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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 127 records · Page 7

EMT Model Validation of a 2 MVA PV Inverter Using Transient and Frequency-Domain Hardware Testing: Preprint

This paper presents results and new insights gained from a hardware test campaign on a 2 MVA PV inverter for validating its vendor-supplied EMT model. The test campaign was conducted using a 7 MVA grid simulator and a 2 MW PV emulator. It considered both time-domain transient tests and frequency-domain impedance scan tests. The paper highlights the inadequacy of transient tests in capturing all critical resonance modes of the inverter, and the effectiveness of the frequency scan testing in addressing this problem. The paper shows the frequency scan testing as an effective tool for EMT model validation of IBR units which can highlight inaccuracies in the EMT models that are easy to overlook when model validation is performed using only the time-domain transient tests such as voltage ride-through and phase jump tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Investigation of competitive sorption and plasticization of hyperaged CANAL ladder polymers for acid gas purification

Identifying membrane materials that have exceptional separation performance and stability to complex CO 2 -containing mixtures is a pressing topic in separation science. In this work, the membrane separation performance for a recently discovered class of contorted polymers synthesized via catalytic arene-norbornene annulation (CANAL) polymerization is presented. These CANAL polymers achieve high CO 2 /CH 4 selectivity of 68 after physical aging (up to ∼1 year), which significantly augments the size-sieving capabilities of the membranes. Binary CO 2 /CH 4 and ternary H 2 S/CO 2 /CH 4 testing result in a 41 % and 50 % enhancement in selectivities, respectively, for hyperaged (∼1 year) contorted CANAL polymers, highlighting their size-sieving capabilities. The remarkably high CO 2 /CH 4 mixed-gas and combined acid gas (CAG, (CO 2 +H 2 S)/CH 4 ) selectivities of 88 and 95, respectively, for CANAL-Me-S 5 F in particular surpass both the 2018 CO 2 /CH 4 mixed-gas and CAG upper bounds. Performance stability was also investigated for high concentrations of CO 2 , revealing a reduction in CO 2 /CH 4 mixed-gas selectivity without compromising CO 2 permeability, suggesting strong sorption of CO 2 but minimal plasticization effects for short testing periods. In addition, time-dependent plasticization shows negligible effects on CO 2 /CH 4 mixed-gas selectivity despite an increase in CO 2 permeability when exposed to high concentrations of plasticizing CO 2 over an extended period of 170 h. This study provides valuable insights into hyperaged CANAL polymers and their performance in practical industrial processes.

03 NATURAL GAS↗

Effects of Strain Gauge Coatings on Water Intrusion in Submerged Composite Coupon Testing

Marine energy structures are typically made using composite materials and are repeatedly loaded by currents and waves. Submersion and repeated loading lead to two environmental effects: moisture intrusion and mechanical fatigue. To understand their combined effects, submerged fatigue testing can be used. Submerged fatigue testing often requires submerged instrumentation to validate component manufacturing methods and models. Strain measurements are critical for understanding marine energy component loads. One common method for measuring strain is by using foil strain gauges, but the durability of strain gauges in submerged fatigue conditions is not well-understood. To increase strain gauge durability and protection from contamination, delamination, and water intrusion, strain gauge coatings may be applied over strain gauges and wire connections. In this study, strain gauges were adhered to composite coupons, coated, and mechanically tested in a water tank. Cycles to composite failure, cycles to strain gauge failure (SGF), strains, and SGF modes were used to measure the effects of strain gauge coatings on composite fatigue life and strain gauge durability. The coatings did not have significant effects on composite fatigue life or strain gauge durability. The methods developed and measurements taken at the coupon scale in this study will be used to inform methods and designs for subsequent submerged subcomponent testing, full-scale testing, and standards development. The benefits of designing marine energy structures to informed standards and designs are decreased lifetime costs and increased reliability and energy production, ultimately leading to a sustainable and low-carbon energy system.

