Search results for: aerial parts of Tanacetum balsamita balsamita L.

Authors: S. Barbaqadze, M. Goderdzishvili, E. Mosidze, L. Lomtadze, V. Mshvildadze, L. Bakuridze, D. Berashvili, A. Bakuridze

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This paper focuses on the formulation of phytobiotic designated for further implantation in poultry farming. Composition was meant to be water-soluble powder containing antibacterial essential oils. The development process involved Thyme, Monarda and Clary sage essential oils. The antimicrobial activity of essential oils composite was meant to be tested against gram-negative and gram-positive bacterial strains. The results are processed using the statistical program Sigma STAT. To make essential oils composition water soluble surfactants were added to them. At the first stage of the study, nine options for the optimal composition of essential oils and surfactants were developed. The effect of the amount of surfactants on the essential oils composition solubility in water has been investigated. On the basis of biopharmaceutical studies, the formulation of phytobiotic has been determined: Thyme, monarda and clary sage essential oils 2:1:1 - 100 parts; Licorice extract 5.25 parts and inhalation lactose 300 parts. A technology for the preparation of phytobiotic has been developed and a technological scheme for the preparation of phytobiotic has been made up. The research was performed within the framework of the grant project CARYS-19-363 funded be the Shota Rustaveli National Science Foundation of Georgia.

Keywords: clary, essential oils, monarda, phytobiotics, poultry, thyme

Procedia PDF Downloads 160

Authors: S. Benessam, T. H. Debieche, S. Amiour, A. Chine, S. Khelili

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Iron is naturally present in groundwater, it comes from the dissolution of the geological formations (clay, schist, mica-schist, gneiss…). Its chemical form and mobility in water are controlled mainly by two physicochemical parameters (Eh and pH). In order to determine its spatiotemporal evolution in groundwater, a two-monthly monitoring of the physicochemical parameters and major elements in the water of the alluvial sheet of Nil river (North-eastern Algerian) was carried out during the period from November 2013 to January 2015. The results show that iron is present in weak concentrations in the upstream part of the alluvial sheet and with raised concentrations, which can exceed the standard of potable drinking water (0.2 mg/L), in the central and downstream parts of the alluvial sheet. This variation of the concentrations is related to the important variation of Eh between the upstream part (200 mV) where the aquiver is unconfined (oxidizing medium) and the central and downstream parts (-100 mV) where the aquifer is confined (reducing medium). Iron in the oxidizing part is presented with the complexes form, where it precipitates or/and adsorbed by the geological formations. On the other hand in the reducing parts, it is released in water. In this study, one will discuss also the mobility and the chemical forms of iron according to the rains and pumping.

Keywords: groundwater, iron, mobility, speciation

Procedia PDF Downloads 334

Authors: Gheimati Salar

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The objective of conducting this research was to study the influence of plyometric exercises on the biomechanical selected factor of elite teen swimmers and compare the influence of plyometric exercises on the speed of front crawl and back crawl in empirical and control groups of teens. In order to conduct these study 30 swimmers with minimum of 3 years' experience who were 11 or 12 were randomly chosen and divided into 2 groups of 15. The first group was empirical and the second was control group. The speed of the swimmer was analyzed after 25 meters of swimming and their speed were recorded in the last. The researcher was standing stable at the beginning and then started the chronometer and stopped it at the end of the swimming. He repeated the record taking two times and then the average was taken. Before conducting plyometric exercises, a speed test was taken from both groups in both types of swimming. The duration of plyometric exercises was 8 weeks, every week 3 sessions and 24 sessions in total. The exercises in this study were focused on 3 parts of the body. Upper limb part, the lower part of the body and trunk area. Upper limb exercises consisted of four parts. The lower limb exercises consisted of 5 parts, and the trunk exercises consisted of four sections. A Medicine ball, cone and different weights were used in these exercises.

