Simulation Speed Research Articles

Fast event-driven simulations for soft spheres: from dynamics to Laves phase nucleation.

Conventional molecular dynamics (MD) simulations struggle when simulating particles with steeply varying interaction potentials due to the need to use a very short time step. Here, we demonstrate that an event-driven Monte Carlo (EDMC) approach was first introduced by Peters and de With [Phys. Rev. E 85, 026703 (2012)] and represents an excellent substitute for MD in the canonical ensemble. In addition to correctly reproducing the static thermodynamic properties of the system, the EDMC method closely mimics the dynamics of systems of particles interacting via the steeply repulsive Weeks-Chandler-Andersen (WCA) potential. In comparison to time-driven MD simulations, EDMC runs faster by over an order of magnitude at sufficiently low temperatures. Moreover, the lack of a finite time step in EDMC circumvents the need to trade accuracy against the simulation speed associated with the choice of time step in MD. We showcase the usefulness of this model to explore the phase behavior of the WCA model at extremely low temperatures and to demonstrate that spontaneous nucleation and growth of the Laves phases are possible at temperatures significantly lower than previously reported.

Optical Imaging Model Based on GPU-Accelerated Monte Carlo Simulation for Deep-Sea Luminescent Objects

Modeling and simulating the underwater optical imaging process can assist in optimizing the configuration of underwater optical imaging technology. Based on the Monte Carlo (MC) method, we propose an optical imaging model which is tailored for deep-sea luminescent objects. Employing GPU parallel acceleration expedites the speed of MC simulation and ray-tracing, achieving a three-order-of-magnitude speedup over a CPU-based program. A deep-sea single-lens imaging system is constructed in the model, composed of a luminescent object, water medium, double-convex lens, aperture diaphragm, and sensor. The image of the luminescent object passing through the imaging system is generated using the forward ray-tracing method. This model enables an intuitive analysis of the inherent optical properties of water and imaging device parameters, such as sensor size, lens focal length, field of view (FOV), and camera position on imaging outcomes in the deep-sea environment.

A lightweight data-driven spiking neuronal network model of Drosophila olfactory nervous system with dedicated hardware support.

Data-driven spiking neuronal network (SNN) models enable in-silico analysis of the nervous system at the cellular and synaptic level. Therefore, they are a key tool for elucidating the information processing principles of the brain. While extensive research has focused on developing data-driven SNN models for mammalian brains, their complexity poses challenges in achieving precision. Network topology often relies on statistical inference, and the functions of specific brain regions and supporting neuronal activities remain unclear. Additionally, these models demand huge computing facilities and their simulation speed is considerably slower than real-time. Here, we propose a lightweight data-driven SNN model that strikes a balance between simplicity and reproducibility. The model is built using a qualitative modeling approach that can reproduce key dynamics of neuronal activity. We target the Drosophila olfactory nervous system, extracting its network topology from connectome data. The model was successfully implemented on a small entry-level field-programmable gate array and simulated the activity of a network in real-time. In addition, the model reproduced olfactory associative learning, the primary function of the olfactory system, and characteristic spiking activities of different neuron types. In sum, this paper propose a method for building data-driven SNN models from biological data. Our approach reproduces the function and neuronal activities of the nervous system and is lightweight, acceleratable with dedicated hardware, making it scalable to large-scale networks. Therefore, our approach is expected to play an important role in elucidating the brain's information processing at the cellular and synaptic level through an analysis-by-construction approach. In addition, it may be applicable to edge artificial intelligence systems in the future.

