Search results for: mechanical modeling

Authors: Ferhat Kadioglu, Hasan Puskul

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A composite material with carbon fiber and polymer matrix has been used as adherent for manufacturing adhesive joints. In order to evaluate different fiber orientations on joint performance, the adherents with the 0°, ±15°, ±30°, ±45° fiber orientations were used in the single lap joint configuration. The joints with an overlap length of 25 mm were prepared according to the ASTM 1002 specifications and subjected to tensile loadings. The structural adhesive used was a two-part epoxy to be cured at 70°C for an hour. First, mechanical behaviors of the adherents were measured using three point bending test. In the test, considerations were given to stress to failure and elastic modulus. The results were compared with theoretical ones using rule of mixture. Then, the joints were manufactured in a specially prepared jig, after a proper surface preparation. Experimental results showed that the fiber orientations of the adherents affected the joint performance considerably; the joints with ±45° adherents experienced the worst shear strength, half of those with 0° adherents, and in general, there was a great relationship between the fiber orientations and failure mechanisms. Delamination problems were observed for many joints, which were thought to be due to peel effects at the ends of the overlap. It was proved that the surface preparation applied to the adherent surface was adequate. For further explanation of the results, a numerical work should be carried out using a possible non-linear analysis.

Keywords: composite materials, adhesive bonding, bonding strength, lap joint, tensile strength

Procedia PDF Downloads 355

Authors: Javier Sandoval Bustamante, Pardis Sheikhzadeh, Vijayanarasimha Hindupur Pakka

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In the pursuit of achieving net-zero carbon emissions, the integration of low carbon technologies into electricity distribution networks is paramount. This paper delves into the critical assessment of how the integration of low carbon technologies, such as heat pumps, electric vehicle chargers, and photovoltaic systems, impacts the infrastructure and operation of electricity distribution networks. The study employs rigorous methodologies, including power flow analysis and headroom analysis, to evaluate the feasibility and implications of integrating these technologies into existing distribution systems. Furthermore, the research utilizes Local Area Energy Planning (LAEP) methodologies to guide local authorities and distribution network operators in formulating effective plans to meet regional and national decarbonization objectives. Geospatial analysis techniques, coupled with building physics and electric energy systems modeling, are employed to develop geographic datasets aimed at informing the deployment of low carbon technologies at the local level. Drawing upon insights from the Local Energy Net Zero Accelerator (LENZA) project, a comprehensive case study illustrates the practical application of these methodologies in assessing the rollout potential of LCTs. The findings not only shed light on the technical feasibility of integrating low carbon technologies but also provide valuable insights into the broader transition towards a sustainable and electrified energy future. This paper contributes to the advancement of knowledge in power electrical engineering by providing empirical evidence and methodologies to support the integration of low carbon technologies into electricity distribution networks. The insights gained are instrumental for policymakers, utility companies, and stakeholders involved in navigating the complex challenges of energy transition and achieving long-term sustainability goals.

Keywords: energy planning, energy systems, digital twins, power flow analysis, headroom analysis

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Dimitrios Karanatsis

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Non-crimp fabrics (NCFs) allow for high mechanical performance of a manufacture composite component by maintaining the fibre reinforcements parallel to each other. The handling of NCFs is enabled by the stitching of the tows. Although the stitching material has negligible influence to the performance of the manufactured part, it can affect the ability of the structural fabric to shear and drape over the part’s geometry. High resistance to shearing is attributed to the high tensile strain of the stitching yarn and can cause defects in the fabric. In the current study, a correlation based on the stitch tension and shear behaviour is examined. The purpose of the research is to investigate the upper and lower limits of non-crimp fabrics manufacture and how these affect the shear behaviour of the fabrics. Experimental observations show that shear behaviour of the fabrics is significantly affected by the stitch tension, and there is a linear effect to the degree of shear they experience. It was found that the lowest possible stitch tension on the manufacturing line settings produces an NCF that exhibits very low tensile strain on it’s yarns and that has shear properties similar to a woven fabric. Moreover, the highest allowable stitch tension results in reduced formability of the fabric, as the stitch thread rearranges the fibre filaments where these become packed in a tight formation with constricted movement.

