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At least 955 records · Page 53

An iris biometric protection scheme using 4D hyperchaotic system and modified equal modulus decomposition in hybrid multi resolution wavelet domain

In this paper, a hybrid iris biometric protection scheme using 4D hyperchaotic system by means of coherent superposition and modified equal modulus decomposition in hybrid multi-resolution wavelet domain is proposed. The 4D hyperchaotic framework is employed for producing the permutation keystream for pixel swap-over mechanism. The hybrid multi-resolution is produced by means of Kronecker product of Walsh transform and fractional Fourier transform of different orders. Fractional orders of the hybrid multiresolution wavelet along with the parameters and initial conditions of the 4D hyperchaotic framework, later fill in as additional keys, thus enhancing the key space of the proposed mechanism. The proposed scheme has nonlinear characteristics and has high robustness against brute-force attack attributable to its enormous key-space. Numerical simulations have been carried out on grayscale images to prove the authenticity and efficacy of the proposed cryptosystem. The functioning of the proposed cryptosystem is investigated against various attacks including special attack. Outcomes display that the proposed iris template protection scheme not only has higher robustness against noise attack but is also unassailable to the iterative transform-based attacks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Renewable energy integration and system operation challenge: control and optimization of millions of devices

The electric power infrastructure, originally designed and built on large-scale power plants, is evolving into a more resilient power generation and delivery system in which millions of smaller units of distributed energy generation resources units will be installed in sub-transmission and distribution networks. In order to control, manage and optimize the future grid, a hierarchical design is presented in this chapter which enables the distributed control on grid edge while inheriting the existing centralized control structure. This layered design of large-scale power system operation and control uses the following principle: reactive power control is treated as a primary control for voltage stability, and the real power control is primarily a grid-level control but can also be a supplementary control for voltage support in the case of insufficient reactive power control capacity. For the purpose of active control and operation at the distribution level, a recursive power network model is derived from nodal injection and branch power flow models. Based on the model, the proposed algorithms of hierarchical control, grid-edge inference and dynamic hosting allowance are developed and presented for multi-level controlled operation. And, a co-simulation architecture of integrated T&D system is presented to validate and demonstrate the feasibility and scalability of proposed algorithms.

Xu, Ying↗

Virtual refrigerant charge sensor for variable-speed heat pumps based on feature selection

The refrigerant charge level in heat pump systems significantly impacts their energy efficiency. Virtual refrigerant charge (VRC) sensing technology has been comprehensively investigated and well-established due to its lower cost compared to physical sensors. However, the previous VRC research often relied on expert judgment and physical reasoning for their variable selection, which can potentially select redundant (or highly correlated) or insignificant features, and it is also primarily focused on single-speed systems. To address these challenges, this study proposes a VRC algorithm for variable-speed heat pumps that selects features through a rigorous feature selection method in combination with physical insights. We also propose a piecewise linear model structure segmented by subcooling temperature to accurately predict charge levels, particularly when subcooling temperatures are substantially low. The proposed algorithm was evaluated using experimental data of a residential R410A heat pump, and the performance was compared with two baseline VRC algorithms. The results are: (1) The proposed algorithm outperforms for the case with subcooling temperature less than 1 °C. (2) The proposed algorithm achieves a tested mean absolute percentage error (MAPE) of 4.23%, and improves the overall accuracy for cooling conditions by approximately 60%, compared with the two baseline algorithms. (3) The proposed algorithm uses two fewer features and improves the accuracy for undercharge cooling conditions by 68.0%, compared with baseline algorithm 2. These improvements enhance prediction accuracy and prevent overfitting, providing a more reliable refrigerant charge level prediction and helping improve the heat pump energy efficiency.

Liang, Chenjiyu↗

Utilization of waste heat from a commercial GT for freshwater production, cooling and additional power: Exergoeconomic analysis and optimization

