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1
Phalitnonkiat, Pakawat, Peter G. M. Hess, Mircea D. Grigoriu, Gennady Samorodnitsky, Wenxiu Sun, Ellie Beaudry, Simone Tilmes, et al. "Extremal dependence between temperature and ozone over the continental US." Atmospheric Chemistry and Physics 18, no. 16 (August 21, 2018): 11927–48. http://dx.doi.org/10.5194/acp-18-11927-2018.
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Abstract. The co-occurrence of heat waves and pollution events and the resulting high mortality rates emphasize the importance of the co-occurrence of pollution and temperature extremes. Through the use of extreme value theory and other statistical methods, tropospheric surface ozone and temperature extremes and their joint occurrence are analyzed over the United States during the summer months (JJA) using measurements and simulations of the present and future climate and chemistry. Five simulations from the Chemistry-Climate Model Initiative (CCMI) reference experiment using specified dynamics (REFC1SD) were analyzed: the CESM1 CAM4-chem, CHASER, CMAM, MOCAGE and MRI-ESM1r1 simulations. In addition, a 25-year present-day simulation branched off the CCMI REFC2 simulation in the year 2000 and a 25-year future simulation branched off the CCMI REFC2 simulation in 2100 were analyzed using CESM1 CAM4-chem. The last two simulations differed in their concentration of carbon dioxide (representative of the years 2000 and 2100) but were otherwise identical. In general, regions with relatively high ozone extremes over the US do not occur in regions of relatively high temperature extremes. A new metric, the spectral density, is developed to measure the joint extremal dependence of ozone and temperature by evaluating the spectral dependence of their extremes. While in many areas of the country ozone and temperature are highly correlated overall, the correlation is significantly reduced when examined on the higher end of the distributions. Measures of spectral density are less than about 0.35 everywhere, suggesting that at most only about a third of the time do extreme temperatures coincide with extreme ozone. Two regions of the US have the strongest measured extreme dependence of ozone and temperature: the northeast and the southeast. The simulated future increase in temperature and ozone is primarily due to a shift in their distributions, not to an increase in their extremes. The locations where the right-hand side of the temperature distribution does increase (by up to 30 %) are consistent with locations where soil–moisture feedback may be expected. Future changes in the right-hand side of the ozone distribution range regionally between +20 % and −10 %. The location of future increases in the high-end tail of the ozone distribution are weakly related to those of temperature with a correlation of 0.3. However, the regions where the temperature extremes increase are not located where the extremes in ozone are large, suggesting a muted ozone response.
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Yao, L., W. Dongxiao, Z. Zhenwei, H. Weihong, and S. Hui. "A Monte Carlo simulation of multivariate general Pareto distribution and its application." Ocean Science Discussions 11, no. 6 (December 8, 2014): 2733–53. http://dx.doi.org/10.5194/osd-11-2733-2014.
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Abstract. This paper presents a multivariate general Pareto distribution (MGPD) method and builds a method for solving MGPD through the use of a Monte Carlo simulation for marine environmental extreme-value parameters. The simulation method has proven to be feasible in the analysis of the joint probability of wave height and its concomitant wind from a hydrological station in the South China Sea (SCS). The MGPD is the natural distribution of the multivariate peaks-over-threshold (MPOT) sampling method, and is based on the extreme-value theory. The existing dependence functions can be used in the MGPD, so it may describe more variables which have different dependence relationships. The MGPD method improves the efficiency of the extremes in raw data. For the wave and the concomitant wind from a period of 23 years (1960–1982), the number of the wave and wind selected is averaged to 19 per year. For the joint conditional probability of the MGPD, the relative error is rather small in the Monte Carlo simulation method.
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Muheki, Derrick, Axel A. J. Deijns, Emanuele Bevacqua, Gabriele Messori, Jakob Zscheischler, and Wim Thiery. "The perfect storm? Co-occurring climate extremes in East Africa." Earth System Dynamics 15, no. 2 (April 24, 2024): 429–66. http://dx.doi.org/10.5194/esd-15-429-2024.
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Abstract. Co-occurring extreme climate events exacerbate adverse impacts on humans, the economy, and the environment relative to extremes occurring in isolation. While changes in the frequency of individual extreme events have been researched extensively, changes in their interactions, dependence, and joint occurrence have received far less attention, particularly in the East African region. Here, we analyse the joint occurrence of pairs of the following extremes within the same location and calendar year over East Africa: river floods, droughts, heatwaves, crop failures, wildfires and tropical cyclones. We analyse their co-occurrence on a yearly timescale because some of the climate extremes we consider play out over timescales up to several months. We use bias-adjusted impact simulations under past and future climate conditions from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). We find an increase in the area affected by pairs of these extreme events, with the strongest increases for joint heatwaves and wildfires (+940 % by the end of the century under RCP6.0 relative to present day), followed by river floods and heatwaves (+900 %) and river floods and wildfires (+250 %). The projected increase in joint occurrences typically outweighs historical increases even under an aggressive mitigation scenario (RCP2.6). We illustrate that the changes in the joint occurrences are often driven by increases in the probability of one of the events within the pairs, for instance heatwaves. The most affected locations in the East Africa region by these co-occurring events are areas close to the River Nile and parts of the Congo basin. Our results overall highlight that co-occurring extremes will become the norm rather than the exception in East Africa, even under low-end warming scenarios.
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Tencer, Bárbara, Andrew Weaver, and Francis Zwiers. "Joint Occurrence of Daily Temperature and Precipitation Extreme Events over Canada." Journal of Applied Meteorology and Climatology 53, no. 9 (September 2014): 2148–62. http://dx.doi.org/10.1175/jamc-d-13-0361.1.
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AbstractThe occurrence of individual extremes such as temperature and precipitation extremes can have a great impact on the environment. Agriculture, energy demands, and human health, among other activities, can be affected by extremely high or low temperatures and by extremely dry or wet conditions. The simultaneous or proximate occurrence of both types of extremes could lead to even more profound consequences, however. For example, a dry period can have more negative consequences on agriculture if it is concomitant with or followed by a period of extremely high temperatures. This study analyzes the joint occurrence of very wet conditions and high/low temperature events at stations in Canada. More than one-half of the stations showed a significant positive relationship at the daily time scale between warm nights (daily minimum temperature greater than the 90th percentile) or warm days (daily maximum temperature above the 90th percentile) and heavy-precipitation events (daily precipitation exceeding the 75th percentile), with the greater frequencies found for the east and southwest coasts during autumn and winter. Cold days (daily maximum temperature below the 10th percentile) occur together with intense precipitation more frequently during spring and summer. Simulations by regional climate models show good agreement with observations in the seasonal and spatial variability of the joint distribution, especially when an ensemble of simulations was used.
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Sanga, Bharat, Reeta Wattal, and D. S. Nagesh. "An FEA based study of thermal behaviour of ultrasonically welded phosphor bronze sheets." Journal of Mechanical Engineering and Sciences 15, no. 2 (June 10, 2021): 8057–71. http://dx.doi.org/10.15282/jmes.15.2.2021.10.0635.
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The ultrasonic joining of phosphor bronze sheets is analyzed using a 3-D finite element model for the study and prediction of the thermal profiles at the weld interface. The heat fluxes are calculated and assigned as boundary conditions during the thermal simulation. The forecast of temperature is done under various welding conditions. The maximum temperature obtained by transient simulation at the weld interface is 366.74℃. The continuous reduction in the temperature is observed towards the extremes of the weld metal. The sonotrode and the anvil achieve a lower temperature in comparison to the weld interface. The effect of clamping force and bonding ratio on the interface temperature is observed as positive. The model is validated with an error of 1.576% between the observed and predicted temperature results and a correlation co-efficient 0.96 is established between the simulated temperature results and the weld strength. Sufficiently strong joints were obtained at the optimum welding conditions with 74% joint efficiency. It is evident that the interface temperature has a strong linear relationship with joint strength and is a major deciding factor for achieving strong joints.
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Anderson, Dylan, Peter Ruggiero, Fernando J. Mendez, Ana Rueda, Jose A. Antolinez, Laura Cagigal, Curt Storlazzi, Patrick Barnard, and John Marra. "TIME-VARYING EMULATOR FOR SHORT- AND LONG-TERM ANALYSIS OF COASTAL FLOODING (TESLA-FLOOD)." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 4. http://dx.doi.org/10.9753/icce.v36.currents.4.