composite materials↗

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING↗

Forecast for a growth-rate measurement using peculiar velocities from LSST supernovae

We investigate whether the cosmic growth-rate parameter fσ 8 can be measured using peculiar velocities (PVs) derived from type Ia supernovae (SNe Ia) in the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST). We produced simulations of different SN types using a realistic LSST observing strategy that incorporated noise, a photometric detection from the difference-image analysis (DIA) pipeline, and a PV field modeled from the Uchuu universe machine simulations. We tested three different observational scenarios that ranged from ideal conditions with spectroscopic host galaxy redshifts and spectroscopic SN typing to realistic photometric typing that resulted in a contamination with non-Ia SNe. Using a maximum likelihood technique, we showed that the LSST can measure fσ 8 with a precision of 10% in the redshift range 0.02 < z < 0.14 for our most realistic scenario. In three tomographic bins, the LSST will be able to constrain the growth-rate parameter with errors below 18% up to redshift z = 0.14. We also tested the contamination effect on the maximum likelihood method and found that for a contamination fraction below ∼2%, we recovered unbiased measurements. The results of this analysis highlight that the LSST SN sample is expected to complement traditional redshift-space distortion measurements at high redshift. This will provide a novel avenue for testing general relativity and different dark energy models.

Rosselli, D↗

Recent Advances in Pipeline Integrity for Transporting Blended Hydrogen-Natural Gas

To achieve US decarbonization goals, hydrogen is being considered as an alternative energy source to reduce carbon emissions. Blending hydrogen into existing natural gas pipelines is an intuitive first step to enable near term emission reductions. However, there are numerous challenges and uncertainties that complicate the transition to transporting hydrogen long-distance through existing natural gas pipelines. The main challenge is hydrogen embrittlement (HE), which reduces the ductility, fracture toughness and fatigue resistance of pipeline steels. This work delivers a technical review on HE effects on the material properties of pipeline carbon steels, such as Grade B, X52, X65, X70, X80, and X100. An important aspect of laboratory tests to capture the HE effect is the hydrogen test environment. This includes hydrogen pre-charged specimens tested in air and specimens tested in a hydrogen gas environment. A review of the mechanical properties of pipeline steel in different hydrogen environments determined through tensile testing is given first, which includes HE effects on yield strength, ultimate tensile strength, and ductility for blended hydrogen-natural gas pipelines. Then, the HE effects on fracture toughness and fatigue crack growth resistance are discussed. Last, impacts of HE to pipeline integrity and major technical challenges are discussed.

: Hydrogen Embrittlement↗

Holistic Microstructure Control Strategies in Photopolymerization‐Induced Phase Separation of Acrylate Systems

Open porous materials, known for their large surface area and interconnected structures, are essential in various applications, including batteries, ion exchange, catalysis, filtration, and electronic waste recycling. A critical aspect of the functionality of porous membranes is the precise control of pore size and morphology. Photopolymerization-induced phase separation (photo-PIPS) offers a convenient and versatile methods for creating porous structures. However, controlling the porous morphology remains challenging due to the complex interplay between thermodynamics, polymerization kinetics, and monomer structures, which makes it difficult to establish the relationship between processing conditions and resulting morphology in photo-PIPS. Herein, a physics-based phase-field model capable of generating and characterizing the microstructures of porous materials based on both average and localized features is developed. Using the phase-field simulations as test bed, the effects of polarity, light intensity, and curing temperature, as well as the previously unexplored roles of chain transfer agents and substrates, on the morphology of the resulting porous microstructure are investigated. Experiments are performed to verify the results predicted by the simulations. This work lays out a comprehensive guide for designing PIPS-derived porous microstructures and offers practical engineering strategies for tailoring microstructure-level topology and size of pores for application-specific needs.