Lattice Boltzmann simulation for wake interactions of aligned wind turbines using actuator line model with turbine control

A wind turbine wake causes a decrease in wind speed and an increase in turbulence intensity. The wind turbine wake interaction is essential for predicting the power output of a wind farm consisting of many wind turbines. This research proposes a CFD method able to reproduce wake interactions and power outputs of multiple wind turbines with high speed and accuracy. Large eddy simulations with the lattice Boltzmann method are used for fluid calculations, specifically for large-scale CFD simulations. The wind turbines are represented using an actuator line model. Optimal power generation efficiency is achieved by controlling the rotor speed and blade pitch angle. Large-scale simulations of eight aligned wind turbines are conducted using 1.75 billion grid points and 40 GPUs. We compare two cases with and without control to investigate the effect of turbine control on wake and power output. Both the instantaneous and mean streamwise velocities confirm that the turbine control reduces the wake velocity deficit of the downwind wind turbine. High-speed inflow of wind to the downstream turbines augments their power output. With implementation of turbine control, the power outputs of the downstream turbines agree well with the observation data obtained in an earlier study. The results demonstrate the importance of controlling the rotational speed and pitch angle for actuator line simulations.

Ray-Tracing modeling for urban photovoltaic energy planning and management

The traditional Radiative Transfer Modelling solutions for Solar Energy monitoring and forecasting often provide outputs for a single point location or an area location. However, for high resolution representation of areas these solutions suffer due to low simulation speeds. This approach makes it difficult for decision-makers to accurately estimate the solar potential of the administrative area and plan installations accordingly. In this direction, the study introduces three-dimensional Ray-Tracing based radiative modeling which is a high-speed area-based solution for solar energy monitoring. The three-dimensional ray-tracing was simulated by using advanced graphic creation platforms and cloud computing in conjunction with satellite data of the clouds, aerosols, building shadows effects and three-dimensional representations of the city using Cesium 3D tiles and Unreal Engine ®. The entire system was developed in a hybrid model to be exploited by urban planners for solar PV installations and by electricity distribution system operators for energy management and efficient incorporation of the produced energy into the regular and smart grids. This study implements and analyses this Ray-Tracing model for solar photovoltaic energy potential estimation at a rooftop level for the city of Athens, Greece. The total rooftop exploitable area in Athens was found to be close to 34 km2, which is able to massively host distributed PVs followed by almost 4.3 TWh of annually produced energy, whilst Penteli (a Municipality in Athens) possessed a potential of 96.8 GWh with an exploitable area of just 0.8 km2. This amount of energy, in a hypothetical full coverage scenario, is able to provide for 48.7% of Athens’s total energy requirement. Similar year-long simulations were conducted using the EU’s largest rooftop solar installation at Stavros Niarchos Foundation Cultural Center and randomly selected rooftops having solar installations in different municipalities in Athens. With these estimated solar potential values, the gross savings in natural gas consumption and hence the CO2 equivalent emissions can be computed. With the current estimated solar potential of Athens, the analyzed savings accounted of nearly 2.43 billion euros and 18 MT CO2 equivalent emissions. These computed annual savings are capable of covering installation costs for nearly 100,000 new solar installations. The end-product of this study is the development of a solar cadastre web tool which will support the decision-makers in the energy transition policies and the solar PV penetration into the urban environment and eventually drive the effort into renewable energy transition across the globe.

TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations.

Achieving a balance between computational speed, prediction accuracy, and universal applicability in molecular simulations has been a persistent challenge. This paper presents substantial advancements in TorchMD-Net software, a pivotal step forward in the shift from conventional force fields to neural network-based potentials. The evolution of TorchMD-Net into a more comprehensive and versatile framework is highlighted, incorporating cutting-edge architectures such as TensorNet. This transformation is achieved through a modular design approach, encouraging customized applications within the scientific community. The most notable enhancement is a significant improvement in computational efficiency, achieving a very remarkable acceleration in the computation of energy and forces for TensorNet models, with performance gains ranging from 2× to 10× over previous, nonoptimized, iterations. Other enhancements include highly optimized neighbor search algorithms that support periodic boundary conditions and smooth integration with existing molecular dynamics frameworks. Additionally, the updated version introduces the capability to integrate physical priors, further enriching its application spectrum and utility in research. The software is available at https://github.com/torchmd/torchmd-net.

