Multidimensional Simulations Research Articles

Efficient method for estimating the time evolution of the proto-neutron star mass and radius from a supernova neutrino signal

ABSTRACTIn this paper, we present a novel method to estimate the time evolution of the proto-neutron star (PNS) structure from the neutrino signal in a core-collapse supernova (CCSN). Employing recent results from multidimensional CCSN simulations, we delve into a relation between the total emitted neutrino energy (TONE) and PNS mass/radius, and we find that they are strongly correlated with each other. We fit the relation by simple polynomial functions connecting the TONE to the mass and radius of the PNS as a function of time. By combining another fitting function representing the correlation between the TONE and the cumulative number of events at each neutrino observatory, the PNS mass and radius can be retrieved from purely observed neutrino data. We demonstrate retrievals of PNS mass and radius from mock data of the neutrino signal, and we assess the capability of our proposed method. While underlining the limitations of the method, we also discuss the importance of the joint analysis with the gravitational wave signal. This would reduce uncertainties of parameter estimations in our method, and may narrow down the possible neutrino oscillation model. The proposed method is a very easy and inexpensive computation, which will be useful in real data analysis of the CCSN neutrino signal.

A multi-component surrogate mechanism of diesel from indirect coal liquefaction for diesel engine combustion and emission simulations

Diesel from indirect coal liquefaction (DICL) is a kind of extremely promising alternative fuel to alleviate the oil security problem caused by excessive dependence on imported oil and reduce the pollutant emission. However, the mechanism of diesel from indirect coal liquefaction is very few, and the numerical simulation of combustion and emission characteristics of diesel from indirect coal liquefaction is even less. Therefore, a reduced mechanism of DICL, entailing 178 components and 650 reactions, was put forward to research the combustion and emission characteristics of engines fueled with DICL under different loads in this work. n-Hexadecane (HXN) mechanism and 2,2,4,4,6,8,8-heptamethylnonane mechanism (HMN) were respectively considered as representative species of straight-chain paraffin and branched alkane in surrogate model. Firstly, direct relation graph and direct relation graph with error propagation were used in turn. Then, sensitivity analysis coupled with rate of production analysis has been used to further reduce the detail 2,2,4,4,6,8,8-heptamethylnonane mechanism. After that, the skeleton mechanism of n-hexadecane and the reduced polycyclic aromatic hydrocarbon (PAH) mechanism were combined with the simplified HMN mechanism to develop a novel multi-component mechanism of HXN-HMN-PAH. Brute-force sensitivity analyses were respectively conducted at different temperatures to find out these key reactions that have great effects on the ignition delay times (IDTs). Then, the optimizations of the reduced mechanism were made based on the ignition delay times of the experimental datum and the detail mechanism. A proportion of 71.5% HXN and 28.5% HMN by mole fraction was determined according to the properties of practical DICL. Furthermore, the optimized mechanism was employed to verify experimental values including the ignition delay times, the species concentrations on jet-stirred reactors (JSR) and the laminar flame speeds. Eventually, the mechanism was coupled into computational fluid dynamic (CFD) to perform multi-dimensional numerical simulation validation in a directed injection compression ignition (DICI) engine under different loads.

Development of empirically derived brief program evaluation measures in Pennsylvania first-episode psychosis coordinated specialty care programs.

The Pennsylvania first episode psychosis program evaluation (PA-FEP-PE) core assessment battery was developed as a standard and comprehensive clinical assessment and data collection tool in Pennsylvania coordinated specialty care programs (CSC). To reduce administrative time and maximize clinical utility by maintaining acceptable levels of precision, we aimed to generate a short form using item response theory (IRT)-based computer-adaptive test (CAT) simulation and analyse the implementation and acceptability of the short form among providers from PA-CSC. FEP participants (n=759; age 14-36) from nine coordinated specialty care programs completed 156 items drawn from the PA-FEP-PE battery. Multidimensional IRT-based CAT simulations were used to select the best PA-FEP-PE items for abbreviated forms. A 67-item PA-FEP-PE short form was developed to capture six factors: (1) positive affect and surgency (with negative loadings on Anxious-Misery items); (2) psychiatric services satisfaction; (3) antipsychotic side effect severity; (4) family turmoil and associated traumas; (5) trauma load; and (6) psychosis. The total number of items was reduced more than 50% in the PA-FEP-PE shortened forms. The short form demonstrated good psychometric properties, and it was well accepted by our providers in the implementation. The empirical derivation and implementation of abbreviated measures of key domains and constructs in FEP care have streamlined and facilitated PA-FEP program evaluation. Our work supports potential application of IRT based methods to empirically reduce core assessment battery measures in large-scale data collection efforts such as in the Early Psychosis Intervention Network.