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The ability to predict coastal flooding events and associated impacts has emerged as a primary societal need within the context of projected sea level rise (SLR) and climate change. The duration and extent of flooding is the result of nonlinear interactions between multiple environmental forcings (oceanographic, meteorological, hydrological) acting at varying spatial (local to global) and temporal scales (hours to centuries). Individual components contributing to total water levels (TWLs) include astronomical tides, monthly sea level anomalies, storm surges, and wave setup. Common practices often use the observational record of extreme water levels to estimate return levels of future extremes. However, such projections often do not account for the individual contribution of processes resulting in compound TWL events, nor do they account for time-dependent probabilities due to seasonal, interannual, and long-term oscillations within the climate system. More robust estimates of coastal flooding risk require the computation of joint probabilities and the simulation of hypothetical TWLs to better constrain the projection of extremes (Serafin [2014]).
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Brunner, Manuela I., and Eric Gilleland. "Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach." Hydrology and Earth System Sciences 24, no. 8 (August 12, 2020): 3967–82. http://dx.doi.org/10.5194/hess-24-3967-2020.
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Abstract. Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but as yet unobserved streamflow time series with the same temporal and distributional characteristics as the observed data. However, the representation of non-stationarities and spatial dependence among sites remains a challenge in stochastic modeling. We investigate whether the use of frequency-domain instead of time-domain models allows for the joint simulation of realistic, continuous streamflow time series at daily resolution and spatial extremes at multiple sites. To do so, we propose the stochastic simulation approach called Phase Randomization Simulation using wavelets (PRSim.wave) which combines an empirical spatio-temporal model based on the wavelet transform and phase randomization with the flexible four-parameter kappa distribution. The approach consists of five steps: (1) derivation of random phases, (2) fitting of the kappa distribution, (3) wavelet transform, (4) inverse wavelet transform, and (5) transformation to kappa distribution. We apply and evaluate PRSim.wave on a large set of 671 catchments in the contiguous United States. We show that this approach allows for the generation of realistic time series at multiple sites exhibiting short- and long-range dependence, non-stationarities, and unobserved extreme events. Our evaluation results strongly suggest that the flexible, continuous simulation approach is potentially valuable for a diverse range of water management applications where the reproduction of spatial dependencies is of interest. Examples include the development of regional water management plans, the estimation of regional flood or drought risk, or the estimation of regional hydropower potential. Highlights. Stochastic simulation of continuous streamflow time series using an empirical, wavelet-based, spatio-temporal model in combination with the parametric kappa distribution. Generation of stochastic time series at multiple sites showing temporal short- and long-range dependence, non-stationarities, and spatial dependence in extreme events. Implementation of PRSim.wave in R package PRSim: Stochastic Simulation of Streamflow Time Series using Phase Randomization.
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Barbariol, Francesco, Alvise Benetazzo, Sandro Carniel, and Mauro Sclavo. "Space–Time Wave Extremes: The Role of Metocean Forcings." Journal of Physical Oceanography 45, no. 7 (July 2015): 1897–916. http://dx.doi.org/10.1175/jpo-d-14-0232.1.
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AbstractWave observations and modeling have recently demonstrated that wave extremes of short-crested seas are poorly predicted by statistics of time records. Indeed, the highest waves pertain to wave groups at focusing that have space–time dynamics. Therefore, the statistical prediction of extremes of short-crested sea states should rely on the multidimensional random wave fields’ assumption. To adapt wave extreme statistics to the space–time domain, theoretical models using parameters of the directional wave spectrum have been recently developed. In this paper, the influence of metocean forcings (wind conditions, ambient current, and bottom depth) on these parameters and hence on wave extremes is studied with a twofold strategy. First, parametric spectral formulations [Pierson–Moskowitz and Joint North Sea Wave Project (JONSWAP) frequency spectra with cos2 directional distribution function] are considered to represent the dependence of wave extremes upon wind speed, fetch, and space domain size. Afterward, arbitrary conditions are simulated by using the SWAN numerical model adapted to store the spectral parameters, and the effects on extremes of current- and depth-induced shoaling are investigated. Preliminarily, the space–time extremes prediction model adopted is assessed by means of numerical simulations of Gaussian random seas. Compared to the significant wave height of the sea state and for a given space domain size, results show that space–time extremes are enhanced by opposite currents, whereas they are weakened by increasing wind conditions (wind speed and fetch) and by depth-induced shoaling. In this respect, the remarkable contribution to wave extremes of the size of the space domain is substantiated.
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Vosniakos, G.-C., and A. Chronopoulos. "Industrial robot path planning in a constraint-based computer-aided design and kinematic analysis environment." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 223, no. 5 (March 27, 2009): 523–33. http://dx.doi.org/10.1243/09544054jem1234.
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Paths of industrial robots are easier to plan by using constraints on accurate computer-aided design (CAD) models of both objects representing the real industrial robotic cell and virtual objects representing the auxiliary geometry that is necessary to define path points. The motion path normally needs to be split into segments possessing uniform characteristics, e.g. common active joints, at points usually corresponding to position or velocity extremes. Each segment corresponds either to point-to-point motion or to constrained motion. Point-to-point motion is implemented by interpolating between original and final position of each joint separately, positions being determined through inverse kinematics in the CAD environment and motion being imparted to each joint directly. Constrained motion may be defined using several alternatives materialized with stationary and moving virtual objects, real robot joints, virtual joints, contact constraints, and motion constraints. Motion duration is specified after the corresponding path geometry has been specified, by exploiting maximum active joints velocity as well as end-tool velocity as dictated by the process. Collisions are detected using available functionality and are alleviated interactively. A user-defined number of interpolated robot poses are generated per segment. These are all ‘sewn’ together at the motion synthesis stage and frame-based simulation is generated. A realistic robotic lathe loading/unloading example is used to verify the use of the above notions and tools.
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Zheng, Feifei, Michael Leonard, and Seth Westra. "Efficient joint probability analysis of flood risk." Journal of Hydroinformatics 17, no. 4 (February 9, 2015): 584–97. http://dx.doi.org/10.2166/hydro.2015.052.
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Flood attributes such as the water level may depend on multiple forcing variables that arise from common meteorological conditions. To correctly estimate flood risk in these situations, it is necessary to account for the joint probability distribution of all the relevant forcing variables. An example of a joint probability approach is the design variable method, which focuses on the extremes of the forcing variables, and approximates the hydraulic response to forcing variables with a water level table. In practice, however, application of the design variable method is limited, even for the bivariate case, partly because of the high computational cost of the hydrologic/hydraulic simulations. We develop methods to minimise the computational cost and assess the appropriate extent and resolution of the water level table in a bivariate context. Flood risk is then evaluated as a bivariate integral, which we implement as an equivalent line integral. The line integral is two orders of magnitude quicker and therefore beneficial to settings that require multiple evaluations of the flood risk (e.g., optimisation studies or uncertainty analyses). The proposed method is illustrated using a coastal case study in which floods are caused by extreme rainfall and storm tide. An open-source R package has been developed to facilitate the uptake of joint probability methods among researchers and practitioners.
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Chiocca, Andrea, Francesco Frendo, and Leonardo Bertini. "Evaluation of residual stresses in a tube-to-plate welded joint." MATEC Web of Conferences 300 (2019): 19005. http://dx.doi.org/10.1051/matecconf/201930019005.
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A deep understanding of the manufacturing process is needed in order to achieve safety and quality requirements for parts and components; to this regard, residual stresses play an important role in welded structures. Residual stresses are mainly caused by the extremely severe thermal cycle to which the welded metal and base material are subjected to during welding process and their knowledge leads to a better static and fatigue assessment of welded joints. This work deals with the study of residual stresses for a tube to plate T-joint, made of S355JR carbon steel. The work was carried out by both numerical simulations and experimental tests. The numerical simulations were performed by Ansys FE code through a structural-thermal full transient analysis to evaluate stress, strain and temperature in each node at each step of the simulation. The “birth and death” method was employed, together with temperature-dependent material properties.A2Danda3D simulation were performed, in order to evaluate possible differences due to the welding process. Numerical results were compared to some preliminary measurements obtained through an incremental cut made on the plate.
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Xu, Zhenyu, and Dayu Zhu. "Impact of Continuous Cable-Strut Joints on the Anti-Progressive-Collapse Performance of Suspended-Dome Structures." Buildings 13, no. 9 (August 31, 2023): 2225. http://dx.doi.org/10.3390/buildings13092225.
