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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 1,081 records · Page 60

Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncer- tainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗

Sapphire Substrate Trenching to Advance Superconducting High-Coherence Quantum Devices

Achieving longer coherence times in superconducting qubits is essential for advancing quantum information processing and enabling scalable quantum computing. This work presents an innovative fabrication strategy focused on sapphire trenching of the substrate of superconducting high-coherence quantum devices, developed by the SQMS Nanofabrication Taskforce in collaboration with the materials characterization team. In this talk, we present a method to efficiently and consistently trench into the sapphire substrate, without compromising the surface roughness or profile of the etched sapphire. In the literature, trenching in the substrate has been shown to decrease losses, unwanted coupling and thermal stress. Sapphire’s strong covalent bonds make it harder to etch compared to silicon, yet it is more favorable for high-coherence quantum devices due to its lower dielectric losses. This innovative technique opens new possibilities for superconducting qubit fabrication: we fabricated high coherence qubit chips on sapphire substrates with trenching, to demonstrate that it will help pushing towards higher coherence times. By integrating this work with ongoing junction process optimization, design innovation, materials characterization and exploration, we outline a clear pathway toward transmon coherence times reaching millisecond scales and beyond.

Garattoni, S. [Fermilab]↗

Sapphire Substrate Trenching to Advance Superconducting High-Coherence Quantum Devices

Achieving longer coherence times in superconducting qubits is essential for advancing quantum information processing and enabling scalable quantum computing. This work presents an innovative fabrication strategy focused on sapphire trenching of the substrate of superconducting high-coherence quantum devices, developed by the SQMS Nanofabrication Taskforce in collaboration with the materials characterization team. In this talk, we present a method to efficiently and consistently trench into the sapphire substrate, without compromising the surface roughness or profile of the etched sapphire. In the literature, trenching in the substrate has been shown to decrease losses, unwanted coupling and thermal stress. Sapphire’s strong covalent bonds make it harder to etch compared to silicon, yet it is more favorable for high-coherence quantum devices due to its lower dielectric losses. This innovative technique opens new possibilities for superconducting qubit fabrication: we fabricated high coherence qubit chips on sapphire substrates with trenching, to demonstrate that it will help pushing towards higher coherence times. By integrating this work with ongoing junction process optimization, design innovation, materials characterization and exploration, we outline a clear pathway toward transmon coherence times reaching millisecond scales and beyond.

Garattoni, S. [Fermilab]↗

Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments

The study presented here focuses on performance characteristics and trade-offs associated with running machine-learning tasks in multi-GPU environments on both on-site cloud computing resources and commercial cloud services (Azure). Specifically, this study examines these tradeoffs by examining the performance of training and fine-tuning of transformer-based deep-learning (DL) networks on clinical notes and data, a task of critical importance in the medical domain. To this end, we perform DL-related experiments on the widely deployed NVIDIA V100 GPUs and on the newer A100 GPUs connected via NVLink or PCIe. This study analyzes the execution time of major operations to train DL models and investigate popular options to optimize each of them. We examine and present the findings on the impacts that various operations (e.g. data loading into GPUs, training, fine-tuning), optimizations, and system configurations (single vs. multi-GPU, NVLink vs. PCIe) have on the overall training performance.

Begoli, Edmon↗

Integrating Electric Vehicle Charging Infrastructure into Commercial Buildings and Mixed-Use Communities: Design, Modeling, and Control Optimization Opportunities: Preprint

This paper discusses modeling and field studies of controlled EV charging that have been performed with the goal of minimizing requirements for infrastructure upgrades, minimizing building peak demand charges, and maximizing the use of on-site generation. We present a large-scale workplace charging pilot of a demand-controlled scheduled EV charging system with over 250 active daily commuters, successfully demonstrating management of aggregate charging power to avoid new infrastructure investments, mitigate peak demand charges, and provide cost-effective workplace charging to users. In addition to understanding opportunities for demand management, integrating these controllable loads into the energy modeling process for new buildings will also be necessary. This paper then presents an example energy modeling process that evaluates the potential effects of EV charging on building load profiles and infrastructure requirements for a mixed-use community. Finally, we discuss an illustration of how EV charging can be controlled to be synergistic with other building loads and distributed generation.