Keywords: plyometric, exercises, front crawl and back crawl, speed

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Authors: Thomas Wimmer, Bernhard Weigand

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The improvement of gas turbine efficiency is one of the main drivers of research and development in the gas turbine market. This has led to elevated gas turbine inlet temperatures beyond the melting point of the utilized materials. The turbine parts need to be actively cooled in order to withstand these harsh environments. However, the usage of compressor air as coolant decreases the overall gas turbine efficiency. Thus, coolant consumption needs to be minimized in order to gain the maximum advantage from higher turbine inlet temperatures. Therefore, sophisticated cooling designs for gas turbine parts aim to minimize coolant mass flow. New design space is accessible as additive manufacturing is maturing to industrial usage for the creation of hot gas flow path parts. By making use of this technology more efficient cooling schemes can be manufacture. In order to find such cooling schemes a generative design method is being developed. It generates cooling schemes randomly which adhere to a set of rules. These assure the sanity of the design. A huge amount of different cooling schemes are generated and implemented in a simulation environment where it is validated. Criteria for the fitness of the cooling schemes are coolant mass flow, maximum temperature and temperature gradients. This way the whole design space is sampled and a Pareto optimum front can be identified. This approach is applied to a flat plate, which resembles a simplified section of a hot gas flow path part. Realistic boundary conditions are applied and thermal barrier coating is accounted for in the simulation environment. The resulting cooling schemes are presented and compared to representative conventional cooling schemes. Further development of this method can give access to cooling schemes with an even better performance having higher complexity, which makes use of the available design space.

Keywords: additive manufacturing, cooling, gas turbine, heat transfer, heat transfer design, optimization

Procedia PDF Downloads 352

Authors: Mazyar Yosofi, Olivier Kerbrat, Pascal Mognol

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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

Authors: Kiran Nawaz, Waheed Anwar, Sehrish Iftikhar, Muhammad Nasir Subhani, Ahmad Ali Shahid

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Plant growth promoting rhizobacteria (PGPR) have been extensively studied and applied for the biocontrol of many soilborne diseases. These rhizobacteria are very efficient against root rot and many other foliar diseases associated with solanaceous plants. These bacteria may inhibit the growth of various pathogens through direct inhibition of target pathogens or indirectly by the initiation of systemic resistance (ISR) which is active all over the complete plant. In the present study, 20 different rhizobacterial isolates were recovered from the root zone of healthy chili plants. All soil samples were collected from various chili-growing areas in Punjab. All isolated rhizobacteria species were evaluated in vitro and in vivo against Phytophthora capsici. Different species of Bacillus and Pseudomonas were tested for the antifungal activity against P. capsici the causal organism of Root rot disease in different crops together with chili. Dual culture and distance culture bioassay were carried out to study the antifungal potential of volatile and diffusible metabolites secreted from rhizobacteria. After seven days of incubation at 22°C, growth inhibition rate was recorded. Growth inhibition rate depended greatly on the tested bacteria and screening methods used. For diffusible metabolites, inhibition rate was 35-62% and 20-45% for volatile metabolites. The screening assay for plant growth promoting and disease inhibition potential of chili associated PGPR indicated 42-100% reduction in disease severity and considerable enhancement in roots fresh weight by 55-87%, aerial parts fresh weight by 35-65% and plant height by 65-76% as compared to untreated control and pathogen-inoculated plants. Pseudomonas flourescene, B. thuringiensis, and B. subtilis were found to be the most efficient isolates in inhibiting P. capsici radial growth, increase plant growth and suppress disease severity.

Keywords: rhizobacteria, chili, phytophthora, root rot

Procedia PDF Downloads 263

Authors: Sirine Sayed, Mostapha Tarfaoui, Abdelmalek Toumi, Youssef Qarssis, Mohamed Daly, Chokri Bouraoui

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This paper delves into the combination of additive manufacturing (AM) and artificial intelligence (AI) to solve challenges related to the mechanical behavior of AM-produced parts. The article highlights the fundamentals and benefits of additive manufacturing, including creating complex geometries, optimizing material use, and streamlining manufacturing processes. The paper also addresses the challenges associated with additive manufacturing, such as ensuring stable mechanical performance and material properties. The role of AI in improving the static behavior of AM-produced parts, including machine learning, especially the neural network, is to make regression models to analyze the large amounts of data generated during experimental tests. It investigates the potential synergies between AM and AI to achieve enhanced functions and personalized mechanical properties. The mechanical behavior of parts produced using additive manufacturing methods can be further improved using design optimization, structural analysis, and AI-based adaptive manufacturing. The article concludes by emphasizing the importance of integrating AM and AI to enhance mechanical operations, increase reliability, and perform advanced functions, paving the way for innovative applications in different fields.