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In suspended-dome structures, cable-strut joints can be categorized into discontinuous joints and continuous joints. In calculations, the discontinuous joints can be treated as hinge joints. However, in the event of a cable breakage, the continuous joints might experience slip and detachment phenomena. Simplifying continuous cable-strut joints as hinge joints for calculation purposes can result in a significant discrepancy from the actual load-bearing state of the continuous joints. In fact, under the scenario of cable rupture, the continuous cable-strut joints might undergo slip and detachment. This could influence the formation of new tension paths within the cable support system, thereby affecting the anti-collapse performance of the suspended-dome structure. Therefore, this paper investigates the influence of the slippage and detachment of continuous cable-strut joints on the anti-progressive collapse performance of suspended-dome structures through joint tests, numerical simulations, and theoretical analyses. Firstly, two cable-strut joint test models were constructed. Apart from the difference that one uses a discontinuous cable-strut joint and the other a continuous cable-strut joint, all other conditions were kept identical. Research was conducted on the hoop cable failure test. The results indicate that the slippage and detachment of continuous joints hinder the formation of new tension paths in the lower cable-strut system. Structures using continuous cable-strut joints have lower anti-collapse capabilities compared to those using discontinuous cable-strut joints. Secondly, a simplified numerical simulation algorithm for cable-strut joints’ slippage and detachment is proposed. This algorithm only considers the support of struts to the upper structure and uses an Abaqus subroutine to achieve an equivalent simulation of the slippage and detachment phenomena of continuous joints during the finite element computation process. Then, using this algorithm, a progressive collapse analysis of suspended domes using continuous cable-strut joints was carried out. It was found that for suspended domes with continuous cable-strut joints, the slippage and detachment of the cable-strut joints are extremely detrimental to forming new tension paths, making the structure more susceptible to a progressive collapse. Lastly, using the resistance index, a quantitative analysis was conducted on the anti-collapse carrying capacity of suspended domes using both continuous and discontinuous cable-strut joints.
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Luo, Y., D. Sui, H. Shi, Z. Zhou, and D. Wang. "Multivariate extreme value analysis of storm surges in SCS on peak over threshold method." Ocean Science Discussions 12, no. 6 (November 13, 2015): 2783–805. http://dx.doi.org/10.5194/osd-12-2783-2015.
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Abstract. We use a novel statistical approach-MGPD to analyze the joint probability distribution of storm surge events at two sites and present a warning method for storm surges at two adjacent positions in Beibu Gulf, using the sufficiently long field data on surge levels at two sites. The methodology also develops the procedure of application of MGPD, which includes joint threshold and Monte Carlo simulation, to handle multivariate extreme values analysis. By comparing the simulation result with analytic solution, it is shown that the relative error of the Monte Carlo simulation is less than 8.6 %. By running MGPD model based on long data at Beihai and Dongfang, the simulated potential surge results can be employed in storm surge warnings of Beihai and joint extreme water level predictions of two sites.
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Hannesdóttir, Ásta, Mark Kelly, and Nikolay Dimitrov. "Extreme wind fluctuations: joint statistics, extreme turbulence, and impact on wind turbine loads." Wind Energy Science 4, no. 2 (June 3, 2019): 325–42. http://dx.doi.org/10.5194/wes-4-325-2019.
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Abstract. For measurements taken over a decade at the coastal Danish site Høvsøre, we find the variance associated with wind speed events from the offshore direction to exceed the prescribed extreme turbulence model (ETM) of the International Electrotechnical Commission (IEC) 61400-1 Edition 3 standard for wind turbine safety. The variance of wind velocity fluctuations manifested during these events is not due to extreme turbulence; rather, it is primarily caused by ramp-like increases in wind speed associated with larger-scale meteorological processes. The measurements are both linearly detrended and high-pass filtered in order to investigate how these events – and such commonly used filtering – affect the estimated 50-year return period of turbulence levels. High-pass filtering the measurements with a cutoff frequency of 1∕300 Hz reduces the 50-year turbulence levels below that of IEC ETM class C, whereas linear detrending does not. This is seen as the high-pass filtering more effectively removes variance associated with the ramp-like events. The impact of the observed events on a wind turbine are investigated using aeroelastic simulations that are driven by constrained turbulence simulation fields. Relevant wind turbine component loads from the simulations are compared with the extreme turbulence load case prescribed by the IEC standard. The loads from the event simulations are on average lower for all considered load components, with one exception: ramp-like events at wind speeds between 8 and 16 m s−1, at which the wind speed rises to exceed rated wind speed, can lead to high thrust on the rotor, resulting in extreme tower-base fore–aft loads that exceed the extreme turbulence load case of the IEC standard.
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Xiong, Genliang, Jingxin Shi, and Haichu Chen. "Cascaded Control of Flexible-Joint Robots Based on Sliding-Mode Estimator Approach." Journal of Robotics 2020 (October 26, 2020): 1–12. http://dx.doi.org/10.1155/2020/8861847.
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The inherent highly nonlinear coupling and system uncertainties make the controller design for a flexible-joint robot extremely difficult. The goal of the control of any robotic system is to achieve high bandwidth, high accuracy of trajectory tracking, and high robustness, whereby the high bandwidth for flexible-joint robot is the most challenging issue. This paper is dedicated to design such a link position controller with high bandwidth based on sliding-mode technique. Then, two control approaches ((1) extended-regular-form approach and (2) the cascaded control structure based on the sliding-mode estimator approach) are presented for the link position tracking control of flexible-joint robot, considering the dynamics of AC-motors in robot joints, and compared with the singular perturbation approach. These two-link position controllers are tested and verified by the simulation studies with different reference trajectories and under different joint stiffness.
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Valent, Peter, and Roman Výleta. "Continuous Simulation of Catchment Runoff in Flood Frequency Analysis: A Case Study from Slovakia." Proceedings 7, no. 1 (November 15, 2018): 16. http://dx.doi.org/10.3390/ecws-3-05828.
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Research questions relating to a reliable estimate of flood discharge have always interested both hydrologists and civil engineers. Over the decades, numerous methods have been proposed and used more or less successfully, all of them with known limitations restricting their use in a wide range of conditions and problems. In the past, the characteristics of hydrological extremes were mostly estimated by the methods of statistical analyses. As this type of method is not suitable to estimate design discharges of high return periods, and by default does not account for uncertainty, a new family of methods is slowly taking the place of the traditional approaches. Many of these methods are based on a combination of stochastic rainfall models (weather generators) and rainfall-runoff models, which enables generation of an arbitrary number of synthetic floods, even in places with short or no record of river discharges available. In addition, as this type of method produces flood hydrographs, they can also be used in a multivariate flood frequency analysis to estimate joint probabilities of two or more flood characteristics. This study presents a methodology for flood frequency analysis that combines stochastic models of both rainfall amounts and air temperatures with a lumped rainfall-runoff model to transfer the outputs of the stochastic models into a series of corresponding river discharges. Both of the stochastic models are single-site weather generators that produce continuous time series of mean areal daily rainfall amounts and air temperatures. In this study, the method was used to generate a time series of 10,000 years of mean daily discharges, which was used to build a flood frequency curve and to estimate extreme flood discharges of given return periods. The method was applied to a mountainous catchment of the River Váh in Slovakia.
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Cruse, Hoik, Jeffrey Dean, Thomas Kindermann, Josef Schmitz, and Michael Schumm. "Simulation of Complex Movements Using Artificial Neural Networks." Zeitschrift für Naturforschung C 53, no. 7-8 (August 1, 1998): 628–38. http://dx.doi.org/10.1515/znc-1998-7-816.
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Abstract A simulated network for controlling a six-legged, insect-like walking system is proposed. The network contains internal recurrent connections, but important recurrent connections utilize the loop through the environment. This approach leads to a subnet for controlling the three joints of a leg during its swing which is arguably the simplest possible solution. The task for the stance subnet appears more difficult because the movements of a larger and varying number of joints (9 -18: three for each leg in stance) have to be controlled such that each leg contributes efficiently to support and propulsion and legs do not work at cross purposes. Already inherently non-linear, this task is further complicated by four factors: 1) the combination of legs in stance varies continuously, 2) during curve walking, legs must move at different speeds, 3) on compliant substrates, the speed of the individual leg may vary unpredictably, and 4) the geometry of the system may vary through growth and injury or due to non-rigid suspension of the joints. This task appears to require some kind of “motor intelligence”. We show that an extremely decentralized, simple controller, based on a combination of negative and positive feedback at the joint level, copes with all these problems by exploiting the physical properties of the system.
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Wang, Xiangyang, Xiantang Zhang, Jingshuang Zhang, Hongmin Zhou, Peng Zhang, and Dan Li. "Study on the Influence of the Joint Angle between Blast Holes on Explosion Crack Propagation and Stress Variation." Processes 11, no. 9 (September 21, 2023): 2805. http://dx.doi.org/10.3390/pr11092805.
