Search results for: initial cost

Authors: A. A. Soliman

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The Modified Regularized Long Wave (MRLW) equation is solved numerically by giving a new algorithm based on collocation method using quartic B-splines at the mid-knot points as element shape. Also, we use the fourth Runge-Kutta method for solving the system of first order ordinary differential equations instead of finite difference method. Our test problems, including the migration and interaction of solitary waves, are used to validate the algorithm which is found to be accurate and efficient. The three invariants of the motion are evaluated to determine the conservation properties of the algorithm. The temporal evaluation of a Maxwellian initial pulse is then studied.

Keywords: collocation method, MRLW equation, Quartic B-splines, solitons

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Authors: Deepa Vasudevan, Thomas Northrup, Angela Stotts, Michelle Klawans

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To date, we have conducted three studies on this subject. The research done to date is through three studies. The initial study was to document that modified criteria independently identified higher numbers of overweight/obese South Asian Indians. The second study was to document physician knowledge of appropriate diagnosis of obesity among South Asian Indians. The final study was an intervention to evaluate the efficacy of a training module on improving physician diagnosis and counseling of overweight/obese Asian patients.

Keywords: South Asian Indians, obesity, physicians, BMI and waist circumference

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Authors: Xiao-Hua Zhu, Xin Yuan, Yi-Ran Zhao

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High-cadmium pollution in rice is a serious problem in many parts of China. Many kinds of remediation technologies have been tested and applied in many farmlands. Because of the productive function of the farmland, most technologies are inappropriate due to their destruction to the tillage soil layer. And the large labours and expensive fees of many technologies are also the restrictive factors for their applications. The conception of 'Root Micro-Geochemical Barrier' was proposed to reduce cadmium (Cd) bioavailability and the concentration of the cadmium in rice. Remediation and mitigation techniques were demonstrated on contaminated farmland in the downstream of some mine. According to the rule of rice growth, Cd would be absorbed by the crops in every growth stage, and the plant-absorb efficiency in the first stage of the tillering stage is almost the highest. We should create a method to protect the crops from heavy metal pollution, which could begin to work from the early growth stage. Many materials with repair property get our attention. The materials will create a barrier preventing Cd from being absorbed by the crops during all the growing process because the material has the ability to adsorb soil-Cd and making it losing its migration activity. And we should choose a good chance to put the materials into the crop-growing system cheaply as soon as early. Per plant, rice has a little root system scope, which makes the roots reach about 15cm deep and 15cm wide. So small root radiation area makes it possible for all the Cd approaching the roots to be adsorbed with a small amount of adsorbent. Mixing the remediation materials with the seed-raising soli and adding them to the tillage soil in the process of transplanting seedlings, we can control the soil-Cd activity in the range of roots to reduce the Cd-amount absorbed by the crops. Of course, the mineral materials must have enough adsorptive capacity and no additional pollution. More than 3000 square meters farmlands have been remediated. And on the application of root micro-geochemical barrier, the Cd-concentration in rice and the remediation-cost have been decreased by 90% and 80%, respectively, with little extra labour brought to the farmers. The Cd-concentrations in rice from remediated farmland have been controlled below 0.1 ppm. The remediation of one acre of contaminated cropland costs less than $100. The concept has its advantage in the remediation of paddy field contaminated by Cd, especially for the field with outside pollution sources.

Keywords: cadmium pollution, growth stage, cost, root micro-geochemistry barrier

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Authors: Kamran Baksh Soomro, Amin Talei, Sina Alaghmand

