Two-point Models Research Articles

Stochastic differential equations for non-analog Monte Carlo model of point kinetics equations

The stochastic form of one-point and two-point reactor kinetics models have been extensively investigated in the literature. We have noticed that, in some studies, the probabilistic nature of neutron interaction mechanisms was not incorporated truly. For instance, in the case of negative reactivity insertions, one of the presented probability functions becomes negative, making the Monte Carlo (MC) simulation impossible. In this manuscript, the non-analog stochastic point reactor kinetics models are developed to simulate the stochastic behavior of nuclear systems. To reduce the imposed variance from the leakage and capture of neurons, both capture and leakage events are sampled implicitly. Precursors are also forced to decay in each simulation step. The true variances of the neutron’s and delayed neutron precursor’s populations are determined from the solution of the developed non-analog stochastic models. Also, they are compared with those of both analog and non-analog Monte Carlo methods. The results show that the analog Monte Carlo (MC) has a larger variance than the non-analog MC.

Multi-layered solid element for seismic analysis of rubber bearings considering stress continuity based on finite particle method

Rubber bearings are crucial components in seismic isolation systems to mitigate the damaging effects of earthquakes on structures. Rubber bearings generally consist of alternate layers of steel and rubber bonded together. Simplified two-point spring models omit this layered construction and have limitations in adaptability and programmability, while refined multiple solid models lead to substantial computational costs. This study presents an effective and efficient approach to simulate rubber bearings by using multi-layered solid element based on the finite particle method (FPM). The traditional “Zigzag” shape function is extended into the 3D situation to reflect the serrated deformation within the layered construction. Based on the simplified assumption of stress continuity, an iterative approach is presented for the deformation gradient to achieve the force continuity between layers in dynamic nonlinear scenarios. The multi-layered solid models for both natural rubber bearings (NRBs) and lead rubber bearings (LRBs) are proposed based on this element. The errors of the hysteresis curves of rubber bearings are below 3.1 % between the numerical results obtained by using the multi-layered solid model and the experimental results. The computational speedup ratio of the proposed multi-layered solid model is verified to be 19 relative to the refined multiple solid model. The proposed method is applied to a base-isolated frame structure to demonstrate its effectiveness in structural seismic analysis.

Efficient decomposition shooting method for tackling two-point boundary value models

AbstractThis research aims to present an efficient numerical method to find approximate numerical solutions for ordinary differential equations (ODEs), specifically, the class of two-point boundary value models. This approach is predicated on coupling the shooting method and the decomposition method, which the method is named as Efficient Decomposition Shooting Method (EDSM). Thus, we provide the complete outline of EDSM, and thereafter, apply it to some test models, comprising linear and nonlinear models. Further, the results are then validated by comparing them to the exact solution and other computational methods. Thus, the proposed method performs excellently over its peers, and is found to converge rapidly to the available exact solution with a good precision.

Determining critical power and W′ in running: Accuracy of different two-point models using the power metric

This study aims to determine the validity of the critical power (CP) and the work capacity over CP (W′) obtained from different two-time trial combinations with respect a five-point model. In a 3-week training period, 15 athletes (age: 23 ± 5 years; height: 166 ± 6 cm; body mass: 58 ± 8 kg; 5 km season-best: 15:29 ± 00:53 mm:ss) performed five time-trials (i.e. 3, 4, 5, 10, 20 min) on a 400 m track, from which the mean power outputs were obtained through the Stryd Power Meter. An acceptable level of agreement was considered if the following criteria were met: low bias and standard error of the estimate (SEE) (<14 W [values corresponding to the ±5% of the mean CP]; W′: <2.0 kJ [values corresponding to the ±10% of the mean W′]), R2 > 0.90, and ICC > 0.81. The CP presented an acceptable SEE for CPwork (1.3 ± 0.5%) and CP1/time (2.7 ± 1.1%) when using the five time-trials. For both CP models, the 3–10 min was the shortest valid combination, whereas the 3–20, 4–20, and 5–20 min showed the greatest level of agreement. The W′ presented a high SEE for CPwork (14.1 ± 5.2%) and CP1/time (13.8 ± 6.2%) when using the five time-trials, therefore, none of the two time-trials combinations were considered. The CP parameter can be accurately estimated from different two time-trial combinations, whereas none reached an acceptable level of accuracy for the determination of W′.