buildings↗

On the memory attribution problem: A solution and case study using MPI

As parallel applications running on large–scale computing systems become increasingly memory constrained, the ability to attribute memory usage to the various components of the application is becoming increasingly important. We present the design and implementation of memnesia, a novel memory usage profiler for parallel and distributed message–passing applications. Our approach captures both application– and message–passing library–specific memory usage statistics from unmodified binaries dynamically linked to a message–passing communication library. Using microbenchmarks and proxy applications, we evaluated our profiler across three Message Passing Interface (MPI) implementations and two hardware platforms. Furthermore, the results show that our approach and the corresponding implementation can accurately quantify memory resource usage as a function of time, scale, communication workload, and software or hardware system architecture, clearly distinguishing between application and MPI library memory usage at a per–process level. With this new capability, we show that job size, communication workload, and hardware/software architecture influence peak runtime memory usage. In practice, this tool provides a potentially valuable source of information for application developers seeking to measure and optimize memory usage.

97 MATHEMATICS AND COMPUTING↗

Neural net modeling of equilibria in NSTX-U

Neural networks (NNs) offer a path towards synthesizing and interpreting data on faster timescales than traditional physics-informed computational models. In this work we develop two NNs relevant to equilibrium and shape control modeling, which are part of a suite of tools being developed for the National Spherical Torus Experiment-Upgrade for fast prediction, optimization, and visualization of plasma scenarios. The networks include Eqnet, a free-boundary equilibrium solver trained on the EFIT01 (Equilibrium FITtting 01) reconstruction algorithm, and Pertnet, which is trained on the Gspert code and predicts the non-rigid plasma response, a nonlinear term that arises in shape control modeling. The NNs are trained with different combinations of inputs and outputs in order to offer flexibility in use cases. In particular, Eqnet can use magnetic diagnostics as inputs and act as an EFIT-like reconstruction algorithm, or, by using pressure and current profile information the NN can act as a forward Grad–Shafranov equilibrium solver. This forward-mode version is envisioned to be implemented in the suite of tools for simulation of plasma scenarios. The reconstruction-mode version gives some performance improvements compared to the online reconstruction code real-time EFIT, especially when vessel eddy currents are significant. Here, we report strong performance for all NNs indicating that the models could reliably be used within closed-loop simulations or other applications. Some limitations are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hybrid time–frequency domain dual-probe coherent anti-Stokes Raman scattering for simultaneous temperature and pressure measurements in compressible flows via spectral fitting

We demonstrate a hybrid time–frequency spectroscopic method for simultaneous temperature/pressure measurements in nonreacting compressible flows with known gas composition. Hybrid femtosecond–picosecond, pure-rotational coherent anti-Stokes Raman scattering (CARS), with two independent, time-delayed probe pulses, is deployed for single-laser-shot measurements of temperature and pressure profiles along an ∼ <#comment/> 5 -mm line. The theory of dual-probe CARS is presented, along with a discussion of the iterative fitting of experimental spectra. Temperature is obtained from spectra acquired with an early, near-collision-free probe time delay ( τ <#comment/> 1 = 0 p s ) and pressure from spectra obtained at probe delays of τ <#comment/> 2 = 150 − <#comment/> 1000 p s , where collisions significantly impact the spectral profile. Unique solutions for temperature and pressure are obtained by iteratively fitting the two spectra to account for small collisional effects observed for the near zero probe delay spectrum. A dual-probe pure-rotational CARS system, in a 1D line-imaging configuration, is developed to demonstrate effectively the simultaneous temperature and pressure profiles recorded along the axial centerline of a highly underexpanded jet. The underexpanded air jet permits evaluation of this hybrid time–frequency domain approach for temperature and pressure measurements across a wide range of low-temperature–low-pressure conditions of interest in supersonic ground-test facilities. Single-laser-shot measurement precisions in both quantities and pressure measurement accuracy are systematically evaluated in the quiet zone upstream of the Mach disk. Precise thermometry approaching 1%−2% is observed in regions of high CARS signal-to-noise ratios. Pressure measurements are optimized at probe time delays where the ratio of the late probe delay to the Raman lifetime exceeds four ( τ <#comment/> 2 / τ <#comment/> R > <#comment/> 4 ). The impact of low-temperature Raman linewidths on CARS pressure measurements is evaluated, and comparisons of CARS pressures obtained with our recent low-temperature pure-rotational Raman linewidth data and extrapolated high-temperature Q -branch linewidths are presented. Considering all measurements with τ <#comment/> 2 / τ <#comment/> R ≥ <#comment/> 4.0 , measured pressures were on average 7.9% of the computed isentropic values with average shot-to-shot deviations representing a combination of instrument noise and fluid fluctuations of 5.0%.