In this work, a multigeneration system is proposed for power, cooling and freshwater production. The waste heat from a SIEMENS SGT6-2000E GT is utilized to drive a supercritical CO 2 recompression Brayton cycle (SCRBC) and multi-effect desalination (MED) with thermal vapor compressor (TVC), while the waste heat from the pre-cooler of the SCRBC is utilized to drive an absorption cooling cycle. Detailed thermodynamic, exergy and exergoeconomic analyses are performed for the proposed multigeneration system using Engineering Equation Solver (EES). A sensitivity study is also performed to study the effects of the main operational parameters on the proposed system performance. Finally, multi-objective optimization using a genetic algorithm approach in EES is carried out to reach the optimal design. The proposed system can consume 34.2% less energy input and reduce CO 2 emission by 39.3% compared to the stand-alone systems for power, cooling and freshwater production. The results show that the energy utilization factor and exergy efficiency of the proposed system are improved by 33.6% and 14.3%, respectively, while the total unit product cost is reduced by 11.3% compared to the stand-alone GT cycle. Further, from exergoeconomic optimization, the proposed system can produce 132.4 MW of power, 7.09 MW of cooling and 650 kg/s of freshwater at energy utilization factor of 57.5%, exergy efficiency of 39.7% and total unit product cost of 16.3 $/GJ.

42 ENGINEERING↗

Asymmetric Yield Function Based on the Stress Invariants for Pressure Sensitive Metals

A general asymmetric yield function is proposed with dependence on the stress invariants for pressure sensitive metals. The pressure sensitivity of the proposed yield function is consistent with the experimental result of Spitzig and Richmond (1984) for steel and aluminum alloys while the asymmetry of the third invariant is preserved to model strength differential (SD) effect of pressure insensitive materials. The proposed yield function is transformed in the space of the stress triaxaility, the von Mises stress and the normalized invariant to theoretically investigate the possible reason of the SD effect. The proposed plasticity model is further extended to characterize the anisotropic behavior of metals both in tension and compression. The extension of the yield function is realized by introducing two distinct fourth-order linear transformation tensors of the stress tensor for the second and third invariants, respectively. The extended yield function reasonably models the evolution of yield surfaces for a zirconium clock-rolled plate during in-plane and through-thickness compression reported by Plunkett et al. (2007). The extended yield function is also applied to describe the orthotropic behavior of a face-centered cubic metal of AA 2008-T4 and two hexagonal close-packed metals of high-purity-titanium and AZ31 magnesium alloy. The orthotropic behavior predicted by the generalized model is compared with experimental results of these metals. The comparison validates that the proposed yield function provides sufficient predictability on SD effect and anisotropic behavior both in tension and compression. When it is necessary to consider r-value anisotropy, the proposed function is efficient to be used with nonassociated flow plasticity by introducing a separate plastic potential for the consideration of r-values as shown in Stoughton & Yoon (2004, 2009).

99 GENERAL AND MISCELLANEOUS↗

A multiscale modeling technique for bridging molecular dynamics with finite element method

In computational mechanics, molecular dynamics (MD) and finite element (FE) analysis are well developed and most popular on nanoscale and macroscale analysis, respectively. MD can very well simulate the atomistic behavior, but cannot simulate macroscale length and time due to computational limits. FE can very well simulate continuum mechanics (CM) problems, but has the limitation of the lack of atomistic level degrees of freedom. Multiscale modeling is an expedient methodology with a potential to connect different levels of modeling such as quantum mechanics, molecular dynamics, and continuum mechanics. This study proposes a new multiscale modeling technique to couple MD with FE. The proposed method relies on weighted average momentum principle. A wave propagation example has been used to illustrate the challenges in coupling MD with FE and to verify the proposed technique. Furthermore, 2-Dimensional problem has also been used to demonstrate how this method would translate into real world applications. -- Highlights: •A weighted averaging momentum method is introduced for bridging molecular dynamics (MD) with finite element (FE) method. •The proposed method shows excellent coupling results in 1-D and 2-D examples. •The proposed method successfully reduces the spurious wave reflection at the border of MD and FE regions. •Big advantages of the proposed method are simplicity and inexpensive computational cost of multiscale analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An efficient computational method for solving nonlinear stochastic Itô integral equations: Application for stochastic problems in physics

Because of the nonlinearity, closed-form solutions of many important stochastic functional equations are virtually impossible to obtain. Thus, numerical solutions are a viable alternative. In this paper, a new computational method based on the generalized hat basis functions together with their stochastic operational matrix of Itô-integration is proposed for solving nonlinear stochastic Itô integral equations in large intervals. In the proposed method, a new technique for computing nonlinear terms in such problems is presented. The main advantage of the proposed method is that it transforms problems under consideration into nonlinear systems of algebraic equations which can be simply solved. Error analysis of the proposed method is investigated and also the efficiency of this method is shown on some concrete examples. The obtained results reveal that the proposed method is very accurate and efficient. As two useful applications, the proposed method is applied to obtain approximate solutions of the stochastic population growth models and stochastic pendulum problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A mass-conserving lattice Boltzmann method with dynamic grid refinement for immiscible two-phase flows

