Academic literature on the topic 'Optimization-based Integration Platform'
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Journal articles on the topic "Optimization-based Integration Platform"
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Li, Ang, and Chun Jie Wang. "Construction of Lander Multidisciplinary Optimization Platform." Key Engineering Materials 407-408 (February 2009): 180–84. http://dx.doi.org/10.4028/www.scientific.net/kem.407-408.180.
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In the course of present space lander’s optimization, the problems, such as hardness of information integration, partiality of optimization, still exist. In order to solve these problems, Lander Multidisciplinary Optimization Platform has been built. Four engineering tools (Pro/Engineer, Patran, Nastran, ADAMS) are integrated into the platform based on optimization software—iSIGHT, which could ensure space lander’s kinematics and dynamics characteristics. Good optimum scheme is obtained after comprehensive optimization of the platform. Besides, the platform is managed by simulation management software—MSC.SimManage. Multidisciplinary optimization can be realized automatically through parameterized interface of the platform.
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Guo, Ruijie, Shengbo Ye, and Yicai Ji. "Optimization Acceleration Integral Method Based on Power Spectrum Estimation." MATEC Web of Conferences 176 (2018): 03012. http://dx.doi.org/10.1051/matecconf/201817603012.
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Due to the excellent performance of the frequency domain integration method, it is widely used for acceleration integral calculations. However, the frequency-domain integration needs to select the effective integration frequency band to achieve its optimal integration performance. This paper proposes the method with power spectrum density (PSD) estimation to realize the optimization integral of the acceleration signal. By analysing the power spectrum density of the acceleration signal, the optimal low frequency cut-off frequency is obtained. Combined with frequency domain integration algorithm, it can effectively remove low-frequency noise and improve integral accuracy. Then, the novel algorithm tested by an experiment platform with a vibration bench. Experiment results show that this algorithm can adaptively select the low-frequency cut-off frequency and realize frequency domain integration optimization and the integration error is controlled within ±0.2mm.
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Zsiros, Attila, Attila Fülöp, and Gábor Jeney. "Joint Optimization in UMTS-Based Video Transmission." Advances in Multimedia 2007 (2007): 1–14. http://dx.doi.org/10.1155/2007/28340.
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A software platform is exposed, which was developed to enable demonstration and capacity testing. The platform simulates a joint optimized wireless video transmission. The development succeeded within the frame of the IST-PHOENIX project and is based on the system optimization model of the project. One of the constitutive parts of the model, the wireless network segment, is changed to a detailed, standard UTRA network simulation module. This paper consists of (1) a brief description of the projects simulation chain, (2) brief description of the UTRAN system, and (3) the integration of the two segments. The role of the UTRAN part in the joint optimization is described, with the configuration and control of this element. Finally, some simulation results are shown. In the conclusion, we show how our simulation results translate into real-world performance gains.
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Tan, Hongyun, and Yiping Li. "News Information Platform Optimization Based on the Internet of Things." Wireless Communications and Mobile Computing 2021 (May 28, 2021): 1–11. http://dx.doi.org/10.1155/2021/9403874.
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The Internet of Things device online recommendation system has been applied in some Internet of Things operating companies and has achieved good results. In the process of designing and implementing the Internet of Things equipment online promotion system, this article uses the news information protocol transmission structure language to explain the use case analysis and activity diagram analysis of the Internet of Things equipment online promotion system and uses the Spring Hibernate (SH) integration framework in the field of the news information topology layer under the Internet of Things. Then, design and implement the technical architecture and main functional modules of the Internet of Things device online recommendation system, effectively improving the development efficiency and operating quality of the Internet of Things device online recommendation system. The system design concept and implementation ideas can be used as a reference for related industries when developing enterprise applications. This article uses the news information protocol transmission structure language to explain the demand analysis of the Internet of Things equipment online promotion system and mainly discusses the analysis of the use case of the Internet of Things equipment online promotion system and the analysis of core business activity diagrams. We completed the design of the Internet of Things device online promotion system based on the news information topology layer platform under the Internet of Things, mainly using the integration framework in the field of the news information topology layer under the Internet of Things to design the technical architecture of the Internet of Things device online promotion system, and design the Internet of Things of the function module structure and data table structure of the equipment online recommendation system. At the same time, they complete the realization of the main functions of the Internet of Things device online recommendation system; elaborate on the realization process of core modules such as Internet of Things device category management, Internet of Things device information management, announcement management, and device recommender management; and discuss the system testing process and application effects.
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Li, Yu, Tai Yong Wang, and Yin Ming Ge. "Adaptable Dynamic Design Platform Based on CAX/PDM System." Advanced Materials Research 694-697 (May 2013): 168–71. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.168.
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This paper proposed a construction method of the adaptable dynamic design platform based on CAX / PDM system. The method includes three main stages: the establishment of adaptable design service platform, trace dynamic design, variable design and optimization. In addition, a PDM server should be erected as the ties of the whole platform. The platform can be applied to other manufacture industries and reduce the waste of resources. This method can accumulate the experience of redesigning and manufacturing. The seamless integration of data transformation, product designing, analysis, simulation and manufacturing is available. The ultimate goal is the optimization and deformation acceleration of target product.
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Zhou, Wei, Qing Min Liao, and Fei Zhou. "A Design of Infrared Spots Tracking Platform Based on the Camera." Applied Mechanics and Materials 336-338 (July 2013): 392–96. http://dx.doi.org/10.4028/www.scientific.net/amm.336-338.392.
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This paper presents a kind of verification platform similar to Wiimote infrared spots tracking, which is based on the ordinary camera, FPGA, MCU, and Bluetooth. By the maximum of data compression and algorithm optimization, this platform reduces the SW/HW resources and achieves the requirements of low-cost ASIC integration.
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Chang, Bao Rong, Yun-Da Lee, and Po-Hao Liao. "Development of Multiple Big Data Analytics Platforms with Rapid Response." Scientific Programming 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/6972461.