Retter, Jonathan E.↗

Source apportionment of aerosols at the White River IMPROVE site near the SAIL site

This data set contains source apportionment results at the White River IMPROVE site (39.1536, -106.8209), which is about 30 km north of the Surface Atmosphere Integrated Field Laboratory (SAIL) Campaign site. The IMPROVE network (Malm et al. 1994) collected 24-hour aerosol filter samples every three days over several decades at this site. Chemical concentrations in the PM2.5 fraction of 19 elements (Al, As, Br, Ca, Cl, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Se, Si, Ti, V, and Zn), along with nitrate, sulfate, elemental carbon (EC), organic carbon (OC), and calculated coarse mass concentrations (PM10−PM2.5 mass concentrations), from 2014 to 2023, were used as input for the PMF analysis. PMF was performed using EPA PMF 5.0 (Norris et al. 2014). A five-factor solution was chosen as the optimal solution. These factors were identified as coarse dust, fine dust, biomass burning, sulfate-dominated, and nitrate-dominated sources. This data set is useful for understanding aerosol sources and their long-term variability near this region.

biomass burning↗

6-Amino-3-methylpyrimidinones as Potent, Selective, and Orally Efficacious SHP2 Inhibitors

Protein tyrosine phosphatase SHP2 is an oncoprotein associated with cancer as well as a potential immune modulator because of its role in the programmed cell death PD-L1/PD-1 pathway. In the preceding manuscript, we described the optimization of a fused, bicyclic screening hit for potency, selectivity, and physicochemical properties in order to further expand the chemical diversity of allosteric SHP2 inhibitors. In this manuscript, we describe the further expansion of our approach, morphing the fused, bicyclic system into a novel monocyclic pyrimidinone scaffold through our understanding of SAR and use of structure-based design. These studies led to the identification of SHP394 (1), an orally efficacious inhibitor of SHP2, with high lipophilic efficiency, improved potency, and enhanced pharmacokinetic properties. We also report other pyrimidinone analogues with favorable pharmacokinetic and potency profiles. Overall, this work improves upon our previously described allosteric inhibitors and exemplifies and extends the range of permissible chemical templates that inhibit SHP2 via the allosteric mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of a New Approach for Entrainment and Detrainment Rate Estimation

Entrainment and detrainment rates (ε and δ) constitute the most critical free parameters in mass flux schemes commonly employed for cumulus parameterizations. Recently, Zhu et al. (2021) introduced a new approach that utilizes aircraft observations to simultaneously estimate ε and δ for cumulus clouds, overcoming the limitation of other observation-based approaches that solely yield ε without offering insights into δ. This study aims to comprehensively evaluate the reliability of this new approach. First, evaluation using an Explicit Mixing Parcel Model demonstrates the capability of the new approach to back-calculate predetermined ε and δ based on the physical properties before and after the entrainment mixing. Second, evaluation using large-eddy simulations illustrates that the new approach yields consistent ε and δ profiles compared to the traditional approach. Sensitivity tests indicate a weak sensitivity of the estimated δ with the new approach to the entrained air source. A decrease in the proportion of cloudy air in the assumed detrained air leads to a reduction in the estimated δ, while ε remains unaffected. Finally, the most appropriate assumptions for entrained and detrained air are discussed. Estimating ε for cumulus parameterizations involves acquiring ambient air more than 500 m away from the cloud edge as entrained air. Due to implicit mean field approximations in the traditional approach, determining the optimal assumption for detrained air properties proves challenging. Finally, this study confirms the reliability of the new approach in estimating ε and δ, providing confidence in its application to extensive observational data and advancement in parameterization.