A mass-conserving lattice Boltzmann method (LBM) for multiphase flows is presented in this paper. The proposed LBM improves a previous model (Lee and Liu, 2010 [21]) in terms of mass conservation, speed-up, and efficiency, and also extends its capabilities for implementation on non-uniform grids. The presented model consists of a phase-field lattice Boltzmann equation (LBE) for tracking the interface between different fluids and a pressure-evolution LBM for recovering the hydrodynamic properties. In addition to the mass conservation property and the simplicity of the algorithm, the advantages of the current phase-field LBE are that it is an order of magnitude faster than the previous interface tracking LBE proposed by Lee and Liu (2010) [21] and it requires less memory resources for data storage. Meanwhile, the pressure-evolution LBM is equipped with a multi-relaxation-time (MRT) collision operator to facilitate attainability of small relaxation rates thereby allowing simulation of multiphase flows at higher Reynolds numbers. Additionally, we reformulate the presented MRT-LBM on nonuniform grids within an adaptive mesh refinement (AMR) framework. Various benchmark studies such as a rising bubble and a falling drop under buoyancy, droplet splashing on a wet surface, and droplet coalescence onto a fluid interface are conducted to examine the accuracy and versatility of the proposed AMR-LBM. The proposed model is further validated by comparing the results with other LB models on uniform grids. A factor of about 20 in savings of computational resources is achieved by using the proposed AMR-LBM. As a more demanding application, the Kelvin–Helmholtz instability (KHI) of a shear-layer flow is investigated for both density-matched and density-stratified binary fluids. The KHI results of the density-matched fluids are shown to be in good agreement with the benchmark AMR results based on the sharp-interface approach. When a density contrast between the two fluids exists, a typical chaotic structure in the flow field is observed at a Reynolds number of 10000, which indicates that the proposed model is a promising tool for direct numerical simulation of two-phase flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Systematic parameter inference in stochastic mesoscopic modeling

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Memory-optimized shift operator alternating direction implicit finite difference time domain method for plasma

Through introducing the alternating direction implicit (ADI) technique and the memory-optimized algorithm to the shift operator (SO) finite difference time domain (FDTD) method, the memory-optimized SO-ADI FDTD for nonmagnetized collisional plasma is proposed and the corresponding formulae of the proposed method for programming are deduced. In order to further the computational efficiency, the iteration method rather than Gauss elimination method is employed to solve the equation set in the derivation of the formulae. Complicated transformations and convolutions are avoided in the proposed method compared with the Z transforms (ZT) ADI FDTD method and the piecewise linear JE recursive convolution (PLJERC) ADI FDTD method. The numerical dispersion of the SO-ADI FDTD method with different plasma frequencies and electron collision frequencies is analyzed and the appropriate ratio of grid size to the minimum wavelength is given. The accuracy of the proposed method is validated by the reflection coefficient test on a nonmagnetized collisional plasma sheet. The testing results show that the proposed method is advantageous for improving computational efficiency and saving computer memory. The reflection coefficient of a perfect electric conductor (PEC) sheet covered by multilayer plasma and the RCS of the objects coated by plasma are calculated by the proposed method and the simulation results are analyzed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Implementing contact angle boundary conditions for second-order Phase-Field models of wall-bounded multiphase flows

In the present work, a general formulation is proposed to implement the contact angle boundary conditions for the second-order Phase-Field models, which is applicable to N-phase (N ≥ 2) moving contact line problems. To remedy the issue of mass change due to the contact angle boundary condition, a source term or Lagrange multiplier is added to the original second-order Phase-Field models, which is determined by the consistent and conservative volume distribution algorithm so that the summation of the order parameters and the consistency of reduction are not influenced. To physically couple the proposed formulation to the hydrodynamics, especially for large-density-ratio problems, the consistent formulation is employed. The reduction-consistent conservative Allen-Cahn models are chosen as examples to illustrate the application of the proposed formulation. The numerical scheme that preserves the consistency and conservation of the proposed formulation is employed to demonstrate its effectiveness. Results produced by the proposed formulation are in good agreement with the exact and/or asymptotic solutions. The proposed method captures complex dynamics of moving contact line problems having large density ratios.

