Search results for: energy efficient building

Authors: Lukas Vierus, Thomas Schuster

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A general framework is examined for dynamic tensor field tomography within an inhomogeneous medium characterized by refraction and absorption, treated as an inverse source problem concerning the associated transport equation. Guided by Fermat’s principle, the Riemannian metric within the specified domain is determined by the medium's refractive index. While considerable literature exists on the inverse problem of reconstructing a tensor field from its longitudinal ray transform within a static Euclidean environment, limited inversion formulas and algorithms are available for general Riemannian metrics and time-varying tensor fields. It is established that tensor field tomography, akin to an inverse source problem for a transport equation, persists in dynamic scenarios. Framing dynamic tensor tomography as an inverse source problem embodies a comprehensive perspective within this domain. Ensuring well-defined forward mappings necessitates establishing existence and uniqueness for the underlying transport equations. However, the bilinear forms of the associated weak formulations fail to meet the coercivity condition. Consequently, recourse to viscosity solutions is taken, demonstrating their unique existence within suitable Sobolev spaces (in the static case) and Sobolev-Bochner spaces (in the dynamic case), under a specific assumption restricting variations in the refractive index. Notably, the adjoint problem can also be reformulated as a transport equation, with analogous results regarding uniqueness. Analytical solutions are expressed as integrals over geodesics, facilitating more efficient evaluation of forward and adjoint operators compared to solving partial differential equations. Certainly, here's the revised sentence in English: Numerical experiments are conducted using a Nesterov-accelerated Landweber method, encompassing various fields, absorption coefficients, and refractive indices, thereby illustrating the enhanced reconstruction achieved through this holistic modeling approach.

Keywords: attenuated refractive dynamic ray transform of tensor fields, geodesics, transport equation, viscosity solutions

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Authors: Shreya Poddar

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Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

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Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

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Authors: Maria A. Castillo H., Andrés R. Leandro C.

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During the last decades, agricultural productivity in Latin America has increased with precision agriculture and more efficient agricultural technologies. The use of automated systems, satellite images, geographic information systems, and tools for data analysis, and artificial intelligence have contributed to making more effective strategic decisions. Twenty years ago, the state of Mérida, located in the Venezuelan Andes, reported the largest area covered by greenhouses in the country, where certified seeds of potatoes, vegetables, ornamentals, and flowers were produced for export and consumption in the central region of the country. In recent years, it is estimated that production under greenhouses has changed, and the area covered has decreased due to different factors, but there are few historical statistical data in sufficient quantity and quality to support this estimate or to be used for analysis and decision making. The objective of this study is to compare data collected about geoposition, use, and covered areas of the greenhouses in 2007 to data available in 2021, as support for the analysis of the current situation of horticultural production in the main municipalities of the state of Mérida. The document presents the development of the work in the diagnosis and integration of geographic coordinates in GIS and data analysis phases. As a result, an evaluation of the process is made, a dashboard is presented with the most relevant data along with the geographical coordinates integrated into GIS, and an analysis of the obtained information is made. Finally, some recommendations for actions are added, and works that expand the information obtained and its geographical traceability over time are proposed. This study contributes to granting greater certainty in the supporting data for the evaluation of social, environmental, and economic sustainability indicators and to make better decisions according to the sustainable development goals in the area under review. At the same time, the methodology provides improvements to the agricultural data collection process that can be extended to other study areas and crops.

Keywords: greenhouses, geographic information system, protected agriculture, data analysis, Venezuela

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Authors: Jonas Sanon

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The valorization of research is becoming a transversal instrument linking different sectors (academic, public and industrial). The practice of valorization seems to impact innovation techniques within companies where, there is often the implementation of industrial conventions of training through research (CIFRE), continuous training programs for employees, collaborations and partnerships around joint research and R&D laboratories focused on the needs of companies to improve or develop more efficient innovations. Furthermore, many public initiatives to support innovation and technology transfer have been developed at the international, European and national levels, with significant budget allocations. Thus, in the context of this work, we tried to analyze the way in which research transfer structures are evaluated within the Saclay ecosystem. In fact, the University-Paris-Saclay is one of the best French universities; it is made up of 10 university components, more than 275 laboratories and is in partnership with the largest French research centers This work mainly focused on how evaluations affected research transfer structures, how evaluations were conducted, and what the managers of research transfer structures thought about assessments. Thus, with the aid of the conducted interviews, it appears that the evaluations do not have a significant impact on the qualitative aspect of research and innovation, but is rather present a directive aspect to allow the structures to benefit or not from the financial resources to develop certain research work, sometimes directed and influenced by the market, some researchers might try to accentuate their research and experimentation work on themes that are not necessarily their areas of interest, but just to comply with the calls for proposed thematic projects. The field studies also outline the primary indicators used to assess the effectiveness of valorization structures as "the number of start-ups generated, the license agreements signed, the structure's patent portfolio, and the innovations of items developed from public research.". Finally, after mapping the actors, it became clear that the ecosystem of the University of Paris-Saclay benefits from a richness allowing it to better value its research in relation to the three categories of actors it has (internal, external and transversal), united and linked by a relationship of proximity of sharing and endowed with a real opportunity to innovate openly.

