Search results for: MSW quantity prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3197

Search results for: MSW quantity prediction

857 Prediction of Boundary Shear Stress with Gradually Tapering Flood Plains

Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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River is the main source of water. It is a form of natural open channel which gives rise to many complex phenomenon of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress and depth averaged velocity. The development of society more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, Conveyance Estimation System (CES) software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth , velocity distribution

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856 Modern Scotland Yard: Improving Surveillance Policies Using Adversarial Agent-Based Modelling and Reinforcement Learning

Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

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Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

Procedia PDF Downloads 148
855 Breast Cancer Survivability Prediction via Classifier Ensemble

Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: classifier ensemble, breast cancer survivability, data mining, SEER

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854 Effects of Test Environment on the Sliding Wear Behaviour of Cast Iron, Zinc-Aluminium Alloy and Its Composite

Authors: Mohammad M. Khan, Gajendra Dixit

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Partially lubricated sliding wear behaviour of a zinc-based alloy reinforced with 10wt% SiC particles has been studied as a function of applied load and solid lubricant particle size and has been compared with that of matrix alloy and conventionally used grey cast iron. The wear tests were conducted at the sliding velocities of 2.1m/sec in various partial lubricated conditions using pin on disc machine as per ASTM G-99-05. Base oil (SAE 20W-40) or mixture of the base oil with 5wt% graphite of particle sizes (7-10 µm) and (100 µm) were used for creating lubricated conditions. The matrix alloy revealed primary dendrites of a and eutectoid a + h and Î phases in the Inter dendritic regions. Similar microstructure has been depicted by the composite with an additional presence of the dispersoid SiC particles. In the case of cast iron, flakes of graphite were observed in the matrix; the latter comprised of (majority of) pearlite and (limited quantity of) ferrite. Results show a large improvement in wear resistance of the zinc-based alloy after reinforcement with SiC particles. The cast iron shows intermediate response between the matrix alloy and composite. The solid lubrication improved the wear resistance and friction behaviour of both the reinforced and base alloy. Moreover, minimum wear rate is obtained in oil+ 5wt % graphite (7-10 µm) lubricated environment for the matrix alloy and composite while for cast iron addition of solid lubricant increases the wear rate and minimum wear rate is obtained in case of oil lubricated environment. The cast iron experienced higher frictional heating than the matrix alloy and composite in all the cases especially at higher load condition. As far as friction coefficient is concerned, a mixed trend of behaviour was noted. The wear rate and frictional heating increased with load while friction coefficient was affected in an opposite manner. Test duration influenced the frictional heating and friction coefficient of the samples in a mixed manner.

Keywords: solid lubricant, sliding wear, grey cast iron, zinc based metal matrix composites

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853 The Analysis of Defects Prediction in Injection Molding

Authors: Mehdi Moayyedian, Kazem Abhary, Romeo Marian

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This paper presents an evaluation of a plastic defect in injection molding before it occurs in the process; it is known as the short shot defect. The evaluation of different parameters which affect the possibility of short shot defect is the aim of this paper. The analysis of short shot possibility is conducted via SolidWorks Plastics and Taguchi method to determine the most significant parameters. Finite Element Method (FEM) is employed to analyze two circular flat polypropylene plates of 1 mm thickness. Filling time, part cooling time, pressure holding time, melt temperature and gate type are chosen as process and geometric parameters, respectively. A methodology is presented herein to predict the possibility of the short-shot occurrence. The analysis determined melt temperature is the most influential parameter affecting the possibility of short shot defect with a contribution of 74.25%, and filling time with a contribution of 22%, followed by gate type with a contribution of 3.69%. It was also determined the optimum level of each parameter leading to a reduction in the possibility of short shot are gate type at level 1, filling time at level 3 and melt temperature at level 3. Finally, the most significant parameters affecting the possibility of short shot were determined to be melt temperature, filling time, and gate type.

Keywords: injection molding, plastic defects, short shot, Taguchi method

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852 Analysis of Problems Faced by the Female Students in Capacity Enhancing at Intermediate Level in Girls College of Khyber Pakhtunkhwa, Pakistan

Authors: Uzma Ahmad

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hyber Pakhtunkhwa (KPK) is the most turbulent province of Pakistan, sharing a longborder with Afghanistan. For about four decades, KPK is facing a series of international events. The peak was reached after 9/11when region was labelled as posing a major theatre of militancy and terrorism which was intensified when Tehrik Taliban Pakistan (TTP) began attempts to seize the authority of state. One of the main focus of TTP was to damage and uprooting of female education system and infrastructure in KPK which later became the site of a massacre of school children of Army Public School Peshawar on 16 December 2014.It resulted to the launching of Zarb-e-Azb against the TTP insurgency,casualty and crime rates in the KPKas a whole dropped by 40.0% as compared to 2011–13. All this has badly hampered the female education both in terms of quantity and quality. Malala Yousafzai who is now an advocate of female education has been a victim of Talibans brutality in that area. And thelanguage in which she managed to express herself to the International community is English.Keeping in view the situation, the present project was designed with a sole aim to focus on female students of the area which are few in numbers and to investigate some specific area, where they have been confronting problems in the use of grammar, vocabulary,tenses and organization of ideas in writings. The reasons might be the careless attitude, insufficient reading habits, lack of interest and poor knowledge of English language. The methodology was a descriptive one as it shows the effects of the internal efficiency(independent variables) on an intermediate college’s progress(dependent variables). It was a case study since data was collected from a focused group of 60 female students of arts and humanities at Swabi college at Intermediate level. The ultimate focus was to explore the possibilities of creating a Gender friendly environment for female students. This research has proved how the correct use of English language has given them confidence to move ahead side by side with men and to acknowledge their right of self-determination.