One- and two-argument equation of state parametrizations with continuous sound speed for neutron star simulations

One- and two-argument equation of state parametrizations with continuous sound speed for neutron star simulations

Tropical cyclone low-level wind speed, shear, and veer: sensitivity to the boundary layer parametrization in the Weather Research and Forecasting model

Abstract. Mesoscale modeling can be used to analyze key parameters for wind turbine load assessment in a large variety of tropical cyclones. However, the modeled wind structure of tropical cyclones is known to be sensitive to the boundary layer scheme. We analyze modeled wind speed, shear, and wind veer across a wind turbine rotor plane in the eyewall and outer cyclone. We further assess the sensitivity of wind speed, shear, and veer to the boundary layer parametrization. Three model realizations of Typhoon Megi are analyzed over the open ocean using three frequently used boundary layer schemes in the Weather Research and Forecasting (WRF) model. All three typhoon simulations reasonably reproduce the cyclone track and structure. The boundary layer parametrization causes up to 15 % differences in median wind speed at hub height between the simulations. The simulated wind speed variability also depends on the boundary layer scheme. The modeled median wind shear is smaller than or equal to 0.11 used in the current IEC (International Electrotechnical Commission) standard regardless of the boundary layer scheme for the eyewall and outer cyclone region. However, up to 43.6 % of the simulated wind profiles in the eyewall region exceed 0.11. While the surface inflow angle is sensitive to the boundary layer scheme, wind veer in the lowest 400 m of the atmospheric boundary layer is less affected by the boundary layer scheme. Simulated median wind veer reaches values up to 1.7×10-2° m−1 (1.2×10-2° m−1) in the eyewall region (outer cyclone region) and is relatively small compared to moderate-wind-speed regimes. On average, simulated wind speed shear and wind veer are highest in the eyewall region. Yet strong spatial organization of wind shear and veer along the rainbands may increase wind turbine loads due to rapid changes in the wind profile at the turbine location.

The added value of simulated near-surface wind speed over the Alps from a km-scale multimodel ensemble

The advancement of computational resources has allowed researchers to run convection-permitting regional climate model (CPRCM) simulations. A pioneering effort promoting a multimodel ensemble of such simulations is the CORDEX Flagship Pilot Studies (FPS) on “Convective Phenomena over Europe and the Mediterranean” over an extended Alps region. In this study, the Distribution Added Value metric is used to determine the improvement of the representation of all available FPS hindcast simulations for the daily mean near-surface wind speed. The analysis is performed on normalized empirical probability distributions and considers station observation data as the reference. The use of a normalized metric allows for spatial comparison among the different regions (coast and inland), altitudes and seasons. This approach permits a direct assessment of the added value between the CPRCM simulations against their global driving reanalysis (ERA-Interim) and respective coarser resolution regional model counterparts. In general, the results show that CPRCMs add value to their global driving reanalysis or forcing regional model, due to better-resolved topography or through better representation of ocean-land contrasts. However, the nature and magnitude of the improvement in the wind speed representation vary depending on the model, the season, the altitude, or the region. Among seasons, the improvement is usually larger in summer than winter. CPRCMs generally display gains at low and medium-range altitudes. In addition, despite some shortcomings in comparison to ERA-Interim, which can be attributed to the assimilation of wind observations on the coast, the CPRCMs outperform the coarser regional climate models, both along the coast and inland.

Semi-empirical model for timber truck speed profile and fuel consumption

ABSTRACT This paper presents a semi-empirical model for driving speed simulation and estimation of energy use in timber trucks in Sweden. The model is composed of two parts; the first part takes as input road properties along a route and applies a kinematic model to simulate a driving pattern. The kinematic model contains parameters that are found statistically from large-scale recordings of CAN bus data from 21 timber trucks in 1 year. The second part applies a mechanistic model on the simulated speed profile to compute fuel use. The driving pattern simulator can predict the driving time and energy use with roughly the same variance as can be observed between different trucks and drivers following the same route. An average rolling resistance coefficient of 0.0068 was found from a coast-down study, but with substantial variation between vehicles.