54 ENVIRONMENTAL SCIENCES↗

Dynamics of inverse metal oxides on metal catalysts using spectro-kinetics: reversible Brønsted acid site formation and irreversible reduction

Brønsted acid sites (BASs) in inverse catalysts are vital for the selective hydrogenolysis of polyols, specifically cleaving secondary C–O bonds. These BASs form dynamically in situ in an H 2 environment. While H 2 enables rapid BAS generation on short timescales, it reduces the catalyst at prolonged exposures. The active center for BAS generation, the kinetics of BAS formation, its reverse decomposition, and the irreversible oxide reduction have lacked direct experimental evidence. Here, aided by advanced spectro-kinetic studies, we identify trimeric W 3 O x sites on Pt as the active centers for BAS generation, whereas isolated WO x species on SiO 2 act merely as spectator species, demonstrated using an inverse WO x /Pt catalyst as a representative system. A detailed kinetic profile capturing the dynamics of W 3 O x sites on Pt is also established. The rate constant for BAS formation is two orders of magnitude higher than for its decomposition, which is one order of magnitude faster than the irreversible site reduction. Co-fed H 2 O suppresses the site reduction by ∼50%. Furthermore, the H 2 partial pressure plays an important role. While lower gas-phase H 2 partial pressure does not influence the reversible BAS formation, it can significantly (∼3×) suppress catalyst reduction. Finally, these findings offer critical insights into optimizing reaction conditions through periodic H 2 pulsing, enhancing catalyst stability and performance in hydrogenolysis reactions.

Sourav, Sagar [Indian Inst. of Technology (IIT), M↗

Quantifying chiral exchange interaction for Néel-type skyrmions via Lorentz transmission electron microscopy

Magnetic skyrmions are topological spin textures that have been observed in bulk magnets and magnetic multilayers. For bulk magnetic materials, their noncollinear spin profiles have often been studied by using Lorentz transmission electron microscopy (TEM). We experimentally utilized Lorentz TEM imaging to study an inversion asymmetric [Pt(1.5nm)/Co(1 nm)/W(1 nm)] 8 heterostructure that exhibits Neel-type skyrmions at zero field. By tracking the evolution of skyrmion diameters as a function of magnetic fields, we determined the strength of the interfacial Dzyaloshinskii-Moriya interaction (DMI). Our results suggest that in situ Lorentz TEM imaging combined with simulations can provide valuable quantitative information about the interfacial DMI strengths, which can be helpful for optimizing skyrmion materials. Furthermore, we show that in theory, Lorentz TEM can identify the spin chirality of Neel-type skyrmions, although an experimental verification is challenging due to the relatively low signal-to-noise ratio.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coated boron layers by boronization and a real-time boron coating using impurity powder dropper in LHD

In Large Helical Device (LHD), diborane (B 2 H 6 ) is used as a standard boron source for boronization, which is assisted by helium glow discharges. In 2019, a new Impurity Powder Dropper (IPD) system has been installed and is under evaluation as a real-time wall conditioning technique. In LHD), which is a large size heliotron device, an additional helium (He) glow discharge cleaning (GDC) after boronization has been operated for a reduction of hydrogen recycling from coated boron layers, and this operational time of 3 h was determined by spectroscopic data during glow discharges. A flat hydrogen profile is obtained on the top surface of coated boron on the specimen exposed to boronization, the result suggests a reduction of hydrogen at the top surface by He-GDC. Trapped oxygen in coated boron was obtained by boronization, and the coated boron, which has boron-oxide, on the first wall by B-IPD was also shown. Finally, considering the difference in coating areas between B 2 H 6 boronization and B-IPD operation, it would be most effective to use the IPD and B 2 H 6 boronization coating together for optimized wall conditioning.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Study of Triple Ar Gas Puff Z-Pinches on 0.9-MA, 200-ns COBRA