Keywords: capacity building, female education, gender friendly, internal efficiency

Procedia PDF Downloads 164
851 Correlations between Wear Rate and Energy Dissipation Mechanisms in a Ti6Al4V–WC/Co Sliding Pair

Authors: J. S. Rudas, J. M. Gutiérrez Cabeza, A. Corz Rodríguez, L. M. Gómez, A. O. Toro

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The prediction of the wear rate of rubbing pairs has attracted the interest of many researchers for years. It has been recently proposed that the sliding wear rate can be inferred from the calculation of the energy rate dissipated by the tribological pair. In this paper some of the dissipative mechanisms present in a pin-on-disc configuration are discussed and both analytical and numerical calculations are carried out. Three dissipative mechanisms were studied: First, the energy release due to temperature gradients within the solid; second, the heat flow from the solid to the environment, and third, the energy loss due to abrasive damage of the surface. The Finite Element Method was used to calculate the dynamics of heat transfer within the solid, with the aid of commercial software. Validation the FEM model was assisted by virtual and laboratory experimentation using different operating points (sliding velocity and geometry contact). The materials for the experiments were Ti6Al4V alloy and Tungsten Carbide (WC-Co). The results showed that the sliding wear rate has a linear relationship with the energy dissipation flow. It was also found that energy loss due to micro-cutting is relevant for the system. This mechanism changes if the sliding velocity and pin geometry are modified though the degradation coefficient continues to present a linear behavior. We found that the less relevant dissipation mechanism for all the cases studied is the energy release by temperature gradients in the solid.

Keywords: degradation, dissipative mechanism, dry sliding, entropy, friction, wear

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850 Modelling and Investigation of Phase Change Phenomena of Multiple Water Droplets

Authors: K. R. Sultana, K. Pope, Y. S. Muzychka

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In recent years, the research of heat transfer or phase change phenomena of liquid water droplets experiences a growing interest in aircraft icing, power transmission line icing, marine icing and wind turbine icing applications. This growing interest speeding up the research from single to multiple droplet phenomena. Impingements of multiple droplets and the resulting solidification phenomena after impact on a very cold surface is computationally studied in this paper. The model used in the current study solves the flow equation, composed of energy balance and the volume fraction equations. The main aim of the study is to investigate the effects of several thermo-physical properties (density, thermal conductivity and specific heat) on droplets freezing. The outcome is examined by various important factors, for instance, liquid fraction, total freezing time, droplet temperature and total heat transfer rate in the interface region. The liquid fraction helps to understand the complete phase change phenomena during solidification. Temperature distribution and heat transfer rate help to demonstrate the overall thermal exchange behaviors between the droplets and substrate surface. Findings of this research provide an important technical achievement for ice modeling and prediction studies.

Keywords: droplets, CFD, thermos-physical properties, solidification

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849 Species Distribution Modelling for Assessing the Effect of Land Use Changes on the Habitat of Endangered Proboscis Monkey (Nasalis larvatus) in Kalimantan, Indonesia

Authors: Wardatutthoyyibah, Satyawan Pudyatmoko, Sena Adi Subrata, Muhammad Ali Imron

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The proboscis monkey is an endemic species to the island of Borneo with conservation status IUCN (The International Union for Conservation of Nature) of endangered. The population of the monkey has a specific habitat and sensitive to habitat disturbances. As a consequence of increasing rates of land-use change in the last four decades, its population was reported significantly decreased. We quantified the effect of land use change on the proboscis monkey’s habitat through the species distribution modeling (SDM) approach with Maxent Software. We collected presence data and environmental variables, i.e., land cover, topography, bioclimate, distance to the river, distance to the road, and distance to the anthropogenic disturbance to generate predictive distribution maps of the monkeys. We compared two prediction maps for 2000 and 2015 data to represent the current habitat of the monkey. We overlaid the monkey’s predictive distribution map with the existing protected areas to investigate whether the habitat of the monkey is protected under the protected areas networks. The results showed that almost 50% of the monkey’s habitat reduced as the effect of land use change. And only 9% of the current proboscis monkey’s habitat within protected areas. These results are important for the master plan of conservation of the endangered proboscis monkey and provide scientific guidance for the future development incorporating biodiversity issue.