Keywords: carbon fibres, composite manufacture, shear testing, textiles

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Authors: Yulin Zhang, Kaixi Dong, Guozhen Zhao

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Background: Different levels of life satisfaction are associated with some individual differences. Understanding the mechanism between them will help to enhance an individual’s well-being. On the one hand, traditional personality such as extraversion has been considered as the most stable and effective factor in predicting life satisfaction to the author’s best knowledge. On the other, individual emotional difference, such as alexithymia (difficulties identifying and describing one’s own feelings), is also closely related to life satisfaction. With the development of positive psychology, positive personalities such as virtues attract wide attention. And according to the broaden-and-build theory, social connectivity may mediate between emotion and life satisfaction. Therefore, the current study aims to explore the mediating role of social connectivity in the effect of positive personality and alexithymia on life satisfaction. Method: This study was conducted with 318 healthy Chinese college students whose age range from 18 to 30. Positive personality (including interpersonal, vitality, and cautiousness) was measured by the Chinese version of Values in Action Inventory of Strengths (VIA-IS). Alexithymia was measured by the Toronto Alexithymia Scale (TAS), and life satisfaction was measured by Satisfaction With Life Scale (SWLS). And social connectivity was measured by six items which have been used in previous studies. Each scale showed high reliability and validity. The mediating model was examined in Mplus 7.2 within a structural equation modeling (SEM) framework. Findings: The model fitted well and results revealed that both positive personality (95% confidence interval of indirect effect was [0.023, 0.097]) and alexithymia (95% confidence interval of indirect effect was [-0.270, -0.089]) predicted life satisfaction level significantly through social connectivity. Also, only positive personality significantly and directly predicted life satisfaction compared to alexithymia (95% confidence interval of direct effect was [0.109, 0.260]). Conclusion: Alexithymia predicts life satisfaction only through social connectivity, which emphasizes the importance of social bonding in enhancing the well-being of Chinese college students with alexithymia. And the positive personality can predict life satisfaction directly or through social connectivity, which provides implications for enhancing the well-being of Chinese college students by cultivating their virtue and positive psychological quality.

Keywords: alexithymia, life satisfaction, positive personality, social connectivity

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Authors: İsmail İnce, Ali Bozdag, Ayla Bozdag, M. Bahadır Tosunlar, M. Ergun Hatır, Mustafa Korkanc

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The building stones used in the construction of historical structures are exposed to atmospheric effects directly or indirectly. As a result of this process, building stones are partially or completely degraded. Historical buildings are important symbols of cultural heritage, so it is very significant to transfer to the future generations by protecting and repairing of these historical buildings. The Eflatunpınar Hitit Monument located near the Eflatunpınar cold water spring was constructed by using natural rock blocks during the Hittites Empire period. The monument has been protected without losing its function until today. The purpose of this study is to evaluate the deteriorations in the Eflatunpınar Hitit Monument and to detect the water chemistry of the Eflatunpınar spring located around the Beysehir County in the west of Konya. For this purpose, the petrographic and mechanical properties of the rocks used in this monument were determined, and the deteriorations in the monument were determined with the aid of non-destructive test methods including Schmidt hardness value, relative humidity measurement, thermal imaging. Additionally, the physical (electrical conductivity (EC), pH and temperature) and chemical characteristics (major anions and cations) of the Eflatunpınar cold water spring have been detected.

Keywords: deteriorations, Eflatunpınar Hitit monument, Eflatunpınar spring, Konya, non-destructıve tests

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Authors: Farrokh Taherkhani, Thomas Pinger, Max Gündel

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The total economic damage caused by corrosion in Germany is estimated to be more than 3% of the GDP per year. Additionally, corrosion and suitable corrosion protection systems are also significant factors in the consideration of life cycle costs for steel hydraulic structures. In addition to classic coating systems (for example, epoxy resin or polyurethane), zinc and its alloys offer effective and very durable corrosion protection for steels. As a protective layer, hot-dip galvanizing prevents the corrosive media from penetrating into the steel matrix and acts as a sacrificial anode, which corrodes in preference to the steel. However, hot-dip galvanizing as a corrosion protection system has not yet been approved by the relevant authority, the Federal Waterways Engineering and Research Institute (BAW) in Germany. In order to make hot-dip galvanizing usable as a corrosion protection system for steel hydraulic structures in the future, different factors must be considered. These factors are (i) corrosion protection type, (ii) resistance to mechanical stress (i.e., abrasion resistance), (iii) combinability with cathodic corrosion protection, (iv) environmental effects and (v) the crack formation and propagation during hot-dip galvanizing. In this work, hot-dip galvanizing as a corrosion protection system for steel hydraulic steel structures, as well as open questions, are discussed. This paper is based on initial long-term exposure tests with corrosion protection systems consisting of hot-dip galvanizing and duplex systems.