Plasma propagation via radiation transfer in millimeter-wave discharge under subcritical condition

An improved model was proposed to reduce a computational cost for subcritical millimeter-wave discharge. The proposed model was able to reproduce the plasma-front propagation via radiation transport as similar to the conventional model, and the plasma-front propagation speed was in agreement with the previous simulation. An electron transport effect by neutral fluid advection, which has been introduced into the conventional model, does not affect the propagation speed. By using the presented model, a computational time was reduced by 35%, which was suitable for a multi-dimensional simulation in the future.

Ionization-Gasdynamic Simulations of Wind-Blown Nebulae around Massive Stars

Using a code that employs a self-consistent method for computing the effects of photo-ionization on circumstellar gas dynamics, we model the formation of wind-driven nebulae around massive stars. We take into account changes in stellar properties and mass-loss over the star’s evolution. Our simulations show how various properties, such as the density and ionization fraction, change throughout the evolution of the star. The multi-dimensional simulations reveal the presence of strong ionization front instabilities in the main-sequence phase, similar to those seen in galactic ionization fronts. Hydrodynamic instabilities at the interfaces lead to the formation of filaments and clumps that are continually being stripped off and mixed with the low density interior. Even though the winds start out as completely radial, the spherical symmetry is quickly destroyed, and the shocked wind region is manifestly asymmetrical. The simulations demonstrate that it is important to include the effects of the photoionizing photons from the star, and simulations that do not include this may fail to reproduce the observed density profile and ionization structure of wind-blown bubbles around massive stars.

Immersed boundary simulations of flows driven by moving thin membranes

Immersed boundary methods are extensively used for simulations of dynamic solid objects interacting with fluids due to their computational efficiency and modeling flexibility compared to body-fitted grid methods. However, thin geometries, such as shells and membranes, cause a violation of the boundary conditions across the surface for many immersed boundary projection algorithms. Using a one-dimensional analytical derivation and multi-dimensional numerical simulations, this manuscript shows that adjustment of the Poisson matrix itself is require to avoid large velocity, pressure, and force prediction errors when the pressure jump across the interface is substantial and that these errors increase with Reynolds number. A new minimal thickness modification is developed for the Boundary Data Immersion Method (BDIM-σ), which avoids these issues while still enabling the use of efficient projection algorithms for high-speed immersed surface simulations.

Two-Dimensional Simulations of Laser Shock Peening of Aluminum With Water Confinement

Nowadays, advanced surface improvement techniques are required, due to continuously rising demands in aerospace and automotive productions. Laser shock peening (LSP) is a widely known modern surface enhancement method. LSP usually deals with nanosecond laser pulses with high intensities exceeding 1 GW/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . Due to very short time scales, all the occurring physical phenomena and processing parameters are extremely difficult to measure and study just based on experimental investigations. Therefore, multidimensional computer simulations of the processes within LSP are required for further optimization. In this work, a 2-D hydrodynamic simulation of water-confined nanosecond laser shock peening of an aluminum target is performed applying the open-source code MULTI2D. Circular laser beam with a pulse energy of 1 J, 20-ns duration, a diameter of 1 mm, and a uniform spatial distribution is used. Spatial profiles of the laser-induced plasma pressure and temperature are determined together with the shock wave parameters. It is shown that the plasma is highly confined and a temperature-affected region is very thin. Radial expansion of the surface pressure profile and the shock wave propagation can be observed, indicating that radial effects have to be considered during the industrial application of LSP. The obtained results are in good agreement with available simulations and measurements, validating the proposed simulation approach. In addition, temporal and spatial distributions of the pressure at the surface of the target material can be applied in finite-element simulations to predict residual stresses distributions.