97 MATHEMATICS AND COMPUTING↗

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗

Nuclear Data Sheets for A=266,270,274,278,282,286,290,294,298☆

Spectroscopic information such as production, identification, half-lives, decay modes and possible excited states for experimentally known nuclides of mass numbers 266, 270, 274, 278, 282, 286, 290, 294, and 298 are presented together with the recommended values, superseding information and data in the previous ENSDF and NDS evaluation by 2005Gu33. No nuclides have yet been identified for A=302. In the last 14 years, large amounts of new and definitive data on the superheavy nuclides (SHN) have become available, thus changing almost entirely the landscape of nuclear data in this mass region, as also indicated by a number of recent review articles: 2017Og01, 2016Ho09, 2016Ho06 (for fission barriers), 2015Og05, 2015Og07, 2015Mo25, 2015OgZX, 2013Th02, and 2011Og07. See 2016Ka49 for IUPAC technical discussions for the discovery of Z=117 (Ts), Z=115 (Mc), Z=113 (Nh), 2001Ka70 and 2003Ka71 for Z=110-112, 2011Ba54 for Z≥113, 2009Ba62 for Z=112, and 2016Ka50 for Z=118 (Og). A special issue of Nuclear Physics A444 (2015) is devoted to research on superheavy elements (SHE) with 27 articles. In particular, see article by 2015Ko20 on mass spectrometric searches for superheavy elements in terrestrial matter. See also Proceedings of Nobel Symposium NS160 ‘Chemistry and Physics of Heavy and Superheavy Elements’ published in Eur. Phys. Jour. Web of Conferences 131 (2016), in particular 2016UtZZ, 2016DmZZ and 2016HoZY. See also 2016DuZX for future prospects of discovery of elements beyond Z=118 A=266: {sup 266}Db, {sup 266}Sg, {sup 266}Bh, {sup 266}Hs and {sup 266}Mt are the experimentally identified nuclides with A=266. Identification of {sup 266}Lr from α decay of {sup 270}Db has been proposed by 2014Kh04 from experiments at GSI, but complete details and analyses of all the four decay chains reported in this experiment have not yet been published, and discussion in 2015Og05 review article considering their work from Dubna (2013Og04, 2011Og04) and from GSI (2014Kh04) still concluded that {sup 270}Db decayed dominantly by SF mode, in contrast with dominant α decay mode proposed by 2014Kh04. Experiments carried out at FLNR-JINR-Dubna in collaboration with LLNL and ORNL, GSI-SHIP facility, RIKEN, and LBNL facilities: {sup 266}Db from the α-decay of {sup 282}Nh in two correlated decay chains at Dubna; {sup 266}Sg as α-daughter of {sup 270}Hs in 12 correlated decay chains at Dubna and GSI; {sup 266}Bh in α decay of {sup 278}Nh in three correlated decay chains observed at RIKEN, and also directly with one event in {sup 249}Bk({sup 22}Ne,5n) at LBNL, and with four events in {sup 243}Am({sup 26}Mg,3n) at HIRFL-Lanzhou; {sup 266}Hs as α-daughter of {sup 270}Ds at GSI in two different experiments, six correlated decays in the first, and 25 decay chains in the second experiment, the analysis of which has not been fully reported as yet; and {sup 266}Mt directly in {sup 209}Bi({sup 58}Fe,n) reaction at GSI in two different experiments, observing three events in the first experiment and 12 events in the second, also produced in {sup 208}Pb({sup 59}Co,n) reaction at LBNL, observing five correlated decay chains. See also 2000Ho27 for discussion on {sup 266}Sg and {sup 266}Mt. A=270: {sup 270}Db, {sup 270}Bh, {sup 270}Hs, {sup 270}Mt and {sup 270}Ds are the experimentally identified nuclides with A=270 are presented. Experiments carried out at FLNR-JINR-Dubna in collaboration with LLNL and ORNL, GSI-SHIP facility, and RIKEN: {sup 270}Db from the decay of {sup 294}Ts in six correlated decay chains at Dubna and GSI; {sup 270}Bh as α great-granddaughter of {sup 282}Nh in two correlated decay chains observed at Dubna; {sup 270}Hs directly in {sup 248}Cm({sup 26}Mg,4n) reaction at GSI, and in {sup 226}Ra({sup 48}Ca,4n) reaction at Dubna; {sup 270}Mt as granddaughter of {sup 278}Ts in three correlated decay chains at RIKEN; and {sup 270}Ds directly in {sup 207}Pb({sup 64}Ni,n) at GSI in 33 correlated decay chains. A=274: {sup 274}Bh, {sup 274}Mt and {sup 274}Rg are the experimentally identified nuclides with A=274. Search for {sup 274}Ds in {sup 238}U({sup 40}Ar, 4n),E=5.7 MeV/nucleon reaction and subsequent α decays at GSI (1990Sc11) proved negative. Experiments carried out at FLNR-JINR-Dubna in collaboration with LLNL and ORNL, GSI-SHIP facility, and RIKEN: {sup 274}Bh from the decay of {sup 294}Ts in six correlated decay chains at Dubna and GSI, {sup 274}Mt produced as α daughter of {sup 282}Nh in two correlated decay chains observed at Dubna, and {sup 274}Rg as α daughter of {sup 278}Nh produced in three correlated decay chains at RIKEN. A=278: {sup 278}Mt, {sup 278}Rg and {sup 278}Nh are the experimentally identified nuclides with A=278. A very tentative evidence is provided for {sup 278}Bh and {sup 278}Hs from a chain originally observed and assigned to {sup 289}Fl by 1999Og10, but later reassigned by 2004Og10 to {sup 290}Fl, and further discussed in detail by 2016Ho09, where, based on systematics of α decays and SF half-lives, {sup 290}Fl is proposed to decay via ε mode to {sup 290}Nh, which then decays by an α chain, ending in {sup 278}Bh that decays by SF mode. Experiments carried out at FLNR-JINR-Dubna in collaboration with LLNL and ORNL labs in the USA, GSI-SHIP facility, and RIKEN: {sup 278}Mt from the decay of {sup 294}Ts in six correlated decay chains at Dubna and GSI, {sup 278}Rg produced as α daughter of {sup 282}Nh in two correlated decay chains observed at Dubna, and {sup 278}Nh produced directly in three correlated decay chains at RIKEN. A=282: {sup 282}Rg, {sup 282}Cn and {sup 282}Nh are the experimentally identified nuclides with A=282. A very tentative evidence is provided for {sup 282}Mt and {sup 282}Ds from a chain originally observed and assigned to {sup 289}Fl by 1999Og10, but later