Soybean-MVS: Annotated Three-Dimensional Model Dataset of Whole Growth Period Soybeans for 3D Plant Organ Segmentation

The study of plant phenotypes based on 3D models has become an important research direction for automatic plant phenotype acquisition. Building a labeled three-dimensional dataset of the whole growth period can help the development of 3D crop plant models in point cloud segmentation. Therefore, the demand for 3D whole plant growth period model datasets with organ-level markers is growing rapidly. In this study, five different soybean varieties were selected, and three-dimensional reconstruction was carried out for the whole growth period (13 stages) of soybean using multiple-view stereo technology (MVS). Leaves, main stems, and stems of the obtained three-dimensional model were manually labeled. Finally, two-point cloud semantic segmentation models, RandLA-Net and BAAF-Net, were used for training. In this paper, 102 soybean stereoscopic plant models were obtained. A dataset with original point clouds was constructed and the subsequent analysis confirmed that the number of plant point clouds was consistent with corresponding real plant development. At the same time, a 3D dataset named Soybean-MVS with labels for the whole soybean growth period was constructed. The test result of mAccs at 88.52% and 87.45% verified the availability of this dataset. In order to further promote the study of point cloud segmentation and phenotype acquisition of soybean plants, this paper proposed an annotated three-dimensional model dataset for the whole growth period of soybean for 3D plant organ segmentation. The release of the dataset can provide an important basis for proposing an updated, highly accurate, and efficient 3D crop model segmentation algorithm. In the future, this dataset will provide important and usable basic data support for the development of three-dimensional point cloud segmentation and phenotype automatic acquisition technology of soybeans.

It takes two to know one: computing accurate one-point PDF covariances from effective two-point PDF models

One-point probability distribution functions (PDFs) of the cosmic matter density are powerful cosmological probes that extract non-Gaussian properties of the matter distribution and complement two-point statistics. Computing the covariance of one-point PDFs is key for building a robust galaxy survey analysis for upcoming surveys like Euclid and the Rubin Observatory LSST and requires good models for the two-point PDFs characterising spatial correlations. In this work, we obtain accurate PDF covariances using effective shifted lognormal two-point PDF models for the mildly non-Gaussian weak lensing convergence and validate our predictions against large sets of Gaussian and non-Gaussian maps. We show how the dominant effects in the covariance matrix capturing super-sample covariance arise from a large-separation expansion of the two-point PDF and discuss differences between the covariances obtained from small patches and full sky maps. Finally, we describe how our formalism can be extended to characterise the PDF covariance for 3D-dimensional spectroscopic fields using the 3D matter PDF as an example. We describe how covariances from simulated boxes with fixed overall density can be supplemented with the missing super-sample covariance effect by relying on theoretical predictions validated against separate-universe style simulations.

The linear regression model provides the force-velocity relationship parameters with the highest reliability

ABSTRACT An a-posteriori multicentre reliability study was conducted to compare the between-session reliability of the force-velocity relationship parameters (force-intercept [F0 ], velocity-intercept [v0 ], and maximum power [Pmax]) between different regression models during the bench press (BP) and bench press throw (BPT) exercises. Data from four and three studies were considered for the BP (n = 102) and BPT (n = 81) exercises, respectively. The force-velocity relationships were determined using five regression models: linear multiple-point, linear two-point, quadratic polynomial, hyperbolic, and exponential. All regression models provided F0 and Pmax with acceptable reliability (cut-off CV ≤ 9.45%; cut-off ICC ≥ 0.79) with the exceptions of F0 for the quadratic polynomial and hyperbolic models (BPT) and Pmax for the exponential model (BP and BPT). Only the linear multiple- and linear two-point models provided v0 with acceptable absolute reliability (cut-off CV ≤ 7.72%). Regardless of the exercise, the reliability of the three parameters was generally higher for the linear multiple- and two-point models compared to the other models (CVratio ≥ 1.22), and no significant differences were observed between multiple- and linear two-point models (CVratio ≤ 1.11). Linear regression models are recommended to maximise the reliability of the force-velocity relationship parameters during the BP and BPT exercises.