On the Emergence of a New Instability during Core Collapse of Very Massive Stars

Abstract The process of uniform supernovae (SNe) explosions is well investigated for all their types. However, observational data suggests that the SNe may be not spherically symmetric. Modern multidimensional simulations of SNe demonstrate development of hydrodynamical instabilities during the explosion phase. But the configuration of a star and inhomogeneities prior to explosion could strongly affect how the SN develops. A number of papers on numerical modeling of pair-instability SNe explosion considered the case when thermonuclear energy in the central region of a massive star is introduced by a series of several hot spots. It leads to the appearance of many fragments of hot matter behind the divergence shock wave. An observable manifestation of this may be the presence of peaks on light curves of gamma-ray bursts associated with explosions of massive stars. The physical nature of such inhomogeneities is not evident and the number and size of spots is conjecture. In this work, we study the possibility of formation of these inhomogeneities at the stage of core collapse (CC) in a massive star. To check this assumption, we chose an analytic self-similar model of CC and investigated the stability of solutions obtained from it with respect to small multidimensional perturbations. It shows there are no conditions where the collapse of a very massive star may remain stable, although, for a less massive star, it is possible. Using the relations obtained, we found characteristic features of developing instability, thereby making it possible to estimate the amount and characteristic size of the inhomogeneities.

Learning to discover: expressive Gaussian mixture models for multi-dimensional simulation and parameter inference in the physical sciences

We show that density models describing multiple observables with (1) hard boundaries and (2) dependence on external parameters may be created using an auto-regressive Gaussian mixture model. The model is designed to capture how observable spectra are deformed by hypothesis variations, and is made more expressive by projecting data onto a configurable latent space. It may be used as a statistical model for scientific discovery in interpreting experimental observations, for example when constraining the parameters of a physical model or tuning simulation parameters according to calibration data. The model may also be sampled for use within a Monte Carlo simulation chain, or used to estimate likelihood ratios for event classification. The method is demonstrated on simulated high-energy particle physics data considering the anomalous electroweak production of a Z boson in association with a dijet system at the Large Hadron Collider, and the accuracy of inference is tested using a realistic toy example. The developed methods are domain agnostic; they may be used within any field to perform simulation or inference where a dataset consisting of many real-valued observables has conditional dependence on external parameters.

Plasma assisted combustion of methane-air mixtures: Validation and reduction

For several years now plasma assisted combustion has been the subject of intense research due to stabilization effects a plasma can have on flames. Particularly, experiments have shown the promising impact of Nanosecond Repetitively Pulsed discharges on combustion while not exceeding an energy consumption of a few percent of the flame power. In this work, an incremental methodology with a step-by-step approach has been used to build a single plasma mechanism upon which combustion is added using the GRI 3.0 and Konnov v0.6. The methodology focuses on three key aspects of plasma assisted combustion: fast gas heating, slow gas heating and radical production. Selected experiments focusing on one or more of these aspects allow to validate the mechanism in large ranges of temperature (300-1500 K) and pressure (0.1-1 bar) in air, methane-air and argon diluted mixtures using glow and spark discharges. These experiments include a plasma assisted ignition case on which the ignition delay time is well captured by the mechanism. Slow gas heating has been modeled using a vibrational relaxation model validated against a detailed vibrational description. Discussions on ambiguous rates for critical reactions of excited nitrogen quenching are made in the light of their impact on the results on the chosen experiments. Finally, the resulting 100-species GRI 3.0-based and 264-species Konnov v0.6-based plasma mechanisms are reduced to make them suitable for multi-dimensional simulations. The DRGEP reduction method, based on plasma experiments and canonical combustion cases, is applied allowing to reduce the number of species by a factor larger than two. For the GRI-3.0 plasma mechanism, the reduced mechanism contains 47 species and 429 reactions. Hence significant performance is gained, opening the way to multi-dimensional simulations of plasma assisted combustion.