36 MATERIALS SCIENCE↗

Moisture-mineral interactions drive bacterial and organic matter turnover in glacier-sourced riparian sediments undergoing pedogenesis

Glacial recession is occurring at unprecedented rates resulting in increased sediment accumula-tions in some riverine ecosystems. Increased sediment deposition has implications for ecosystem stability (e.g., floods and river paths) and environmental services (e.g., carbon sequestration). Soils and sediments have an enormous potential to retain carbon (C), predominantly due to sorp-tion to mineral surfaces. However, C persistence may be sensitive to climate-change induced temperature and moisture variations. We coupled ultrahigh resolution organic matter composition classification with bacterial characterization and respiration measurements to test the combined effects of temperature (4 vs 20°C) and moisture (50 vs 100% water-filled pore space) on C turn-over in sediments maintained under different mineralogical conditions (illite-amended vs non-amended). Here we show that the inhibition of CO 2 emissions from the combined effect of in-creased moisture content and illite was reflected in the turnover of key molecular signatures, such as the nominal oxidation state of C, often irrespective of temperature. However, shifts in bacteri-al communities from a coupled moisture-mineral interaction, were temperature-dependent. Our results highlight the importance of moisture in driving mineral-organic interactions and suggest that C in clay-rich, water-saturated sediments is both thermodynamically unfavorable and miner-al-protected from microbial consumption.

58 GEOSCIENCES↗

Determining the Reaction Kinetics and Thermodynamics of a Diels–Alder Network Using Dynamic Gel Criteria

We undertook a detailed rheological investigation to evaluate the kinetic parameters of the forward and reverse Diels–Alder (DA) reactions of a model network cross-linked using a furan prepolymer and a common aromatic bismaleimide. At high temperature where the Winter–Chambon’s criterion of frequency-independence was more applicable, a multiwave technique permitted van’t Hoff analysis and calculation of the reaction thermodynamic parameters, specifically the enthalpy and entropy of the reaction: ΔH° = –38.3 ± 5.2 kJ mol –1 and ΔS° = –94.3 ± 13.4 J mol –1 . At mild temperatures where the G'–G" crossover point is experimentally convenient to measure gelation, isothermal tests were used to obtain reasonable fDA kinetic parameters from Eyring analysis such as the apparent activation enthalpy and entropy of ΔH$^{‡}_{fDA}$ = 76.8 ± 6.9 kJ mol –1 and ΔS$^{‡}_{fDA}$= –82.8 ± 22.2 J mol –1 K –1 . Comparable rheokinetic methods include cross-linking density measurements and stress relaxation tests to calculate effective kinetics, whereas the critical gel conversion was consistently applied here. As a result, rate data are fitted with the Arrhenius equation for comparison purposes and the Eyring equation to demonstrate its broader utility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Conformational Control as a Design Strategy to Tune the Redox Behavior of Benzotriazole Negolytes for Nonaqueous Flow Batteries

Here, we present a molecular engineering strategy to tune the reduction potentials of benzotriazole derivatives as high-energy-density negolytes in nonaqueous redox flow batteries. Within nonaqueous electrolytes, these derivatives, notably 2-(o-tolyl)-2H-benzo[d][1,2,3]triazole (1), demonstrate a theoretical capacity of up to 93.8 Ah L⁻¹ and a reduction potential of –2.35 V vs ferrocene/ferrocenium (Fc/Fc⁺). Introducing dimethyl substitution (i.e., 2-(2,6-dimethylphenyl)-2H-benzo[d][1,2,3]triazole (4)) shifts the reduction potential even more negatively to –2.55 V vs Fc/Fc⁺. We ascribe the nonlinear effect of dimethyl substitution on reduction potential to ground-state conformational effects. Flow battery tests with negolyte 1 and ferrocene posolyte demonstrated >90% Coulombic efficiency at 6.7 mA cm⁻² with improved cyclability in the presence of lithium bis(trifluoromethylsuylfonyl)imide supporting salt.

25 ENERGY STORAGE↗

Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models

Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.

