Fast Code Research Articles

Lattice Boltzmann Simulation of Nonequilibrium Flows Using Spectral Multiple-Relaxation-Time Collision Model

Prediction of nonequilibrium flows is critical to space flight. The present work demonstrates that the recently developed spectral multiple-relaxation-time (SMRT) lattice Boltzmann (LB) model is theoretically equivalent to Grad’s eigensystem [“Principles of the Kinetic Theory of Gases,” Thermodynamik der Gase/Thermodynamics of Gases, Springer–Verlag, Berlin, 1958, pp. 205–294], where the eigenfunctions obtained by tensor decomposition of the Hermite polynomials are also those of the linearized Boltzmann equation. Numerical results of shock structure simulation using the Maxwell molecular model agree very well with those of a high-resolution fast spectral method code up to Mach 7, provided that the relaxation times of the irreducible tensor components match their theoretical values. If a reduced set of relaxation times is used, such as in the Shakhov model and lumped-sum relaxation of Hermite modes, non-negligible discrepancies start to occur as the Mach number is raised, indicating the necessity of the fine-grained relaxation model. Together with the proven advantages of LB, the LB-SMRT scheme offers a competitive alternative for nonequilibrium flow simulation.

Development of multi-physics calculation method in lead cooled fast reactor code system MOSASAUR

A full-core three-dimensional multi-physics calculation method was researched based on the Lead cooled fast reactor (LFR) code system MOSASAUR, which is focused on both core steady-state and transient analyses of LFR. In the previous version of MOSASAUR, cross-sections generation module and core steady-state simulation module have been developed. In this research, the stiffness confinement method is employed to solve the time-dependent multi-group neutron transport equation to expand the capabilities of core transient analyses. And the thermal hydraulic calculation method is developed as thermal feedback module for core steady-state and transient analyses. Based on the fixed-point iteration scheme, the neutron module and thermal hydraulic module are coupled at each time step. The LMW benchmark and the problem based on ORAL 19-rod bundle are employed to verify the accuracy of transient calculation and thermal hydraulic module respectively. Finally, the multi-physics calculation method is utilized to simulate the transient process of the MicroURANUS core. The simulation results demonstrate the capability of the constructed multi-physics calculation framework to accurately simulate the transient behaviors of LMRs. Numerical results showed the good accuracy of the newly-developed multi-physics calculation module with MOSASAUR.

Learning-based CU partition prediction for fast panoramic video intra coding

In recent years, Virtual Reality (VR) technology has been applied in various aspects of life. As an indispensable component of VR, panoramic video offers viewers immersive experiences, thereby attracting widespread attention. The high resolution of panoramic video poses significant challenges for its storage and transmission, requiring efficient video compression. The Versatile Video Coding (VVC) exhibits superior coding efficiency, albeit at the expense of a several dozen-fold increase in encoding complexity. In this paper, we propose a fast Coding Unit (CU) partition algorithm for intra-coding based on Support Vector Machine (SVM), which selects appropriate features for online training of multiple classifiers based on frame texture characteristics. Additionally, in response to distortion issues in panoramic video coding, we divide video frames into different regions and adjust the Quantization Parameter (QP) values of CUs within each region to improve the encoding efficiency. Experimental results show that the proposed method achieves an average encoding time reduction of 46.21%, with an average BDBR increase of only 1.01%, achieving a good trade-off between time-saving and encoding efficiency.