Rapid calculation for avalanche maps by GPGPU-based snow avalanche model

The required time for producing snow avalanche maps is influenced by computation speed of simulations. Commonly, integrating terrain assessment with dynamic flow simulation aids in mapping dangerous areas for human and structural threats. This approach enables the evaluation of avalanche paths, as well as the assessment of flow rate and thickness during avalanche movement. However, the substantial computational cost of the simulation results in long calculation times when using the Central Processing Unit (CPU). In this study, a new rapid snow avalanche simulator was developed by applying massively parallel computation with the General-Purpose computing on Graphics Processing Unit (GPGPU) technique. By avoiding slower data transfer and utilizing faster memory, computational speed could be accelerated up to 80 times faster than conventional simulation using a CPU. Additionally, the rapid calculation models were validated based on the Mt. Nasu event in 2017, and pilot studies of the avalanche map of Mt. Nasu in Japan demonstrated the usefulness of the developed model for vulnerability evaluation. A total of 123 simulations were conducted for each susceptible source area, and all simulations were completed within only 6.5 h. This high-performance calculation can significantly reduce the time cost of producing and expanding conventional avalanche maps.

Uniform gradient magnetic field and spatial localization method based on Maxwell coils for virtual surgery simulation

AbstractWith the development of virtual reality technology, simulation surgery has become a low‐risk surgical training method and high‐precision positioning of surgical instruments is required in virtual simulation surgery. In this paper we design and validate a novel electromagnetic positioning method based on a uniform gradient magnetic field. We employ Maxwell coils to generate the uniform gradient magnetic field and propose two positioning algorithms based on magnetic field, namely the linear equation positioning algorithm and the magnetic field fingerprint positioning algorithm. After validating the feasibility of proposed positioning system through simulation, we construct a prototype system and conduct practical experiments. The experimental results demonstrate that the positioning system exhibits excellent accuracy and speed in both simulation and real‐world applications. The positioning accuracy remains consistent and high, showing no significant variation with changes in the positions of surgical instruments.

Influence of the tip speed ratio on the wake dynamics and recovery of axial-flow turbines

Detached eddy simulation is employed to investigate the wake development downstream of the rotor of an axial-flow turbine and its dependence on the tip speed ratio. In this study, we found that the trend of the momentum deficit as a function of the rotational speed shows opposite directions in the near wake and further downstream. While the momentum deficit in the near wake increases with the rotational speed, it decreases further downstream. For instance, we found that at six diameters downstream of the rotor the streamwise velocity in its wake recovered to about 30% of its free-stream value at the lowest simulated tip speed ratio of 4, while its recovery was equal to about 65% at the largest tip speed ratio of 10. This is due to the earlier breakdown of the tip vortices. The results of the computations demonstrate indeed that mutual inductance phenomena between tip vortices, promoting pairing events and the eventual instability of the helical structures, occur at shorter downstream distances for higher values of tip speed ratio. Wake instability enhances the process of wake recovery, especially due to radial advection. Therefore, higher rotational speeds do not promote wake recovery through more intense tip vortices, but through their greater instability. Implications are important, affecting the optimal distance between rows of axial-flow turbines in array configurations: the operation at higher rotational speeds allows for smaller distances between turbines, decreasing the cost and environmental impact of farms consisting of several devices.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part II: Sensitivity of Surface Wind Speeds to Model Resolution and Physics

