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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Approximating a linear multiplicative objective in watershed management optimization

Implementing management practices in a cost-efficient manner is critical for regional efforts to reduce the amount of pollutants entering the Chesapeake Bay. We study the problem of selecting a subset of practices that minimizes pollutant load—subject to budgetary and environmental constraints—as simulated in a widely used regulatory watershed model. Mimicking the computation of pollutant load in the regulatory model, we formulate this problem as a continuous optimization model with a linear multiplicative objective function and linear constraints. To lay the groundwork for incorporating additional stakeholder requirements in the future, especially those that would require integer variables, we present and study a continuous linear optimization model that approximates the nonlinear model. The linear model, which requires an exponential number of variables, arises naturally as an alternative model for the same underlying physical process. We examine the theoretical behavior of these optimization models and investigate restrictions of the linear model to handle its large number of variables. Through extensive computational tests on real and randomly generated instances, we demonstrate that the linear model and its restrictions provide optimal solutions close to those of the nonlinear model in practice, despite poor approximation properties in the worst case. We conclude that the linear model—together with our approach to handling its large number of variables—provides a viable framework from which to extend the optimization model to better meet the needs of the Chesapeake Bay watershed management stakeholders.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Cutting the Deployment Costs of Physics-Based MPC in Buildings by Simulation-Based Imitation Learning

It has been shown that model predictive control (MPC) is a promising solution for energy-efficient building operations. However, the deployment of MPC in a large portion of the building stock has not been possible partially because of high installation costs. Every building is unique and requires a tailored MPC solution. The best performing solutions are often based on physics-based modeling, which is, however, computationally expensive and requires dedicated software. A promising direction that tackles this problem is to train a neural network-based optimal control policy to imitate the behavior of physics-based MPC from the simulation data generated offline. The neural networks give control actions that closely approximate those produced by physics-based MPC, but with a fraction of the computational and memory requirements and without the need for licensed software. The main advantage of the proposed approach stems from simple evaluation at execution time, leading to low computational footprints and easy deployment on embedded HW platforms. In the case study, we present the energy savings potential of physics-based MPC applied to an office building in Belgium. We demonstrate how neural network approximators can be used to cut the implementation and maintenance costs of MPC deployment without compromising performance. We also critically assess the presented approach by pointing out the remaining challenges and open research questions.

Drgona, Jan↗
DOE OSTI2020

Advancing the physics basis for quasi-helically symmetric stellarators

A new optimized quasi-helically symmetric configuration is described that has the desirable properties of improved energetic particle confinement, reduced turbulent transport by three-dimensional shaping and non-resonant divertor capabilities. The configuration presented in this paper is explicitly optimized for quasi-helical symmetry, energetic particle confinement, neoclassical confinement and stability near the axis. Post optimization, the configuration was evaluated for its performance with regard to energetic particle transport, ideal magnetohydrodynamic stability at various values of plasma pressure and ion temperature gradient instability induced turbulent transport. The effects of discrete coils on various confinement figures of merit, including energetic particle confinement, are determined by generating single-filament coils for the configuration. Preliminary divertor analysis shows that coils can be created that do not interfere with expansion of the vessel volume near the regions of outgoing heat flux, thus demonstrating the possibility of operating a non-resonant divertor.

Physics↗
DOE OSTI2023

HetArch: Heterogeneous Microarchitectures for Superconducting Quantum Systems

Noisy Intermediate-Scale Quantum Computing (NISQ) has dominated headlines in recent years, with the longer-term vision of Fault-Tolerant Quantum Computation (FTQC) offering significant potential but at currently intractable resource costs and quantum error correction (QEC) overheads. For problems of interest, FTQC will require millions of physical qubits with long coherence times, high-fidelity gates, and compact sizes to surpass classical systems. Just as heterogeneous specialization has offered scaling benefits in classical computing, it is likewise gaining interest in FTQC. However, systematic use of heterogeneity in either hardware or software elements of FTQC systems remains a serious challenge due to the vast design space and the variable physical constraints. This paper meets the challenge of making heterogeneous FTQC design practical by introducing HetArch, a toolbox for designing heterogeneous quantum systems, and using it to explore heterogeneous design scenarios. Using a hierarchical approach, we successively break quantum algorithms into smaller operations (akin to classical application kernels), thus greatly simplifying the design space and resulting tradeoffs. Specializing to superconducting systems, we then design optimized heterogeneous hardware composed of varied superconducting devices, abstracting physical constraints into design rules that enable devices to be assembled into standard cells optimized for specific operations, which, in turn, form heterogeneous modules optimized for quantum subroutines. Finally, we provide a heterogeneous design space exploration framework which reduces the simulation burden by a factor of 10^4 or more and allows us to characterize optimal design points. We use these techniques to design superconducting quantum modules for entanglement distillation, error correction, and code teleportation, reducing error rates by 2.6×, 10.7×, and 3.4× compared to homogeneous systems.