(Invited) Model-Based BMS for Current and Next-Generation Batteries

Fast charging is researched heavily for the widespread implementation of lithium-ion batteries for electric vehicles. However, charging at high currents accelerates several parasitic reactions that lead to the degradation of the cell, affecting its lifetime. These reactions lead to loss of lithium inventory, loss of active material, and increased impedance in the cell. Examples of these side reactions include the growth of the solid-electrolyte interphase (SEI) layer, transition metal dissolution and deposition, lithium plating, solvent oxidation, etc. These mechanisms degrade the cell and reduce its cycle life.Physics-based multi-scale battery models solve for equations that govern the charge and mass balances within the cell. Using these detailed mathematical models, it is possible to study material degradation mechanisms and predict their impact on capacity loss under several operating conditions. These models can be used to design new batteries with appropriate materials and design parameters suited for any given purpose.More critically, these models can be integrated with battery management systems (BMS) to control the cell’s performance. These models can further be used to design novel charging protocols that enable safe and optimal cell performance and suppress cell material degradation. The BMS monitors and maintains the voltage, current, and temperature and estimates the internal states of the cell. Model-based BMS algorithms require fast codes that can predict and estimate battery parameters in real-time and control the battery’s performance under different loads.Currently, the BMS implements equivalent circuit models that inadequately predict the cell’s performance for various conditions and design parameters. This talk presents the current efforts to move the models for BMS for current and next-generation batteries for single-cell to pack-level simulations. Figure 1

Ti‐Doped ZnO Thin Films‐Based Transparent Photovoltaic for High‐Performance Broadband and Wide‐Field‐of‐View Photocommunication Window

Transparent photovoltaics (TPVs) are crucial for developing next‐generation see‐through electronics. However, TPV devices (TPVDs) require wide‐bandgap materials that are typically only responsive to short wavelength (ultraviolet, UV) lights rather than visible lights. Is it possible to improve the TPV performance by harvesting the longer wavelength lights without degradation of transparency? It may be satisfied with the function of intermediate energy states, which can utilize the lower photon energy (longer wavelength light) by a two‐step transition. To achieve this, co‐sputtered Ti‐doped ZnO (Ti:ZnO) film‐based high‐performance TPVDs have been developed. Density functional theory analysis revealed the formation of intermediate energy states due to the hybridization of O 2p and Ti 3d orbitals in the Ti:ZnO system. The Ti:ZnO‐based TPVDs show 65% average visible transparency with a power production value of 655 μW cm−2. These devices exhibit good photodetection behavior under UV to visible illuminations with high responsivity and detectivity values of 1.85 A W−1 and 2.5 × 1013 Jones, respectively. Finally, a high‐performance UV to visible broadband and wide‐field‐of‐view photocommunication system is designed based on the TPVDs to generate the fast Morse code signal. Therefore, Ti doping in ZnO provides a good way to improve the device's functionality for futuristic applications.

Research and development of the neutron-photon coupled transport method in the fast reactor code system MOSASAUR

In the high-fidelity reactor physics design of fast reactors, the influence of photon effect needs to be explicitly simulated with the neutron-photon coupled transport method. The neutron-photon coupled transport-burnup method was researched based on the fast reactor physics design software package MOSASAUR. Photon library, photon cross-section production, photon source and photon power calculation methods were researched and the related calculation modules were developed and verified with the RBEC-M benchmark and the MET-1000 benchmark. Numerical results showed the good accuracy of the newly-developed neutron-photon coupled transport ability with MOSASAUR. The photon effect introduced the 80% difference for the assembly power in the RBEC-M benchmark, which showed the importance of the neutron-photon coupled transport in the fast reactor design.

RDBD-based Fast Depth Inter Coding for 3D-HEVC

RDBD-based Fast Depth Inter Coding for 3D-HEVC

Toward the Next Generation of Density Functionals: Escaping the Zero-Sum Game by Using the Exact-Exchange Energy Density.