Keywords: research valorization, technology transfer, innovation, evaluation, impacts and performances, innovation policy

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Authors: Imine Zakaria, Meftah Sidi Mohamed El Amine

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One of the most vital aerodynamic organs of a flying machine is the wing, which allows it to fly in the air efficiently. The flow around the wing is very sensitive to changes in the angle of attack. Beyond a value, there is a phenomenon of the boundary layer separation on the upper surface, which causes instability and total degradation of aerodynamic performance called a stall. However, controlling flow around an airfoil has become a researcher concern in the aeronautics field. There are two techniques for controlling flow around a wing to improve its aerodynamic performance: passive and active controls. Blowing and suction are among the active techniques that control the boundary layer separation around an airfoil. Their objective is to give energy to the air particles in the boundary layer separation zones and to create vortex structures that will homogenize the velocity near the wall and allow control. Blowing and suction have long been used as flow control actuators around obstacles. In 1904 Prandtl applied a permanent blowing to a cylinder to delay the boundary layer separation. In the present study, several numerical investigations have been developed to predict a turbulent flow around an aerodynamic profile. CFD code was used for several angles of attack in order to validate the present work with that of the literature in the case of a clean profile. The variation of the lift coefficient CL with the momentum coefficient

Keywords: CFD, control flow, lift, slot

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Authors: Vikas Chawla, Buta Singh Sidhu, Amita Rani, Amit Handa

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The main objective of the present work is microstructural and mechanical characterization of the conventional and nanostructured TiAlN and AlCrN coatings deposited on T-11 boiler steel. In case of conventional coatings, Al-Cr and Ti-Al metallic powders were deposited using plasma spray process followed by gas nitriding of the surface which was done in the lab with optimized parameters after conducting several trials on plasma-sprayed coated specimens. The physical vapor deposition process (PAPVD) was employed for depositing nanostructured TiAlN and AlCrN coatings. The field emission scanning electron microscopy (FE-SEM) with energy dispersive X-ray analysis (EDAX) attachment, X-ray diffraction (XRD) analysis, atomic force microscopy (AFM) analysis and the X-Ray mapping analysis techniques have been used to study surface and cross-sectional morphology of the coatings. The surface roughness and micro-hardness were also measured. A good adhesion of the conventional thick TiAlN and AlCrN coatings was found. The coatings under study are recommended for the applications to super-heater and re-heater tubes of the boilers based upon the outcomes of the research work.

Keywords: nanostructure, physical vapour deposition, oxides, thin films, electron microscopy

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Authors: Siddharth Ahuja, T. M. Muruganandam

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An analytical investigation is performed to study the unsteady response of a one-dimensional, non-linear dynamic shock system to external downstream pressure perturbations in a supersonic flow in a varying area duct. For a given pressure ratio across a wind tunnel, the normal shock's location can be computed as per one-dimensional steady gas dynamics. Similarly, for some other pressure ratio, the location of the normal shock will change accordingly, again computed using one-dimensional gas dynamics. This investigation focuses on the small-time interval between the first steady shock location and the new steady shock location (corresponding to different pressure ratios). In essence, this study aims to shed light on the motion of the shock from one steady location to another steady location. Further, this study aims to create the foundation of the Unsteady Gas Dynamics field enabling further insight in future research work. According to the new pressure ratio, a pressure pulse, generated at the exit of the tunnel which travels and perturbs the shock from its original position, setting it into motion. During such activity, other numerous physical phenomena also happen at the same time. However, three broad phenomena have been focused on, in this study - Traversal of a Wave, Fluid Element Interactions and Wave Interactions. The above mentioned three phenomena create, alter and kill numerous waves for different conditions. The waves which are created by the above-mentioned phenomena eventually interact with the shock and set it into motion. Numerous such interactions with the shock will slowly make it settle into its final position owing to the new pressure ratio across the duct, as estimated by one-dimensional gas dynamics. This analysis will be extremely helpful in the prediction of inlet 'unstart' of the flow in a supersonic engine intake and its prominence with the incoming flow Mach number, incoming flow pressure and the external perturbation pressure is also studied to help design more efficient supersonic intakes for engines like ramjets and scramjets.