Двумерная частично когерентная геометрическая модель распределенного радиолокационного объекта

The possibility of the substitution of a two-dimensional distributed radar object by a 4-point partly coherent model is considered. As a criterion of adequacy we accepted the coincidence of the angle noise distribution function for the model and the substituted object. It is shown that the proposed four-point configuration can be represented as two orthogonal equivalent two-point models. Relations are obtained for calculating the parameters (power ratios of the signals and coefficients of the correlation matrix) of the signals of the four-point model through the parameters of the signals of the equivalent two-point models. The signal parameters of the equivalent two-point models can be calculated for the given parameters of the joint distribution of azimuthal and elevation noises. These relations obtained for the two-dimensional model are the result of this work. The results obtained were tested using numerical experiments for the test values of the parameters of the angle noise distribution function. To generate samples of signals whose correlation matrix has the required form the linear transformation method was used. The parameters of the distribution function of the simulated angle noise were estimated by the method of matching moments. The results of numerical experiments confirm the reliability of the obtained ratios. They can be used in mathematical and simulation modeling of distributed radar objects.

Use of two-point models in \u201cModel choice in time-series studies of air pollution and mortality\u201d

In this work, a new technique is proposed to study short-term exposure and adverse health effects. The presented approach uses hierarchical clusters with the following structure: each pair of two sequential days in 1 year is embedded in the year. We have 183 clusters per year with the embedded structure <year:2 days>. Time-series analysis is conducted using a conditional Poisson regression with the constructed clusters as a stratum. Unmeasured confounders such as seasonal and long-term trends are not modelled but are controlled by the structure of the clusters. The proposed technique is illustrated using four freely accessible databases, which contain complex simulated data. These data are available as the compressed R workspace files. Results based on the simulated data were very close to the truth based on the presented methodology. In addition, the case-crossover method with 1-month and 2-week window, and a conditional Poisson regression on 3-day clusters as a stratum, was also applied to the simulated data. Difficulties (high type I error rate) were observed for the case-crossover method in the presence of high concurvity in the simulated data. The proposed methods using various forms of a stratum were further applied to the Chicago mortality data. The considered methods have often different qualitative and quantitative estimations.

Steering bends and changing lanes: The impact of optic flow and road edges on two point steering control.

Successful driving involves steering corrections that respond to immediate positional errors while also anticipating upcoming changes to the road layout ahead. In popular steering models these tasks are often treated as separate functions using two points: the near region for correcting current errors, and the far region for anticipating future steering requirements. Whereas two-point control models can capture many aspects of driver behavior, the nature of perceptual inputs to these two "points" remains unclear. Inspired by experiments that solely focused on road-edge information (Land & Horwood, 1995), two-point models have tended to ignore the role of optic flow during steering control. There is recent evidence demonstrating that optic flow should be considered within two-point control steering models (Mole, Kountouriotis, Billington, & Wilkie, 2016). To examine the impact of optic flow and road edges on two-point steering control we used a driving simulator to selectively and systematically manipulate these components. We removed flow and/or road-edge information from near or far regions of the scene, and examined how behaviors changed when steering along roads where the utility of far-road information varied. While steering behaviors were strongly influenced by the road-edges, there were also clear contributions of optic flow to steering responses. The patterns of steering were not consistent with optic flow simply feeding into two-point control; rather, the global optic flow field appeared to support effective steering responses across the time-course of each trajectory.

