Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “dependence analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,171 records · Page 65

Coexistence of unconventional spin Hall effect and antisymmetric planar Hall effect in IrO 2

Crystal symmetry plays an important role in the Hall effects. Unconventional spin Hall effect (USHE), characterized by Dresselhaus and out-of-plane spins, has been observed in materials with low crystal symmetry. Recently, antisymmetric planar Hall effect (APHE) was discovered in rutile RuO 2 and IrO 2 (101) thin films, which also exhibit low crystal symmetry. In this study, we report the observation of both USHE and APHE in IrO 2 (111) films, using spin-torque ferromagnetic resonance and harmonic Hall measurements, respectively. Notably, the unconventional spin-torque efficiency from Dresselhaus spin was more than double that of a previous report. Additionally, the temperature dependence of APHE suggests that it arises from the Lorentz force, constrained by crystal symmetry. Here, symmetry analysis supports the coexistence of USHE and APHE and demonstrates that both originate from the crystal symmetry of IrO 2 (111), paving the way for a deeper understanding of Hall effects and related physical phenomena.

Crystal structure↗

A Divergent Clade KAI2 Protein in the Root Parasitic Plant Orobanche minor Is a Highly Sensitive Strigolactone Receptor and Is Involved in the Perception of Sesquiterpene Lactones

Abstract Strigolactones (SLs) were initially discovered as germination inducers for root parasitic plants. In 2015, three groups independently reported the characterization of the SL receptor in the root parasitic plant Striga hermonthica, which causes significant damage to crop production, particularly in sub-Saharan Africa. The characterized receptors belong to HYPOSENSITIVE TO LIGHT/KARRIKIN INSENSITIVE2 (HTL/KAI2), which is a member of the α/β-hydrolase protein superfamily. In non-parasitic plants, HTL/KAI2 perceives the smoke-derived germination inducer karrikin and a yet-unidentified endogenous ligand. However, root parasitic plants evolved a specific clade of HTL/KAI2 that has diverged from the KAI2 clade of non-parasitic plants. The S. hermonthica SL receptors are included in this specific clade, which is called KAI2 divergent (KAI2d). Orobanche minor is an obligate root holoparasitic plant that grows completely dependent on the host for water and nutrients because of a lack of photosynthetic ability. Previous phylogenetic analysis of KAI2 proteins in O. minor has demonstrated the presence of at least five KAI2d clade genes. Here, we report that KAI2d3 and KAI2d4 in O. minor have the ability to act as the SL receptors. They directly interact with SLs in vitro, and when expressed in Arabidopsis, they rescue thermo-inhibited germination in response to the synthetic SL analog GR24. In particular, KAI2d3 showed high sensitivity to GR24 when expressed in Arabidopsis, suggesting that this receptor enables highly sensitive SL recognition in O. minor. Furthermore, we provide evidence that these KAI2d receptors are involved in the perception of sesquiterpene lactones, non-strigolactone-type germination inducers.

Cell Biology↗

Neutron scattering study of magnetic anisotropy in the tetragonal antiferromagnet Bi 2 CuO 4

In this work, we present a comprehensive study of magnon excitations in the tetragonal easy-plane antiferromagnet Bi 2 CuO 4 using inelastic neutron scattering and spin-wave analyses. The nature of low-energy magnons, and hence the anisotropy in this material, has been controversial. We show unambiguously that the low-energy magnon spectrum consists of a gapped and a gapless mode, which we attribute to out-of-plane and in-plane spin fluctuations, respectively. We modeled the observed magnon spectrum using linear spin-wave analysis of a minimal anisotropic spin model motivated by the lattice symmetry. By studying the magnetic field dependence of the (1,0,0) Bragg peak intensity and the in-plane magnon intensity, we observed a spin-flop transition in the ab plane at ~0.4 T, which directly indicates the existence of a small in-plane anisotropy that is classically forbidden. It is only by taking into account magnon zero-point fluctuations beyond the linear spin-wave approximation that we could explain this in-plane anisotropy and its magnitude, the latter of which is deduced from the critical field of the spin-flop transition. The microscopic origins of the observed anisotropic interactions are also discussed. We found that our data are inconsistent with a large Dzyaloshinskii-Moriya interaction, which suggests a potential departure of Bi 2 CuO 4 from the conventional theories of magnetic anisotropy for other cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Magnetic field-temperature phase diagram of the spin-$\frac{1}{2}$ triangular lattice antiferromagnet KYbSe 2