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The joints and fissures in a natural rock mass can affect the mechanical properties of the rock mass, the propagation of a blasting stress wave, and the blasting effect of the smooth surface of roadways. In the process of roadway drilling and blasting, there will inevitably be some joints between the two blast holes. Taking the joint angle as the starting point, this paper studies the rule of rock explosion crack propagation and stress variation when there are joints with different angles between two blast holes and analyzes the influence of joints on rock mechanical properties and blasting effects. The numerical simulation method and the software ANSYS/LS-DYNA are used to establish 7 rock mass models with various joint angles. When there is no joint between two holes and joints of 15°, 30°, 45°, 60°, 75°, and 90°, the propagation of explosive cracks and stress variations in the rock mass are discussed. The results show that the joints at different angles have obvious guiding and blocking effects on the propagation of explosive cracks, and as joint angles increase, the guiding effect becomes more apparent and the blocking effect becomes weaker. The effective stress of the rock mass will vary depending on the angles of the joints between the hole and the joint. As the joint angle increases, the joint’s influence on the reflection and superposition of stress waves gradually weakens, and the peak value of the effective stress of the rock mass gradually decreases. The peak effective stress of the rock mass on the blasting side of the joint is similarly impacted by the superposition of stress waves, and the extreme value may be seen at the critical node of each change curve. The explosive crack will break through at the critical location because the maximal effective stress of the rock mass is distributed in a “W” form on the blasting side of the joint.
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Janssen, Peter A. E. M. "On a random time series analysis valid for arbitrary spectral shape." Journal of Fluid Mechanics 759 (October 23, 2014): 236–56. http://dx.doi.org/10.1017/jfm.2014.565.
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AbstractWhile studying the problem of predicting freak waves it was realized that it would be advantageous to introduce a simple measure for such extreme events. Although it is customary to characterize extremes in terms of wave height or its maximum it is argued in this paper that wave height is an ill-defined quantity in contrast to, for example, the envelope of a wave train. Also, the last measure has physical relevance, because the square of the envelope is the potential energy of the wave train. The well-known representation of a narrow-band wave train is given in terms of a slowly varying envelope function ${\it\rho}$ and a slowly varying frequency ${\it\omega}=-\partial {\it\phi}/\partial t$ where ${\it\phi}$ is the phase of the wave train. The key point is now that the notion of a local frequency and envelope is generalized by also applying the same definitions for a wave train with a broad-banded spectrum. It turns out that this reduction of a complicated signal to only two parameters, namely envelope and frequency, still provides useful information on how to characterize extreme events in a time series. As an example, for a linear wave train the joint probability distribution of envelope height and period is obtained and is validated against results from a Monte Carlo simulation. The extension to the nonlinear regime is, as will be seen, fairly straightforward.
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Mazas, Franck, and Luc Hamm. "AN EVENT-BASED APPROACH FOR EXTREME JOINT PROBABILITIES OF WAVES AND SEA LEVELS." Coastal Engineering Proceedings, no. 35 (June 23, 2017): 20. http://dx.doi.org/10.9753/icce.v35.management.20.
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A methodology for determining extreme joint probabilities of two metocean variables, in particular wave height and sea level, is presented in the paper. This methodology focuses in particular on the sampling of the time series, which should be based on the notion of event: either the event generating the variables whose joint probabilities are wanted (such as a storm generating waves and surges) or the event that is a result of the combination of these variables (such as a beach erosion event generated by waves at high sea level). A classification is proposed for multivariate analyses in order to help the choice of the sampling method. The dependence between the variables is analysed using tools such as the chi-plot, of which an enhanced presentation is proposed, then is modelled by extreme-value copulas (Gumbel-Hougaard, Galambos and Hüsler-Reiss) estimated by Canonical Maximum Likelihood or by the upper tail dependence coefficient. Joint return periods are then computed. A comparison is made with a simulation from the JOIN-SEA software on a dataset of wave height and sea levels offshore Brest, France. Then the bivariate methodology is extended to a multivariate framework. The distribution of sea level is determined by an indirect approach (extrapolation of extreme surges then convolution with the astronomical tide) and the dependence is analyzed between the wave height and the surge component only. A bidimensional convolution between the joint distribution of wave height and surge and the distribution of the astronomical tide yields the joint distribution of wave height and sea level. The application of this method to the dataset of Brest and its comparison with the bivariate approach are finally discussed.
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Dong, Xu, Jian Meng, Bin Zhang, Zhizhou Sun, Jian Li, and Shangwei Yang. "Torque Simulation and Analysis of Quadruped Robot under Trot Gait." Journal of Physics: Conference Series 2383, no. 1 (December 1, 2022): 012082. http://dx.doi.org/10.1088/1742-6596/2383/1/012082.
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The quadruped robot can overcome the unevenness of the wheeled chassis on steps and gravel roads, and has good passability. The Trot gait is the basic gait of the quadruped robot, and the walking is realized by the gait of alternating footsteps. In this paper, the dynamic simulation of the static equilibrium state of the quadruped robot in different poses on the ground and stair is carried out, and the movement of the robot body under the trot gait is simulated to obtain the joint torques of the upper and lower leg of the quadruped robot, which is the driving torque of the joint motor. The model selection provides a theoretical basis, and at the same time, the motion analysis of the quadruped robot is carried out, and the moving distance of the chassis under the extreme posture is planned.
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Poonia, Neeraj, and Sarita Azad. "A New Statistical Distribution Derived from a Clayton Copula for Modeling Bivariate Processes." Journal of Hydrometeorology 24, no. 10 (October 2023): 1659–78. http://dx.doi.org/10.1175/jhm-d-23-0011.1.
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Abstract Rainfall and temperature extremes have become more frequent and severe in recent times due to changing climate. Since these catastrophic occurrences directly affect a region’s hydrology, it is imperative to develop models that can project and explain the joint behavior of climate variables. Copula functions have been used relatively successfully to capture multivariate processes. With climate being a multifaceted process, there is interdependence between variables, making copula use desirable since traditional bivariate distributions do not account for the dependent structure. In this study, we introduced a bivariate exponentiated Teissier distribution based on a Clayton copula. For parameter estimation, the maximum likelihood and inference functions for margin approaches are used. A simulation study that considered various sets of parameters is also conducted in order to select the most efficient parameter estimation method. Last, the applicability of the proposed model is demonstrated using real-world data from flood and temperature processes. After fitting, the log-likelihood, Akaike information criteria (AIC), and Bayesian information criteria (BIC) values of the proposed model are −145.00, 300.00, and 311.71 for flood data, respectively, and −128.71, 267.42, and 275.98 for temperature data, respectively. Estimated parameters are for flood data and for temperature data. It is concluded that this model may be effectively used for modeling the hydrological processes for calculating the probabilities of flood and extreme temperature events.
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Lawrence, D., E. Paquet, J. Gailhard, and A. K. Fleig. "Stochastic semi-continuous simulation for extreme flood estimation in catchments with combined rainfall–snowmelt flood regimes." Natural Hazards and Earth System Sciences 14, no. 5 (May 23, 2014): 1283–98. http://dx.doi.org/10.5194/nhess-14-1283-2014.
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Abstract. Simulation methods for extreme flood estimation represent an important complement to statistical flood frequency analysis because a spectrum of catchment conditions potentially leading to extreme flows can be assessed. In this paper, stochastic, semi-continuous simulation is used to estimate extreme floods in three catchments located in Norway, all of which are characterised by flood regimes in which snowmelt often has a significant role. The simulations are based on SCHADEX, which couples a precipitation probabilistic model with a hydrological simulation such that an exhaustive set of catchment conditions and responses is simulated. The precipitation probabilistic model is conditioned by regional weather patterns, and a bottom–up classification procedure was used to define a set of weather patterns producing extreme precipitation in Norway. SCHADEX estimates for the 1000-year (Q1000) discharge are compared with those of several standard methods, including event-based and long-term simulations which use a single extreme precipitation sequence as input to a hydrological model, statistical flood frequency analysis based on the annual maximum series, and the GRADEX method. The comparison suggests that the combination of a precipitation probabilistic model with a long-term simulation of catchment conditions, including snowmelt, produces estimates for given return periods which are more in line with those based on statistical flood frequency analysis, as compared with the standard simulation methods, in two of the catchments. In the third case, the SCHADEX method gives higher estimates than statistical flood frequency analysis and further suggests that the seasonality of the most likely Q1000 events differs from that of the annual maximum flows. The semi-continuous stochastic simulation method highlights the importance of considering the joint probability of extreme precipitation, snowmelt rates and catchment saturation states when assigning return periods to floods estimated by precipitation-runoff methods. The SCHADEX methodology, as applied here, is dependent on observed discharge data for calibration of a hydrological model, and further study to extend its application to ungauged catchments would significantly enhance its versatility.
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Lawrence, D., E. Paquet, J. Gailhard, and A. K. Fleig. "Stochastic semi-continuous simulation for extreme flood estimation in catchments with combined rainfall-snowmelt flood regimes." Natural Hazards and Earth System Sciences Discussions 1, no. 6 (November 26, 2013): 6785–828. http://dx.doi.org/10.5194/nhessd-1-6785-2013.
