Set Of Scaling Factors Research Articles

Результати верифікації радіонуклідного вектора для характеризації твердих радіоактивних відходів ЧАЕС, що спрямовуються на захоронення

The first radionuclide vector (RV) for characterization of operational solid radioactive wastes (SRW) of Chornobyl Nuclear Power Plant (ChNPP) according to the IAEA methodology was established in 2018 and consisted of a set of scaling factors (SF), which have never been refined and updated, as it is recommended to be done from time to time. In this work, verification algorithm of previously established SF values, provided for by RV setting technique, was tested, and their values were updated with taking into account the implementation of a new approach for sorting ChNPP SRW into the streams. It was established that for such nuclides as 90Sr, 94Nb and 241Am, geometric mean values of SF or correlation function (CF) established on the basis of regression analysis of logarithms of nuclide content, can be used. For the other radionuclides (14С, 3Н and 235, 238U), whose activity levels were higher than the minimum detectable activity (MDA), arithmetic mean values of SF only can be used. For uranium isotopes 235, 238U, a high degree of correlation between their content is observed in all SRW materials, regardless of whether they belong to combustible or non-combustible operational waste of the ChNPP. According to the test results (testing for significance of difference under the null hypothesis) using the Student’s t-statistics, it was established that the same SF values can be applied to the waste temporarily stored in the eastern and western compartments of the ChNPP SRW repository. The waste should be separated into non-combustible and combustible materials only. This follows from the fact that combustible solid waste, if they are to be burned as it is planned, must be re-characterized using the SF value already determined for ash and by a different technique. However, until these wastes are burned, the obtained data allow estimating the expected levels of nuclide content in their ash residue.

Effect of model scale on helical piles response established from shake table tests

This paper investigates the effect of model scale on seismic response of prototype helical pile (HP) groups employing finite element modelling approach verified by the results of single gravity shaking table models of piles installed in dry and saturated sands. The prototype shaking test configuration was established from model shake table tests by adopting a set of similarity and dimensional laws. The results demonstrated that the scaled models exhibited generally similar responses. The HPs' response in the saturated sand bed was dominated by the rocking behaviour, while the flexural behaviour dominated the response in the dry tests. In addition, the HPs' lateral response followed the lateral soil uniform deformation in the dry tests, while they did not follow the nonuniform soil deformation in the saturated tests. However, the prototype models' axial and lateral responses were different from the results of the shaking table scale. The HP exhibited less scaled lateral deformation, bending moments, and settlement in the prototype models than those at the shaking table scale in the dry and saturated tests. Meanwhile, the prototype helices’ stress was higher than the shaking table helices in the saturated tests and less than them in the dry tests. A set of scaling factors was suggested for extrapolating the soil and HP responses from 1 g shake table model tests. Based on the obtained results, the soil and HP responses may be extrapolated from 1 g shake table model tests employing the following scaling factors: soil displacement increase factor, SDIF = 0.8n in the saturated tests, and SDIF = 0.6n in the dry tests, while the pile displacement increase factor, PDIF = 0.7n in the saturated test and 0.5n in the dry test.

Research on a component characteristic adaptive correction method for variable cycle engines

Abstract There is inevitably a performance deviation between an engine model and an actual engine that is influenced by unpredictable factors such as the unsuspected environmental conditions and the natural performance degradation in the process of use. Because the engine model precision largely depends on the accuracies of the component maps, it is possible to revise the engine model to determine a better trend for the engine performance from recorded measurements by adjusting the maps. This paper presents a new method for updating the variable geometry component maps of a variable cycle engine (VCE) by using a set of scaling factors estimated with the cubature Kalman filter (CKF). A mapping function is created between the scaling factors and the component characteristic scaling coefficients for the adjustments of the maps. The proposed method is applied to a VCE model according to the VCE benchmark steady-state performance data. The results show that the maximum simulation error of the engine steady-state model decreases from 5.33 to 0.93%, and the CKF-based adaptation method provides a much faster computing rate than the particle swarm optimization (PSO) based adaptation method, which verifies the effectiveness and engineering applicability of the variable geometry characteristic adaptive correction method.