Keywords: additive manufacturing, mechanical behavior, artificial intelligence, machine learning, neural networks, reliability, advanced functionalities

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Authors: Andrew R. Willis, Kevin Brink, Kathleen Dipple

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This article describes a software package called ROS-georegistration intended for use with the robot operating system (ROS) and the Gazebo 3D simulation environment. ROSgeoregistration provides tools for the simulation, test, and deployment of aerial georegistration algorithms and is available at github.com/uncc-visionlab/rosgeoregistration. A model creation package is provided which downloads multi-spectral images from the Google Earth Engine database and, if necessary, incorporates these images into a single, possibly very large, reference image. Additionally a Gazebo plugin which uses the real-time sensor pose and image formation model to generate simulated imagery using the specified reference image is provided along with related plugins for UAV relevant data. The novelty of this work is threefold: (1) this is the first system to link the massive multi-spectral imaging database of Google’s Earth Engine to the Gazebo simulator, (2) this is the first example of a system that can simulate geospatially and radiometrically accurate imagery from multiple sensor views of the same terrain region, and (3) integration with other UAS tools creates a new holistic UAS simulation environment to support UAS system and subsystem development where real-world testing would generally be prohibitive. Sensed imagery and ground truth registration information is published to client applications which can receive imagery synchronously with telemetry from other payload sensors, e.g., IMU, GPS/GNSS, barometer, and windspeed sensor data. To highlight functionality, we demonstrate ROSgeoregistration for simulating Electro-Optical (EO) and Synthetic Aperture Radar (SAR) image sensors and an example use case for developing and evaluating image-based UAS position feedback, i.e., pose for image-based Guidance Navigation and Control (GNC) applications.

Keywords: EO-to-EO, EO-to-SAR, flight simulation, georegistration, image generation, robot operating system, vision-based navigation

Procedia PDF Downloads 104

Authors: Mathewos Temesgen, Lemi Geleta

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Lake Koka is one of the Ethiopian Central Rift Valleys lakes, where the absorbance of domestic, agricultural, and industrial waste from the nearby industrial and agro-industrial activities is very common. The aim of this research was to assess the heavy metal bioaccumulation in edible parts of common carp (Cyprinus carpio) in Lake Koka and the health risks associated with the dietary intake of the fish. Three sampling sites were selected randomly for primary data collection. Physicochemical parameters (pH, Total Dissolved Solids, Dissolved Oxygen and Electrical Conductivity) were measured in-situ. Four heavy metals (Cd, Cr, Pb, and Zn) in water and bio-accumulation in the edible parts of the fish were analyzed with flame atomic absorption spectrometry. The mean values of TDS, EC, DO and pH of the lake water were 458.1 mg/L, 905.7 µ s/cm, 7.36 mg/L, and 7.9, respectively. The mean concentrations of Zn, Cr, and Cd in the edible part of fish were also 0.18 mg/kg, ND-0.24 mg/kg, and ND-0.03 mg/kg, respectively. Pb was, however, not identified. The amount of Cr in the examined fish muscle was above the level set by FAO, and the accumulation of the metals showed marked differences between sampling sites (p<0.05). The concentrations of Cd, Pb and were below the maximum permissible limit. The results also indicated that Cr has a high transfer factor value and Zn has the lowest. The carcinogenic hazard ratio values were below the threshold value (<1) for the edible parts of fish. The estimated weekly intake of heavy metals from fish muscles ranked as Cr>Zn>Cd, but the values were lower than the Reference Dose limit for metals. The carcinogenic risk values indicated a low health risk due to the intake of individual metals from fish. Furthermore, the hazard index of the edible part of fish was less than unity. Generally, the water quality is not a risk for the survival and reproduction of fish, and the heavy metal contents in the edible parts of fish exhibited low carcinogenic risk through the food chain.

