Search results for: pairing computation

Authors: Jian Li

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The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

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Authors: Hamidreza Namazi

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Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeffrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot.

Keywords: EEG signals, fractal analysis, fractal dimension, hurst exponent, Jeffrey’s measure

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Authors: Revanth Rallapalli

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Manually dispensing powders can be difficult as it requires gradually pouring and checking the amount on the scale to be dispensed. Current systems are manual and non-continuous in nature and are user-dependent and difficult to control powder dispensation. Recurrent dosing of powdered medicines in precise amounts quickly and accurately has been an all-time challenge. Various new powder dispensing mechanisms are being designed to overcome these challenges. A battery-operated screw conveyor mechanism is being innovated to overcome the above problems faced. These inventions are numerically evaluated at the concept development level by employing Computational Fluid Dynamics (CFD) of gas-solids multiphase flow systems. CFD has been very helpful in the development of such devices saving time and money by reducing the number of prototypes and testing. This paper describes a simulation of powder dispensation from the trocar’s end by considering the powder as secondary flow in the air, is simulated by using the technique called Dense Discrete Phase Model incorporated with Kinetic Theory of Granular Flow (DDPM-KTGF). By considering the volume fraction of powder as 50%, the transportation of powder from the inlet side to the trocar’s end side is done by rotation of the screw conveyor. The performance is calculated for a 1-sec time frame in an unsteady computation manner. This methodology will help designers in developing design concepts to improve the dispensation and the effective area within a quick turnaround time frame.

Keywords: multiphase flow, screw conveyor, transient, dense discrete phase model (DDPM), kinetic theory of granular flow (KTGF)

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Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, a one-dimensional (1d) Parallel Elasto- Plastic Model (PEPM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement, is presented. The parallel modeling concept is applied to discretize the continuously decreasing tangent stiffness function, thus allowing to simulate the dynamic behavior of seismic isolation bearings by putting linear elastic and nonlinear elastic-perfectly plastic elements in parallel. The mathematical model has been validated by comparing the experimental force-displacement hysteresis loops, obtained testing a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted numerically. Good agreement between the simulated and experimental results shows that the proposed model can be an effective numerical tool to predict the forcedisplacement relationship of seismic isolators within relatively large displacements. Compared to the widely used Bouc-Wen model, the proposed one allows to avoid the numerical solution of a first order ordinary nonlinear differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort, and requires the evaluation of only three model parameters from experimental tests, namely the initial tangent stiffness, the asymptotic tangent stiffness, and a parameter defining the transition from the initial to the asymptotic tangent stiffness.

Keywords: base isolation, earthquake engineering, parallel elasto-plastic model, seismic isolators, softening hysteresis loops

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Authors: Lormaine Anne A. Branzuela, Elysa V. Largo, Monet Concepcion M. Detras, Neil C. Concibido

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The electricity demand is still increasing, and currently, the Philippine government is investigating the feasibility of operating the Bataan Nuclear Power Plant (BNPP) to address the country’s energy problem. However, the lack of process safety studies on BNPP focused on the effects of hazardous substances on the integrity of the structure, equipment, and other components, have made the plant operationalization questionable to the public. The three major nuclear power plant incidents – TMI-2, Chernobyl, and Fukushima – have made many people hesitant to include nuclear energy in the energy matrix. This study focused on the safety evaluation of possible operations of a nuclear power plant installed with a Pressurized Water Reactor (PWR), which is similar to BNPP. Failure Mode and Effects Analysis (FMEA) is one of the Process Hazard Analysis (PHA) techniques used for the identification of equipment failure modes and minimizing its consequences. Using the FMEA technique, this study was able to recognize 116 different failure modes in total. Upon computation and ranking of the risk priority number (RPN) and criticality rating (CR), it showed that failure of the reactor coolant pump due to earthquakes is the most critical failure mode. This hazard scenario could lead to a nuclear meltdown and radioactive release, as identified by the FMEA team. Safeguards and recommended risk reduction strategies to lower the RPN and CR were identified such that the effects are minimized, the likelihood of occurrence is reduced, and failure detection is improved.

Keywords: PHA, FMEA, nuclear power plant, bataan nuclear power plant

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Authors: Abdulrahman Abdulrahman

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A side weir is a hydraulic structure set into the side of a channel. This structure is used for water level control in channels, to divert flow from a main channel into a side channel when the water level in the main channel exceeds a specific limit and as storm overflows from urban sewerage system. Computation of water surface over the side weirs is essential to determine the flow rate of the side weir. Analytical solutions for water surface profile along rectangular side weir are available only for the special cases of rectangular and trapezoidal channels considering constant specific energy. In this paper, a rectangular side weir located in a combined (trapezoidal with exponential) channel was considered. Expanding binominal series of integer and fraction powers and the using of reduction formula of cosine function integrals, a general analytical formula was obtained for water surface profile along a side weir in a combined (trapezoidal with exponential) channel. Since triangular, rectangular, trapezoidal and parabolic cross-sections are special cases of the combined cross section, the derived formula, is applicable to triangular, rectangular, trapezoidal cross-sections as analytical solution and semi-analytical solution to parabolic cross-section with maximum relative error smaller than 0.76%. The proposed solution should be a useful engineering tool for the evaluation and design of side weirs in open channel.