Keywords: steel hydraulic structure, hot-dip galvanizing, corrosion, corrosion resistance, zinc coating, organic coating, duplex sytems

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Authors: Hisashi Imai, Kuan-Yu Chen, Katsuyoshi Kondoh, Hung-Yin Tsai, Junko Umeda

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Microstructural and electrical properties of copper-chromium alloy (Cu-Cr) dispersed with vapor-grown carbon fiber (VGCF) prepared by powder metallurgy (P/M) process have been investigated. Cu-0.7 mass% Cr pre-alloyed powder (Cu-Cr) made by water atomization process was used as raw materials, which contained solid solute Cr elements in Cu matrix. The alloy powder coated with un-bundled VGCF by using oil coating process was consolidated at 1223 K in vacuum by spark plasma sintering, and then extruded at 1073 K. The extruded Cu-Cr alloy (monolithic alloy) had 209.3 MPa YS and 80.4 IACS% conductivity. The extruded Cu-Cr with 0.1 mass% VGCF composites revealed a small decrease of YS compared to the monolithic Cu-Cr alloy. On the other hand, the composite had a higher electrical conductivity than that of the monolithic alloy. For example, Cu-Cr with 0.1 mass% VGCF composite sintered for 5 h showed 182.7 MPa YS and 89.7 IACS% conductivity. In the case of Cu-Cr with VGCFs composites, the Cr concentration was observed around VGCF by SEM-EDS analysis, where Cr23C6 compounds were detected by TEM observation. The amount of Cr solid solution in the matrix of the Cu-Cr composites alloy was about 50% compared to the monolithic Cu-Cr sintered alloy, and resulted in the remarkable increment of the electrical conductivity.

Keywords: powder metallurgy Cu-Cr alloy powder, vapor-grown carbon fiber, electrical conductivity

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Authors: Z. Ezzouine, A. Nakheli

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This paper presents a high position electromagnetic sensor system (HPESS) that is applicable for moving object detection. The authors have developed a high-performance position sensor prototype dedicated to students’ laboratory. The challenge was to obtain a highly accurate and real-time sensor that is able to calculate position, length or displacement. An electromagnetic solution based on a two coil induction principal was adopted. The HPESS converts mechanical motion to electric energy with direct contact. The output signal can then be fed to an electronic circuit. The voltage output change from the sensor is captured by data acquisition system using LabVIEW software. The displacement of the moving object is determined. The measured data are transmitted to a PC in real-time via a DAQ (NI USB -6281). This paper also describes the data acquisition analysis and the conditioning card developed specially for sensor signal monitoring. The data is then recorded and viewed using a user interface written using National Instrument LabVIEW software. On-line displays of time and voltage of the sensor signal provide a user-friendly data acquisition interface. The sensor provides an uncomplicated, accurate, reliable, inexpensive transducer for highly sophisticated control systems.

Keywords: electromagnetic sensor, accurately, data acquisition, position measurement

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Authors: Seon Ho Kim, Minho Bang, Seok Min Choi, Young Moon Lee, Dong Kwan Kim, Hyung Hee Cho

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Gas turbines are heat engines that convert chemical energy into electrical energy through mechanical energy. Since their high energy density per unit volume and low pollutant emissions, gas turbines are classified as clean energy. In order to obtain better performance, the turbine inlet temperature of the current gas turbine is operated at about 1600℃, and thermal damage is a very serious problem. Especially, these thermal damages are more prominent in off-design conditions than in design conditions. In this study, the thermal damage characteristics of high temperature components of a gas turbine made of a single crystal material are studied numerically for the off-design operating conditions. The target gas turbine is configured as a reheat cycle and is operated in peak load operation mode, not normal operation. In particular, the target gas turbine features a lot of low-load operation. In this study, a commercial code, ANSYS 18.2, was used for analyzing the thermal-flow coupling problems. As a result, the flow separation phenomenon on the pressure side due to the flow reduction was remarkable at the off-design condition, and the high heat transfer coefficient at the upper end of the suction surface due to the tip leakage flow was appeared.

