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1
Buhari, Rosnawati, Munzilah Md Rohani, and Mohd Ezree Abdullah. "Dynamic Load Coefficient of Tyre Forces from Truck Axles." Applied Mechanics and Materials 405-408 (September 2013): 1900–1911. http://dx.doi.org/10.4028/www.scientific.net/amm.405-408.1900.
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This study aims to predict the Dynamic Load Coefficient (DLC) of tyre forces from truck axles. Dynamic Load Coefficient is frequently used to characterise the dynamic loads generated by axles. It is a simple measurement of the dynamic variation magnitude of the axle load, for a specific combination of road roughness and speed. Under normal operating conditions, the DLCs value is typically in the range of 0.05-0.3, and close to zero when the trucks wheels are moving over a perfectly smooth road. To achieve the objectives of this study, which is to determine the DLCs value for seven different types of axles, a simple validated quarter-truck model was excited by a random road surface profile, in order to simulate a vehicle-road interaction. Points are equally spaced along the simulated road to generate dynamic loadings over a broad range of truck speeds. Multiple trucks gross-weight conditions were used to present realistic traffic behaviour. The results showed that irregular road profiles, exciting the vehicle as it travelled, caused continually changing tyre forces. Also, dynamic loading was seen to be fundamentally influenced by the type of suspension (i.e., air and steel), loading condition, and vehicle speed. For example, the DLC value of the tyre forces of the quarter-truck fitted with a steel suspension was found to be more than twice that of the truck fitted with an air suspension. Tyre forces of the one-third laden truck were more aggressive than any other loading condition, due to the uncertain body-bounce generated by the truck, which was strongly dependent on surface irregularities. At low speed, the DLC was greatly decreased if the load was increased. Furthermore, DLC value was always lower for trucks with air suspension over steel suspension, for the same load and vehicle speed. However, air suspension efficiency was clearly better for higher axle loads.
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Wang, Zhenyu, Yan Zhao, Fuqiang Li, and Jianqun Jiang. "Extreme Dynamic Responses of MW-Level Wind Turbine Tower in the Strong Typhoon Considering Wind-Rain Loads." Mathematical Problems in Engineering 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/512530.
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The damage and collapse accidents of wind turbines during violent typhoons and rainstorms have increased in recent years. To determine the dynamic response characteristics of high-power wind turbines under extreme conditions, wind load and rain load are simulated. The typhoon average wind velocity and fluctuating wind velocity are simulated by the unstable wind profile and harmony superposition method. The raindrop size distribution is simulated by the M-P spectrum, and the rain load is calculated according to the momentum theorem. A finite element model is established to study the aerodynamic responses of a wind turbine under random typhoon load and typhoon-rain loads. The maximum displacements and accelerations at the tower top and the maximum von Mises stresses at the tower bottom are calculated and compared after considering various combinations of wind direction deflections and rainfall intensities. The results indicate that instantaneous wind direction deflection has a substantial impact on the dynamic responses of wind turbines, and after introducing the effect of rain, the dynamic responses increase up to 13.7% with increasing rainfall intensities. This study has significant implications for analysing collapse accidents of wind turbines and for optimising the design of wind turbines under extreme typhoon conditions.
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Jiang, Wei, Jieyun Wang, Qianlong Wang, Song Xu, Seiji Hashimoto, and Zhong Liu. "Design and Implementation of a Low-Power Low-Cost Digital Current-Sink Electronic Load ‡." Energies 12, no. 13 (July 7, 2019): 2611. http://dx.doi.org/10.3390/en12132611.
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Electronic load (e-load) is essential equipment for power converter performance test, where a designated load profile is executed. Electronic load is usually implemented with the analog controller for fast tracking of the load profile reference. In this paper, a low-power low-cost electronic load is proposed. MOSFETs (metal-oxide-semiconductor field-effect transistors) are used as the power consumption devices, which are regulated to the active region as controlled current-sink. In order to achieve fast transient response using the low-cost digital signal controller (DSC) PWM peripherals, the interleaving PWM method is proposed to achieve active current ripple mitigation. To obtain the system open-loop gain for current-sink operation, an offline digital system identification method, followed by model reduction, is proposed by applying Pseudo-Random Binary Sequence (PRBS) excitation. Pole-zero cancelation method is used in the control system design and later implemented in a DSC. The prototype is built and tested, in which meaningful testing scenarios under constant current-sink mode, pulse current sink mode, and double line-frequency current mode are verified. The experimental results indicate that the proposed e-load can sink pre-programmed current profile with well-attenuated ripple for static and dynamic load testing, and is applicable to fully digitalized power testing equipment.
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Nassif, Hani H., and Ming Liu. "Analytical Modeling of Bridge-Road-Vehicle Dynamic Interaction System." Journal of Vibration and Control 10, no. 2 (February 2004): 215–41. http://dx.doi.org/10.1177/1077546304033950.
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We present a three-dimensional (3D) dynamic model for the bridge-road-vehicle interaction system. A slab-on-girder bridge is modeled as a grillage system subjected to multiple moving truck loads. Multi-axle semi-tractor-trailer is idealized as a 3D vehicle model with a nonlinear tire-suspension system, having eleven independent degrees of freedom. Road roughness profiles are generated from the random Gaussian process as well as limited measurements of actual road profiles. Truck wheel loads are applied at any point and then transferred to nodes as equivalent nodal forces. The Newmark-\#946; integration method is applied as a numerical algorithm for solving the bridge-road-vehicle dynamic interaction equations. The major parameters affecting the bridge dynamic response (or the dynamic load factor) include road roughness, truck weight, speed and mechanical properties of the tire-suspension system and bridge stiffness and boundary conditions. Results from other dynamic models as well as field tests are compared with those from the current 3D model. The results show that the dynamic load factor is highly dependent on road roughness, vehicle suspension, and bridge geometry.
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Podrubalov, V. K., M. V. Podrubalov, and A. N. Nikitenko. "Applicability of different models of wheel tractor dynamic system for the calculation assessment of its vibration load." Traktory i sel hozmashiny 81, no. 1 (January 15, 2014): 20–25. http://dx.doi.org/10.17816/0321-4443-65657.
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Data concerning vertical vibration levels on an operator’s seat and a wheel suspension deflection calculated using three calculation models of a tractor vibratory system, namely chain three-mass, plain and spatial twelve-mass ones, in the mode of moving on the reference track of random profile are given. Application inadmissibility of the chain model because of inadequacy of vibration level to operational one and possibility of restricted using of the plain model are shown. The spatial model ensures the best convergence to the measured data.
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García, Eduardo Martínez, Marcos García Alberti, and Antonio Alfonso Arcos Álvarez. "Measurement-While-Drilling Based Estimation of Dynamic Penetrometer Values Using Decision Trees and Random Forests." Applied Sciences 12, no. 9 (April 30, 2022): 4565. http://dx.doi.org/10.3390/app12094565.
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Machine learning is a branch of artificial intelligence (AI) that consists of the application of various algorithms to obtain information from large data sets. These algorithms are especially useful to solve nonlinear problems that appear frequently in some engineering fields. Geotechnical engineering presents situations with complex relationships of multiple variables, making it an ideal field for the application of machine learning techniques. Thus, these techniques have already been applied with a certain degree of success to determine such things as soil parameters, admissible load, settlement, or slope stability. Moreover, dynamic penetrometers are a very common type of test in geotechnical studies, and, in many cases, they are used to design the foundation solution. In addition, its continuous nature allows us to know the variations of the terrain profile. The objective of this study was to correlate the drilling parameters of deep foundation machinery (Measurement-While-Drilling, MWD) with the number of blows of the dynamic penetrometer test. Therefore, the drilling logs could be equated with said tests, providing information that can be easily interpreted by a geotechnical engineer and that would allow the validation of the design hypotheses. Decision trees and random forest algorithms have been used for this purpose. The ability of these algorithms to replicate the complex relationships between drilling parameters and terrain characteristics has allowed obtaining a reliable reproduction of the penetrometric profile of the traversed soil.
