Models Of Inertia Research Articles

Near-Wall Settling Behavior of a Particle in Stratified Fluids.

The phenomenon of near-wall particle settling in a stratified fluid is an emerging topic in the field of multiphase flow, and it is also widely found in nature and engineering applications. In stratified fluids, particle settling characteristics are affected by the physical and chemical properties of the upper and lower fluids, the particle size, the particle density, and the initial sedimentation conditions. In this study, the main objective is to determine the effect of liquid viscosity and particle density on the detaching process, and the trajectory and velocity of near-wall settling particles in stratified fluids. The inertia and velocity of the particle had a greater impact on the tail pinch-off model in low-viscosity lower fluids; that is, the lower the inertia and velocity, the more apparent the order between deep and shallow seal pinch-off. In comparison, in high-viscosity lower fluids, the tail pinch-off models of different inertia and velocity particles were similar. In terms of particle trajectory, the transverse motion of the particle in the low-viscosity lower fluid exhibited abrupt changes; that is, the particles moved away from the wall suddenly, whereas in the high-viscosity lower fluid, the transverse movement was gradual. Due to the existence of the wall, the transverse motion direction of the free settling particles in the stratified fluid, which is determined by the rotation direction of the particles, changed to a direction away from the wall regardless of the particle rotation direction. This transverse movement also caused the particle settling velocity to drop suddenly or its rising rate to decrease, this is because part of the energy was used for transverse motion and to increase the transverse velocity. In our study, the near-wall settling of particles in a stratified fluid mainly affected the particle trajectory; that is, forced movement away from the wall, thus changing the particle velocity. This characteristic provides a new approach to manipulate particles away from the wall.

Improving Estimation of Soil Moisture Content Using a Modified Soil Thermal Inertia Model

There has been substantial research for estimating and mapping soil moisture content (SMC) of large areas using remotely sensed images by developing models of soil thermal inertia (STI). However, it is still a great challenge to accurately estimate SMC because of the impact of vegetation canopies and vegetation-induced shadows in mixed pixels on the estimates. In this study, a new method was developed to increase the estimation accuracy of SMC for an irrigated area located in YingKe of Heihe, China, using ASTER data. In the method, an original model of estimating bare STI was modified by decomposing a mixed pixel into three components, bare soil, vegetated soil, and shaded soil, as well as extracting their fractions using a spectral unmixing analysis and then deriving their fluxes. Moreover, the 90 m spatial resolution thermal images were scaled down to the 15 m spatial resolution by data fusion of a discrete wavelet transform (DWT) and re-sampling using the nearest neighbor method (NNM). The modified model was compared with the original model based on the mean absolute error (MAE) and relative root mean square error (RRMSE) between the SMC estimates and observations from 30 validation soil samples. The results indicated that compared to the original model based on the parallel dual layer, the modified STI model based on the serial dual layer statistically significantly decreased the MAE and RRMSE of the SMC estimates by 63.0–63.2% and 63.0–63.5%, respectively. The 15 m spatial resolution thermal bands obtained by the DWT data fusion provided more detailed information of SMC but did not significantly improve its estimation accuracy than the 15 m spatial resolution thermal bands by re-sampling using NNM. This implied that the novel method offered insights on how to increase the accuracy of retrieving SMC estimates in vegetated areas.

Static Characteristic Analysis of Spatial (Non-Planar) Links in Planar Parallel Manipulator

SUMMARYConventional planar manipulators have their links in a single plane. Increasing payload at the end effector/mobile platform can induce high stress in the links due to the cantilever nature of links. Thus, it limits the total vertical load that can be applied on the mobile platform. In contrast to the links in conventional planar parallel mechanisms, non-planar links are proposed in this paper, that is, links are made inclined to the horizontal plane and non-planar legs are constructed. Though the links are made non-planar, the end effectors’ planar motion is retained. For studying the application of such non-planar links in planar manipulators, new models of inertia, stiffness and leg dynamics have to be developed. In this article, these models are developed by the static analysis of the planar manipulators with non-planar links, and the performance is compared with the corresponding conventional planar manipulators.