Research on a component characteristic adaptive correction method for variable cycle engines

Abstract There is inevitably a performance deviation between an engine model and an actual engine that is influenced by unpredictable factors such as the unsuspected environmental conditions and the natural performance degradation in the process of use. Because the engine model precision largely depends on the accuracies of the component maps, it is possible to revise the engine model to determine a better trend for the engine performance from recorded measurements by adjusting the maps. This paper presents a new method for updating the variable geometry component maps of a variable cycle engine (VCE) by using a set of scaling factors estimated with the cubature Kalman filter (CKF). A mapping function is created between the scaling factors and the component characteristic scaling coefficients for the adjustments of the maps. The proposed method is applied to a VCE model according to the VCE benchmark steady-state performance data. The results show that the maximum simulation error of the engine steady-state model decreases from 5.33 to 0.93%, and the CKF-based adaptation method provides a much faster computing rate than the particle swarm optimization (PSO) based adaptation method, which verifies the effectiveness and engineering applicability of the variable geometry characteristic adaptive correction method.

Equivalent Modelling of Wind Farms for Probabilistic Harmonic Propagation Studies

This paper investigates the effect of modelling of different aspects of wind farms (WF) as a first step towards development of the equivalent harmonic model initially of WF, and later of other types of converter connected generation, for studies of harmonic propagation and mitigation in power electronics (PE) rich transmission networks. The aim of the study was to establish a set of scaling factors that can be used when modelling the entire WF as a single probabilistic harmonic generator in harmonic propagation studies, considering different WF configurations, weather conditions, harmonic cancellation effects, individual wind generator availability, cable disconnection, and the influence of the non-ideal external grid. The importance of modelling resonance and individual characteristic harmonics on the equivalent modelling of WF has also been established. The results facilitate the assessment of global contribution of PE connected RES to harmonic levels in transmission networks and more generally harmonic propagation studies in large PE rich transmission networks.

Quantitative Estimation of Dynamic Modulation in Remote Environment Sensing

Teleoperated robots are an effective means to sense a remote environment. Impedance control is often preferred in teleoperated robots due to its capability to modulate the dynamic relationship between the position and force of the robot. One of the challenges in the practical implementation of impedance controllers is the determination of the extent to which the dynamic properties of the robot are to be modified. A methodology for quantitatively estimating the desired dynamic parameters of the robot in order to have stable interaction with the environment is proposed in this paper. The best set of scaling factors by which the environment parameters need to be scaled to obtain a corresponding desired parameter for the robot are formulated. In addition, novel impedance controllers for teleoperated robots, which achieve the desired dynamic performance even under time-varying delays, are formulated in this paper. The uniqueness of the proposed controllers lies in enabling the system to interact with a wide range of environments, unlike the traditional teleoperation controllers which allow interaction with only those environments whose dynamic properties are within a specific range. Passivity analysis is performed to prove the global asymptotic stability of the system. Experimental implementation demonstrates the successful sensing of a wide range of environments.

COEFFICIENTS FOR ESTIMATING PRENATAL DOSE IN PREGNANT WORKERS FROM ACUTE INTAKES.

Inhalation and ingestion dose coefficients for the embryo and fetus from intakes of radionuclides by the mother are provided in the International Commission on Radiological Protection (ICRP) Publication 88 for intake of each of 74 radionuclides. To address the many other possible radionuclides to which workers may be exposed, effective dose coefficients were developed for the embryo/fetus for all additional radionuclides addressed in ICRP Publication 107 with half-life of 10min or more. The general approach was to use the estimated dose to the mother's uterus during pregnancy as a scalable proxy for the dose to the embryo/fetus. The set of scaling factors used in the study was derived from analyses of the relationships of the dose to the mother's uterus and the effective dose to the embryo/fetus for the ~400 cases (considering two intake modes and multiple forms of many of the radionuclides) addressed in Publication 88.

Performance of Coarse Graining in Estimating Polymer Properties: Comparison with the Atomistic Model.

