Academic literature on the topic 'Soil Digital Twin'
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Journal articles on the topic "Soil Digital Twin"
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Nasirahmadi, Abozar, and Oliver Hensel. "Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm." Sensors 22, no. 2 (January 10, 2022): 498. http://dx.doi.org/10.3390/s22020498.
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Digitalization has impacted agricultural and food production systems, and makes application of technologies and advanced data processing techniques in agricultural field possible. Digital farming aims to use available information from agricultural assets to solve several existing challenges for addressing food security, climate protection, and resource management. However, the agricultural sector is complex, dynamic, and requires sophisticated management systems. The digital approaches are expected to provide more optimization and further decision-making supports. Digital twin in agriculture is a virtual representation of a farm with great potential for enhancing productivity and efficiency while declining energy usage and losses. This review describes the state-of-the-art of digital twin concepts along with different digital technologies and techniques in agricultural contexts. It presents a general framework of digital twins in soil, irrigation, robotics, farm machineries, and food post-harvest processing in agricultural field. Data recording, modeling including artificial intelligence, big data, simulation, analysis, prediction, and communication aspects (e.g., Internet of Things, wireless technologies) of digital twin in agriculture are discussed. Digital twin systems can support farmers as a next generation of digitalization paradigm by continuous and real-time monitoring of physical world (farm) and updating the state of virtual world.
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Skobelev, P. O., A. S. Tabachisnkiy, E. V. Simonova, Yu N. Zhuravel, and G. N. Miatov. "REGARDING SOME OF THE METHODS FOR CROP STATE CALCULATION IN DIGITAL TWIN OF PLANT." Izvestiya of Samara Scientific Center of the Russian Academy of Sciences 24, no. 3 (2022): 100–111. http://dx.doi.org/10.37313/1990-5378-2022-24-3-100-111.
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In this paper, a concept of digital twin of plant, which is a decision support system to implement precise farming technologies. Digital twin of plant allows to forecast and simulate real crop state and suggest agricultural measures to the fi elds based on weather and soil data. Digital twin of plant is developed with the use of multi-agent technologies and ontology-based domain formalization.
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Nemtinov, Kirill, Maria Eruslanova, Alexander Zazulya, Yulia Nemtinova, and Haider Sabah Salih. "Creating a digital twin of an agricultural machine." MATEC Web of Conferences 329 (2020): 05002. http://dx.doi.org/10.1051/matecconf/202032905002.
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In this paper, the authors developed an approach to creating a digital twin or an electronic model of complex agricultural machinery and proposed its structure as a set of frames. It is represented by a tuple that includes: a frame describing structural composition of the technical system under consideration; a frame describing the properties that characterize it as a whole; a set of ways to determine its properties; a set of attributive characteristics; a set of parametric graphic models of elements and a set of two-dimensional drawings. Examples of digital twins of agricultural machinery are given: a combined unit for soil preparation and sowing of grain crops and a unit for cleaning and calibration of grain seeds.
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Augustyn, Dawid, Martin D. Ulriksen, and John D. Sørensen. "Reliability Updating of Offshore Wind Substructures by Use of Digital Twin Information." Energies 14, no. 18 (September 16, 2021): 5859. http://dx.doi.org/10.3390/en14185859.
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This paper presents a probabilistic framework for updating the structural reliability of offshore wind turbine substructures based on digital twin information. In particular, the information obtained from digital twins is used to quantify and update the uncertainties associated with the structural dynamics and load modeling parameters in fatigue damage accumulation. The updated uncertainties are included in a probabilistic model for fatigue damage accumulation used to update the structural reliability. The updated reliability can be used as input to optimize decision models for operation and maintenance of existing structures and design of new structures. The framework is exemplified based on two numerical case studies with a representative offshore wind turbine and information acquired from previously established digital twins. In this context, the effect of updating soil stiffness and wave loading, which constitute two highly uncertain and sensitive parameters, is investigated. It is found that updating the soil stiffness significantly affects the reliability of the joints close to the mudline, while updating the wave loading significantly affects the reliability of the joints localized in the splash zone. The increased uncertainty related to virtual sensing, which is employed to update wave loading, reduces structural reliability.
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Myalenko, V. I. "Development of a Digital Model of the Agricultural Tool Working Element." Agricultural Machinery and Technologies 14, no. 4 (December 18, 2020): 57–62. http://dx.doi.org/10.22314/2073-7599-2020-14-4-57-62.