reassigned by 2004Og10 to {sup 290}Fl, and further discussed in detail by 2016Ho09, where, based on systematics of α decays and SF half-lives, {sup 290}Fl is proposed to decay via ε mode to {sup 290}Nh, which then decays by an α chain, ending in {sup 278}Bh that decays by SF mode. Experiments carried out at FLNR-Dubna, in collaboration with LLNL and ORNL labs in the USA, and at GSI-SHIP facility confirm the identification of these isotopes, {sup 282}Rg in α decay chain of {sup 294}Ts in six correlated decay chains at Dubna and GSI, {sup 282}Cn produced in four ways at Dubna: independently in one correlated decay chain, as α daughter of {sup 286}Lv in 11 correlated decay chains, as α grand-daughter of {sup 290}Lv in 12 correlated decay chains, as α great-grand daughter of {sup 294}Og in four correlated decay chains, and {sup 282}Nh produced at Dubna directly in two correlated decay chains. A=286: {sup 286}Nh and {sup 286}Fl are the only experimentally identified nuclides with A=286. A very tentative evidence is provided for {sup 286}Rg and {sup 286}Cn from a chain originally observed and assigned to {sup 289}Fl by 1999Og10, but later reassigned by 2004Og10 to {sup 290}Fl, and further discussed in detail by 2016Ho09, where, based on systematics of α decays and SF half-lives, {sup 290}Fl is proposed to decay via ε mode to {sup 290}Nh, which then decays by an α chain, ending in {sup 278}Bh that decays by SF mode. 2017Ka66 in experiments at RIKEN using GARIS separator interpret one correlated decay chain in three different ways, one involving possible production of {sup 294}Lv in {sup 248}Cm({sup 48}Ca,2n),E=261.6 MeV, and α decay to {sup 290}Fl which further decays to {sup 286}Cn. Experiments carried out at FLNR-Dubna, in collaboration with LLNL and ORNL labs in the USA, and at GSI-SHIP facility confirm the identification of these isotopes, {sup 286}Nh as α grand-daughter of {sup 294}Ts in six correlated decay chains, and {sup 286}Fl produced in three ways: independently in 11 correlated decay chains, as α daughter of {sup 290}Lv in 12 correlated decay chains, and as α grand-daughter of {sup 294}Og in four correlated decay chains. A=290: {sup 290}Mc and {sup 290}Lv are the only experimentally identified nuclides with A=290. A tentative evidence is provided for {sup 290}Nh and {sup 290}Fl from a chain originally observed and assigned to {sup 289}Fl by 1999Og10, but later reassigned by 2004Og10 to {sup 290}Fl, and further discussed in detail by 2016Ho09, where, based on systematics of α decays and SF half-lives, {sup 290}Fl is proposed to decay via ε mode to {sup 290}Nh, which then decays by an α chain, ending in {sup 278}Bh that decays by SF mode. 2017Ka66 in experiments at RIKEN using GARIS separator interpret one correlated decay chain in three different ways, one involving possible production of {sup 294}Lv in {sup 248}Cm({sup 48}Ca,2n),E=261.6 MeV, and α decay to {sup 290}Fl. Experiments carried out at FLNR-Dubna, in collaboration with LLNL and ORNL labs in the USA, and at GSI-SHIP facility confirm the identification of these isotopes, {sup 290}Mc as α daughter of {sup 294}Ts in six correlated decay chains, and {sup 290}Lv produced in two ways, independently in 14 correlated decay chains, and as α daughter of {sup 294}Og in four correlated decay chains. A=294: {sup 294}Ts and {sup 294}Og are the only experimentally identified nuclides with A=294. Experiments carried out at FLNR-Dubna, in collaboration with LLNL and ORNL labs in the USA, and at GSI-SHIP facility confirm the identification of these isotopes, with a total of six EVR-α-SF correlated decay chains observed for {sup 294}Ts and four for {sup 294}Og. Tentative identification of {sup 294}Lv is provided by 2017Ka66 from the observation one correlated event using GARIS-RIKEN facility, where this event is interpreted in three possible ways, two interpretations lead to production of {sup 293}Lv and successive odd-A nuclides of {sup 289}Fl, {sup 285}Cn and {sup 281}Ds, whereas the third prediction starts with the production of {sup 294}Lv and successive {sup 290}Fl and {sup 286}Cn nuclides. Search for {sup 294}Rg in natural gold materials (2011De03), and for {sup 294}Ds, {sup 294}Fl and {sup 294}Mc in natural Pt, Pb and Bi samples (2011De21) using accelerator mass spectroscopy (AMS) proved negative, with extremely low upper limits established. Also 1980St05 did not see any evidence for {sup 294}Ds in natural Pt sample using AMS. A=298: Search for {sup 298}120 through fusion-evaporation reaction at Dubna, and for {sup 298}Fl and {sup 298}Mc in natural Pt, Pb and Bi samples using accelerator mass spectroscopy (AMS) proved negative. Tentative assignment of three α-α-α decay chains by 2016Ho09 to {sup 299}120 in {sup 248}Cm({sup 54}Cr,3n){sup 299}120 at GSI was refuted by 2017He11, assigning these correlations to random events, instead. A=302: Fluorescent x rays from Z=120 element were observed by 2012Fr03 from compound nucleus {sup 302}120 produced in {sup 238}U({sup 64}Ni,X),E=6.6 MeV/nucleon at GANIL, and x-ray yields were measured, together with minimum average time deduced from x-ray multiplicity. The compound nucleus could decay by 3n- or 4n-channels to produce {sup 299}120 or {sup 298}120. 2012He05 and 2016Ho09 also produced {sup 302}120 compound nucleus in {sup 248}Cm({sup 54}Cr, xn){sup 302}120{sup *},E=6.035 MeV/nucleon; and {sup 238}U({sup 64}Ni,xn){sup 302}120{sup *},E=5.53 MeV/nucleon reactions using UNILAC at GSI. Three α-α-α correlated decays from {sup 248}Cm({sup 54}Cr,xn){sup 302}120{sup *} reaction were tentatively assigned by 2016Ho09 to {sup 299}120 decay, however, a detailed analysis by 2017He11 refuted this claim, ascribing these events to random sequences. There are no data tables for A=302.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DeepONet-grid-UQ: A trustworthy deep operator framework for predicting the power grid’s post-fault trajectories