Keywords: analytical investigation, compression and expansion waves, fluid element interactions, shock trajectory, supersonic flow, unsteady gas dynamics, varying area duct, wave interactions

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Authors: Wasi Khan, Suboohi Shervani, Swaleha Naseem, Mohd. Shoeb, J. A. Khan, B. R. Singh, A. H. Naqvi

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We have successfully synthesized ZnO/TiO2 nanocomposite using a two-step solochemical synthesis method. The influence of annealing temperature on microstructural, optical, anticandidal, photocatalytic activities and dielectric properties were investigated. X-ray diffraction (XRD) and scanning electron microscopy (SEM) show the formation of nanocomposite and uniform surface morphology of all samples. The UV-Vis spectra indicate decrease in band gap energy with increase in annealing temperature. The anticandidal activity of ZnO/TiO2 nanocomposite was evaluated against MDR C. albicans 077. The in-vitro killing assay revealed that the ZnO/TiO2 nanocomposite efficiently inhibit the growth of the C. albicans 077. The nanocomposite also exhibited the photocatalytic activity for the degradation of methyl orange as a function of time at 465 nm wavelength. The electrical behaviour of composite has been studied over a wide range of frequencies at room temperature using complex impedance spectroscopy. The dielectric constants, dielectric loss and ac conductivity (σac) were studied as the function of frequency, which have been explained by ‘Maxwell Wagner Model’. The data reveals that the dielectric constant and loss (tanδ) exhibit the normal dielectric behavior and decreases with the increase in frequency.

Keywords: ZnO/TiO2 nanocomposites, SEM, photocatalytic activity, dielectric properties

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Authors: Brenda Margaret Behan

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Kenya is a water-stressed country with highly varied socio-ecological environments in its devolved county system, and is currently implementing a polycentric water governance system; this paper examines the importance of social capital in community-based natural resource management and its role in supporting good water governance systems in the Kenya context. Through a robust literature review of theory and case studies, specific aspects of social capital are examined to determine their importance in the implementation of local community-based water management arrangements which support and complement the more formal institutions outlined in the 2002 and 2016 Water Acts of Kenya. Water is an increasingly important and scarce resource not only for Kenya, but for many communities across the globe, and lessons learned in the Kenya context can be useful for other countries and communities faced with similar challenges. Changing climates, increasing populations, and increased per capita consumption of water is contributing to a situation in which the management of water resources will be vital to community resilience. Community-based natural resource management is widely recognized as a building block and component of wider water resource management systems, and when properly conducted can provide a way to enable sustainable use of resources and empower communities. Greater attention to the social and cultural norms and traditional institutions associated with a community’s social capital can lead to better results for Kenya’s polycentric governance of water. The key findings and recommendations from this research show that in Kenya, traditional institutions need to be understood and integrated into governance systems; social values and cultural norms have a significant impact on the implementation of community-based water management efforts; and social capital is a dynamic concept which influences and is influenced by policies and practices. The community-based water management approach will continue to be a key cornerstone for Kenya’s polycentric water governance structure, especially in the more remote arid and semi-arid lands; thus, the successful integration of social capital aspects into planning and implementation will contribute to a strengthened, sustainable, and more equitable national water governance system. Specific observations and recommendations from this study will help practitioners and policymakers to better craft community-based interventions.

Keywords: community-based natural resource management, social capital, traditional institutions, water governance

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

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Authors: B. Gopal, Pannala Krishna Murthy, G. N. Sreenivas

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The increasing demand of electric power is giving an emphasis on the need for the maximum utilization of renewable energy sources. On the other hand maintaining power quality to satisfaction of utility is an essential requirement. In this paper the design aspects of a Unified Power Quality Conditioner integrated with photovoltaic system in a distributed generation is presented. The proposed system consist of series inverter, shunt inverter are connected back to back on the dc side and share a common dc-link capacitor with Distributed Generation through a boost converter. The primary task of UPQC is to minimize grid voltage and load current disturbances along with reactive and harmonic power compensation. In addition to primary tasks of UPQC, other functionalities such as compensation of voltage interruption and active power transfer to the load and grid in both islanding and interconnected mode have been addressed. The simulation model is design in MATLAB/ Simulation environment and the results are in good agreement with the published work.