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The crucial problem of the integration of multiple platforms is how to adapt for their own computing features so as to execute the assignments most efficiently and gain the best outcome. This paper introduced the new approaches to big data platform, RHhadoop and SparkR, and integrated them to form a high-performance big data analytics with multiple platforms as part of business intelligence (BI) to carry out rapid data retrieval and analytics with R programming. This paper aims to develop the optimization for job scheduling using MSHEFT algorithm and implement the optimized platform selection based on computing features for improving the system throughput significantly. In addition, users would simply give R commands rather than run Java or Scala program to perform the data retrieval and analytics in the proposed platforms. As a result, according to performance index calculated for various methods, although the optimized platform selection can reduce the execution time for the data retrieval and analytics significantly, furthermore scheduling optimization definitely increases the system efficiency a lot.
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Kushwaha, Arvinda, and Mohd Amjad. "A Particle Swarm Optimization Based Load Scheduling Algorithm in Cloud Platform for Wireless Sensor Networks." Scalable Computing: Practice and Experience 20, no. 1 (March 9, 2019): 71–82. http://dx.doi.org/10.12694/scpe.v20i1.1464.
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Integration of wireless sensor network into cloud computing is a growing paradigm that supports a massive amount of applications in cloud computing, optimization of resources required in the machines. This integration requires the optimization of resources to efficiently complete the different tasks in the devices at cloud platform. This optimization can be done using load scheduling algorithms. These algorithms reduce overload and achieve higher throughput by maximizing the machine utilization concerning cost stabilization. There are lots of methods like First Come First Serve, Min-Min, Particle Swarm Optimization (PSO) for optimizing the load but we use Particle Swarm Optimization as it obtains the motivation from the social behavior of the flock of birds and analyses various approaches for load scheduling. In this paper, we propose the load scheduling algorithm based on PSO in wireless sensor networks for cloud computing to minimize total transfer time and cost stabilization. The proposed method is compared with the existing approaches used for load scheduling in Cloudlets. It is clear from the simulation results that the proposed method is more efficient because it minimizes the transfer time and cost than the conventional algorithms thereby making a system for cost stable.
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Ding, Ke, Qi Yuan He, and Gang Chen. "Research of Information Integration for the Grid Panoramic Information Platform Based on SOA." Applied Mechanics and Materials 667 (October 2014): 50–54. http://dx.doi.org/10.4028/www.scientific.net/amm.667.50.
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The development and construction of the smart grid require the efficient integration of the communication data of the grid enterprises, the optimization of operation and management of the grid. The paper introduces the characteristics and the requirements of the construction of the grid panoramic information platform, in allusion to the heterogeneous professional application system and the information isolated island phenomenon in power grid. The paper designs the panoramic information system frame based on the service oriented architecture (SOA) and proposes the schemes of the panoramic information integration and the information integration solution, providing a firm basic information platform for the unified management, production and operation and the forewarning decision of the smart grid.
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Yan, Yan, Liyan Zhang, Yuhan Li, Xiangyu Xu, Zhencheng Jiang, and Feiyu Cheng. "Research on solar water heating system based on TRNSYS simulation optimization." Journal of Mines, Metals and Fuels 69, no. 4 (May 13, 2021): 132. http://dx.doi.org/10.18311/jmmf/2021/27801.
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In this paper, the typical system of solar energy system: natural circulation system and forced circulation system are analyzed. The two systems are simulated on the TRNSYS platform, and the configuration of the system itself has been discussed. The purpose is to provide reference for the scientific implementation of solar energy architecture integration. On the basis of summarizing the solar energy construction technology, the natural circulation system and the forced circulation system of solar hot water system have been discussed emphatically. The simulation experiment is designed on the TRNSYS platform. The influence of different heat collection area and water tank volume on solar energy guarantee rate and system efficiency has been discussed by simulation data. Finally, the optimal allocation scheme of natural constraints of natural circulation and forced circulation has been obtained.
Dissertations / Theses on the topic "Optimization-based Integration Platform"
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Dai, Lei. "An Open Platform of Parameterized Shape Optimization based-on CAD/CAE Integration Technique." Reims, 2006. http://theses.univ-reims.fr/exl-doc/GED00000752.pdf.
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The main content in the research is developing an open platform of parameterized shape optimization based-on CAD/CAE integration technique. Through integration, structural analysis and design optimization are seamless combined with parametric geometry modeling and embed into the CAD system. POSHAPE can provide parameterized shape optimization method for 3D solid structure, spatial shell structure and cell structure of composite material. To realize such a general method, integration is the most essential part. In this platform, integration is realized includes: 1) Integrating structure analysis tool of different disciplinary with structure shape optimization. Structure response from different disciplinary will be studied according structure shape. 2) Integrating finite element modeling with parametric geometry modeling through Boundary Representative Tree (simplified as: B-Rep) used in solid modeling. Finite element model is parameterized to be dynamic regenerated during optimization design steps. 3) Parametric solid modeling is extended to realize parameterized surface modeling under integration between surface model definition and solid model. Parameterized finite element modeling of shell structure is also achieved which is similar to that of solid structure
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Dai, Lei Guo Ying Qiao. "An Open Platform of Parameterized Shape Optimization based-on CAD/CAE Integration Technique." Reims : S.C.D. de l'Université, 2006. http://scdurca.univ-reims.fr/exl-doc/GED00000752.pdf.
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Juvert, Sández Joan. "Development and optimization of silicon based light sources for integration into a sensor platform." Doctoral thesis, Universitat de Barcelona, 2014. http://hdl.handle.net/10803/275940.
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We have characterized electroluminescent devices based on silicon rich oxide and/or silicon rich nitride. We have discussed the photoluminescence and structural characterization of the active layers and the electrical and electroluminescent characterization of full devices.
We have noted that the electroluminescence can appear in the form of discrete points scattered across the active area of the devices, in the form of emission along the rim of the active area, or homogeneously distributed across the area. These different kinds of emission have been related to the optical and electrical properties of the devices.