Policy Inertia, Election Uncertainty, and Incumbency Disadvantage of Political Parties

Abstract We document that postwar U.S. elections show a strong pattern of “incumbency disadvantage”: if a party has held the presidency of the country or the governorship of a state for some time, that party tends to lose popularity in the subsequent election. We show that this fact can be explained by a combination of policy inertia and unpredictability in election outcomes. A quantitative analysis shows that the observed magnitude of incumbency disadvantage can arise in several different models of policy inertia. Normative and positive implications of policy inertia leading to incumbency disadvantage are explored.

Two-dimensional models of variable inertia from LiDAR data for structural analysis of timber trusses

Historical wooden structures often present numerous irregularities and changes of section along the longitudinal axis of the beams that compose them. For this reason, in order to carry out a structural analysis, the creation of models that take into account the variation in the moment of inertia presented by each beam of the structure is fundamental. This geometrical characteristic is especially important in structures of timber beams and trusses when the loads are located out of the nodes. To achieve this aim, this work presents an algorithm that makes it possible to automatically carry out 2D models of variable inertia for the analysis of structures of beams from LiDAR data. The proposed methodology is based on the creation of beam elements of variable inertia, where the geometrical properties of each section of each beam and the general geometry of the structure are considered. The results obtained are very promising, presenting relative errors in the deformation analysis lower than 8% compared to other methods of classical modelling and a reduction of the processing time by more than 85%.

Placement and Implementation of Grid-Forming and Grid-Following Virtual Inertia and Fast Frequency Response

The electric power system is witnessing a shift in the technology of generation. Conventional thermal generation based on synchronous machines is gradually being replaced by power electronics interfaced renewable generation. This new mode of generation, however, lacks the natural inertia and governor damping which are quintessential features of synchronous machines. The loss of these features results in increasing frequency excursions and, ultimately, system instability. Among the numerous studies on mitigating these undesirable effects, the main approach involves virtual inertia emulation to mimic the behavior of synchronous machines. In this work, explicit models of grid-following and grid-forming virtual inertia (VI) devices are developed for inertia emulation in low-inertia systems. An optimization problem is formulated to optimize the parameters and location of these devices in a power system to increase its resilience. Finally, a case study based on a high-fidelity model of the South-East Australian system is used to illustrate the effectiveness of such devices.

The Real Effects of Credible Disinflation in the Presence of Real Wage Rigidities

The paper re‐examines the real effects of credible disinflation in the presence of real wage rigidities and non‐linear dynamics. A credible, gradual disinflation is shown to lead to a delayed output slump along the transition path if real wage rigidities are sufficiently strong. This result is novel and holds across alternative models of nominal inertia—price staggering and price adjustment costs. In the special case of a cold‐turkey disinflation, price adjustment costs imply an immediate but short‐lived slump while price staggering implies a long‐lasting boom.

The Influence of Non-planar (Spatial) Links in the Static Characteristics Behavior of Planar Parallel Manipulator

<span>Conventional planar manipulators have all their links in a single plane. Increasing payload at the end-effecter/mobile platform can induce high stress in the links due to cantilever nature of links. Thus it limits the total vertical load that can be applied on the mobile platform. In contrast to the links in conventional planar parallel mechanisms, non-planar links are proposed in this paper, i.e., links are made inclined to the horizontal plane and non planar legs are constructed. Although the links are made non-planar, the rotary (or prismatic) joints axes remain perpendicular (or parallel) to the plane of the base platform, which retains the planar motion of the end-effecter. For studying the application of such non planar links in planar manipulators, new models of inertia, stiffness and leg dynamics have to be developed. In this article, these models are developed and with the developed models, the static analysis is done on the planar manipulators with non-planar links and the performance is compared with the corresponding conventional planar manipulators.</span>

