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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 109 records · Page 6

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DOE OSTI2021

AURORA: Automated Refinement of Coarse-Grained Reconfigurable Accelerators

Coarse-grained reconfigurable arrays (CGRAs), loosely defined as arrays of functional units interconnected through a network-on-chip (NoC), provide higher flexibility than domain-specific ASIC accelerators while offering increased hardware efficiency with respect to fine-grained reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs). Un-fortunately, designing a CGRA for a specific application domain involves enormous software/hardware engineering effort (e.g., designing the CGRA, map operations onto the CGRA, etc) and requires the exploration on a large design space (e.g., applying appropriate loop transformation on each application, specializing the reconfigurable processing elements of the CGRA, refining the network topology, deciding the size of the data memory, etc). Int his paper, we propose AURORA – a software/hardware co-design framework to automatically synthesize optimal CGRA given a set of applications of interest

Tan, Cheng↗

DOE OSTI2024

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large-scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Autotuning↗

DOE OSTI2021

Comparative studies of 2HDMs under the Higgs boson precision measurements

We perform comparative studies for four types of the two Higgs Doublet Models (2HDMs) under the precision measurements of the Standard Model (SM) Higgs observables at the proposed Higgs factories. We explore the discovery potential based on the hypothetical deviations in the precision data for the 2HDMs up to one-loop level. We find 5σ observability from the χ2 fitting in a significant theory parameter space at future Higgs factories. For the Type-I 2HDM, regions with cos(β - α) ≲ -0.1 or cos(β - α) ≳ 0.08 are discoverable at more than 5σ level. For the other three types of 2HDMs, the 5σ region is even bigger: | cos(β - α)| ≳ 0.02 for tan β ~ 1. At small and large values of tan β, the region in cos(β - α) is further tightened. We examine the extent to which the different 2HDM theories may be distinguishable from one to the other at the 95% Confidence Level with four benchmark points as case studies. We show that a large part of the parameter space of the other types of 2HDMs can be distinguished from the benchmark points of the target model. The impacts of loop corrections are found to be significant in certain parameter regions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Self-supervised learning of spatiotemporal thermal signatures in additive manufacturing using reduced order physics models and transformers

Microstructure control via additive manufacturing has enormous potential as manufacturers, materials scientists, and designers alike seek to exploit novel fabrication technologies to improve component performance. Recent works have demonstrated the feasibility of producing materials with controlled microstructures across various length scales. However, the experimental approach towards exploring the process-structure space can be laborious and costly. This is particularly true if also considering scan pattern optimization which is well suited for processes such as powder bed fusion electron beam melting. In this work we propose an approach for encoding additive manufacturing layer-wise thermal response signatures using self-supervised representation learning. Thermal simulations from a reduced order model are utilized to estimate the spatiotemporal response during printing. A machine learning framework, using video-transformers, is utilized to efficiently distill spatiotemporal patterns into a compact latent space representation. This latent state representation encodes the relevant physics which is then utilized to establish a data-driven process-structure model for an additively manufactured Ni-based superalloy. In conclusion, the proposed methodology could potentially be used towards in-situ process monitoring, scan pattern experimental design, and component qualification.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Non-equilibrium reducing flame aerosol process to create supported high-entropy alloy nanoparticles

High-entropy alloy (HEA) nanomaterials provide opportunities and property combinations for energy and electronic applications, but their practical synthesis faces challenges of elemental immiscibility, metal reducibility, and particle aggregation during their synthesis. Herein, we report a broadly applicable non-equilibrium, scalable, and in-situ reducing flame aerosol process for synthesis of supported HEA nanoparticles. This versatile process can directly load a high concentration of 2 ~ 4 nm HEA nanoparticles on various 1- to 3-dimensional supports. Notably, simultaneous formation of HEA nanoparticles and a mesoporous silica support was successfully realized in a single step. Exploration of this process demonstrates the role of kinetics and entropy on decreasing alloy particle size and altering the reducibility of elements. We propose an entropy-induced reduction mechanism to incorporate oxidizable elements into HEAs, which extends the compositional space of HEA nanoparticles. As a representative catalytic application, we present a RuPdOsIrPt/graphene electrocatalyst with high activity and stability for hydrogen oxidation reaction. Our findings open horizons for high-performance HEA design and applications in diverse fields such as catalysis, electrochemistry, and sensing.

organic↗

DOE OSTI2024

The science case for an intermediate energy advanced and novel accelerator linear collider facility