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Abstract. Simulation methods for extreme flood estimation represent an important complement to statistical flood frequency analysis because a spectrum of catchment conditions potentially leading to extreme flows can be assessed. In this paper, stochastic, semi-continuous simulation is used to estimate extreme floods in three catchments located in Norway, all of which are characterised by flood regimes in which snowmelt often has a significant role. The simulations are based on SCHADEX, which couples a precipitation probabilistic model with a hydrological simulation such that an exhaustive set of catchment conditions and responses are simulated. The precipitation probabilistic model is conditioned by regional weather patterns, and a "bottom-up" classification procedure was used for defining a set of weather patterns producing extreme precipitation in Norway. SCHADEX estimates for the 1000 yr (Q1000) discharge are compared with those of several standard methods, including event-based and long-term simulations which use a single extreme precipitation sequence as input to a hydrological model, with statistical flood frequency analysis based on the annual maximum series, and with the GRADEX method. The comparison suggests that the combination of a precipitation probabilistic model with a long-term simulation of catchment conditions, including snowmelt, produces estimates for given return periods which are more in line with those based on statistical flood frequency analysis, as compared with the standard simulation methods, in two of the catchments. In the third case, the SCHADEX method gives higher estimates than statistical flood frequency analysis and further suggests that the seasonality of the most likely Q1000 events differs from that of the annual maximum flows. The semi-continuous stochastic simulation method highlights the importance of considering the joint probability of extreme precipitation, snowmelt rates and catchment saturation states when assigning return periods to floods estimated by precipitation-runoff methods. The SCHADEX methodology, as applied here, is dependent on observed discharge data for calibration of a hydrological model, and further study to extend its application to ungauged catchments would significantly enhance its versatility.
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Pang, Bo, Zhongqiu Ji, Zihua Zhang, Yunchuan Sun, Chunmin Ma, Zirong He, Xin Hu, and Guiping Jiang. "Strength Training Characteristics of Different Loads Based on Acceleration Sensor and Finite Element Simulation." Sensors 21, no. 2 (January 19, 2021): 647. http://dx.doi.org/10.3390/s21020647.
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Deep squat, bench press and hard pull are important ways for people to improve their strength. The use of sensors to measure force is rare. Measuring strength with sensors is extremely valuable for people to master the intensity of exercise to scientifically effective exercise. To this end, in this paper, we used a real-time wireless motion capture and mechanical evaluation system of the wearable sensor to measure the dynamic characteristics of 30 young men performing deep squat, bench press and hard pull maneuvers. The data of tibia were simulated with AnyBody 5.2 and ANSYS 19.2 to verify the authenticity. The result demonstrated that the appropriate force of the deep squat elbow joint, the hip joint and the knee joint is 40% 1RM, the appropriate force of the bench press is 40% 1RM and the appropriate force of the hard pull is 80% 1RM. The external force is the main factor of bone change. The mechanical characteristics of knee joint can be simulated after the Finite Element Analysis and the simulation of AnyBody model are verified.
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Kou, Lei, Zhihui Xiong, Hao Cui, and Jinjie Zhao. "Study on Mechanical Characteristics of Segmental Joints of a Large-Diameter Shield Tunnel under Ultrahigh Water Pressure." Sensors 21, no. 24 (December 16, 2021): 8392. http://dx.doi.org/10.3390/s21248392.
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At present, there is no clear design standard for segmental joints of large-diameter shield tunnels under high water pressure. In this paper, a theoretical calculation model for the bending stiffness of segmental joints under high water pressure is proposed. The numerical simulation method is used to investigate the failure and crack formation processes of single-layer and double-layer lining segments under large axial forces. The effects of axial force, bolt strength, and concrete strength on the bending stiffness of joints are then studied using a theoretical calculation model of segmental joints. The results show that under extremely high water pressure, the influence of double lining on joint stiffness is limited. It is more rational and safe to compute the bending stiffness of segmental joints using this theoretical model rather than the numerical simulation method. The parameter analysis reveals that increasing the bolt strength has a minor impact on bending stiffness and deformation, whereas increasing the concrete strength has the opposite effect. The influence of ultimate bearing capacity and deformation decreases non-linearly as the axial force increases.
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Yao, Fang, Jiawei Wang, Fushuan Wen, Chung-Li Tseng, Xingyong Zhao, and Qiang Wang. "An Integrated Planning Strategy for a Power Network and the Charging Infrastructure of Electric Vehicles for Power System Resilience Enhancement." Energies 12, no. 20 (October 16, 2019): 3918. http://dx.doi.org/10.3390/en12203918.
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This paper addresses the integrated planning problem of a power network and the charging infrastructure of electric vehicles (EVs) for enhancing power system resilience under various extreme weather scenarios. The planning methodology determines the optimal joint expansion decisions while modeling the benchmark system operation under the n − k resilience criterion. The proposed coordinated planning framework is a robust two-stage/tri-level mixed-integer optimization model. The proposed robust joint planning model includes the construction plan in the first level, identifying the worst-case scenario in the second level, and optimizing the operation cost and load shedding in the final level. To solve this model, a duality-based column and constraint generation (D-CCG) algorithm is developed. Using case studies, both the robust sole transmission planning and joint planning models are demonstrated on the IEEE 30-bus and IEEE 118-bus power systems. Numerical simulations of the benchmark systems validate the effectiveness of the developed framework and the efficiency of the proposed solution approach. Simulation results show the superiority of the proposed robust integrated planning over the sole transmission planning model.
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Zach, L., S. Konvickova, and P. Ruzicka. "Finite Element Analysis of the Lower Extrtemity - Hinge Knee Behavior Under Dynamic Load." International Journal of Mathematics and Computers in Simulation 15 (November 27, 2021): 89–91. http://dx.doi.org/10.46300/9102.2021.15.16.
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A key goal of joint endoprosthesis is to become a full-featured functional and anatomical replacement. The joint damage may occur for several reasons - primarily a disease of different nature and magnitude, resulting in gradual and irreversible changes and in an extreme solution in the implantation of artificial joints. However, there should be also mentioned accidents leading to joint destruction, which are often "trigger mechanism" of the disease. This work therefore presents a dynamic computational finite element analysis of a hinge-type knee replacement, which aim to streamline and accelerate the development of knee endoprosthesis. It tackles a question of the overall strength of the implant and detects sites of elevated concentrations of stresses that may be potential sources of implant damages. It also studies the behavior of the endoprosthesis under dynamic loads with emphasis on the study of the shape and size of the contact surfaces, which are closely related to the size of the contact pressure and material wear. Aside the hinged knee replacement, the computational model consisted of femur, fibula, tibia, patella and 25 most important muscles of the lower limb. Due to realistic definition of the boundary conditions, this model is suitable for investigation of invivo knee joint replacement behavior.
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Yang, Weihua, and Fei Wang. "The Effect of Acupuncture on Elbow Joint Sports Injuries Based on Magnetic Resonance Imaging." Computational and Mathematical Methods in Medicine 2022 (April 4, 2022): 1–7. http://dx.doi.org/10.1155/2022/9005792.
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Purpose. Elbow joint injuries are extremely common in most athletes. Athletes’ chronic elbow injuries can involve multiple complex anatomical structures related to orthopedics. Therefore, it is of great significance to explore the characteristics of magnetic resonance (MR) images of chronic sports injuries of the elbow joint and the influence of acupuncture treatment on MR images and clinical symptoms. Methods. A total of 60 elbow joints of 39 athletes from 15-25 years old were selected for coronal, sagittal, and axial MR scans to observe the image characteristics; 60 elbow joints were randomly divided into acupuncture group and control group and observed changes in MR images and clinical symptoms after acupuncture treatment. Results. After acupuncture treatment, the clinical symptoms were significantly improved. MR images showed that the elbow joint effusion was reduced, and the bone marrow edema was reduced. The effective rate of acupuncture treatment is as high as 100%, while the effective rate of the control group is only 40%. Acupuncture treatment has significantly improved the range of motion of the elbow joint. Conclusion. Acupuncture treatment can significantly relieve athletes’ elbow joint pain and locking symptoms, improve joint range of motion, and is beneficial to recovery of special training and high-level competitive competitions. It is a sensitive, effective, and noninvasive method.
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Scarf, P. A. "On the limiting joint distribution of the extreme order statistics." Applied Stochastic Models and Data Analysis 9, no. 3 (September 1993): 267–78. http://dx.doi.org/10.1002/asm.3150090307.
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Xiang, Yujiang. "Human Carrying Simulation With Symmetric and Asymmetric Loads Using Optimization." Journal of Applied Biomechanics 30, no. 1 (February 2014): 140–46. http://dx.doi.org/10.1123/jab.2012-0159.
