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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Score-based deterministic density sampling

We propose a deterministic sampling framework using Score-Based Transport Modeling for sampling an unnormalized target density π given only its score ∇ log π. Our method approximates the Wasserstein gradient flow on KL($f_t$∥π) by learning the time-varying score ∇ log $f_t$ on the fly using score matching. While having the same marginal distribution as Langevin dynamics, our method produces smooth deterministic trajectories, resulting in monotone noise-free convergence. We prove that our method dissipates relative entropy at the same rate as the exact gradient flow, provided sufficient training. Numerical experiments validate our theoretical findings: our method converges at the optimal rate, has smooth trajectories, and is often more sample efficient than its stochastic counterpart. Experiments on high-dimensional image data show that our method produces high-quality generations in as few as 15 steps and exhibits natural exploratory behavior. The memory and runtime scale linearly in the sample size.

97 MATHEMATICS AND COMPUTING↗

A novel approach for calculating galaxy rotation curves using spaxel cross-correlation and iterative smoothing

ABSTRACT Precise measurements of the internal dynamics of galaxies have proven of great importance for understanding the internal dark matter distribution of galaxies. We present a novel method for measuring the line-of-sight (LOS) velocities across the face of galaxies by cross-correlation of spectral pixels (spaxels) and an iterative method of smoothing. On simulated data the method can accurately recover the input LOS velocities for different types of spectra (absorption-line dominated, emission-line dominated, and differing shapes of the continuum), and can handle stellar population radial gradients. Most important of all, it continues to provide reliable measurements of LOS velocities with reasonable uncertainties even when the spectra are very low signal-to-noise ratio (approaching ∼1), which is a challenge for traditional template-fitting approaches. We apply our method to data from a real MaNGA galaxy as a demonstration and find promising results with good precision. This novel approach can be complementary to existing methods primarily based on template fitting.

79 ASTRONOMY AND ASTROPHYSICS↗

Scaled boundary cubature scheme for numerical integration over planar regions with affine and curved boundaries

This paper introduces the scaled boundary cubature (SBC) scheme for accurate and efficient integration of functions over polygons and two-dimensional regions bounded by parametric curves. Over two-dimensional domains, the SBC method reduces integration over a region bounded by m curves to integration over m regions (referred to as curved triangular regions), where each region is bounded by two line segments and a curve. With proper (counterclockwise) orientation of the boundary curves, the scheme is applicable to convex and nonconvex domains. Additionally, for star-convex domains, a tensor-product cubature rule with positive weights and integration points in the interior of the domain is obtained. If the integrand is homogeneous, we show that this new method reduces to the homogeneous numerical integration scheme; however, the SBC scheme is more versatile since it is equally applicable to both homogeneous and non-homogeneous functions. This paper also introduces several methods for smoothing integrands with point singularities and near-singularities. When these methods are used, highly efficient integration of weakly singular functions is realized. Finally, the SBC method is applied to a number of benchmark problems, which reveal its broad applicability and superior performance (in terms of time to generate a rule and accuracy per cubature point) when compared to existing methods for integration.

42 ENGINEERING↗

Surface smoothing for laser powder-bed Ti-6Al-4V by a transient liquid phase

Surface roughness is the primary driver of fatigue for additively manufactured metals. To address surface roughness, this work introduces a new method to smooth features beyond line-of-sight without material removal. The method applies a coating that triggers local surface remelting by activating a eutectic reaction during heat treatment. The associated liquid phase then wets and isothermally solidifies into a smoother surface. For Ti-6Al-4V fabricated with laser powder bed fusion, samples with and without TLP smoothing (using a Cu coating) were characterized with a suite of techniques, including mechanical testing, electron backscatter diffraction, synchrotron X-ray tomography, and fractography. TLP smoothing reduced surface roughness by 80% and amplified compressive residual stress at the surface by about 50%. With statistically equivalent virtual microstructures, crystal plasticity scrutinized the roles of phases, porosity, and surface roughness. Although the tensile strain-to-failure was reduced to 1% strain, the TLP smoothing process increased high-cycle fatigue strength by about 20% compared to control samples, pointing to future opportunities to optimize the new process through various coating compositions and heat treatment schedules. Overall, this work establishes a new paradigm for treating surfaces of materials for smoothness and compressive residual stress.

