of the Full Potential Linear Augmented Plane Waves Plus the Local Orbitals (FP-LAPW+LO) within the Local Spin Density Approximation (LSDA) and the Generalized Gradient Approximation (GGA). In order to take into account the strong on-site Coulomb interaction, we included the Hubbard correlation terms: LSDA+U and GGA+U approaches. Whereas half-metallic ferromagnetic character is observed due to dominant Mn spin-up and Mo spin-down contributions insulating ground state is obtained. The LSDA+U and GGA+U calculations yield better agreement with the theoretical and the experimental results than LSDA and GGA do.

Keywords: electronic structure, double perovskite, first principles, Ba2MnMoO6, half-metallic

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Authors: Abdullah Eqal Al Mazrooei

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Kalman filter is a famous algorithm that utilizes to estimate the state in the linear systems. It has numerous applications in technology and science. Since of the most of applications in real life can be described by nonlinear systems. So, Kalman filter does not work with the nonlinear systems because it is suitable to linear systems only. In this work, a nonlinear filtering algorithm is presented which is suitable to use with the special kinds of nonlinear systems. This filter generalizes the Kalman filter. This means that this filter also can be used for the linear systems. Our algorithm depends on a special linearization of the second degree. We introduced the nonlinear algorithm with a bilinear state-space model. A simulation example is presented to illustrate the efficiency of the algorithm.

Keywords: Kalman filter, filtering algorithm, nonlinear systems, state-space model

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Authors: Claudia H. Swanson, Jens Günster

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This research addresses the densification via compaction and sintering of naturally occurring rock salt which was motivated by the fact that in a saline environment rock salt is thermodynamically stable and does show a mechanical behavior compatible to the surrounding host material. The sintering of rock salt powder compacts was systematically investigated using temperature and pressure as variables for the sinter process. The behavior of rock salt showed segregations of anhydrite, CaSO4 - the major impurity found in rock salt, to the grain boundaries between individual sodium chloride crystals. Powder compacts treated with lower pressures lost those anhydrite segregates over time while high pressure treated compacts remained with anhydrite segregates. The density reached in this study is 2.008 g cm-3 corresponding to a density of 92.5 % of the theoretical value. This high density is making the sintering a promising technique for rock salt as applications in underground appropriate environment.

Keywords: rock salt, sinter, anhydrite, nuclear safety

Procedia PDF Downloads 489

Authors: Jared Beard, Ali Baheri

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As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

Procedia PDF Downloads 158

Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: Neetu Malik, Sharad Shrivastava, Subrata Bandhu Ghosh

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Biocomposite materials were fabricated using mixing biodegradable polymer polycaprolactone (PCL) and Thermally Exfoliated Graphene Oxide (TEGO) through solution casting. Various samples of biocomposite films were prepared by varying the TEGO wt% composition by 0.1%, 0.5%, 1% and 1.5%. Thereafter, the density and water absorption of the composites were investigated with respect to immersion time in water. The moisture absorption results show that with an increase in weight percentage (from 0.1 to wt 1.5%) of TEGO within the biopolymer films, the absorption value of bio-nanocomposite films reduced rapidly from 27.4% to 14.3%. The density of hybrid composites also increased with increase in weight percentage of TEGO. These results indicate that the optimized composition of constituents in composite membrane could effectively reduce the anhydrous conditions of bio-composite film.

Keywords: thermally exfoliated graphene oxide, PCL, water absorption, density

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Authors: Faris Alkhalil, Rana Bitar, Amer Azaz, Hisham Natour, Noora Almeraikhi, Mohamad Miqdady