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Sathishkumar, Palanisamy, Jeyaraj Jancirani, John Dennie, and B. Arun. "Controller Design for Convoluted Air Spring System Controlled Suspension." Applied Mechanics and Materials 592-594 (July 2014): 1025–29. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.1025.
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This paper focuses on the analysis and controlling automotive vibration using semi-active air spring suspension system by implementing fuzzy and Proportional-Integral derivative (PID) controllers for light vehicles. Due to low transmissibility coefficients and their ability to varying the force generated depends on load capacities the air spring is modelled as an actuator. The dynamic behavior of semi active actuator controlled is contrasted with passive suspension under single bump, double bump and random road profile. The performance of air spring controlled suspension has been investigated. Results show that the fuzzy controller gives optimized results.
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Cai, Chun Sheng, Wei Zhang, Lu Deng, and Miao Xia. "Performance Evaluation of Existing Bridges under Vehicle Dynamic Effects." Advanced Materials Research 639-640 (January 2013): 42–53. http://dx.doi.org/10.4028/www.scientific.net/amr.639-640.42.
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This paper summarizes the recent work by the first author’s research group related to the performance evaluation of existing bridges under vehicle dynamic effects. Based on the data from short-term monitoring of existing bridges, a framework to estimate the extreme structure responses from the live load in a mean recurrence interval is developed in the first part. The Gumbel distribution of the extreme values was derived from an extreme value theory and Monte Carlo Simulation. In the second part, a framework of fatigue damage and reliability assessment for existing bridges is presented to include the effects of the progressively deteriorated road conditions and random dynamic vehicle loads in bridge’s life cycle. The random effects of vehicle speed and type, road profiles, and stress ranges are included. Studies have shown that the vehicle-induced dynamic allowance IM value prescribed by the AASHTO LRFD code may be underestimated under poor road surface conditions (RSCs) of some existing bridges. In addition, multiple dynamic stress ranges induced by vehicles cannot be included in the maximum displacement-based dynamic allowance IM values. In the third part of this paper, the reliability indices of a selected group of prestressed concrete girder bridges are calculated by modeling the IM explicitly as a random variable for different RSCs. Nevertheless, a reliability based dynamic amplification factor on stress ranges (DAFS) for fatigue design is proposed to include the fatigue damages from multiple stress range cycles due to each vehicle passage at varied vehicle speeds under various road conditions in the bridge’s life cycle.
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Kropáč, Oldřich, and Peter Múčka. "Classification Scheme for Random Longitudinal Road Unevenness Considering Road Waviness and Vehicle Response." Shock and Vibration 16, no. 3 (2009): 273–89. http://dx.doi.org/10.1155/2009/935858.
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A novel approach to the road unevenness classification based on the power spectral density with consideration of vehicle vibration response and broad interval of road waviness (road elevation PSD slope) is presented. This approach enables transformation of two basic parameters of road profile elevation PSD (unevenness index,C, and waviness,w) into a single-number indicatorCwwhen using a correction factorKwaccounting forw. For the road classification proposal two planar vehicle models (passenger car and truck), ten responses (reflecting ride comfort, dynamic load of road and cargo, ride safety) and three different vehicle velocities have been considered. The minimum of ten estimated vibration response ranges sum for a broad waviness interval typical for real road sections (w= 1.5 to 3.5) has been used for the correction factor estimation. The introduced unevenness indicator,Cw, reflects the vehicle vibration response and seems to be a suitable alternative to the other currently used single-number indicators or as an extension of the road classification according to the ISO 8608: 1995, which is based on constant waviness value,w= 2.
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Fadel Miguel, Letícia Fleck, and Guilherme Piva dos Santos. "Optimization of Multiple Tuned Mass Dampers for Road Bridges Taking into Account Bridge-Vehicle Interaction, Random Pavement Roughness, and Uncertainties." Shock and Vibration 2021 (April 20, 2021): 1–17. http://dx.doi.org/10.1155/2021/6620427.
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Road bridge designs are based on technical standards, which, to date, consider dynamic loading as equivalent static loads. Additionally, the few engineers who perform a dynamic analysis typically do not consider the effects of bridge-vehicle interaction and also simplify the road’s irregularity profile. Moreover, often, even when a simplified dynamic analysis is carried out and shows that there will be a high dynamic amplification factor (DAF), designers prefer to solve this problem by adopting high safety factors and thereby oversizing the bridge, rather than using energy dissipation devices that would allow reducing the amplitude of vibration. In this context, the present work proposes a complete methodology to minimize the dynamic response of road bridges by optimizing multiple tuned mass dampers (MTMD), taking into account the bridge-vehicle interaction, the random profile of pavement irregularities, and the uncertainties present in the coupled system and in the excitation. For illustrative purposes, the coupled vibration problem of a regular truck traveling on a random road profile over a typical Brazilian bridge is analyzed. Three different scenarios for the MTMD are considered. The proposed optimization problem is solved by employing the Whale Optimization Algorithm (WOA). The results showed the excellent ability of the proposed methodology, reducing the bridge’s DAF to acceptable values for all analyzed cases, considering or not the uncertainties present in the system. Furthermore, the results obtained by the proposed methodology are compared with results obtained using classical tuned mass damper (TMD) design methods, showing the best performance of the proposed optimization method. Thus, the proposed method can be employed to optimize MTMD, improving bridge design.
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Carreno, Alvaro, Marcelo Perez, Carlos Baier, Alex Huang, Sanjay Rajendran, and Mariusz Malinowski. "Configurations, Power Topologies and Applications of Hybrid Distribution Transformers." Energies 14, no. 5 (February 24, 2021): 1215. http://dx.doi.org/10.3390/en14051215.
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Distribution systems are under constant stress due to their highly variable operating conditions, which jeopardize distribution transformers and lines, degrading the end-user service. Due to transformer regulation, variable loads can generate voltage profiles out of the acceptable bands recommended by grid codes, affecting the quality of service. At the same time, nonlinear loads, such as diode bridge rectifiers without power factor correction systems, generate nonlinear currents that affect the distribution transformer operation, reducing its lifetime. Variable loads can be commonly found at domiciliary levels due to the random operation of home appliances, but recently also due to electric vehicle charging stations, where the distribution transformer can cyclically vary between no-load, rated and overrated load. Thus, the distribution transformer can not safely operate under highly-dynamic and stressful conditions, requiring the support of alternative systems. Among the existing solutions, hybrid transformers, which are composed of a conventional transformer and a power converter, are an interesting alternative to cope with several power quality problems. This article is a review of the available literature about hybrid distribution transformers.
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Belhorma, Mohamed, and Aboubakar Seddik Bouchikhi. "Multi-Objective Optimisation of the Electric Wheelchair Ride Comfort and Road Holding Based on Jourdain’s Principle Model and Genetic Algorithm." Acta Mechanica et Automatica 16, no. 1 (January 1, 2022): 58–69. http://dx.doi.org/10.2478/ama-2022-0008.
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Abstract The paper addresses the multi-body modelling of an electric wheelchair using Jourdain’s principle. First, a description of the adopted approach was presented. Next, the mathematical equations were developed to obtain the dynamic behaviour of the concerned system. The numerical computation was performed with MATLAB (matrix laboratory: a high performance language of technical computing) and validated by MBD (Multi-Body Dynamics) for Ansys, a professional multi-body dynamics simulation software powered by RecurDyn. Afterwards, the model was treated as an objective function included in genetic algorithm. The goal was to improve the ride quality and the road holding as well as the suspension workspace. The multi-objective optimisation aimed to reduce the Root-Mean-Square (RMS) of the seat’s vertical acceleration, the wheels load and the workspace modulus by varying the bodies’ masses, the spring-damper coefficients and the characteristics of the tires. Acceptable solutions were captured on the Pareto fronts, in contrast to the relatively considerable processing time involved in the use of a random road profile generated by the power spectral density (PSD). During the process, the compatibility and the efficiency of Jourdain’s equations were inspected.