ConspectusKohn-Sham density functional theory (KS DFT) is arguably the most widely applied electronic-structure method with tens of thousands of publications each year in a wide variety of fields. Its importance and usefulness can thus hardly be overstated. The central quantity that determines the accuracy of KS DFT calculations is the exchange-correlation functional. Its exact form is unknown, or better "unknowable", and therefore the derivation of ever more accurate yet efficiently applicable approximate functionals is the "holy grail" in the field. In this context, the simultaneous minimization of so-called delocalization errors and static correlation errors is the greatest challenge that needs to be overcome as we move toward more accurate yet computationally efficient methods. In many cases, an improvement on one of these two aspects (also often termed fractional-charge and fractional-spin errors, respectively) generates a deterioration in the other one. Here we report on recent notable progress in escaping this so-called "zero-sum-game" by constructing new functionals based on the exact-exchange energy density. In particular, local hybrid and range-separated local hybrid functionals are discussed that incorporate additional terms that deal with static correlation as well as with delocalization errors. Taking hints from other coordinate-space models of nondynamical and strong electron correlations (the B13 and KP16/B13 models), position-dependent functions that cover these aspects in real space have been devised and incorporated into the local-mixing functions determining the position-dependence of exact-exchange admixture of local hybrids as well as into the treatment of range separation in range-separated local hybrids. While initial functionals followed closely the B13 and KP16/B13 frameworks, meanwhile simpler real-space functions based on ratios of semilocal and exact-exchange energy densities have been found, providing a basis for relatively simple and numerically convenient functionals. Notably, the correction terms can either increase or decrease exact-exchange admixture locally in real space (and in interelectronic-distance space), leading even to regions with negative admixture in cases of particularly strong static correlations. Efficient implementations into a fast computer code (Turbomole) using seminumerical integration techniques make such local hybrid and range-separated local hybrid functionals promising new tools for complicated composite systems in many research areas, where simultaneously small delocalization errors and static correlation errors are crucial. First real-world application examples of the new functionals are provided, including stretched bonds, symmetry-breaking and hyperfine coupling in open-shell transition-metal complexes, as well as a reduction of static correlation errors in the computation of nuclear shieldings and magnetizabilities. The newest versions of range-separated local hybrids (e.g., ωLH23tdE) retain the excellent frontier-orbital energies and correct asymptotic exchange-correlation potential of the underlying ωLH22t functional while improving substantially on strong-correlation cases. The form of these functionals can be further linked to the performance of the recent impactful deep-neural-network "black-box" functional DM21, which itself may be viewed as a range-separated local hybrid.

Easily porting material point methods codes to GPU

AbstractThe material point method (MPM) is computationally costly and highly parallelisable. With the plateauing of Moore’s law and recent advances in parallel computing, scientists without formal programming training might face challenges in developing fast scientific codes for their research. Parallel programming is intrinsically different to serial programming and may seem daunting to certain scientists, in particular for GPUs. However, recent developments in GPU application programming interfaces (APIs) have made it easier than ever to port codes to GPU. This paper explains how we ported our modular C++ MPM code to GPU without using low-level hardware APIs like CUDA or OpenCL. We aimed to develop a code that has abstracted parallelism and is therefore hardware agnostic. We first present an investigation of a variety of GPU APIs, comparing ease of use, hardware support and performance in an MPM context. Then, the porting process of to the Kokkos ecosystem is detailed, discussing key design patterns and challenges. Finally, our parallel C++ code running on GPU is shown to be up to 85 times faster than on CPU. Since Kokkos also supports Python and Fortran, the principles presented therein can also be applied to codes written in these languages.

MONKES: a fast neoclassical code for the evaluation of monoenergetic transport coefficients in stellarator plasmas

MONKES is a new neoclassical code for the evaluation of monoenergetic transport coefficients in stellarators. By means of a convergence study and benchmarks with other codes, it is shown that MONKES is accurate and efficient. The combination of spectral discretization in spatial and velocity coordinates with block sparsity allows MONKES to compute monoenergetic coefficients at low collisionality, in a single core, in approximately one minute. MONKES is sufficiently fast to be integrated into stellarator optimization codes for direct optimization of the bootstrap current and to be included in predictive transport suites. The code and data from this paper are available at https://github.com/JavierEscoto/MONKES/.