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Background: Children with liver transplantation are achieving very good survival and so there is now a need to concentrate on achieving good health in these patients and preventing disease. Immunosuppressive medications have side effects that need to be monitored and if possible avoided. Glucocorticoids and calcineurin inhibitors are detrimental to bone and mineral homeostasis in addition steroids can also affect linear growth. Steroid sparing regimes in renal transplant children has shown to improve children’s height. Aim: We aim to review the growth and bone health of children post liver transplant by measuring bone mineral density (BMD) using dual energy X-ray absorptiometry (DEXA) scan and assessing if there is a clear link between poor growth and impaired bone health and use of long term steroids. Subjects and Methods: This is a single centre retrospective Cohort study, we reviewed the medical notes of children (0-16 years) who underwent a liver transplantation between November 2000 to November 2016 and currently being followed at our centre. Results: 39 patients were identified (25 males and 14 females), the median transplant age was 2 years (range 9 months - 16 years), and the median follow up was 6 years. Four patients received a combined transplant, 2 kidney and liver transplant and 2 received a liver and small bowel transplant. The indications for transplant included, Biliary Atresia (31%), Acute Liver failure (18%), Progressive Familial Intrahepatic Cholestasis (15%), transplantable metabolic disease (10%), TPN related liver disease (8%), Primary Hyperoxaluria (5%), Hepatocellular carcinoma (3%) and other causes (10%). 36 patients (95%) were on a calcineurin inhibitor (34 patients were on Tacrolimus and 2 on Cyclosporin). The other three patients were on Sirolimus. Low dose long-term steroids was used in 21% of the patients. A considerable proportion of the patients had poor growth. 15% were below the 3rd centile for weight for age and 21% were below the 3rd centile for height for age. Most of our patients with poor growth were not on long term steroids. 49% of patients had a DEXA scan post transplantation. 21% of these children had low bone mineral density, one patient had met osteoporosis criteria with a vertebral fracture. Most of our patients with impaired bone health were not on long term steroids. 20% of the patients who did not undergo a DEXA scan developed long bone fractures and 50% of them were on long term steroid use which may suggest impaired bone health in these patients. Summary and Conclusion: The incidence of impaired bone health, although studied in limited number of patients; was high. Early recognition and treatment should be instituted to avoid fractures and improve bone health. Many of the patients were below the 3rd centile for weight and height however there was no clear relationship between steroid use and impaired bone health, reduced weight and reduced linear height.

Keywords: bone, growth, pediatric, liver, transplantation

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: Waris Piyaphon, Sathaphorn O-Suwankul, Kittima Bootdee, Manit Nithitanakul

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Starch from rice was used as a filler in low density polyethylene in preparation of low density polyethylene/rice starch composite. This study aims to prepare LDPE/rice starch composites. Glycerol (GC) was used as a plasticizer in order to increase dispersion and reduce agglomeration of rice starch in low density polyethylene (LDPE) matrix. Low density polyethylene grafted maleic anhydride (LDPE-g-MA) was used as a compatibilizer to increase the compatibility between LDPE and rice starch. The content of rice starch was varied between 10, 20, and 30 %wt. Results indicated that increase of rice starch content reduced tensile strength at break, elongation, and impact strength of composites. LDPE-g-MA showed positive effect on mechanical properties which increased in tensile strength and impact properties as well as compatibility between rice starch and LDPE matrix. Moreover, the addition of LDPE-g-MA significantly improved the impact strength by 50% compared to neat composite. The incorporation of GC enhanced the processability of composite. Introduction of GC affected the viscosity after blending by reducing the viscosity at all shear rate. The presence of plasticizer increased the impact strength but decreased the stiffness of composite. Water absorption of the composite was increased when plasticizer was added.

Keywords: composite material, plastic starch composite, polyethylene composite, PE grafted maleic anhydride

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Authors: T. Zergoug, S. E. H. Abaidia, A. Nedjar, M. Y. Mokeddem

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Physical properties of uranium di-nitride (UN2) were investigated in detail using first principles calculations based on density functional theory. To treat the strong correlation effects caused by 5f Uranium valence electrons, on-site Coulomb interaction correction via the Hubbard-like term, U (DFT+U) was employed. The UN2 structural, mechanical and thermodynamic properties were calculated within DFT and Various U of DFT+U approach. The Perdew–Burke–Ernzerhof (PBE.5.2) version of the generalized gradient approximation (GGA) is used to describe the exchange-correlation with the projector-augmented wave (PAW) pseudo potentials. A comparative study shows that results are improved by using the Hubbard formalism for a certain U value correction like the structural parameter. For some physical properties the variation versus Hubbard U is strong like Young modulus but for others it is weakly noticeable such as the density of state (DOS) or bulk modulus. We noticed also that up from U=7.5 eV, elastic results become not conform to the cubic cell elastic criteria since the C44 values turn out to be negative.