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Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom. An optimization-based approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joint dynamics using optimization schemes and task-based physical constraints. The results indicate that the model can predict different carrying strategies during symmetric and asymmetric load-carrying tasks. The model can also indicate the risk factors for extreme loading situations. With such robust prediction capability, the model could be used for biomedical and ergonomic studies.
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Nail-Ulloa, Iván, Michael Zabala, Richard Sesek, Howard Chen, Mark C. Schall, and Sean Gallagher. "Estimating Compressive and Shear Forces at L5-S1: Exploring the Effects of Load Weight, Asymmetry, and Height Using Optical and Inertial Motion Capture Systems." Sensors 24, no. 6 (March 18, 2024): 1941. http://dx.doi.org/10.3390/s24061941.
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This study assesses the agreement of compressive and shear force estimates at the L5-S1 joint using inertial motion capture (IMC) within a musculoskeletal simulation model during manual lifting tasks, compared against a top-down optical motion capture (OMC)-based model. Thirty-six participants completed lifting and lowering tasks while wearing a modified Plug-in Gait marker set for the OMC and a full-body IMC set-up consisting of 17 sensors. The study focused on tasks with variable load weights, lifting heights, and trunk rotation angles. It was found that the IMC system consistently underestimated the compressive forces by an average of 34% (975.16 N) and the shear forces by 30% (291.77 N) compared with the OMC system. A critical observation was the discrepancy in joint angle measurements, particularly in trunk flexion, where the IMC-based model underestimated the angles by 10.92–11.19 degrees on average, with the extremes reaching up to 28 degrees. This underestimation was more pronounced in tasks involving greater flexion, notably impacting the force estimates. Additionally, this study highlights significant differences in the distance from the spine to the box during these tasks. On average, the IMC system showed an 8 cm shorter distance on the X axis and a 12–13 cm shorter distance on the Z axis during lifting and lowering, respectively, indicating a consistent underestimation of the segment length compared with the OMC system. These discrepancies in the joint angles and distances suggest potential limitations of the IMC system’s sensor placement and model scaling. The load weight emerged as the most significant factor affecting force estimates, particularly at lower lifting heights, which involved more pronounced flexion movements. This study concludes that while the IMC system offers utility in ergonomic assessments, sensor placement and anthropometric modeling accuracy enhancements are imperative for more reliable force and kinematic estimations in occupational settings.
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Hieronymus, Magnus. "The sea level simulator v1.0: a model for integration of mean sea level change and sea level extremes into a joint probabilistic framework." Geoscientific Model Development 16, no. 9 (May 5, 2023): 2343–54. http://dx.doi.org/10.5194/gmd-16-2343-2023.
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Abstract. A statistical model called the sea level simulator v1.0 is introduced. The model integrates mean sea level change and sea level extremes into a joint probabilistic framework that is useful for coastal spatial planning. Given a user-defined planning period, the model can estimate the flood risk as a function of height above the current mean sea level. These flood risk estimates are derived through Monte Carlo simulations of a very large number of planning periods. The derived flood risk is contingent on user-assigned probabilities for future greenhouse gas emission pathways, and the model is thus also useful for quantifying the dependence of flood risk on such pathways and their probabilities. Moreover, the simulator can quantify whether flood risk is dominated by sea level extremes or mean sea level rise and how this depends on the length of the planning period. The code, written in MATLAB, is parallelized and lightweight enough that it can be run on an ordinary PC. The code is easily adaptable to include new locations, new mean sea level projections and similar model developments. The flood risk estimates derived from the simulator are well suited to tackle adaptation and decision problems. Applications for construction of coastal protection and land development in coastal areas have been demonstrated in the past. The paper gives an in-depth technical description of the model. Example simulations from a Swedish nuclear site are also given, and the capabilities of the simulator are discussed. The main aim of the paper is to work as a technical reference for the first public release of the sea level simulator.
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Wang, Wenhai, Chaolei Wu, Yiming Yang, Xiaohan Peng, Lishuai Jiang, and Yifeng Huang. "Numerical Analysis on the Influence of Joint Density on the Stability of Complex Jointed Roadway Surrounding Rock." Sustainability 15, no. 18 (September 11, 2023): 13561. http://dx.doi.org/10.3390/su151813561.
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The random distribution of a complex joint network within a coal–rock mass has a significant weakening effect on its bearing capacity, making the surrounding rock of the roadway highly susceptible to instability and failure under the influence of in situ stress and mining-induced stress. This poses challenges in controlling the surrounding rock and seriously affects the normal production of mines. Consequently, it is imperative to conduct stability analysis on complex jointed roadway surrounding rock. Therefore, taking the transport roadway of Panel 11030 in the Zhaogu No. 2 Coal Mine as a case study, the microscopic contact parameters of particles and joint surfaces in each rock layer were calibrated through uniaxial compression and shear simulation tests using the particle flow simulation software PFC2D 5.0. Based on the calibrated microscopic contact parameters, a multilayered roadway surrounding rock model containing complex joints was established, and the joint density was quantified to analyze its effects on the displacement field, stress field, force chain field, and energy field of the roadway surrounding rock. The research findings indicate that as the distance to the sidewall decreases, the impact of joint density on the deformation of the surrounding rock of the roadway increases. The displacement of the roadway roof, floor, and sidewalls is affected differently by the joint density, predominantly contingent upon the properties of the rock mass. During the process of stress redistribution in the surrounding rock, the vertical stress of the roof and floor is released more intensively compared to the horizontal stress, while the horizontal stress of the sidewalls is released more intensively compared to the vertical stress. The increase in joint density leads to an increasing release rate of the surrounding rock stress, causing the load-bearing rock mass to transfer towards the deeper part. As the joint density increases, the force chain network gradually transitions from dense to sparse, resulting in a decrease in strong force chains and a decline in the bearing capacity of the surrounding rock, accompanied by an expansion in the range of force chain failure and deformation. With the continuous increase in joint density, the values of maximum released kinetic energy and residual released kinetic energy become larger. Once the joint density reaches a certain threshold, the kinetic energy stability zone consistently maintains a high energy level, indicating extreme instability in the roadway and sustained deformation. The results provide a valuable insight for analyzing the failure mechanism of complex jointed roadway surrounding rock and implementing corresponding support measures.
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Hao, Ruonan, and Zhixu Bai. "Comparative Study for Daily Streamflow Simulation with Different Machine Learning Methods." Water 15, no. 6 (March 18, 2023): 1179. http://dx.doi.org/10.3390/w15061179.
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Rainfall–runoff modeling has been of great importance for flood control and water resource management. However, the selection of hydrological models is challenging to obtain superior simulation performance especially with the rapid development of machine learning techniques. Three models under different categories of machine learning methods, including support vector regression (SVR), extreme gradient boosting (XGBoost), and the long-short term memory neural network (LSTM), were assessed for simulating daily runoff over a mountainous river catchment. The performances with different input scenarios were compared. Additionally, the joint multifractal spectra (JMS) method was implemented to evaluate the simulation performances during wet and dry seasons. The results show that: (1) LSTM always obtained a higher accuracy than XGBoost and SVR; (2) the impacts of the input variables were different for different machine learning methods, such as antecedent streamflow for XGBoost and rainfall for LSTM; (3) XGBoost showed a relatively high performance during dry seasons, and the classification of wet and dry seasons improved the simulation performance, especially for LSTM during dry seasons; (4) the JMS analysis indicated the advantages of a hybrid model combined with LSTM trained with wet-season data and XGBoost trained with dry-season data.
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SOYJAUDAH, K. M. S., and T. P. FOWDUR. "CRITICAL ANALYSIS OF A COMBINED HUFFMAN AND CONVOLUTIONAL CODING SCHEME." Journal of Circuits, Systems and Computers 15, no. 04 (August 2006): 641–57. http://dx.doi.org/10.1142/s0218126606003222.
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In this paper, a critical analysis of the joint source channel coding scheme proposed by Honary et al.1 is given. We show mathematically that although the algorithm leads to a reduction in the overall number of decoding states it increases both the time and space complexity of the decoding process. Moreover, the hardware complexity of the proposed scheme is also analyzed and it is observed that the joint decoding algorithm is in the first place extremely complex to implement and secondly, it significantly increases the number of components required, thereby increasing the power consumption. A mathematical proof that the joint decoding scheme has the same error performance as a separate scheme is also given. Finally, the simulation results show that the joint decoding scheme takes a significantly greater time to decode than a separate scheme, for the same error performance.
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Dzienis, P., I. Zaborowska, and R. Mosdorf. "JRP analysis of synchronization loss between signals recording during bubble departures." Nonlinear Dynamics 108, no. 1 (January 21, 2022): 433–44. http://dx.doi.org/10.1007/s11071-022-07217-9.