Fast Coding Unit Partitioning Algorithm for Video Coding Standard Based on Block Segmentation and Block Connection Structure and CNN

The recently introduced Video Coding Standard, VVC, presents a novel Quadtree plus Nested Multi-Type Tree (QTMTT) block structure. This structure enables a more flexible block partition and demonstrates enhanced compression performance compared to its predecessor, HEVC. However, The introduction of the new structure has led to a more complex partition search process, resulting in a considerable increase in time complexity. The QTMTT structure yields diverse Coding Unit (CU) block sizes, posing challenges for CNN model inference. In this study, we propose a representation structure termed Block Segmentation and Block Connection (BSC), rooted in texture features. This ensures that partial CU blocks are uniformly represented in size. To address different-sized CUs, various levels of CNN models are designed for prediction. Moreover, we introduce a post-processing method and a multi-thresholding scheme to further mitigate errors introduced by CNNs. This allows for flexible and adjustable acceleration, achieving a trade-off between coding time complexity and performance. Experimental results indicate that, in comparison to VTM-10.0, our “Fast” scheme reduces the average complexity by 57.14% with a 1.86% increase in BDBR. Meanwhile, the “Moderate” scheme reduces average complexity by 50.14% with only a 1.39% increase in BDBR.

Coupling hydrological and sanitation datasets to simulate wastewater-derived contamination in European rivers: Model development and calibration

Wastewater treatment plant (WWTP) discharges of microcontaminants negatively impact freshwater streams, underscoring the need for accurately mapping wastewater-derived contamination in water bodies across Europe (EU). In this study, we present a fast and open-source code for a microcontaminants fate and transport (MFT) model, capable of simulating contamination at a high resolution (15 arc second scale) across the EU. The model was developed using the best publicly available hydrological (HydroSHEDS) and sanitation (UWWTD) datasets and was rigorously calibrated, with a goodness of fit of 77.5% as measured by the R2. Importantly, the model demonstrated the ability to predict wastewater-derived contamination in water bodies, making it a valuable tool for planning the upgrade of WWTPs and improving the ecological condition of freshwater streams in the EU.

Fast forward modelling of galaxy spatial and statistical distributions

A forward modelling approach provides simple, fast and realistic simulations of galaxy surveys, without a complex underlying model. For this purpose, galaxy clustering needs to be simulated accurately, both for the usage of clustering as its own probe and to control systematics. We present a forward model to simulate galaxy surveys, where we extend the Ultra-Fast Image Generator to include galaxy clustering. We use the distribution functions of the galaxy properties, derived from a forward model adjusted to observations. This population model jointly describes the luminosity functions, sizes, ellipticities, SEDs and apparent magnitudes. To simulate the positions of galaxies, we then use a two-parameter relation between galaxies and halos with Subhalo Abundance Matching (SHAM). We simulate the halos and subhalos using the fast PINOCCHIO code, and a method to extract the surviving subhalos from the merger history. Our simulations contain a red and a blue galaxy population, for which we build a SHAM model based on star formation quenching. For central galaxies, mass quenching is controlled with the parameter Mlimit, with blue galaxies residing in smaller halos. For satellite galaxies, environmental quenching is implemented with the parameter tquench, where blue galaxies occupy only recently merged subhalos. We build and test our model by comparing to imaging data from the Dark Energy Survey Year 1. To ensure completeness in our simulations, we consider the brightest galaxies with i < 20. We find statistical agreement between our simulations and the data for two-point correlation functions on medium to large scales. Our model provides constraints on the two SHAM parameters Mlimit and tquench and offers great prospects for the quick generation of galaxy mock catalogues, optimized to agree with observations.

RISMiCal: A software package to perform fast RISM/3D-RISM calculations.

Solvent plays an essential role in a variety of chemical, physical, and biological processes that occur in the solution phase. The reference interaction site model (RISM) and its three-dimensional extension (3D-RISM) serve as powerful computational tools for modeling solvation effects in chemical reactions, biological functions, and structure formations. We present the RISM integrated calculator (RISMiCal) program package, which is based on RISM and 3D-RISM theories with fast GPU code. RISMiCal has been developed as an integrated RISM/3D-RISM program that has interfaces with external programs such as Gaussian16, GAMESS, and Tinker. Fast 3D-RISM programs for single- and multi-GPU codes written in CUDA would enhance the availability of these hybrid methods because they require the performance of many computationally expensive 3D-RISM calculations. We expect that our package can be widely applied for chemical and biological processes in solvent. The RISMiCal package is available at https://rismical-dev.github.io.