Abstract Strong wind events can cause severe economic loss and societal impacts. Peak winds over Wyoming and Colorado occur during the wintertime months, and in the first part of this two-part series, it was shown that the High-Resolution Rapid Refresh (HRRR) model displays large negative biases with respect to strong wind events. In this part of the study, we address two questions: 1) does increasing the horizontal resolution improve the representation of strong wind events over this region, and 2) are the biases in HRRR-forecasted winds related to the selected planetary boundary layer (PBL), surface layer (SL), and/or land surface model (LSM) parameterizations? We conduct Weather Research and Forecasting (WRF) Model simulations to address these two main questions. Increasing the horizontal resolution leads to a small improvement in the simulation of strong wind speeds over the complex terrain of Wyoming and Colorado. In general, changes in the PBL, SL, and LSM parameterizations show much larger changes in simulated wind speeds compared to increasing the model resolution alone. Specifically, changing from the Mellor–Yamada–Nakanishi–Niino scheme to the Mellor–Yamada–Janjić PBL and SL schemes results in nearly no change in the r2 values, but there is a decrease in the magnitude of the strong wind speed bias (from −12.52 to −10.16 m s−1). We attribute these differences to differences in the diagnosis of surface wind speeds and mixing in the boundary layer. Further analysis is conducted to determine the value of 1-km forecasts of strong winds compared with wind speed diagnostics commonly used by the National Weather Service. Significance Statement Motivated by prior studies showing low skill in the prediction of strong winds using state-of-the-art weather forecast models, in this study, we aim to investigate two questions: 1) does increasing the horizontal resolution improve the prediction of strong wind events over the complex terrain of Wyoming and Colorado, and 2) are the biases in High-Resolution Rapid Refresh (HRRR) forecasted winds related to the selected planetary boundary layer, surface layer, and/or land surface model parameterizations? We find that increasing the horizontal resolution provides a slight improvement in the prediction of strong winds. Further, considerable improvement in the prediction of strong winds is found for varying boundary layer, surface layer, and land surface parameterizations.

Testing for biofilm release as a function of simulated ship speed using a calibrated water jet device

Biofouling release coatings (BRCs) have received attention for their potential to limit the negative impacts of biofouling on marine shipping. The calibrated water jet (CWJ, patent # US 8,984,958 B1) can be used to study the effectiveness of BRCs as a function of ship speed. Using a balance of force and linear momentum, we examined the theory and application of the CWJ for simulating the effect of ship speed on biofilm release for surfaces fouled under (1) laboratory and (2) natural conditions. Greater fouling release corresponded with an increase in CWJ pressure and, therefore, simulated ship speed for the surfaces coated with HullKote. The effectiveness of the CWJ was further confirmed for biofilm release from glass fouled naturally by submersion in flow-through seawater. A scaling analysis confirms that the results of these small-scale experiments are applicable to larger-scale biofouling release from ship hulls. This study is the first to utilize the pressure of a CWJ to quantify biofouling release as a function of simulated ship speed.

基于EDEM的滩涂养殖双螺旋推进器仿真分析与试验

Aiming at the problems of coastal ecological damage and low yield of mudflat aquaculture caused by the invasion of M. alterniflora, in order to improve the operational efficiency of mudflat wet and soft ground, and to promote the ecological balance and the development of coastal agriculture, a walking device with twin spiral propellers for muddy wet and soft ground was designed. Using EDEM simulation software to simulate and analyze, the discrete element model of muddy soil particles is established to analyze the interaction mechanism with the spiral propeller and the operation propulsion effect, and it is concluded that the spiral propeller will not produce congestion phenomenon during the operation; data are collected through several simulation tests, and the optimal parameter design of the spiral propeller structure is derived from the response surface analysis, and the spiral propeller is designed to operate at a speed of 2.416 mph in the simulation with the optimal parameter of structural design. The field test shows that the optimal height of the spiral blades is 50 mm, the total length of the drum is 2,970 mm, the helix angle of lift is 30 °, the pitch is 453 mm, and the propelling speed is 2.36 m/s. The data collected through several simulation tests are used to find the optimal parameter design of the spiral propeller structure, and the simulation speed of the spiral propeller in the optimal structural design parameter is 2.416 m/s.

Optimization algorithm of 500kVGIS circuit breaker electric field simulation based on GPU acceleration

It proposes an optimization approach for electric field simulation in 500kV gas-insulated switchgear (GIS) circuit breakers that use GPU acceleration. Accurate modelling of electric field distribution within GIS circuit breakers is critical for assuring the dependability and safety of high voltage power systems. However, the computational complexity of simulating these systems presents substantial obstacles to established approaches. The goal of this work is to improve the speed, efficiency, and scalability of electric field simulations by leveraging GPU parallel processing capabilities. They methodically build and refine the simulation algorithm, utilizing techniques such as parallel algorithm design, GPU architecture optimization, and efficient memory management. Through rigorous performance studies, they demonstrate significant increases in computational efficiency relative to CPU-based techniques, with an average speed up of 15x. Furthermore, the scalability of the GPU-accelerated method is evaluated, demonstrating near-linear scalability up to 8 GPUs. Validation against experimental observations and analytical models indicates that the simulation findings are accurate and robust. This study helps the progress of electric field simulation tools for GIS circuit breakers by providing insights into electric field behaviour and aiding design optimization and performance evaluation in high voltage power systems.