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AbstractThe synchronization between the air pressure fluctuations and the depth of liquid penetration into the nozzle during bubble departures was investigated using joint recurrence quantification analysis. In the experiment, the bubbles were generated from a glass nozzle into distilled water. During the analysis, the recurrent rate coefficients were calculated for the depth of liquid penetration into the glass nozzle and pressure changes in the gas supply system. The study was conducted by two air volume flow rates, i.e. 0.023 l/min and 0.026 l/min. The air volume flow rates were selected so that the appearance and disappearance of period bubble departures were clearly visible. It has been shown that the synchronization of the pressure changes and the depth of liquid penetration appears when periodic changes in the depth of liquid penetration occur in a relatively long period of time. The process of changing the distance between the extremes of liquid penetration into the nozzle and pressure changes in the gas supply system was observed. It has been found that the decrease in the distance between these extremes is responsible for the appearance of periodic bubble departures. This behaviour has not been reported in previous papers. This process was modelled by numerical simulations.
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De Luca, Giovanni, and Paola Zuccolotto. "A double clustering algorithm for financial time series based on extreme events." Statistics & Risk Modeling 34, no. 1-2 (January 1, 2017): 1–12. http://dx.doi.org/10.1515/strm-2015-0026.
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AbstractThis paper is concerned with a procedure for financial time series clustering, aimed at creating groups of time series characterized by similar behavior with regard to extreme events. The core of our proposal is a double clustering procedure: the former is based on the lower tail dependence of all the possible pairs of time series, the latter on the upper tail dependence. Tail dependence coefficients are estimated with copula functions. The final goal is to exploit the two clustering solutions in an algorithm designed to create a portfolio that maximizes the probability of joint positive extreme returns while minimizing the risk of joint negative extreme returns. In financial crisis scenarios, such a portfolio is expected to outperform portfolios generated by the traditional methods. We describe the results of a simulation study and, finally, we apply the procedure to a dataset composed of the 50 assets included in the EUROSTOXX index.
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Bai, Yun, and YuanBin Hou. "Research of Pose Control Algorithm of Coal Mine Rescue Snake Robot." Mathematical Problems in Engineering 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/4751245.
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Aiming at how to achieve optimal control of joint pitch angles in the process of the robot surmounting obstacle, taking the developed coal mine rescue snake robot as an experimental platform, a pose control algorithm based on particle swarm optimization weight coefficient of extreme learning machine (PSOELM) is proposed. In order to obtain the optimized hidden layer matrix of the extreme learning machine (ELM), particle swarm optimization (PSO) is applied to optimize the weight coefficient of hidden layer matrix. The simulation and experiment results prove that, compared with the ELM algorithm, the smaller mean square error (MSE) between the joint pitch angles of robot and the expected values is acquired by the PSOELM, which overcomes the shortcoming that traditional extreme learning machine cannot reach the best performance because of the random selection of the parameters of the hidden layer nodes. PSOELM is superior to ELM algorithm in control accuracy, fast searching for the optimal and stability. Optimal control of robot’s joint pitch angles is achieved. The algorithm is applied to the surmounting obstacle control of the developed snake robot, and it lays the foundation for further implement of the coal mine rescue.
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Yun, Seokhoon. "The distributions of cluster functionals of extreme events in a dth-order Markov chain." Journal of Applied Probability 37, no. 1 (March 2000): 29–44. http://dx.doi.org/10.1239/jap/1014842266.
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The paper concerns the asymptotic distributions of cluster functionals of extreme events in a dth-order stationary Markov chain {Xn, n = 1,2,…} for which the joint distribution of (X1,…,Xd+1) is absolutely continuous. Under some distributional assumptions for {Xn}, we establish weak convergence for a class of cluster functionals and obtain representations for the asymptotic distributions which are well suited for simulation. A number of examples important in applications are presented to demonstrate the usefulness of the results.
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Khan, Said, Samir Bendoukha, and Salem Abdelmalek. "Chaos Stabilization and Tracking Recovery of a Faulty Humanoid Robot Arm in a Cooperative Scenario." Vibration 2, no. 1 (February 6, 2019): 87–101. http://dx.doi.org/10.3390/vibration2010006.
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Synchronised motion is an important requirement for two cooperating humanoid robot arms. In this work a cooperative scenario is considered where two humanoid robot arms (using 4DOF each, namely Shoulder Flexion Joint, Shoulder abduction Joint, Humeral rotation joint and Elbow Flexion Joint) motion are synchronized. The master robot arm is controlled by a sliding mode controller and the slave robot arm is synchronized using a basic PD plus adaptive control, employing the position and velocity errors between the master and the slave. During the operation, if a joint of the slave robot arm saturates or malfunctions (for instance, Elbow flexion joint does not respond or free swinging), consequently, slave robot arm will go into chaos (i.e., chaotic motion of the end effector). In this case, a chaos controller kicks in to recover and re-synchronize the motion of the slave robot arm end effector. This re-synchronization is extremely important to complete the task in hand to address any safety issues arising from any joint malfunction of the slave robot. Effectiveness of the scheme is tested in simulation using Bristol Robotics Laboratory Humanoid BERT II arms.
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Ruosteenoja, Kimmo, Timo Vihma, and Ari Venäläinen. "Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations." Journal of Climate 32, no. 19 (August 30, 2019): 6467–90. http://dx.doi.org/10.1175/jcli-d-19-0023.1.
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Abstract Future changes in geostrophic winds over Europe and the North Atlantic region were studied utilizing output data from 21 CMIP5 global climate models (GCMs). Changes in temporal means, extremes, and the joint distribution of speed and direction were considered. In concordance with previous research, the time mean and extreme scalar wind speeds do not change pronouncedly in response to the projected climate change; some degree of weakening occurs in the majority of the domain. Nevertheless, substantial changes in high wind speeds are identified when studying the geostrophic winds from different directions separately. In particular, in northern Europe in autumn and in parts of northwestern Europe in winter, the frequency of strong westerly winds is projected to increase by up to 50%. Concurrently, easterly winds become less common. In addition, we evaluated the potential of the GCMs to simulate changes in the near-surface true wind speeds. In ocean areas, changes in the true and geostrophic winds are mainly consistent and the emerging differences can be explained (e.g., by the retreat of Arctic sea ice). Conversely, in several GCMs the continental wind speed response proved to be predominantly determined by fairly arbitrary changes in the surface properties rather than by changes in the atmospheric circulation. Accordingly, true wind projections derived directly from the model output should be treated with caution since they do not necessarily reflect the actual atmospheric response to global warming.
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Yun, Seokhoon. "The distributions of cluster functionals of extreme events in a dth-order Markov chain." Journal of Applied Probability 37, no. 01 (March 2000): 29–44. http://dx.doi.org/10.1017/s0021900200015230.
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The paper concerns the asymptotic distributions of cluster functionals of extreme events in a dth-order stationary Markov chain {X n , n = 1,2,…} for which the joint distribution of (X 1,…,X d+1) is absolutely continuous. Under some distributional assumptions for {X n }, we establish weak convergence for a class of cluster functionals and obtain representations for the asymptotic distributions which are well suited for simulation. A number of examples important in applications are presented to demonstrate the usefulness of the results.
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Ren, Sheng Le, Ye Dai, Ming Che, and Xu Du. "The Characteristic Simulation Analysis Method Based on the Theory of Similarity for Combined Interface of Heavy Machine Tools." Applied Mechanics and Materials 274 (January 2013): 183–86. http://dx.doi.org/10.4028/www.scientific.net/amm.274.183.
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The research on the combination of the characteristics becomes extremely important to the success of machine tool design. This paper mainly studies the dynamic and static characteristic parameters of heavy machine tool guide-way joint. And put forward a practical machine tool combining surface analysis method according to the experimental verification. It is presented that small linear guide as a scale model based on similarity theory. And make a research on the static and dynamic characteristics of small guide joint and the conclusion extended to heavy machine set of faces. And the conclusion is extended to the heavy machine set of faces. The results can be used as reference data about structure and design of the machine tool due to the similarity principle and error range.
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Montgomery, Matthew G., Miles B. Yaw, and John S. Schwartz. "Joint Failure Probability of Dams Based on Probabilistic Flood Hazard Analysis." Water 16, no. 6 (March 17, 2024): 865. http://dx.doi.org/10.3390/w16060865.
