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Physics-Informed Neural Network for Mining Truck Suspension Parameters Identification 16th

Physics-Informed Neural Network for Mining Truck Suspension ...

引用

16th International Symposium on Advanced Vehicle Control

作者： Wu, Mingyu Wang, Yafei Zhang, Yichen Li, Zexing Shanghai Jiao Tong Univ Sch Mech Engn Shanghai Peoples R China

ISBN: (纸本)9783031703942;9783031703928;9783031703911

Mining truck suspensions are prone to performance degradation under complex external excitation of the mining area, leading to high safety risks and maintenance costs. However, the lack of unsprung kinematic information and harsh operating environments lead to inadequate accuracy of current physical models. On the other hand, data-driven methods partially address the issue of incomplete information, but suffer from the absence of interpretability and generalization. To address these challenges, this paper introduces a Physics-Informed Neural Network (PINN) for precise suspension characteristic identification of mining trucks. Specifically, the physical model of the longitudinal-vertical dynamics of the mining truck is established. Then, based on the model, baseline values of suspension parameters are regressed through the instrumental variable method. Therefore, the hybrid modeling architecture is established to precisely identify suspension parameters by utilizing a recurrent neural network. Under this architecture, the states of the mining truck can be effectively updated. Real truck experiments demonstrate the proposed hybrid model outperforms traditional physical and data-driven models in estimating suspension nonlinear parameters and truck dynamic characteristics under typical longitudinal motions.

关键词： Mining Truck Hybrid Model Neural Network Parameter Identification

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Numerical Study of the Flow Distribution in Parallel Pipes of Water Cooling System of Diesel Locomotives 14th

Numerical Study of the Flow Distribution in Parallel Pipes o...

引用

14th International Conference on Computational Heat and Mass Transfer (ICCHMT)

作者： Hou, Bo Na, Xin Guo, Yuqian Wang, Liangbi Lanzhou Jiaotong Univ Sch Mech & Elect Engn Lanzhou Peoples R China Lanzhou Jiaotong Univ Key Lab Railway Vehicle Thermal Engn Minist Educ Lanzhou Peoples R China

ISBN: (纸本)9783031672408;9783031672415

This study employs a numerical approach to investigate the flow distribution characteristics within the parallel branch pipes of a water cooling system in diesel locomotives. The analysis reveals a considerable non-uniformity in the flow distribution within the parallel branch pipes of the cooling system, with 15% flow deviations. To address this issue, a study of the pipeline's velocity and pressure fields was conducted. The results uncovere that changes of the area of recirculation regions and static pressure are the primary contributors to this non-uniform flow distribution. As a solution, interceptors were installed in both the manifold box and the branch pipe inlets to regulate the flow within the pipeline. Among the measures involving using flow interceptors in the manifold box, when three interceptors are used and their cross section areas are S-1 = 32 cm(2), S-2 = 28 cm(2), S-3 = 24 cm(2), the most effective regulation appears, the flow deviation decreases to approximately 6%, but the pressure drop increases 11%. Installing one interceptor with different cross section area at every branch pipe inlet reduces the flow distribution unevenness from 15% to about 2%, the pressure drop increases 10%. This underscores the effectiveness of installing an interceptor at every branch pipe inlet for flow regulation.

关键词： Cooling system Parallel branch pipes Flow distribution

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Nonlinear Dynamics of a Controlled Two-Wheeled Trailer 16th

Nonlinear Dynamics of a Controlled Two-Wheeled Trailer

引用

16th International Symposium on Advanced Vehicle Control

作者： Horvath, Hanna Zsofia Feher, Adam Balint Takacs, Denes Budapest Univ Technol & Econ Fac Mech Engn Dept Appl Mech Budapest Hungary HUN REN BME Dynam Machines Res Grp Budapest Hungary

ISBN: (纸本)9783031703942;9783031703928;9783031703911

The nonlinear dynamics of towed two-wheeled trailers is investigated using a spatial, 4-DoF model. Namely, the yaw, pitch, and roll motions are all taken into account. Geometrical nonlinearities and the non-smooth characteristics of the tire forces are considered. A linear state feedback controller with feedback delay is designed to enhance the stability performance of the trailer. Numerical bifurcation analysis is performed to investigate the large amplitude vibrations and unsafe (bistable) zones, where the stable rectilinear motion and the stable limit cycle coexist with each other. The effects of the control gain and the feedback delay of the controller are presented on bifurcation diagrams. It is shown, that with appropriately chosen control gains, the size of the bistable region can be limited.

关键词： towed two-wheeled trailer stability control nonlinear analysis feedback delay

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Deep Reinforcement Learning-Based Approach to Dynamically Balance Multi-manned Assembly Lines 32nd

Deep Reinforcement Learning-Based Approach to Dynamically Ba...