Keywords: analytical solution, combined channel, exponential channel, side weirs, trapezoidal channel, water surface profile

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Authors: Guang Zou, Kian Banisoleiman, Arturo González

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Crack initiation and propagation threatens structural integrity of welded joints and normally inspections are assigned based on crack propagation models. However, the approach based on crack propagation models may not be applicable for some high-quality welded joints, because the initial flaws in them may be so small that it may take long time for the flaws to develop into a detectable size. This raises a concern regarding the inspection planning of high-quality welded joins, as there is no generally acceptable approach for modeling the whole fatigue process that includes the crack initiation period. In order to address the issue, this paper reviews treatment methods for crack initiation period and initial crack size in crack propagation models applied to inspection planning. Generally, there are four approaches, by: 1) Neglecting the crack initiation period and fitting a probabilistic distribution for initial crack size based on statistical data; 2) Extrapolating the crack propagation stage to a very small fictitious initial crack size, so that the whole fatigue process can be modeled by crack propagation models; 3) Assuming a fixed detectable initial crack size and fitting a probabilistic distribution for crack initiation time based on specimen tests; and, 4) Modeling the crack initiation and propagation stage separately using small crack growth theories and Paris law or similar models. The conclusion is that in view of trade-off between accuracy and computation efforts, calibration of a small fictitious initial crack size to S-N curves is the most efficient approach.

Keywords: crack initiation, fatigue reliability, inspection planning, welded joints

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Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha

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Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.

Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier

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Authors: Kristine Joy Simpao

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Improving labour productivity is one of the most enthralling and challenging aspects of managing hotels and restaurant business. The demand to secure countless productivity became an increasingly pivotal role of managers to survive and sustain the business. Besides making business profitable, they are in the doom to make every resource to become productive and effective towards achieving company goal while maximizing the value of organization. This paper examines what productivity means to the services industry, in particular, to the hotel industry. This is underpinned by an investigation of the extent of practice of respondent hotels to the labour productivity aspect in the areas of materials management, human resource management and leadership management and in a way, computing the labour productivity ratios using the hotel simple ratios of productivity in order to find a suitable measurement and control standards for hotels with SBMA, Olongapo City as the locale of the study. The finding shows that hotels labour productivity ratings are not perfect with some practices that are far below particularly on strategic and operational decisions in improving performance and productivity of its human resources. It further proves of the no significant difference ratings among the respondent’s type in all areas which indicated that they are having similar perception of the weak implementation of some of the indicators in the labour productivity practices. Furthermore, the results in the computation of labour productivity efficiency ratios resulted relationship of employees versus labour productivity practices are inversely proportional. This study provides a potential measurement and control standards for the enhancement of hotels labour productivity. These standards should also contain labour productivity customized for standard hotels in Subic Bay Freeport Zone to assist hotel owners in increasing the labour productivity while meeting company goals and objectives effectively.

Keywords: labour productivity, hotel, measurement and control, standards, efficiency ratios, practices

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Authors: Mohiuddin Ahsanul Kabir Chowdhury, Nafisa Lira Huq, Afroza Khanom, Rafiqul Islam, Abdullah Nurus Salam Khan, Farhana Karim, Nabila Zaka, Shams El Arifeen, Sk. Masum Billah