Ar gas puff z-pinch experiments were conducted on the 0.9 MA, 200 ns COBRA generator at Cornell University. In the experiments, a triple-nozzle gas valve was used to produce the zpinch load with concentric outer and inner gas puffs and a central gas jet. We used Planer Laser Induced Fluorescence (PLIF) to measure the initial gas profile of the load, two 4-frame 4-ns gated XUV cameras to image the imploding plasma, and filtered Photo- Conducting Diamond Detectors (PCDs) to measure the x-ray output. We have observed shock heating and/or photoionization of the dense center jet by the imploding plasma. With an outer to inner plenum pressure ratio of 1:3, de-acceleration of the imploding plasma occurred when the outer plasma shell imploded on the inner shell resulting in a stable implosion. By varying the plenum pressure for the center jet, the x-ray emission was optimized. In conclusion, an Ar K-shell x-ray (3-4 keV) yield of 77±17 J was produced at a current level of 0.87±0.2 MA and an implosion time of 200-ns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

STRESS AND DISTORTION SIMULATION OF ADDITIVE MANUFACTURING PROCESS BY HIGH PERFORMANCE COMPUTING

Numerical simulation is an efficient way to better understand the thermal and mechanical evolution during additive manufacturing (AM) and to design and optimize the process. However, with today’s computational tools, pass-by-pass thermal-mechanical numerical simulation of the AM process is extremely time-consuming. In this study, a new finite element code recently developed in house at Oak Ridge National Lab was used for additive manufacturing simulation. Our new code effectively utilizes GPU based high-performance computers to allow for realistic simulation of the transient thermal and mechanical response of materials during additive manufacturing. A benchmark study on a cylinder model by powder bed selective laser melting was carried out and distortion profile was compared to the experimental measurements. The accuracy and efficiency of the code was also demonstrated by analyzing a wire and arc additive manufacturing (WAAM) model which consists of a base plate and four deposited layers.

Huang, Hui↗

Quantum Efficiency of Gallium Nitride–Based Heterostructures with GaInN Quantum Wells

An important parameter of light-emitting heterostructures is their external quantum efficiency. However, another strict requirement for the structures used in fabricating blue and white light-emitting diodes is that the wavelength in the emission spectrum peak and its spread over the entire structure must be 460 ± 5 nm. This is explained primarily by the most frequently used white light-emitting diode design being based on crystals coated with a luminescent layer of a certain composition excited by blue emissions. Deviating from the specified spectral parameters of heterostructures strongly degrades the light and color characteristics of light-emitting diodes. In this work, we solve the problem of optimizing the design and way of growing the active region of an emitting structure consisting of a set of Ga{sub 1 – x}In{sub x}N quantum wells and wider-gap GaN barriers with a certain wavelength in the emission spectrum peak. The variation in the critical thickness of the pseudomorphic layer in the Poisson ratio ranges of 0 to 0.2 for GaAlN and 0 to 0.4 for GaInN is calculated. The emission wavelength is determined by both the bulk Ga{sub 1 – x}In{sub x}N band gap, which depends on the molar fraction of In in quantum wells, and the quantum well thickness in quantum-sized layers. It is found from the obtained dependences that to obtain the required wavelength of 460 nm in the emission spectrum peak, the Ga{sub 1 – x}In{sub x}N layers must be around 10.3% indium and have a quantum well thickness of about 2.5 nm. The effect the In distribution profile in quantum wells has on the external quantum efficiency, the uniformity of the emission wavelength distribution in the spectral peak, and the emission power distribution over the structure is considered. The best results are obtained for a trapezoidal In distribution, since it ensures the narrowest emission wavelength spread in the spectral peak and the most uniform emission power distribution over the structure. Studying the effect the number of quantum wells has on the properties of a heterostructure shows that the maximum external quantum efficiency corresponds to 4 to 5 quantum wells. The highest emission wavelength uniformity in the spectral peak over the structure is obtained at 5 to 7 quantum wells. The optimum number of quantum wells in the active region of the heterostructure is found to be 5.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