Additive manufacturing↗

Optimal Polynomial Smoothers and One‐Sided V‐Cycles for Poisson Problems

The solution to the Poisson equation arising from the spectral element discretization of the incompressible Navier‐Stokes equations needs robust preconditioning strategies. One such strategy is multigrid. To realize the potential of multigrid methods, effective smoothing strategies are needed. Chebyshev polynomial smoothers, in conjunction with pointwise Jacobi or additive Schwarz methods (ASMs), prove to be an effective smoother. Other polynomial smoothers, however, may provide superior convergence to the multigrid preconditioner. The authors compare the standard Chebyshev polynomial smoothers to both the novel fourth‐kind Chebyshev polynomial smoothers proposed by Lottes as well as smoothers based on the polynomial of best uniform approximation to as proposed by Kraus, Vassilevski, and Zikatanov. At the cost of symmetry, further improvements may be made. For example, a order polynomial smoother on both sides of the V‐cycle may be substituted with an order polynomial smoother on one side at no additional cost. The choice of omitting the postsmoother in favor of higher‐order polynomial presmoothing is advantageous in cases where the multigrid approximation property constant is large. The authors consider a 2D model problem based on finite differences to motivate the choice of polynomial smoother, order, and whether to apply postsmoothing for the target application of high‐order ‐geometric multigrid methods for GPU architectures. Results from both domains demonstrate the substantial improvement of these approaches over the standard Chebyshev polynomial smoother with a symmetric V‐cycle.

97 MATHEMATICS AND COMPUTING↗

COUPLING SMOOTHED PARTICLE HYDRODYNAMICS WITH FINITE ELEMENT METHOD TO SIMULATE RESIDUAL STRESSES FROM FRICTION STIR PROCESSING

Friction stir processing (FSP) is a solid-state material processing technique that locally modifies the microstructure but also induces undesirable residual stresses. A robust numerical model for the FSP can help in mitigating these residual stresses. Heat source models within a finite element method (FEM) framework suffer from inaccuracies. In contrast, smoothed particle hydrodynamics (SPH) model that explicitly captures the material flow near the tool and the associated heat generation are accurate. However, the computational expense of SPH simulations can be prohibitive. In this work, we propose a coupled SPH-FEM framework. SPH is used to model the heat generation accurately near the tool and which is then inserted into to the FEM model as a heat source. To verify this proposed coupling approach, a test case is set up with typical FSP conditions and it is modeled in both SPH and SPH-FEM. The temperatures profiles were compared after the simulations have reached steady-state temperatures. The similarity of the temperature profiles from SPH-FEA and SPH validated the proposed coupling approach. This proposed approach achieves the accuracy of the SPH method while potentially retaining the low computational expense of FEM.

smoothed particle hydrodynamics, Finite Element Me↗

Three-dimensional phase field sintering simulations accounting for the rigid-body motion of individual grains

Sintering is a widely used powder processing technique in industrial applications. During sintering, atoms migrate to decrease the energy of the system via two main mechanisms: coarsening and densification, both of which lead to significant morphological variation of the sintered microstructure. When simulating sintering dynamics, the phase-field method has been broadly utilized because of its convenience in tracking morphology evolution. When a large number of grains is involved, it is common to use the same order parameter to describe multiple grains that are not in direct contact with one another (in order to reduce the computational memory demands). However, with this treatment it is difficult to handle the rigid-body motion of individual grains during densification. In this work, an implementation scheme is introduced to overcome the challenge of calculating individual particle motion based on existing equations. It uses a grouping algorithm and sets a cutoff radius on each grain for calculating the particle velocity during densification. This method allows for the incorporation of the densification mechanism, which has been commonly ignored in previous work, into phase-field sintering models in three-dimensional simulations with a large number of particles/grains. Moreover, through combination with the smoothed boundary method, material properties of sintered microstructures, such as the effective diffusivity and Young’s modulus, can be calculated during the sintering processes.