Keywords: distributed generation (DG), interconnected mode, islanding mode, maximum power point tracking (mppt), power quality (PQ), unified power quality conditioner (UPQC), photovoltaic array (PV)

Procedia PDF Downloads 484

Authors: Luís F. da Silva, Ariadne C. Catto, Osmando F. Lopes, Khalifa Aguir, Valmor R. Mastelaro, Caue Ribeiro, Elson Longo

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Gas detection is important for controlling industrial, and vehicle emissions, agricultural residues, and environmental control. In last decades, several semiconducting oxides have been used to detect dangerous or toxic gases. The excellent gas-sensing performance of these devices have been observed at high temperatures (~250 °C), which forbids the use for the detection of flammable and explosive gases. In this way, ultraviolet light activated gas sensors have been a simple and promising alternative to achieve room temperature sensitivity. Among the semiconductor oxides which exhibit a good performance as gas sensor, the zinc oxide (ZnO) and tin oxide (SnO2) have been highlighted. Nevertheless, their poor selectivity is the main disadvantage for application as gas sensor devices. Recently, heterostructures combining these two semiconductors (ZnO-SnO2) have been studied as an alternative way to enhance the gas sensor performance (sensitivity, selectivity, and stability). In this work, we investigated the influence of mass ratio Zn:Sn on the properties of ZnO-SnO2 nanocomposites prepared by hydrothermal treatment for 4 hours at 200 °C. The crystalline phase, surface, and morphological features were characterized by X-ray diffraction (XRD), high-resolution transmission electron (HR-TEM), and X-ray photoelectron spectroscopy (XPS) measurements. The gas sensor measurements were carried out at room-temperature under ultraviolet (UV) light irradiation using different ozone levels (0.06 to 0.61 ppm). The XRD measurements indicate the presence of ZnO and SnO2 crystalline phases, without the evidence of solid solution formation. HR-TEM analysis revealed that a good contact between the SnO2 nanoparticles and the ZnO nanorods, which are very important since interface characteristics between nanostructures are considered as challenge to development new and efficient heterostructures. Electrical measurements proved that the best ozone gas-sensing performance is obtained for ZnO:SnO2 (50:50) nanocomposite under UV light irradiation. Its sensitivity was around 6 times higher when compared to SnO2 pure, a traditional ozone gas sensor. These results demonstrate the potential of ZnO-SnO2 heterojunctions for the detection of ozone gas at room-temperature when irradiated with UV light irradiation.

Keywords: hydrothermal, zno-sno2, ozone sensor, uv-activation, room-temperature

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Authors: Shruti Jain

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During its independence struggle in the early 20th century, India witnessed trends of politicisation of various spiritual paths, one of them being that of Shaktism. Interestingly, Nietzsche’s teachings were being interpreted as being essentially the worship of Shakti. The present paper aims at investigating this claim and hence undertakes an intercultural archaeological excavation in the realm of the Goddess archetypes that Nietzsche’s work invokes. Ariadne is placed next to Radha, Baubo to Lajja Gauri, Medusa to Chhinnamasta, Hecate to Kali and Dhumavati and Athena to Sarawati. Indeed, the Eternal Feminine plays a vital role in Nietzsche’s writings. One might recall that Nietzsche even declared himself to be the first Psychologist of the Eternal Feminine. The present paper aims to illustrate how, the matter of the Eternal Feminine, like all other matters, is subjected to Nietzsche’s basic creative principle of transvaluation of values and new meaning making. In order to achieve this, Nietzsche applies what Heidegger calls a 'cross-wise striking-through' technique in his analysis of what can be termed as his engagement with Shaktism. Hence, not only is the mystical ascent and descent of the creative energy (Kundalini Shakti) dealt with under erasure in Thus Spake Zarathustra, but coincidentally also the Three Metamorphoses emerge as an instance of such an erasure, making the Devi invisible and yet not so invisible for an Indian reader.

Keywords: eternal feminine, Nietzsche and India, Shaktism, transvaluation of values

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Authors: Rofida Gamal, Mostafa Mohammed, Mariam Adel, Marwa Gamal, Marwa kamal, Ayat Saber, Maha Mamdouh, Amira Emad, Mai Ramadan

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Lynch Syndrome is an inherited genetic condition associated with an increased risk of colorectal and other cancers. Detecting Lynch Syndrome in individuals is crucial for early intervention and preventive measures. This study proposes a computational pipeline for Lynch Syndrome detection by integrating alignment, variant calling, and annotation. The pipeline leverages popular tools such as FastQC, Trimmomatic, BWA, bcftools, and ANNOVAR to process the input FASTQ file, perform quality trimming, align reads to the reference genome, call variants, and annotate them. It is believed that the computational pipeline was applied to a dataset of Lynch Syndrome cases, and its performance was evaluated. It is believed that the quality check step ensured the integrity of the sequencing data, while the trimming process is thought to have removed low-quality bases and adaptors. In the alignment step, it is believed that the reads were accurately mapped to the reference genome, and the subsequent variant calling step is believed to have identified potential genetic variants. The annotation step is believed to have provided functional insights into the detected variants, including their effects on known Lynch Syndrome-associated genes. The results obtained from the pipeline revealed Lynch Syndrome-related positions in the genome, providing valuable information for further investigation and clinical decision-making. The pipeline's effectiveness was demonstrated through its ability to streamline the analysis workflow and identify potential genetic markers associated with Lynch Syndrome. It is believed that the computational pipeline presents a comprehensive and efficient approach to Lynch Syndrome detection, contributing to early diagnosis and intervention. The modularity and flexibility of the pipeline are believed to enable customization and adaptation to various datasets and research settings. Further optimization and validation are believed to be necessary to enhance performance and applicability across diverse populations.