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Goenaga, Boris Jesús, Luis Guillermo Fuentes Pumarejo, and Otto Andrés Mora Lerma. "Evaluation of the methodologies used to generate random pavement profiles based on the power spectral density: An approach based on the International Roughness Index." Ingeniería e Investigación 37, no. 1 (January 1, 2017): 49. http://dx.doi.org/10.15446/ing.investig.v37n1.57277.
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The pavement roughness is the main variable that produces the vertical excitation in vehicles. Pavement profiles are the main determinant of (i) discomfort perception on users and (ii) dynamic loads generated at the tire-pavement interface, hence its evaluation constitutes an essential step on a Pavement Management System. The present document evaluates two specific techniques used to simulate pavement profiles; these are the shaping filter and the sinusoidal approach, both based on the Power Spectral Density. Pavement roughness was evaluated using the International Roughness Index (IRI), which represents the most used index to characterize longitudinal road profiles. Appropriate parameters were defined in the simulation process to obtain pavement profiles with specific ranges of IRI values using both simulation techniques. The results suggest that using a sinusoidal approach one can generate random profiles with IRI values that are representative of different road types, therefore, one could generate a profile for a paved or an unpaved road, representing all the proposed categories defined by ISO 8608 standard. On the other hand, to obtain similar results using the shaping filter approximation a modification in the simulation parameters is necessary. The new proposed values allow one to generate pavement profiles with high levels of roughness, covering a wider range of surface types. Finally, the results of the current investigation could be used to further improve our understanding on the effect of pavement roughness on tire pavement interaction. The evaluated methodologies could be used to generate random profiles with specific levels of roughness to assess its effect on dynamic loads generated at the tire-pavement interface and user’s perception of road condition.
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Buhari, Rosnawati, and Ac Collop. "Pavement Primary Response Using Influence Function and Peak Influence Function." Applied Mechanics and Materials 256-259 (December 2012): 1871–81. http://dx.doi.org/10.4028/www.scientific.net/amm.256-259.1871.
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It was identified in previous research that errors in theoretical damage much associated with the influence function calculation. Thus, this paper present the efficient prediction of primary response due to dynamic vehicle loading using influence function and peak influence function approach. In order to provide the realistic loading condition, dynamic road response model with idealised loads representative by mathematical quarter-truck model with two degree of freedom was excited by a random road surface profile which equally spaced points along the simulated road with various different speeds. Consequently, the simplified computational approach (peak influence function method) was identified only a few points gave a small different compare with the influence function method for along the longitudinal distance. In order to identify the impact of both methods, further implementation was done to calculate fatigue damage (horizontal tensile strain at the bottom of a bound layer) or rutting damage (vertical compressive strain at the top of the subgrade layer) predicted by constant load moving at varies speed. It was found that the differences in response are particularly small and increased steadily as the increasing of the vehicle speed. It was conclude that the simplify calculation was able to predict stresses and strains sufficiently accurately and identified relatively small errors into the pavement damage prediction. Hence the simplification in particular much reduced the computation time sufficiently and minimized the computer resources significantly.
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Dekker, S., G. Wurzel, and R. Alderliesten. "Reliability modelling for rotorcraft component fatigue life prediction with assumed usage." Aeronautical Journal 120, no. 1232 (July 8, 2016): 1658–92. http://dx.doi.org/10.1017/aer.2016.79.
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ABSTRACTFatigue life is a random variable. Thus, the reliability of a conservative fatigue life prediction for a component in the helicopter dynamic system needs to be substantiated. A standard analytical substantiation method uses averaged manoeuvre loads instead of seeing manoeuvre loads as a random variable whose distribution is estimated with limited precision. This simplification may lead to inaccuracies. A new simulation-based method is developed to conservatively predict fatigue life, while also accounting for the full random distribution and uncertainty of manoeuvre loads. Both methods fully account for uncertain fatigue strength but assume that the mission profile is known or can at least be conservatively estimated. Simulations under synthetic but realistic engineering conditions demonstrate that both methods may be used for accurate substantiation of conservative fatigue life predictions. The simulations also demonstrate that, under the tested conditions, uncertainties from manoeuvre loads may be neglected in fatigue life substantiations as the resulting error is not significant with respect to uncertainties in component fatigue strength.
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Hatalis, Kostas, Chengbo Zhao, Parv Venkitasubramaniam, Larry Snyder, Shalinee Kishore, and Rick S. Blum. "Modeling and Detection of Future Cyber-Enabled DSM Data Attacks." Energies 13, no. 17 (August 21, 2020): 4331. http://dx.doi.org/10.3390/en13174331.
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Demand-Side Management (DSM) is an essential tool to ensure power system reliability and stability. In future smart grids, certain portions of a customer’s load usage could be under the automatic control of a cyber-enabled DSM program, which selectively schedules loads as a function of electricity prices to improve power balance and grid stability. In this scenario, the security of DSM cyberinfrastructure will be critical as advanced metering infrastructure and communication systems are susceptible to cyber-attacks. Such attacks, in the form of false data injections, can manipulate customer load profiles and cause metering chaos and energy losses in the grid. The feedback mechanism between load management on the consumer side and dynamic price schemes employed by independent system operators can further exacerbate attacks. To study how this feedback mechanism may worsen attacks in future cyber-enabled DSM programs, we propose a novel mathematical framework for (i) modeling the nonlinear relationship between load management and real-time pricing, (ii) simulating residential load data and prices, (iii) creating cyber-attacks, and (iv) detecting said attacks. In this framework, we first develop time-series forecasts to model load demand and use them as inputs to an elasticity model for the price-demand relationship in the DSM loop. This work then investigates the behavior of such a feedback loop under intentional cyber-attacks. We simulate and examine load-price data under different DSM-participation levels with three types of random additive attacks: ramp, sudden, and point attacks. We conduct two investigations for the detection of DSM attacks. The first studies a supervised learning approach, with various classification models, and the second studies the performance of parametric and nonparametric change point detectors. Results conclude that higher amounts of DSM participation can exacerbate ramp and sudden attacks leading to better detection of such attacks, especially with supervised learning classifiers. We also find that nonparametric detection outperforms parametric for smaller user pools, and random point attacks are the hardest to detect with any method.
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Duy, Le Dinh. "AN INVESTIGATION OF A TWO-STAGE ASYMMETRIC DAMPER’ EFFECT ON THE RIDE COMFORT OF AN INNER-CITY BUS BY USING 3-DOFS VEHICLE MODEL SUBJECTED TO RANDOM ROAD PROFILES." JOURNAL OF TECHNOLOGY & INNOVATION 2, no. 2 (2022): 41–47. http://dx.doi.org/10.26480/jtin.02.2022.41.47.
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The effect of the asymmetric damper on the vertical acceleration of the driver’s body, suspension deflection and tire dynamic load were studied thoroughly in order to provide suggestions for choosing damping parameters while building a bus’s suspension system. The vehicle model with three DOFs exposed to random road profiles was employed to investigate the dynamic responses for both two cases of linear symmetric and two-stage asymmetric dampers. The investigation was carried out in the time domain by simulation, then the root-mean-square of oscillatory parameters was calculated and examined by using a program made in the MATLAB software. The results of the analysis show that a two-stage asymmetric damper ensures good oscillatory comfort of the driver but provides less handling stability of the bus when compared to a linear symmetric one.
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Tung, Nguyen Thanh, and Luong Van Van. "A study on the vibration of a bus with air suspension system moving on random road surface profiles with different speeds." Engineering Solid Mechanics 11, no. 2 (2023): 119–24. http://dx.doi.org/10.5267/j.esm.2023.1.004.
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This paper presents the results of research on the vibration of the Hyundai Universe bus using an air suspension system and mechanical suspension system when it is run at different speeds on random road surface profiles according to ISO 8608:2016. The research results show that the used air suspension system ensures smooth movement and dynamic safety according to TCVN 6964:2008 (ISO 2631:2003) and VDI 2057:2017 standards. The maximum vehicle speeds on different road classes varied from 105km/h to 65km/h. A vehicle with an air suspension system provided a smaller root mean square of vibration acceleration RMS(Z) than a vehicle with a mechanical suspension system. The root means square of the wheel load RMS(Fz) of a vehicle with an air suspension system is about 99.6% of that of a vehicle with a mechanical suspension system.
