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At least 937 records · Page 52

Neutrino transport in general relativistic neutron star merger simulations

Abstract Numerical simulations of neutron star–neutron star and neutron star–black hole binaries play an important role in our ability to model gravitational-wave and electromagnetic signals powered by these systems. These simulations have to take into account a wide range of physical processes including general relativity, magnetohydrodynamics, and neutrino radiation transport. The latter is particularly important in order to understand the properties of the matter ejected by many mergers, the optical/infrared signals powered by nuclear reactions in the ejecta, and the contribution of that ejecta to astrophysical nucleosynthesis. However, accurate evolutions of the neutrino transport equations that include all relevant physical processes remain beyond our current reach. In this review, I will discuss the current state of neutrino modeling in general relativistic simulations of neutron star mergers and of their post-merger remnants. I will focus on the three main types of algorithms used in simulations so far: leakage, moments, and Monte-Carlo scheme. I will review the advantages and limitations of each scheme, as well as the various neutrino–matter interactions that should be included in simulations. We will see that the quality of the treatment of neutrinos in merger simulations has greatly increased over the last decade, but also that many potentially important interactions remain difficult to take into account in simulations (pair annihilation, oscillations, inelastic scattering).

Foucart, Francois (ORCID:0000000346174738)↗

Investigating the Chinese postman problem on a quantum annealer

The recent availability of quantum annealers has fueled a new area of information technology where such devices are applied to address practically motivated and computationally difficult problems with hardware that exploits quantum mechanical phenomena. D-Wave annealers are promising platforms to solve these problems in the form of quadratic unconstrained binary optimization. Here we provide a formulation of the Chinese postman problem that can be used as a tool for probing the local connectivity of graphs and networks. We treat the problem classically with a tabu algorithm and simulated annealing, and using a D-Wave device. The efficiency of quantum annealing with respect to the simulated annealing has been demonstrated using the optimal time to solution metric. We systematically analyze computational parameters associated with the specific hardware. Our results clarify how the interplay between the embedding due to limited connectivity of the Chimera graph, the definition of logical qubits, and the role of spin-reversal controls the probability of reaching the expected solution

36 MATERIALS SCIENCE↗

A semi-agnostic ansatz with variable structure for variational quantum algorithms

Quantum machine learning—and specifically Variational Quantum Algorithms (VQAs)—offers a powerful, flexible paradigm for programming near-term quantum computers, with applications in chemistry, metrology, materials science, data science, and mathematics. Here, one trains an ansatz, in the form of a parameterized quantum circuit, to accomplish a task of interest. However, challenges have recently emerged suggesting that deep ansatzes are difficult to train, due to flat training landscapes caused by randomness or by hardware noise. This motivates our work, where we present a variable structure approach to build ansatzes for VQAs. Our approach, called VAns (Variable Ansatz), applies a set of rules to both grow and (crucially) remove quantum gates in an informed manner during the optimization. Consequently, VAns is ideally suited to mitigate trainability and noise-related issues by keeping the ansatz shallow. We employ VAns in the variational quantum eigensolver for condensed matter and quantum chemistry applications, in the quantum autoencoder for data compression and in unitary compilation problems showing successful results in all cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Adiabatic quantum support vector machines

Adiabatic quantum computers can solve difficult optimization problems (e.g., the quadratic unconstrained binary optimization problem), and they seem well suited to train machine learning models. In this paper, we describe an adiabatic quantum approach for training support vector machines. We show that the time complexity of our quantum approach is an order of magnitude better than the classical approach. Next, we compare the test accuracy of our quantum approach against a classical approach that uses the Scikit-learn library in Python across five benchmark datasets (Iris, Wisconsin Breast Cancer (WBC), Wine, Digits, and Lambeq). We show that our quantum approach obtains accuracies on par with the classical approach. Finally, we perform a scalability study in which we compute the total training times of the quantum approach and the classical approach with an increasing number of features and an increasing number of data points in the training dataset. In conclusion, our scalability results show that the quantum approach obtains a 3.5–4.5x speedup over the classical approach on datasets with many (millions of) features.