36 MATERIALS SCIENCE↗

Wet-Etching of Acoustically Spalled GaAs for Substrate Reuse

Acoustic spalling is a promising technique for substrate reuse in the fabrication of gallium arsenide (GaAs) photovoltaic cells. However, the acoustic spalling process can leave the substrate with areas of rough surface morphology that can interfere with subsequent cell growth and processing. In this work, we investigate the use of wet etchants to smooth the surface of acoustically spalled GaAs substrates. We evaluated six different etchants. Of those tested, an 8:1:1 mixture of sulfuric acid, hydrogen peroxide, and water at 30 degrees C and a moderate stirring rate showed the greatest roughness reduction per mass loss while producing the desired morphology. This etchant was then applied to an acoustically spalled 2-inch GaAs wafer. A single-junction GaAs cell was then grown via metalorganic vapor-phase epitaxy on this substrate, an acoustic spalled substrate without a smoothing etch, and an epi-ready substrate. Use of the 8:1:1 H2SO4:H2O2:H2O etchant produced cells an average efficiency of 12.8% as compared to that of 2.0% grown on the unetched acoustically spalled substrate and 16.3% grown on the epi-ready substrate. The results of this work demonstrate that wet etching is a viable method for smoothing the surface of spalled GaAs substrates, paving the way for substrate reuse via acoustic spalling at efficiencies that approach growth on epi-ready substrates.

etching↗

Toward Higher-order Accuracy in Self-gravitating Hydrodynamics

High-order algorithms have emerged in numerical astrophysics as a promising avenue to reduce truncation error (proportional to a power of the linear resolution Δ x ) with only a moderate increase to computational expense. Significant effort has been placed in the development of finite-volume algorithms for (magneto)hydrodynamics; however, state-of-the-art astrophysical simulations tightly couple a plenitude of physics, additionally including gravity, photon transport, cosmic-ray transport, chemistry, and/or diffusion, to name a few. Algorithms frequently operator-split this additional physics (often a first-order error in time) and/or adopt a model wherein their evaluation is limited to second-order accuracy in space. In this work, we present a fourth-order-accurate finite-volume scheme for self-gravitating hydrodynamics on a uniform Cartesian grid. The method supplies source terms for the gravitational acceleration ( ρ g ) and gravitational energy release ( ρ v · g ) associated with fourth-order-accurate solutions to the Poisson equation. Our scheme (1) guarantees the conservation of total linear momentum while (2) decreasing (in proportion to Δ x 4 ) the effects of spurious heating and/or cooling associated with truncation error in the gravity. We demonstrate expected convergence rates for the algorithm by measuring errors in test problems evolving self-gravity modified linear waves and 3D polytropic equilibria. We test robustness of the algorithm by integrating an induced “inside-out” adiabatic collapse. We also discuss a method to smoothly downgrade the solution to second-order spatial accuracy to avoid spurious overshoots near steep density and/or pressure gradients.

79 ASTRONOMY AND ASTROPHYSICS↗

A Two-Stage Decomposition Approach for AC Optimal Power Flow

The alternating current optimal power flow (AC-OPF) problem is critical to power system operations and planning, but it is generally hard to solve due to its nonconvex and large-scale nature. Furthermore, this paper proposes a scalable decomposition approach in which the power network is decomposed into a master network and a number of subnetworks, where each network has its own AC-OPF subproblem. This formulates a two-stage optimization problem and requires only a small amount of communication between the master and subnetworks. The key contribution is a smoothing technique that renders the response of a subnetwork differentiable with respect to the input from the master problem, utilizing properties of the barrier problem formulation that naturally arises when subproblems are solved by a primal-dual interior-point algorithm. Consequently, existing efficient nonlinear programming solvers can be used for both the master problem and the subproblems. The advantage of this framework is that speedup can be obtained by processing the subnetworks in parallel, and it has convergence guarantees under reasonable assumptions. The formulation is readily extended to instances with stochastic subnetwork loads. Numerical results show favorable performance and illustrate the scalability of the algorithm which is able to solve instances with more than 11 million buses.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Missing-Data Nonparametric Coherency Estimation

Chave recently proposed an estimator for multitaper spectral density where the time series contains missing values. In this article we generalize this technique to a multitaper estimator of coherence and phase and show that one can also obtain bootstrapped confidence intervals. Additionally, we give two examples. The first is a toy example in which the true coherence is known. In the second example we show that the multitaper missing-data coherence estimator computed on real data with a single gap comprising 11% of the data outperforms the Daniell-smoothed coherence estimator where there are no gaps. The case where the two time series have different missing indices is also discussed.