A quantum spin liquid (QSL) is a state of matter characterized by fractionalized quasiparticle excitations, quantum entanglement, and a lack of long-range magnetic order. However, QSLs have evaded definitive experimental observation. Several Yb 3+ -based triangular lattice antiferromagnets with effective 𝑆 = $\frac{1}{2}$ have been suggested to stabilize the QSL state as the ground state. Here, in this work, we build a comprehensive magnetic temperature phase diagram of a high-quality single crystalline KYbSe 2 via heat capacity and magnetocaloric effect down to 30 mK with magnetic field applied along the 𝑎 axis. At zero magnetic field, we observe the magnetic long-range order at 𝑇 N =0.29 K entering 120 degrees ordered state in heat capacity, consistent with neutron scattering studies. Analysis of the low-temperature (𝑇) specific heat (𝐶) at zero magnetic field indicates linear 𝑇 dependence of 𝐶/𝑇 and a broad hump of 𝐶/𝑇 in the proximate QSL region above 𝑇 N . By applying magnetic field, we observe the up-up-down phase with 1/3 magnetization plateau and oblique phases, in addition to two new phases. These observations strongly indicate that while KYbSe 2 closely exhibits characteristics resembling an ideal triangular lattice, deviations may exist, such as the effect of the next-nearest-neighbor exchange interaction, calling for careful consideration for spin Hamiltonian modeling. Further investigations into tuning parameters, such as chemical pressure, could potentially induce an intriguing QSL phase in the material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Informing nuclear physics via machine learning methods with differential and integral experiments

Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quasiclassical evaluation of gluon saturation induced helicity effects

At sub-eikonal order in the high-energy limit, helicity dependences are generally contained in the transverse components of the gluon field. In the gluon saturation regime, novel helicity effects arise from the nonlinear interaction between the eikonal-order longitudinal gluon field and the sub-eikonal-order transverse gluon field. We derive this saturation induced helicity-dependent field both by solving the classical Yang-Mills equations and through direct diagrammatic calculations. Our analysis shows that the saturation induced helicity effect is intrinsically a two-particle (or multiparticle) correlation effect, rather than a single-particle distribution effect. Furthermore, we evaluate this effect in the context of double-spin asymmetry for incoherent diffractive dijet production in longitudinally polarized electron-nucleus collisions, using a simplified helicity-extended McLerran-Venugopalan model. We find that the saturation induced helicity effect further suppresses the back-to-back peak in the dijet azimuthal angle correlation, with a magnitude comparable to that of the direct helicity effect. This gluon saturation induced helicity effect may offer a novel avenue to probe gluon saturation in polarized collisions. Published by the American Physical Society 2025

Li, Ming (ORCID:0000000195509691)↗

Sixfold Way of Traversable Wormholes in the Sachdev-Ye-Kitaev Model

In the infrared limit, a nearly anti–de Sitter spacetime in two dimensions ( AdS 2 ) perturbed by a weak double trace deformation and a two-site ( q > 2 )-body Sachdev-Ye-Kitaev (SYK) model with N Majoranas and a weak 2 r -body intersite coupling share the same near-conformal dynamics described by a traversable wormhole. We exploit this relation to propose a symmetry classification of traversable wormholes depending on N , q , and r , with q > 2 r , and confirm it by a level statistics analysis using exact diagonalization techniques. Intriguingly, a time-reversed state never results in a new state, so only six universality classes occur—A, AI, BDI, CI, C, and D—and different symmetry sectors of the model may belong to distinct universality classes. Published by the American Physical Society 2024

Physics↗

Machine learning assisted unfolding for neutrino cross-section measurements with the OmniFold technique

The choice of unfolding method for a cross-section measurement is tightly coupled to the model dependence of the efficiency correction and the overall impact of cross-section modeling uncertainties in the analysis. A key issue is the dimensionality used in unfolding, as the kinematics of all outgoing particles in an event typically affect the reconstruction performance in a neutrino detector. OmniFold is an unfolding method that iteratively reweights a simulated dataset, using machine learning to utilize arbitrarily high-dimensional information, that has previously been applied to proton-proton and proton-electron datasets. This paper demonstrates OmniFold’s application to a neutrino cross-section measurement for the first time using a public T2K near detector simulated dataset, comparing its performance with traditional approaches using a mock data study.