A novel V-cut method for explosive-free breakage of biaxially loaded rock using soundless chemical demolition agents

Interest in soundless chemical demolition agents (SCDAs), also known as expansive cements, as potentially viable alternatives to explosives for rock fragmentation, has been growing in recent years. Consequently, there is an increasing amount of literature on the use of SCDA for the breakage of rock blocks and boulders. Limited research has been conducted so far on the breakage of excavation fronts, such as tunnel or drift faces, using SCDA. This is due to the perception that the planar compressive in-situ stresses in the face would inhibit the creation and propagation of fracturing due to expansive pressure. This study proposes a novel V-cut method for demolishing rock panels under biaxial stress using SCDA. This method was examined through large-scale tests and numerical modelling. The rock panels were subjected to high biaxial confinements of 26 and 40 MPa. Such a level of confinement corresponds to an in-situ stress state 1000 m below the surface in the Canadian shield. The V-cut drillhole pattern employs two sets of three SCDA holes angled at 45° from the face of a Stanstead granite panel. The drillhole arrangement aims to create a V-shaped wedge in the plane of major principal stress. When angled drillholes are subjected to expansive pressure, they tend to cast out of the panel face, causing fragmentation. Two panels of 1 m × 1 m × 0.25 m were successfully demolished using the proposed method. The three-dimensional fast Lagrangian analysis code FLAC3D modelling was used to reconstruct the panel failure mechanism owing to the V-cut. This study demonstrates the feasibility of fragmenting an excavation front, such as a rock excavation face, with SCDA using a V-cut drill hole pattern while subjected to high biaxial confinement.

Multi-hazard stochastic response analysis and reliability evaluation of a 5 MW monopile offshore wind turbine based on extended platform FAST-S

This study investigates the random dynamic response of a 5 MW monopile offshore wind turbine (MOWT) subjected to wind, wave and earthquake loads. Based on the aero-hydro-servo-elastic code FAST, a multi-field coupled simulation module considering earthquake, FAST-S, is developed for the fully coupled multi-hazard analysis of OWTs. Compared to the original FAST code, a seismic analysis module (SeismoDyn) and a soil-structure interaction (SSI) module (SoilDyn) have been supplemented in FAST-S. SeismoDyn is developed by modifying the Kane’s kinetic equation in the FAST, and the SoilDyn is developed through Winkler foundation model in order to consider the nonlinear SSI. Moreover, FAST-S has been validated by other recognized codes. Based on FAST-S, a fully coupled numerical analysis model of the NREL 5 MW MOWT is established, the random responses and reliability evaluation of the offshore wind turbine under wind, wave and earthquake loads are analyzed by probability density evolution method. The results show that the aerodynamic and hydrodynamic actions increase the damping of the wind turbine system, which has a certain effect on inhibiting the tower’s vibration caused by the earthquake. Therefore, compared with the coupled wind-wave-earthquake case, the sole earthquake case may be more unfavorable, and should be paid more attention to in high risk earthquake regions. The results show that the probability density functions of offshore wind turbine response under strong earthquakes obviously deviates from the typical regular distribution models. Based on the theory of equivalent extreme value event, the dynamic reliability of the offshore wind turbine is calculated. Seismic actions maybe the major factor in the design of the support structure. Nevertheless, owing to the aerodynamic and hydrodynamic damping effects of wind and wave loadings, the structural responses under wind-wave-earthquake are more moderate than ones subjected to solely earthquake. The strong seismic loads would cause significant complex variations of time-dependent probability density function of the OWT response.