Development of communication models of wireless environment in emergency situations

Two-point communication model of the wireless environment with one-beam and multi-beam propagation of radio waves were developed. The specified models make it possible to create various particular two-point communication models of wireless environment, taking into account the assigned geometry of location of shadowing and scattering structures in the environment. The practical use of the proposed models is limited to arbitrary points of radiation and reception in the environment, taking into account location of directional aerials in them. To study known multipoint technologies under conditions of emergency situations, we developed the multipoint communication models with one-beam and multibeam propagation of radio waves from each radiation point to each reception point, predetermined by the presence of shadowing and scattering structures in the environment. The developed multipoint models make it possible to create specific models at the physical level for various multi-aerial technologies, taking into consideration the use of aerial arrays of arbitrary configuration at the transmitting and receiving sides. Verification of the developed communication models of the wireless environment was performed. It was found that the use of directional aerials at the transmitting and receiving sides of the wireless environment in the presence of considerable shadowing and scattering structures makes it possible to significantly improve noise immunity. It is noted that with the use of the developed communication models, it is possible to carry out in-depth examination of the physical level with a view to developing a reliable and stable architecture of communications under conditions of emergency situations.

Two-point statistics of synthetic three-dimensional polycrystalline microstructures

The two-point spatial statistics of a heterogeneous material are crucial in ultrasonic attenuation and backscatter calculations. In this presentation, several common assumptions used for modeling polycrystals are examined. In most studies, the spatial and tensorial elements of the covariance function are assumed to be decoupled. Also, two-point correlation models often assume a single effective grain size for polycrystalline materials and a spatial correlation function that has an exponential decay at a rate directly proportional to the average grain diameter. This investigation uses the Dream.3D software platform to generate three-dimensional (3D) realizations of polycrystalline materials in order to study their two-point statistics. Using lognormal distributions with fixed means but different widths, a variety of different polycrystalline microstructures are simulated. The results show that the spatial correlation function is directly influenced by the grain size distribution. For a fixed mean grain size, wider distributions exhibit longer range correlations than narrower ones. The results also show that decoupling of the tensorial and spatial elements of the covariance function may not be valid for all lognormal grain size distributions. These results are anticipated to have an important impact on ultrasonic attenuation and backscatter models. [Research supported by AFRL under prime contract FA8650-15-D-5231.]

Grade and Tonnage Uncertainty Analysis of an African Copper Deposit Using Multiple-Point Geostatistics and Sequential Gaussian Simulation

Spatial uncertainty analysis is a complex and difficult task for orebody estimation in the mining industry. Conventional models (kriging and its variants) with variogram-based statistics fail to capture the spatial complexity of an orebody. Due to this, the grade and tonnage are incorrectly estimated resulting in inaccurate mine plans, which lead to costly financial decision. Multiple-point geostatistical simulation model can overcome the limitations of the conventional two-point spatial models. In this study, a multiple-point geostatistical method, namely SNESIM, was applied to generate multiple equiprobable orebody models for a copper deposit in Africa, and it helped to analyze the uncertainty of ore tonnage of the deposit. The grade uncertainty was evaluated by sequential Gaussian simulation within each equiprobable orebody models. The results were validated by reproducing the marginal distribution and two- and three-point statistics. The results show that deviations of volume of the simulated orebody models vary from − 3 to 5% compared to the training image. The grade simulation results demonstrated that the average grades from the different simulation are varied from 3.77 to 4.92% and average grade 4.33%. The results also show that the volume and grade uncertainty model overestimates the orebody volume as compared to the conventional orebody. This study demonstrates that incorporating grade and volume uncertainty leads to significant changes in resource estimates.

Delineating sources of groundwater recharge in an arsenic-affected Holocene aquifer in Cambodia using stable isotope-based mixing models