Machine learning↗

Physics-Based Continuum Modeling for an Aqueous Rechargeable Zn/MnO 2 Battery

This study introduces a framework for modeling the aqueous Zn/MnO 2 rechargeable battery. A reaction system and a physics-based continuum model are proposed based on two reaction types, one involving insertion and the second related to dissolution and deposition of a solid reaction product. The model, fitted to empirical data, predicts voltage behavior and capacity limitations during cycling, identifying electrolytic zinc depletion as a limiting mechanism, depending on the original cell construction. The research suggests the need for further material characterization and reaction analysis, which will advance our understanding and facilitate the development of grid-scale energy storage solutions.

Electrochemistry↗

Spatiotemporal Plasma-Particle Characterization of Dry Aerosols Using Nanosecond, Femtosecond, and Filament Laser-Produced Plasmas

The ability to rapidly characterize dry aerosols in air using laser-induced breakdown spectroscopy (LIBS) with femtosecond laser pulses promises advancement towards real-time atmospheric sampling and standoff capabilities. Of particular interest is the ability to apply LIBS in the context of low-particle loaded environments where discrete particle interactions must be observed within the sampling volume of the laser-produced plasma (LPP). In this study, dry nanoparticles in suspension are generated from a standard solution and sampled in air using Q-switched nanosecond (ns-) pulses, short-focus (SF) femtosecond (fs-) pulses, and filaments. Short time-gated plasma images are captured to observe spatially and temporally varying discrete plasma-particle interactions, which is shown to influence early air breakdown behavior and subsequent plasma evolution. Along with images, photo-multiplier tube (PMT) measurements are conducted where strong spatiotemporal dependencies are exhibited by the collected emission signal on particle proximity and plasma expansion behavior. Finally, conditional analysis is performed on LIBS measurements to determine associated sampling probabilities and filter out spectra with poor or absent emission peaks with an adaptive threshold algorithm.

42 ENGINEERING↗

Natural Language Processing for Text Based Event Extraction: Identifying Events of Interest Related to Worldwide State-Sponsored Civil Nuclear Power

Beginning in FY20, SRNL was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development to develop a prototype natural language processing/natural language understating machine learning-based modeling and analysis pipeline to extract and forecast events of interest from massive open data sources. The working hypothesis within the approach is that contextual shifts in key words and phrases act as indicators of events of interest over time. Therefore, by identifying points in time where contextual shifts occur, events of interest can be extracted along with explicit and implicit connections of entities and activities. The development of the preliminary prototype pipeline proved successful, meriting further testing of the pipeline on more broad topical domains and in a worldwide data environment. Therefore, SRNL, in collaboration with the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Tech, have continued development with a test case of identifying events of interest related to worldwide state-sponsored civil nuclear power in open data sources. In the first year of this follow-on effort, the team has curated domain-specific data corpuses using an automated scheme and applied the modeling and analysis pipeline. This robust, focused, and efficient approach consists of an ensemble of analyses applied to time dependent word embedding models that are trained on the data corpuses. In this report, the team has demonstrated the capability of the existing pipeline (as development has continued in parallel) by exploring several specific case-studies centered around Rosatom’s international activities regarding the planning, construction, operation, and/or shutdown of nuclear reactors. A basic timeline events has been generated by manually cataloging known “milestone” events that have occurred at reactors in Turkey, Finland, Hungary, and Egypt and compared with the output of the modeling pipeline. In this approach, the team has characterized the lead time using the prototype pipeline, as well as the ability to capture relevant information, which proved 100% successful. A deep dive example of the Akkuyu reactor (Turkey) is presented that shows the breadth of information that can be captured using the approach. In this case study, events were extracted pertaining to the planning/construction of Akkuyu including protests from the population, information campaigns in response to the protests, forged regulatory documents and lawsuits, budgetary/shareholder information, geopolitical tensions, and the various construction milestones. This has demonstrated the pipeline’s utility as a research aid or real-time event extraction tool, where summary-level information and detailed text extractions from millions of articles or Tweets across long time periods can be generated with significantly less effort than current techniques.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

An Assessment of Receiver Algorithms for Distributed Massive MIMO Systems: Investigating Design Solutions and Performance