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The inflation bias under Calvo and Rotemberg pricing

New Keynesian analysis relies heavily on two workhorse models of nominal inertia – due to Calvo (1983) and Rotemberg (1982), respectively – to generate a meaningful role for monetary policy. These are often used interchangeably since they imply an isomorphic linearized Phillips curve and, if the steady-state is efficient, the same policy conclusions. In this paper we compute time-consistent optimal monetary policy in the benchmark New Keynesian model containing each form of price stickiness using global solution techniques. We find that, due to an offsetting endogenous impact on average markups, the inflation bias problem under Calvo contracts is often significantly greater than under Rotemberg pricing, despite the fact that the former typically exhibits far greater welfare costs of inflation. The nonlinearities inherent in the New Keynesian model are significant and the form of nominal inertia adopted is not innocuous.

The role of the mobility law of dislocations in the plastic response of shock loaded pure metals

This article examines the role that the choice of a dislocation mobility law has in the study of plastic relaxation at shock fronts. Five different mobility laws, two of them phenomenological fits to data, and three more based on physical models of dislocation inertia, are tested by employing dynamic discrete dislocation plasticity (D3P) simulations of a shock loaded aluminium thin foil. It is found that inertial laws invariably entail very short acceleration times for dislocations changing their kinematic state. As long as the mobility laws describe the same regime of terminal speeds, all mobility laws predict the same degree of plastic relaxation at the shock front. This is used to show that the main factor affecting plastic relaxation at the shock front is in fact the speed of dislocations.

The Inflation Bias Under Calvo and Rotemberg Pricing

New Keynesian models rely heavily on two workhorse models of nominal inertia - price contracts of random duration Calvo (1983) and price adjustment costs Rotemberg (1982) - to generate a meaningful role for monetary policy. These alternative descriptions of price stickiness are often used interchangeably since, to a first order of approximation they imply an identical Phillips curve and, if the steady-state is efficient, identical objectives for the policy maker and as a result in an LQ framework, identical policy conclusions. In this paper we compute time-consistent optimal monetary policy in benchmark New Keynesian models containing each form of price stickiness. Using global solution techniques we find that the inflation bias problem under Calvo contracts is significantly greater than under Rotemberg pricing, despite the fact that the former typically exhibits far greater welfare costs of inflation. The rates of inflation observed under this policy are non-trivial and suggest that the model can comfortably generate the rates of inflation at which the problematic issues highlighted in the trend inflation literature emerge, as well as the movements in trend inflation emphasized in empirical studies of the evolution of inflation. Finally, we consider the response to cost push shocks across both models and find these can also be significantly different. The choice of which form of nominal inertia to adopt is not innocuous.

“Set His Image in Motion:” John Dennis and Early Eighteenth-Century Motion Imagery

This article examines early eighteenth-century attempts to explain how poetic descriptions of physical motion generated vivid scenes in the imagination. Motion was central to neo-Augustan theories of representation because, for much of this period, writers understood motion as a central principle of human nature. Questions about the mind/soul's “agitations” were crucial to a wide range of Enlightenment theories about mental imagery, rhetorical persuasion, and aesthetic beauty. Many writers, including John Dennis, linked the aesthetic import of spatial movement to Newtonian laws of motion. I trace the ways that Dennis's theories about motion imagery address not only the classical tradition of “bringing-before-the-eyes,” but also the modern philosophical models of inertia and force. In arguing that writing about poetry could better elucidate the motions of the mind/soul than could moral philosophy or physics, Dennis's essays can also teach us about eighteenth-century proto-disciplinary organization. Recent work in cognitive cultural studies has shown that the concept of motion is of vital importance to understanding the way the brain comprehends and structures language. This has especially wide-reaching implications for scholars of Restoration and eighteenth-century literature because it was during this period that writers began to codify connections between universal laws of nature, beauty, and human cognition.