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After having astounding achievements in reducing maternal mortality and achieving the target for Millennium Development Goal (MDG) 5, the Government of Bangladesh has set new target to reduce Maternal Mortality Ratio (MMR) to 70 per 100,000 live births aligning with targets of Sustainable Development Goals (SDGs). Aversion of deaths from maternal complication by ensuring quality health care could be an important path to accelerate the rate of reduction of MMR. This formative research was aimed at exploring the provision of quality maternal health services at different level of health facilities. The study was conducted in 1 district hospital (DH) and 4 Upazila health complexes (UHC) of Kurigram district of Bangladesh, utilizing both quantitative and qualitative research methods. We conducted 14 key informant interviews with facility managers and 20 in-depth interviews with health care providers and support staff. Besides, we observed 387 normal deliveries from which we found 17 cases of post partum haemorrhage (PPH) and 2 cases of eclampsia during the data collection period extended from July-September 2016. The quantitative data were analyzed by using descriptive statistics, and the qualitative component underwent thematic analysis with the broad themes of facility readiness for maternal complication management, and management of complications. Inadequacy in human resources has been identified as the most important bottleneck to provide quality care to manage maternal complications. The DH had a particular paucity of human resources in medical officer cadre where about 61% posts were unfilled. On the other hand, in the UHCs the positions mostly empty were obstetricians (75%, paediatricians (75%), staff nurses (65%), and anaesthetists (100%). The workload on the existing staff is increased because of the persistence of vacant posts. Unavailability of anesthetists and consultants does not permit the health care providers (HCP) of lower cadres to perform emergency operative procedures and forces them to refer the patients although referral system is not well organized in rural Bangladesh. Insufficient bed capacity, inadequate training, shortage of emergency medicines etc. are other hindrance factors for facility readiness. Among the 387 observed delivery case, 17 (4.4%) were identified as PPH cases, and only 2 cases were found as eclampsia/pre-eclampsia. The majority of the patients were treated with uterine message (16 out of 17, 94.1%) and injectable Oxytocin (14 out of 17, 82.4%). The providers of DH mentioned that they can manage the PPH because of having provision for diagnostic and blood transfusion services, although not as 24/7 services. Regarding management of eclampsia/pre-eclampsia, HCPs provided Diazepam, MgSO4, and other anti-hypertensives. The UHCs did not have MgSO4 at stock even, and one facility manager admitted that they treat eclampsia with Diazepam only. The nurses of the UHCs were found to be afraid to handle eclampsia cases. The upcoming interventions must ensure refresher training of service providers, continuous availability of essential medicine and equipment needed for complication management, availability of skilled health workforce, availability of functioning blood transfusion unit and pairing of consultants and anaesthetists to reach the newly set targets altogether.

Keywords: Bangladesh, health facilities, maternal complications, quality of care

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Authors: Ahmad Odeh

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Researchers are currently more concerned about the calculations of energy at the operational stage, mainly due to its larger environmental impact, but the fact remains, embodied energies represent a substantial contributor unaccounted for in the overall energy computation method. The calculation of materials’ embodied energy during the construction stage is complicated. This is due to the various factors involved. The equipment used, fuel needed, and electricity required for each type of materials varies with location and thus the embodied energy will differ for each project. Moreover, the method used in manufacturing, transporting and putting in place will have significant influence on the materials’ embodied energy. This anomaly has made it difficult to calculate or even bench mark the usage of such energies. This paper presents a model aimed at calculating embodied energies based on such variabilities. It presents a systematic approach that uses an efficient method of calculation to provide a new insight for the selection of construction materials. The model is developed in a BIM environment. The quantification of materials’ energy is determined over the three main stages of their lifecycle: manufacturing, transporting and placing. The model uses three major databases each of which contains set of the construction materials that are most commonly used in building projects. The first dataset holds information about the energy required to manufacture any type of materials, the second includes information about the energy required for transporting the materials while the third stores information about the energy required by machinery to place the materials in their intended locations. Through geospatial data analysis, the model automatically calculates the distances between the suppliers and construction sites and then uses dataset information for energy computations. The computational sum of all the energies is automatically calculated and then the model provides designers with a list of usable equipment along with the associated embodied energies.

Keywords: BIM, lifecycle energy assessment, building automation, energy conservation

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Authors: Rolando B. Llave Jr.

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In many countries, wheat flour is used an essential component in production/preparation of bread and other baked products considered to have a significant role in man’s diet. Partial replacement of wheat flour with other flours (composite flour) in preparation of the said products is seen as a solution to the scarcity of wheat flour (in non-wheat producing countries), and improved nourishment. In composite flour, other flours may come from cereals, legumes, root crops, and those that are rich in starch. Many countries utilize whatever is locally available. “Adlai” or Job’s tears is a tall cereal plant that belongs to the same family of grass as wheat, rice, and corn. In some countries, it is used as an ingredient in producing many dishes and alcoholic and non-alcoholic beverages. As part of the Food Staple Self-Sufficiency Program (FSSP) of the Department of Agriculture (DA) in the Philippines, “adlai” is being promoted as alternative food source for the Filipinos. In this study, the grits coming from the seeds of “adlai” were turned into flour. The resulting flour was then used as partial replacement for wheat flour in selected baked products namely “pan de sal” (salt bread), cupcakes and cookies. The supplementation of “adlai” flour ranged 20%-45% with 20%-35% for “pan de sal”; 30%-45% for cupcakes; and 25% - 40% for cookies. The study was composed of four (4) phases. Phase I was product formulation studies. Phase II included the acceptability test/sensory evaluation of the baked products where the statistical analysis of the data gathered followed. Phase III was the computation of the theoretical protein content of the most acceptable “pan de sal”, cupcake and cookie, and lastly, in Phase IV, cost benefit was analyzed, specifically in terms of the direct material cost.