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Lozia, Zbigniew. "Application of Modelling and Simulation in Durability Tests of Vehicles and Their Components." Energies 15, no. 24 (December 12, 2022): 9398. http://dx.doi.org/10.3390/en15249398.
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The use of simulation and modelling has been proposed for determining the excitations to be applied in the procedures of laboratory testing of a car’s structural components, without the need to test the complete vehicle. The paper presents the general concept as well as an example of the procedure. It covers determining the spectrum and time-domain realization of a load on a selected node of the vehicle structure under durability tests. The author used both the mathematical and physical model of the tractor-semitrailer unit, where the input was considered as a random process resulting from the road profile. He calculated the transmittance modules and the power spectral densities of the vertical force on the joint between the tractor’s fifth wheel and the kingpin of the semitrailer and the extreme values of the dynamic components of this force. The inverse discrete Fourier transform makes it possible to generate the realization of the said force. It can be used in durability studies. The limitation of the work to the testing of a specific structural node reduces the scope and, in consequence, the cost of the process. The method presented may also be used for various types of vehicle models, including hybrid and electric vehicles.
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Muriithi, Grace, and Sunetra Chowdhury. "Optimal Energy Management of a Grid-Tied Solar PV-Battery Microgrid: A Reinforcement Learning Approach." Energies 14, no. 9 (May 8, 2021): 2700. http://dx.doi.org/10.3390/en14092700.
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In the near future, microgrids will become more prevalent as they play a critical role in integrating distributed renewable energy resources into the main grid. Nevertheless, renewable energy sources, such as solar and wind energy can be extremely volatile as they are weather dependent. These resources coupled with demand can lead to random variations on both the generation and load sides, thus complicating optimal energy management. In this article, a reinforcement learning approach has been proposed to deal with this non-stationary scenario, in which the energy management system (EMS) is modelled as a Markov decision process (MDP). A novel modification of the control problem has been presented that improves the use of energy stored in the battery such that the dynamic demand is not subjected to future high grid tariffs. A comprehensive reward function has also been developed which decreases infeasible action explorations thus improving the performance of the data-driven technique. A Q-learning algorithm is then proposed to minimize the operational cost of the microgrid under unknown future information. To assess the performance of the proposed EMS, a comparison study between a trading EMS model and a non-trading case is performed using a typical commercial load curve and PV profile over a 24-h horizon. Numerical simulation results indicate that the agent learns to select an optimized energy schedule that minimizes energy cost (cost of power purchased from the utility and battery wear cost) in all the studied cases. However, comparing the non-trading EMS to the trading EMS model operational costs, the latter one was found to decrease costs by 4.033% in summer season and 2.199% in winter season.
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Gomes, Herbert Martins. "Multi-objective optimization of quarter car passive suspension design in the frequency domain based on PSO." Engineering Computations 33, no. 5 (July 4, 2016): 1422–34. http://dx.doi.org/10.1108/ec-01-2015-0021.
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Purpose – The purpose of this paper is to investigate the optimum design of a quarter car passive suspension system using a particle swarm optimization algorithm in order to minimize the applied loads and vibrations. Design/methodology/approach – The road excitation is assumed as zero-mean random field and modeled by single-sided power spectral density (PSD) based on international standard ISO 8608. The variance of sprung mass displacements and variance of dynamic applied load are evaluated by PSD functions and used as cost function for the optimization. Findings – The advantages in using this methodology are emphasized by an example of the multi-objective optimization design of suspension parameters and the results are compared with values reported in the literature and other gradient based and heuristic algorithms. The paper shows that the algorithm effectively leads to reliable results for suspension parameters with low computational effort. Research limitations/implications – The procedure is applied to a quarter car passive suspension design. Practical implications – The proposed procedure implies substantial time savings due to frequency domain analysis. Social implications – The paper proposes a procedure that allows complex optimization designs to be feasible and cost effective. Originality/value – The design optimization is performed in the frequency domain taking into account standard defined road profiles PSD without the need to simulate in the time domain.
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Hao, Qiang, Jian Yin, Yu Liu, Lu Jin, Shengfang Zhang, and Zhihua Sha. "Time-Varying Wear Calculation Method for Fractal Rough Surfaces of Friction Pairs." Coatings 13, no. 2 (January 25, 2023): 270. http://dx.doi.org/10.3390/coatings13020270.
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For the wear problem of the real rough surface during sliding friction, based on fractal theory and Hertz contact theory, a 3-D fractal rough surface with random characteristics is constructed, and the relationship between the wear deformation depth of the rough peak and its real contact area during the wear process is derived. Furthermore, considering the peak wear and pit scratch phenomena of rough surfaces in different contact states, the time-varying wear calculation model of the worn surface and the compensation wear calculation model of the unworn surface are established, respectively, and the relationship between the instantaneous wear amount and the dynamic change in the rough surface topography is comprehensively characterized. Combined with image digitization technology, the 3-D rough surface is converted into a 2-D discrete plane with 3-D information. According to the dynamic real-time update of the graph data, the iterative calculation of the wear cycle is completed, the time-varying wear calculation method for fractal rough surfaces of friction pairs is proposed, and the dynamic change in the wear amount and surface topography of the rough surface is simulated. The simulation results are experimentally verified and the influence of friction parameters on the surface topography is analyzed. The results show that after the wear simulation, the profile height of the rough surface is reduced, and the average wear depth is 0.02 mm. Increases in rotational speeds and external loads can exacerbate surface wear, surface topography tends to be flattened, and surface carrying capacity increases. This provides theoretical guidance for the development and manufacture of friction pairs.
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Sengupta, D., and A. Datta. "Validation of optimal electric vehicle charging station allotment on IEEE 15-bus system." Electrical Engineering & Electromechanics, no. 3 (June 23, 2021): 68–73. http://dx.doi.org/10.20998/2074-272x.2021.3.11.
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Introduction. The diminishing conventional energy resources and their adverse environmental impacts compelled the researchers and industries to move towards the nonconventional energy resources. Consequently, a drastic paradigm shift is observed in the power and transportation sectors from the traditional fossil fuel based to the renewable energy-based technologies. Considering the proliferation of electric vehicles, the energy companies have been working continuously to extend electric vehicle charging facilities. Problem. Down the line, the inclusion of electric vehicle charging stations to the electric grid upsurges the complication as charging demands are random in nature all over the grid, and in turn, an unplanned electric vehicle charging station installation may cause for the system profile degradation. Purpose. To mitigate the problem, optimum allocation of the charging stations in existing power distribution system in a strategic manner is a matter of pronounced importance in maintaining the system stability and power quality. In this paper, optimum allocation of electric vehicle charging stations in IEEE 15-bus system is studied in order to minimize the highest over and under voltage deviations. Methodology. Primarily, voltage stability analysis is carried out for identification of the suitable system nodes for the integration. Voltage sensitivity indices of all the system nodes are calculated by introducing an incremental change in reactive power injection and noting down the corresponding change in node voltage for all nodes. Henceforth, dynamic load-flow analysis is performed using a fast and efficient power flow analysis technique while using particle swarm optimization method in finding the optimal locations. Results. The results obtained by the application of the mentioned techniques on IEEE 15-bus system not only give the optimum feasible locations of the electric vehicle charging stations, but also provide the maximum number of such charging stations of stipulated sizes which can be incorporated while maintaining the voltage profile. Originality. The originality of the proposed work is the development of the objective function; voltage stability analysis; power flow analysis and optimization algorithms. Practical value. The proposed work demonstrates the detailed procedure of optimum electric vehicle charging station allotment. The experimental results can be used for the subsequent execution in real field.