Keywords: bio-accumulation, cyprinus carpio, hazard index, heavy metals, Lake Koka

Procedia PDF Downloads 114

Authors: M. Zyczkowski, P. Markowski, M. Karol

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The team from IOE MUT is developing fiber optic sensors for the security systems for 15 years. The conclusions of the work indicate that these sensors are complicated. Moreover, these sensors are expensive to produce and require sophisticated signal processing methods.We present the results of the investigations of three different applications of the modalmetric sensor: • Protection of museum collections and heritage buildings, • Protection of fiber optic transmission lines, • Protection of objects of critical infrastructure. Each of the presented applications involves different requirements for the system. The results indicate that it is possible to developed a fiber optic sensor based on a single fiber. Modification of optoelectronic parts with a change of the length of the sensor and the method of reflections of propagating light at the end of the sensor allows to adjust the system to the specific application.

Keywords: modalmetric fiber optic sensor, security sensor, optoelectronic parts, signal processing

Procedia PDF Downloads 619

Authors: A. P. Mikhailovich, V. V. Fomin, E. M. Agapitov, V. E. Rogachev, E. A. Kostousova, E. S. Perekhodova

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Woody vegetation among the upper limit of its habitat is a sensitive indicator of biota reaction to regional climate changes. Quantitative assessment of temporal and spatial changes in the distribution of trees and plant biocenoses calls for the development of new modeling approaches based upon selected data from measurements on the ground level and ultra-resolution aerial photography. Statistical models were developed for the study area located in the Polar Urals. These models allow obtaining probabilistic estimates for placing Siberian Larch trees into one of the three age intervals, namely 1-10, 11-40 and over 40 years, based on the Weilbull distribution of the maximum horizontal crown projection. Authors developed the distribution map for larch trees with crown diameters exceeding twenty centimeters by deciphering aerial photographs made by a UAV from an altitude equal to fifty meters. The total number of larches was equal to 88608, forming the following distribution row across the abovementioned intervals: 16980, 51740, and 19889 trees. The results demonstrate that two processes can be observed in the course of recent decades: first is the intensive forestation of previously barren or lightly wooded fragments of the study area located within the patches of wood, woodlands, and sparse stand, and second, expansion into mountain tundra. The current expansion of the Siberian Larch in the region replaced the depopulation process that occurred in the course of the Little Ice Age from the late 13ᵗʰ to the end of the 20ᵗʰ century. Using data from field measurements of Siberian larch specimen biometric parameters (including height, diameter at root collar and at 1.3 meters, and maximum projection of the crown in two orthogonal directions) and data on tree ages obtained at nine circular test sites, authors developed a model for artificial neural network including two layers with three and two neurons, respectively. The model allows quantitative assessment of a specimen's age based on height and maximum crone projection values. Tree height and crown diameters can be quantitatively assessed using data from aerial photographs and lidar scans. The resulting model can be used to assess the age of all Siberian larch trees. The proposed approach, after validation, can be applied to assessing the age of other tree species growing near the upper tree boundaries in other mountainous regions. This research was collaboratively funded by the Russian Ministry for Science and Education (project No. FEUG-2023-0002) and Russian Science Foundation (project No. 24-24-00235) in the field of data modeling on the basis of artificial neural network.

Keywords: treeline, dynamic, climate, modeling

Procedia PDF Downloads 83

Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

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Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

Procedia PDF Downloads 126

Authors: Hossam M. Abdallah, Ali M. El-Halawany, Gamal A. Mohamed, Khalid Z. Alshali, Zainy M. Banjar, Hany A. El-Bassossy