The launching of cosmic ray-driven outflows

ABSTRACT Cosmic rays (CRs) are thought to be an important feedback mechanism in star-forming galaxies. They can provide an important source of pressure support and possibly drive outflows. We perform multidimensional CR magnetohydrodynamic simulations including transport by streaming and diffusion to investigate wind launching from an initially hydrostatic atmosphere by CRs. We estimate a characteristic Eddington limit on the CR flux for which the CR force exceeds gravity and compare it to simulated systems. Scaling our results to conditions in star-forming galaxies, we find that CRs are likely to contribute to driving outflows for a broad range of star formation environments. We quantify the momentum and energy transfer between CRs and gas, along with the associated mass outflow rates under different assumptions about the relative importance of streaming and diffusion for transport. In simulations with streaming, we observe the growth and saturation of the CR acoustic instability, but the CRs and gas remain well coupled, with CR momentum transferred efficiently to the gas even when this instability is present. Higher CR fluxes transfer more energy to the gas and drive stronger outflows. When streaming is present, most of the transferred energy takes the form of Alfvén wave heating of the gas, raising its pressure and internal energy, with a lower fractional contribution to the kinetic energy of the outflow. We also consider runs with radiative cooling, which modifies gas temperature and pressure profiles but does not seem to have a large impact on the mass outflow for super-Eddington CR fluxes.

Multi-dimensional electrostatic plasma simulations using the particle-in-cell method for the low-temperature plasmas for materials processing

Multi-dimensional electrostatic plasma simulations using the particle-in-cell method for the low-temperature plasmas for materials processing

Digital Twins of Operational Scenarios in Mining for Design of Customized Product-Service Systems Solutions

The paper presents an approach, based on the development of digital twins, to support the transition toward electromobility and autonomy in the mining industry, by supporting the design space exploration of future operational scenarios based on different construction equipment and mining site configurations. With such an intent, the paper presents an approach combining systems and systems-of-systems simulations to run trade-off analysis based on different product-service systems (PSS) configurations. Additionally, the paper integrates the “operational context” variables in PSS design simulations to create a digital twin of a “mining operational scenario” customizable for the specific configurations of each mine. The paper exemplifies the proposed approach by contextualizing in a reference mining site describing how the multi-dimensional simulations have enabled PSS trade-off analysis and PSS sensitivity analyses, and how operational context variables are integrated into the digital twin of the operational scenario.

A 3D printing method of customized magnetic focusing generator for magnetic field therapy

As one of the most malignant tumors, brain tumors seriously threaten people's health. Traditional treatment methods, such as surgery combined with radiotherapy and chemotherapy, will bring great side effects and high treatment costs. As a new type of brain tumor treatment method, magnetic field therapy has the advantages of well effectiveness, non-invasive property and relatively low treatment cost. However, it has the disadvantage that magnetic field energy cannot effectively focus on tumors, especially when facing the differences of brain tumors among different patients. This may lead to side effects similar to those caused by traditional chemotherapy methods that cannot focus on tumors. For this, a 3D printing method of customized magnetic focusing generator for magnetic field therapy is proposed in the paper. First, a state-of-the-art 3D-Unet artificial intelligence model is used to segment the magnetic resonance imaging (MRI) data of patients to obtain the spatial information of brain tumors and personalized patient skulls. Then, through the design of the hemispherical solenoid array model, the multi-dimensional simulation and actual measurement of the magnetic focusing mode are carried out to obtain a solenoid focusing scheme that gives consideration to both magnetic focusing and energy efficiency. Finally, based on high-precision 3D printing technology, 3D reconstruction is carried out for the spatial information of brain tumors and personalized patient skulls with the solenoid focusing scheme. The magnetic field generator is thus obtained based on customized 3D printing. The device not only fits the patient's skull and is suitable for wearing, but also can accurately control the spatial information related to the tumor, so that the magnetic field energy can accurately focus on the brain tumor area of specific patients to achieve accurate magnetic field treatment. Through the experiment, the actual measurement of the magnetic field distribution generated by the device is carried out and compared with the simulation results. While the magnetic focusing is verified, the error between the measurement and simulation reaches only 2.2%, which verifies the feasibility of the overall method. The customized magnetic focusing generator proposed in the paper is expected to provide a new and effective clinical approach for the treatment of brain tumors.