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Due to the declining freshwater availability to agriculture in many areas, the utilization of saline irrigation requires more consideration. For this purpose, the effects of saline irrigation on the economics of crop yield and soil salinity should be understood. A two-year field experiment was carried out during 2017-18 with three replications to investigate the effect of saline groundwater on the economics of bitter gourd production and soil salinity status after harvesting the crop. Two irrigation treatments, i.e., fresh quality irrigation water (IT₁ EC 0.56 dS.m⁻¹ (control) and other is saline groundwater ( IT₂ EC 2.56 dS.m⁻¹) were used under drip system of irrigation. Cost-benefit analysis is often used to assess adaptation approaches. In this study, it has been observed that the salts under IT₁ (fresh quality water) and IT₂ (saline groundwater) did not accumulate in the wetted zone. However, the salts were observed deposited at wetted periphery under both the treatments after the crop end at all the three sampling depths under drip system of irrigation. Moreover, the costs and benefits associated with different irrigation treatments for two consecutive seasons for bitter-gourd cultivation were also investigated, and it was found that the average gross returns per hectare in season 1 were USD 5008.22 and 4454.78 under irrigation treatment IT₁ and IT₂ respectively. Whereas in season 2 the average gross returns per hectare were 3713.47 and 3140.51 under IT₁ and IT₂ respectively.

Keywords: ground-water, soil salinity, drip irrigation, wetted zone, wetted periphery, cost benefit analysis

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Authors: Fatima Zahra Moussa, Yamina Belhadef, Souheyla Ferouani

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In this work, we present a new form of miniature circular patch antenna based on CSRR metamaterials with an extended bandwidth proposed for 5 GHz Wi-Fiapplications. A reflection coefficient of -35 dB and a radiation pattern of 7.47 dB are obtained when simulating the initial proposed antenna with the CST microwave studio simulation software. The notch insertion technique in the radiating element was used for matching the antenna to the desired frequency in the frequency band [5150-5875] MHz.An extension of the bandwidth from 332 MHz to 1423 MHz was done by the DGS (defected ground structure) technique to meet the user's requirement in the 5 GHz Wi-Fi frequency band.

Keywords: patch antenna, miniaturisation, CSRR, notches, wifi, DGS

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Authors: Shahriar Ghammamy, Maryam Gholipoor

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Metronidazole nano -powders with the average mean particle size around 90 nm were synthesized by high-energy milling using a planetary ball mill is provided. The Scattering factors, milling of time,the ball size and ball to powder ratio on the material properties powder by the Ray diffraction (XRD) study, scanning electron microscopy (SEM), IR. It has been observed that the density of nano-sized grinding balls as ball to powder ratio depends. Using the dispersion factor, the density Can be reduced below the initial particle size was achieved.

Keywords: metronidazole, ball-milling, nanoparticles, characterization, XRD diffraction

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Authors: Udeh Nneka Evelyn

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The shortcoming of traditional costing system in terms of validity, accuracy, consistency, and Relevance increased the need for modern management accounting system. Activity –Based Costing (ABC) can be used as a modern tool for planning, Control and decision making for management. Past studies on ABC system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing technique in service oriented business organizations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on ABC. Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry and government organization. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: identification the most profitable customers: more accurate product and service pricing: increase product profitability: Well organized process costs.

Keywords: business, costing, organizations, planning, techniques

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Authors: Elham Dehghan, A. Shirzadi Javid, Mohsen Tadayon

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Labor productivity is very important and gained special concerns among professionals in the construction industry, worldwide. Productivity improvements on labors achieve higher cost savings with minimal investment. Due to the fact that profit margins are small on construction projects, cost savings associated with productivity are crucial to become a successful contractor. This research program studies and highlights the factors affecting labor productivity in Iranian construction industry. A questionnaire was used to gather the relevant data from respondents who involve in managing various types of projects in wide areas in Iran. It involved ranking 57 predefined factors divided into 5 categories: Human/Labor; Financial; Management; Equipments/Materials and Environmental. Total 62 feedbacks were analyzed through the Relative Importance Index (RII) technique. The top ten factors affecting construction labor productivity in Iran are: 1) Professional capability of contractor project manager, 2) skills of contractor’s project management team, 3) professional capability of owner project manager, 4) professional capability of Consulting Project manager, 5) discipline working, 6) delay payments by the owner, 7) material shortages, 8) delays in delivery of materials, 9) turnover power of the owner, 10) poor site management. Recommendations have been made in the study to address these factors. The research has direct benefits to key stakeholders in Iranian construction industry.