Combining atomistic and coarse-grained (CG) models is a promising approach for quantitative prediction of polymer properties. However, the gaps between the length and time scales of atomistic and CG models still need to be bridged. Here, the scale gaps of the atomistic model of polyethylene melts, the bead–spring Kremer–Grest model, and dissipative particle dynamics with the slip-spring model were investigated. A single set of spatial and temporal scaling factors was determined between the atomistic model and each CG model. The results of the CG models were rescaled using the set of scaling factors and compared with those of the atomistic model. For each polymer property, a threshold value indicating the onset of static or dynamic universality of polymers was obtained. The scaling factors also revealed the computational efficiency of each CG model with respect to the atomistic model. The performance of the CG models of polymers was systematically evaluated in terms of both the accuracy and computational efficiency.

Validation of a finite element modelling approach on soil-foundation-structure interaction of a multi-storey wall-frame structure under dynamic loadings

Validated numerical approaches are very important in dynamic studies of soil-structure interaction. Experimental outputs of physical models are required to validate the numerical approaches. Testing and analysis of an experimental scaled model is economical in comparison with investigating real size structures. However, a set of scale factors are required to model a full-scale structure accurately as a scaled model in a laboratory environment. In this paper, the scaling procedure and design of a scaled multi-storey concrete wall-frame structure with a scale factor of 1:50 are addressed. A specially selected dry sand with round shaped particles and specific grain size distribution was adopted in this study. A flexible soil container was designed and built to represent the soil boundary behaviour during time-history seismic excitations. The experimental investigations were divided into three different stages: fixed based structure without soil interaction; soil container without any structure; and, a structure with raft and pile foundations in the soil container. Finally, the same experimental stages were modelled numerically using a 3D finite element software. The results showed that the finite element simulations produced a good response when compared with the experimental results and these numerical models are suitable to be employed for further dynamic studies.

Semi-Supervised Feature Selection via Sparse Rescaled Linear Square Regression

With the rapid increase of the data size, it has increasing demands for selecting features by exploiting both labeled and unlabeled data. In this paper, we propose a novel semi-supervised embedded feature selection method. The new method extends the least square regression model by rescaling the regression coefficients in the least square regression with a set of scale factors, which is used for evaluating the importance of features. An iterative algorithm is proposed to optimize the new model. It has been proved that solving the new model is equivalent to solving a sparse model with a flexible and adaptable $\ell _{2,p}$ l 2 , p norm regularization. Moreover, the optimal solution of scale factors provides a theoretical explanation for why we can use $\lbrace \left\Vert \mathbf {w}^{1} \right\Vert _{2},\ldots, \left\Vert \mathbf {w}^{d} \right\Vert _{2}\rbrace$ { w 1 2 , ... , w d 2 } to evaluate the importance of features. Experimental results on eight benchmark data sets show the superior performance of the proposed method.

Generator of a Toy Dataset of Multi-Polygon Monochrome Images for Rapidly Testing and Prototyping Semantic Image Segmentation Networks

Abstract In the paper, the problem of building semantic image segmentation networks in a more efficient way is considered. Building a network capable of successfully segmenting real-world images does not require a real semantic image segmentation task. At this stage, called prototyping, a toy dataset can be used. Such a dataset can be artificial and thus may not need augmentation for training. Besides, its entries are images of much smaller size, which allows training and testing the network a way faster. Objects to be segmented are one or few convex polygons in one image. Thus, a toy dataset generator is created whose complexity is regulated by the number of edges in a polygon, the maximal number of polygons in one image, the set of scale factors, and the set of probabilities determining how many polygons in a current image are generated. The dataset capacity and image size are concurrently adjustable, although they are much less influential.

Multi-region dynamic economic dispatch of solar–wind–hydro–thermal power system incorporating pumped hydro energy storage

This paper suggests chaotic fast convergence evolutionary programming (CFCEP) for solving multi-region dynamic economic dispatch (MRDED) problem, multi-region economic dispatch (MRED) problem and economic dispatch (ED) problem. MRDED problem is based on multi-reservoir cascaded hydro plant with time delay, thermal plants with nonsmooth fuel cost function, wind and solar power units with uncertainty and pumped hydro energy storage. MRED problem deals with tie line constraints, transmission losses, valve point effect and proscribed workable area of thermal generators. ED problem deals with valve point effect, proscribed workable area and ramp rate limits of thermal generators. In the recommended technique, chaotic sequences have been pertained for acquiring the dynamic scaling factor setting in fast convergence evolutionary programming (FCEP). The efficacy of the proposed technique has been verified on convoluted three-area system for MRDED problem, four-area system for MRED problem and 140-unit Korean system for ED problem. Test results acquired from the suggested CFCEP technique have been fit to that acquired from FCEP, differential evolution (DE) and particle swarm optimization (PSO). It has been observed from the comparison that the recommended CFCEP technique has the capability to bestow with better-quality solution.