Chronic exposure to arsenic (As) through the consumption of contaminated groundwaters is a major threat to public health in South and Southeast Asia. The source of As-affected groundwaters is important to the fundamental understanding of the controls on As mobilization and subsequent transport throughout shallow aquifers. Using the stable isotopes of hydrogen and oxygen, the source of groundwater and the interactions between various water bodies were investigated in Cambodia’s Kandal Province, an area which is heavily affected by As and typical of many circum-Himalayan shallow aquifers. Two-point mixing models based on δD and δ18O allowed the relative extent of evaporation of groundwater sources to be estimated and allowed various water bodies to be broadly distinguished within the aquifer system. Model limitations are discussed, including the spatial and temporal variation in end member compositions. The conservative tracer Cl/Br is used to further discriminate between groundwater bodies. The stable isotopic signatures of groundwaters containing high As and/or high dissolved organic carbon plot both near the local meteoric water line and near more evaporative lines. The varying degrees of evaporation of high As groundwater sources are indicative of differing recharge contributions (and thus indirectly inferred associated organic matter contributions). The presence of high As groundwaters with recharge derived from both local precipitation and relatively evaporated surface water sources, such as ponds or flooded wetlands, are consistent with (but do not provide direct evidence for) models of a potential dual role of surface-derived and sedimentary organic matter in As mobilization.

A Geostatistical Study in Support of CO2 Storage in Deep Saline Aquifers of the Shenhua CCS Project, Ordos Basin, China

The Shenhua Carbon Capture and Storage (CCS) project at the Shenbei Slope injection site in North Yulin is the first 100,000 ton-per-year scale CCS pilot project in China with an injection operation lasting nearly 3 years. In this study, we investigate various geostatistical methods and their impact on the respective geologic models on which simulation is performed to understand the phenomena observed during 3 years of Shenhua CCS operations. Although there was a brief period of wellhead pressure increase at the injection well, it unexpectedly dropped for most of the time. Another interesting observation showed that the majority of CO2 gas injection was received by the topmost sandstone Liujiagou formation instead of the basement limestone Majiagou formation, which was predicted to have much more injectivity and storage capacity. Based on the current geostatistical methods and available data, 3 steps of reservoir modeling and flow simulation are carried out and they go from having homogeneous property models to incorporating standard 2-point geostatistical methods to using object-based models. The layer-cake models generate a rather uniform plume shape and increased pressure response. Meanwhile, two-point statistical models add more complexity to the size and shape of CO2 plume, however are not capable of reproducing the pressure decline behavior. These results demonstrate homogeneous and 2-point geostatistical models are inadequate in interpreting subsurface heterogeneity, both due to their method and data limitations. Further work is being done with object-based models to produce a system of meandering rivers based on the geological concept of Shenhua injection site. This will help offset the data limitation and bring our model closer to geologic reality.

Simulation results from a coupled model of carbon dioxide and methane global cycles

The problem of greenhouse effect due to the anthropogenic influence on the global cycles of greenhouse gases is discussed extensively in the scientific literature. This paper aims to contribute solving this problem by presenting the simulation results of a new model of combined carbon and methane biogeochemical cycles considering the spatial structure of their sources and sinks on a global scale. All reservoirs and fluxes of the carbon and methane that are taken into consideration in the model have different temporal scales, while the spatial scale for sources and sinks of carbon and methane on the land is considered as 4° by latitude and 5° by longitude. The World Ocean is parameterized by two-point models with four levels in depth with a separation between pelagic and upwelling zones. In addition, the interaction between the atmosphere and carbon reservoirs on the land and in the ocean includes the processes of photosynthesis, decomposition, respiration and burning. The global cycle of methane in the atmosphere-hydrosphere-land system is described by the scheme that takes into account the potential of the radiation fluxes, which is a function of time. Furthermore, the structure of the model used for the coupling of the carbon and methane cycles consists of 12 blocks, which carry out basic calculation procedures for their fluxes. Finally, the results of simulation experiments are discussed considering scenarios for changes in forest areas, showing their significant role in the climate change issue.