Keywords: Lynch Syndrome, computational pipeline, alignment, variant calling, annotation, genetic markers

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Liza Ireni-Saban

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The 6.6 magnitude quake event that occurred in 2003 (Bam, Iran) made it impossible for the Iranian government to handle disaster relief efforts domestically. In this extreme event, the Iranian government reached out to the international community, and this created a momentum that had to be carried out by trust-building efforts on all sides, often termed ‘Disaster Diplomacy’. Indeed, the circumstances were even more critical when one considers the increasing political and economic isolation of Iran within the international community. The potential for transformative political space to be opened by disaster has been recognized by dominant international political actors. Despite the fact that Bam 2003 post-disaster relief efforts did not catalyze any diplomatic activities on all sides, it is suggested that few international aid agencies have successfully used disaster recovery to enhance their popular legitimacy and reputation among the international community. In terms of disaster diplomacy, an actor’s reputational capital may affect his ability to build coalitions and alliances to achieve international political ends, to negotiate and build understanding and trust with foreign publics. This study suggests that the post-disaster setting may benefit from using the ecology of games framework to evaluate the role of bridging actors and mediators in facilitating collaborative governance networks. Recent developments in network theory and analysis provide means of structural embeddedness to explore how reputational capital can be built through brokerage roles of actors engaged in a disaster management network. This paper then aims to structure the relations among actors that participated in the post-disaster relief efforts in the 2003 Bam earthquake (Iran) in order to assess under which conditions actors may be strategically utilized to serve as mediating organizations for future disaster events experienced by isolated nations or nations in conflict. The results indicate the strategic use of reputational capital by the Iranian Ministry of Foreign Affairs as key broker to build a successful coordinative system for reducing disaster vulnerabilities. International aid agencies rarely played brokerage roles to coordinate peripheral actors. U.S. foreign assistance (USAID), despite coordination capacities, was prevented from serving brokerage roles in the system.

Keywords: coordination, disaster diplomacy, international aid organizations, Iran

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Authors: Sarah Noaman

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Utilizing renewable resources has become extensive solution for most problems in Egypt nowadays. It plays role in environmental issues such as energy crisis, lake of natural resources and climate change. This paper focuses on the importance of working with the key concepts of creating eco-friendly spaces in Egypt by using traditional perennial plants, such as Guadua bamboo as renewable resources in structures manufacture. Egypt is in critical need to search for alternative raw materials. Thus, this paper focuses on studying the usage of neglected yet affordable materials, such as Guadua bamboo in light weight structures and digital fabrication. Guadua bamboo has been cultivated throughout in tropical and subtropical areas. In Egypt, they exist in many rural areas where people try to control their growth by using pesticides as it serves no economic purpose. This paper aims to discuss the usage of Guadua bamboo either in its original state or after fabrication in the context of interior design and architecture. The results will show the applicability of using perennial plants as complementary materials in the manufacturing processes; also the conclusion will focus the lights on the importance of re-forming shallow water plants in interior design and architecture.

Keywords: digital fabrication, Guadua bamboo, zero-waste material, sustainable material, interior architecture

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Authors: F. Mohammadsadeghi

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Relevance of research: Axial compressors are used in both aircraft engine construction and ground-based gas turbine engines. The compressor is considered to be one of the main gas turbine engine units, which define absolute and relative indicators of engine in general. Failure of compressor often leads to drastic consequences. Therefore, safe (stable) operation must be maintained when using axial compressor. Currently, we can observe a tendency of increase of power unit, productivity, circumferential velocity and compression ratio of axial compressors in gas turbine engines of aircraft and ground-based application whereas metal consumption of their structure tends to fall. This causes the increase of dynamic loads as well as danger of damage of high load compressor or engine structure elements in general due to transient processes. In operating practices of aeronautical engineering and ground units with gas turbine drive the operational stability failure of gas turbine engines is one of relatively often failure causes what can lead to emergency situations. Surge occurrence is considered to be an absolute buckling failure. This is one of the most dangerous and often occurring types of instability. However detailed were the researches of this phenomenon the development of measures for surge before-the-fact prevention is still relevant. This is why the research of transient processes for axial compressors is necessary in order to provide efficient, stable and secure operation. The paper addresses the problem of automatic control system improvement by integrating the anti-surge algorithms for axial compressor of aircraft gas turbine engine. Paper considers dynamic exhaustion of gas dynamic stability of compressor stage, results of numerical simulation of airflow flowing through the airfoil at design and stalling modes, experimental researches to form the criteria that identify the compressor state at pre-surge mode detection. Authors formulated basic ways for developing surge preventing systems, i.e. forming the algorithms that allow detecting the surge origination and the systems that implement the proposed algorithms.