Keywords: uranium diNitride, UN2, DFT+U, elastic properties

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Authors: E. M. D. Akuoko, Eliana Vasquez Osorio, Marcel Van Herk, Marianne Aznar

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Radiotherapy is an integral part of treatment for many patients with breast cancer. However, side effects can occur, e.g., fibrosis or erythema. If patients at higher risks of radiation-induced side effects could be identified before treatment, they could be given more individual information about the risks and benefits of radiotherapy. We hypothesize that breast density is correlated with the risk of side effects and present a novel method for automatic evaluation based on radiotherapy planning CT scans. Methods: 799 supine CT scans of breast radiotherapy patients were available from the REQUITE dataset. The methodology was first established in a subset of 114 patients (cohort 1) before being applied to the whole dataset (cohort 2). All patients were scanned in the supine position, with arms up, and the treated breast (ipsilateral) was identified. Manual experts contour available in 96 patients for both the ipsilateral and contralateral breast in cohort 1. Breast tissue was segmented using atlas-based automatic contouring software, ADMIRE® v3.4 (Elekta AB, Sweden). Once validated, the automatic segmentation method was applied to cohort 2. Breast density was then investigated by thresholding voxels within the contours, using Otsu threshold and pixel intensity ranges based on Hounsfield units (-200 to -100 for fatty tissue, and -99 to +100 for fibro-glandular tissue). Volumetric breast density (VBD) was defined as the volume of fibro-glandular tissue / (volume of fibro-glandular tissue + volume of fatty tissue). A sensitivity analysis was performed to verify whether calculated VBD was affected by the choice of breast contour. In addition, we investigated the correlation between volumetric breast density (VBD) and patient age and breast size. VBD values were compared between ipsilateral and contralateral breast contours. Results: Estimated VBD values were 0.40 (range 0.17-0.91) in cohort 1, and 0.43 (0.096-0.99) in cohort 2. We observed ipsilateral breasts to be denser than contralateral breasts. Breast density was negatively associated with breast volume (Spearman: R=-0.5, p-value < 2.2e-16) and age (Spearman: R=-0.24, p-value = 4.6e-10). Conclusion: VBD estimates could be obtained automatically on a large CT dataset. Patients’ age or breast volume may not be the only variables that explain breast density. Future work will focus on assessing the usefulness of VBD as a predictive variable for radiation-induced side effects.

Keywords: breast cancer, automatic image segmentation, radiotherapy, big data, breast density, medical imaging

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Authors: Noureddine Benharkat, Abdelkader Chouaih, Nourdine Boukabcha

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A thiourea derivative compound was synthesized and subjected to structural analysis using single-crystal X-ray diffraction (XRD). The crystallographic data unveiled its crystallization in the P21/c space group within the monoclinic system. Examination of the dihedral angles indicated a notable non-planar structure. To support and interpret these resulats, density functional theory (DFT) calculations were conducted utilizing the B3LYP functional along with a 6–311 G (d, p) basis set. Additionally, to assess the contribution of intermolecular interactions, Hirshfeld surface analysis and 2D fingerprint plots were employed. Various types of interactions, whether weak intramolecular or intermolecular, within a molecule can significantly impact its stability. The distinctive signature of non-covalent interactions can be detected solely through electron density analysis. The NCI-RDG analysis was employed to investigate both repulsive and attractive van der Waals interactions while also calculating the energies associated with intermolecular interactions and their characteristics. Additionally, a molecular docking study was studied to explain the structure-activity relationship, revealing that the title compound exhibited an affinity energy of -6.8 kcal/mol when docked with B-DNA (1BNA).