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Kooman, Jeroen P., Len A. Usvyat, Marijke J. E. Dekker, Dugan W. Maddux, Jochen G. Raimann, Frank M. van der Sande, Xiaoling Ye, Yuedong Wang, and Peter Kotanko. "Cycles, Arrows and Turbulence: Time Patterns in Renal Disease, a Path from Epidemiology to Personalized Medicine?" Blood Purification 47, no. 1-3 (November 16, 2018): 171–84. http://dx.doi.org/10.1159/000494827.
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Patients with end-stage renal disease (ESRD) experience unique patterns in their lifetime, such as the start of dialysis and renal transplantation. In addition, there is also an intricate link between ESRD and biological time patterns. In terms of cyclic patterns, the circadian blood pressure (BP) rhythm can be flattened, contributing to allostatic load, whereas the circadian temperature rhythm is related to the decline in BP during hemodialysis (HD). Seasonal variations in BP and interdialytic-weight gain have been observed in ESRD patients in addition to a profound relative increase in mortality during the winter period. Moreover, nonphysiological treatment patters are imposed in HD patients, leading to an excess mortality at the end of the long interdialytic interval. Recently, new evidence has emerged on the prognostic impact of trajectories of common clinical and laboratory parameters such as BP, body temperature, and serum albumin, in addition to single point in time measurements. Backward analysis of changes in cardiovascular, nutritional, and inflammatory parameters before the occurrence as hospitalization or death has shown that changes may already occur within months to even 1–2 years before the event, possibly providing a window of opportunity for earlier interventions. Disturbances in physiological variability, such as in heart rate, characterized by a loss of fractal patterns, are associated with increased mortality. In addition, an increase in random variability in different parameters such as BP and sodium is also associated with adverse outcomes. Novel techniques, based on time-dependent analysis of variability and trends and interactions of multiple physiological and laboratory parameters, for which machine-learning approaches may be necessary, are likely of help to the clinician in the future. However, upcoming research should also evaluate whether dynamic patterns observed in large epidemiological studies have relevance for the individual risk profile of the patient.
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Cho, Yong Jun. "Nonlinear Destructive Interaction between Wind and Wave Loads Acting on the Substructure of the Offshore Wind Energy Converter: A Numerical Study." Journal of Marine Science and Engineering 8, no. 12 (December 7, 2020): 999. http://dx.doi.org/10.3390/jmse8120999.
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Even though the offshore wind industry’s growth potential is immense, the offshore wind industry is still suffering from problems, such as the large initial capital requirements. Many factors are involved, and among these, the extra costs incurred by the conservative design of offshore wind energy converters can be quickly addressed at the design stage by accounting for the nonlinear destructive interaction between wind and wave loads. Even when waves approach offshore wind energy converters collinearly with the wind, waves and wind do not always make the offshore wind energy converter’s substructure deformed. These environmental loads can intermittently exert a force of resistance against deformation due to the nonlinear destructive interaction between wind and wave loads. Hence, the nonlinear destructive interaction between wave and wind loads deserves much more attention. Otherwise, a very conservative design of offshore wind energy converters will hamper the offshore wind energy industry’s development, which is already suffering from enormous initial capital expenditures. In this rationale, this study numerically simulates a 5 MW offshore wind energy converter’s structural behavior subject to wind and random waves using the dynamic structural model developed to examine the nonlinear destructive interaction between wind and wave loads. Numerical results show that the randomly fluctuating water surface as the wind blows would restrict the offshore wind energy converter’s substructure’s deflection. Nonuniform growth of the atmospheric boundary layer due to the wavy motions at the water surface as the wind blows results in a series of hairpin vortices, which lead to the development of a large eddy out of hairpin vortices swirling in the direction opposite to the incoming wind near the atmospheric boundary layer. As a result, the vertical profile of the longitudinal wind velocity is modified; the subsequent energy loss drastically weakens the wind velocity, which consequently leads to the smaller deflection of the substructure of the offshore wind energy converter by 50% when compared with that in the case of wind with gusts over a calm sea.
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Ghosh, Bhaskar, and S. Muthukrishnan. "Dynamic Load Balancing by Random Matchings." Journal of Computer and System Sciences 53, no. 3 (December 1996): 357–70. http://dx.doi.org/10.1006/jcss.1996.0075.
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Rahmani, N., and M. Mostefai. "Multi-Objective MPSO/GA Optimization of an Autonomous PV-Wind Hybrid Energy System." Engineering, Technology & Applied Science Research 12, no. 4 (August 7, 2022): 8817–24. http://dx.doi.org/10.48084/etasr.4877.
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This article presents a study of the energy efficiency and the optimal sizing of an autonomous hybrid energy system (PV-wind-battery) as a power source for a typical household in an isolated village in Adrar, Algeria using the multi-objective Particle Swarm Optimization (MPSO) algorithm and Genetic Algorithm (GA). This study presents a new approach to obtain an optimal configuration and sizing of the main components integrated into the autonomous hybrid system (PV/wind) which meets the requirements of the desired system. In the first phase, the reliability criterion (LPSP) is met with the lowest Energy Cost (EC) value (min Total Net Present Cost (TNPC)). The required storage bank must have a low rate of aging in order to extend the battery life, which contributes to the reduction of the overall cost of the system. Due to the inability to meet the needs demanded by random load profiles, we have incorporated a complementary approach to home insulation to significantly improve energy efficiency. In order to improve the thermal comfort of the house and reduce the energy consumed by air conditioning and heating, a thermal and energy study on this house has been evaluated using TRNSYS 18 simulation software for the overall thermal and energy behavior of a habitat and its environment in dynamic regime. The simulation results show that the thermal insulation of the walls reduces energy consumption by 13.39% in the case of heating and by 10% in the case of air conditioning. Assuming a 10% decrease in energy needs for heating and air conditioning, we observe its positive effect on optimizing the battery lifetime.
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Chen, Gang, Dianxing Hu, Ensong Guo, Bin Yang, Xu Qin, Yu Fu, Junpeng Fan, et al. "Potential indicators in circulating cell-free DNA for monitoring PARP inhibitor resistance in high-grade serous ovarian cancer." Journal of Clinical Oncology 40, no. 16_suppl (June 1, 2022): 5564. http://dx.doi.org/10.1200/jco.2022.40.16_suppl.5564.
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5564 Background: Although the clinical application of PARP inhibitors (PARPis) has brought great survival benefits to patients with high-grade serous ovarian carcinoma (HGSOC), its resistance has gradually become a major challenge for clinicians with the widespread use of PARPis. Unfortunately, there are no effective, non-invasive means for monitoring PARPis resistance in time during maintain therapy. Methods: We collected peripheral blood samples (n = 37) from 37 healthy subjects and a series of longitudinal peripheral blood samples (n = 61) of 25 platinum-sensitive HGSOC patients undergoing Olaparib maintenance therapy. The genome of white blood cell and cfDNA in plasma was extracted for germline and somatic mutation detection by Circular Ligation Amplification and sequencing (CLAmp-seq) based on a targeted 42-gene panel, respectively. Before cfDNA mutation analysis, background noise introduced by random NGS error was removed and clonal hematopoietic mutations were filtered. Variant-supporting reads > 2 and without germline mutations were defined as the criterion for somatic mutations. Progression-free survival (PFS) was collected through regular follow-up. We analyzed the dynamic changes of cfDNA mutation profiles, the correlation between cfDNA mutations and the prognosis of patients, and screened specific mutation sites that closely associated with Olaparib resistance. Results: The elevation of maximum mutant allele frequency (Max MAF) in cfDNA during Olaparib maintenance therapy predicted a poor prognosis of patients ( P = 0.0043). Pathogenic germline mutations in BRCA1/2 or RAD51 were strongly associated with longer PFS ( P = 0.0229) and acquired new MRE11A mutations significantly shortened the PFS in patients ( P = 0.0005). Dynamic fluctuations of somatic mutation sites in CHEK2:p.K373E ( P = 0.0091) and CHEK2:p.R406H ( P = 0.0002) can be used to evaluate the therapeutic efficacy of patients. Remarkably, MRE11A:p.K464R may be a vital driving factor of Olaparib resistance and all patients who acquired new MRE11A:p.K464R in post-treatment cfDNA developed resistance to Olaparib and had significantly shorter PFS than those without it ( P = 0.0005). Besides, the combination of CHEK2:p.R406H and acquired new MRE11A:p.K464R in post-treatment improved the predictive efficiency of patients’ prognosis compared with them alone ( P < 0.0001). Conclusions: Olaparib resistance was robustly associated with the mutation load of tumor cells, and analysis of mutation profiles in cfDNA can be accurately monitor the status of Olaparib resistance in patients with HGSOC. Acquired new MRE11A:p.K464R may be a vital driver of Olaparib resistance and is expected to be a target for anti-tumor drug development.