Keywords: Iranian construction projects, labor, productivity, relative importance index

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Authors: S. A. Gayvoronsky, T. A. Ezangina

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The robust control system objects with interval-undermined parameters is considers in this paper. Initial information about the system is its characteristic polynomial with interval coefficients. On the basis of coefficient estimations of quality indices and criterion of the maximum stability degree, the methods of synthesis of a robust regulator parametric is developed. The example of the robust stabilization system synthesis of the rope tension is given in this article.

Keywords: interval polynomial, controller synthesis, analysis of quality factors, maximum degree of stability, robust degree of stability, robust oscillation, system accuracy

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

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This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

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Authors: N. Azouaou, H. Mokaddem, D. Senadjki, K. Kedjit, Z. Sadaoui

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Introduction: Water contamination caused by dye industries, including food, leather, textile, plastic, cosmetics, paper-making, printing and dye synthesis, has caused more and more attention, since most dyes are harmful to human being and environments. Untreated coffee grounds were used as a high-efficiency adsorbent for the removal of a cationic dye (methylene blue, MB) from aqueous solution. Characterization of the adsorbent was performed using several techniques such as SEM, surface area (BET), FTIR and pH zero charge. The effects of contact time, adsorbent dose, initial solution pH and initial concentration were systematically investigated. Results showed the adsorption kinetics followed the pseudo-second-order kinetic model. Langmuir isotherm model is in good agreement with the experimental data as compared to Freundlich and D–R models. The maximum adsorption capacity was found equal to 52.63mg/g. In addition, the possible adsorption mechanism was also proposed based on the experimental results. Experimental: The adsorption experiments were carried out in batch at room temperature. A given mass of adsorbent was added to methylene blue (MB) solution and the entirety was agitated during a certain time. The samples were carried out at quite time intervals. The concentrations of MB left in supernatant solutions after different time intervals were determined using a UV–vis spectrophotometer. The amount of MB adsorbed per unit mass of coffee grounds (qt) and the dye removal efficiency (R %) were evaluated. Results and Discussion: Some chemical and physical characteristics of coffee grounds are presented and the morphological analysis of the adsorbent was also studied. Conclusions: The good capacity of untreated coffee grounds to remove MB from aqueous solution was demonstrated in this study, highlighting its potential for effluent treatment processes. The kinetic experiments show that the adsorption is rapid and maximum adsorption capacities qmax= 52.63mg/g achieved in 30min. The adsorption process is a function of the adsorbent concentration, pH and metal ion concentration. The optimal parameters found are adsorbent dose m=5g, pH=5 and ambient temperature. FTIR spectra showed that the principal functional sites taking part in the sorption process included carboxyl and hydroxyl groups.

Keywords: adsorption, methylene blue, coffee grounds, kinetic study

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Authors: Karoline Reis de Sena

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Endocrine disruptors are unregulated or not fully regulated compounds, even in the most developed countries, and which can be a danger to the environment and human health. They pass untreated through the secondary stage of conventional wastewater treatment plants, then the effluent from the wastewater treatment plants is discharged into the rivers, upstream and downstream from the drinking water treatment plants that use the same river water as the tributary. Long-term consumption of drinking water containing low concentrations of these compounds can cause health problems; these are persistent in nature and difficult to remove. In this way, research on emerging pollutants is expanding and is fueled by progress in finding the appropriate method for treating wastewater. Adsorption is the most common separation process, it is a simple and low-cost operation, but it is not eco-efficient. Concomitant to this, biosorption arises, which is a subcategory of adsorption where the biosorbent is biomass and which presents numerous advantages when compared to conventional treatment methods, such as low cost, high efficiency, minimization of the use of chemicals, absence of need for additional nutrients, biosorbent regeneration capacity and the biomass used in the production of biosorbents are found in abundance in nature. Thus, the use of alternative materials, such as sewage sludge, for the synthesis of adsorbents has proved to be an economically viable alternative, together with the importance of valuing the generated by-product flows, as well as managing the problem of their correct disposal. In this work, an alternative for the management of sewage sludge is proposed, transforming it into activated carbon and using it in the adsorption process of 17a-ethinylestradiol.