Dynamic economic dispatch with demand-side management incorporating renewable energy sources and pumped hydroelectric energy storage

This paper recommends chaotic fast convergence evolutionary programming (CFCEP) for solving real-world dynamic economic dispatch (DED) with demand-side management (DSM) incorporating renewable energy sources and pumped-storage hydroelectric unit. Here, solar–wind–thermal energy system has been considered taking into account pumped-storage hydroelectric unit and uncertainty of solar and wind energy sources. DSM programs reduce cost and boost up power system security. To investigate the upshot of DSM, the DED problem is solved with and without DSM. In the recommended technique, chaotic sequences have been applied for acquiring the dynamic scaling factor setting in FCEP. The efficiency of the recommended technique is revealed on two test systems. Simulation outcomes of the suggested technique have been matched against those acquired by fast convergence evolutionary programming (FCEP), colonial competitive differential evolution and heterogeneous strategy particle swarm optimization. It has been observed from the comparison that the recommended CFCEP technique has the ability to give better-quality solution.

Combined heat and power dynamic economic dispatch with demand side management incorporating renewable energy sources and pumped hydro energy storage

This study suggests chaotic fast convergence evolutionary programming (CFCEP) rooted in Tent equation for solving intricate actual world combined heat and power dynamic economic dispatch (CHPDED) problem with demand side management (DSM) incorporating renewable energy sources and pumped-storage-hydraulic unit. The valve point effect and proscribed workable area of thermal generators and solar and wind power uncertainty have been pondered. DSM programmes decrease cost and boost up power system security. To investigate the upshot of DSM, the CHPDED problem is solved with and without DSM. In the recommended CFCEP technique, chaotic sequences have been pertained for acquiring the dynamic scaling factor setting in fast convergence evolutionary programming (FCEP). Introduction of chaotic sequences helps FCEP to avoid premature convergence. The efficiency of the recommended technique is revealed in a test system. Simulation outcomes of the recommended technique have been evaluated with those attained by FCEP and differential evolution. It has been examined from the assessment that the recommended CFCEP has the capability to bestow with a better-quality solution.

Dynamic economic dispatch incorporating renewable energy sources and pumped hydroenergy storage

Due to mounting infiltration of solar and wind energy sources, it becomes essential to investigate its brunt on the dynamic economic dispatch. Here, solar–wind–thermal system integrating pumped-storage hydraulic unit has been considered. This work recommends chaotic fast convergence evolutionary programming (CFCEP) rooted in Tent equation for solving dynamic economic dispatch problem incorporating renewable energy sources and pumped-storage hydraulic unit. Chaotic sequences increase the exploitation ability in the searching space and enhance the convergence property. In the recommended technique, chaotic sequences have been pertained for acquiring the dynamic scaling factor setting in fast convergence evolutionary programming (FCEP). The efficiency of the recommended technique is revealed on two test systems. Simulation outcomes of the suggested technique have been matched up to those acquired by FCEP, differential evolution and particle swarm optimization. It has been observed from the comparison that the recommended CFCEP technique has the capability to confer with better quality solution.

Optimal generation scheduling of hydrothermal system with demand side management considering uncertainty and outage of renewable energy sources

Due to escalating permeation of renewable energy sources, it becomes essential to investigate its brunt on the optimal power generation scheduling. But, highly intermittent nature of renewable energy sources and their higher rate of outages may have detrimental effect on the entire grid. This work recommends chaotic fast convergence evolutionary programming (CFCEP) rooted in Tent equation to solve hydrothermal generation scheduling incorporating pumped-storage-hydraulic (PSH) unit with demand side management (DSM) considering uncertainty and outage of renewable energy sources. Chaotic sequences increase the exploitation ability in the searching space and enhance the convergence property. In the recommended technique, chaotic sequences have been pertained for acquiring the dynamic scaling factor setting in fast convergence evolutionary programming (FCEP). Simulation outcomes of the test system have been matched up to those acquired by FCEP, differential evolution (DE) and particle swarm optimization (PSO). It has been observed from the comparison that the recommended CFCEP technique has the capability to bestow with superior-quality solution.

