High Flexibility Hybrid Architecture Real-Time Simulation Platform Based on Field-Programmable Gate Array (FPGA)

With the expansion of system scale and the reduction in simulation step size, the design of a power system real-time simulation platform faces many difficulties. The interactive operation of real-time simulation presents the characteristics of phased and centralized. This paper proposes selecting the appropriate simulation method for each sub-network according to the system operation requirements, and the sub-network simulation method can be changed with the change in system operation requirements in the simulation process. In order to change the sub-network simulation method in the simulation process, a high flexibility hybrid architecture real-time simulation platform based on FPGA was designed. The main body of the architecture runs in the high control mode of instruction flow and uses instruction flexibility to realize the requirement of changing methods. The algorithm modularity architecture is used as an auxiliary architecture to reduce the instruction cost and increase the computing power. Finally, the hybrid architecture real-time simulation platform was implemented in the Xilinx VC709 board (Xilinx corporation, San Jose, CA, USA), and the verification results show that under the same system scale, the hybrid architecture simulation platform combined with simulation method changing realizes shorter simulation step and complex interactive operation.

DESIGN AND SIMULATION OF A SPECIAL MEDIUM POWER INDUCTION HEATING SYSTEM FOR OXYGEN FREE COPPER PRODUCTION

For sustainability purposes this project is studying the recycling of copper scrap. It is intended to melt a copper in oxygen free environment to achieve a highly conducting copper suitable for electrical installation and bus-bars manufacturing. Such a project must be started by a design and simulation step. Since the furnace composed of two main parts, the power supply and the induction coil, the power supply is a current fed inverter (CFI) simulated using Matlab, and the induction coil simulated by Finite Element Method (FEM) using ANSYS computer package. The induction coil design of this project is a special task due to the limitation of the maximum output voltage of the available power supply. The results approve the visibility of the system to be implemented in near future.

Protein–Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

Most of the protein–protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein–protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein–protein complexes, we obtained acceptable quality models for a significant number of cases.

Low-rank density-matrix evolution for noisy quantum circuits

In this work, we present an efficient rank-compression approach for the classical simulation of Kraus decoherence channels in noisy quantum circuits. The approximation is achieved through iterative compression of the density matrix based on its leading eigenbasis during each simulation step without the need to store, manipulate, or diagonalize the full matrix. We implement this algorithm using an in-house simulator and show that the low-rank algorithm speeds up simulations by more than two orders of magnitude over existing implementations of full-rank simulators, and with negligible error in the noise effect and final observables. Finally, we demonstrate the utility of the low-rank method as applied to representative problems of interest by using the algorithm to speed up noisy simulations of Grover’s search algorithm and quantum chemistry solvers.

SIMULATION OF PARTICLE SWARM OPTIMIZATION FOR INVESTMENTS ON STOCK MARKET

This work reports simulations performed using Particle Swarm Optimization (PSO) as applied to investments on the stock market. About 480 stocks belonging to the S&P500 index have been taken into account. A naive approach has been developed in which one simulation step corresponded to one trading period. As a second ingredient of the investment strategy, the relative strength of an asset has been employed. The results are analyzed with respect to the parameters of PSO.

A stepwise surrogate model for parameter calibration of the Variable Infiltration Capacity model: the case of the upper Brahmaputra, Tibet Plateau

To alleviate the computational burden of parameter calibration of the Variable Infiltration Capacity (VIC) model, a stepwise surrogate model (SM) is developed based on AdaBoost. An SM first picks out the parameter sets in the range that the values of objective functions are close to the optimization objectives and then approximates the values of objective functions with these parameter sets. The ɛ-NSGA II (Nondominated Sorting Genetic Algorithm II) algorithm is used to search the optimal solutions of SM. The SM is tested with a case study in the upper Brahmaputra River basin, Tibet Plateau, China. The results show that the stepwise SM performed well with the rate of misclassification less than 2.56% in the global simulation step and the root mean square error less than 0.0056 in the local simulation step. With no large difference in the optimal solutions between VIC and the SM, the SM-based algorithm saves up to 90% time.