Keywords: 17α-ethinylestradiol, adsorption, activated carbon, sewage sludge, micropollutants

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Authors: Syed Muhammad Awais Tahir, Syed Hossein Raza Hamdani

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In the last two years, there has been a substantial increase in the rate of satellite launches. To keep up with the technology, it is imperative that the launch cost must be made affordable, especially in developing and underdeveloped countries. Launch cost is directly affected by the launch vehicle’s aerodynamic performance. Pegasus-XL SLV (Satellite Launch Vehicle) has been serving as a commercial SLV for the last 26 years, commencing its commercial flight operation from the six operational sites all around the US and Europe, and the Marshal Islands. Aerodynamic heating and drag contribute largely to Pegasus’s flight performance. The objective of this study is to reduce the aerodynamic heating and drag on Pegasus’s body significantly for supersonic and hypersonic flight regimes. Aerodynamic data for Pegasus’s first flight has been validated through CFD (Computational Fluid Dynamics), and then drag and aerodynamic heating is reduced by using a combination of a forward-facing cylindrical spike and a conical aero-disk at the actual operational flight conditions. CFD analysis using ANSYS fluent will be carried out for Mach no. ranges from 0.83 to 7.8, and AoA (Angle of Attack) ranges from -4 to +24 degrees for both simple and spiked-configuration, and then the comparison will be drawn using a variety of graphs and contours. Expected drag reduction for supersonic flight is to be around 15% to 25%, and for hypersonic flight is to be around 30% to 50%, especially for AoA < 15⁰. A 5% to 10% reduction in aerodynamic heating is expected to be achieved for hypersonic regions. In conclusion, the aerodynamic performance of air-launched Pegasus-XL SLV can be further enhanced, leading to its optimal fuel usage to achieve a more economical orbital flight.

Keywords: aerodynamics, pegasus-XL, drag reduction, aerodynamic heating, satellite launch vehicle, SLV, spike, aero-disk

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Authors: Todor N. Penchev, Dimitar N. Karastoianov, Stanislav D. Gyoshev

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For compacting of iron powder are used hydraulic presses and high velocity hammers. In this paper are presented initial research on application of an innovative powder compacting method, which uses a hammer working with controlled impact. The results show that by this method achieves the reduction of rebounds and improve efficiency of impact, compared with a high-speed compacting. Depending on the power of the engine (industrial rocket engine), this effect may be amplified to such an extent as to obtain a impact without rebound (sticking impact) and in long-time action of the impact force.

Keywords: powder metallurgy, impact, iron powder compacting, rocket engine

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Authors: Jaeun Park, Daekyoung Kim, Ho Kyoon Chung, Heeyeop Chae

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Quantum dots light-emitting diodes (QD-LEDs) have been considered as the next generation display and lighting devices due to their excellent color purity, photo-stability solution process possibility and good device stability. Currently typical quantum dot light emitting diodes contain organic layers such as PEDOT:PSS and PVK for charge transport layers. To make quantum dot light emitting diodes (QD-LED) more stable, it is required to replace those acidic and relatively unstable organic charge transport layers with inorganic materials. Therefore all inorganic and solution processed quantum dot light emitting diodes can potentially be a solution to stable and cost-effective display devices. We studied solution processed NiO films to replace organic charge transport layers that are required for stable all-inorganic based light emitting diodes. The transition metal oxides can be made by various vacuum and solution processes, but the solution processes are considered more cost-effective than vacuum processes. In this work we investigated solution processed NiOx for a hole transport layer (HTL). NiOx, has valence band energy levels of 5.3eV and they are easy to make sol-gel solutions. Water vapor oxidation process was developed and applied to solution processed all-inorganic QD-LED. Turn-on voltage, luminance and current efficiency of QD in this work were 5V, 1800Cd/m2 and 0.5Cd/A, respectively.