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Li, Qian, Jun Qing Liu, and Hong Liu. "Random Dynamic Response Analysis of Asphalt Pavement Based on the Vehicle-Pavement Interaction." Applied Mechanics and Materials 744-746 (March 2015): 1288–97. http://dx.doi.org/10.4028/www.scientific.net/amm.744-746.1288.
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In order to analyze the dynamic response of asphalt pavement under vehicle load, the random characteristic of pavement roughness was considered and the vehicle was simplified into 1/2 model with four freedom degrees when establishing the dynamic load model. Then the sequence of the random dynamic load coefficient was obtained by developing a MATLAB program based on the incremental Newmark-β method. Based on the plane strain assumption, a two-dimensional layered finite element model of asphalt pavement was established by ABAQUS software. Then the dynamic load coefficient was used to modify tire pressure that would be applied on the ABAQUS model. Then dynamic response rule of the model and how it was effected by vehicle speed were studied under random load. The results show that under the condition of random load, dynamic response of the pavement structure exhibiting a fluctuation trend as vehicle speed increases and the dynamic response characteristics of each point is different.
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Wang Zheng and Xie Liyang. "Dynamic Reliability Model of Components Under Random Load." IEEE Transactions on Reliability 57, no. 3 (September 2008): 474–79. http://dx.doi.org/10.1109/tr.2008.928184.
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Gao, Peng, and Liyang Xie. "Reliability Evaluation Based on Different Distributions of Random Load." Scientific World Journal 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/415327.
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The reliability models of the components under the nonstationary random load are developed in this paper. Through the definition of the distribution of the random load, it can be seen that the conventional load-strength interference model is suitable for the calculation of the static reliability of the components, which does not reflect the dynamic change in the reliability and cannot be used to evaluate the dynamic reliability. Therefore, by developing an approach to converting the nonstationary random load into the random load whose pdf is the same at each moment when the random load applies, the reliability model based on the longitudinal distribution is derived. Moreover, through the definition of the transverse standard load and the transverse standard load coefficient, the reliability model based on the transverse distribution is derived. When the occurrence of the random load follows the Poisson process, the dynamic reliability models considering the strength degradation are derived. These models take the correlation between the random load and the strength into consideration. The result shows that the dispersion of the initial strength and that of the transverse standard load coefficient have great influences on the reliability and the hazard rate of the components.
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Lee, Chinwai, Hsiang Hsi Lin, Fred B. Oswald, and Dennis P. Townsend. "Influence of Linear Profile Modification and Loading Conditions on The Dynamic Tooth Load and Stress of High-Contact-Ratio Spur Gears." Journal of Mechanical Design 113, no. 4 (December 1, 1991): 473–80. http://dx.doi.org/10.1115/1.2912807.
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This paper presents a computer simulation for the dynamic response of high-contact-ratio spur gear transmissions. High contact ratio gears have the potential to produce lower dynamic tooth loads and minimum root stress but they can be sensitive to tooth profile errors. The analysis presented in this paper examines various profile modifications under realistic loading conditions. The effect of these modifications on the dynamic load (force) between mating gear teeth and the dynamic root stress is presented. Since the contact stress is dependent on the dynamic load, minimizing dynamic loads will also minimize contact stresses. This paper shows that the combination of profile modification and the applied load (torque) carried by a gear system has a significant influence on gear dynamics. The ideal modification at one value of applied load will not be the best solution for a different load. High-contact-ratio gears were found to require less modification than standard low-contact-ratio gears. High-contact-ratio gears are more adversely affected by excess modification than by under modification. In addition, the optimal profile modification required to minimize the dynamic load (hence the contact stress) on a gear tooth differs from the optimal modification required to minimize the dynamic root (bending) stress. Computer simulation can help find the design tradeoffs to determine the best profile modification to satisfy the conflicting constraints of minimizing both the load and root stress in gears which must operate over a range of applied loads.
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Moraes, Luciene S., José C. A. Cintra, and Nelson Aoki. "Dynamic Plate Load Tests." Soils and Rocks 30, no. 2 (May 1, 2007): 113–22. http://dx.doi.org/10.28927/sr.302113.
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Dynamic load test is often used for bearing capacity evaluation of driven pile foundation. It is also reported the successful use of this test in bored piles and caissons. This research is mainly concerned with the adaptation, performance and interpretation of the dynamic load test in circular steel plate aiming at the verification of the bearing capacity of shallow foundations. The dynamic increasing energy test (DIET) was used. The tests were performed at the USP/São Carlos experimental foundation site, which soil profile consists of superficial unsaturated, porous and collapsible soil, and for that reason matric suction’s measurements were made, since it has strong influence on the bearing capacity. It could be verified that it is possible to make use of the dynamic load test to plates, associated with analysis methods based on the stress propagation in bars (wave equation), to infer the plate-soil system bearing capacity. Good adjustments were found from dynamic and static load tests performed in a plate tested in this research field. It was also verified that the plate penetration into the soil caused an important increase in the plate-soil system bearing capacity.
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Thomas, P. C., Shinosh Mathew, and Bobin K. Mathew. "Random Furrowing for a Stochastic Unit Commitment Solution." Engineering World 5 (November 6, 2023): 125–37. http://dx.doi.org/10.37394/232025.2023.5.14.
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The Unit Commitment Problem involves the inherent difficulty of obtaining optimal combinatorial power generation schedules over a future short term period. The formulation of the generalized Unit Commitment Schedule formulation involves the specific combination of generation units at several de-rated capacities during each hour of the planning horizon, the load demand profile, load indeterminateness and several other operating constraints. This largely deterministic schedule continues to find favor with several plant operators, keeping in mind the close operating time-periods involved. However, the deterministic nature of the load profile is sought to be phased out by a stochastic pattern that is realistic and mirrors real-life situations, owing to modern trends in Demand side management. This shift is in tune with the ongoing power restructuring activities of electricity power reforms. The stochastic profile is obtained by a suitably tuned 2-parameter Weibull distribution that uses appropriate shape and scale parameters. The resulting band of generated load profiles are used to evaluate net power and penal costs associated with a set of pervasive randomized probability indices. The exact UCS comprises of a specific unit absolute state corresponding to a certain time period within the planning horizon. Subsequently, regression analysis is applied to establish the correlation between the absolute states and the cumulative randomized load demand against the intervals within the planning horizon. This method is analogous to random furrowing of probabilistic demand profile.
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Liu, Ming, and Hui Mei Zhang. "Dynamic Reliability of Stochastic Truss Structures under Random Load." Applied Mechanics and Materials 525 (February 2014): 218–21. http://dx.doi.org/10.4028/www.scientific.net/amm.525.218.
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Aim at the dynamic reliability of stochastic truss structures under stationary random excitation. In consideration of the randomness of structural physical parameters and the geometric parameters and the random excitations were first transformed into sinusoidal ones in terms of the pseudo excitation method ( PEM) , that turned the joint-random problem into a single random problem for which only structural parameters remain random, and thus the analysis is greatly simplified. The mean value and the variance of the mean square value of the structural displacement and velocity were computed by using the theory of spectral analysis. And then the expressions of stochastic truss structural dynamic reliability were educed from the Poisson formula. Finally, the influence of the randomness of structural parameters on the structural dynamic reliability was analyzed by an example; the method of this paper was proved feasible and available comparing with the Monte Carlo method.