A recent deep earthquake doublet in light of long-term evolution of Nazca subduction

Earthquake faulting at ~600 km depth remains puzzling. Here we present a new kinematic interpretation of two Mw7.6 earthquakes of November 24, 2015. In contrast to teleseismic analysis of this doublet, we use regional seismic data providing robust two-point source models, further validated by regional back-projection and rupture-stop analysis. The doublet represents segmented rupture of a ∼30-year gap in a narrow, deep fault zone, fully consistent with the stress field derived from neighbouring 1976–2015 earthquakes. Seismic observations are interpreted using a geodynamic model of regional subduction, incorporating realistic rheology and major phase transitions, yielding a model slab that is nearly vertical in the deep-earthquake zone but stagnant below 660 km, consistent with tomographic imaging. Geodynamically modelled stresses match the seismically inferred stress field, where the steeply down-dip orientation of compressive stress axes at ∼600 km arises from combined viscous and buoyant forces resisting slab penetration into the lower mantle and deformation associated with slab buckling and stagnation. Observed fault-rupture geometry, demonstrated likelihood of seismic triggering, and high model temperatures in young subducted lithosphere, together favour nanometric crystallisation (and associated grain-boundary sliding) attending high-pressure dehydration as a likely seismogenic mechanism, unless a segment of much older lithosphere is present at depth.

Anisotropic triadic closures for shear-driven and buoyancy-driven turbulent flows

Abstract We show how two-point turbulence models based on triadic closures, initially developed for homogeneous isotropic turbulence, can be applied to anisotropic turbulent flows. Efficient numerical solution of these models is now feasible thanks to new computational capabilities. This permits exploration of their dynamics and structure at high Reynolds numbers and offers a complementary approach to direct numerical simulations. In this paper, implementation strategies, developed for shear and buoyancy driven turbulence, are reviewed and compared. A single formalism for anisotropic turbulence is proposed for both problems. Analyses of weakly anisotropic turbulence, for scales much smaller than Corrsin’s scale (shear case) and Ozmidov’s scale (stratified case) are revisited and new scaling laws are proposed. The effect of initial data is analyzed. The entire spectral range, including the infrared range, is considered.

Informatics-Based Energy Fitting Scheme for Correlation Energy at Complete Basis Set Limit.

Energy fitting schemes based on informatics techniques using hierarchical basis sets with small cardinal numbers were numerically investigated to estimate correlation energies at the complete basis set limits. Numerical validations confirmed that the conventional two-point extrapolation models can be unified into a simple formula with optimal parameters obtained by the same test sets. The extrapolation model was extended to two-point fitting models by a relaxation of the relationship between the extrapolation coefficients or a change of the fitting formula. Furthermore, n-scheme fitting models were developed by the combinations of results calculated at several theory levels and basis sets to compensate for the deficiencies in the fitting model at one level of theory. Systematic assessments on the Gaussian-3X and Gaussian-2 sets revealed that the fitting models drastically reduced errors with equal or smaller computational effort. © 2016 Wiley Periodicals, Inc.

Context matters: community characteristics and mental health among war‐affected youth in Sierra Leone

Worldwide, over one billion children and adolescents live in war-affected settings. At present, only limited research has investigated linkages between disrupted social ecology and adverse mental health outcomes among war-affected youth. In this study, we examine three community-level characteristics - social disorder and collective efficacy within the community, as reported by caregivers, and perceived stigma as reported by youth - in relation to externalizing behaviors and internalizing symptoms among male and female former child soldiers in postconflict Sierra Leone. A total of 243 former child soldiers (30% female, mean age at baseline: 16.6years) and their primary caregivers participated in interviews in 2004 and 2008, as part of a larger prospective cohort study of war-affected youth in Sierra Leone. Two-point growth models were estimated to examine the relationship between community-level characteristics and externalizing and internalizing outcomes across the time points. Both social disorder within the community, reported by caregivers, and perceived stigma, reported by youth, positively covaried with youths' externalizing and internalizing scores - indicating that higher levels of each at baseline and follow-up were associated with higher levels of mental health problems at both time points (p<.05). The relationship between collective efficacy and mental health outcomes was nonsignificant (p>.05). This study offers a rare glimpse into the role that the postconflict social context plays in shaping the mental health among former child soldiers. Results indicate that both social disorder and perceived stigma within the community demonstrate an important relationship to externalizing and internalizing problems among adolescent ex-combatants. Moreover, these relationships persisted over a 4-year period of follow-up. These results underscore the importance of the postconflict social environment and the need to develop postconflict interventions that address community-level processes in addition to the needs of families and individuals.