Keywords: QD-LED, metal oxide solution, NiO, all-inorganic QD-LED device

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Authors: B. Tiseo, V. Quaranta, G. Bruno, G. Sisinni

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There is an increasing demand of nano-satellite development among universities, small companies, and emerging countries. Low-cost and fast-delivery are the main advantages of such class of satellites achieved by the extensive use of commercial-off-the-shelf components. On the other side, the loss of reliability and the poor success rate are limiting the use of nano-satellite to educational and technology demonstration and not to the commercial purpose. Standardization of nano-satellite environmental testing by tailoring the existing test standard for medium/large satellites is then a crucial step for their market growth. Thus, it is fundamental to find the right trade-off between the improvement of reliability and the need to keep their low-cost/fast-delivery advantages. This is particularly even more essential for satellites of CubeSat family. Such miniaturized and standardized satellites have 10 cm cubic form and mass no more than 1.33 kilograms per 1 unit (1U). For this class of nano-satellites, the qualification process is mandatory to reduce the risk of failure during a space mission. This paper reports the description and results of the space qualification test campaign performed on Endurosat’s CubeSat nano-satellite and modules. Mechanical and environmental tests have been carried out step by step: from the testing of the single subsystem up to the assembled CubeSat nano-satellite. Functional tests have been performed during all the test campaign to verify the functionalities of the systems. The test duration and levels have been selected by tailoring the European Space Agency standard ECSS-E-ST-10-03C and GEVS: GSFC-STD-7000A.

Keywords: CubeSat, nano-satellite, shock, testing, vibration

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Authors: Riyadh Jamegh, Alla Eldin Kassam, Sawsan Sabih

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In order to overcome uncertainty conditions and inability to meet customers' requests due to these conditions, organizations tend to reserve a certain safety stock level (SSL). This level must be chosen carefully in order to avoid the increase in holding cost due to excess in SSL or shortage cost due to too low SSL. This paper used soft computing fuzzy logic to identify optimal SSL; this fuzzy model uses the dynamic concept to cope with high complexity environment status. The proposed model can deal with three input variables, i.e., demand stability level, raw material availability level, and on hand inventory level by using dynamic fuzzy logic to obtain the best SSL as an output. In this model, demand stability, raw material, and on hand inventory levels are described linguistically and then treated by inference rules of the fuzzy model to extract the best level of safety stock. The aim of this research is to provide dynamic approach which is used to identify safety stock level, and it can be implanted in different industries. Numerical case study in the dairy industry with Yogurt 200 gm cup product is explained to approve the validity of the proposed model. The obtained results are compared with the current level of safety stock which is calculated by using the traditional approach. The importance of the proposed model has been demonstrated by the significant reduction in safety stock level.

Keywords: inventory optimization, soft computing, safety stock optimization, dairy industries inventory optimization

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Authors: Margarita Dufresne

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This study devoted to development TPS for small space re-usable launchers. We have used SIRIUS design for S1 prototype. Multiphysics coupling for hypersonic reactive flow and thermos-structural analysis with and without ablation is provided by -CCM+ and COMSOL Multiphysics and FASTRAN and ACE+. Flow around hypersonic flight vehicles is the interaction of multiple shocks and the interaction of shocks with boundary layers. These interactions can have a very strong impact on the aeroheating experienced by the flight vehicle. A real gas implies the existence of a gas in equilibrium, non-equilibrium. Mach number ranged from 5 to 10 for first stage flight.The goals of this effort are to provide validation of the iterative coupling of hypersonic physics models in STAR-CCM+ and FASTRAN with COMSOL Multiphysics and ACE+. COMSOL Multiphysics and ACE+ are used for thermal structure analysis to simulate Conjugate Heat Transfer, with Conduction, Free Convection and Radiation to simulate Heat Flux from hypersonic flow. The reactive simulations involve an air chemical model of five species: N, N2, NO, O and O2. Seventeen chemical reactions, involving dissociation and recombination probabilities calculation include in the Dunn/Kang mechanism. Forward reaction rate coefficients based on a modified Arrhenius equation are computed for each reaction. The algorithms employed to solve the reactive equations used the second-order numerical scheme is obtained by a “MUSCL” (Monotone Upstream-cantered Schemes for Conservation Laws) extrapolation process in the structured case. Coupled inviscid flux: AUSM+ flux-vector splitting The MUSCL third-order scheme in STAR-CCM+ provides third-order spatial accuracy, except in the vicinity of strong shocks, where, due to limiting, the spatial accuracy is reduced to second-order and provides improved (i.e., reduced) dissipation compared to the second-order discretization scheme. initial unstructured mesh is refined made using this initial pressure gradient technique for the shock/shock interaction test case. The suggested by NASA turbulence models are the K-Omega SST with a1 = 0.355 and QCR (quadratic) as the constitutive option. Specified k and omega explicitly in initial conditions and in regions – k = 1E-6 *Uinf^2 and omega = 5*Uinf/ (mean aerodynamic chord or characteristic length). We put into practice modelling tips for hypersonic flow as automatic coupled solver, adaptative mesh refinement to capture and refine shock front, using advancing Layer Mesher and larger prism layer thickness to capture shock front on blunt surfaces. The temperature range from 300K to 30 000 K and pressure between 1e-4 and 100 atm. FASTRAN and ACE+ are coupled to provide high-fidelity solution for hot hypersonic reactive flow and Conjugate Heat Transfer. The results of both approaches meet the CIRCA wind tunnel results.