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Chatti, Karim, and Doseung Lee. "Development of New Profile-Based Truck Dynamic Load Index." Transportation Research Record: Journal of the Transportation Research Board 1806, no. 1 (January 2002): 149–59. http://dx.doi.org/10.3141/1806-17.
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Gao, Peng, Liyang Xie, and Wei Hu. "Reliability and Random Lifetime Models of Planetary Gear Systems." Shock and Vibration 2018 (September 12, 2018): 1–12. http://dx.doi.org/10.1155/2018/9106404.
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Conventional reliability models of planetary gear systems are mainly static. In this paper, dynamic reliability models and random lifetime models of planetary gear systems are developed with dynamic working mechanism considered. The load parameters, the geometric parameters, and the material parameters are taken as the inputs of the reliability models and the random lifetime models. Moreover, failure dependence and dynamic random load redistributions are taken into account in the models. Monte Carlo simulations are carried out to validate the proposed models. The results show that the randomness of the load distribution is obvious in the system working process. Failure dependence has significant influences on system reliability. Moreover, the dispersion of external load has great impacts on the reliability, lifetime distribution, and redundancy of planetary gear systems.
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Zhang, Li Ping, and Li Xin Guo. "The Vehicle Dynamic Load Indentification under the Excitation of Random Road Surface." Advanced Materials Research 299-300 (July 2011): 255–59. http://dx.doi.org/10.4028/www.scientific.net/amr.299-300.255.
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In this paper, inverse pseudo excitation method for vehicle dynamic load identification is used. When the vehicle is in stationary random vibration, the vehicle dynamic load spectrum recognition problem is solved by using the deterministic method. The auto-PSD and cross-PSD of vehicle vibration response is known. Base on the reversing the power spectrum of road excitation, Vehicle dynamic load PSD is obtained. The results show that, Inverse pseudo excitation method for solving the vehicle dynamic load spectrum has good solution accuracy, put forward new ideas and methods for vehicle engineering practice, and has broad application prospects.
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MAHAPATRA, NIHAR R., and SHANTANU DUTT. "RANDOM SEEKING: A GENERAL, EFFICIENT, AND INFORMED RANDOMIZED SCHEME FOR DYNAMIC LOAD BALANCING." International Journal of Foundations of Computer Science 11, no. 02 (June 2000): 231–46. http://dx.doi.org/10.1142/s0129054100000144.
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We propose a completely general, informed randomized dynamic load balancing method called random seeking (RS) suitable for parallel algorithms with characteristics found in many search algorithms used in artificial intelligence and operations research and many divide-and-conquer algorithms. In it, source processors randomly seek out sink processors for load balancing by flinging "probe" messages. These probes not only locate sinks, but also collect load distribution information which is used to efficiently regulate load balancing activities. We empirically compare RS with a well-known randomized dynamic load balancing method, the random communication (RC) strategy, by using them in parallel best-first branch-and-bound algorithms on up to 512 processors of a parallel system. We find that the RC execution times are more than those of RS by 16–67% when used to perform combined dynamic quantitative and qualitative load balancing, and by 9–74% when used to perform only dynamic quantitative load balancing.
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Alistarh, Dan, Giorgi Nadiradze, and Amirmojtaba Sabour. "Dynamic Averaging Load Balancing on Cycles." Algorithmica 84, no. 4 (December 24, 2021): 1007–29. http://dx.doi.org/10.1007/s00453-021-00905-9.
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AbstractWe consider the following dynamic load-balancing process: given an underlying graph G with n nodes, in each step $$t\ge 0$$ t ≥ 0 , a random edge is chosen, one unit of load is created, and placed at one of the endpoints. In the same step, assuming that loads are arbitrarily divisible, the two nodes balance their loads by averaging them. We are interested in the expected gap between the minimum and maximum loads at nodes as the process progresses, and its dependence on n and on the graph structure. Peres et al. (Random Struct Algorithms 47(4):760–775, 2015) studied the variant of this process, where the unit of load is placed in the least loaded endpoint of the chosen edge, and the averaging is not performed. In the case of dynamic load balancing on the cycle of length n the only known upper bound on the expected gap is of order $$\mathcal {O}( n \log n )$$ O ( n log n ) , following from the majorization argument due to the same work. In this paper, we leverage the power of averaging and provide an improved upper bound of $$\mathcal {O} ( \sqrt{n} \log n )$$ O ( n log n ) . We introduce a new potential analysis technique, which enables us to bound the difference in load between k-hop neighbors on the cycle, for any $$k \le n/2$$ k ≤ n / 2 . We complement this with a “gap covering” argument, which bounds the maximum value of the gap by bounding its value across all possible subsets of a certain structure, and recursively bounding the gaps within each subset. We also show that our analysis can be extended to the specific instance of Harary graphs. On the other hand, we prove that the expected second moment of the gap is lower bounded by $$\Omega (n)$$ Ω ( n ) . Additionally, we provide experimental evidence that our upper bound on the gap is tight up to a logarithmic factor.
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Yang, Hexu, Xiaopeng Li, Jinchi Xu, Zemin Yang, and Renzhen Chen. "Dynamic characteristics analysis of planetary gear system with internal and external excitation under turbulent wind load." Science Progress 104, no. 3 (July 2021): 003685042110356. http://dx.doi.org/10.1177/00368504211035604.
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According to the working characteristics of a 1.5 MW wind turbine planetary gear system under complex and random wind load, a two-parameter Weibull distribution model is used to describe the distribution of random wind speed, and the time-varying load caused by random wind speed is obtained. The nonlinear dynamic model of planetary gear transmission system is established by using the lumped parameter method, and the relative relations among various components are derived by using Lagrange method. Then, the relative relationship between the components is solved by Runge Kutta method. Considering the influence of random load and stiffness ratio on the planetary gear transmission system, the nonlinear dynamic response of cyclic load and random wind load on the transmission system is analyzed. The analysis results show that the variation of the stiffness ratio makes the planetary gear have abundant nonlinear dynamics behavior and the planetary gear can get rid of chaos and enter into stable periodic motion by changing the stiffness ratio properly on the premise of ensuring transmission efficiency. For the variable pitch wind turbine, the random change of external load increases the instability of the system.
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Li, Kun, Yue Zhao, Zhuo Fu, Chenghao Tan, Xianfeng Man, and Chi Liu. "Equivalent Identification of Distributed Random Dynamic Load by Using K–L Decomposition and Sparse Representation." Machines 10, no. 5 (April 26, 2022): 311. http://dx.doi.org/10.3390/machines10050311.
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By aiming at the common distributed random dynamic loads in engineering practice, an equivalent identification method that is based on K–L decomposition and sparse representation is proposed. Considering that the establishment of a probability model of the distributed random dynamic load is usually unfeasible because of the requirement of a large number of samples, this method describes it by using an interval process model. Through K–L series expansion, the interval process model of the distributed random dynamic load is recast as the sum of the load median function and the load uncertainty. Then, the original load identification problem is transformed into two deterministic ones: the identification of the load median function and the reconstruction of the load covariance matrix, which reveals the load uncertainty characteristics. By integrating the structural modal parameters, and by adopting the Green’s kernel function method and sparse representation, the continuously distributed load median function is equivalently identified as several concentrated dynamic loads that act on the appropriate positions. On the basis of the realization of the first inverse problem, the forward model of the load covariance matrix reconstruction is derived by using K–L series expansion and spectral decomposition. The resolutions to both inverse problems are assisted by the regularization operation so as to overcome the inherent ill-posedness. At the end, a numerical example is presented to show the effectiveness of the proposed method.
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Wang, Ai Hong, Ge Ning Xu, Ping Yang, and You Shan Gao. "Research on Random Stress Spectrum for Cumulative Fatigue of Crane Metal Structure." Advanced Materials Research 189-193 (February 2011): 1122–26. http://dx.doi.org/10.4028/www.scientific.net/amr.189-193.1122.