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The digital twin is a virtual model of the agricultural tool working element that allows you to calculate and predict its expected behavior during the entire period of operation.(Research purpose) To develop an algorithm for consistent models that make up the digital twin of the agricultural tool working element.(Materials and methods) The fi rst component of the digital twin algorithm was determined by the method of accelerated imitation loading of the wedgelock ripper working element, which was accepted as the research object. The second component was determined by testing various soils with the specifi cation of power equivalents. The physical and mechanical properties of soils and materials (hardening) for the manufacture of working elements were taken into account during the description of the following components.(Results and discussion) The author showed that the algorithm for constructing a digital twin of the agricultural tool working element consisted from a chain of successive actions and was a system for digital description of the working element, which ensured the standard lifetime during operation. The results of a simulated immersion which registered the nature of the normal forces distribution over the friction surfaces were accepted as the fi rst component of the algorithm. The second component – the results of determining the force equivalent when loading the working element in a real soil environment. The possibility of constructing maps of the intensity of the friction surface abrasive wear, predictive calculations of structural elements was revealed. The third and fourth components were used to ensure the working element standard lifetime, based on the minimum production costs, correlated to the standard resource unit of development.(Conclusions) The resulting algorithm for constructing a digital twin is a convenient tool for creating new designs of agricultural tools working elements.
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Kutumov, Yu D., V. E. Mizonov, A. I. Tikhonov, and T. Yu Shadrikova. "Development of digital twin model of underground electric cable: thermal part of the problem." Vestnik IGEU, no. 3 (June 30, 2021): 59–65. http://dx.doi.org/10.17588/2072-2672.2021.3.059-065.
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Innovative technologies of generative design using the concept of digital twins of the designed objects play an important role in growing digitalization trend of project activities. The digital twin of an object is the object simulation model with high accuracy of mathematical description. It is used to solve the problems of regime and structural optimization of the object. Usually, generative design technologies are implemented using 3D models of physical fields. And specialized packages which have high requirements for computer resources and user skills are used. At the same time, quite often the object for which the digital twin model is developed consists of several subsystems that allow relatively independent modeling. A one-dimensional model of the thermal process cannot provide the required accuracy, but a 2D-model is quite sufficient for this purpose. The development of such a model that combines the required accuracy, and low cost of machine time is currently topical scientific and practical problem. The method of mathematical modeling is used to solve this problem. The model uses the mathematical apparatus of the Markov chain theory. The model is two-dimensional and is adapted to the multi-layer environment representing the soil, in a separate cell of which a non-stationary heat source may be found. Heat passage through the surrounding soil is described in terms of thermal conductivity, and the heat exchange with the environment is described in terms of heat transfer. The influence of the parameters on the process flow is studied by numerical methods. At this stage of the study, experimental verification of the model is not expected. A mathematical two-dimensional model of digital twin of underground electric cable has been developed. It allows us to predict the cable temperature and its distribution in the surrounding soil. The assessment of thermal state of the power transmission line is given according to the power and the depth of the heat source location. It is found that the results of simulation modeling are consistent with the physical concepts of the process. The results obtained are of scientific novelty, since they are based on a universal modeling algorithm and allow us to describe the transients in the object under study, which is a part of the digital twin of the underground cable. The model is easy to use and requires little machine time. It can be easily used in generative design practice.
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Silva, Letícia, Francisco Rodríguez-Sedano, Paula Baptista, and João Paulo Coelho. "The Digital Twin Paradigm Applied to Soil Quality Assessment: A Systematic Literature Review." Sensors 23, no. 2 (January 15, 2023): 1007. http://dx.doi.org/10.3390/s23021007.
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This article presents the results regarding a systematic literature review procedure on digital twins applied to precision agriculture. In particular, research and development activities aimed at the use of digital twins, in the context of predictive control, with the purpose of improving soil quality. This study was carried out through an exhaustive search of scientific literature on five different databases. A total of 158 articles were extracted as a result of this search. After a first screening process, only 11 articles were considered to be aligned with the current topic. Subsequently, these articles were categorised to extract all relevant information, using the preferred reporting items for systematic reviews and meta-analyses methods. Based on the obtained results, there are two main conclusions to draw: First, when compared with industrial processes, there is only a very slight rising trend regarding the use of digital twins in agriculture. Second, within the time frame in which this work was carried out, it was not possible to find any published paper on the use of digital twins for soil quality improvement within a model predictive control context.
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Weckesser, Fabian, Michael Beck, Kurt-Jürgen Hülsbergen, and Sebastian Peisl. "A Digital Advisor Twin for Crop Nitrogen Management." Agriculture 12, no. 2 (February 21, 2022): 302. http://dx.doi.org/10.3390/agriculture12020302.