In the two former cases, the electroluminescence comes with high current densities,of the order of 1 A/cm2, and low efficiencies of the order of 10-8. On the other hand, the homogeneous emission comes with lower current densities, of the order of 0.01 A/cm2, and better efficiencies, in the range 10-7–10-5.
We have concluded that the homogeneous emission is optimal in terms of efficiency. Furthermore, a simple model has been proposed to explain the appearance and occasional coexistence of the different kinds of emission.
The effect of a nitride layer on top of the SRO has been explored, concluding that it helps in achieving a uniform conduction that favors the homogeneous emission in the active layer.
The conductivity states of the active layer associated with the different kinds of emission have been related with its CV behavior. The results of the study show that the homogeneous emission corresponds to well behaved CV curves, whereas the emission through points does not.
The injection mechanisms in PECVD and ion implanted samples have been studied, concluding that no single emission mechanism can account for the injection at all regimes in the studied range of electric fields. Fowler-Nordheim or trap assisted tunneling have been found to play a significant role in PECVD samples. In implanted samples, Fowler-Nordheim dominates at low fields, whereas Poole-Frenkel is more likely to be the dominant mechanism at higher fields.
Comparison of the photoluminescence and electroluminescence spectra of bilayers SRO/SRN, allows us to conclude that each layer contributes a different band in the total emission, which results in a wider distribution of the energy across the visible spectrum.
The comparison between the photoluminescence and electroluminescence has revealed massive differences in their spectra, which have been attributed to interference effects.
A computer software based in the Crawford method for the study of the interference effects in multilayer stacks has been presented. The program has been used to quantitatively study the interference effects in the emission of our devices. We can conclude that the photoluminescence and electroluminescence spectra are the same despite their apparent difference. Our analysis has also made it apparent that a quantitative understanding of the interference effects in the system is important in order to draw valid conclusions regarding the origins of the luminescence.
We have presented the design, fabrication and characterization of a CMOS compatible optical transceiver, and two main challenges in the integration of the emitter, waveguide and detector have been successfully overcome, namely achieving a reasonably flat and uniform silicon oxide trench and a good detector.
In the end, the transceiver has not worked as expected, most likely due to a poor SRN emitter. More work is required in order to better control the fabrication process of the SRN layers. However, we believe the basic design to be valid, given the low electrical coupling detected between the emitter and the detector components of the transceiver.Aquesta tesi presenta un estudi de les propietats òptiques de capes d'òxid de silici enriquit en silici (SRO) i nitrur de silici enriquit en silici (SRN) que han sofert un procés tèrmic d'alta temperatura. Aquest procés indueix la creació de nanoaglomerats de silici en la matriu dielèctrica. Aquestes nanoestructures de silici presenten una superior eficiència en l'emissió respecte al silici en bloc, i a més a més emeten en el visible en comptes de l'infraroig. Això és interessant per a l'obtenció de dispositius fotònics integrats basats en silici que poden ser fabricats monolíticament en un procés compatible amb la tecnologia CMOS que domina la indústria microelectrònica. A més a més, hem estudiat les propietats òptiques i elèctriques de dispositius metall-aïllant-semiconductor en les quals l'aïllant és una capa d'SRO o SRN amb nanoaglomerats de silici. N'hem mesurat paràmetres d'interès com ara l'eficiència de conversió d'energia elèctrica-òptica o la potència òptica, i n'hem estudiat els mecanismes d'injecció que hi tenen lloc. S'han identificat tres tipus diferents d'emissió: per punts, per la vora del dispositiu, i emissió homogènia, i hem determinat que l'emissió homogènia és la més adecuada pel que fa a l'eficiència dels dispositius. Hem desenvolupat un programa que permet el càlcul de les interferències òptiques que tenen lloc als sistemes multicapa que conformen els dispositius estudiats, i que distorsionen l'espectre observat respecte al que les capes realment emeten. L'habilitat de poder calcular aquests efectes ens permet, en molts casos, eliminar l'efecte de les interferències i determinar l'autèntic espectre d'emissió de les capes i per tant estar en millors condicions d'assignar l'emissió als mecanismes correctes. Finalment, hem proposat un prototip per a un transceptor en el qual l'emissor, la guia d'ones i el detector estan integrats monolíticament en un procés CMOS. Hem fabricat el dispositiu i l'hem caracteritzat. Tot i que no hem aconseguit acoblament òptic entre l'emissor i el detector, creiem que el disseny bàsic queda validat, ja que els principals obstacles en l'obtenció del dispositiu han sigut superats amb èxit.
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LIAO, PO-HAO, and 廖柏豪. "Deep Learning Based Integration and Optimization of Big Data Analytics Platforms." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/349jtp.
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碩士國立高雄大學
資訊工程學系碩士班
106
This study focused on big data analysis job scheduling mechanism, predicting the time for big data analysis based on deep learning DNN (Deep Neural Network), and shortening the average waiting time of overall work by intelligent scheduling optimization. The proposed mechanism is expected to enhance the execution efficiency of big data analysis platform greatly. A multi-platform big data processing system, characterized by high efficiency, high availability and high expandability, is integrated with Hadoop and Spark to make the platform support R command-based data analysis capability. The time complexity, priority and data size of working program can influence the efficiency of overall execution work and the average waiting time for fulfilling the work, especially in the environment of big data, the average waiting time for fulfilling the work is prolonged. This problems can be solved only by designing optimal scheduling to enhance system effectiveness. This study uses DNN to predict the execution time for R program, and implements intelligent scheduling according to Shortest Job First, the optimal program execution platform is selected, so as to shorten the average waiting time for fulfilling the work to optimize the multiple big data platforms.
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LEE, YUN-DA, and 李昀達. "Deep Learning Based Integration and Optimization of Rapid Data Retrieval in Big Data Platforms." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/96k95v.