Keywords: computational chemistry, density functional theory, crystallography, molecular docking, molecular structure, powder x-ray diffraction, single crystal x-ray diffraction

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Authors: Yingjeng James Li, Yun Jyun Ou, Chih Chi Hsu, Chiao-Chih Hu

Abstract:

A fuel cell is a device that produces electric power by reacting fuel and oxidant electrochemically. There is no pollution produced from a fuel cell if hydrogen is employed as the fuel. Therefore, a fuel cell is considered as a zero emission device and is a source of green power. A membrane electrode assembly (MEA) is the key component of a fuel cell. It is, therefore, beneficial to develop MEAs with high performance. In this study, an MEA for proton exchange membrane fuel cell (PEMFC) was prepared from a 15-micron thick reinforced PEM. The active area of such MEA is 25 cm2. Carbon supported platinum (Pt/C) was employed as the catalyst for both anode and cathode. The platinum loading is 0.6 mg/cm2 based on the sum of anode and cathode. Commercially available carbon papers coated with a micro porous layer (MPL) serve as gas diffusion layers (GDLs). The original thickness of the GDL is 250 μm. It was compressed down to 163 μm when assembled into the single cell test fixture. Polarization curves were taken by using eight different test conditions. At our standard test condition (cell: 70 °C; anode: pure hydrogen, 100%RH, 1.2 stoic, ambient pressure; cathode: air, 100%RH, 3.0 stoic, ambient pressure), the cell current density is 1250 mA/cm2 at 0.6 V, and 2400 mA/cm2 at 0.4 V. At self-humidified condition and cell temperature of 55 °C, the cell current density is 1050 mA/cm2 at 0.6 V, and 2250 mA/cm2 at 0.4 V. Hydrogen crossover rate of the MEA is 0.0108 mL/min*cm2 according to linear sweep voltammetry experiments. According to the MEA’s Pt loading and the cyclic voltammetry experiments, the Pt electrochemical surface area is 60 m2/g. The ohmic part of the impedance spectroscopy results shows that the membrane resistance is about 60 mΩ*cm2 when the MEA is operated at 0.6 V.

Keywords: fuel cell, membrane electrode assembly, proton exchange membrane, reinforced

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Authors: Fatemeh Safdari, Amirnaser Shamkhali, Gholamabbas Parsafar

Abstract:

Carbon nanostructures are of great importance in academic research and industry, which can be mentioned to chemical sensors, catalytic processes, pharmaceutical and environmental issues. Common point in all of these applications is the occurrence of adsorption of molecules on these structures. Important carbon nanostructures in this case are mainly nanotubes and graphene. To modify pure graphene, recently, many experimental and theoretical studies have carried out to investigate of metal adsorption on graphene. In this work, the adsorption of CO molecules on pure graphene and on metal adatom on graphene surface has been simulated based on density functional theory (DFT). All calculations were performed by PBE functional and Troullier-Martins pseudopotentials. Density of states (DOS) for graphene-CO, graphen and CO around the Fermi energy has been moved and very small mixing occured which implies the physisorption of CO on the bare graphen surface. While, the results have showed that CO adsorption on transition-metal adatom on graphene surface is chemisorption.

Keywords: adsorption, density functional theory, graphene, metal adatom

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Authors: Moulay Driss Mellaoui, Abdallah Imjjad, Rachid Boutiddar, Haydar Mohammad-Salim, Nivedita Acharjee, Hassan Bourzi, Souad El Issami, Khalid Abbiche, Hanane Zejli

Abstract:

We have investigated the underlying molecular processes involved in the [3+2] cycloaddition (32CA) reactions between N-methyl-C-(2-furyl) nitrone and three acetylene derivatives: 4b, 5b, and 6b. For this investigation, we utilized molecular electron density theory (MEDT) and density functional theory (DFT) methods at the B3LYP-D3/6 31G (d) computational level. These 32CA reactions, which exhibit a zwitterionic (zw-type) nature, proceed through a one-step mechanism with activation enthalpies ranging from 8.80 to 14.37 kcal mol−1 in acetonitrile and ethanol solvents. When the nitrone reacts with phenyl methyl propiolate (4b), two regioisomeric pathways lead to the formation of two products: P1,5-4b and P1,4-4b. On the other hand, when the nitrone reacts with dimethyl acetylene dicarboxylate (5b) and acetylene dicarboxylic acid (but-2-ynedioic acid) (6b), it results in the formation of a single product. Through topological analysis, we can categorize the nitrone as a zwitterionic three-atom component (TAC). Furthermore, the analysis of conceptual density functional theory (CDFT) indices classifies the 32CA reactions of the nitrone with 4b, 5b, and 6b as forward electron density flux (FEDF) reactions. The study of bond evolution theory (BET) reveals that the formation of new C-C and C-O covalent bonds does not initiate in the transition states, as the intermediate stages of these reactions display pseudoradical centers of the atoms already involved in bonding.