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In order to calculate the fatigue life, lifting or unloading position, lifting weight and load mobile line of crane with automatic acquisition device were recorded on spot. Probability distribution model and its characteristic parameters of lifting weight and lifting or unloading position were analyzed with goodness of fit test. The random samples of the load spectrum parameters for the cumulative fatigue were also calculated with Latin Hypercube Sampling. Dynamic simulation model of crane metal structure was formed. Dynamic load function that dynamic load changed with time was also established, from which the stress spectrum through structural dynamics analysis in fatigue calculation point was acquired. Based on then above calculation, the remaining fatigue life of the prototype is 38 years.
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Jiang, Xian Long, Suo Huai Zhang, Yan Xu Jia, and Hao Zhang. "Analysis on Transient Dynamic Load of Planetary Gear Pair." Advanced Materials Research 988 (July 2014): 353–58. http://dx.doi.org/10.4028/www.scientific.net/amr.988.353.
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The geometry of a precise involute NGW planetary gear train has been built by Solidworks, the overall finite element model of planetary gear train has been built in ANSYS Workbench. According to the non-linear finite element contact theory and the finite element theory, instantaneous state mesh of Planetary Gear Pair has been simulated dynamically. And the time curve of the maximum stress strain for planetary gear train and the stress law of the mesh for each gear in different tooth profile were obtained. The variation of stress in different tooth profile of mesh has been analyzed to improve the performance of the planetary gear and reliability to provide some theoretical guidance.
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TENG, Sheng-bo, Jian-xin LIAO, and Xiao-min ZHU. "Dynamic weighted random load balancing algorithm for SIP application server." Journal of China Universities of Posts and Telecommunications 16, no. 4 (August 2009): 67–70. http://dx.doi.org/10.1016/s1005-8885(08)60250-2.
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Yang, Mingchuan, Guanchang Xue, Botao Liu, Yupu Yang, and Yanyong Su. "Load Estimation Based Dynamic Access Protocol for Satellite Internet of Things." Remote Sensing 14, no. 24 (December 19, 2022): 6402. http://dx.doi.org/10.3390/rs14246402.
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In recent years, the Internet of Things (IoT) industry has become a research hotspot. With the advancement of satellite technology, the satellite Internet of Things is further developed along with a new generation of information technology and commercial markets. However, existing random access protocols cannot cope with the access of a large number of sensors and short burst transmissions. The current satellite Internet of Things application scenarios are divided into two categories, one has only sensor nodes and no sink nodes, and the other has sink nodes. A time-slot random access protocol based on Walsh code is proposed for the satellite Internet-of-Things scenario with sink nodes. In this paper, the load estimation algorithm is used to reduce the resource occupancy rate in the case of medium and low load, and a dynamic Walsh code slot random access protocol is proposed to select the appropriate Walsh code length and frame length h. The simulation results show that the slotted random access protocol based on Walsh code can effectively improve the throughput of the system under high load. The introduction of load estimation in the case of medium and low load can effectively reduce the resource utilization of the system, and ensure that the performance of the access protocol based on Walsh codes does not deteriorate. However, in the case of high load, a large resource overhead is still required to ensure the access performance of the system.
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He, Wenbo, Xiaoqiang Zhang, Zhenyu Feng, Qiqi Leng, Bufeng Xu, and Xinmin Li. "Random Dynamic Load Identification with Noise for Aircraft via Attention Based 1D-CNN." Aerospace 10, no. 1 (December 25, 2022): 16. http://dx.doi.org/10.3390/aerospace10010016.
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Dynamic load identification plays an important role in the field of fault diagnosis and structural modification design for aircraft. In conventional dynamic load identification approaches, accurate structural modeling is usually needed, which is difficult to obtain for highly nonlinear or unknown structures. In this paper, a one-dimensional convolution neural network with multiple modules is proposed for random dynamic load identification of aircraft. Firstly, the convolution module is designed for temporal feature extraction. Secondly, the extracted features are linearly weighted based on the contributions to the final output. The contributions are learned in a data driven manner via the designed attention module. Lastly, the dynamic load of a certain time stamp is predicted from the learned and weighted features. The proposed model is trained and tested using the real data from a GARTEUR aircraft model. Extensive experimental results with qualitative and quantitative evaluations have demonstrated the identification performance with satisfactory accuracy of the proposed approach under different strengths of load noises.
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Haff, G. Gregory, Amador Garcia-Ramos, and Lachlan P. James. "Using Velocity to Predict the Maximum Dynamic Strength in the Power Clean." Sports 8, no. 9 (September 18, 2020): 129. http://dx.doi.org/10.3390/sports8090129.
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The primary aim of the present study was to examine the commonly performed training exercise for athlete preparation. Twenty-two recreationally trained males (age: 26.3 ± 4.1 y, height: 1.80 ± 0.07 m; body mass (BM): 87.01 ± 13.75 kg, 1-repetitoon maximum(1-RM)/BM: 0.90 ± 0.19 kg) participated in the present study. All subjects had their 1-RM power clean tested with standard procedures. On a separate testing day, subjects performed three repetitions at 30% and 45%, and two repetitions at 70% and 80% of their 1-RM power clean. During all trials during both sessions, peak velocity (PV) and mean velocity (MV) were measured with the use of a GymAware device. There were no significant differences between the actual and estimated 1-RM power clean (p = 0.37, ES = −0.11) when the load-PV profile was utilized. There was a large typical error (TE) present for the load-PV- and load-MV-estimated 1-RM values. Additionally, the raw TE exceeded the smallest worthwhile change for both load-PV and load-MV profile results. Based upon the results of this study, the load-velocity profile is not an acceptable tool for monitoring power clean strength.
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Govardhan, T., Achintya Choudhury, and Deepak Paliwal. "Load Distribution in a Rolling Element Bearing under Dynamic Radial Load." Applied Mechanics and Materials 592-594 (July 2014): 1099–103. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.1099.
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External load in a bearing is transferred from one race to another race through the rolling elements. In the present work, an investigation has been made to estimate the load on a rolling element in a bearing subjected to dynamic loading. The dynamic loading, in the present study, included harmonic and periodic loadings which are deterministic functions of time. The roller load is also investigated under random loading with known statistical values of mean and variance. Numerical values have been obtained for NJ204 bearing with known radial clearance. These results show the variation in the spectra obtained for different nature of external loadings. These results can be expected to satisfy the difference in theoretical and experimental spectra obtained by earlier researchers.
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Jang, Minseok, Hyun-Cheol Jeong, Taegon Kim, and Sung-Kwan Joo. "Load Profile-Based Residential Customer Segmentation for Analyzing Customer Preferred Time-of-Use (TOU) Tariffs." Energies 14, no. 19 (September 26, 2021): 6130. http://dx.doi.org/10.3390/en14196130.
Full textAbstract:
Smart meters and dynamic pricing are key factors in implementing a smart grid. Dynamic pricing is one of the demand-side management methods that can shift demand from on-peak to off-peak. Furthermore, dynamic pricing can help utilities reduce the investment cost of a power system by charging different prices at different times according to system load profile. On the other hand, a dynamic pricing strategy that can satisfy residential customers is required from the customer’s perspective. Residential load profiles can be used to comprehend residential customers’ preferences for electricity tariffs. In this study, in order to analyze the preference for time-of-use (TOU) rates of Korean residential customers through residential electricity consumption data, a representative load profile for each customer can be found by utilizing the hourly consumption of median. In the feature extraction stage, six features that can explain the customer’s daily usage patterns are extracted from the representative load profile. Korean residential load profiles are clustered into four groups using a Gaussian mixture model (GMM) with Bayesian information criterion (BIC), which helps find the optimal number of groups, in the clustering stage. Furthermore, a choice experiment (CE) is performed to identify Korean residential customers’ preferences for TOU with selected attributes. A mixed logit model with a Bayesian approach is used to estimate each group’s customer preference for attributes of a time-of-use (TOU) tariff. Finally, a TOU tariff for each group’s load profile is recommended using the estimated part-worth.