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Probabilistic risk methods are becoming increasingly accepted as a means of carrying out risk-informed decision making regarding the design and operation policy of structures such as dams. Probabilistic risk calculations require the quantification of epistemic and aleatory uncertainties not investigated through deterministic methodologies. In this hydrological study, a stochastic sampling methodology is employed to investigate the joint failure probability of three dams in adjacent similarly sized watersheds within the same hydrologic unit code (HUC) 6 basin. A probabilistic flood hazard analysis (PFHA) framework is used to simulate the hydrologic loading of a range of extreme precipitation events across the combined watershed area of the three studied dams. Precipitation events are characterized by three distinct storm types influential in the Tennessee Valley region with implications for weather variability and climate change. The stochastic framework allows for the simulation of hundreds of thousands of spillway outflows that are used to produce empirical bivariate exceedance probabilities for spillway discharge pairs at selected dams. System response curves that indicate the probability of failure given spillway discharge are referenced for each dam and applied to generate empirical bivariate failure probability (joint failure probability) estimates. The stochastic simulation results indicate the range of spillway discharges for each pair of dams that pose the greatest risk of joint failure. The estimate of joint failure considering the dependence of spillway discharges between dams is shown to be three to four orders of magnitude more likely (7.42 × 102 to 5.68 × 103) than estimates that assume coincident failures are the result of independent hydrologic events.
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Marcinkevičienė, Aušra, Rimantas Velička, Robertas Kosteckas, Aušra Rudinskienė, Inga Adamonytė, and Zita Kriaučiūnienė. "Effects of Nitrogen Rates on the Productivity and Nutritive Value of Forage Grass Grown under Extreme Climatic Conditions." Agronomy 11, no. 12 (December 17, 2021): 2572. http://dx.doi.org/10.3390/agronomy11122572.
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This vegetative experiment was carried out at the greenhouse of Vytautas Magnus University Agriculture Academy Open Access Joint Research Centre of Agriculture and Forestry (Lithuania) in 2020–2021. The aim of these studies was to determine the effect of different nitrogen rates on the productivity and nutritional quality of forage grasses (a mixture of red clover and timothy) under the most common extremes of climate change, i.e., soil moisture deficiency and surplus. Under drought and waterlogging stresses, fertilization of the red clover and timothy mixture with high N rates was ineffective. The clover and timothy mixture recovery after drought took 21 days. The aboveground dry biomass of the clover and timothy mixture grown under drought conditions was significantly lower by 36.3 to 47.2% compared to that formed under optimum soil moisture and waterlogging conditions. The root biomass of forage grass mixtures was lowest under drought conditions when fertilized at the highest N rate (N25+120). The aboveground biomass of clover grown under different soil moisture conditions depended on the number of plants (r2 = 0.78, p < 0.01) and assimilating leaf area (r2 = 0.83, p < 0.01), and that of timothy on the number of vegetative tillers (r2 = 0.46, p < 0.05). Under drought simulation conditions, increasing the N rate increased the crude protein and crude fibre contents in the aboveground biomass of the clover and timothy mixture, while the crude ash content decreased.
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Guo, Chao-Yu, Xing-Yi Huang, Pei-Cheng Kuo, and Yi-Hau Chen. "Extensions of the distributed lag non-linear model (DLNM) to account for cumulative mortality." Environmental Science and Pollution Research 28, no. 29 (March 18, 2021): 38679–88. http://dx.doi.org/10.1007/s11356-021-13124-0.
Full textAbstract:
AbstractThe effects of meteorological factors on health outcomes have gained popularity due to climate change, resulting in a general rise in temperature and abnormal climatic extremes. Instead of the conventional cross-sectional analysis that focuses on the association between a predictor and the single dependent variable, the distributed lag non-linear model (DLNM) has been widely adopted to examine the effect of multiple lag environmental factors health outcome. We propose several novel strategies to model mortality with the effects of distributed lag temperature measures and the delayed effect of mortality. Several attempts are derived by various statistical concepts, such as summation, autoregressive, principal component analysis, baseline adjustment, and modeling the offset in the DLNM. Five strategies are evaluated by simulation studies based on permutation techniques. The longitudinal climate and daily mortality data in Taipei, Taiwan, from 2012 to 2016 were implemented to generate the null distribution. According to simulation results, only one strategy, named MVDLNM, could yield valid type I errors, while the other four strategies demonstrated much more inflated type I errors. With a real-life application, the MVDLNM that incorporates both the current and lag mortalities revealed a more significant association than the conventional model that only fits the current mortality. The results suggest that, in public health or environmental research, not only the exposure may post a delayed effect but also the outcome of interest could provide the lag association signals. The joint modeling of the lag exposure and the delayed outcome enhances the power to discover such a complex association structure. The new approach MVDLNM models lag outcomes within 10 days and lag exposures up to 1 month and provide valid results.
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Chen, Jung-Chieh, Min-Han Chiu, Yi-Syun Yang, Kuan-Yuen Liao, and Chih-Peng Li. "Efficient Capacity-Based Joint Quantized Precoding and Transmit Antenna Selection Using Cross-Entropy Method for Multiuser MIMO Systems." International Journal of Antennas and Propagation 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/965834.
Full textAbstract:
The current paper considers the joint precoding and transmit antenna selection to reduce hardware cost, such as radio-frequency chains, associated with antennas in the downlink of multiuser multiple-input multiple-output systems with limited feedback. The joint precoding and transmit antenna selection algorithm requires an exhaustive search of all possible combinations and permutations to find the optimum solution at the transmitter, thus resulting in extremely high computational complexity. To reduce the computational load while still maximizing channel capacity, the cross-entropy (CE) method is adopted to determine the suboptimum solution. Compared with the conventional genetic algorithm and random search method, the CE method provides better performance under the same computational complexity, as shown by the simulation results.
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Ewans, Kevin C. "A Response-Based Method for Developing Joint Metocean Criteria for On-Bottom Pipeline Stability." Journal of Offshore Mechanics and Arctic Engineering 125, no. 2 (April 16, 2003): 119–25. http://dx.doi.org/10.1115/1.1555114.
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A response-based method for deriving joint metocean criteria for the on-bottom stability design of submarine pipelines is described. The method consists of applying a response function to convert a long time history of ocean wave and current conditions into a corresponding pipe response time history, from which extreme values and the joint metocean criteria can be obtained. In the case of designing for the 100-year return period conditions, the joint criteria are defined as either the value of the steady current to associate with the wave conditions that have a return period of 100 years or the value of the wave conditions to associate with the value of the steady current that has a return period of 100 years. The method involves first determining the extreme values, of the waves, currents and the responses, such as those with a 100-year return period, and then deriving the pair of wave and current combinations by inverting the response function at the 100-year return period level. Response functions for both the traditional static design approach and the state-of-the-art dynamic simulation design approach are presented. Both response functions are expressed in terms of the pipe weight per unit pipe length required for the pipe to be stable. In the case of the traditional approach, this is the weight required to keep the pipe static on the sea bed; but in the case of the dynamic approach, it is the weight that will allow a maximum lateral pipe displacement of three pipe diameters. The dynamic response function was developed from the AGA Level-3 pipeline stability software, by performing pipeline response simulations for many combinations of different sea state and steady current conditions. Joint wave and current criteria obtained from the response functions, for two test locations, are compared and evaluated against both the independent wave and current criteria and the joint criteria values recommended in design codes. A method is also outlined on how the response functions may be used to make estimates of the pipeline reliability with respect to on-bottom stabilization.
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Rooppakhun, Supakit, and Jakkree Wichairahad. "The Strength Analysis of a Bus Superstructure Based on the Accuracy Improvement of T-Junction Flexible Joint Stiffness." International Journal of Engineering & Technology 7, no. 3.24 (August 10, 2018): 62. http://dx.doi.org/10.14419/ijet.v7i3.24.17302.
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The strength analysis of bus superstructure was extremely important that the manufacturer must take into account, especially in the maximum stress analysis as well as the construction stiffness. In this study, the finite element (FE) model of an intercity bus superstructure consisted of chassis frame and body structure has been analyzed based on the improved beam joint considerations. The accuracy improvement of beam type element model was performed using the equivalent joint stiffness of T-junction beam modeling, and then compared with shell and volume elements. According to the improved T-junction FE model, the flexible joint stiffness consideration has been obtained, in which the behavioral error was reduced to less than 6%. The FE model of bus superstructure with improved beam joint was then compared to the rigid joint condition in bending, torsion, longitudinal and lateral load cases. The numerical results revealed that magnitude of maximum stress in the improved beam joint model displayed increasing of 11.53 %, 14.11 %, and 18.45 % in torsion, longitudinal and lateral load cases, respectively. However, the maximum stresses reduced in a case of bending with value of 5.72 %. In addition, the value of construction stiffness of improved beam joint model exhibited lower than the rigid beam joint as 44.85%, and 10.68% in the bending and torsion load case, respectively. To improve the accuracy of computer simulation, it will be beneficial to the passenger and the bus structure design and improvement procedure.