Modeling the angular momentum control of small spacecraft with a magnetic attitude control system

The problem of modeling the angular momentum control modes of small spacecraft using electromagnetic systems interacting with the Earth’s magnetic field is considered. The electromagnetic system control law has been constructed for various compositions of measurable parameters. A set of scale factors has been formed to investigate the angular momentum control mode of dynamically similar models. Based on a dynamical test stand, we have carried out experimental studies to model the angular motion dynamics of small spacecraft with a magnetic attitude control system.

Dynamic measurements of drainage capillary pressure curves in carbonate rocks

The heterogeneity of rocks represents a challenge for interpreting and using outcomes from multiphase-flow experiments carried out on laboratory samples. While the capillary pressure–saturation function, pc(S), is known to vary spatially and cause local saturation development during immiscible displacements, its variation remains difficult to measure. This is particularly challenging for rocks with complex fabrics, such as carbonates. Here, we present a workflow for the dynamic measurement of core- and subcore-scale drainage pc(S) curves in heterogeneous porous media. Multi-rate, two-phase core-flooding tests are conducted on three carbonate rocks with direct observations of local saturation data. The interpretation of the experiments is done by fitting the parameters of the pc(S) curve, while describing both steady-state saturation and pressure profiles with a detailed one-dimensional model that accounts for the variation of subcore-scale properties in the direction of displacement. Workflow validation is achieved by means of synthetic data, thereby demonstrating the uniqueness of the solution of the resulting multi-objective optimisation problem. The model reproduces accurately experimental data on the three rocks and enables computing the effective core-scale pc(S) curve in the limit of zero velocity, as it would be expected during a porous-plate experiment. The output of the proposed technique is however much richer and includes the relativepc(S) curve that is universal and independent of the specific pattern of heterogeneity, in addition to a set of scaling factors. The latter describe the distribution of the pc(S) curves at the subcore-scale due to heterogeneity and form the statistical basis needed for upscaling studies.

Modeling the Angular Momentum Control of Small Spacecraft with a Magnetic Attitude Control System

The problem of modeling the angular momentum control modes of small spacecraft using electromagnetic systems interacting with the Earth’s magnetic field is considered. The electromagnetic system control law has been constructed for various compositions of measurable parameters. A set of scale factors has been formed to investigate the angular momentum control mode of dynamically similar models. Based on a dynamical test stand, we have carried out experimental studies to model the angular motion dynamics of small spacecraft with a magnetic attitude control system.

Towards an Accurate Prediction of Nitrogen Chemical Shifts by Density Functional Theory and Gauge‐Including Atomic Orbital

AbstractAn efficient, yet accurate, computational protocol for predicting nitrogen nuclear magnetic resonance (NMR) chemical shifts based on density functional theory and the gauge‐including atomic orbital approach is proposed. A database of small and relatively rigid compounds containing nitrogen atoms is compiled. Scaling factors for the linear correlation between experimental 15N chemical shifts and calculated isotropic shielding constants are systematically investigated with seven different levels of theory in both chloroform and dimethyl sulfoxide, two commonly used solvents for NMR experiments. The best method yields a root‐mean‐square deviation of about 5.30 and 7.00 ppm in CHCl3 and dimethyl sulfoxide (DMSO), respectively. Moreover, another set of scaling factors for –NH2 chemical shifts is also proposed based on a separate database with three levels of theory. Furthermore, it is encouraging that a reasonable transferability for the linear correlation is found between these two solvents. This finding will enable broader applications of the developed empirical scaling factors to other commonly used solvents in NMR experiments. The consistency between theoretical predictions and experimental results for structural elucidations is illustrated for selected examples including regioisomers, tautomers, oxidation states, and protonated structures.