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32nd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Santos, Romao Marques, Catarina Toscano, Cesar Ferreira, Hugo M. Ribeiro, Joel INESC TEC Inst Syst & Comp Engn Technol & Sci Porto Portugal

ISBN: (纸本)9783031382406;9783031382413

Assembly lines are at the core of many manufacturing systems, and planning for a well-balanced flow is key to ensure long-term efficiency. However, in flexible configurations such as Multi-Manned Assembly Lines (MMAL), the balancing problem also becomes more challenging. Due to the increased relevance of these assembly lines, this work aims to investigate the MMAL balancing problem, to contribute for a more effective decision-making process. Therefore, a new approach is proposed based on Deep Reinforcement Learning (DRL) embedded in a Digital Twin architecture. The proposed approach provides a close-to-reality training environment for the agent, using Discrete Event Simulation to simulate the production system dynamics. This methodology was tested on a real-world instance with preliminary results showing that similar solutions to the ones obtained using optimization-based strategies are achieved. This research provides evidence of success in terms of dynamic resource assignment to tasks and workers as a basis for future developments.

关键词： Assembly Line Balancing Deep Reinforcement Learning Real-time Decision-making Digital Twin

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Numerical Prediction of Flow and Heat Transfer in a Molten Corium Pool

Numerical Prediction of Flow and Heat Transfer in a Molten C...

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Saudi International Conference on Nuclear Power engineering (SCOPE)

作者： Siddiqui, Osman Balabaid, Abdallah Al-Gazlan, Osamah Shams, Afaque KFUPM Mech Engn Dept Dhahran 31261 Saudi Arabia KFUPM Interdisciplinary Res Ctr Ind Nucl Energy IRC INE Dhahran 31261 Saudi Arabia KFUPM Chem Engn Dept Dhahran 31261 Saudi Arabia

ISBN: (纸本)9783031643613;9783031643620

The integrity of the reactor pressure vessel is of the utmost importance in nuclear reactor safety. One of the cases that need to be studied more thoroughly is the formation of a corium pool which could happen during severe accident scenarios. The melted core is a mixture of multiple melted materials, giving the fluid a unique flow structure. Additionally, the presence of high-temperature variations within the corium pool causes an extremely high Rayleigh number for a natural convection flow regime. This unique problem requires significant research efforts;hence, an effort has been put forward to study it numerically. This paper studies a quarter-circular vessel with internal heat generation representing a high-temperature melted core and corresponds to the famous BALI experiments. In this context, a wide range of RANS (Reynolds-Averaged Navier-Stokes) based CFD (Computational Fluid Dynamics) simulations are performed to better understand the complex thermal-hydraulics phenomena in a corium pool. Additionally, a comparative study is performed to assess the prediction capabilities of different RANS models.

关键词： Nuclear Safety Corium Pool Natural Convection Flow CFD RANS

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Integration of a NLP-Based Industrial Robot Programming System 33rd

Integration of a NLP-Based Industrial Robot Programming Syst...

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Makrylakis, Panagiotis Benardos, Panorios Natl Tech Univ Athens Sch Mech Engn Mfg Technol Lab Heroon Polytechniou 9 Athens 15772 Greece

ISBN: (纸本)9783031744815;9783031744822

This paper presents the integration of a Natural Language Processing (NLP) approach with an industrial robot to enable voice control for online programming. This approach initially involves real-time conversion of voice commands into text, utilizing the Microsoft Speech Software Development Kit (SDK). The generated text is processed to extract numerical data corresponding to desired positions and orientations. Subsequently, a machine learning binary classification model is trained to distinguish between robot related and unrelated commands. The recognized commands undergo further keyword-based classification based on a preselected vocabulary of supported robot operations, so that finally the inverse kinematics problem can be solved and the relevant robot program can be generated. A custom graphical user interface (GUI) facilitates user interaction. Two modes are supported, the first for issuing multiple individual commands and the second for programming typical pick-and-place industrial tasks. The obtained results using a 6-DOF Staubli RX90L robot verify the approach's feasibility.

关键词： Online robot programming natural language processing support vector machines word embeddings inverse kinematics

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Estimation of Shoreline Changes Along the Kozhikode Coast Using High-Resolution Remote Sensing 1

引用

2022 International Association for Hydraulic Environmental engineering and Research Asia Pacific Division

作者： Saikrishnan, K. Anand, K., V Agilan, V Natl Inst Technol Calicut Dept Civil Engn Kozhikode India

ISBN: (数字)9789819760091

ISBN: (纸本)9789819760084;9789819760091

The coastal zone is one of the most dynamic environments on earth. Geologic, physical, biologic, and anthropomorphic factors shape and constantly modify the coast. Accurate shoreline data is required to design coastal protection structures, identify vulnerable areas and for coastal developmental plans. The availability of satellite data has helped to generate information about the coastal and marine environment. It is efficient in monitoring the changes taking place in the coastal zone. Remote sensing technology has been used to map and effectively monitor shoreline changes in different locations as it provides long-term data. In the present study, shoreline change analysis is carried out for 10 years (2011-2020) along the Kozhikode coast, a district located in the northern part of Kerala. Satellite images from Cartosat 1 and Resourcesat 2 are used in the study. The shoreline change rate for 10 years is calculated using the end point rate (EPR) method with Digital Shoreline Analysis System (DSAS). Based on the shoreline change rates values obtained from DSAS analysis, the location is classified into 5 classes (high, moderate, low erosion, stable and accreting coast). The shoreline change rate ranges from -30 m/year to 20 m/year along the Kozhikode coast. The analysis shows that 64.6% of the district coast is under erosion and 35.4% of the coast is stable and accreting. Locations of erosions are identified so that proper protective measures can be taken to reduce the rate of erosion along the coast.