Keywords: endemic species, land use change, maximum entropy, spatial distribution

Procedia PDF Downloads 158
848 Predicting Options Prices Using Machine Learning

Authors: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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847 Predicting Dose Level and Length of Time for Radiation Exposure Using Gene Expression

Authors: Chao Sima, Shanaz Ghandhi, Sally A. Amundson, Michael L. Bittner, David J. Brenner

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In a large-scale radiologic emergency, potentially affected population need to be triaged efficiently using various biomarkers where personal dosimeters are not likely worn by the individuals. It has long been established that radiation injury can be estimated effectively using panels of genetic biomarkers. Furthermore, the rate of radiation, in addition to dose of radiation, plays a major role in determining biological responses. Therefore, a better and more accurate triage involves estimating both the dose level of the exposure and the length of time of that exposure. To that end, a large in vivo study was carried out on mice with internal emitter caesium-137 (¹³⁷Cs). Four different injection doses of ¹³⁷Cs were used: 157.5 μCi, 191 μCi, 214.5μCi, and 259 μCi. Cohorts of 6~7 mice from the control arm and each of the dose levels were sacrificed, and blood was collected 2, 3, 5, 7 and 14 days after injection for microarray RNA gene expression analysis. Using a generalized linear model with penalized maximum likelihood, a panel of 244 genes was established and both the doses of injection and the number of days after injection were accurately predicted for all 155 subjects using this panel. This has proven that microarray gene expression can be used effectively in radiation biodosimetry in predicting both the dose levels and the length of exposure time, which provides a more holistic view on radiation exposure and helps improving radiation damage assessment and treatment.

Keywords: caesium-137, gene expression microarray, multivariate responses prediction, radiation biodosimetry

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846 Multi-Objective Optimization and Effect of Surface Conditions on Fatigue Performance of Burnished Components Made of AISI 52100 Steel

Authors: Ouahiba Taamallah, Tarek Litim

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The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

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845 Occurrence and Levels of Mycotoxins in On-Farm Stored Sesame in Major-Growing Districts of Ethiopia

Authors: S. Alemayehu, F. A. Abera, K. M. Ayimut, R. Mahroof, J. Harvey, B. Subramanyam

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The occurrence of mycotoxins in sesame seeds poses a significant threat to food safety and the economy in Ethiopia. This study aimed to determine the levels and occurrence of mycotoxins in on-farm stored sesame seeds in major-growing districts of Ethiopia. A total of 470 sesame seed samples were collected from randomly selected farmers' storage structures in five major-growing districts using purposive sampling techniques. An enzyme-linked immunosorbent assay (ELISA) was used to analyze the collected samples for the presence of four mycotoxins: total aflatoxins (AFT), ochratoxin A (OTA), total fumonisins (FUM), and deoxynivalenol (DON). The study found that all samples contained varying levels of mycotoxins, with AFT and DON being the most prevalent. AFT concentrations in detected samples ranged from 2.5 to 27.8 parts per billion (ppb), with a mean concentration of 13.8 ppb. OTA levels ranged from 5.0 ppb to 9.7 ppb, with a mean level of 7.1 ppb. Total fumonisin concentrations ranged from 300 to 1300 ppb in all samples, with a mean of 800 ppb. DON concentrations ranged from 560 to 700 ppb in the analyzed samples. The majority (96.8%) of the samples were safe from AFT, FUM, and DON mean levels when compared to the Federal Drug Administration maximum limit. AFT-OTA, DON-OTA, AFT-FUM, FUM-DON, and FUM-OTA, respectively, had co-occurrence rates of 44.0, 38.3, 33.8, 30.2, 29.8 and 26.0% for mycotoxins. On average, 37.2% of the sesame samples had fungal infection, and seed germination rates ranged from 66.8% to 91.1%. The Limmu district had higher levels of total aflatoxins, kernel infection, and lower germination rates than other districts. The Wollega variety of sesame had higher kernel infection, total aflatoxins concentration, and lower germination rates than other varieties. Grain age had a statistically significant (p<0.05) effect on both kernel infection and germination. The storage methods used for sesame in major-growing districts of Ethiopia favor mycotoxin-producing fungi. As the levels of mycotoxins in sesame are of public health significance, stakeholders should come together to identify secure and suitable storage technologies to maintain the quantity and quality of sesame at the level of smallholder farmers. This study suggests the need for suitable storage technologies to maintain the quality of sesame and reduce the risk of mycotoxin contamination.

Keywords: districts, seed germination, kernel infection, moisture content, relative humidity, temperature

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844 Chatter Prediction of Curved Thin-walled Parts Considering Variation of Dynamic Characteristics Based on Acoustic Signals Acquisition

Authors: Damous Mohamed, Zeroudi Nasredine

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High-speed milling of thin-walled parts with complex curvilinear profiles often encounters machining instability, commonly referred to as chatter. This phenomenon arises due to the dynamic interaction between the cutting tool and the part, exacerbated by the part's low rigidity and varying dynamic characteristics along the tool path. This research presents a dynamic model specifically developed to predict machining stability for such curved thin-walled components. The model employs the semi-discretization method, segmenting the tool trajectory into small, straight elements to locally approximate the behavior of an inclined plane. Dynamic characteristics for each segment are extracted through experimental modal analysis and incorporated into the simulation model to generate global stability lobe diagrams. Validation of the model is conducted through cutting tests where acoustic intensity is measured to detect instabilities. The experimental data align closely with the predicted stability limits, confirming the model's accuracy and effectiveness. This work provides a comprehensive approach to enhancing machining stability predictions, thereby improving the efficiency and quality of high-speed milling operations for thin-walled parts.