Keywords: gas turbine, single crystal blade, off-design, thermal analysis

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Authors: Nilanjana Chanda, Rangeet Bhattacharyya

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Grover’s search algorithm is the fastest possible quantum mechanical algorithm to search a certain element from an unstructured set of data of N items. The algorithm can determine the desired result in only O(√N) steps. It has been demonstrated theoretically and experimentally on two-qubit systems long ago. In this work, we investigate the fidelity of Grover’s search algorithm by implementing it on an open quantum system. In particular, we study with what accuracy one can estimate that the algorithm would deliver the searched state. In reality, every system has some influence on its environment. We include the environmental effects on the system dynamics by using a recently reported fluctuation-regulated quantum master equation (FRQME). We consider that the environment experiences thermal fluctuations, which leave its signature in the second-order term of the master equation through its appearance as a regulator. The FRQME indicates that in addition to the regular relaxation due to system-environment coupling, the applied drive also causes dissipation in the system dynamics. As a result, the fidelity is found to depend on both the drive-induced dissipative terms and the relaxation terms, and we find that there exists a competition between them, leading to an optimum drive amplitude for which the fidelity becomes maximum. For efficient implementation of the search algorithm, precise knowledge of this optimum drive amplitude is essential.

Keywords: dissipation, fidelity, quantum master equation, relaxation, system-environment coupling

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Authors: Daniel Aberdam

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Haploinsufficiency of PAX6 in humans is the main cause of congenital aniridia, a rare eye disease characterized by reduced visual acuity. Patients have also progressive disorders including cataract, glaucoma and corneal abnormalities making their condition very challenging to manage. Aniridia-related keratopathy (ARK), caused by a combination of factors including limbal stem-cell deficiency, impaired healing response, abnormal differentiation, and infiltration of conjunctival cells onto the corneal surface, affects up to 95% of patients. It usually begins in the first decade of life resulting in recurrent corneal erosions, sub-epithelial fibrosis with corneal decompensation and opacification. Unfortunately, current treatment options for aniridia patients are currently limited. Although animal models partially recapitulate this disease, there is no in vitro cellular model of AKT needed for drug/therapeutic tools screening and validation. We used genome editing (CRISPR/Cas9 technology) to introduce a nonsense mutation found in patients into one allele of the PAX6 gene into limbal stem cells. Resulting mutated clones, expressing half of the amount of PAX6 protein and thus representative of haploinsufficiency were further characterized. Sequencing analysis showed that no off-target mutations were induced. The mutated cells displayed reduced cell proliferation and cell migration but enhanced cell adhesion. Known PAX6 targets expression was also reduced. Remarkably, addition of soluble recombinant PAX6 protein into the culture medium was sufficient to activate endogenous PAX6 gene and, as a consequence, rescue the phenotype. It strongly suggests that our in vitro model recapitulates well the epithelial defect and becomes a powerful tool to identify drugs that could rescue the corneal defect in patients. Furthermore, we demonstrate that the homeotic transcription factor Pax6 is able to be uptake naturally by recipient cells to function into the nucleus.

Keywords: Pax6, crispr/cas9, limbal stem cells, aniridia, gene therapy

Procedia PDF Downloads 190

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Ayman Othman, Tallat Abd el Wahed

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The current research is directed towards studying the creep compliance characteristics of asphalt concrete mixtures modified with cement dust. This study can aid in assessing the permanent deformation potential of asphalt concrete mixtures. Cement dust was added to the mixture as mineral filler and compared with regular lime stone filler. A power law model was used to characterize the creep compliance behavior of the studied mixtures. Creep testing results have revealed that the creep compliance power law parameters have a strong relationship with mixture type. Testing results of the studied mixtures, as indicated by the creep compliance parameters revealed an enhancement in the creep resistance, Marshall stability, indirect tensile strength and compressive strength for cement dust mixtures as compared to mixtures with traditional lime stone filler. It is concluded that cement dust can be successfully used to decrease the potential of asphalt concrete mixture to permanent deformation and improve its mechanical properties. This is in addition to the environmental benefits that can be gained when using cement dust in asphalt paving technology.