Keywords: hypersonic, first stage, high speed compressible flow, shock wave, aerodynamic heating, conugate heat transfer, conduction, free convection, radiation, fastran, ace+, comsol multiphysics, star-ccm+, thermal protection system (tps), space launcher, wind tunnel

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

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Authors: Sheng-Yu Lee

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Aim: Opioid use disorder is often characterized by repetitive drug-seeking and drug-taking behaviors with severe public health consequences. Animal model showed that opioid-induced perturbations in the gut microbiota causally relate to neuroinflammation, deficits in reward responding, and opioid tolerance, possibly due to changes in gut microbiota. Therefore, we propose that the dysbiosis of gut microbiota can be associated with pathogenesis of opioid dependence. In this current study, we explored the differences in gut microbiota between patients and normal controls and in patients before and after initiation of methadone treatment program for 12 weeks. Methods: Patients with opioid use disorder between 20 and 65 years were recruited from the methadone maintenance outpatient clinic in 2 medical centers in the Southern Taiwan. Healthy controls without any family history of major psychiatric disorders (schizophrenia, bipolar disorder and major depressive disorder) were recruited from the community. After initial screening, 15 patients with opioid use disorder joined the study for initial evaluation (Week 0), 12 of them completed the 12-week follow-up while receiving methadone treatment and ceased heroin use (Week 12). Fecal samples were collected from the patients at baseline and the end of 12th week. A one-time fecal sample was collected from the healthy controls. The microbiota of fecal samples were investigated using 16S rRNA V3V4 amplicon sequencing, followed by bioinformatics and statistical analyses. Results: We found no significant differences in species diversity in opioid dependent patients between Week 0 and Week 12, nor compared between patients at both points and controls. For beta diversity, using principal component analysis, we found no significant differences between patients at Week 0 and Week 12, however, both patient groups showed significant differences compared to control (P=0.011). Furthermore, the linear discriminant analysis effect size (LEfSe) analysis was used to identify differentially enriched bacteria between opioid use patients and healthy controls. Compared to controls, the relative abundance of Lactobacillaceae Lactobacillus (L. Lactobacillus), Megasphaera Megasphaerahexanoica (M. Megasphaerahexanoica) and Caecibacter Caecibactermassiliensis (C Caecibactermassiliensis) were increased in patients at Week 0, while Coriobacteriales Atopobiaceae (C. Atopobiaceae), Acidaminococcus Acidaminococcusintestini (A. Acidaminococcusintestini) and Tractidigestivibacter Tractidigestivibacterscatoligenes (T. Tractidigestivibacterscatoligenes) were increased in patients at Week 12. Conclusion: In conclusion, we suggest that the gut microbiome community maybe linked to opioid use disorder, such differences may not be altered even after 12-week of cessation of opioid use.