Keywords: chatter, curved thin-walled part, semi-discretization method, stability lobe diagrams

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843 Adaptive Strategies to Nutrient Deficiency of Doubled Diploid Citrumelo 4475: A Prospective Study Based on Structural, Ultrastructural, Physiological and Biochemical Parameters

Authors: J. Oustric, L. Berti, J. Santini

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Nowadays, the objective of durable agriculture, and in particular organic agriculture, is to reduce the level of fertilizer inputs used in crops. Limiting the quantity of fertilizer inputs would optimize the economical result and minimizing the environmental impact. Nutrient deficiency, particularly of a major nutrient (N, P, and K), can seriously affect fruit production and quality. In citrus crops, rootstock/scion combinations. In citrus crop, scion/rootstock combinations are used frequently to improve tolerance to various abiotic stresses. New rootstocks are needed to respond to these constraints, and the use of new tetraploid rootstocks better adapted to lower nutrient intake could offer a promising way forward. The aim of this work was to determine whether a better tolerance to nutrient deficiency could be observed in a doubled diploid seedling and whether this tolerance could be observed in common clementine scion if used as rootstocks. We selected diploid (CM2x) and doubled diploid (CM4x) Citrumelo 4475 seedlings and common clementine (C) grafted onto Citrumelo 4475 diploid (C/CM2x) and doubled diploid (C/CM4x) rootstocks. Nutrient deficiency effects on the seedlings and scion/rootstock combinations were analyzed by studying anatomical, structural and ultrastructural determinants (chlorosis, stomata, ostiole and cells and their organelles), photosynthetic properties (leaf net photosynthetic rate (Pₙₑₜ), stomatal conductance (gₛ), chlorophyll a fluorescence (Fᵥ/Fₘ)) and oxidative marker (malondialdehyde). Nutrient deficiency affected differently foliar tissues, physiological parameters, and oxidative metabolism in leaves of seedlings depending on their ploidy level and of common clementine scion depending on their rootstocks ploidy level. Both CM4x and C/CM4x presented lower foliar damages (chlorosis, chloroplasts, mitochondria, and plastoglobuli), photosynthesis processes alteration (Pₙₑₜ, gₛ, and Fᵥ/Fₘ), and malondialdehyde accumulation than CM2x and C/CM2x after nutrient deficiency. Doubled diploid Citrumelo 4475 can improve nutrient deficiency tolerance, and its use as a rootstock allows to confer this tolerance to the common clementine scion.

Keywords: nutrient deficiency, oxidative stress, photosynthesis, polyploid rootstocks

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842 Improving the Digestibility of Agro-Industrial Co-Products by Treatment with Isolated Fungi in the Meknes-Morocco Region

Authors: Mohamed Benaddou, Mohammed Diouri

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country, such as Morocco, generates a high quantity of agricultural and food industry residues. A large portion of these residues is disposed of by burning or landfilling. The valorization of this waste biomass as feed is an interesting alternative because it is therefore considered among the best sources of cheap carbohydrates. However, its nutritional yield without any pre-treatment is very low because lignin protects cellulose, the carbohydrate used as a source of energy by ruminants. Fungal treatment is an environmentally friendly, easy and inexpensive method. This study investigated the treatment of wheat straw (WS), cedar sawdust (CS) and olive pomace (OP) with fungi selected according to the source of Carbon for improving its digestibility. Two were selected in a culture medium in which cellulose was the only source of Carbon: Cosmospora Viridescens (C.vir) and Penicillium crustosum (P.crus), two were selected in a culture medium in which lignin is the only source of Carbon: Fusarium oxysporum (F.oxy) and Fusarium sp. (F. Sp), and two in a culture medium where cellulose and lignin are the two sources of Carbon at the same time: Fusarium solani (F. solani) and Penicillium chrysogenum (P.chryso). P.chryso degraded more CS cellulose. It is very important to notice that the delignification by F. Solani reached 70% after 12 weeks of treatment of wheat straw. Ligninase enzymatic was detected in F.solani, F.sp, F.oxysporum, which made it possible to delignify the treated substrates. Delignification by C.vir is negligible in all three substrates after 12 weeks of treatment. P.crus and P.chryso degraded the lignin very slightly in WC (it did not exceed 12% after 12 weeks of treatment) but in OP this delignification is slight reaching 25% and 13% for P.chryso and P.crus successively. P.chryso allowed 30% degradation of lignin from 4 weeks of treatment. The degradation of the lignin was able to reach the maximum within 8 weeks of treatment for most of the fungi except F. solani who continued the treatment after this period. Digestibility variation (IVTD.variation) is highly very significant from fungus to fungi, duration to time, substrate to substrate and its interactions (P <0.001). indeed, all the fungi increased digestibility after 12 weeks of treatment with a difference in the degree of this increase. F.solani and F.oxy increased digestibility more than the others. this digestibility exceeded 50% in CS and O.P but did not exceed 20% for WS after treatment with F.oxy. IVTD.Var was not exceeded 20% in W.S.cedar treated with P.chryso but reached 45% after 8 weeks of treatment in W.straw.