Computational Complexity↗

Scheduling and Performance of Asynchronous Tasks in Fortran 2018 with FEATS

Most parallel scientific programs contain compiler directives (pragmas) such as those from OpenMP (Hermanns in Parallel programming in Fortran 95 using openMP, 2002. School of Aeronautical Engineering, Universidad Politécnica de Madrid, España, 2011), explicit calls to runtime library procedures such as those implementing the Message Passing Interface (MPI) (in A message-passing interface standard version 4.0, 2021. https://www.mpi-forum.org/docs/mpi-4.0/mpi40-report.pdf), or compiler-specific language extensions such as those provided by CUDA (Ruetsch and Fatica in CUDA Fortran for scientists and engineers: best practices for efficient CUDA Fortran programming, Elsevier, 2013). By contrast, the recent Fortran standards empower developers to express parallel algorithms without directly referencing lower-level parallel programming models (Numrich in Parallel programming with co-arrays, CRC Press, 2018, and Curcic in Modern Fortran: building efficient parallel applications, Manning Publications, 2020). Fortran’s parallel features place the language within the Partitioned Global Address Space (PGAS) class of programming models. When writing programs that exploit data parallelism, application developers often find it straightforward to develop custom parallel algorithms. Problems involving complex, heterogeneous, staged calculations, however, pose much greater challenges. Such applications require careful coordination of tasks in a manner that respects dependencies prescribed by a directed acyclic graph. When rolling one’s own solution proves difficult, extending a customizable framework becomes attractive. Further, the paper presents the design, implementation, and use of the Framework for Extensible Asynchronous Task Scheduling (FEATS), which we believe to be the first task scheduling tool written in modern Fortran. We describe the benefits and compromises associated with choosing Fortran as the implementation language, and we propose ways in which future Fortran standards can best support the use case in this paper.

97 MATHEMATICS AND COMPUTING↗

Chapter 3 - Harvesting Thermal Energy with Ferroelectric Materials

Thermal energy is considered the ubiquitous form of energy as all other forms of energy ultimately degrade to thermal energy. Thermal to electrical energy conversion is currently an important method for electricity generation. The traditional power cycles, however, become technically and economically unviable when heat source temperature reduces below 100 °C. Thermal energy harvesting has been proposed as a viable alternative for low-grade thermal to electrical energy conversion. Thermal energy harvesting is a method of generating electricity using temperature-induced variations in material properties. It is particularly useful when the heat sources are available free-of-cost, either in the form of natural heat or waste heat. While there are several thermal energy harvesting techniques, pyroelectricity is the most promising as it can be used in situations where spatial thermal gradients are difficult to establish or the temperature of the heat source is changing. Despite the fact that the pyroelectric effect in ferroelectric materials has been known for past several decades, thermal energy harvesting using ferroelectric materials has not been much explored in the literature. In this chapter, we would explore various aspects of thermal energy harvesting using ferroelectric materials. We have first established the physics behind ferroelectricity, then provided a detailed description on ferroelectric thermal energy harvesting, discussed various ferroelectric thermodynamic cycles and devices proposed in the literature, and finally described various other emerging applications of ferroelectricity.

DIRECT ENERGY CONVERSION,MATERIALS SCIENCE,OTHER I↗

Artificial-intelligence-based prediction and control of combustion instabilities in spark-ignition engines

In recent years, as engine control strategies have grown increasingly sophisticated in a continued drive for increasing efficiency and reducing emissions, engine operation has been pushed into regimes that are limited by combustion instabilities. These instabilities produce undesirable abnormal combustion events, which pose barriers to further improvement in engine efficiency. Many of the phenomena involved are difficult to model or control using traditional, purely physics-based models and reactive control approaches. Artificial intelligence (AI) techniques offer some promise for achieving more effective combustion stability control, especially when appropriately applied within a physics-informed framework. This chapter illustrates the current state-of-the-art in applying AI to combustion stability control and examines three case studies with application to the dilute stability limit in spark-ignition engines to illustrate the utility and limitations of AI in these applications.