Keywords: “adlai”, composite flour, supplementation, sensory evaluation

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Authors: Sonu Khanal, Mandira Shrestha

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Snow and Glaciers are the largest dependable reserved sources of water for the river system originating from the Himalayas so an accurate estimate of the volume of water contained in the snowpack and the rate of release of water from snow and glaciers are, therefore, needed for efficient management of the water resources. This research assess the fusion of energy exchanges between the snowpack, air above and soil below according to mass and energy balance which makes it apposite than the models using simple temperature index for the snow and glacier melt computation. UEBGrid a Distributed energy based model is used to calculate the melt which is then routed by Geo-SFM. The model robustness is maintained by incorporating the albedo generated from the Landsat-7 ETM images on a seasonal basis for the year 2002-2003 and substrate map derived from TM. The Substrate file includes predominantly the 4 major thematic layers viz Snow, clean ice, Glaciers and Barren land. This approach makes use of CPC RFE-2 and MERRA gridded data sets as the source of precipitation and climatic variables. The subsequent model run for the year between 2002-2008 shows a total annual melt of 17.15 meter is generate from the Marshyangdi Basin of which 71% is contributed by the glaciers , 18% by the rain and rest being from the snow melt. The albedo file is decisive in governing the melt dynamics as 30% increase in the generated surface albedo results in the 10% decrease in the simulated discharge. The melt routed with the land cover and soil variables using Geo-SFM shows Nash-Sutcliffe Efficiency of 0.60 with observed discharge for the study period.

Keywords: Glacier, Glacier melt, Snowmelt, Energy balance

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Authors: Iveta Bryjova

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Recording of viscoelastic strain-vs-time curves with the aid of the suction method and a follow-up analysis, resulting into evaluation of standard viscoelastic parameters, is a significant technique for non-invasive contact diagnostics of mechanical properties of skin and assessment of its conditions, particularly in acute burns, hypertrophic scarring (the most common complication of burn trauma) and reconstructive surgery. For elimination of the skin thickness contribution, usable viscoelastic parameters deduced from the strain-vs-time curves are restricted to the relative ones (i.e. those expressed as a ratio of two dimensional parameters), like grosselasticity, net-elasticity, biological elasticity or Qu’s area parameters, in literature and practice conventionally referred to as R2, R5, R6, R7, Q1, Q2, and Q3. With the exception of parameters R2 and Q1, the remaining ones substantially depend on the position of inflection point separating the elastic linear and viscoelastic segments of the strain-vs-time curve. The standard algorithm implemented in commercially available devices relies heavily on the experimental fact that the inflection time comes about 0.1 sec after the suction switch-on/off, which depreciates credibility of parameters thus obtained. Although the Qu’s US 7,556,605 patent suggests a method of improving the precision of the inflection determination, there is still room for nonnegligible improving. In this contribution, a novel method of inflection point determination utilizing the advantageous properties of the Savitzky–Golay filtering is presented. The method allows computation of derivatives of smoothed strain-vs-time curve, more exact location of inflection and consequently more reliable values of aforementioned viscoelastic parameters. An improved applicability of the five inflection-dependent relative viscoelastic parameters is demonstrated by recasting a former study under the new method, and by comparing its results with those provided by the methods that have been used so far.

Keywords: Savitzky–Golay filter, scarring, skin, viscoelasticity

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Authors: Yuxi Zhu, Zhenqian Chen

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It is of great interest to investigate the thermal properties of non-precious metal catalysts for Proton exchange membrane fuel cell (PEMFC) based on the thermal management requirements. Due to the low symmetry of materials, to accurately obtain the thermal conductivity of materials, it is necessary to obtain the second and third order force constants by combining density functional theory and machine learning interatomic potential. To be specific, the interatomic force constants are obtained by moment tensor potential (MTP), which is trained by the computational trajectory of Ab initio molecular dynamics (AIMD) at 50, 300, 600, and 900 K for 1 ps each, with a time step of 1 fs in the AIMD computation. And then the thermal conductivity can be obtained by solving the Boltzmann transport equation. In this paper, the thermal transport properties of single metal atom catalysts are studied for the first time to our best knowledge by machine-learning interatomic potential (MLIP). Results show that the single metal atom catalysts exhibit anisotropic thermal conductivities and partially exhibit good thermal conductivity. The average lattice thermal conductivities of G-FeN₄, G-CoN₄ and G-NiN₄ at 300 K are 88.61 W/mK, 205.32 W/mK and 210.57 W/mK, respectively. While other single metal atom catalysts show low thermal conductivity due to their low phonon lifetime. The results also show that low-frequency phonons (0-10 THz) dominate thermal transport properties. The results provide theoretical insights into the application of single metal atom catalysts in thermal management.