This paper proposes a novel data-driven method for the reliable prediction of the power grid’s post-fault trajectories, i.e., the power grid’s dynamic response after a disturbance or fault. Here, the proposed method is based on the recently proposed concept of Deep Operator Networks (DeepONets). Unlike traditional neural networks that learn to approximate functions, DeepONets are designed to approximate nonlinear operators, i.e., mappings between infinite-dimensional spaces. Under this operator framework, we design a novel and efficient DeepONet that (i) takes as inputs the trajectories collected before and during the fault and (ii) outputs the predicted post-fault trajectories. In addition, we endow our method with the much-needed ability to balance efficiency with reliable/trustworthy predictions via uncertainty quantification. To this end, we propose and compare two novel methods that enable quantifying the predictive uncertainty. First, we propose a Bayesian DeepONet (B-DeepONet) that uses stochastic gradient Hamiltonian Monte-Carlo to sample from the posterior distribution of the DeepONet trainable parameters. Then, we design a Probabilistic DeepONet (Prob-DeepONet) that uses a probabilistic training strategy to enable quantifying uncertainty at virtually no extra computational cost. Finally, we validate the proposed methods’ predictive power and uncertainty quantification capability using the New York-New England power grid model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. Additionally, an error compensation mechanism is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The result show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92% - 95% from one hour to one week ahead forecasting.