Keywords: cement dust, asphalt concrete mixtures, creep compliance, Marshall stability, indirect tensile strength, compressive strength

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Authors: Jonmichael Weaver, David Miller

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Dyneema is an ultra-high molecular weight polyethylene (UHMWPE) fiber created by DSM. This fiber has many applications due to the high tensile strength, low weight, and inability to absorb water. DSM manufactures a non-woven unidirectional cross-ply [0,90]2 lamina, using the Dyneema fiber. Using this lamina system, various thickness panels are created for a 40% lighter weight alternative to Kevlar for the same ballistics protection. Environmental effects on the ply/laminate system alter the material properties, resulting in diminished ultimate performance. Understanding the specific environmental parameters and characterizing the resulting material property degradation is essential for determining the safety and reliability of Dyneema in service. Two laminas were contrasted for their response to accelerated aging by UV, humidity, and temperature cycling. Both lamina contain the same fiber, SK-99, but differ in matrix composition, Dyneema HB-210 employs a polyurethane (PUR) based matrix, and HB-212 contains a rubber-based matrix. Each system was inspected using a scanning electron microscope (SEM) and evaluated by dynamic mechanical analysis (DMA) to characterize the material property changes alongside the corresponding composite damage and matrix failure mode over the aging parameters. Overall, resulting in the HB-212 degrading faster compared with the HB-210.

Keywords: dyneema, accelerated aging, polymers, ballistics protection, armor, DSM, kevlar, composites

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Authors: Mehdi Modabberifar, Sanaz Jabary, Mojtaba Ghodsi

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Stiffness sensing is an important issue in medical diagnostic, robotics surgery, safe handling, and safe grasping of objects in production lines. Detecting and obtaining the characteristics in dwelling lumps embedded in a soft tissue and safe removing and handling of detected lumps is needed in surgery. Also in industry, grasping and handling an object without damaging in a place where it is not possible to access a human operator is very important. In this paper, a method for object handling is presented. It is based on the use of an intelligent gripper to detect the object stiffness and then setting a programmable force for grasping the object to move it. The main components of this system includes sensors (sensors for measuring force and displacement), electrical (electrical and electronic circuits, tactile data processing and force control system), mechanical (gripper mechanism and driving system for the gripper) and the display unit. The system uses a rotary potentiometer for measuring gripper displacement. A microcontroller using the feedback received by the load cell, mounted on the finger of the gripper, calculates the amount of stiffness, and then commands the gripper motor to apply a certain force on the object. Results of Experiments on some samples with different stiffness show that the gripper works successfully. The gripper can be used in haptic interfaces or robotic systems used for object handling.

Keywords: gripper, haptic, stiffness, robotic

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Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

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The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

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Authors: Hyun KI Kang, Hi Won Jeong

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The gas turbine operates for a long period of time under harsh, cyclic conditions of high temperature and pressure, where high turbine inlet temperature (TIT) can range from 1273 to 1873K. Therefore, Ni-base superalloys such as IN738, IN939, Rene 45, Rene 71, Rene 80, Mar M 247, CM 247, and CMSX-4 with excellent mechanical properties and resistance to creep, corrosion and oxidation at high temperatures are indeed used. Among the alloying additions for these alloys, aluminum (Al) and titanium (Ti) form gamma prime and enhance the high-temperature properties. However, when crack-damaged high-temperature turbine components such as blade and vane are repaired by fusion welding, they cause cracks. For example, when arc welding is applied to certain superalloys that contain Al and Ti with more than 3 wt.% and T3.5 wt%, respectively, such as IN738, IN939, Rene 80, Mar M 247, and CM 247, aging cracks occur. Therefore, repair technologies using diffusion brazing, which has less heat input into the base material, are being developed. Analysis of microstructural evolution of the brazed joints with a base metal of IN 939 Ni-base superalloy using brazing different filler metals was also carried out using X-ray diffraction, OEM, SEM-EDS, and EPMA. Stress rupture and high-temperature tensile strength properties were also measured to analyze the effects of different brazing heat cycles. The boron amount in the diffusion-affected zone (DAZ) was decreased towards the base metal and the formation of borides at grain boundaries was detected through EPMA.

Keywords: gas turbine, diffusion brazing, superalloy, gas turbine repair

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Authors: K. P. v. R. de Silva, R. W. Senevirathna, M. M. A. J. Kumara, J. P. M. Kumarasinghe, R. L. Gunawardana, S. M. Uluwitiya, G. C. P. Jayawickrama, W. K. T. I. Madushani