Keywords: proton exchange membrane fuel cell, single metal atom catalysts, density functional theory, thermal conductivity, machine-learning interatomic potential

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Authors: Bijay Kumar Sahoo

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An important feature of InₓGa₁-ₓN/GaN heterostructures is strong built-in polarization (BIP) electric field at the hetero-interface due to spontaneous (sp) and piezoelectric (pz) polarizations. The intensity of this electric field reaches several MV/cm. This field has profound impact on optical, electrical and thermal properties. In this work, the effect of BIP field on thermal conductivity of InₓGa₁-ₓN/GaN heterostructure has been investigated theoretically. The interaction between the elastic strain and built in electric field induces additional electric polarization. This additional polarization contributes to the elastic constant of InₓGa₁-ₓN alloy. This in turn modifies material parameters of InₓGa₁-ₓN. The BIP mechanism enhances elastic constant, phonon velocity and Debye temperature and their bowing constants in InₓGa₁-ₓN alloy. These enhanced thermal parameters increase phonon mean free path which boost thermal conduction process. The thermal conductivity (k) of InxGa1-xN alloy has been estimated for x=0, 0.1, 0.3 and 0.9. Computation finds that irrespective of In content, the room temperature k of InₓGa₁-ₓN/GaN heterostructure is enhanced by BIP mechanism. Our analysis shows that at a certain temperature both k with and without BIP show crossover. Below this temperature k with BIP field is lower than k without BIP; however, above this temperature k with BIP field is significantly contributed by BIP mechanism leading to k with BIP field become higher than k without BIP field. The crossover temperature is primary pyroelectric transition temperature. The pyroelectric transition temperature of InₓGa₁-ₓN alloy has been predicted for different x. This signature of pyroelectric nature suggests that thermal conductivity can reveal pyroelectricity in InₓGa₁-ₓN alloy. The composition dependent room temperature k for x=0.1 and 0.3 are in line with prior experimental studies. The result can be used to minimize the self-heating effect in InₓGa₁-ₓN/GaN heterostructures.

Keywords: built-in polarization, phonon relaxation time, thermal properties of InₓGa₁-ₓN /GaN heterostructure, self-heating

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Authors: Adandé Belarmain Fandohan

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Climate change has become a major concern globally, particularly in rural communities that have to find rapid coping solutions. Several vulnerability assessment approaches have been developed in the last decades. This comes along with a higher risk for different methods to result in different conclusions, thereby making comparisons difficult and decision-making non-consistent across areas. The effect of methods and computational approaches on estimates of people’s vulnerability was assessed using data collected from the Gambia. Twenty-four indicators reflecting vulnerability components: (exposure, sensitivity, and adaptive capacity) were selected for this purpose. Data were collected through household surveys and key informant interviews. One hundred and fifteen respondents were surveyed across six communities and two administrative districts. Results were compared over three computational approaches: the maximum value transformation normalization, the z-score transformation normalization, and simple averaging. Regardless of the approaches used, communities that have high exposure to climate change and extreme events were the most vulnerable. Furthermore, the vulnerability was strongly related to the socio-economic characteristics of farmers. The survey evidenced variability in vulnerability among communities and administrative districts. Comparing output across approaches, overall, people in the study area were found to be highly vulnerable using the simple average and maximum value transformation, whereas they were only moderately vulnerable using the z-score transformation approach. It is suggested that assessment approach-induced discrepancies be accounted for in international debates to harmonize/standardize assessment approaches to the end of making outputs comparable across regions. This will also likely increase the relevance of decision-making for adaptation policies.

Keywords: maximum value transformation, simple averaging, vulnerability assessment, West Africa, z-score transformation

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Authors: Abbas Al-Refaie, Ruba Najdawi, Nour Bata, Mohammad D. AL-Tahat

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The pharmaceutical industry is an important component of health care systems throughout the world. Measurement of a production unit-performance is crucial in determining whether it has achieved its objectives or not. This paper applies data envelopment (DEA) window analysis to assess the efficiencies of two packaging lines; Allfill (new) and DP6, in the Penicillin plant in a Jordanian Medical Company in 2010. The CCR and BCC models are used to estimate the technical efficiency, pure technical efficiency, and scale efficiency. Further, the Malmquist productivity index is computed to measure then employed to assess productivity growth relative to a reference technology. Two primary issues are addressed in computation of Malmquist indices of productivity growth. The first issue is the measurement of productivity change over the period, while the second is to decompose changes in productivity into what are generally referred to as a ‘catching-up’ effect (efficiency change) and a ‘frontier shift’ effect (technological change). Results showed that DP6 line outperforms the Allfill in technical and pure technical efficiency. However, the Allfill line outperforms DP6 line in scale efficiency. The obtained efficiency values can guide production managers in taking effective decisions related to operation, management, and plant size. Moreover, both machines exhibit a clear fluctuations in technological change, which is the main reason for the positive total factor productivity change. That is, installing a new Allfill production line can be of great benefit to increasing productivity. In conclusions, the DEA window analysis combined with the Malmquist index are supportive measures in assessing efficiency and productivity in pharmaceutical industry.