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Farmers and consultants face an unmanageable amount of diverse knowledge and information for crop management decisions. To determine optimal actions, decision makers require knowledge-based support. In this way, decisions can be improved and heuristics can be replaced over time. The study presents a digital knowledge base with an integrated decision support system (DSS), using the example of nutrient supply, specifically nitrogen (N), fertilization. Therefore, the requirements of farmers and crop consultants for DSS to inform fertilization decisions for winter wheat (Triticum aestivum L.) were elaborated using surveys, expert interviews, and a prototype test. Semantic knowledge was enriched by expert knowledge and combined in a web application, the Crop Portal. To map regional and personal decision making patterns and experiences, the tacit knowledge on the complex advisory problem of N fertilization is made digitally usable. For this purpose, 16 fuzzy variables were specified and formalized. Individual decision trees and their interactions with an integrative knowledge base were used to multiply the consulting reach of experts. Using three consultants and nine model farms from different soil–climate areas in Germany, the Crop Portal was tested under practical conditions and the perceived pragmatic and hedonic quality of the system was evaluated using a standardized questionnaire. The field test showed that the variation in fertilizer recommendations from the ‘digital advisor twin’ ranged from 5 kg N ha−1 to 16 kg N ha−1 when compared with the decisions of the experts in the field. The study presents the participatory development and evaluation of a rule-based DSS prototype in agricultural practice.
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Laryukhin, Vladimir, Petr Skobelev, Oleg Lakhin, Sergey Grachev, Vladimir Yalovenko, and Olga Yalovenko. "Towards developing a cyber-physical multi-agent system for managing precise farms with digital twins of plants." Cybernetics and Physics, Volume 8, 2019, Number 4 (December 30, 2019): 257–61. http://dx.doi.org/10.35470/2226-4116-2019-8-4-257-261.
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The paper presents the multi-agent approach for developing cyber-physical system for managing precise farms with digital twins of plants. It discusses complexity of the problem caused by a priori incompleteness of knowledge about factors of plant growth and development, high uncertainty of crops cultivation, variety of weather, business and technical requirements, etc. The approach proposes knowledge bases and multi-agent technology in combination with machine learning methods for designing considered systems. Digital twin of plant is specified as an agent based on ontology model of objects relevant for plant cultivation (specific sort of plant, soil, etc) associated with history of operations and environment conditions. The architecture and functions of system components are designed. The expected results of system implementation and the benefits for farmers are discussed.
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Panarin, R. N., А. А. Soloviev, and Любовь Анатольевна Хворова. "Application of Artificial Intelligence and Computer Vision Technologies in Solving Problems of Automation of Processing and Recognition of Biological Objects." Izvestiya of Altai State University, no. 1(123) (March 18, 2022): 101–7. http://dx.doi.org/10.14258/izvasu(2022)1-16.
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The article considers the application of artificial intelligence and computer vision technologies to solve the automation of processing and analysis of botanical micro and macro objects (images of fern spores). Also, there is a problem of developing software for a digital twin of an agrobot. The first problem is an interdisciplinary research aimed at solving applied and fundamental problems in botanical objects' biosystematics and studying microevolutionary processes using computer vision technologies, methods of intelligent image analysis, machine learning, and artificial intelligence. The article presents the developed software module FAST (Functional Automated System Tool) for solving the direct problem — performing measurements from images obtained by scanning electron microscopy, virtual herbaria image library, entomological collections, or images taken in a natural environment.
The second problem is software development for the digital twin of the agrorobot, designed for precise mechanical processing of plants and soil. The proposed solution includes several components: the control unit — NVIDIA Jetson NANO computing module; the actuator — 6-axis robotic arm; the machine vision unit based on an Intel RealSense camera; the chassis unit — tracked tracks and software drivers and components for their control. The digital twin of the robot considers the environmental conditions and the landscape of the operation area.
The use of ROS (Robot Operating System) allows minimal effort to transfer a digital model to a physical one (prototype and serial robot) without changing the source code. Furthermore, consideration of the environmental conditions during the programming stage provides opportunities for further development and testing of real-life mathematical models for device control.
Dissertations / Theses on the topic "Soil Digital Twin"
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Rull, Patricia. "Hydrological modeling enhancement using GIS : An improved topographic wetness index for wetland detection." Thesis, Stockholms universitet, Institutionen för naturgeografi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-126004.