Keywords: lignin, cellulose, digestibility, fungi, treatment, lignocellulosic biomass

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841 Precision Pest Management by the Use of Pheromone Traps and Forecasting Module in Mobile App

Authors: Muhammad Saad Aslam

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In 2021, our organization has launched our proprietary mobile App i.e. Farm Intelligence platform, an industrial-first precision agriculture solution, to Pakistan. It was piloted at 47 locations (spanning around 1,200 hectares of land), addressing growers’ pain points by bringing the benefits of precision agriculture to their doorsteps. This year, we have extended its reach by more than 10 times (nearly 130,000 hectares of land) in almost 600 locations across the country. The project team selected highly infested areas to set up traps, which then enabled the sales team to initiate evidence-based conversations with the grower community about preventive crop protection products that includes pesticides and insecticides. Mega farmer meeting field visits and demonstrations plots coupled with extensive marketing activities, were setup to include farmer community. With the help of App real-time pest monitoring (using heat maps and infestation prediction through predictive analytics) we have equipped our growers with on spot insights that will help them optimize pesticide applications. Heat maps allow growers to identify infestation hot spots to fine-tune pesticide delivery, while predictive analytics enable preventive application of pesticides before the situation escalates. Ultimately, they empower growers to keep their crops safe for a healthy harvest.

Keywords: precision pest management, precision agriculture, real time pest tracking, pest forecasting

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840 Development of Biodegradable Wound Healing Patch of Curcumin

Authors: Abhay Asthana, Shally Toshkhani, Gyati Shilakari

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The objective of the present research work is to develop a topical biodegradable dermal patch based formulation to aid accelerated wound healing. It is always better for patient compliance to be able to reduce the frequency of dressings with improved drug delivery and overall therapeutic efficacy. In present study optimized formulation using biodegradable components was obtained evaluating polymers and excipients (HPMC K4M, Ethylcellulose, Povidone, Polyethylene glycol and Gelatin) to impart significant folding endurance, elasticity, and strength. Molten gelatin was used to get a mixture using ethylene glycol. Chitosan dissolved in acidic medium was mixed with stirring to Gelatin mixture. With continued stirring to the mixture Curcumin was added with the aid of DCM and Methanol in an optimized ratio of 60:40 to get homogenous dispersion. Polymers were dispersed with stirring in the final formulation. The mixture was sonicated casted to get the film form. All steps were carried out under strict aseptic conditions. The final formulation was a thin uniformly smooth textured film with dark brown-yellow color. The film was found to have folding endurance was around 20 to 21 times without a crack in an optimized formulation at RT (23°C). The drug content was in range 96 to 102% and it passed the content uniform test. The final moisture content of the optimized formulation film was NMT 9.0%. The films passed stability study conducted at refrigerated conditions (4±0.2°C) and at room temperature (23 ± 2°C) for 30 days. Further, the drug content and texture remained undisturbed with stability study conducted at RT 23±2°C for 45 and 90 days. Percentage cumulative drug release was found to be 80% in 12h and matched the biodegradation rate as tested in vivo with correlation factor R2>0.9. In in vivo study administration of one dose in equivalent quantity per 2 days was applied topically. The data demonstrated a significant improvement with percentage wound contraction in contrast to control and plain drug respectively in given period. The film based formulation developed shows promising results in terms of stability and in vivo performance.

Keywords: wound healing, biodegradable, polymers, patch

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839 Improved Classification Procedure for Imbalanced and Overlapped Situations

Authors: Hankyu Lee, Seoung Bum Kim

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The issue with imbalance and overlapping in the class distribution becomes important in various applications of data mining. The imbalanced dataset is a special case in classification problems in which the number of observations of one class (i.e., major class) heavily exceeds the number of observations of the other class (i.e., minor class). Overlapped dataset is the case where many observations are shared together between the two classes. Imbalanced and overlapped data can be frequently found in many real examples including fraud and abuse patients in healthcare, quality prediction in manufacturing, text classification, oil spill detection, remote sensing, and so on. The class imbalance and overlap problem is the challenging issue because this situation degrades the performance of most of the standard classification algorithms. In this study, we propose a classification procedure that can effectively handle imbalanced and overlapped datasets by splitting data space into three parts: nonoverlapping, light overlapping, and severe overlapping and applying the classification algorithm in each part. These three parts were determined based on the Hausdorff distance and the margin of the modified support vector machine. An experiments study was conducted to examine the properties of the proposed method and compared it with other classification algorithms. The results showed that the proposed method outperformed the competitors under various imbalanced and overlapped situations. Moreover, the applicability of the proposed method was demonstrated through the experiment with real data.