Quantum Computing, Quantum Physics, Computer Archi↗
DOE OSTI2021

Predicting temperature-dependent ultimate strengths of body-centered-cubic (BCC) high-entropy alloys

This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature, T break , introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay below T break . We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

DIII-D High Field Side Lower Hybrid Current Drive Experiment Overview

In preparation for high field side lower hybrid current drive (HFS LHCD) experiments in DIII-D, the HFS LHCD was to be commissioned and physics experiments commence once the system operated up to 300 kW for 0.5 s. The initial physics experiments sought to characterize coupling, wave propagation, and driven current measurements. In HFS LHCD first campaign, the maximum power was limited to <200 kW due to waveguide pressure leaks limiting the number of available modules and power per module. Here we summarize commissioning progress and initial physics observations. The HFS LHCD coupler was optimized for high qmin, DIII-D discharges where efficient off-axis current at r/a~0.6-0.8 is desired. The coupler n|| spectrum is peaked at 2.7 and is predicted to generate ~0.14 MA/MW coupled for 1.6 MW injected. In preparation, the HFS scrape-off layer density profile was characterized and found to have steeper profiles and lower fluctuation levels than the low field side. Furthermore, the HFS SOL density profile can be accurately predicted using global plasma quantities using machine learning. Thus far, one module has injected ~100 kW for 0.5 s with <5% reflected power. Nonthermal electrons have been observed on lower frequency channels of the electron cyclotron emission radiometer correlated with the LH power indicating core wave absorption. To avoid 30R neutral beam heat flux, a split launcher is proposed to avoid the high heat flux region while maintaining power spectrum and directivity.

Wukitch, Stephen J. [Massachusetts Inst. of Techno↗
DOE OSTI2023

Full-Field Strain Measurement Integrated with Two Dimension Regression Analysis to Evaluate the Bi-Modulus Elastic Properties of Isotropic and Transversely Isotropic Materials

Background: Measuring the physical properties of shale is critical for optimizing engineering activities such as geothermal energy generation and hydraulic fracturing. Shale is a transversely isotropic material. Furthermore, this material can also include micro and macro cracks at different locations and orientations that cause it to behave differently under tensile or compressive loading. Objective: In this work, a combined experimental–numerical approach is proposed to evaluate the bi-modulus elastic properties of isotropic and transversely isotropic materials. Methods: Full-field strain measurements for a circular disk under diametral compression are integrated with a regression analysis technique to evaluate the elastic properties of bi-modulus materials subjected to tensile and compressive loads using two loading configurations on the same specimen. Digital Image Correlation (DIC) is used to measure the full-field strains. Subsequently, in the case of an isotropic material, a linear least-squares approach is utilized to process the experimentally determined strains in conjunction with analytical expressions of the stress fields (in terms of far-field loading) to determine the elastic modulus E, the shear modulus G, and the Poisson’s ratio $v$. In the case of a transversely isotopic material, such as shale, a finite element model is implemented to determine the stress fields (again in terms of far-field loading), which is followed by repeating the previous regression analysis in an iterative process to estimate the elastic parameters. Results: The results show that the proposed technique successfully provides a complete set of elastic properties as a function of both the loading condition and the principal material directions. The technique is validated by measurements on a known isotropic material and then applied to determine the properties of shale. Conclusion: In this work, the proposed approach is successfully used to calculate the bi-modulus elastic response of poly(methyl meth- acrylate) (PMMA) and shale. As expected, PMMA exhibits an isotropic response with no bi-modulus effect, however, shale exhibits both transverse isotropy and a bi-modulus effect. Therefore, this approach holds promise for investigating the elastic properties of materials like rocks and fiber-reinforced composite laminates as functions of the principal material directions and the loading conditions.

42 ENGINEERING↗
DOE OSTI2023

A framework for understanding efficient diurnal CO 2 reduction using Si and GaAs photocathodes

Integrated solar fuels and photoelectrochemical (PEC) CO 2 reduction (CO 2 R) are promising pathways toward producing value-added chemicals from CO 2 . However, improvements are needed in activity and selectivity as well as in fundamental understanding of device behavior to engender wide deployment. Here, we report two single-junction, integrated photocathodes for PEC CO 2 R based on TOPCon Si and GaAs substrates, which achieve -10 mA cm -2 at -0.33 V vs. RHE with 41% selectivity to C 2+ products and at -0.03 V vs. RHE with 27% selectivity to C 2+ products, respectively. We investigated the viability of a light-mediated strategy to direct selectivity in buried-junction PEC devices and confirmed that these devices could be optimized independently and described by the physics-based models of the individual components. Finally, we designed a framework to assess operational modes for PEC CO 2 R devices and demonstrated this framework under continuous galvanostatic control and variable illumination conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins

Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.