Keywords: window analysis, malmquist index, efficiency, productivity

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Authors: Siddhi Khaire, Samarth Hawaldar, Baladitya Suri

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As efforts towards quantum communication advance, the need for single photon sources becomes imminent. Due to the extremely low energy of a single microwave photon, efforts to build single photon sources and detectors in the microwave range are relatively recent. We plan to use a Cooper Pair Box (CPB) that has a ‘sweet-spot’ where the two energy levels have minimal separation. Moreover, these qubits have fairly large anharmonicity making them close to ideal two-level systems. If the external gate voltage of these qubits is varied rapidly while passing through the sweet-spot, due to Landau-Zener effect, the qubit can be excited almost deterministically. The rapid change of the gate control voltage through the sweet spot induces a non-adiabatic population transfer from the ground to the excited state. The qubit eventually decays into the emission line emitting a single photon. The advantage of this setup is that the qubit can be excited without any coherent microwave excitation, thereby effectively increasing the usable source efficiency due to the absence of control pulse microwave photons. Since the probability of a Landau-Zener transition can be made almost close to unity by the appropriate design of parameters, this source behaves as an on-demand source of single microwave photons. The large anharmonicity of the CPB also ensures that only one excited state is involved in the transition and multiple photon output is highly improbable. Such a system has so far not been implemented and would find many applications in the areas of quantum optics, quantum computation as well as quantum communication.

Keywords: quantum computing, quantum communication, quantum optics, superconducting qubits, flux qubit, charge qubit, microwave single photon source, quantum information processing

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Authors: Hadas Sopher, Davide Schaumann, Yehuda E. Kalay

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This paper addresses the shortcomings of architectural computation tools in representing human behavior in built environments, prior to construction and occupancy of those environments. Evaluating whether a design fits the needs of its future users is currently done solely post construction, or is based on the knowledge and intuition of the designer. This issue is of high importance when designing complex buildings such as hospitals, where the quality of treatment as well as patient and staff satisfaction are of major concern. Existing computational pre-occupancy human behavior evaluation methods are geared mainly to test ergonomic issues, such as wheelchair accessibility, emergency egress, etc. As such, they rely on Agent Based Modeling (ABM) techniques, which emphasize the individual user. Yet we know that most human activities are social, and involve a number of actors working together, which ABM methods cannot handle. Therefore, we present an event-based model that manages the interaction between multiple Actors, Spaces, and Activities, to describe dynamically how people use spaces. This approach requires expanding the computational representation of Actors beyond their physical description, to include psychological, social, cultural, and other parameters. The model presented in this paper includes cognitive abilities and rules that describe the response of actors to their physical and social surroundings, based on the actors’ internal status. The model has been applied in a simulation of hospital wards, and showed adaptability to a wide variety of situated behaviors and interactions.

Keywords: agent based modeling, architectural design evaluation, event modeling, human behavior simulation, spatial cognition

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Authors: F. Farzan Nasab, H. J. M. Geijselaers, I. Baran, A. De Boer

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A method is introduced for the coupled skin-rib optimization of a wing box where mass minimization is the objective and local buckling is the constraint. The structure is made of composite materials where continuity of plies in multiple adjacent panels (blending) has to be satisfied. Blending guarantees the manufacturability of the structure; however, it is a highly challenging constraint to treat and has been under debate in recent research in the same area. To fulfill design guidelines with respect to symmetry, balance, contiguity, disorientation and percentage rule of the layup, a reference for the stacking sequences (stacking sequence table or SST) is generated first. Then, an innovative fully gradient-based optimization approach in relation to a specific SST is introduced to obtain the optimum thickness distribution all over the structure while blending is fulfilled. The proposed optimization approach aims to turn the discrete optimization problem associated with the integer number of plies into a continuous one. As a result of a wing box deflection, a rib is subjected to load values which vary nonlinearly with the amount of deflection. The bending stiffness of a skin affects the wing box deflection and thus affects the load applied to a rib. This indicates the necessity of a coupled skin-rib optimization approach for a more realistic optimized design. The proposed method is examined with the optimization of the layup of a composite stiffened skin and rib of a wing torsion box subjected to in-plane normal and shear loads. Results show that the method can successfully prescribe a valid design with a significantly cheap computation cost.