Keywords: classification, imbalanced data with class overlap, split data space, support vector machine

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838 Hydrological Evaluation of Satellite Precipitation Products Using IHACRES Rainfall-Runoff Model over a Basin in Iran

Authors: Mahmoud Zakeri Niri, Saber Moazami, Arman Abdollahipour, Hossein Ghalkhani

Abstract:

The objective of this research is to hydrological evaluation of four widely-used satellite precipitation products named PERSIANN, TMPA-3B42V7, TMPA-3B42RT, and CMORPH over Zarinehrood basin in Iran. For this aim, at first, daily streamflow of Sarough-cahy river of Zarinehrood basin was simulated using IHACRES rainfall-runoff model with daily rain gauge and temperature as input data from 1988 to 2008. Then, the model was calibrated in two different periods through comparison the simulated discharge with the observed one at hydrometric stations. Moreover, in order to evaluate the performance of satellite precipitation products in streamflow simulation, the calibrated model was validated using daily satellite rainfall estimates from the period of 2003 to 2008. The obtained results indicated that TMPA-3B42V7 with CC of 0.69, RMSE of 5.93 mm/day, MAE of 4.76 mm/day, and RBias of -5.39% performs better simulation of streamflow than those PERSIANN and CMORPH over the study area. It is noteworthy that in Iran, the availability of ground measuring station data is very limited because of the sparse density of hydro-meteorological networks. On the other hand, large spatial and temporal variability of precipitations and lack of a reliable and extensive observing system are the most important challenges to rainfall analysis, flood prediction, and other hydrological applications in this country.

Keywords: hydrological evaluation, IHACRES, satellite precipitation product, streamflow simulation

Procedia PDF Downloads 241
837 Detection and Molecular Identification of Bacteria Forming Polyhydroxyalkanoate and Polyhydroxybutyrate Isolated from Soil in Saudi Arabia

Authors: Ali Bahkali, Rayan Yousef Booq, Mohammad Khiyami

Abstract:

Soil samples were collected from five different regions in the Kingdom of Saudi Arabia. Microbiological methods included dilution methods and pour plates to isolate and purify bacteria soil. The ability of isolates to develop biopolymer was investigated on petri dishes containing elements and substance concentrations stimulating developing biopolymer. Fluorescent stains, Nile red and Nile blue were used to stain the bacterial cells developing biopolymers. In addition, Sudan black was used to detect biopolymers in bacterial cells. The isolates which developed biopolymers were identified based on their gene sequence of 1 6sRNA and their ability to grow and synthesize PHAs on mineral medium supplemented with 1% dates molasses as the only carbon source under nitrogen limitation. During the study 293 bacterial isolates were isolated and detected. Through the initial survey on the petri dishes, 84 isolates showed the ability to develop biopolymers. These bacterial colonies developed a pink color due to accumulation of the biopolymers in the cells. Twenty-three isolates were able to grow on dates molasses, three strains of which showed the ability to accumulate biopolymers. These strains included Bacillus sp., Ralstonia sp. and Microbacterium sp. They were detected by Nile blue A stain with fluorescence microscopy (OLYMPUS IX 51). Among the isolated strains Ralstonia sp. was selected after its ability to grow on molasses dates in the presence of a limited nitrogen source was detected. The optimum conditions for formation of biopolymers by isolated strains were investigated. Conditions studied included, best incubation duration (2 days), temperature (30°C) and pH (7-8). The maximum PHB production was raised by 1% (v1v) when using concentrations of dates molasses 1, 2, 3, 4 and 5% in MSM. The best inoculated with 1% old inoculum (1= OD). The ideal extraction method of PHA and PHB proved to be 0.4% sodium hypochlorite solution, producing a quantity of polymer 98.79% of the cell's dry weight. The maximum PHB production was 1.79 g/L recorded by Ralstonia sp. after 48 h, while it was 1.40 g/L produced by R.eutropha ATCC 17697 after 48 h.

Keywords: bacteria forming polyhydroxyalkanoate, detection, molecular, Saudi Arabia

Procedia PDF Downloads 347
836 Torque Loss Prediction Test Method of Bolted Joints in Heavy Commercial Vehicles

Authors: Volkan Ayik

Abstract:

Loosening as a result of torque loss in bolted joints is one of the most encountered problems resulting in loss of connection between parts. The main reason for this is the dynamic loads to which the joints are subjected while the vehicle is moving. In particular, vibration-induced loads can loosen the joints in any size and geometry. The aim of this study is to study an improved method due to road-induced vibration in heavy commercial vehicles for estimating the vibration performance of bolted joints of the components connected to the chassis, before conducting prototype level vehicle structural strength tests on a proving ground. The frequency and displacements caused by the road conditions-induced vibration loads have been determined for the parts connected to the chassis, and various experimental design scenarios have been formed by matching specific components and vibration behaviors. In the studies, the performance of the torque, washer, test displacement, and test frequency parameters were observed by maintaining the connection characteristics on the vehicle, and the sensitivity ratios for these variables were calculated. As a result of these experimental design findings, tests performed on a developed device based on Junker’s vibration device and proving ground conditions versus test correlation levels were found.