Improved Real‐Time Post‐Processing for Quantum Random Number Generators

AbstractRandomness extraction is a key problem in cryptography and theoretical computer science. With the recent rapid development of quantum cryptography, quantum‐proof randomness extraction has also been widely studied, addressing the security issues in the presence of a quantum adversary. In contrast with conventional quantum‐proof randomness extractors characterizing the input raw data as min‐entropy sources, it is found that the input raw data generated by a large class of trusted‐device quantum random number generators can be characterized as the so‐called reverse block source. This fact enables us to design improved extractors. Two novel quantum‐proof randomness extractors for reverse block sources that realize real‐time block‐wise extraction are proposed specifically. In comparison with the general min‐entropy randomness extractors, the designs achieve a significantly higher extraction speed and a longer output data length with the same seed length. In addition, they enjoy the property of online algorithms, which process the raw data on the fly without waiting for the entire input raw data to be available. These features make the design an adequate choice for the real‐time post‐processing of practical quantum random number generators. Applying the extractors to the raw data generated by a widely used quantum random number generator, a simulated extraction speed as high as 300 Gbps is achieved.

An improved social force model for improving pedestrian avoidance by reducing search size

In order to solve the slow simulation speed of the social force model in complex indoor scenes, an improved social force model is proposed to reduce the iteration scale of obstacles. The proposed model takes into account the factor of a person’s field of view (FOV) in indoor scenes, and the acting force between pedestrians and obstacles in the social force model is improved to find the optimal number of obstacle iterations without affecting the pedestrian movement law in the traditional model, so as to accelerate the simulation speed. The self-built simulation platform and real evacuation experiments are used to compare the performance indicators of traditional and optimized models and to analyze the relationship between scene complexity and machine computing efficiency. The results show that the optimized model takes less time to predict the evacuation path than traditional models, and as the number of initial pedestrians and obstacles increases, the proportion of machine computation time between the two models will gradually increase. Second, the CPU computation time of the optimized model increases gently, indicating better stability. Therefore, reducing the obstacle iteration scale based on the pedestrian’s FOV factor provides an effective method to solve the slow simulation speed of traditional models.

Bounding Volume Hierarchy-Assisted Fast SAR Image Simulation Based on Spatial Segmentation

In order to improve the simulation efficiency under the premise of ensuring the fidelity of synthetic aperture radar (SAR) simulation images, we propose a BVH-assisted fast SAR image simulation method based on spatial segmentation. The beam scanning model is established based on RD imaging geometric relation, and the bounding volume hierarchy (BVH) algorithm is used to assist in obtaining the time-varying latticed radiation and shadow areas within the radar beam, combining them with the real-time position of the sensors to complete the simulation of the electromagnetic (EM) wave transmission. The ray tracing algorithm is used to calculate the multiple backscatter fields of EM waves, including various material properties of the target surface. The SAR spatial traversal is adopted to spatially segment the latticed radiation area, and the compute unified device architecture (CUDA) kernel function is designed using the echo matrix cell method to make each cell of the target echo matrix as a subfield of the backscattering field, and the position of the echo matrix cell is traversed to obtain the target backscattering field. The target simulated echo is processed by the range Doppler (RD) imaging algorithm to obtain the SAR-simulated image. The simulation results show that compared with a CPU single-thread simulation, the simulation speed of the proposed method is significantly improved, and the SAR simulation image has high structural similarity with the real image, which fully verifies the effectiveness of the proposed method.