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Hypertension and vascular dysfunction are major components and complications of many diseases like metabolic syndrome. In addition, vascular dysfunction is considered the initial step in diabetic atherosclerosis, the main etiology for mortality and a great percent of morbidity in diabetic patients. In spite of the significant developments in antidiabetic therapy, diabetic complications, particularly seen in long-term diabetes, continue to be seriously deleterious. Herbal drugs are prescribed widely in treatment of different aliment because of their effectiveness, fewer side effects and relatively low cost. Nine plants belong to five different families grown in Kingdom of Saudi Arabia were evaluated for their effect on exaggerated vasoconstriction and impaired relaxation in aortae isolated from metabolic syndrome rats. The aerial parts of Onopordum ambiguum Fresen. (OA), Astragalus abyssinicus Steud. (AA), Pulicaria Arabica Cass. (PA), Echinops sheilae Kit Tan (ES), Aizoon canariense L. (AC), Cleome viscosa L. (CV), Chrozophora oblongifolia (Delile) A.Juss. ex Spreng (CO), Centaurea pseudosinaica Mouterde (CP) and Tephrosia nubica Baker (TN) were dried and extracted with methanol. The effect of thirty minute incubation with the total extracts (10-330 µg/ml) or their fractions on the exaggerated vasoconstriction response to phenylephrine (10nM to 10microM) and impaired vasodilation to acetylcholine (10-330 µg /ml) of aortae isolated from metabolic syndrome animals was studied. Incubating aortae isolated from metabolic syndrome animals with total methanol extract of OA, AA, PA, AC, CV, and TN at concentrations (10-330 microgram/ml) in the organ bath led to concentration dependent alleviation of exaggerated vasoconstriction response to phenylephrine without having beneficial effect on impaired vasodilation to acetylcholine. In conclusion, addition of OA, AA, PA, AC, CV and TN to the standard therapies may provide superior means to alleviate the associated vascular complications.

Keywords: vascular dysfunction, exaggerated vasoconstriction, metabolic syndrome, Saudi plants

Procedia PDF Downloads 279

Authors: Barenten Suciu

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In this paper, effectiveness of a machine design process is evaluated on the basis of the specific output calculus. Concretely, a screw-worm gear mechanical transmission is designed by using the classical and the 3D-CAD methods. Strength analysis and drawing of the designed parts is substantially aided by employing the SolidWorks software. Quality of the design process is assessed by manufacturing (printing) the parts, and by computing the efficiency, specific load, as well as the specific output (work) of the mechanical transmission. Influence of the stroke, travelling velocity and load on the mechanical output, is emphasized. Optimal design of the mechanical transmission becomes possible by the appropriate usage of the acquired results.

Keywords: mechanical transmission, design, screw, worm-gear, efficiency, specific output, 3D-printing

Procedia PDF Downloads 143

Authors: Saeid Shahraki, Mohammad Mahdi Kaekha

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1030 steel, a kind of carbon steel used in homogenization, cold-forming, quenching, and tempering conditions, is generally utilized in small parts resisting medium stress, such as connection foundations, hydraulic cylinders, tiny gears, pins, clamps, automotive normal forging parts, camshafts, levers, pundits, and nuts. In this study, AC3 software was used to measure the effect of carbon and manganese percentage, dimensions and geometry of pieces, the type of the cooling fluid, temperature, and time on hardness and the content of 1030 steel phases. Next, the results are compared with the analytical values obtained from the Lumped Capacity Method.

Keywords: 1030Steel, AC3software, heat treatment, lumped capacity method

Procedia PDF Downloads 281

Authors: Shoeb Ahmed Adeel, Vivek Paul, K. Prajwal, Michael Fenelon

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Techniques have been used to tether and stabilize a multi-rotor MAV but carrying out the same process to a fixed wing MAV is a novel method which can be utilized in order to reduce damage occurring to the fixed wing MAVs while conducting flight test trials and PID tuning. A few sensors and on board controller is required to carry out this experiment in horizontal and vertical plane of the vehicle. Here we will be discussing issues such as sensitivity of the air vehicle, endurance and external load of the string acting on the vehicle.

Keywords: MAV, PID tuning, tethered flight, UAV

Procedia PDF Downloads 635

Authors: Chitra Rajagopal, Indra Deo Kumar, Ila Chauhan, Ruchi Joshi, Binoy Bhargavan