Radiation-hydrodynamics with MPI-AMRVAC

Context. Radiation controls the dynamics and energetics of many astrophysical environments. To capture the coupling between the radiation and matter, however, is often a physically complex and computationally expensive endeavor. Aims. We sought to develop a numerical tool to perform radiation-hydrodynamics simulations in various configurations at an affordable cost. Methods. We built upon the finite volume code MPI-AMRVAC to solve the equations of hydrodynamics on multi-dimensional adaptive meshes and introduce a new module to handle the coupling with radiation. A non-equilibrium, flux-limiting diffusion approximation was used to close the radiation momentum and energy equations. The time-dependent radiation energy equation was then solved within a flexible framework, fully accounting for radiation forces and work terms and further allowing the user to adopt a variety of descriptions for the radiation-matter interaction terms (“opacities”). Results. We validated the radiation module on a set of standard test cases for which different terms of the radiative energy equation predominate. As a preliminary application to a scientific case, we calculated spherically symmetric models of the radiation-driven and optically thick supersonic outflows from massive Wolf-Rayet stars. This also demonstrates our code’s flexibility, as the illustrated simulation combines opacities typically used in static stellar structure models with a parametrized form for the enhanced line-opacity expected in supersonic flows. Conclusions. This new module provides a convenient and versatile tool for performing multi-dimensional and high-resolution radiative-hydrodynamics simulations in optically thick environments with the MPI-AMRVAC code. The code is ready to be used for a variety of astrophysical applications, where our first target is set to be multi-dimensional simulations of stellar outflows from Wolf-Rayet stars.

NUMERICAL SIMULATION OF SUPERCRITICAL AND SUBCRITICAL INJECTION OF CRYOGENIC NITROGEN BASED ON THE HOMOGENEOUS EQUILIBRIUM MODEL OF TWO-PHASE FLOW

Multidimensional numerical simulations of the outflow of the dense turbulent jet of cryogenic nitrogen into a chamber filled with nitrogen at normal temperature are performed using the homogeneous equilibrium model of the two-phase flow and the new accurate analytical equation of state (EOS) of real gas for nitrogen. The applicability of the new EOS is verified in a wide range of density (from 0 to the liquid density in the triple point) and temperature (from 100 K to 5000 K). The results of calculations are compared with available experimental data on nitrogen density variation in the jets. The satisfactory agreement of the results is obtained. The developed EOS allows the identification of two-phase flow regions and the mass fractions of liquid and gas based on the local instantaneous values of density and temperature in the jet without using the two-fluid flow model.

Seeding the multi-dimensional nonequilibrium pulling for Hamiltonian variation: indirect nonequilibrium free energy simulations at QM levels.