Keywords: opioid use disorder, gut microbiota, methadone treatment, follow up study

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Authors: Cecile Meier, Drago Diaz Aleman, Itahisa Perez Conesa, Jose Luis Saorin Perez, Jorge De La Torre Cantero

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In this work, two ways of creating small-sized metal sculptures are proposed: the first by means of microcasting and the second by electroforming from models printed in 3D using an FDM (Fused Deposition Modeling‎) printer or using a DLP (Digital Light Processing) printer. It is viable to replace the wax in the processes of the artistic foundry with 3D printed objects. In this technique, the digital models are manufactured with resin using a low-cost 3D FDM printer in polylactic acid (PLA). This material is used, because its properties make it a viable substitute to wax, within the processes of artistic casting with the technique of lost wax through Ceramic Shell casting. This technique consists of covering a sculpture of wax or in this case PLA with several layers of thermoresistant material. This material is heated to melt the PLA, obtaining an empty mold that is later filled with the molten metal. It is verified that the PLA models reduce the cost and time compared with the hand modeling of the wax. In addition, one can manufacture parts with 3D printing that are not possible to create with manual techniques. However, the sculptures created with this technique have a size limit. The problem is that when printed pieces with PLA are very small, they lose detail, and the laminar texture hides the shape of the piece. DLP type printer allows obtaining more detailed and smaller pieces than the FDM. Such small models are quite difficult and complex to melt using the lost wax technique of Ceramic Shell casting. But, as an alternative, there are microcasting and electroforming, which are specialized in creating small metal pieces such as jewelry ones. The microcasting is a variant of the lost wax that consists of introducing the model in a cylinder in which the refractory material is also poured. The molds are heated in an oven to melt the model and cook them. Finally, the metal is poured into the still hot cylinders that rotate in a machine at high speed to properly distribute all the metal. Because microcasting requires expensive material and machinery to melt a piece of metal, electroforming is an alternative for this process. The electroforming uses models in different materials; for this study, micro-sculptures printed in 3D are used. These are subjected to an electroforming bath that covers the pieces with a very thin layer of metal. This work will investigate the recommended size to use 3D printers, both with PLA and resin and first tests are being done to validate use the electroforming process of microsculptures, which are printed in resin using a DLP printer.

Keywords: sculptures, DLP 3D printer, microcasting, electroforming, fused deposition modeling

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

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Authors: T. Lydon, A. McNabola, P. Coughlan

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Energy consumption in the water distribution network (WDN) is a well established problem equating to the industry contributing heavily to carbon emissions, with 0.9 kg CO2 emitted per m3 of water supplied. It is indicated that 85% of energy wasted in the WDN can be recovered by installing turbines. Existing potential in networks is present at small capacity sites (5-10 kW), numerous and dispersed across networks. However, traditional turbine technology cannot be scaled down to this size in an economically viable fashion, thus alternative approaches are needed. This research aims to enable energy recovery potential within the WDN by exploring the potential of pumps-as-turbines (PATs), to realise this potential. PATs are estimated to be ten times cheaper than traditional micro-hydro turbines, presenting potential to contribute to an economically viable solution. However, a number of technical constraints currently prohibit their widespread use, including the inability of a PAT to control pressure, difficulty in the selection of PATs due to lack of performance data and a lack of understanding on how PATs can cater for fluctuations as extreme as +/- 50% of the average daily flow, characteristic of the WDN. A PAT prototype is undergoing testing in order to identify the capabilities of the technology. Results of preliminary testing, which involved testing the efficiency and power potential of the PAT for varying flow and pressure conditions, in order to develop characteristic and efficiency curves for the PAT and a baseline understanding of the technologies capabilities, are presented here: •The limitations of existing selection methods which convert BEP from pump operation to BEP in turbine operation was highlighted by the failure of such methods to reflect the conditions of maximum efficiency of the PAT. A generalised selection method for the WDN may need to be informed by an understanding of impact of flow variations and pressure control on system power potential capital cost, maintenance costs, payback period. •A clear relationship between flow and efficiency rate of the PAT has been established. The rate of efficiency reductions for flows +/- 50% BEP is significant and more extreme for deviations in flow above the BEP than below, but not dissimilar to the reaction of efficiency of other turbines. •PAT alone is not sufficient to regulate pressure, yet the relationship of pressure across the PAT is foundational in exploring ways which PAT energy recovery systems can maintain required pressure level within the WDN. Efficiencies of systems of PAT energy recovery systems operating conditions of pressure regulation, which have been conceptualise in current literature, need to be established. Initial results guide the focus of forthcoming testing and exploration of PAT technology towards how PATs can form part of an efficiency energy recovery system.