Combining thermal inertia and a diurnal temperature difference cycle model to estimate thermal inertia from MSG-SEVIRI data

Thermal inertia is an important parameter in geological and agricultural applications. In this study, we present a method that combines models of thermal inertia and the diurnal temperature difference cycle to estimate the thermal inertia from Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) data. This method can directly derive thermal inertia from MSG-SEVIRI brightness temperatures without the need to include the land surface temperature and emissivity. Two important parameters (the time of the maximum temperature and the diurnal temperature difference) that were input into the thermal inertia model were obtained by fitting the diurnal temperature difference cycle model to the diurnal cycle of land surface temperatures. The spatial distribution of thermal inertia shows that high thermal inertia values occur over vegetated areas, whereas low thermal inertia values occur over bare areas. The uncertainty in thermal inertia is investigated in terms of the uncertainties in the surface albedo, the time of the maximum temperature, and the diurnal temperature difference. The results indicate that the uncertainty in thermal inertia over vegetated areas is greater than that over bare areas. The consistency of the thermal inertia model is evaluated by analysing the difference in thermal inertia values on two consecutive days. The root mean square error of the thermal inertia differences under nearly identical surface and atmospheric conditions on two consecutive days is considered to be the error of the thermal inertia model.

TEXTURAL IMAGING AND DISCRIMINANT ANALYSIS FOR DISTINGUISHINGWEEDS FOR SPOT SPRAYING

Advanced computer vision and statistical methods were employed for identifying living plants from soil/residue background for two species of grasses (Shattercane, Green Foxtail) and two broadleaf species (Velvetleaf, RedRoot Pigweed) weeds. The excess green index method was used as a contrast enhancement for specifically identifyingplant from soil regions. Excess green classified plant and soil regions correctly over the entire three-week observationperiod with high accuracies (99% plus). Plant and soil binary images were derived from excess green images andprovided edge boundaries. These boundaries were used with corresponding gray scale images to extract four classicaltextural features for plants and soil: angular second moment, inertia, entropy, and local homogeneity. These features werederived from the co-occurrence matrix. Stepwise and canonical discriminant analyses were used to test the classificationperformance of the texture and excess green features. Discrimination models of local homogeneity, inertia, and angularsecond moment were found to classify grass and broadleaf categories of plants, with classification accuracies of 93 and85%, respectively. Classification accuracies of individual species only ranged from 30 to 77%. Soil classificationaccuracies were also high for textural feature algorithms (97%). The time required to produce tokensets ranged from 15 to20 s on a UNIX computer system. Additional time required for the system to reach a plant/soil classification ranged from5 to 10 s. This translated into an overall system response time of 20 to 30 s, with the preprocessing step constituting themajor part of the system response time.

Markov Models of Inertia and Dynamism on Two Contiguous Ohio Landscapes

This study examined landcover change during 1940–1988 in two contiguous landscapes of approximately 12,400 hectares in central Ohio, USA: an inertial till plain area and a more dynamic moraine area. Agriculture dominated both landscapes throughout, however, the cover of natural vegetation and urban‐suburban development increased over time on the moraine while natural vegetation decreased and agriculture increased on the till plain. Markov process models for landcover change were constructed for three 14–17‐year time intervals and for the entire forty‐eight‐year study period. Probabilities of self‐replacement for agricultural lands (0.91–0.97) were higher and those for forests (0.54–0.65) lower than those reported for other landscapes. Predictions of landcover percentages for fifty years in the future were made using Markov process models derived from actual cover changes in 1940–1957, 1971–1988, and 1940–1988. All three models produced similar predictions for the inertial till plain area. In contrast, the three models' predictions differed considerably for the moraine area. Only the 1971–1988 transition matrix was sensitive to increases in urbanization and reforestation which began on the moraine in the 1970s. These results indicate that reliance on lengthy study intervals and net rates of change can obscure spatial and temporal patterns of landcover change that are caused by natural and socioeconomic factors operating on shorter time scales.