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碩士國立高雄大學
資訊工程學系碩士班
106
The purpose of this study is to focus on the data pre-processing mechanism and to use Deep Autoencoder and Solr to group data intelligently and reduce the scope of search required by Query. It is expected that the proposed mechanism will greatly improve the efficiency of system query. A set of multiple big data processing platform with high efficiency and high availability was adopted, and the integration of Apache Hive, Cloudera Impala and Apache SparkSQL enabled the platform to support the big data retrieval capability of SQL commands. Through the above platform and mechanism, the overall performance can be significantly improved. Data tables often need to be searched completely when data is retrieved. In order to solve the serious problem that the system I/O takes longer and longer time when the amount of data becomes larger and larger, the effect of intelligent clustering practiced by deep learning method is considered, as it is superior to the efficiency of traditional neural network. Therefore, a deep model was designed to improve the overall efficiency of the system.
Book chapters on the topic "Optimization-based Integration Platform"
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Dral, Pavlo O., Fuchun Ge, Bao Xin Xue, Yi-Fan Hou, Max Pinheiro, Jianxing Huang, and Mario Barbatti. "MLatom 2: An Integrative Platform for Atomistic Machine Learning." In Topics in Current Chemistry Collections, 13–53. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07658-9_2.
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AbstractAtomistic machine learning (AML) simulations are used in chemistry at an everincreasing pace. A large number of AML models has been developed, but their implementations are scattered among different packages, each with its own conventions for input and output. Thus, here we give an overview of our MLatom 2 software package, which provides an integrative platform for a wide variety of AML simulations by implementing from scratch and interfacing existing software for a range of state-of-the-art models. These include kernel method-based model types such as KREG (native implementation), sGDML, and GAP-SOAP as well as neuralnetwork- based model types such as ANI, DeepPot-SE, and PhysNet. The theoretical foundations behind these methods are overviewed too. The modular structure of MLatom allows for easy extension to more AML model types. MLatom 2 also has many other capabilities useful for AML simulations, such as the support of custom descriptors, farthest-point and structure-based sampling, hyperparameter optimization, model evaluation, and automatic learning curve generation. It can also be used for such multi-step tasks as Δ-learning, self-correction approaches, and absorption spectrum simulation within the machine-learning nuclear-ensemble approach. Several of these MLatom 2 capabilities are showcased in application examples.
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Kümpel, Michaela, Christian A. Mueller, and Michael Beetz. "Semantic Digital Twins for Retail Logistics." In Dynamics in Logistics, 129–53. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88662-2_7.
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AbstractAs digitization advances, stationary retail is increasingly enabled to develop novel retail services aiming at enhancing efficiency of business processes ranging from in-store logistics to customer shopping experiences. In contrast to online stores, stationary retail digitization demands for an integration of various data like location information, product information, or semantic information in order to offer services such as customer shopping assistance, product placement recommendations, or robotic store assistance.We introduce the semantic Digital Twin (semDT) as a semantically enhanced virtual representation of a retail store environment, connecting a symbolic knowledge base with a scene graph. The ontology-based symbolic knowledge base incorporates various interchangeable knowledge sources, allowing for complex reasoning tasks that enhance daily processes in retail business. The scene graph provides a realistic 3D model of the store, which is enhanced with semantic information about the store, its shelf layout, and contained products. Thereby, the semDT knowledge base can be reasoned about and visualized and simulated in applications from web to robot systems. The semDT is demonstrated in three use cases showcasing disparate platforms interacting with the semDT: Optimization of product replenishment; customer support using AR applications; retail store visualization, and simulation in a virtual environment.
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He, Yan. "Study on Secure Dynamic Covering Algorithm for E-Logistics Information in a Cloud Computing Platform." In Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, 1097–111. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5339-8.ch051.
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For traditional coverage method, local adaptive weighted search is adopted for subspace reconstruction of e-logistics information, which requires significant iterative computations and leads to large coverage errors and unsatisfactory results. This paper proposes a secure dynamic covering algorithm for e-logistics information based on the basis of directional clustering for the envelope of optimization solution vectors. A data network distribution model of e-logistics information on a cloud computing platform is constructed to extract features of e-logistics information and to construct time series of information flows. The directional clustering algorithm for the envelope of optimization solution vectors is introduced to schedule features of e-logistics information. The experimental results show that the proposed algorithm has higher coverage rate, smaller error, and increases performance of e-logistics information transmission and higher application value on a cloud computing platform.
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Biswas, Rathindra Nath, Anurup Saha, Swarup Kumar Mitra, and Mrinal Kanti Naskar. "PSO-Based Antenna Pattern Synthesis." In Nature-Inspired Algorithms for Big Data Frameworks, 218–45. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5852-1.ch009.
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An antenna pattern synthesis scheme based on particle swarm optimization (PSO) technique is proposed. Synthesized patterns always contain narrower beamwidth and minimum side-lobes level reducing coverage areas towards the attackers in wireless networks. On such patterns, deep nulls are also steered at various interfering directions as to provide a second layer of protection. Using selective patterns at each point-to-point link, data privacy is ensured throughout entire route from source to sink. This approach is simple enough to be commensurate with flexible design methods on a real-time platform. Thus, an FSM (finite state machine) rule-based digital system model is further developed and tested on Xilinx Virtex4 FPGA (field programmable gate array) board. Its performance under harsh radio environmental conditions is also verified with several fixed-point simulations in terms of pattern synthesis accuracy and computational overheads. These results corroborate such system integration onto wireless infrastructures for the secured data communication services.
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Lezak, Emil, Enrico Ferrera, Rosaria Rossini, Zofia Masluszczak, Malgorzata Fialkowska-Filipek, Gunnar Große Hovest, Alexander Schneider, et al. "Towards Industry 4.0." In Research Anthology on Cross-Industry Challenges of Industry 4.0, 411–35. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8548-1.ch022.