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Hydrological modeling, like runoff modelling for flood prevention, is based on digital elevation models (DEMs). The fact that the DEMs do not represent existing road culverts can lead to considerable hydrological misinterpretations. In order to overcome this limitation, a GIS method was developed to automatically adjust the elevation model, hydrologically enforcing the DEM, so that the results of hydrological modeling accounts for flow through culverts. The hydro-enforced DEM showed to better represent the drainage network than the former DEM when compared with the river map. The topographic wetness index is the most commonly applied topographic index and a good indicator of soil moisture distribution. It has been integrated into many hydrological models and pollution risk indices as well as into the prediction of wetland distribution. Using the hydro-DEM from the previous step and the soil map in conjunction with the TWI, an improved TWI was achieved, namely a soil-topographic wetness index (STI). The linkages between specific soil types and TWI or STI values were analyzed. They revealed a clear linkage between STI values and soil type based on the soil transmissivity (R2=0.77). However, the TWI values showed low correlations to the soil types (R2=0.02). As a specific application, both TWI and STI were tested for the detection of wetlands. Wetlands are important ecosystems which act as buffer zones by filtering pollutants and slowing floodwater. Being able to identify their distribution is important in landscape planning and ecology. A wetland threshold value was determined for each index and their results where compared with the wetland map from the property map (assumed as ground truth) and with the potential wetland area. Finally, a visual validation was performed with the use of an aerial photography. The results showed that the STI performed slightly better than the TWI for the detection of wetlands, detecting 3% more wetlands. The impact of the soil map on the topographic wetness index was therefore determined as positive.
Book chapters on the topic "Soil Digital Twin"
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Caro-González, A., A. Serra, X. Albala, C. E. Borges, D. Casado-Mansilla, J. Colobrans, E. Iñigo, J. Millard, A. Mugarra-Elorriaga, and Renata Petrevska Nechkoska. "The Three MuskEUteers." In Contributions to Management Science, 3–28. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-11065-8_1.
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AbstractUnder the inspiring and aspiring title: Paving the way for pushing and pursuing a “one for all, all for one” triple transition: social, green, and digital: The Three MuskEUteers, a group of remarkable co-authors and contributors have developed radically new forward-looking visions, principles, approaches, and action recommendations for an attuned indivisible social, green, and digital transition.The triple transition is aimed at helping humanity gather around a life-sustaining purpose, as opposed to life-destroying one in terms of wars of all kinds (military, economic, political, etc.); nature decay and wreckage (carbon footprint, plastic pollution, soil poisoning, etc.); human alienation (favelas, homeless persons, refugee camps, child malnutrition, poverty, exclusion of any kind); and geographic imbalances with empty rural spaces and overcrowded megacities (creating difficult access of rural and/or remote population to care, health, and other essential services; difficulty of urban population to contact with natural environments).The work highlights the urgent need to speed up a third social transition (Within this social transition dimension we understand the socio-cultural scope as any social shift implies a cultural transition and vice versa, with its very deep implications.), in addition to the green and digital transitions more widely recognised by the international community. Innovation, or a European industry-led twin transition aiming for climate neutrality and digital leadership, cannot be supported without a firm, responsive, responsible social and environmental engagement. Neither is it possible to tackle a JUST triple transition which is not firmly rooted in worthwhile human development, underpinned by the Sustainable Development Goals. And none of these transitions can go separately and/or isolated; they all need to intertwine around the notion of (more, firmer, and determined) just transition.European society is presented as a huge “co-laboratory” for this “all for one, one for all” boundaryless triple transition to respond to the urgent radical changes demanded by humanity and by the planet. The chapter proposes a radically new vision to pursue a non-explored transformative way to ideate, design, develop, and deliver science, innovation, and collaboration through experimentation and learning, and throughout multi-stakeholder engagement from the n-helix spectrum. It proposes systemic innovation tactics for the “how” (green, techno-digital), for the strategic “what” (green, social), for the purposeful “why” (green, social), and for the operational “how best” (green, social, techno-digital) within the governing principles of eco-centric society. This encompasses: Courageous goal-aligned alternatives, as a shift to new (yet ancient) principles of eco-centric rather than ego-centric behaviour. The adoption of a “complex system mind-set” to build up dynamic, context-sensitive, and holistic approaches to co-design mission and purpose-driven actions, outcomes, outputs, and no-harm impacts. The ignition of the transformative capacity of all forms of collaboration (international, interdisciplinary, intersectoral, intergenerational, inter-institutional, inter-genders) vs hierarchy as alternative governance and distribution models to overcome the unjust and unsustainable biased status quo within evolving, adaptable, flexible, and transformational n-helix ecosystems. The Three MuskEUteers, deeply anchored in European values (human dignity, freedom, democracy, equality, rule of law, and human rights), will pave the way and drive humanity towards the achievement of the ambitious, but achievable, targets of the United Nations 2030 Global Agenda, the Sustainable Development Goals.Europe can be the initiator of co-laboratory experiments where social change drives the “all for one, one for all” dream into transforming this three-prong transition into possible real good ecosystems working.