Primary sources, simulations and peanut butter and jelly

PurposeThis paper seeks to provide instructional methods for using simulations to teach primary and secondary sources within a social studies classroom. Classroom simulations provide students with authentic opportunities to engage in meaningful learning experiences that are both hands-on in nature and promote the use of critical thinking.Design/methodology/approachThis paper opted to describe an approach to teach students about primary and secondary sources through a classroom simulation. Step-by-step instruction was provided via an included table, so that readers can recreate the lesson in their own classrooms.FindingsThis paper offers insights about how simulations can be used to provide students an authentic experience with primary and secondary sources. These experiences include opportunities to critically think about the benefits and limitations that both primary and secondary sources offer students while engaging in historical inquiry.Practical implicationsThis paper is designed for teachers to utilize and replicate in their own social studies classrooms.Originality/valueThis paper recognizes the important role that primary and secondary sources have in the social studies classroom. Through an original approach, using simulations, the authors present a unique perspective on how to teach about primary and secondary sources in a manner that supports historical inquiry.

Changes on Totten glacier dependent on oceanic forcing based on ISMIP6

<p>Totten glacier is draining 68% of the Aurora basin, East Antarctica, - an equivalent to 3.5m global sea level rise. Further, Totten’s thickness and velocity have been fluctuating during the last decades showing periodic speed-ups and thinning.</p><p>We investigate the effect of different ocean forcing on Totten glacier using the state-of-the-art ice sheet model BISICLES and based on the high-resolution data sets BedMachine Antarctica and REMA (Morlighem et al., 2019; Howat et al., 2019). Our simulations (2015-2100) are following the ISMIP6 setup and are based on CMIP5 & CMIP6 AOGCM outputs under RCP8.5 and RCP2.6. The contribution to sea level at 2100 varies between plus and minus 6mm. For all scenarios, we see thinning at the sides of Totten glacier in the slower flowing areas, but only climate models with sub-shelf melt rates that are at least 8m/a above the reference melt rates (1995 – 2017) lead to thinning and acceleration across Totten's grounding line. In agreement with ISMIP6 results, non-local quadratic melt rates adjusted to present day conditions at Pine island glacier, West Antarctica, results in the highest sub-shelf melt rates for all AOGCMs (up to 80m/a locally).</p><p>The ISMIP6 ocean melt scheme is based on a feedback given the simulated ice draft change: the thermal forcing of the ocean model is taken from the ocean layer closest to the bottom of the ice shelf at the current simulation step. Simulations not including this feedback lead to higher mass loss than the standard ISMIP6 scenario including the feedback.</p>

Modeling the viscoelastic effects in P-waves with modified viscoacoustic wave propagation

Accurate full-waveform seismic modeling is a powerful tool for understanding wave propagation and building subsurface images. However, it can be computationally expensive for viscoelastic media. Viscoacoustic seismic modeling is much cheaper, but at the trade-off of using incomplete physics. We have developed a modified viscoacoustic wave simulation algorithm for modeling the viscoelastic effects of P-waves. The algorithm contains two viscoacoustic forward-modeling steps; the first is the same as the traditional viscoacoustic modeling, whereas the second propagation is generated using a residual error source, which is derived by comparing the viscoacoustic and viscoelastic wave equations in the form of stress-particle velocity formulations. The corrected P-wave particle velocities can be obtained by adding the wavefield from the second simulation step to the original (the first simulation step) viscoacoustic wavefield. Only P-waves are modeled. The overall cost is about twice that of viscoacoustic modeling, but it is significantly less than a viscoelastic propagation because there are fewer calculations, and we can use a coarser grid and larger time steps for the same accuracy. Numerical examples indicate that the P-wave waveforms, after correction, match those from viscoelastic wave modeling better than those from the original viscoacoustic simulation. Our method provides a cost-efficient alternative for approximating the viscoelastic effects in P-wave modeling.