A multiresolution method for modelling galaxy and massive black hole mergers

ABSTRACT The coalescence of the most massive black hole (MBH) binaries releases gravitational waves (GWs) within the detectable frequency range of pulsar timing arrays (PTAs; 10−9 to 10−6 Hz). The incoherent superposition of GWs from MBH mergers, the stochastic gravitational wave background (GWB), can provide unique information on MBH parameters and the large-scale structure of the Universe. The recent evidence for a GWB reported by the PTAs opens an exciting new window on to MBHs and their host galaxies. However, the astrophysical interpretation of the GWB requires accurate estimations of MBH merger time-scales for a statistically representative sample of galaxy mergers. This is numerically challenging; a high numerical resolution is required to avoid spurious relaxation and stochastic effects, while a large number of simulations are needed to sample a cosmologically representative volume. Here, we present a new multimass modelling method to increase the central resolution of a galaxy model at a fixed particle number. We follow mergers of galaxies hosting central MBHs with the fast multiple method code griffin at two reference resolutions and with two refinement schemes. We show that both refinement schemes are effective at increasing central resolution, reducing spurious relaxation and stochastic effects. A particle number of N ≥ 106 within a radius of five times the sphere of influence of the MBHs is required to reduce numerical scatter in the binary eccentricity and the coalescence time-scale to &amp;lt;30 per cent, a resolution that can only be reached at present with the mass refinement scheme.

Model and analysis of the data readout architecture for the ITS3 ALICE Inner Tracker System

The ALICE collaboration is developing the Inner Tracker System 3 (ITS3), a novel detector that exploits the stitching technique to construct single-die monolithic pixel sensors of up-to 266 mm × 93 mm. ITS3 requires all hits from a particle flux of 5.75 MHz/cm2 to be transmitted on-chip to one of the sensor edges. This on-chip readout must balance the resources of power consumption, dead area, and readout performance by tuning different design parameters such as on-chip memories or on-chip links bandwidth. For doing so, a model of the ITS3 on-chip readout architecture will be presented. This model combines an accurate simulation of the particle flux fluctuations expected in ALICE with a clock-accurate digital readout simulator, combining high accuracy with fast code in terms of simulation speed.

Code development and preliminary validation for lead-cooled fast reactor thermal-hydraulic transient behavior

Lead-cooled fast reactors (LFRs) have a wide range of application scenarios, which require the thermal-hydraulic characteristics of LFRs to be reliable. In the present paper, the Lead-cooled fast reactor Thermal-Hydraulic Analysis Code LETHAC was developed, including the models of pipe, heat exchanger, and pool. To verify the correctness of LETHAC, two experimental facilities and three experimental cases were selected, including GFT and PLOFA tests for NACIE-UP and Test-1 for CIRCE. The calculated results show the same and consistent trend with the experimental data, but there are some discrepancies. It can be found that LETHAC is suitable and reliable in predicting the transient behavior of lead-cooled system.

Smart Contract Generation through NLP and Blockchain for Legal Documents

The rise in legislation and the need for task automation systems has resulted in an amplified requirement for software development. This is aimed at improving the accuracy and efficiency of reading and interpreting laws in legal activities, allowing for enhanced precision and swiftness. Currently, there is a need for analysts to interpret written legislation and then encode it into computer programs, which often leads to errors. As cryptocurrencies gain popularity, there is growing interest in utilizing Blockchain technology in the legal field. Specifically, smart contracts can be used to integrate business rules into laws and automate blockchain management. However, the process of writing fast and high-quality code can be improved by leveraging artificial intelligence based techniques such as natural language processing (NLP) to help practitioners. Despite reviewing the current state-of-the-art, there is a lack of existing work that combines smart contracts and NLP in the context of legislation analysis. This study work generates intelligent code from legislation analysis, utilizing NLP and Blockchain for this purpose. In this research work a pilot prototype for smart contract generation is developed and initial code samples are presented. This work demonstrates a promising results with 96% accuracy in Name Entity Recognition (NER) and also highlights the importance of smart contract generation through NLP.