14 SOLAR ENERGY↗

A Real-Time Vehicle-Specific Eco-Routing Model for On-Board Navigation Applications Capturing Transient Vehicle Behavior

The paper develops a real-time vehicle-specific eco-routing model for use in on-board navigation systems for both conventional fuel- and battery-powered electric vehicles. The model uses a novel link cost function that retains all microscopic transient behavior along a link by capturing within-link speed, acceleration, and road grade variations. Specifically, eight vehicle-agnostic link-specific variables are transmitted to the cloud and fused with information received from other connected vehicles. The fused data are then sent back to the connected vehicles and used to compute vehicle-specific eco-routes (edge computing). The solution produces an energy-efficient dynamic user-equilibrium traffic assignment that is solved incrementally. A numerical experiment is first designed to test the model, demonstrating the benefits associated with vehicle-specific eco-routes compared to those produced by traditional models. The model is then implemented in a micro-simulation framework to evaluate the network-wide impacts of the proposed energy-efficient user-optimum incremental traffic assignment for different traffic demand levels. Results demonstrate that the proposed model produces lower network-wide energy consumption levels compared to traditional energy-efficient and travel time user-optimum traffic assignment methods for both conventional fuel and electric vehicles. Conventional fuel savings relative to travel time routing decrease with increasing traffic demand levels, while electric power savings do not vary monotonically with congestion levels. Energy savings relative to traditional eco-routing are also demonstrated to not vary monotonically with demand levels. Results of the study also demonstrate that the transportation network layout significantly affects the eco-routing system performance. Finally, the feasibility of the proposed model in real-world applications is discussed and presented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Acoustic emission Bayesian source location: Onset time challenge

Robust identification of the most accurate observed input data among a pool of observations is key in modeling and decision making. A statistically biased observed measurement deteriorates the predictive power of a model and affects decision-making ability based on the prediction of the model. When two competing methods of measurement are available, such as methods which identify arrival times in acoustic emission (AE) signals, a principal question is whether one of the two obtained datasets, or a combination of the two, should be used later on, for example, to localize an AE source. This question becomes more important when collecting not repeatable data such as AE signals created by a propagating crack. Here this paper considers an inverse source location problem in a concrete block to address the mentioned issue, a proposed methodology which also has wider application in competitive data selection. Elastic energy released by an AE event, such as a propagating crack, is recorded by acoustic emission data acquisition system. The onset time of AE signals is often used to locate the source of the event, and its accuracy directly affects the precision of source identification. This research proposes an innovative approach to select the most probable onset time obtained from two automatic picker methods. The proposed method selects the most probable onset times, which are observed by each picker for each sensor, in a probabilistic fashion. To validate the proposed method, the most accurate onset time observed by each picker is identified by visual inspection and is compared with the one is selected by the proposed method. Finally, the dataset is used for source location identification. Results show that picked onset times determined by the proposed method generate more accurate source identification when compared with coordinates obtained using each dataset individually.

97 MATHEMATICS AND COMPUTING↗