Keywords: axial compressor, rotation stall, Surg, unstable operation of gas turbine engine

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Authors: Scott Andersen

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Perhaps simply and rather unadornedly, consciousness is having multiple goals for action and the continuously adjudication of such goals to implement action, referred to as the Maps of Meaning (MoM) Consciousness Theory. The MoM theory triangulates through three parallel corollaries, action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains a fluid, nested goals. These goals are not intentionality, but intersectionality, embodiment meeting the world. i.e., Darwinian inclusive fitness or randomization, then survival of the fittest. These goals form via gradual descent under inclusive fitness, the goals being the abstraction of a ‘match’ between the evolutionary environment and organism. Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience crystallize efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary, but determine the operation and level of one’s consciousness, termed extreme thrownness. Since inclusive fitness drives efficiencies in physiologic mechanism, morphology and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as its the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. Perception is the operant process of consciousness and is the consciousness’ de facto goal adjudication process. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception isn’t a ‘frame rate,’ but Bayesian priors of efficiency based on one’s extreme thrownness. Consciousness and human consciousness is a modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as emergent phenomena at various modularities, like stratified factors in factor analysis). The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

Keywords: consciousness, perception, prospection, embodiment

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Authors: Sunjay

Abstract:

Plate tectonics is of very great significance as it represents the spatial relationships of volcanic rock suites at plate margins, the distribution in space and time of the conditions of different metamorphic facies, the scheme of deformation in mountain belts, or orogens, and the association of different types of economic deposit. Orogenic belts are characterized by extensive thrust faulting, movements along large strike-slip fault zones, and extensional deformation that occur deep within continental interiors. Within oceanic areas there also are regions of crustal extension and accretion in the backarc basins that are located on the landward sides of many destructive plate margins.Collisional orogens develop where a continent or island arc collides with a continental margin as a result of subduction. collisional and noncollisional orogens can be explained by differences in the strength and rheology of the continental lithosphere and by processes that influence these properties during orogenesis.Seismic Imaging Difficulties-In triangle zones, several factors reduce the effectiveness of seismic methods. The topography in the central part of the triangle zone is usually rugged and is associated with near-surface velocity inversions which degrade the quality of the seismic image. These characteristics lead to low signal-to-noise ratio, inadequate penetration of energy through overburden, poor geophone coupling with the surface and wave scattering. Depth Seismic Imaging Techniques-Seismic processing relates to the process of altering the seismic data to suppress noise, enhancing the desired signal (higher signal-to-noise ratio) and migrating seismic events to their appropriate location in space and depth. Processing steps generally include analysis of velocities, static corrections, moveout corrections, stacking and migration. Exploration seismology Bow-tie effect -Shadow Zones-areas with no reflections (dead areas). These are called shadow zones and are common in the vicinity of faults and other discontinuous areas in the subsurface. Shadow zones result when energy from a reflector is focused on receivers that produce other traces. As a result, reflectors are not shown in their true positions. Subsurface Discontinuities-Diffractions occur at discontinuities in the subsurface such as faults and velocity discontinuities (as at “bright spot” terminations). Bow-tie effect caused by the two deep-seated synclines. Seismic imaging of thrust faults and structural damage-deepwater thrust belts, Imaging deformation in submarine thrust belts using seismic attributes,Imaging thrust and fault zones using 3D seismic image processing techniques, Balanced structural cross sections seismic interpretation pitfalls checking, The seismic pitfalls can originate due to any or all of the limitations of data acquisition, processing, interpretation of the subsurface geology,Pitfalls and limitations in seismic attribute interpretation of tectonic features, Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence (or variance) cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Carbon capture and geological storage leakage surveillance because fault behave as a seal or a conduit for hydrocarbon transportation to a trap,etc.