The combination of free energy simulations in the alchemical and configurational spaces provides a feasible route to access the thermodynamic profiles under a computationally demanding target Hamiltonian. Normally, due to the significant differences between the computational cost of ab initio quantum mechanics (QM) calculations and those of semi-empirical quantum mechanics (SQM) and molecular mechanics (MM), this indirect method could be used to obtain the QM thermodynamics by combining the SQM or MM results and the SQM-to-QM or MM-to-QM corrections. In our previous work, a multi-dimensional nonequilibrium pulling framework for Hamiltonian variations was introduced based on bidirectional pulling and bidirectional reweighting. The method performs nonequilibrium free energy simulations in the configurational space to obtain the thermodynamic profile along the conformational change pathway under a selected computationally efficient Hamiltonian, and uses the nonequilibrium alchemical method to correct or perturb the thermodynamic profile to that under the target Hamiltonian. The BAR-based method is designed to achieve the best generality and transferability and thus leads to modest (∼20 fold) speedup. In this work, we explore the possibility of further accelerating the nonequilibrium free energy simulation by employing unidirectional pulling and using the selection criterion to obtain the initial configurations used to initiate nonequilibrium trajectories following the idea of adaptive steered molecular dynamics (ASMD). A single initial condition is used to seed the whole multi-dimensional nonequilibrium free energy simulation and the sampling is performed fully in the nonequilibrium ensemble. Introducing very short ps-length equilibrium sampling to grab more initial seeds could also be helpful. The ASMD scheme estimates the free energy difference with the unidirectional exponential average (EXP), but it does not follow exactly the requirements of the EXP estimator. Another deficiency of the seeding simulation is the inherently sequential or serial pulling due to the inter-segment dependency, which triggers some problems in the parallelizability of the simulation. Numerical tests are performed to grasp some insights and guidelines for using this selection-criterion-based ASMD scheme. The presented selection-criterion-based multi-dimensional ASMD scheme follows the same perturbation network of the BAR-based method, and thus could be used in various Hamiltonian-variation cases.

Implementation of the Hll-Grp Solver for Multidimensional Ideal Mhd Simulations Based on Finite Volume Method

Implementation of the Hll-Grp Solver for Multidimensional Ideal Mhd Simulations Based on Finite Volume Method

Multi-dimensional dynamic simulation of rainstorm waterlogging in urban communities

One major threat to cities at present is the increasing rainstorm waterlogging hazards due to climate change and accelerated urbanization. This paper explores the mechanism of rainstorm waterlogging and enables the fine simulation of surface water propagation over complex urban terrain. A novel community-scale waterlogging modeling scheme is presented by loosely coupling a one-dimensional sewer model with a two-dimensional overland model under an open-source framework. The coupled model was applied to Waigaoqiao Free Trade Zone located in Pudong New Area of Shanghai. To quantify the influence of rainfall intensity and drainage conditions on the waterlogging, 12 scenarios were constructed by combining four rainfall return periods (3, 5, 10, and 20 a) and three startup water depths (1.5, 2.0, and 2.5 m) of pump stations. The multi-scenario simulation results show that the waterlogging risk increases from north to south in the study area, and that risk zones with water depth above 0.3 m are mostly concentrated in the southwest and southeast corners of the site. The longer the rainfall return period, the larger the submerged area, and the spatial distribution of surface water accumulation is affected by local topography and drainage system. In addition, reducing the startup water depth of pump stations has an obvious effect on inhibiting the severity of water accumulation. The results provide insights into overland flow across an urban area with densely populated buildings and help to reduce the risk of rainstorm-induced waterlogging disasters.

Equation of state-driven radiative models for simulation of lightning strikes

This work is concerned with the numerical simulation of plasma arc interaction with aerospace substrates under conditions akin to lightning strike and in particular with the accurate calculation of radiative heat losses. These are important because they have a direct effect on the calculation of thermal and pressure loads on the substrates, which can lead to material damage under certain conditions. Direct numerical solution of the radiation transport equation (RTE) in mesoscale simulations is not viable due to its computational cost, so for practical applications reduced models are usually employed. To this end, four approximations for solving the RTE are considered in this work, ranging from a simple local thermodynamical behavior consideration, to a more complex spectral absorption dependent on the arc geometry. Their performance is initially tested on a one-dimensional cylindrical arc, before implementing them in a multi-dimensional magnetohydrodynamics code. Results indicate that inclusion of spectral absorption is necessary in order to obtain consistent results. However, the approaches accounting for the arc geometry require repeated solution of the computationally intensive Helmholtz equations, making them prohibitive for multi-dimensional simulations. As an alternative, a method using the net emission coefficient is employed, which provides a balance between computational efficiency and accuracy, as shown by comparisons against experimental measurements for a plasma arc attaching to an aluminum substrate.