It is widely accepted that the next lepton collider beyond a Higgs factory would require center-of-mass energy of the order of up to 15 TeV. Since, given reasonable space and cost restrictions, conventional accelerator technology reaches its limits near this energy, high-gradient advanced acceleration concepts are attractive. Advanced and novel accelerators (ANAs) are leading candidates due to their ability to produce acceleration gradients on the order of 1–100 GV/m, leading to compact acceleration facilities. However, intermediate energy facilities (IEF) are required to test the critical technology elements on the way towards multi-TeV-class colliders. Here a science case for a 20–100 GeV center-of-mass energy ANA-based lepton collider that can be a candidate for an intermediate energy facility is presented. The IEF can provide numerous opportunities for high energy physics studies including precision Quantum Chromodynamics and Beyond the Standard Model physics measurements, investigation of charged particle interactions with extreme electromagnetic fields, and exploring muon and proton beam acceleration. Possible applications of this collider include the studies of γγ and electron beam-fixed target/beamdump collider designs. Thus, the goal of the proposed IEF is to both carry out particle physics measurements in the 20-100 GeV ranges as well as to serve as an ANA demonstrator facility.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Navigator function for the conformal bootstrap

Current numerical conformal bootstrap techniques carve out islands in theory space by repeatedly checking whether points are allowed or excluded. We propose a new method for searching theory space that replaces the binary information "allowed"/"excluded" with a continuous "navigator" function that is negative in the allowed region and positive in the excluded region. Such a navigator function allows one to efficiently explore high-dimensional parameter spaces and smoothly sail towards any islands they may contain. The specific functions we introduce have several attractive features: they are well-defined in large regions of parameter space, can be computed with standard methods, and evaluation of their gradient is immediate due to an SDP gradient formula that we provide. The latter property allows for the use of efficient quasi-Newton optimization methods, which we illustrate by navigating towards the 3d Ising island.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Alternative Treatment of Defense Waste Processing Facility Recycle via Reuse of Existing Liquid Waste Facilities - 20097

The Defense Waste Processing Facility (DWPF) at Savannah River Site (SRS) has been immobilizing high level waste since 1996. The chemical process within DWPF generates a large volume of condensate, which is recycled to the SRS H-Area Tank Farm. The recycle stream includes a small quantity of sludge solids, as well as soluble cesium that is volatilized during melter operation. The recycle waste is currently received into a large, underground waste tank that separates insoluble solids via decanting. The supernate is treated by an evaporator with a concentrate stream that is stored for future processing. The evaporator overheads are collected and sent to the Effluent Treatment Project (ETP) for final polishing and testing prior to discharge to local surface water. Recycle storage and treatment as described above complicates the overall mission within the tank farms, which are primarily engaged in waste retrieval and preparation activities that support sludge and salt disposition, as well as tank characterization and closure. The need to devote a portion of available storage space to recycle treatment limits operational flexibility, and ultimately the DWPF recycle stream must be diverted to fully close all the SRS waste tanks. An alternative treatment process is being explored to decouple the recycle stream from the tank farm. The proposed treatment process will accomplish solids separation via crossflow filtration and will utilize a wiped film evaporator to volume-reduce the filtrate stream. Evaporator overheads will continue to be further processed in ETP while the solids stream and evaporator concentrate stream will be returned for reprocessing with the DWPF and Salt Waste Processing Facility (SWPF). This process will utilize existing facilities within DWPF and the tank farm that were previously dedicated to Interim Salt Disposition (ISD), but no longer have an identified mission with the startup of SWPF. The reuse of these facilities will remove several constraints from the current Liquid Waste (LW) System Plan without expanding the current footprint of Department of Energy Environmental Management (EM) infrastructure within LW. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Isochronous and period-doubling diagrams for symplectic maps of the plane