Keywords: tectonics, seismic imaging, fold and thrust belts, seismic interpretation

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Authors: Abhijith N. V., Abhijit Pattnayak, Deepak Kumar

Abstract:

Nowadays, a group of alloys, namely high entropy alloys (HEA), because of their excellent properties. However, the fabrication of HEAs requires multistage techniques, especially mill-ing, sieving, compaction, sintering, inert media, etc. These processes are laborious, costly, time-oriented, and unsuitable for commercial application. This study adopted a single-stage process-based HVOF thermal spray to develop HEA coating on SS304L substrates. The wear behavior of the deposited HEA coating was explored under different milling time durations (5h, 10h, and 15h, respectively). The effect of feedstock preparation, microstructure, surface chemistry, and mechanical and metallurgical properties on wear resistance was also investigated. The microstructure and composition of both coating and feedstock were evaluated by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) analysis. Finally, the phase distribution was correlated by X-ray diffraction (XRD ) analysis. The results showed that 15h milled powder coating indicated better tribological than the base substrate and 5h,10h milled powder coating. A chemically stable Body Centered Cubic (BCC) solid solution phase was generated within the 15h milled powder-coated system, which resulted in superior tribological properties.

Keywords: high entropy alloys coating, wear mechanism, HVOF coating, microstructure

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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Authors: Jonathan A. Sánchez Muñoz, Gustavo Flores Eraña, Juan M. Silva

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Mexican Mezcal industry has reached attention during the last decade due to it has been a popular beverage demanded by North American and European markets, reaching popularity due to its crafty character. Despite its wide demand, productive processes are still made with rudimentary equipment, and there is a lack of evidence to improve kiln energy efficiency. Tec21 is a challenge-based learning curricular model implemented by Tecnológico de Monterrey since 2019, where each formation unit requires an industrial partner. “Problem processes solution” is a formation unity designed for mechatronics engineers, where students apply the acquired knowledge in thermofluids and apply electronic. During five weeks, students are immersed in an industrial problem to obtain a proper level of competencies according to formation unit designers. This work evaluates the competencies acquired by the student through qualitative research methodology. Several evaluation instruments (report, essay, and poster) were selected to evaluate etic argumentation, principles of sustainability, implemented actions, process modelling, and redesign feasibility.

Keywords: applied electronic, challenge based learning, competencies, mezcal industry, thermofluids

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Authors: Josee Charette

Abstract:

The academic and educational success of migrant students is a current issue in education, especially in western societies such in the province of Quebec, in Canada. For people who immigrate with school-age children, the success of the family’s migratory project is often measured by the benefits drawn by children from the educational institutions of their host society. In order to support the academic achievement of their children, migrant parents try to develop practices that derive from their representations of school and related challenges inspired by the socio-cultural context of their country of origin. These findings lead us to the following question: How does strategies implemented by migrant parents to manage the representational distance between school of their country of origin and school of their host society support or not the academic and educational success of their child? In the context of a qualitative exploratory approach, we have made interviews in the French , English and Spanish languages with 32 newly immigrated parents and 10 of their children. Parents were invited to complete a network of free associations about «School in Quebec» as a premise for the interview. The objective of this paper is to present strategies implemented by migrant parents to manage the distance between their representations of schools in their country of origin and in the host society, and to explore the influence of this management on their child’s academic and educational trajectories. Data analysis led us to develop various types of strategies, such as continuity, adaptation, resources mobilization, compensation and "return to basics" strategies. These strategies seem to be part of a continuum from oppositional-conflict scenario, in which parental strategies act as a risk factor, to conciliator-integrator scenario, in which parental strategies act as a protective factor for migrant students’ academic and educational success. In conclusion, we believe that our research helps in highlighting strategies implemented by migrant parents to support their child’s academic and educational success in the host society and also helps in providing a more efficient support to migrant parents and contributes to develop a wider portrait of migrant students’ academic achievement.

Keywords: academic and educational achievement of immigrant students, family’s migratory project, immigrants parental strategies, representational distance between school of origin and school of host society

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Authors: Anil Kumar, Diwakar Aggarwal, M. Sudhakara Reddy

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The wood of Eucalyptus, Populus and bamboos are some important species used as raw material for the manufacture of pulp. However, higher levels of lignin pose a problem during Kraft pulping and yield of pulp is also lower. In order to increase the yield of pulp per unit wood and reduce the use of chemicals during kraft pulping it is important to reduce the lignin content and/or increase cellulose content in wood. Cellulose biosynthesis in wood takes place by the coordinated action of many enzymes. The two important enzymes are KORRIGAN and SUCROSE SYNTHASE. KORRIGAN (Endo-1,4--glucanase) is implicated in the process of editing growing cellulose chains and improvement of the crystallinity of produced cellulose, whereas SUCROSE SYNTHASE is involved in providing substrate (UDP-glucose) for growing cellulose chains. The present study was aimed at the cloning, characterization and overexpression of these genes in Eucalyptus and Populus. An efficient shoot organogenesis protocol from leaf explants taken from micro shoots of the species has been developed. Agrobacterium mediated genetic transformation using Agrobacterium tumefaciens strain EHA105 and LBA4404 harboring binary vector pBI121 was achieved. Both the genes were cloned from cDNA library of Populus deltoides. These were subsequently characterized using various bioinformatics tools. The cloned genes were then inserted into pBI121 under the CaMV35S promotors replacing GUS gene. The constructs were then mobilized into above strains of Agrobacterium and used for the transformation work. Subsequently, genetic transformation of these clones with target genes following already developed protocol is in progress. Four transgenic lines of Eucalyptus tereticornis overexpressing Korrigan gene under the strong constitutive promoters CaMV35S have been developed, which are being further evaluated. Work on development of more transgenic lines overexpressing these genes in Populus and Eucalyptus is also in progress. This presentation will focus on important developments in this direction.