关键词： Coastal zone EPR method Remote sensing Supervised classification

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Dynamic Frequency Adjustment and Dispatching for Cloud Computing System with Energy Cost Considerations 1

引用

33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Wu, Ze-Kai Lin, Yen-Ju Yang, Yu-Chieh Wu, Cheng-Hung Natl Taiwan Univ Inst Ind Engn Taipei Taiwan Natl Taiwan Univ Inst Ind Engn Taipei Taiwan Natl Taiwan Univ Dept Business Adm Taipei Taiwan Natl Taiwan Univ Dept Mech Engn Taipei Taiwan

ISBN: (数字)9783031744853

ISBN: (纸本)9783031744846;9783031744853

This research studies the dynamic frequency adjustment and task dispatching problems for cloud computing systems under user demand uncertainties. The objective of the research is to minimize energy consumption and waiting costs. A dynamic programming model is presented to minimize total costs by adjusting CPU frequency dynamically. In this model, we implement real-time job dispatching based on the current state. With the objective of minimizing the total waiting time for tasks. Additionally, the model employs a stochastic process to accurately estimate the transition probability between various events. Backward induction is used to solve the model and make the optimal decision for the different states. Compared with other control methods from the literature, our numerical results show that the proposed method reduces total energy and waiting costs. The improvement is particularly significant when cloud servers and tasks have higher heterogeneity. This approach provides a comprehensive solution to the challenges of cloud computing, balancing performance and cost efficiency.

关键词： Dynamic dispatching Stochastic process Cloud computing

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Text Mining via ChatGPT to Extract Voice of Customer Insights from Twitter Conversational Interactions Dataset 1

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Shahin, Mohammad Maghanaki, Mazdak Chen, F. Frank Hosseinzadeh, Ali Rashidifar, Rasoul Univ Texas San Antonio Dept Mech Engn San Antonio TX 78249 USA

ISBN: (数字)9783031744853

ISBN: (纸本)9783031744846;9783031744853

Traditional Voice of Customer (VoC) extraction techniques often fail to fully grasp the depth and subtlety of customer sentiments. Even though modern Machine Learning (ML) methods have made progress, they still face challenges in accurately interpreting the nuances of digital customer communication. This article aims to show the usefulness of OpenAI's GPT-3.5 Turbo, leveraging its advanced Natural Language Processing (NLP) capabilities for extracting VoC information from online customer support interactions on Twitter. This study demonstrates the effective use of GPT-3.5 Turbo in VoC extraction, highlighting its ability to deeply understand conversational context and process data in a more intuitive manner. The model's extensive, multilingual processing ability also allows for a broader and more inclusive VoC analysis. The findings suggest a significant advancement in VoC analysis, paving the way for more insightful, data-driven customer service strategies and improved decision-making in product development and process enhancement.

关键词： Machine Learning Voice of Customer Natural Language Processing ChatGPT Decision-making

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Tribological Characterization of Aged Mollusc Shells-UHMWPE Biocomposites Manufactured by Hot Compression Molding Process 10th

Tribological Characterization of Aged Mollusc Shells-UHMWPE ...

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10th International Conference on Design and Modeling of mechanical Systems (CMSM)

作者： Sidia, Besma Bensalah, Walid Univ Monastir Natl Engn Sch Monastir Mech Engn Lab LR99ES32 Monastir Tunisia

ISBN: (纸本)9783031650062;9783031650079

This study examined the impact of hygrothermal aging on the tribological properties of biocomposites fabricated by hot compression molding. Mollusc shell particles (MS) are incorporated, at variable weight percentage, into a UHMWPE matrix to create biocomposites. These biocomposites then undergo accelerated hygrothermal aging by immersion in a Ringer's solution at 80 degrees C. The friction and wear behavior of the biocomposites was evaluated using a pin-on-disk tribometer under dry and ambient conditions. The results indicate that hygrothermal aging leads to an improvement in the tribological behavior of the biocomposites and particularly their wear resistance, which is influenced by the amount of MS particles incorporated. The study investigated the wear behavior of the aged biocomposite and proposed a corresponding wear mechanism.

关键词： Hot compression molding aging MS-UHMWPE wear resistance Ringer's solution

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