Maldonado Puente, Bryan↗

Optimization of Graded Bed Reactors for Syngas to Olefin (STO) Processes

Reactor designs with mixed catalysts play an important role to transform a multiple reactor system to single-shot reactors. In addition to savings in capital and ease of implementation, single-shot reactors are useful to break equilibrium limitations, therefore increasing the yield and selectivity of desired product. However, the nonlinear, highly exothermic and poorly conditioned nature of mixed-catalyst systems makes it difficult for commercial process simulation and optimization tools to optimize these systems. Here, this study describes the zone and partial moving finite element approaches and their applications to o-xylene oxidation and syngas to olefin (STO) processes. 35% and 5% increases are achieved in the product yield for o-xylene oxidation and STO problems, respectively. Shown with these two examples, this tool is very promising in process intensification for other reactive systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Toolpath considerations for hybrid additive manufacturing

Hybrid additive manufacturing combines both additive and subtractive manufacturing processes to fabricate geometrically complex, dimensionally accurate parts that are difficult to make using either additive or subtractive manufacturing alone. Industrial applications for hybrid additive manufacturing include direct manufacturing (building whole parts), feature addition (adding onto existing parts), and remanufacturing or repair operations. To coordinate the additive and subtractive processes, computer-aided manufacturing (CAM) software must generate distinct toolpaths for each process. Each application requires different considerations and inputs when generating the toolpaths. For example, when building a part with an internal cavity that would otherwise be unmanufacturable due to reach or access limitations, a CAM must determine which layer(s) of deposition are appropriate to machine to create the internal cavity. This chapter explores the area of toolpath generation for hybrid manufacturing by discussing the necessary considerations that are unique to a hybrid process.

Feldhausen, Thomas↗

Late-time small body disruptions for planetary defense

Here, diverting hazardous small bodies on impact trajectories with the Earth can in some circumstances be impossible without risking disrupting them. Disruption is a much more difficult planetary defense scenario to assess, being linked both to the response of the body to shock loading and the much more complicated gravitational dynamics of the fragments in the solar system relative to pure deflection scenarios. In this work we present a new simulation suite built on N-body gravitational methods that solves fragment orbits in the full gravitational system without recourse to more approximate methods. We assess the accuracy of our simulations and the simplifying assumptions we adopt to make the system tractable, and then discuss in more detail several specific, plausible planetary defense scenarios based on real close encounters. We find that disruption can be a very effective planetary defense strategy even for very late (sub-year) interventions, and should be considered an effective backup strategy should preferred methods, which require long warning times, fail.

42 ENGINEERING↗

Air-coupled tsunamis generated from impacts and airbursts: Our understanding before Hunga-Tonga Hunga-Ha'apai

The effort to prevent or mitigate the effects of an impact on Earth is known as planetary defense. A significant component of planetary defense research involves risk assessment. Much of our understanding of the risk from near-Earth objects comes from the geologic record in the form of impact craters, but not all asteroid impacts are crater-forming events. Small asteroids explode before reaching the surface, generating an airburst, and most impacts into the ocean do not penetrate the water to form a crater in the sea floor. The risk from these non-crater-forming ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall threat. We are currently working to better understand impact scenarios that can generate dangerous tsunamis.

54 ENVIRONMENTAL SCIENCES↗

High entropy alloys: A focused review of mechanical properties and deformation mechanisms