Keywords: 4-isoxazoline, DFT/B3LYP-D3, regioselectivity, cycloaddition reaction, MEDT, ELF

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Authors: Tomoaki Hashimoto

Abstract:

Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.

Keywords: optimal control, stochastic systems, random dither, quantization

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Authors: Reza Miresmaeili, Asghar Heydari Astaraee, Fereshteh Dolati

Abstract:

In the present study, an analytical model based on dislocation density model was developed to simulate grain refinement in surface mechanical attrition treatment (SMAT). The correlation between SMAT time and development in plastic strain on one hand, and dislocation density evolution, on the other hand, was established to simulate the grain refinement in SMAT. A dislocation density-based constitutive material law was implemented using VUHARD subroutine. A random sequence of shots is taken into consideration for multiple impacts model using Python programming language by utilizing a random function. The simulation technique was to model each impact in a separate run and then transferring the results of each run as initial conditions for the next run (impact). The developed Finite Element (FE) model of multiple impacts describes the coverage evolution in SMAT. Simulations were run to coverage levels as high as 4500%. It is shown that the coverage implemented in the FE model is equal to the experimental coverage. It is depicted that numerical SMAT coverage parameter is adequately conforming to the well-known Avrami model. Comparison between numerical results and experimental measurements for residual stresses and depth of deformation layers confirms the performance of the established FE model for surface engineering evaluations in SMA treatment. X-ray diffraction (XRD) studies of grain refinement, including resultant grain size and dislocation density, were conducted to validate the established model. The full width at half-maximum in XRD profiles can be used to measure the grain size. Numerical results and experimental measurements of grain refinement illustrate good agreement and show the capability of established FE model to predict the gradient microstructure in SMA treatment.

Keywords: dislocation density, grain refinement, severe plastic deformation, simulation, surface mechanical attrition treatment

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Authors: A. A. James, A. O. Adesanya, M. R. Odekunle, D. G. Yakubu

Abstract:

This paper examines the development of one step, five hybrid point method for the solution of first order initial value problems. We adopted the method of collocation and interpolation of power series approximate solution to generate a continuous linear multistep method. The continuous linear multistep method was evaluated at selected grid points to give the discrete linear multistep method. The method was implemented using a constant order predictor of order seven over an overlapping interval. The basic properties of the derived corrector was investigated and found to be zero stable, consistent and convergent. The region of absolute stability was also investigated. The method was tested on some numerical experiments and found to compete favorably with the existing methods.

Keywords: interpolation, approximate solution, collocation, differential system, half step, converges, block method, efficiency

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Authors: Sharifah M. Syed Mohsin, Sayid J. Azimi, Abdoullah Namdar

Abstract:

The present article reports the findings of a study into the behavior of oil palm shell reinforced concrete (OPSRC) beams with the addition of kenaf fibres. The work aim is to examine the potential of using kenaf fibres to improve the strength and ductility of the OPSRC beams and also observe its potential in serving as part of shear reinforcement in the beams. Two different arrangements of the shear links in OPSRC beams with a selection of kenaf fibres (amount of [10kg/m] ^3 and [20kg/m] ^3) content are tested under monotonic loading. In the first arrangement, the kenaf fibres are added to the beam which has full shear reinforcement to study the structural behavior of OPSRC beams with fibres. In the second arrangement, the spacing between the shear links in the OPSRC beams are increased by 50% and experimental work is carried out to study the effect of kenaf fibres without compromising the beams strength and ductility. The results show that the addition of kenaf fibres enhanced the load carrying capacity, ductility and also altered the failure mode of the beams from a brittle shear mode to a flexural ductile one. Furthermore, the study depicts that kenaf fibres are compatible with OPSRC and suggest prospective results.

Keywords: oil palm shell reinforced concrete, kenaf fibres, peak strength, ductility

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