Keywords: blending, buckling optimization, composite panels, wing torsion box

Procedia PDF Downloads 409

Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

Abstract:

Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

Procedia PDF Downloads 279

Authors: Shamsulhaq Amin

Abstract:

Drought can arise from several hydrometeorological phenomena that result in insufficient precipitation, soil moisture, and surface and groundwater flow, leading to conditions that are considerably drier than the usual water content or availability. Drought is often assessed using indices that are associated with meteorological, agricultural, and hydrological phenomena. In order to effectively handle drought disasters, it is essential to accurately determine the kind, intensity, and extent of the drought using drought characterization. This information is critical for managing the drought before, during, and after the rehabilitation process. Over a hundred drought assessments have been created in literature to evaluate drought disasters, encompassing a range of factors and variables. Some models utilise solely hydrometeorological drivers, while others employ remote sensing technology, and some incorporate a combination of both. Comprehending the entire notion of drought and taking into account drought indices along with their calculation processes are crucial for researchers in this discipline. Examining several drought metrics in different studies requires additional time and concentration. Hence, it is crucial to conduct a thorough examination of approaches used in drought indices in order to identify the most straightforward approach to avoid any discrepancies in numerous scientific studies. In case of practical application in real-world, categorizing indices relative to their usage in meteorological, agricultural, and hydrological phenomena might help researchers maximize their efficiency. Users have the ability to explore different indexes at the same time, allowing them to compare the convenience of use and evaluate the benefits and drawbacks of each. Moreover, certain indices exhibit interdependence, which enhances comprehension of their connections and assists in making informed decisions about their suitability in various scenarios. This study provides a comprehensive assessment of various drought indices, analysing their types and computation methodologies in a detailed and systematic manner.

Keywords: drought classification, drought severity, drought indices, agriculture, hydrological

Procedia PDF Downloads 41

Authors: Shashank Gupta, Iteash Agarwal, Vijayalaxmi Mogiligidda, Rajesh Kumar Krishnan, Sruthi Chennuri, Deepika Aggarwal, Anwesha Hoodati, Sheroy Cooper, Ranjan, Mohammad Bilal Sheik, Bhavya K. M., Manasa Hegde, M. Naveen Krishna, Amit Kumar Chauhan, Mallikarjun Korrapati, Sumit Singh, J. B. Singh, Sunil Sud, Sunil Gupta, Sidhartha Pant, Sankar, Neha Agrawal, Ashish Ranjan, Piyush Mohapatra, Roopak T., Arsh Ahmad, Nanjunda M., Dilip Singh

Abstract:

Major research interests on quantum key distribution (QKD) are primarily focussed on increasing 1. point-to-point transmission distance (1000 Km), 2. secure key rate (Mbps), 3. security of quantum layer (device-independence). It is great to push the boundaries on these fronts, but these isolated approaches are neither scalable nor cost-effective due to the requirements of specialised hardware and different infrastructure. Current and future QKD network requires addressing different sets of challenges apart from distance, key rate, and quantum security. In this regard, we present ChaQra -a sub-quantum network with core features as 1) Crypto agility (integration in the already deployed telecommunication fibres), 2) Software defined networking (SDN paradigm for routing different nodes), 3) reliability (addressing denial-of-service with hybrid quantum safe cryptography), 4) upgradability (modules upgradation based on scientific and technological advancements), 5) Beyond QKD (using QKD network for distributed computing, multi-party computation etc). Our results demonstrate a clear path to create and accelerate quantum secure Indian subcontinent under the national quantum mission.

Keywords: quantum network, quantum key distribution, quantum security, quantum information

Procedia PDF Downloads 56

Authors: Duvert A. Puentes T., Javier A. Maldonado E., Ivan Quintero., Diego F. Villegas

Abstract:

Mechanical Computation is a great tool to study the performance of complex models. An example of it is the study of the human body structure. This paper took advantage of different types of software to make a 3D model of the glenohumeral joint and apply a finite element analysis. The main objective was to study the change in the biomechanical properties of the joint when it presents an injury. Specifically, a BANKART lesion, which consists in the detachment of the anteroinferior labrum from the glenoid. Stress and strain distribution of the soft tissues were the focus of this study. First, a 3D model was made of a joint without any pathology, as a control sample, using segmentation software for the bones with the support of medical imagery and a cadaveric model to represent the soft tissue. The joint was built to simulate a compression and external rotation test using CAD to prepare the model in the adequate position. When the healthy model was finished, it was submitted to a finite element analysis and the results were validated with experimental model data. With the validated model, it was sensitized to obtain the best mesh measurement. Finally, the geometry of the 3D model was changed to imitate a BANKART lesion. Then, the contact zone of the glenoid with the labrum was slightly separated simulating a tissue detachment. With this new geometry, the finite element analysis was applied again, and the results were compared with the control sample created initially. With the data gathered, this study can be used to improve understanding of the labrum tears. Nevertheless, it is important to remember that the computational analysis are approximations and the initial data was taken from an in vitro assay.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, bankart lesion, labrum

Procedia PDF Downloads 161

Authors: Dhanuja S. Patil, Sanjay B. Waykar

Abstract:

Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

Procedia PDF Downloads 323

Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

Abstract:

This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

Procedia PDF Downloads 166

Authors: M. A. Askari, M. A. Nazari, P. Perrier, Y. Payan

Abstract:

Growth and remodeling of biological structures have gained lots of attention over the past decades. Determining the response of the living tissues to the mechanical loads is necessary for a wide range of developing fields such as, designing of prosthetics and optimized surgery operations. It is a well-known fact that biological structures are never stress-free, even when externally unloaded. The exact origin of these residual stresses is not clear, but theoretically growth and remodeling is one of the main sources. Extracting body organs from medical imaging, does not produce any information regarding the existing residual stresses in that organ. The simplest cause of such stresses is the gravity since an organ grows under its influence from its birth. Ignoring such residual stresses might cause erroneous results in numerical simulations. Accounting for residual stresses due to tissue growth can improve the accuracy of mechanical analysis results. In this paper, we have implemented a computational framework based on fixed-point iteration to determine the residual stresses due to growth. Using nonlinear continuum mechanics and the concept of fictitious configuration we find the unknown stress-free reference configuration which is necessary for mechanical analysis. To illustrate the method, we apply it to a finite element model of healthy human face whose geometry has been extracted from medical images. We have computed the distribution of residual stress in facial tissues, which can overcome the effect of gravity and cause that tissues remain firm. Tissue wrinkles caused by aging could be a consequence of decreasing residual stress and not counteracting the gravity. Considering these stresses has important application in maxillofacial surgery. It helps the surgeons to predict the changes after surgical operations and their consequences.

Keywords: growth, soft tissue, residual stress, finite element method

Procedia PDF Downloads 354

Authors: Kizito Ugochukwu Nwajeri

Abstract:

This paper explores the application of hybrid block methods for solving boundary value problems (BVPs), which are prevalent in various fields such as science, engineering, and applied mathematics. Traditionally, numerical approaches such as finite difference and shooting methods, often encounter challenges related to stability and convergence, particularly in the context of complex and nonlinear BVPs. To address these challenges, we propose a hybrid block method that integrates features from both single-step and multi-step techniques. This method allows for the simultaneous computation of multiple solution points while maintaining high accuracy. Specifically, we employ a combination of polynomial interpolation and collocation strategies to derive a system of equations that captures the behavior of the solution across the entire domain. By directly incorporating boundary conditions into the formulation, we enhance the stability and convergence properties of the numerical solution. Furthermore, we introduce an adaptive step-size mechanism to optimize performance based on the local behavior of the solution. This adjustment allows the method to respond effectively to variations in solution behavior, improving both accuracy and computational efficiency. Numerical tests on a variety of boundary value problems demonstrate the effectiveness of the hybrid block methods. These tests showcase significant improvements in accuracy and computational efficiency compared to conventional methods, indicating that our approach is robust and versatile. The results suggest that this hybrid block method is suitable for a wide range of applications in real-world problems, offering a promising alternative to existing numerical techniques.

Keywords: hybrid block methods, boundary value problem, polynomial interpolation, adaptive step-size control, collocation methods

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Authors: Rakesh Kumar Soni

Abstract:

Under free living conditions, human biological clocks show a periodicity of 24 hour for numerous physiological, behavioral and biochemical variables. However, this period is not the original period; rather it merely exhibits synchronization with the solar clock. It is, therefore, most important to investigate characteristics of human circadian clock, essentially in shift workers, who normally confront with contrasting social clocks. Aim of the present study was to investigate rest-activity rhythm and to vouch for the best technique for the computation of periods in this rhythm in subjects randomly selected from different groups of shift workers. The rest-activity rhythm was studied in forty-eight shift workers from three different organizations, namely Newspaper Printing Press (NPP), Chhattisgarh State Electricity Board (CSEB) and Raipur Alloys (RA). Shift workers of NPP (N = 20) were working on a permanent night shift schedule (NS; 20:00-04:00). However, in CSEB (N = 14) and RA (N = 14), shift workers were working in a 3-shift system comprising of rotations from night (NS; 22:00-06:00) to afternoon (AS; 14:00-22:00) and to morning shift (MS; 06:00-14:00). Each subject wore an Actiwatch (AW64, Mini Mitter Co. Inc., USA) for 7 and/or 21 consecutive days, only after furnishing a certificate of consent. One-minute epoch length was chosen for the collection of wrist activity data. Period was determined by using Actiware sleep software (Periodogram), Lomb-Scargle Periodogram (LSP) and Spectral analysis software (Spectre). Other statistical techniques, such as ANOVA and Duncan’s multiple-range test were also used whenever required. A statistically significant circadian rhythm in rest-activity, gauged by cosinor, was documented in all shift workers, irrespective of shift work. Results indicate that the efficiency of the technique to determine the period (τ) depended upon the clipping limits of the τs. It appears that the technique of spectre is more reliable.

Keywords: biological clock, rest activity rhythm, spectre, periodogram

Procedia PDF Downloads 163