The high-entropy alloy (HEA) concept was based on the idea that high mixing entropy can promote formation of stable single-phase microstructures. During the past 15 years, various alloy systems have been explored to identify HEA systems with improved property combinations, leading to an extraordinary growth of this field. In the large pool of alloys with varying characteristics, the first single-phase HEA with good tensile properties, the equiatomic CrMnFeCoNi alloy has become the benchmark material, and it forms the basis of much of our current fundamental understanding of HEA mechanical behavior. As the field is evolving to the more broadly defined complex concentrated alloys (CCAs) and the available data in the literature increase exponentially, a fundamental question remains unchanged: how special are these new materials? In the first part of this review, select mechanical properties of HEAs and CCAs are compared with those of conventional engineering alloys. This task is difficult because of the limited tensile data available for HEAs and CCAs. Additionally, the wider suite of mechanical properties needed to assess structural materials is woefully lacking. Nonetheless, our evaluations have not revealed many HEAs or CCAs with properties far exceeding those of conventional engineering alloys, although specific alloys can show notable enhancements in specific properties. Consequently, it is reasonable to first approach the understanding of HEAs and CCAs through the assessment of how the well-established deformation mechanisms in conventional alloys operate or are modified in the presence of the high local complexity of the HEAs and CCAs. The second part of the paper provides a detailed review of the deformation mechanisms of HEAs with the FCC and BCC structures. For the former, we chose the CrMnFeCoNi (Cantor) alloy because it is the alloy on which the most rigorous and thorough investigations have been performed and, for the latter, we chose the TiZrHfNbTa (Senkov) alloy because this is one of the few refractory HEAs that exhibits any tensile ductility at room temperature. As expected, our review shows that the fundamental deformation mechanisms in these systems, and their dependence on basic physical properties, are broadly similar to those of conventional FCC and BCC metals. The third part of this review examines the theoretical and modeling efforts to date that seek to provide either qualitative or quantitative understanding of the mechanical performance of FCC and BCC HEAs. Since experiments reveal no fundamentally new mechanisms of deformation, this section starts with an overview of modeling perspectives and fundamental considerations. Next, the review turns to the evolution of modeling and predictions as compared to recent experiments, highlighting both successes and limitations. Finally, in spite of some significant successes, important directions for further theory development are discussed. Overall, while the individual deformation mechanisms or properties of the HEAs and CCAs are not, by and large, “special” relative to conventional alloys, the present HEA rush remains valuable because the compositional freedom that comes from the multi-element space will allow exploration of whether multiple mechanisms can operate sequentially or simultaneously, which may yet lead to the creation of new alloys with a spectrum of mechanical properties that are significantly superior to those of current engineering alloys.

36 MATERIALS SCIENCE↗

Defect behavior and radiation tolerance of MAB phases (MoAlB and Fe2AlB2) with comparison to MAX phases

MAB phases are a new class of layered ternary materials that have already shown a number of outstanding properties. Here, we investigate defect evolution and radiation tolerance of two MAB phases, MoAlB and Fe 2 AlB 2 , using a combination of experimental characterization and first-principles calculations. We find that Fe 2 AlB 2 is more tolerant to radiation-induced amorphization than MoAlB, both at 150 °C and at 300 °C. The results can be explained by the fact that the Mo Frenkel pair is unstable in MoAlB and as a result, irradiated MoAlB is expected to have a significant concentration of Mo Al antisites, which are difficult to anneal even at 300 °C. We find that the tolerance to radiation-induced amorphization of MAB phases is lower than in MAX phases, but it is comparable to that of SiC. However, MAB phases do not show radiation-induced cracking which is observed in MAX phases under the same irradiation conditions. This research suggests that MAB phases might be a promising class of materials for applications that involve radiation.

36 MATERIALS SCIENCE↗

Effects of Solidification Cooling Rates on Microstructures and Physical Properties of Fe-6.5%Si Alloys

Compared to the widely used Fe-3.2wt%Si steel, Fe-6.5wt%Si has superior electric and magnetic properties, including higher electrical resistivity, lower iron loss, higher permeability, and near zero magnetostriction. However, Fe-6.5wt%Si sheet is difficult to produce using traditional manufacturing processes as the high silicon content favors the formation of ordered phases that embrittle the material. Fortunately, these ordered phases can be suppressed if the alloy is cooled fast enough from a high temperature kinetically trapping the disordered solid solution or amorphous state. Planar flow casting is known for its rapid solidification rate. In order to consider it as a viable method to manufacture ductile Fe-6.5wt%Si sheets, the effect of cooling rate on physical properties of Fe-6.5wt%Si alloy are systematically investigated. In this work, various cooling rates are achieved by changing melt-spin wheel speeds, which significantly affect the solidification temperature profile and have profound effects on ordering, microstructures, textures, hardness, and magnetic properties. High cooling rates result in refined grains, reduced ordering, enhanced <100> out of the plane texture, decreased hardness, and increased coercivity. This study demonstrates a critical cooling rate at ~1.7 × 10 5 K/s, corresponding to a tangential wheel speed of 5-7 m/s, below which the hardness significantly increases in agreement with the sudden increase of the ordered phases that causes the material embrittlement.