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Introduction: The limited literature supporting the utilization of mechanical bowel preparation (MBP) for patients undergoing laparoscopic anterior resection (LAR) remains a notable issue. This study was conducted to examine the clinical consequences of anastomosis in colorectal surgery with MBP compared to cases where MBP was not utilized (no-MBP) in the context of LAR. Methods: This was a retrospective comparative study conducted in the professorial surgical wards of the teaching hospital karapitiya (THK). Colorectal cancer patients(n=306) participated in the study, including 151 MBP patients and 155 no-MBP patients, where the postoperative complications and mortality rates were compared. Results: The anastomotic leakage rate was 2.6%(n=4) in the no-MBP group and 6.0%(n=9) in the MBP group (p=0.143). The postoperative paralytic ileus rate was 18.5%(n=28) and 5.8%(n=9) in the MBP group and no-MBP group, respectively, displaying a statistically significant difference (p=0.001). Wound infection, pneumonia, urinary tract infection, and cardiac complication rates also were higher in the MBP group. The overall mortality rate was 1.3%(n=3) in the no-MBP group and 2.0%(n=2) in the MBP group. Conclusions: The evidence concludes that MBP increases post-operative complications. Therefore, prophylactic MBP in LAR has not been proven to benefit patients. However, further research is necessary to understand the comparative effects of MBP versus no preparation comprehensively.

Keywords: MBP, anastomosis, LAR, paralytic ileus

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Alok Srivastava, Vidit Gupta, Aparna Singh, Chandra Sekher Yerramalli

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Carbon-fiber epoxy composites show extremely high modulus and strength in the uniaxial direction. However, they are prone to fail under low load in transverse direction due to the weak nature of the interface between the carbon-fiber and epoxy. In the current study, we have coated graphene nano-platelets (GNPs) on the carbon-fibers in an attempt to strengthen the interface/interphase between the fiber and the matrix. Vacuum Assisted Resin Transfer Moulding (VARTM) has been used to make the laminates of eight cross-woven fabrics. Tensile, flexural and fracture toughness tests have been performed on pristine carbon-fiber composite (P-CF), GNP coated carbon-fiber composite (GNP-CF) and functionalized-GNP coated carbon-fiber composite (F-GNP-CF). The tensile strength and flexural strength values are pretty similar for P-CF and GNP-CF. The micro-structural examination of the GNP coated carbon-fibers, as well as the fracture surfaces, have been carried out using scanning electron microscopy (SEM). The micrographs reveal the deposition of GNPs onto the carbon fibers in transverse and longitudinal direction. Fracture surfaces show the debonding and pull outs of the carbon fibers in P-CF and GNP-CF samples.

Keywords: carbon fiber, graphene nanoplatelets, strength, VARTM, Vacuum Assisted Resin Transfer Moulding

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Authors: Farnaz Sadeghi, Moslem Tavakol

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In this study, an attempt has been made to prepare a physically cross-linked gel by cooling of tannic acid (TA)-polyvinyl alcohol (PVA) solution that subsequently convert to antibacterial chemically cross-linked hydrogel by using electron beam irradiation. PVA is known for its biocompatibility and hydrophilicity, and TA is known for being a natural compound which can serve as a cross-linking agent and a therapeutic agent. Swelling behavior, gel content, pore size, and mechanical properties of hydrogels which prepared at 14, 28, and 56 (kGy) with different ratios of polymers were investigated. PVA-TA hydrogel showed sustained release of tannic acid as approximately 20% and 50% of loaded TA released from the hydrogel after 4 and 72 h release time. We found that gel content decreased and the moisture retention capability increased by an increase in TA composition. In addition, PVA-TA hydrogels showed a good antibacterial activity against S.aureus. MTT analysis indicated that close to 83% of fibroblast cells remained viable after 48 h exposure to hydrogel extract. Moreover, the cooling of 10% PVA solution containing 0.5 and 0.75% w/v tannic acid to room and refrigerator, respectively, led to formation of physical gel that did not present any flow index after inversion of hydrogel cast. According to the results, the hydrogel prepared by electron beam irradiation of blended PVA-TA solution could be further investigated as a promising candidate for wound healing.

Keywords: poly vinyl alcohol, tannic acid, electron beam irradiation, hydrogel wound dressing

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Authors: Duc V. Nguyen

Abstract:

Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

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Authors: Peter Jean-Paul, Shanaz Wahid

Abstract:

The problem of division by zero can be stated as: “what is the value of 0 x 1/0?” This expression has been considered undefined by mathematicians because it can have two equally valid solutions either 0 or 1. Recently semi-structured complex number set was invented to solve “division by zero”. However, whilst the number set had some merits it was considered to have a poor theoretical foundation and did not provide a quality solution to “division by zero”. Moreover, the set lacked consistency in simple algebraic calculations producing contradictory results when dividing by zero. To overcome these issues this research starts by treating the expression " 0 x 1/0" as a quantum mechanical system that produces two tangled results 0 and 1. Dirac Notation (a tool from quantum mechanics) was then used to redefine the unstructured unit p in semi-structured complex numbers so that p represents the superposition of two results (0 and 1) and collapses into a single value when used in algebraic expressions. In the process, this paper describes a new number set called Quantum Semi-structured Complex Numbers that provides a valid solution to the problem of “division by zero”. This research shows that this new set (1) forms a “Field”, (2) can produce consistent results when solving division by zero problems, (3) can be used to accurately describe systems whose mathematical descriptions involve division by zero. This research served to provide a firm foundation for Quantum Semi-structured Complex Numbers and support their practical use.

Keywords: division by zero, semi-structured complex numbers, quantum mechanics, Hilbert space, Euclidean space

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Authors: Jalal Haghighat Monfared, Zahra Akbari

Abstract:

Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: business intelligence, business intelligence capability, decision making, decision quality

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Authors: Kwabena A. Boakye, Eugene Atiemo, Trinity A. Tagbor, Delali Adjei

Abstract:

The use of mineral admixtures such as metakaolin, GGBS, fly ash, etc., in concrete is a common practice in the world. However, the only admixture available for use in the Ghanaian construction industry is calcined clay pozzolan. This research, therefore, studies the alternate use of granite dust, a by-product from stone quarrying, as a mineral admixture in concrete. Granite dust, which is usually damped as waste or as an erosion control material, was collected and pulverized to about 75µm. Some physical, chemical, and mineralogical tests were conducted on the granite dust. 5%-25% ordinary Portland cement of Class 42.5N was replaced with granite dust which was used as the main binder in the preparation of 150mm×150mm×150mm concrete cubes according to methods prescribed by BS EN 12390-2:2000. Properties such as workability, compressive strength, flexural strength, water absorption, and durability were determined. Compressive and flexural strength results indicate that granite dust could be used to replace ordinary Portland cement up to an optimum of 15% to achieve C25. Water permeability increased as the granite dust admixture content increased from 5% - 25%. Durability studies after 90 days proved that even though strength decreased as granite dust content increased, the concrete containing granite dust had better resistance to sulphate attack comparable to the reference cement. Pulverized granite can be used to partially replace ordinary Portland cement in concrete.

Keywords: admixture, granite dust, permeability, pozzolans

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Authors: Mohammad-Ali Latifi, Harry Bouwman

Abstract:

Changes in the business environment accelerated dramatically over the last decades as a result of changes in technology, regulation, market, and competitors’ behavior. Firms need to change the way they do business in order to survive or maintain their growth. Innovating business model (BM) can create competitive advantages and enhance firm performance. However, many companies fail to achieve expected outcomes in practice, mostly due to irreversible fundamental changes in key components of the company’s BM. This leads to more ambiguity, uncertainty, and risks associated with business performance. However, the relationship among BM Innovation, moderating factors, and the firm’s overall performance is by and large ignored in the current literature. In this study, we identified twenty moderating factors from our comprehensive literature review. We categorized these factors based on two criteria regarding the extent to which: the moderating factors can be controlled and managed by firms, and they are generic or specific changes to the firms. This leads to four moderation groups. The first group is BM implementation, which includes management support, employees’ commitment, employees’ skills, communication, detailed plan. The second group is called BM practices, which consists of BM tooling, BM experimentation, the scope of change, speed of change, degree of novelty. The third group is Firm characteristics, including firm size, age, and ownership. The last group is called Industry characteristics, which considers the industry sector, competitive intensity, industry life cycle, environmental dynamism, high-tech vs. low-tech industry. Through collecting data from 508 European small and medium-sized enterprises (SMEs) and using the structural equation modeling technique, the developed moderation model was examined. Results revealed that all factors highlighted through these four groups moderate the relation between BMI and firm performance significantly. Particularly, factors related to BM-Implementation and BM-Practices are more manageable and would potentially improve firm overall performance. We believe that this result is more important for researchers and practitioners since the possibility of working on factors in Firm characteristics and Industry characteristics groups are limited, and the firm can hardly control and manage them to improve the performance of BMI efforts.

Keywords: business model innovation, firm performance, implementation, moderation

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Authors: Sandip Suman

Abstract:

Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

Abstract:

Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

Abstract:

The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

Procedia PDF Downloads 182