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Reliability and safety are essential for the success of mission-critical and safety-critical defense systems. Humans are part of the entire life cycle of defense systems development and deployment. The majority of industrial accidents or disasters are attributed to human errors. Therefore, considerations of human performance and human reliability are critical in all complex systems, including defense systems. Defense systems are operating from the ground, naval and aerial platforms in diverse conditions impose unique physical and psychological challenges to the human operators. Some of the safety and mission-critical defense systems with human-machine interactions are fighter planes, submarines, warships, combat vehicles, aerial and naval platforms based missiles, etc. Human roles and responsibilities are also going through a transition due to the infusion of artificial intelligence and cyber technologies. Human operators, not accustomed to such challenges, are more likely to commit errors, which may lead to accidents or loss events. In such a scenario, it is imperative to understand the human factors in defense systems for better systems performance, safety, and cost-effectiveness. A case study using Task Analysis (TA) based methodology for assessment and reduction of human errors in the Air and Missile Defense System in the context of emerging technologies were presented. Action-oriented task analysis techniques such as Hierarchical Task Analysis (HTA) and Operator Action Event Tree (OAET) along with Critical Action and Decision Event Tree (CADET) for cognitive task analysis was used. Human factors assessment based on the task analysis helps in realizing safe and reliable defense systems. These techniques helped in the identification of human errors during different phases of Air and Missile Defence operations, leading to meet the requirement of a safe, reliable and cost-effective mission.

Keywords: defence systems, reliability, risk, safety

Procedia PDF Downloads 135

Authors: Yannick Willemin

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Carbon fibre-reinforced plastic (CFRP) offers outstanding value. However, like all materials, CFRP also has its challenges. Many forming processes are largely manual and hard to automate, making it challenging to control repeatability and reproducibility (R&R); they generate significant scrap and are too slow for high-series production; fibre costs are relatively high and subject to supply and cost fluctuations; the supply chain is fragmented; many forms of CFRP are not recyclable, and many materials have yet to be fully characterized for accurate simulation; shelf life and outlife limitations add cost; continuous-fibre forms have design limitations; many materials are brittle; and small and/or thick parts are costly to produce and difficult to automate. A majority of small structural parts are metal due to high CFRP fabrication costs for the small-size class. The fact that CFRP manufacturing processes that produce the highest performance parts also tend to be the slowest and least automated is another reason CFRP parts are generally higher in cost than comparably performing metal parts, which are easier to produce. Fortunately, business is in the midst of a major manufacturing evolution—Industry 4.0— one technology seeing rapid growth is additive manufacturing/3D printing, thanks to new processes and materials, plus an ability to harness Industry 4.0 tools. No longer limited to just prototype parts, metal-additive technologies are used to produce tooling and mold components for high-volume manufacturing, and polymer-additive technologies can incorporate fibres to produce true composites and be used to produce end-use parts with high aesthetics, unmatched complexity, mass customization opportunities, and high mechanical performance. A new hybrid manufacturing process combines the best capabilities of additive—high complexity, low energy usage and waste, 100% traceability, faster to market—and post-consolidation—tight tolerances, high R&R, established materials, and supply chains—technologies. The platform was developed by Zürich-based 9T Labs AG and is called Additive Fusion Technology (AFT). It consists of a design software offering the possibility to determine optimal fibre layup, then exports files back to check predicted performance—plus two pieces of equipment: a 3d-printer—which lays up (near)-net-shape preforms using neat thermoplastic filaments and slit, roll-formed unidirectional carbon fibre-reinforced thermoplastic tapes—and a post-consolidation module—which consolidates then shapes preforms into final parts using a compact compression press fitted with a heating unit and matched metal molds. Matrices—currently including PEKK, PEEK, PA12, and PPS, although nearly any high-quality commercial thermoplastic tapes and filaments can be used—are matched between filaments and tapes to assure excellent bonding. Since thermoplastics are used exclusively, larger assemblies can be produced by bonding or welding together smaller components, and end-of-life parts can be recycled. By combining compression molding with 3D printing, higher part quality with very-low voids and excellent surface finish on A and B sides can be produced. Tight tolerances (min. section thickness=1.5mm, min. section height=0.6mm, min. fibre radius=1.5mm) with high R&R can be cost-competitively held in production volumes of 100 to 10,000 parts/year on a single set of machines.

Keywords: additive manufacturing, composites, thermoplastic, hybrid manufacturing

Procedia PDF Downloads 96

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

Procedia PDF Downloads 155

Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Ashwini Kumar, Vinod Nayak, Shankar M. Bakkannavar

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The identification of humans is important in forensic investigations not only in living but also in dead, especially in cases of mass disorders. The procedure followed in dead known as post-mortem identification is a challenging task for the forensic pathologist. However, it is mandatory in terms of the law to fulfill the social norms. Many times, due to mutilation of body parts, the normal methods of identification using skeletal remains cannot be used in the process of identification. In such cases, the intact components of the skeletal remains or bony parts play an important role in identification. In these situations, digital forensics can come to our rescue. The authors hereby made a study for determination of sex based on nasal index by using (Big Bore 16 Slice) Multidetector Computed Tomography 2D Scans. The results are represented as a poster.