Keywords: bolted joints, junker’s test, loosening failure, torque loss

Procedia PDF Downloads 124
835 Technology in the Calculation of People Health Level: Design of a Computational Tool

Authors: Sara Herrero Jaén, José María Santamaría García, María Lourdes Jiménez Rodríguez, Jorge Luis Gómez González, Adriana Cercas Duque, Alexandra González Aguna

Abstract:

Background: Health concept has evolved throughout history. The health level is determined by the own individual perception. It is a dynamic process over time so that you can see variations from one moment to the next. In this way, knowing the health of the patients you care for, will facilitate decision making in the treatment of care. Objective: To design a technological tool that calculates the people health level in a sequential way over time. Material and Methods: Deductive methodology through text analysis, extraction and logical knowledge formalization and education with expert group. Studying time: September 2015- actually. Results: A computational tool for the use of health personnel has been designed. It has 11 variables. Each variable can be given a value from 1 to 5, with 1 being the minimum value and 5 being the maximum value. By adding the result of the 11 variables we obtain a magnitude in a certain time, the health level of the person. The health calculator allows to represent people health level at a time, establishing temporal cuts being useful to determine the evolution of the individual over time. Conclusion: The Information and Communication Technologies (ICT) allow training and help in various disciplinary areas. It is important to highlight their relevance in the field of health. Based on the health formalization, care acts can be directed towards some of the propositional elements of the concept above. The care acts will modify the people health level. The health calculator allows the prioritization and prediction of different strategies of health care in hospital units.

Keywords: calculator, care, eHealth, health

Procedia PDF Downloads 264
834 Modeling of Full Range Flow Boiling Phenomenon in 23m Long Vertical Steam Generator Tube

Authors: Chaitanya R. Mali, V. Vinod, Ashwin W. Patwardhan

Abstract:

Design of long vertical steam generator (SG) tubes in nuclear power plant involves an understanding of different aspects of flow boiling phenomenon such as flow instabilities, flow regimes, dry out, critical heat flux, pressure drop, etc. The knowledge of the prediction of local thermal hydraulic characteristics is necessary to understand these aspects. For this purpose, the methodology has been developed which covers all the flow boiling regimes to model full range flow boiling phenomenon. In this methodology, the vertical tube is divided into four sections based on vapor fraction value at the end of each section. Different modeling strategies have been applied to the different sections of the vertical tube. Computational fluid dynamics simulations have been performed on a vertical SG tube of 0.0126 m inner diameter and 23 m length. The thermal hydraulic parameters such as vapor fraction, liquid temperature, heat transfer coefficient, pressure drop, heat flux distribution have been analyzed for different designed heat duties (1.1 MW (20%) to 3.3 MW (60%)) and flow conditions (10 % to 80 %). The sensitivity of different boiling parameters such as bubble departure diameter, nucleation site density, bubble departure frequency on the thermal hydraulic parameters was also studied. Flow instability has been observed at 20 % designed heat duty and 20 % flow conditions.

Keywords: thermal hydraulics, boiling, vapor fraction, sensitivity

Procedia PDF Downloads 147
833 Detection of Internal Mold Infection of Intact Tomatoes by Non-Destructive, Transmittance VIS-NIR Spectroscopy

Authors: K. Petcharaporn

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

Procedia PDF Downloads 363
832 Development of Antioxidant Rich Bakery Products by Applying Lysine and Maillard Reaction Products

Authors: Attila Kiss, Erzsébet Némedi, Zoltán Naár

Abstract:

Due to the rapidly growing number of conscious customers in the recent years, more and more people look for products with positive physiological effects which may contribute to the preservation of their health. In response to these demands Food Science Research Institute of Budapest develops and introduces into the market new functional foods of guaranteed positive effect that contain bioactive agents. New, efficient technologies are also elaborated in order to preserve the maximum biological effect of the produced foods. The main objective of our work was the development of new functional biscuits fortified with physiologically beneficial ingredients. Bakery products constitute the base of the food nutrients’ pyramid, thus they might be regarded as foodstuffs of the largest consumed quantity. In addition to the well-known and certified physiological benefits of lysine, as an essential amino acid, a series of antioxidant type compounds is formed as a consequence of the occurring Maillard-reaction. Progress of the evoked Maillard-reaction was studied by applying diverse sugars (glucose, fructose, saccharose, isosugar) and lysine at several temperatures (120-170°C). Interval of thermal treatment was also varied (10-30 min). The composition and production technologies were tailored in order to reach the maximum of the possible biological benefits, so as to the highest antioxidant capacity in the biscuits. Out of the examined sugar components, theextent of the Maillard-reaction-driven transformation of glucose was the most pronounced at both applied temperatures. For the precise assessment of the antioxidant activity of the products FRAP and DPPH methods were adapted and optimised. To acquire an authentic and extensive mechanism of the occurring transformations, Maillard-reaction products were identified, and relevant reaction pathways were revealed. GC-MS and HPLC-MS techniques were applied for the analysis of the 60 generated MRPs and characterisation of actual transformation processes. 3 plausible major transformation routes might have been suggested based on the analytical result and the deductive sequence of possible occurring conversions between lysine and the sugars.