Additive Manufacturing↗
DOE OSTI2025

Investigation of the temperature-dependent failure processes in PVD Cr-coated ZIRLO nuclear fuel cladding using in situ X-ray micro-tomography imaging

In this work, an accident tolerant fuel cladding system with Cr coating deposited using physical vapour deposition (PVD) method onto commercial Optimized ZIRLO™ was studied. The cladding tubes were machined into C-rings and loaded to failure under compression with real-time synchrotron micro-X-ray computed tomography (XCT) imaging at room temperature (RT), 345 °C, 650 °C and 950 °C in argon (Ar) atmosphere. The mechanical behaviour and failure processes were found strongly temperature-dependent where the Cr coating showed brittle fracture at RT and 345 °C, ductile fracture at 650 °C and a reversion to brittle fracture at 950 °C. Nanoindentation measurements and scanning electron microscopy (SEM) imaging were conducted on the materials after high temperature testing. It was found that recrystallisation of the Cr coating occurred at elevated temperatures, which significantly affected its local properties hence the failure behaviour at different temperatures. This work represents the first in situ 3D XCT observation of progressive failure processes in PVD Cr-coated ZIRLO claddings up to 950 °C providing critical insights into its brittle-to-ductile transition (BDTT) behaviour and subsequent ductile-to-brittle reversion with the increase in temperature. Moreover, results are compared with other PVD Cr-coated Zircaloy materials from open literature; the influences of the coating microstructure and local properties on the failure stress/strain and fracture processes are discussed.

Yuan, Guanjie↗
DOE OSTI2021

Climate-Induced Tradeoffs in Planning and Operating Costs of a Regional Electricity System

Electricity grid planners design the system in order to supply electricity to end users reliably and affordably. Climate change threatens both objectives through potentially compounding supply- and demand-side climate-induced impacts. Uncertainty surrounds each of these future potential impacts. Given long planning horizons, system planners must weigh investment costs against operational costs under this uncertainty. Here, we developed a comprehensive and coherent integrated modeling framework combining physically-based models with cost-minimizing optimization models in the power system. We applied this modeling framework to analyze potential tradeoffs in planning and operating costs in the power grid due to climate change in the Southeast U.S. in 2050. We find that planning decisions that do not account for climate-induced impacts would result in a substantial increase in social costs associated with loss of load. These social costs are a result of under-investment in new capacity and capacity deratings of thermal generators when we included climate change impacts in the operation stage. Finally, these results highlight the importance of including climate change effects in the planning process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Data-driven approach to parameterize SCAN + U for an accurate description of 3 d transition metal oxide thermochemistry

Semilocal density-functional theory (DFT) methods exhibit significant errors for the phase diagrams of transition-metal oxides that are caused by an incorrect description of molecular oxygen and the large self-interaction error in materials with strongly localized electronic orbitals. Empirical and semiempirical corrections based on the DFT + U method can reduce these errors, but the parameterization and validation of the correction terms remains an on-going challenge. Here we develop a systematic methodology to determine the parameters and to statistically assess the results by considering interlinked thermochemical data across a set of transition metal compounds. We consider three interconnected levels of correction terms: (1) a constant oxygen binding correction, (2) Hubbard-U correction, and (3) DFT/DFT + U compatibility correction. The parameterization is expressed as a unified optimization problem. We demonstrate this approach for 3d transition metal oxides, considering a target set of binary and ternary oxides. With a total of 37 measured formation enthalpies taken from the literature, the dataset is augmented by the reaction energies of 1710 unique reactions that were derived from the formation energies by systematic enumeration. To ensure a balanced dataset across the available data, the reactions were grouped by their similarity using clustering and suitably weighted. The parameterization is validated using leave-one-out cross validation (CV), a standard technique for the validation of statistical models. We apply the methodology to the strongly constrained and appropriately normed (SCAN) density functional. Based on the CV score, the error of binary (ternary) oxide formation energies is reduced by 40% (75%) to 0.10 (0.03) eV/atom. A simplified correction scheme that does not involve SCAN/SCAN + U compatibility terms still achieves an error reduction of 30% (25%). The method and tools demonstrated here can be applied to other classes of materials or to parameterize the corrections to optimize DFT + U performance for other target physical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Spin squeezing with itinerant dipoles: A case for shallow lattices