36 MATERIALS SCIENCE↗

Probing fundamental constant oscillation in the Galactic Center with S-Star Spectroscopy

Astrophysical spectroscopy provides a powerful probe of spacetime variations of fundamental constants, as atomic and ionic emission and absorption lines depend sensitively on the fine-structure constant. In particular, coherent temporal oscillations induced by an ultralight scalar background produce characteristic, time-resolved signatures that can be robustly disentangled from intrinsic variability. In the Galactic Center, such scalar backgrounds can be substantially enhanced, either through the formation of dense scalar clouds powered by black hole rotational energy extraction or as ultralight scalar dark matter forming a soliton-like core. These scalar configurations generically induce oscillations of the fine-structure constant, with periods set by the scalar mass and spatial profiles determined by the scalar wavefunction and its coupling to the electromagnetic sector. We show that precise, time-resolved spectroscopy of S-stars orbiting the supermassive black hole Sgr A^* provides a sensitive test of these effects, enabling constraints on quadratic scalar-photon couplings in the exceptionally high boson-density environment of the Galactic Center.

Bai, Zhaoyu [Weizmann Inst.] (ORCID:00000002075815↗

𝑁 = 8 Shell Breaking in 12 Be from a Single-Particle Perspective

Experimental observations of the low-lying states in 12 Be and their accurate modeling play an essential role in understanding the disappearance of the 𝑁 = 8 magic number. Long-standing experimental ambiguities have been clarified using an one-neutron adding (𝑑, 𝑝) reaction on 11 Be using the ISOLDE Solenoidal Spectrometer at CERN’s HIE-ISOLDE facility. The single-particle energies of 1⁢𝑠 1/2 , 0⁢𝑑 5/2 , and 0⁢𝑝 1/2 orbitals in 12 Be have been determined from the extracted spectroscopic factors. A significant reduction between the separation of 1⁢𝑠 1/2 and 0⁢𝑝 1/2 orbitals is found in comparison with the carbon isotones, highlighting the breakdown of the 𝑁 = 8 shell. These observations serve as an important test of different effects incorporated in theoretical models. It is found that two synergistic mechanisms, core deformation and weak binding, are responsible for the 𝑁 = 8 shell breaking and the exotic near-threshold phenomena observed in 12 Be, including the narrow unnatural-parity resonance $0^{-}_1$ and the possible halolike nature of the $0^+_2$ isomer.

Chen, Jie [Southern University of Science and Tech↗

Test of the Gravitational Force Law on Cosmological Scales Using the Kinematic Sunyaev-Zeldovich Effect

The mean pairwise velocity of massive halos reflects the gravitational force law on cosmic scales. For this work, we combine cosmic microwave background intensity maps from the Atacama Cosmology Telescope and a galaxy catalog from the Sloan Digital Sky Survey to estimate the mean pairwise velocity using the kinematic Sunyaev-Zeldovich (kSZ) effect. On scales from 30 to 230 megaparsecs, we constrain the gravitational acceleration between pairs of halos at separation 𝑟 to be 𝑔 ∝ 1/𝑟 𝑛 with 𝑛 = 2.1 ± 0.3, which is consistent with Newtonian gravity in an expanding spacetime (i.e., the standard Λ⁢ CDM model). This constraint shows agreement with an inverse quadratic radial dependence over the large distances separating galaxy halos, as expected in standard cosmology. Upcoming surveys have the potential to rule out 𝑛 = 1 at 10⁢𝜎 significance. Our results establish the kSZ effect as a powerful tool for testing gravity on cosmological scales.

alternative gravity theories↗

Adaptive Dynamic Digital Twin for Test Scenario Generation

Vehicle testing has been an important part in the development of both highly automated vehicles (HAV) and advanced driving assistant systems (ADAS). Obtaining a good representation of the Vehicle Under Test (VUT) is crucial for test scenario library generation (TSLG). Current vehicle testing methods often involve calibrating car-following models using vehicle trajectory data to create static representations that cannot be dynamically updated. For instance, when multiple vehicle trajectories are collected, it is difficult to automatically determine whether a new trajectory improves the model's representativeness or degrades its accuracy. In this paper, we introduce a dynamically updated digital twin modeling framework featuring an adaptive mechanism that evaluates new trajectory data. This mechanism can decide whether to incorporate newly collected data into the current model or create a separate digital twin model when the trajectory significantly differs from prior data. Vehicle location, speed, and acceleration extracted from the newly collected trajectory data are used to support the dynamic update decision. By integrating this digital twin model into the test library generation process, we demonstrate its ability to assist in generating test libraries while effectively handling newly collected data.