Keywords: sex determination, multidetector computed tomography, nasal index, digital forensic

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Authors: Hye Kyung Kim, Myung-Gyou Kim, Kang-Hyun Leem

Abstract:

It has been reported that deer antler extract has bone-strengthening activity and effectively used in bone diseases therapy. However, little is known about the cellular and molecular mechanism of this effect. The upper section, mid section, and base of the antler has been known to exhibit different biological properties. Present study investigated the effects of these three parts of deer antler extracts on bone formation and resorption. The effects of deer antler extracts (DH) on bone formation were determined by cell proliferation, alkaline phosphatase (ALP) activity, collagen synthesis, and mineralization in human osteoblastic MG-63 cells. The effect on bone resorption was determined by osteoclastogenesis from bone marrow-derived precursor cells driven by RANKL. Ethanol extracts of DH (50 ~ 100 µg/ml) dose-dependently increased cell proliferation, and upper part increased the cell proliferation by 118.4% while mid and base parts increased proliferation by 107.8% and 102.3%, respectively. ALP activity was significantly increased by upper part of the DH treatment. After enhancement of ALP activity, significant augmentation of collagen synthesis and calcification assessed by Sirus red and Alzarin red staining, respectively, was observed in upper part of the DH treatment. The effect of DH on bone resorption was not observed in all three parts of the DH. These results could provide a mechanistic explanation for the bone-strengthening effects of DH.

Keywords: alkaline phosphatase, collagen synthesis, deer antler, osteoblastic MG-63 cells

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Authors: M. A. Alhubail, A. I. Alateyah, D. Alenezi, B. Aldousiri

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In this study conformal cooling channel (CCC) was employed to dissipate heat of, Polypropylene (PP) parts injected into the Stereolithography (SLA) insert to form tensile and flexural test specimens. The direct metal laser sintering (DMLS) process was used to fabricate a mould with optimised CCC, while optimum parameters of injection moulding were obtained using Optimal-D. The obtained results show that optimisation of the cooling channel layout using a DMLS mould has significantly shortened cycle time without sacrificing the part’s mechanical properties. By applying conformal cooling channels, the cooling time phase was reduced by 20 seconds, and also defected parts were eliminated.

Keywords: optimum parameters, injection moulding, conformal cooling channels, cycle time

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Authors: Attila Vámosi, Tamás Mankovits, Dávid Huri, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. The shape optimization problem of rubber parts led to the study of FEM based calculation processes. This type of problems was posed and investigated by several authors. In this paper the time demand of certain calculation methods are studied and the possibilities of time reduction is presented.

Keywords: rubber bumper, data acquisition, finite element analysis, support vector regression

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Authors: Frederic Heymes, Michael Albrecht Birk, Roland Eyssette

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Boiling Liquid Expanding Vapor Explosion (BLEVE) has been a well know industrial accident for over 6 decades now, and yet it is still poorly predicted and avoided. BLEVE is created when a vessel containing a pressure liquefied gas (PLG) is engulfed in a fire until the tank rupture. At this time, the pressure drops suddenly, leading the liquid to be in a superheated state. The vapor expansion and the violent boiling of the liquid produce several shock waves. This works aimed at understanding the contribution of vapor ad liquid phases in the overpressure generation in the near field. An experimental work was undertaken at a small scale to reproduce realistic BLEVE explosions. Key parameters were controlled through the experiments, such as failure pressure, fluid mass in the vessel, and weakened length of the vessel. Thirty-four propane BLEVEs were then performed to collect data on scenarios similar to common industrial cases. The aerial overpressure was recorded all around the vessel, and also the internal pressure changed during the explosion and ground loading under the vessel. Several high-speed cameras were used to see the vessel explosion and the blast creation by shadowgraph. Results highlight how the pressure field is anisotropic around the cylindrical vessel and highlights a strong dependency between vapor content and maximum overpressure from the lead shock. The time chronology of events reveals that the vapor phase is the main contributor to the aerial overpressure peak. A prediction model is built upon this assumption. Secondary flow patterns are observed after the lead. A theory on how the second shock observed in experiments forms is exposed thanks to an analogy with numerical simulation. The phase change dynamics are also discussed thanks to a window in the vessel. Ground loading measurements are finally presented and discussed to give insight into the order of magnitude of the force.