Keywords: Maillard-reaction, lysine, antioxidant activity, GC-MS and HPLC-MS techniques

Procedia PDF Downloads 482
831 Quantitative Structure-Activity Relationship Analysis of Binding Affinity of a Series of Anti-Prion Compounds to Human Prion Protein

Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Milica Karadžić

Abstract:

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina.

Keywords: anti-prion activity, chemometrics, molecular modeling, QSAR

Procedia PDF Downloads 304
830 A Machine Learning Approach for Earthquake Prediction in Various Zones Based on Solar Activity

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Saifur Rahman Sabuj

Abstract:

This paper examines relationships between solar activity and earthquakes; it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

Keywords: k-nearest neighbour, support vector regression, random forest regression, long short-term memory network, earthquakes, solar activity, sunspot number, solar wind, solar flares

Procedia PDF Downloads 73
829 Detection of Internal Mold Infection of Intact For Tomatoes by Non-Destructive, Transmittance VIS-NIR Spectroscopy

Authors: K. Petcharaporn, N. Prathengjit

Abstract:

The external characteristics of tomatoes, such as freshness, color and size are typically used in quality control processes for tomatoes sorting. However, the internal mold infection of intact tomato cannot be sorted based on a visible assessment and destructive method alone. In this study, a non-destructive technique was used to predict the internal mold infection of intact tomatoes by using transmittance visible and near infrared (VIS-NIR) spectroscopy. Spectra for 200 samples contained 100 samples for normal tomatoes and 100 samples for mold infected tomatoes were acquired in the wavelength range between 665-955 nm. This data was used in conjunction with partial least squares-discriminant analysis (PLS-DA) method to generate a classification model for tomato quality between groups of internal mold infection of intact tomato samples. For this task, the data was split into two groups, 140 samples were used for a training set and 60 samples were used for a test set. The spectra of both normal and internally mold infected tomatoes showed different features in the visible wavelength range. Combined spectral pretreatments of standard normal variate transformation (SNV) and smoothing (Savitzky-Golay) gave the optimal calibration model in training set, 85.0% (63 out of 71 for the normal samples and 56 out of 69 for the internal mold samples). The classification accuracy of the best model on the test set was 91.7% (29 out of 29 for the normal samples and 26 out of 31 for the internal mold tomato samples). The results from this experiment showed that transmittance VIS-NIR spectroscopy can be used as a non-destructive technique to predict the internal mold infection of intact tomatoes.

Keywords: tomato, mold, quality, prediction, transmittance

Procedia PDF Downloads 519
828 Environmental Performance Improvement of Additive Manufacturing Processes with Part Quality Point of View

Authors: Mazyar Yosofi, Olivier Kerbrat, Pascal Mognol

Abstract:

Life cycle assessment of additive manufacturing processes has evolved significantly since these past years. A lot of existing studies mainly focused on energy consumption. Nowadays, new methodologies of life cycle inventory acquisition came through the literature and help manufacturers to take into account all the input and output flows during the manufacturing step of the life cycle of products. Indeed, the environmental analysis of the phenomena that occur during the manufacturing step of additive manufacturing processes is going to be well known. Now it becomes possible to count and measure accurately all the inventory data during the manufacturing step. Optimization of the environmental performances of processes can now be considered. Environmental performance improvement can be made by varying process parameters. However, a lot of these parameters (such as manufacturing speed, the power of the energy source, quantity of support materials) affect directly the mechanical properties, surface finish and the dimensional accuracy of a functional part. This study aims to improve the environmental performance of an additive manufacturing process without deterioration of the part quality. For that purpose, the authors have developed a generic method that has been applied on multiple parts made by additive manufacturing processes. First, a complete analysis of the process parameters is made in order to identify which parameters affect only the environmental performances of the process. Then, multiple parts are manufactured by varying the identified parameters. The aim of the second step is to find the optimum value of the parameters that decrease significantly the environmental impact of the process and keep the part quality as desired. Finally, a comparison between the part made by initials parameters and changed parameters is made. In this study, the major finding claims by authors is to reduce the environmental impact of an additive manufacturing process while respecting the three quality criterion of parts, mechanical properties, dimensional accuracy and surface roughness. Now that additive manufacturing processes can be seen as mature from a technical point of view, environmental improvement of these processes can be considered while respecting the part properties. The first part of this study presents the methodology applied to multiple academic parts. Then, the validity of the methodology is demonstrated on functional parts.

Keywords: additive manufacturing, environmental impact, environmental improvement, mechanical properties

Procedia PDF Downloads 288