Keywords: energy recovery, pump-as-turbine, water distribution network, water distribution network

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: D. G. Badagha, C. D. Modhera, S. A. Vasanwala

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There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Keywords: artificial neural network, high performance concrete, rebound hammer, strength prediction

Procedia PDF Downloads 151

Authors: Mohammad Nehal Hasnine, Md Kamrul Hasan Chayon, Md Mobasswer Rahman

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Organizational tendencies towards computer-based information processing have been observed noticeably in the third-world countries. Many enterprises are taking major initiatives towards computerized working environment because of massive benefits of computer-based information processing. However, designing and developing information resource management software for small and mid-size enterprises under budget costs and strict deadline is always challenging for software engineers. Therefore, we introduced an approach to design mid-size enterprise software by using the Waterfall model, which is one of the SDLC (Software Development Life Cycles), in a cost effective way. To fulfill research objectives, in this study, we developed mid-sized enterprise software named “BSK Management System” that assists enterprise software clients with information resource management and perform complex organizational tasks. Waterfall model phases have been applied to ensure that all functions, user requirements, strategic goals, and objectives are met. In addition, Rich Picture, Structured English, and Data Dictionary have been implemented and investigated properly in engineering manner. Furthermore, an assessment survey with 20 participants has been conducted to investigate the usability and performance of the proposed software. The survey results indicated that our system featured simple interfaces, easy operation and maintenance, quick processing, and reliable and accurate transactions.

Keywords: end-user application development, enterprise software design, information resource management, usability

Procedia PDF Downloads 433

Authors: Iyad Al-Attar

Abstract:

Air filters installed in HVAC equipment and gas turbine for power generation confront several atmospheric contaminants with various concentrations while operating in different environments (tropical, coastal, hot). This leads to engine performance degradation, as contaminants are capable of deteriorating components and fouling compressor assembly. Compressor fouling is responsible for 70 to 85% of gas turbine performance degradation leading to reduction in power output and availability and an increase in the heat rate and fuel consumption. Therefore, filter design must take into account face velocities, pleat count and its corresponding surface area; to verify filter performance characteristics (Efficiency and Pressure Drop). The experimental work undertaken in the current study examined two groups of four filters with different pleating densities were investigated for the initial pressure drop response and fractional efficiencies. The pleating densities used for this study is 28, 30, 32 and 34 pleats per 100mm for each pleated panel and measured for ten different flow rates ranging from 500 to 5000 m3/h with increment of 500m3/h. This experimental work of the current work has highlighted the underlying reasons behind the reduction in filter permeability due to the increase in face velocity and pleat density. The reasons that led to surface area losses of filtration media are due to one or combination of the following effects: pleat-crowding, deflection of the entire pleated panel, pleat distortion at the corner of the pleat and/or filtration medium compression. It is evident from entire array of experiments that as the particle size increases, the efficiency decreases until the MPPS is reached. Beyond the MPPS, the efficiency increases with increase in particle size. The MPPS shifts to a smaller particle size as the face velocity increases, while the pleating density and orientation did not have a pronounced effect on the MPPS. Throughout the study, an optimal pleat count which satisfies initial pressure drop and efficiency requirements may not have necessarily existed. The work has also suggested that a valid comparison of the pleat densities should be based on the effective surface area that participates in the filtration action and not the total surface area the pleat density provides.

Keywords: air filters, fractional efficiency, gas cleaning, glass fibre, HEPA filter, permeability, pressure drop

Procedia PDF Downloads 132