Keywords: phase change, superheated state, explosion, vapor expansion, blast, shock wave, pressure liquefied gas

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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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Authors: Anochao Phetcharat

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This research aims to study problems of translation basic knowledge, particularly from English into Thai. The researcher used 38 2nd-year non-English speaking students of Suratthani Rajabhat University as samples. The samples were required to translate an A4-sized article from English into Thai assigned as a part of BEN0202 Translation for Business, a requirement subject for Business English Department, which was also taught by the researcher. After completion of the translation, numerous problems were found and the research grouped them into 4 major types. The normally occurred problems in English-Thai translation works are the lack of knowledge in terms of parts of speech, word-by-word translation employment, misspellings as well as the poor knowledge in English language structure. However, this research is currently under the process of data analysis and shall be completed by the beginning of August. The researcher, nevertheless, predicts that all the above-mentioned problems, will support the researcher’s hypothesizes, that are; 1) the lack of knowledge in terms of parts of speech causes the mistranslation problem; 2) employing word-by-word translation technique hugely results in the mistranslation problem; 3) misspellings yields the mistranslation problem; and 4) the poor knowledge in English language structure also brings about translation errors. The research also predicts that, of all the aforementioned problems, the following ones are found the most, respectively: the poor knowledge in English language structure, word-by-word translation employment, the lack of knowledge in terms of parts of speech, and misspellings.

Keywords: problem, student, Thai, translation

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Authors: Jigg Pelayo, Ricardo Villar

Abstract:

The Philippines is long considered as a valuable producer of high value crops globally. The country’s employment and economy have been dependent on agriculture, thus increasing its demand for the efficient agricultural mechanism. Remote sensing and geographic information technology have proven to effectively provide applications for precision agriculture through image-processing technique considering the development of the aerial scanning technology in the country. Accurate information concerning the spatial correlation within the field is very important for precision farming of high value crops, especially. The availability of height information and high spatial resolution images obtained from aerial scanning together with the development of new image analysis methods are offering relevant influence to precision agriculture techniques and applications. In this study, an algorithm was developed and implemented to detect and count high value crops simultaneously through adaptive scaling of support vector machine (SVM) algorithm subjected to object-oriented approach combining watershed transformation and local maxima filter in enhancing tree counting and detection. The methodology is compared to cutting-edge template matching algorithm procedures to demonstrate its effectiveness on a demanding tree is counting recognition and delineation problem. Since common data and image processing techniques are utilized, thus can be easily implemented in production processes to cover large agricultural areas. The algorithm is tested on high value crops like Palm, Mango and Coconut located in Misamis Oriental, Philippines - showing a good performance in particular for young adult and adult trees, significantly 90% above. The s inventories or database updating, allowing for the reduction of field work and manual interpretation tasks.

Keywords: high value crop, LiDAR, OBIA, precision agriculture

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

Abstract:

Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Nader Zirak, Mohammadali Shirinbayan, Abbas Tcharkhtchi

Abstract:

Additive manufacturing is referred to as a method for fabrication of parts with a mechanism of layer by layer. Suitable economic efficiency and the ability to fabrication complex parts have made this method the focus of studies and industry. In recent years many studies focused on the fabrication of impellers, which is referred to as a key component of turbomachinery, through this technique. This study considers the important effect of the final surface quality of the impeller on the performance of the system, investigates the fabricated printed rotors through the fused deposition modeling with different process parameters. In this regard, the surface of each impeller was analyzed through the 3D scanner. The results show the vital role of surface quality on the final performance of the centrifugal compressor.

Keywords: additive manufacturing, impeller, centrifugal compressor, performance

Procedia PDF Downloads 147