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An overview of the work under development within the EU-funded collaborative project MAESTRI is presented in this chapter. The project provides a framework of new Industrial methodology, integrating several tools and methods, to help industries facing the fourth industrial revolution. This concept, called the MAESTRI Total Efficiency Framework (MTEF), aims to advance the sustainability of manufacturing and process industries by providing a management system in the form of a flexible and scalable platform and methodology. The MTEF is based on four pillars: a) an effective management system targeted at continuous process improvement; b) Efficiency assessment tools to support improvements, optimization strategies and decision-making support; c) Industrial Symbiosis paradigm to gain value from waste and energy exchange; d) an Internet-of-Things infrastructure to support easy integration and data exchange among shop-floor, business systems and MAESTRI tools.
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Lezak, Emil, Enrico Ferrera, Rosaria Rossini, Zofia Masluszczak, Malgorzata Fialkowska-Filipek, Gunnar Große Hovest, Alexander Schneider, et al. "Towards Industry 4.0." In Technological Developments in Industry 4.0 for Business Applications, 199–223. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-4936-9.ch009.
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An overview of the work under development within the EU-funded collaborative project MAESTRI is presented in this chapter. The project provides a framework of new Industrial methodology, integrating several tools and methods, to help industries facing the fourth industrial revolution. This concept, called the MAESTRI Total Efficiency Framework (MTEF), aims to advance the sustainability of manufacturing and process industries by providing a management system in the form of a flexible and scalable platform and methodology. The MTEF is based on four pillars: a) an effective management system targeted at continuous process improvement; b) Efficiency assessment tools to support improvements, optimization strategies and decision-making support; c) Industrial Symbiosis paradigm to gain value from waste and energy exchange; d) an Internet-of-Things infrastructure to support easy integration and data exchange among shop-floor, business systems and MAESTRI tools.
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Brahmane, Anilkumar V., and B. Chaitanya Krishna. "DSAE – Deep Stack Auto Encoder and RCBO – Rider Chaotic Biogeography Optimization Algorithm for Big Data Classification." In Recent Trends in Intensive Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210198.
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In today’s era Big data classification is a very crucial and equally widely arise issue is many applications. Not only engineering applications but also in social, agricultural, banking, educational and many more applications are there in science and engineering where accurate big data classification is required. We proposed a very novel and efficient methodology for big data classification using Deep stack encoder and Rider chaotic biogeography algorithms. Our proposed algorithms are the combinations of two algorithms. First one is Rider Optimization algorithm and second one is chaotic biogeography-based optimization algorithm. So, we named it as RCBO which is integration is ROA and CBBO. Our proposed system also uses the Deep stack auto encoder for the purpose of training the system which actually produced the accurate classification. The Apache spark platform is used initial distribution of the data from master node to slave nodes. Our proposed system is tested and executed on the UCI Machine learning data set which gives the excellent results while comparing with other algorithms such as KNN classification, Extreme Learning Machine Random Forest algorithms.
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Wu, Lei, Ming Wei, and Xiang Chen. "Optimization Model of Unmanned Aerial Vehicle Distribution Path with Integrated Loading and Unloading." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210205.
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Unmanned aerial vehicle (UAV) delivery has the advantages of small size, high speed, and low cost. A new drone delivery path optimization model with loading and unloading integration is proposed in this study to make full use of UAV(drone) delivery by improving its efficiency. The model considers drone range constraints and loading capacity limitations, analyzes the start and end points of multiple orders, assigns orders to drones from the optimal distribution centers, calculating the order and time to visit all sets and delivery points, and pursuing the least transportation mileage. The ant colony optimization (ACO) algorithm is adopted to solve the problem in two stages. In the first stage, construction rules and pheromones of the solution are defined, and the orders to the UAVs are assigned. In the second stage, by adding constraints to the ACO algorithm, the sequence order of the UAVs visiting the set and delivery points is determined to obtain the optimal path. Finally, a GIS-based delivery platform is developed using Java Development Kit, which is used to produce the optimal scheduling scheme for an example case. A sensitivity analysis of the model parameters is conducted t, which proves the proposed model effectiveness.
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Aijaz, Fahad. "Mobile Web Services for P2P Computing." In Developing Advanced Web Services through P2P Computing and Autonomous Agents, 133–57. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-61520-973-6.ch008.
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The Information Technology (IT) and Telecommunication (TelCo) sectors face enormous integration challenges, due to the prominent heterogeneity in existing systems. Service-oriented computing tackles such challenges by providing a fundamental platform that facilitates the convergence of distinct domains based on Web Services (WSs). With the mobility and technological advancements, service-oriented computing has been pushed towards the mobile sector enabling P2P Mobile Web Services (MobWSs) provisioning. In this work, we investigate the interaction, architecture and design characteristics of MobWSs for P2P computing. Here, the two MobWS interaction strategies are presented followed by the architectural discussion, enfolding server and client side components, of a resource-oriented MobWS framework. We follow REST design principles to propose an efficient way of architecting P2P MobWS systems, as an alternative to SOAP, enabling significant payload reduction and performance optimization in mobile servers. The detailed performance evaluation is also presented and compared to SOAP based on real-time measurements. By analyzing performance characteristics, we show that REST is a promising technique to architect P2P MobWS systems for resource-constraint mobile nodes.
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Gebremeskel, Gebeyehu Belay, Zhongshi He, and Xuan Jing. "Semantic Integrating for Intelligent Cloud Data Mining Platform and Cloud Based Business Intelligence for Optimization of Mobile Social Networks." In Data Mining in Dynamic Social Networks and Fuzzy Systems, 173–211. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-4213-3.ch009.
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In this chapter, the authors focused on optimization of MSNs based on integrating for intelligent DM and BI platforms, which involves mobile devices. The approach is defining the challenges based social network trends and current situation explorations, and then applying the techniques to exploring the social media towards social cloud technology, which focused on creating a scalable, adaptable and optimal social cloud as the users’ contexts and IT technologies. The newly proposed method is vigorously significant to develop flexible social networking in relation to the development of IT, which facilitates data/information access, distributions, high availability and a large amount of data analysis and others. Therefore, the techniques this chapter is vitally crucial to improve the performance and use of social networking in a comprehensive and powerful way. Nutshell, this chapter overviews the impetus for the development of intelligent semantic cloud and diversified social-networking in both physical and wireless sectors, which representing a wide aspect of social cloud change, and increasingly appropriate service providing a platform for innovative ideas and technological innovation in the business environment.