42 ENGINEERING↗

Hierarchical Speed Planner for Automated Vehicles: A Framework for Lagrangian Variable Speed Limit in Mixed-Autonomy Traffic

Here, this article presents a novel hierarchical speed planning framework for variable speed limits in mixed-autonomy traffic environments, leveraging server-side macroscopic control and vehicle-side microscopic execution. The framework integrates real-time traffic state estimation (TSE) and reinforcement learning (RL)-based control to mitigate congestion and improve traffic flow. A TSE enhancement module combines macroscopic data from sources like INRIX with high-resolution observations from connected autonomous vehicles (CAVs), enabling predictive modeling to address latency and noise. The target speed design module employs kernel smoothing and a buffer zone strategy to optimize traffic density and flow around bottlenecks. The proposed system was validated in the largest open-road test to date with 100 CAVs, demonstrating an overall 8% traffic density decrease, with a specific decrease of 7% upstream, 10% downstream, and a 52% decrease during the congestion formation phase at bottlenecks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design, Preparation, and Execution of the 100-AV Field Test for the CIRCLES Consortium: Methodology and Implementation of the Largest Mobile Traffic Control Experiment to Date

This article presents the comprehensive design, setup, execution, and evaluation of the MegaVanderTest (MVT) experiment conducted by the Congestion Impacts Reduction via CAV-in-the-Loop Lagrangian Energy Smoothing (CIRCLES) Consortium, which aimed to mitigate traffic congestion using partially autonomous vehicles (AVs) (see “Summary”). The experiment involved 100 vehicles on Nashville’s Interstate 24 (I-24) highway, utilizing various control algorithms to smooth stop-and-go traffic waves. The execution of the MVT experiment required a coordinated effort from multiple teams. This article details the meticulous planning process, the coordinated efforts of multiple teams, and the innovative use of a dynamic agent-based simulation framework for traffic evaluation. Here, the contributions of this work include demonstrating and providing a detailed roadmap for large-scale live traffic experiments, illustrating the lessons learned from the MVT experiment, and introducing the other articles in this issue and their complementary relationship in the MVT experiment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Traffic Smoothing Using Explicit Local Controllers: Experimental Evidence for Dissipating Stop-and-go Waves with a Single Automated Vehicle in Dense Traffic

This article presents experimental evidence of the ability of a single automated vehicle acting as a controller to effectively dissipate stop-and-go waves in real traffic. The automated vehicle succeeded in stabilizing the speed profile by reducing oscillations in time and speed variations between vehicles during rush hour on I-24 in the Nashville area. Here, we detail the control design, deployment and results obtained in this experiment, conducted as part of the CIRCLES consortium’s “MegaVanderTest” 2022, which involved a total of 100 automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Planarization of Rough (100) GaAs Substrates via Growth by Hydride Vapor Phase Epitaxy

Wafer reuse techniques help offset the cost of III-V growth substrates by using a single wafer for multiple growths, but costly re-polishing after device removal limits the end benefit. In this work, we present planarization growth by hydride vapor-phase epitaxy (HVPE), a potentially low-cost growth technique, as a method of smoothing rough substrates for subsequent high-quality device growth without the need for polishing. First, we show there is a threshold for allowable substrate roughness without device degradation by comparing devices grown by organometallic vapor-phase epitaxy (OMVPE) on epi-ready polished and pre-polished substrates that did not have the final epi-ready polish. We then demonstrate successful smoothing with HVPE growth on substrates with different surface morphologies, with features ranging from general roughness to large facets. Initial devices grown by HVPE on a pre-polished substate showed no degradation compared to a control wafer, indicating that planarizing rough substrates through HVPE growth is a promising path toward being able to use rough substrates directly for growth, without costly polishing steps.

GaAs↗