36 MATERIALS SCIENCE↗

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗

Formation of misfit dislocation arrays and helium nanochannels near copper surface assisted by high-temperature graphene deposition

Misfit dislocation arrays (MDAs) at semi-coherent heterogeneous interface have been demonstrated effectiveness to trap and then outgas helium (He) for alleviating void swelling in metals, but limited by atomic-level thin film deposition that is difficult to scale-up for industrial production. In this work, we proposed an innovative strategy that could generate semi-coherent homophase interfaces in a same grain by varying surface energy density assisted by high-temperature graphene (Gr) deposition. This strategy transforms strain energy and surface energy, two originally distinctive processes into successive processes, and demonstrates experimentally and theoretically by introducing {111} copper (Cu) in a {100} Cu grain. Subsequent He implantation and electrical resistivity measurement results suggest that high-density MDAs originated at this {111}/{100} interface could form stable He nanochannels near Cu surface with Gr assistance, manifesting by ultra-low increased ratio of the electrical resistivity (i.e. ~3800% of Cu vs. ~90% of Gr/Cu) after He implantation. Finally, the present findings may provide a new strategy for efficiently managing He and achieving surface protection of advanced metals, merely by depositing a super-rigid material on metal surface to greatly reduce surface energy density.

36 MATERIALS SCIENCE↗

Intermetallic particle heterogeneity controls shear localization in high-strength nanostructured Al alloys

The mechanical behavior of two nanocrystalline Al alloys, Al-Mg-Y and Al-Fe-Y, is investigated with in-situ micropillar compression testing. Both alloys were strengthened by a hierarchical microstructure including grain boundary segregation, nanometer-thick amorphous complexions, carbide nanorod precipitates with sizes of a few nanometers, and submicron-scale intermetallic particles. The maximum yield strength of the Al-Mg-Y system is measured to be 950 MPa, exceeding that of the Al-Fe-Y system (680 MPa), primarily due to a combination of more carbide nanorods and more amorphous complexions. Both alloys exhibited yield strengths much higher than those of commercial Al alloys, and therefore have great potential for structural applications. However, some micropillar specimens were observed to plastically soften through shear banding. Post-mortem investigation revealed that intermetallic-free deformation pathways of a few micrometers in length were responsible for this failure. Further characterization showed significant grain growth within the shear band. The coarsened grains maintained the same orientation with each other, pointing to grain boundary mechanisms for plastic flow, specifically grain rotation and/or grain boundary migration. Here, the presence of intermetallic particles makes it difficult for both matrix and intermetallic grains to rotate into the same orientation due to the different lattice parameters and slip systems. Therefore, we are able to conclude that a uniform distribution of intermetallic particles with an average spacing less than the percolation length of shear localization can effectively prevent the maturation of shear bands, offering a design strategy for high-strength nanocrystalline Al alloys with both high strength and stable plastic flow.

36 MATERIALS SCIENCE↗

Probing phase stability in CrMoNbV using cluster expansion method, CALPHAD calculations and experiments

High entropy alloys (HEA), a novel class of materials with multiple principal elements, allow us to tune the properties within a wide composition range where the solid-solution phase is stable. However, it is difficult to experimentally determine the boundaries of the single-phase region. In this paper, we calculate the phase diagram of the CrMoNbV quaternary system, as well as its constituent binary and ternary subsystems, using a combination of the cluster expansion method and CALPHAD calculations. We further verify these results by carrying out experiments at two different compositions of the full quaternary system. Furthermore, our work shows how these computational tools can enable efficient discovery and development of new HEAs.

36 MATERIALS SCIENCE↗