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Samikannu, Ravi, Ashok Kumar Koshariya, E. Poornima, S. Ramesh, Ashok Kumar, and S. Boopathi. "Sustainable Development in Modern Aquaponics Cultivation Systems Using IoT Technologies." In Human Agro-Energy Optimization for Business and Industry, 105–27. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-4118-3.ch006.
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The main problem in developing reliable and economically feasible solutions for aquaponics is combining aquaculture (the farming of fish) and hydroponics (the growing of plants without soil). The purpose of this chapter is to aid in the development of a workable commercial aquaponics system. Additionally, it looks at the internet of things (IoT) and smart systems in the literature. For the purpose of real-time monitoring and physical system control in an aquaponics system, an application that uses digital twinning is created. A tool that models the relationship between crop size and fresh weight, and then estimates crop size as it grows, using image segmentation is suggested. The various parameters of the aquaponics system and the sensors used in the IoT and digital twin framework system are demonstrated. The controlling strategies, various smart technologies, and implementation procedures are also illustrated.
Conference papers on the topic "Soil Digital Twin"
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Ayello, Francois, Guanlan Liu, Yonghe Yang, and Ning Cui. "Probabilistic Digital Twins for Transmission Pipelines." In 2020 13th International Pipeline Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/ipc2020-9240.
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Abstract Digitalization in the oil and gas industry has led to the formation of digital twins. Digital twins bring closer the physical and virtual world as data is transmitted seamlessly between real time sensors, databases and models. The strength of the digital twin concept is the interconnectivity of data and models. Any model can use any combination of inputs (e.g. operator owned data sets and sensors, third-party databases such as soil composition or weather data, results from other models such as flow assurance, threat modelling or risk modelling). Consequently, the result of one model may become the input of another. This strength is also a weakness, as uncertain (or missing data) will lead to a great source of uncertainty and may lead to wrong results. Worst case scenarios have been used to solve this issue without success. This paper presents a new concept: probabilistic digital twins for pipelines. Probabilistic digital twins do not lose uncertainty as results pass from one model to another, thus providing greater confidence in the final results. This publication reviews the probabilistic digital twin concept and demonstrates how it can be implemented using gas pipeline data from West Pipeline Company, CNPC.
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An, Di, and YangQuan Chen. "A Digital Twin Enabled Internet of Living Things (IoLT) Framework for Soil Carbon Management." In 2022 18th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA). IEEE, 2022. http://dx.doi.org/10.1109/mesa55290.2022.10004406.
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Ji, Beilei, Xiaoben Liu, Ning Shi, Jianping Liu, Pengchao Chen, Dong Zhang, and Hong Zhang. "Digital Twin of Buried Oil Pipe in Permafrost Regions: A Multi-Source Monitoring and Numerical Simulation Model." In ASME 2021 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/pvp2021-61991.
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Abstract Geohazards have become one of the major threats for pipeline safety as catastrophic consequences can be induced by the ground displacement. To prevent pipe failure, multi-source monitoring technics have been adopted by pipeline operators in engineering practice. While the strain gauge monitored strain results are discretely distributed along the pipeline, which makes the most dangerous pipe section might be not derived directly via sensors. Therefore, it is of great significance to establish an accurate numerical simulation model based on digital twin technology in the geological disaster areas to predict the actual stress and strain status in pipelines. In this paper, an automatically generated parametrical finite element model was established by combining using the general nonlinear finite element software package ABAQUS and the numerical calculation software MATLAB. Numerous numerical strain results were generated as database for a multi-layer backpropagation artificial neural network regressing pipe’s strain state and the geohazard loading conditions (i.e. soil displacement, length of the geohazard areas etc.). Finally, particle swarm optimization algorithm was employed to obtain the most fitting geohazard loading conditions based on monitoring data. An actual case of a buried X65 crude oil pipeline in northeast China was considered as an example, results show that after 5 iterations a relatively accurate strain distribution along the pipe was obtained via the optimization results. The proposed method can be adopted in the integrity management of pipeline crossing geohazard areas.
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Yang, Yong, Zhu Chen, Jing Yan, Zhi Xiong, Jun Zhang, Hongxia Yuan, Yali Tu, and Tianyun Zhang. "State Evaluation of Power Transformer Based on Digital Twin." In 2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). IEEE, 2019. http://dx.doi.org/10.1109/soli48380.2019.8955043.
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