Chen, Hanlin [ORNL] (ORCID:0000000165087715)↗

Resilience Assessment for Distribution Systems during Hurricanes: A Learning-Based Framework

This paper presents a proactive strategy for hurricane-resilient distribution systems. It proposes a Bayesian Neural Network-based outage prediction model considering various parameters, including electrical components, and weather and environmental factors. Addressing challenges in imbalanced outage datasets, a Bias-Variance Tradeoff method is proposed. A resilience assessment model quantifies resilience indices, providing insights into system weaknesses. The approach identifies weak points and serves as a planning benchmark. Numerical results on the modified IEEE 123-node test system demonstrate effectiveness in realistic hurricane scenarios.

Vahedi, Soroush↗

Impacts of floating-point non-associativity on reproducibility for HPC and deep learning applications

Run to run variability in parallel programs caused by floating-point non-associativity has been known to significantly affect reproducibility in iterative algorithms, due to accumulating errors. Non-reproducibility can critically affect the efficiency and effectiveness of correctness testing for stochastic programs. Recently, the sensitivity of deep learning training and inference pipelines to floating-point non-associativity has been found to sometimes be extreme. It can prevent certification for commercial applications, accurate assessment of robustness and sensitivity, and bug detection. New approaches in scientific computing applications have coupled deep learning models with high-performance computing, leading to an aggravation of debugging and testing challenges. Here we perform an investigation of the statistical properties of floating-point non-associativity within modern parallel programming models, and analyze performance and productivity impacts of replacing atomic operations with deterministic alternatives on GPUs. We examine the recently-added deterministic options in PyTorch within the context of GPU deployment for deep learning, uncovering and quantifying the impacts of input parameters triggering run to run variability and reporting on the reliability and completeness of the documentation. Finally, we evaluate the strategy of exploiting automatic determinism that could be provided by deterministic hardware, using the Groq LPUTM accelerator for inference portions of the deep learning pipeline. We demonstrate the benefits that a hardware-based strategy can provide within reproducibility and correctness efforts.

Shanmugavelu, Sanjif↗

Robust Iterative Method for Symmetric Quantum Signal Processing in All Parameter Regimes

Here, this paper addresses the problem of solving nonlinear systems in the context of symmetric quantum signal processing (QSP), a powerful technique for implementing matrix functions on quantum computers. Symmetric QSP focuses on representing target polynomials as products of matrices in SU(2) that possess symmetry properties. We present a novel Newton’s method tailored for efficiently solving the nonlinear system involved in determining the phase factors within the symmetric QSP framework. Our method demonstrates rapid and robust convergence in all parameter regimes, including the challenging scenario with ill-conditioned Jacobian matrices, using standard double precision arithmetic operations. For instance, solving symmetric QSP for a highly oscillatory target function α cos(1000x) (polynomial degree ≈ 1433) takes 6 iterations to converge to machine precision when α = 0.9, and the number of iterations only increases to 18 iterations when α = 1 – 10 -9 with a highly ill-conditioned Jacobian matrix. Leveraging the matrix product state structure of symmetric QSP, the computation of the Jacobian matrix incurs a computational cost comparable to a single function evaluation. Moreover, we introduce a reformulation of symmetric QSP using real-number arithmetics, further enhancing the method’s efficiency. Extensive numerical tests validate the effectiveness and robustness of our approach, which has been implemented in the QSPPACK software package.

97 MATHEMATICS AND COMPUTING↗