Symplectic mappings of the plane serve as key models for exploring the fundamental nature of complex behavior in nonlinear systems. Central to this exploration is the effective visualization of stability regimes, which enables the interpretation of how systems evolve under varying conditions. While the area-preserving quadratic Hénon map has received significant theoretical attention, a comprehensive description of its mixed parameter-space dynamics remain lacking. This limitation arises from early attempts to reduce the full two-dimensional phase space to a one-dimensional projection, a simplification that resulted in the loss of important dynamical features. Consequently, there is a clear need for a more thorough understanding of the underlying qualitative aspects. This paper aims to address this gap by revisiting the foundational concepts of reversibility and associated symmetries, first explored in the early works of G.D. Birkhoff. We extend the original framework proposed by Hénon by adding a period-doubling diagram to his isochronous diagram, which allows to represents the system’s bifurcations and the groups of symmetric periodic orbits that emerge in typical bifurcations of the fixed point. A qualitative and quantitative explanation of the main features of the region of parameters with bounded motion is provided, along with the application of this technique to other symplectic mappings, including cases of multiple reversibility. Modern chaos indicators, such as the Reversibility Error Method (REM) and the Generalized Alignment Index (GALI), are employed to distinguish between various dynamical regimes in the mixed space of variables and parameters. These tools prove effective in differentiating regular and chaotic dynamics, as well as in identifying twistless orbits and their associated bifurcations. Additionally, we discuss the application of these methods to real-world problems, such as visualizing dynamic aperture in accelerator physics, where our findings have direct relevance.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Sunbeam: Near-sun statites as beam platforms for beam-driven rockets

Here, we outline a method of beamed power for propulsion that utilizes relativistic electron beams. The physics of charged particle beam propagation in the space plasma environment is discussed and the long-range (> 100 AU) advantage of relativistic electron beams is emphasized. A preliminary statite-based beam emitter for powering probes to 0.1c is proposed and the challenges in beamed-power uses are explored.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

New insights on the nebular emission, ionizing radiation, and low metallicity of Green Peas from advanced modelling

ABSTRACT Low-metallicity, compact starburst galaxies referred to as Green Peas (GPs) provide a unique window to study galactic evolution across cosmic epochs. In this work, we present new deep optical spectra for three GPs from OSIRIS at the 10-m Gran Telescopio Canarias, which are studied using a state-of-the-art methodology. A stellar population synthesis is conducted with 1098 spectral templates. The methodology succeeds at characterizing stellar populations from 0.5 Myr to 10 Gyr. The light distribution shows a large red excess from a single population with ${log}\left({age}\right) \gt 8.5\, \mathrm{yr}$ in the GP sample analysed. This points towards an incomplete characterization of the gas luminosity, whose continuum already accounts between 7.4 and $27.6{{\ \rm per\ cent}}$ in the galaxy sample. The emission spectra are fitted with the largest Bayesian chemical model consisting of an electron temperature, an electron density, the logarithmic extinction coefficient and eleven ionic species under the direct method paradigm. Additionally, building on previous work, we propose a neural networks sampler to constrain the effective temperature and ionization parameter of each source from photoionization model grids. Finally, we combine both methodologies into a 16-dimensional model, which for the first time, simultaneously explores the direct method and photoionization parameter spaces. Both techniques consistently indicate a low-metallicity gas, $7.76\lt 12+{\rm log}\left(O/H \right)\lt 8.04$, ionized by strong radiation fields, in agreement with previous works.

Fernández, V. (ORCID:0000000305315450)↗

DOE OSTI2022

Reliability-Informed Economic and Energy Evaluation for Bi-Level Design for Remanufacturing: A Case Study of Transmission and Hydraulic Manifold

Abstract Design for remanufacturing (DfRem) is one attractive strategy that encourages the reuse of a product and extends the product's life cycle. Traditional design processes often only consider product reliability at an early design stage. However, from the perspective of environmental sustainability, it is becoming increasingly important to evaluate the long-term economic and environmental impacts of design decisions during early-stage design. We propose a bi-level DfRem framework consisting of system-level reusability allocation and component-level design tradeoff analysis, considering reliability and product warranty policy. First, a system-level reusability allocation problem aims at a theoretical exploration of the design space where all the components comprising the system are allocated certain reuse rates to achieve target energy savings with minimum cost. Following the theoretical exploration at the system level, a component-level analysis looks at practical design options for each component and trades-off between the overall cost and energy consumption for multiple remanufacturing cycles. Both levels of the framework require modeling component reuse for multiple remanufacturing cycles, which we achieve by using a branched power-law model that provides probabilistic scenarios of reusing the component or replacing it with a new part. We demonstrate the utility of this framework with the case study of an infinitely variable transmission (IVT) used by some agricultural machines manufactured by John Deere and show snapshots of a prototype software tool that we developed for easy use by designers.