Conference papers on the topic "Optimization-based Integration Platform"
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Alsaeedi, Ayesha Ahmed Abdulla Salem, Manar Maher Mohamed Elabrashy, Mohamed Ali Alzeyoudi, Mohamed Mubarak Albadi, Sandeep Soni, Jose Isambertt, Deepak Tripathi, and Melvin Hidalgo. "Leveraging Business Intelligence and Data Analytics in an Integrated Digital Production Platform to Unlock Optimization Potentials." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/208209-ms.
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Abstract This paper discusses business intelligence algorithms and data analytics capabilities of an integrated digital production platform implemented in a giant gas condensate field. The advanced workflow focuses on helping the user navigate through the bulk of data to identify patterns and make predictions utilizing exception-based intelligence alarming. This helps derive insightful findings and provides recommendations for users to make efficient business decisions for achieving field potential optimization objectives. An Integrated digital production platform within a giant gas condensate field is implemented with numerous production optimization workflows encompassing daily well and facility performance monitoring and surveillance. The data integration within the systems is enhanced by integration with powerful Business Intelligence (BI) tools, enabling users to create customized dashboards, KPI screens, and exception-based alarm screens. An additional integration to the production platform is carried out with data from real-time sources like PI Asset Framework and corporate databases, improving the integrated production system's daily well and facility surveillance capabilities. The advanced integration of BI tools provided users with various opportunities to identify bottlenecks, production improvement chances, and troubleshooting areas by capitalizing insights from various dashboards and business KPI screens. Further, integrating these dashboards with several corporate data sources and a real-time asset data framework enabled users to harness maximized information embedded in the bulk of data. This also enabled end-users to harness maximized system potential, with all information available under a single collaborative platform. The integration powered by various inbuilt complex algorithms extended scripting capabilities, and enhanced visualization assisted the asset in realizing business KPIs requirements. Business intelligence algorithms in user interface established a drill-down approach to utilize information associated with multiple variables on top of one another. This allowed for the quick identification of trends and patterns in data. The customization approach helped the user to draw maximum information out of data as per their engineering requirements and current practices. This advanced integration facilitated users to minimize their efforts in traditional data analysis such as gathering, mapping, filtering, and plotting. With the help of these powerful features embedded in an integrated platform, the user was able to drive more focus on optimization and minimize time and effort on system configuration. This unique integration was one of its kind. An online integrated digital production platform comprising of wells, networks, and various workflows was integrated with business intelligence tools, thereby providing end-users tremendous opportunities related to system optimization.
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Li, Yunpeng, and Utpal Roy. "Challenges in Developing a Computational Platform to Integrate Data Analytics With Simulation-Based Optimization." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46410.
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The focus of the work presented in this paper is to identify and find possible solutions for major implementation challenges in designing a computational platform for integrating data analytics paradigm with the simulation-based optimization technique to facilitate the modeling of a smart manufacturing system. A simulation model of a manufacturing system generates real-time monitoring data for machine status and these data are then mined by data mining algorithms to discover hidden knowledge that might not be predefined in the simulation model. The new knowledge is then fed into the simulation model such that the model adapts and evolves, and eventually it can predict future status. This procedure involves heterogeneous modeling techniques, information exchange among different tools, as well as model composition and interaction. We extend an early presented “Hypercube” information model that was specifically developed for the purpose of formal representation of smart manufacturing systems, in order to harmonize the information required by the simulation modeling tool and the data analytics tool. A strong emphasis is given to emerging areas of multi-domain and multiscale modeling by means of integration and interoperability between existing modeling tools and technologies. A specific case study related to preventive and predictive maintenance of a typical manufacturing system has been elaborated in the paper as the initial scope and application area in order to illustrate and validate the proposed computational framework.
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"NAS-wide Simulation-Based Evaluation Platform for Validation of a Traffic Flow Management Optimization Tool." In 12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference and 14th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2012. http://dx.doi.org/10.2514/6.2012-5471.
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Chen, Cheng, Noman Mithani, Tiffany Jin, and Allen Guo. "Liquid Cooling Practice on Meta’s AI Training Platform." In ASME 2022 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipack2022-96972.
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Abstract Due to continuous growth of AI accelerator chip power and heat flux, implementation of advanced cooling technologies for AI platforms seems to be inevitable for hyper scale users. Liquid cooling is one of the relatively more mature category of advanced cooling technologies, and has been adopted in a variety of forms across industry. However, not all liquid cooling solutions are able to deliver high performance with reasonable cost and efficiency. In addition, it’s not straightforward to arrive at proper balance of performance, reliability, serviceability, and scalability for a product, and prepare the facility accordingly to align with long term strategy. In this presentation, we will introduce a passive cold plate loop solution (Tide 1.0), based on Meta’s AI training platform (Zion) with eight Open Accelerator Modules (OAM). It reflects the design considerations on performance and serviceability. Thermal simulation and optimization studies will be presented. The solution was tested on dummy thermal test vehicles and real functional system, along with cooling capability forecast. Results showed a good match between simulation, TTV test and real system test. The resulting performance demonstrated strong use case of liquid cooling solutions on upcoming AI platforms.
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Shetty, Devdas, Naresh Poudel, and Esther Ososanya. "Design of Robust Mechatronics Embedded Systems by Integration of Virtual Simulation and Mechatronics Platform." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-52784.