Entangled spin squeezed states generated via dipolar interactions in lattice models provide unique opportunities for quantum enhanced sensing and are now within reach of current experiments. A critical question in this context is which parameter regimes offer the best prospects under realistic conditions. Light scattering in deep lattices can induce significant decoherence and strong Stark shifts, while shallow lattices face motional decoherence as a fundamental obstacle. Here we analyze the interplay between motion and spin squeezing in itinerant fermionic dipoles in one dimensional chains using exact matrix product state simulations. We demonstrate that shallow lattices can achieve more than 5 dB of squeezing, outperforming deep lattices by up to more than 3 dB, even in the presence of low filling, loss, and decoherence. We relate this finding to SU(2)-symmetric superexchange interactions, which keep spins aligned and protect collective correlations. We show that the optimal regime is achieved for small repulsive off-site interactions, with a trade-off between maximal squeezing and optimal squeezing time. Published by the American Physical Society 2024

Wellnitz, David (ORCID:0000000349788938)↗
DOE OSTI2021

Global minimization via classical tunneling assisted by collective force field formation

Simple elements interacting in networks can give rise to intricate emergent behaviors. Examples such as synchronization and phase transitions often apply in many contexts, as many different systems may reduce to the same effective model. Here, we demonstrate such a behavior in a model inspired by memristors. When weakly driven, the system is described by movement in an effective potential, but when strongly driven, instabilities cause escapes from local minima, which can be interpreted as an unstable tunneling mechanism. We dub this collective and nonperturbative effect a “Lyapunov force,” which steers the system toward the global minimum of the potential function, even if the full system has a constellation of equilibrium points growing exponentially with the system size. This mechanism is appealing for its physical relevance in nanoscale physics and for its possible applications in optimization, Monte Carlo schemes, and machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Basin-scale biogeography of marine phytoplankton reflects cellular-scale optimization of metabolism and physiology

Extensive microdiversity within Prochlorococcus, the most abundant marine cyanobacterium, occurs at scales from a single droplet of seawater to ocean basins. To interpret the structuring role of variations in genetic potential, as well as metabolic and physiological acclimation, we developed a mechanistic constraint-based modeling framework that incorporates the full suite of genes, proteins, metabolic reactions, pigments, and biochemical compositions of 69 sequenced isolates spanning the Prochlorococcus pangenome. Optimizing each strain to the local, observed physical and chemical environment along an Atlantic Ocean transect, we predicted variations in strain-specific patterns of growth rate, metabolic configuration, and physiological state, defining subtle niche subspaces directly attributable to differences in their encoded metabolic potential. Predicted growth rates covaried with observed ecotype abundances, affirming their significance as a measure of fitness and inferring a nonlinear density dependence of mortality. Our study demonstrates the potential to interpret global-scale ecosystem organization in terms of cellular-scale processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Spatio-temporally shaped deep UV laser source for ultrabright photocathodes using novel upconversion techniques (Final Report)

The goal of this project was to take a VUV laser system designed by Kapteyn-Murnane Labs (KMLabs)—the Hyperion VUV, and increase its functionality, efficiency, and applicability by further probing the fundamental physics taking place in the system and optimizing the system performance. More specifically, DOE accelerator applications—particularly for XFELs that require low-emittance electron beams, require precisely controlled ultrashort pulses in the deep-UV at 250-260 nm to drive the photocathode electron source. This is conventionally done using an ultrafast infrared laser, with subsequent stages of nonlinear upconversion in solid-state nonlinear-optical crystal media (principally BBO, which is commonly used for UV upconversion). However, maintaining high spatial mode beam quality, as well as precisely controlled temporal profile, has proven a persistent challenge. As a possible alternative to this approach, KMLabs has demonstrated a system that generates vacuum ultraviolet light (VUV) by upconverting pulses from an infrared ultrafast laser in a gas-filled hollow waveguide, driving a process of highly cascaded harmonic generation (HCHG). Because HCHG upconversion is done in a gas, rather than a solid, at high intensity in a guided-wave geometry, it retains an excellent beam spatial profile as well as a large spectral bandwidth that allows for control over the temperal structure of the pulse. A challenge, however, is in energy scaling of this HCHG technique to the ~1-20 μJ pulses required for photocathode applications. To-date, the pulse energies used in published HCHG work are sub-10-nJ. This project proposed to explore ways to generate higher-energy pulses using HCHG, as well as to investigate spectral and temporal shaping of the deep UV pulses by pulse shaping the infrared laser used to seed the process. Although we showed that our approach works for generating light at 259 nm, the total pulse energy achieved seems limited to approximately the same value as past work. However, the techniques we investigated may well have benefits for extending this source to much shorter wavelength output.

43 PARTICLE ACCELERATORS↗