Engineering↗

DOE OSTI2024

Chiral kinematic theory and converse vortical effects

Response theories in condensed matter typically describe the response of an electron fluid to external electromagnetic fields, while perturbations on neutral particles are often designed to mimic such fields. Here, we study the response of fermions to a space-time-dependent velocity field, thereby sidestepping the issue of gauge charge. First, we use a semiclassical chiral kinematic theory to obtain the local density of current and extract the orbital magnetization. The theory immediately predicts a "converse vortical effect," defined as an orbital magnetization driven by linear velocity. It receives contributions from magnetic moments on the Fermi surface and the Berry curvature of the occupied bands. Then, transcending semiclassics via a complementary Kubo formalism reveals that the uniform limit of a clean system receives only the Berry curvature contribution while other limits sense the Fermi surface magnetic moments too. We propose CoSi as a candidate material and suggest magnetometry of a sample under a thermal gradient to detect the effect. Overall, our study sheds light on the effects of a space-time-dependent velocity field on electron fluids and paves the way for exploring quantum materials using new probes and perturbations.

Chen, Kai↗

DOE OSTI2022

Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling

Abstract Effective plasma transport modeling of magnetically confined fusion devices relies on having an accurate understanding of the ion composition and radiative power losses of the plasma. Generally, these quantities can be obtained from solutions of a collisional-radiative (CR) model at each time step within a plasma transport simulation. However, even compact, approximate CR models can be computationally onerous to evaluate, and in-situ evaluation of these models within a larger plasma transport code can lead to a rigid bottleneck. As a way to bypass this bottleneck, we propose deploying artificial neural network (ANN) surrogates to allow rapid evaluation of the necessary plasma quantities. However, one issue with training an accurate ANN surrogate is the reliance on a sufficiently large and representative training and validation data set, which can be time-consuming to generate. In this work we explore a data-driven active learning and training routine to allow autonomous adaptive sampling of the problem parameter space to ensure a sufficiently large and meaningful set of training data is assembled for the network training. As a result, we can demonstrate approximately order-of-magnitude savings in required training data samples to produce an accurate surrogate.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Not so HOT Triangulations

Here, we propose primal–dual mesh optimization algorithms that overcome shortcomings of the standard algorithm while retaining some of its desirable features. “Hodge-Optimized Triangulations” defines the “HOT energy” as a bound on the discretization error of the diagonalized Delaunay Hodge star operator. HOT energy is a natural choice for an objective function, but unstable for both mathematical and algorithmic reasons: it has minima for collapsed edges, and its extrapolation to non-regular triangulations is inaccurate and has unbounded minima. We propose a different extrapolation with a stronger theoretical foundation, and avoid extrapolation by recalculating the objective just beyond the flip threshold. We propose new objectives, based on normalizations of the HOT energy, with barriers to edge collapses and other undesirable configurations. We propose mesh improvement algorithms coupling these. When HOT optimization nearly collapses an edge, we actually collapse the edge. Otherwise, we use the barrier objective to update positions and weights and remove vertices. By combining discrete connectivity changes with continuous optimization, we more fully explore the space of possible meshes and obtain higher quality solutions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Proposal for a proton-bunch compression experiment at IOTA in the strong space-charge regime

The longitudinal compression of intense proton bunches with strong space-charge force is an essential component of a proton-based muon source for a muon collider. This paper discusses a proton-bunch compression experiment at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab to explore optimal radio frequency (RF) cavity and lattice configurations. IOTA is a compact fixed-energy storage ring that can circulate a 2.5-MeV proton beam with varying beam parameters and lattice configurations. The study will aim to demonstrate a bunch-compression factor of at least 2 in the IOTA ring while examining the impact of intense space-charge effects on the compression process.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Proposal for a Proton-Bunch Compression Experiment at IOTA in the Strong Space-Charge Regime

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

AdjointBackMapV2: Precise reconstruction of arbitrary CNN unit’s activation via adjoint operators

Adjoint operators have been found to be effective in the exploration of CNN’s inner workings (Wan and Choe, 2022). However, the previous no-bias assumption restricted its generalization. We overcome the restriction via embedding input images into an extended normed space that includes bias in all CNN layers as part of the extended space and propose an adjoint-operator-based algorithm that maps high-level weights back to the extended input space for reconstructing an effective hypersurface. Such hypersurface can be computed for an arbitrary unit in the CNN, and here we prove that this reconstructed hypersurface, when multiplied by the original input (through an inner product), will precisely replicate the output value of each unit. We show experimental results based on the CIFAR-10 and CIFAR-100 data sets where the proposed approach achieves near 0 activation value reconstruction error.

97 MATHEMATICS AND COMPUTING↗