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Increasing demands on the productivity of complex systems, such as machine tools and their steadily growing technological importance will require the application of new methods in the product development process. This paper shows that the analysis of the simulation results from the simulation based mechatronic model of a complex system followed by a procedure that allows a better understanding of the dynamic behavior and interactions of the components. Mechatronics is a design philosophy, which is an integrating approach to engineering design. Through a mechanism of simulating interdisciplinary ideas and techniques, mechatronics provides ideal conditions to raise the synergy, thereby providing a catalytic effect for the new solutions to technically complex situations. This paper shows how the mechatronic products can exhibit performance characteristics that were previously difficult to achieve without the synergistic combination. The paper further examines an approach used in modeling, simulation and optimization of dynamic machine tools and adopts it for general optimized design of mechatronics instrumentation and portable products. By considering the machine tool as a complete mechatronic system, which can be broken down into subsystems, forms the fundamental basis for the procedure. Starting from this point of view it is necessary to establish appropriate simulation models, which are capable of representing the relevant properties of the subsystems and the dynamic interactions between the machine components. Many real-world systems can be modeled by the mass-spring-damper system and hence considering one such system, namely Mechatronics Technology Demonstrator (MTD) is discussed here. MTD is a portable low cost, technology demonstrator, developed and refined by the authors. It is suitable for studying the key elements of mechatronic systems including; mechanical system dynamics, sensors, actuators, computer interfacing, and application development. An important characteristic of mechatronic devices and systems is their built-in intelligence that results through a combination of precision, mechanical and electrical engineering, and real time programming integrated to the design process. The synergy can be generated by the right combination of parameters, that is, the final product can be better than just the sum of its parts. The paper highlights design optimization of several mechatronic products using the procedures derived by the use of mass spring damper based mechatronic system. The paper shows step by step development of a mechatronic product and the use of embedded software for portability of hand held equipment. A LabVIEW based platform was used as a control tool to control the MTD, perform data acquisition, post-processing, and optimization. In addition to the use of LabVIEW software, the use of embedded control system has been proposed for real-time control and optimization of the mass-spring-damper system. Integrating embedded control system with the mass-spring-damper system makes the MTD a multi-concepts Mechatronics platform. This allows interface with external sensors and actuators with closed-loop control and real-time monitoring of the physical system. This teaches students the skill set required for embedded control: design control algorithms (model-based embedded control software development, signal processing, communications), Computer Software (real-time computation, multitasking, interrupts), Computer hardware (interfacing, peripherals, memory constraints), and System Performance Optimization. This approach of deriving a mathematical model of system to be controlled, developing simulation model of the system, and using embedded control for rapid prototyping and optimization, will practically speed product development and improve productivity of complex systems.
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Ntonas, Konstantinos, Nikolaos Aretakis, Ioannis Roumeliotis, and Konstantinos Mathioudakis. "A Marine Turbocharger Retrofitting Platform." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14643.
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Abstract A turbocharger retrofitting platform utilizing 1D models for calculating turbomachinery components maps and a fully coupled process for integration with the turbomachinery components and the diesel engine, is presented. The platform has been developed with two modes of operation, allowing the retrofitting process to become fully automatic. In the first mode, available turbo-components are examined, in order to select the one that best matches the entire engine system, aiming to retain or improve the diesel engine efficiency. In the second mode, an optimization procedure is employed, in order to redesign the compressor to match the entire system in an optimum way. Dimensionless parameters are used as optimization variables, for a given compressor mass flow and power. A retrofitting case study is presented, where three retrofitting options are analyzed (compressor retrofit, turbocharger retrofit and compressor redesign). In the first and second option, turbocharger retrofitting is carried out, using available turbo-components. It is shown that initial performance cannot be reconstituted using off-the-self solutions. In the third option, compressor designing is performed, using the optimization mode, in order to provide an improved retrofitting solution, aiming to at least reconstituting the original diesel engine performance. Finally, a CFD analysis is carried out, in order to validate the compressor optimization tool capability to capture the performance trends, based on geometry variation.
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Kopczynski, Jerry A., Bill Dickson, and Gerhard J. Weiss. "Common Electronic Platform for the Steam Turbine and Generator Controls: Upgrade Installed at the Mt. Poso Cogeneration Power Station — A Case Study." In ASME 2004 Power Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/power2004-52159.
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The scope of modern power plant controls usually includes plant DCS, boiler control and protection, steam/gas turbine governor and protection, auxiliaries control, automatic voltage controller, automatic synchronizer and operator/engineering stations. Usually these control packages come from different manufacturers (OEM). They are typically based on various electronic hardware and software platforms. Different communication protocols often present problems during system integration; and maintenance costs of these various electronic hardware and software platforms are normally greater than that of a stand alone system. Advantages of an integrated, distributed, open architecture, digital system, (Fig. 1) which covers all the power plant needs are discussed in this paper. A common electronic hardware/ software platform allows optimization of the new constructions and upgrades, shorten delivery and commissioning time, and improve availability and safety of the new and upgraded power plants. Specific benefits of this concept are presented in the Mt. Poso controls upgrade Case Study. The common electronic hardware/ software platform installed at Mt. Poso allowed optimization of the upgrade, shortened commissioning time, improved availability, reliability and safety and reduced maintenance cost of the control systems.
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Alsaeedi, Ayesha, Mohamed Mubarak Albadi, Fahad Alharthi, Manar Elabrashy, Mohamed Alzeyoudi, Ammar Al-Ameri, Eissa Al Mheiri, et al. "Improved Field Production Planning and Cost Optimization Using Predictive Analytical Choke Performance Model and Intelligent Alarms in an Integrated Platform." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211314-ms.