Keywords: Eucalyptus tereticornis, genetic transformation, Kraft pulping Populus deltoides

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Authors: Akram Salah Eddine Belaidi, Said Kenai, El-Hadj Kadri, Benchaâ Benabed, Hamza Soualhi

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Self-compacting concrete (SCC) was developed in the middle of the 1980’s in Japan. SCC flows alone under its dead weight and consolidates itself without any entry of additional compaction energy and without segregation. As an integral part of a SCC, self-compacting mortars (SCM) may serve as a basis for the mix design of concrete since the measurement of the rheological properties of SCCs. This paper discusses the effect of using natural pozzolana (PZ) and marble powder (MP) in two alternative systems ratios PZ/MP = 1 and 1/3 of the performance of the SCC. A total of 11 SCC’s were prepared having a constant water-binder (w/b) ratio of 0.40 and total cementitious materials content of 475 kg/m3. Then, the fresh properties of the mortars were tested for mini-slump flow diameter and mini-V-funnel flow time for SCMs and Slumps flow test, L-Box height ratio, V-Funnel flow time and sieve stability for SCC. Moreover, the development in the compressive strength was determined at 3, 7, 28, 56, and 90 days. Test results have shown that using of ternary blends improved the fresh properties of the mixtures. The compressive strength of SCC at 90 days with 30% of PZ and MP was similar to those of ordinary concrete use in situ.

Keywords: self-compacting mortar, self-compacting concrete, natural pozzolana, marble powder, rheology, compressive strength

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Authors: Mohan Bikram Thapa

Abstract:

Despite the successful implementation of community forestry program, a number of pros and cons have been raised on Terai community forestry in the case of lowland locally called Terai region of Nepal, which climatically belongs to tropical humid and possessed high-quality forests in terms of ecology and economy. The study aims to investigate the local pricing strategy of forest products and its impacts on equitable forest benefits sharing, the collection of community fund and carrying out livelihood improvement activities. The study was carried out on six community forests revealed that local people have substantially benefited from the community forests. However, being the region is heterogeneous by socio-economic conditions and forest resources have higher economic potential, the decision of low pricing strategy made by the local people have created inequality problems while sharing the forest benefits, and poorly contributed to community fund collection and consequently carrying out limited activities of livelihood improvement. The paper argued that the decision of low pricing strategy of forest products is counterproductive to promote the equitable benefit-sharing in the areas of heterogeneous socio-economic conditions with high-value forests. The low pricing strategy has been increasing accessibility of better off households at a higher rate than poor, as such households always have the higher affording capacity. It is also defective to increase the community fund and carry out activities of livelihood improvement effectively. The study concluded that unilateral decentralized forest policy and decision-making autonomy to the local people seems questionable unless their decision-making capacities are enriched sufficiently. Therefore, it is recommended that empowerments of decision-making capacity of local people and their respective institutions together with policy and program formulation are prerequisite for efficient and equitable community forest management and its long-term sustainability.

Keywords: benefit sharing, community forest, livelihood, pricing mechanism, Nepal

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Authors: Bahar Ayhan

Abstract:

The present paper is concerned with the numerical modeling of the inelastic behavior of the anisotropically damaged ductile materials, which are based on a generalized macroscopic theory within the framework of continuum damage mechanics. Kinematic decomposition of the strain rates into elastic, plastic and damage parts is basis for accomplishing the structure of continuum theory. The evolution of the damage strain rate tensor is detailed with the consideration of anisotropic effects. Helmholtz free energy functions are constructed separately for the elastic and inelastic behaviors in order to be able to address the plastic and damage process. Additionally, the constitutive structure, which is based on the standard dissipative material approach, is elaborated with stress tensor, a yield criterion for plasticity and a fracture criterion for damage besides the potential functions of each inelastic phenomenon. The finite element method is used to approximate the linearized variational problem. Stress and strain outcomes are solved by using the numerical integration algorithm based on operator split methodology with a plastic and damage (multiplicator) variable separately. Numerical simulations are proposed in order to demonstrate the efficiency of the formulation by comparing the examples in the literature.

Keywords: anisotropic damage, finite element method, plasticity, coupling

Procedia PDF Downloads 182