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Abstract One of the critical aspects of production optimization and planning is to meet the production targets or to meet some operational requirements such as workovers or maintenance activities. This paper demonstrates how an advanced integration in a digital platform, coupled with a predictive analytical model for choke performance and intelligent alarming, can significantly help asset in production planning and cost optimization while accurately regulating the field rates. First, the bulk of well-test data from corporate databases is integrated into an advanced digital platform with an automated well-test validation workflow. The workflow output provides the choke tuning factors for each test while validating the well-test parameters. The digital platform provided the initial data check to ensure the validated tests with choke tuning factors were processed for further regression analysis. The network model in the digital platform for the entire asset was run for a predefined set of iterations to generate the representative choke tuning factors for each well, based on production test parameters and flow line pressure constraints. The regression analysis output was used to predict the choke sizes for different inflow performance rates and various operating wellhead pressures and vice versa. The predictive choke analytical model outputs were utilized to predict the choke size for a set of well parameters, such as rates and wellhead pressures, based on historical well performance. The choke sizes predicted could be used to identify preferred wells in an area to be controlled to achieve production targets, minimizing the operational effort and time. The predictive choke model with intelligent alarm feature provided users instantaneous insight into underperforming and overperforming wells, assisting them to take further actions in an effective way. The other intelligent alarms worked in combination to detect lifting problems associated with wells more efficiently, such as the liquid loading intelligent alarm. The predictive model was also valuable for efficient production planning in terms of setting the quarterly well allowable, choke sizes, or performing field capacity tests to meet the business production target on field & well level and to analyze short-term and medium-term forecast cases using an automated reservoir integration workflow in the digital platform. This was helpful in planning ahead of time for future operations and saving a significant amount of time and effort for engineers and the operation team. This specialized approach of predictive choke performance modeling in a digital platform provided asset a robust tool to plan and optimize their field production while leveraging the power of data-driven digital platforms consisting of closed-loop automated engineering workflows. The accuracy of prediction proved significant cost optimization and proactive planning, where the bulk of data was handled effectively and efficiently to identify production optimization opportunities and field bottlenecks.
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Zhao, Xin, Smruti Sahoo, Konstantinos Kyprianidis, Sharmila Sumsurooah, Giorgio Valente, Mohamed Rashed, Gaurang Vakil, et al. "A Framework for Optimization of Hybrid Aircraft." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91335.
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Abstract To achieve the goals of substantial improvements in efficiency and emissions set by Flightpath 2050, fundamentally different concepts are required. As one of the most promising solutions, electrification of the aircraft primary propulsion is currently a prime focus of research and development. Unconventional propulsion sub-systems, mainly the electrical power system, associated thermal management system and transmission system, provide a variety of options for integration in the existing propulsion systems. Different combinations of the gas turbine and the unconventional propulsion sub-systems introduce different configurations and operation control strategies. The trade-off between the use of the two energy sources, jet fuel and electrical energy, is primarily a result of the trade-offs between efficiencies and sizing characteristics of these sub-systems. The aircraft structure and performance are the final carrier of these trade-offs. Hence, full design space exploration of various hybrid derivatives requires global investigation of the entire aircraft considering these key propulsion sub-systems and the aircraft structure and performance, as well as their interactions. This paper presents a recent contribution of the development for a physics-based simulation and optimization platform for hybrid electric aircraft conceptual design. Modeling of each subsystem and the aircraft structure are described as well as the aircraft performance modeling and integration technique. With a focus on the key propulsion sub-systems, aircraft structure and performance that interfaces with existing conceptual design frameworks, this platform aims at full design space exploration of various hybrid concepts at a low TRL level.
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Arroyos, Marina Roche, Javier Arturo Corea Araujo, Didac Sabria, Vinayak Padmaji, Pablo Cano, and Patrice Garmier. "Model based component co-optimization and scalability of virtual testing for electric drivetrain vehicle." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-dgt-045.
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"Within the automotive product development cycle virtual and heterogeneous testing is becoming increasingly established through component, module and vehicle-level simulation. Though a number of standards in this field have been established, models are still mostly created in a fragmented manner: using domain-specific tools to create, manage and execute simulations without standardization of the content of the functional interfaces (FMI does only standardize the format) and limited scalability. This fragmentation leads to a lot of redundant effort as models of the same component or system are re-created several times. HIFI-ELEMENTS project addressed this fragmentation through two main mechanisms: Firstly, developing, validating and publishing a recommendation for standardization of model interfaces for common e-drive components (e-machine, inverter, battery, DC/DC converter, thermal management) and implementation of compliant versions of existing models. Secondly, implementing a seamless workflow linking extended versions of existing tools with effort-saving automated methods for model parameterization and test case generation. This seamless integration will substantially increase the number of integrations and test cases that can be early validated through simulation, leading to optimized efficiency designs and development effort reduction. The standardization also guarantees scalability among fidelity levels, from concept design to XiL through detailed modelling. In this paper we present the results of the Use Case C: Component co-optimization. The purpose of use cases is the demonstration of the advantages of the standardized models and workflow industry relevant scenarios. The work content performed in the use case is very extensive and multidisciplinary. In the first step, the high fidelity models from the expert components developers were validated independently with automated testing tools and later integrated to create a complete vehicle architecture integration. The standardization permitted to seamlessly test several component variants developed within the project for the same architecture, including tens of motor models with different technologies, inverters and high voltage converters with different IGBT technology and various battery packs. This possibility was exploited through co-optimization with multi objective Genetic Algorithm, permitting to select the optimal component combination, powertrain architecture (with and without high voltage DCDC converter) and components parametrization considering the trade-off of consumption and performances. The optimized and baseline variants were used to demonstrate the scalability of the models to different simulation objectives. The model was co-simulated with a traffic simulation environment in order to evaluate the impact of eco-driving recommendation algorithms in a realistic driving situation. The optimized solution was also validated against a wide database of driving conditions including real driving cycles, performance and vehicle dynamics. Finally, the integrated models were seamlessly transferred to real time simulation platform for Model-in-the-Loop testing with a simulated 3D environment aimed at ADAS testing. Real-time capability demonstrates that next steps such as Driver-in-the-Loop and Hardware-in-the loop can be achieved smoothly. The extensive simulation activities performed in this use case demonstrate the benefits of the standard in models exchangeability and effort reduction in model based development. This project received funding from the European Union’s (EU) Horizon 2020 Research and innovation program under grant agreement N 769935."