This study investigates receiver design solutions for distributed Massive Multiple Input Multiple Output (D-m MIMO) systems, taking into account parameters such as number of access points as well as concerns related to channel estimates that use single-carrier frequency-domain equalization (SC-FDE). A significant contribution of this research is the integration of Low-Density Parity-Check (LDPC) codes to simplify coding complexity and enhance communication efficiency. The research examines different receiver designs, such as spatial antenna correlation and sophisticated channel estimation methods. The authors propose integrating LDPC codes into the receiver architecture to simplify computations and enhance error correction and decoding. Moreover, the paper examines performance evaluation measures and approaches, highlighting the trade-offs among complexity, spectral efficiency, and error performance. The comparative analysis indicates the benefits, in terms of performance, of incorporating LDPC codes and improving system throughput and dependability. We examine four distinct receiver algorithms: zero-forcing (ZF), minimum mean square error (MMSE), maximum ratio combining (MRC), and equal gain combining (EGC). The study shows that MRC and EGC receivers work well in D-m MIMO because they make the receiver system less computationally demanding.

Gashtasbi, Ali↗

The Radius of PSR J0740+6620 from NICER with NICER Background Estimates

We report a revised analysis for the radius, mass, and hot surface regions of the massive millisecond pulsar PSR J0740+6620, studied previously with joint fits to NICER and XMM-Newton data by Riley et al. (2021) and Miller et al. (2021). We perform a similar Bayesian estimation for the pulse-profile model parameters, except that instead of fitting simultaneously the XMM-Newton data, we use the best available NICER background estimates to constrain the number of photons detected from the source. This approach eliminates any potential issues in the cross-calibration between these two instruments, providing thus an independent check of the robustness of the analysis. The obtained neutron star parameter constraints are compatible with the already published results, with a slight dependence on how conservative the imposed background limits are. A tighter lower limit causes the inferred radius to increase, and a tighter upper limit causes it to decrease. We also extend the study of the inferred emission geometry to examine the degree of deviation from antipodality of the hot regions. We show that there is a significant offset to an antipodal spot configuration, mainly due to the non-half-cycle azimuthal separation of the two emitting spots. The offset angle from the antipode is inferred to be above 25° with 84% probability. This seems to exclude a centered-dipolar magnetic field in PSR J0740+6620.

79 ASTRONOMY AND ASTROPHYSICS↗

Fluorescent bioaerosol particle concentrations measured by the DU WIBS during the AGINSGP field experiment

Real-time, immersion mode ambient fluorescent bioaerosol concentrations were measured at ARM’s Southern Great Plains (SGP) site during the AGINSGP field experiment using a Wideband Integrated Bioaerosol Sensor (DMT Inc.; WIBS-4A). The WIBS-4A is an optical particle counter that also measures single particle fluorescence in three channels, along with particle asymmetry. Particles are grouped into different types depending on which channels they fluoresce in. The instrument was located in the guest instrument facility (GIF) and measured fluorescent particle concentrations from April 7th to April 29th. Data presented here are the concentrations for each particle type, binned in 5 minute increments. Air was drawn into the GIF through custom aluminum stack inlets (6” inner diameter) attached vertically to the outer GIF wall and the GIF outside platform. A blower pulled air through the stacks at a velocity of 1 m/s. Aerosol instruments subsampled via wall ports, through either 3/8” or 1/4" copper lines, depending on sample flow of the instrument. Particles were dried using a silica diffusion dryer prior to analysis.

54 ENVIRONMENTAL SCIENCES↗

Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma: Preprint

Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of a conceptual microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.

Cambium↗

Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma

Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.

Cambium↗

Gait Characterization and Analysis of Hereditary Amyloidosis Associated with Transthyretin Patients: A Case Series

Hereditary amyloidosis associated with transthyretin (ATTRv), is a rare autosomal dominant disease characterized by length-dependent symmetric polyneuropathy that has gait impairment as one of its consequences. The gait pattern of V30M ATTRv amyloidosis patients has been described as similar to that of diabetic neuropathy, associated with steppage, but has never been quantitatively characterized. In this study we aim to characterize the gait pattern of patients with V30M ATTRv amyloidosis, thus providing information for a better understanding and potential for supporting diagnosis and disease progression evaluation. We present a case series in which we conducted two gait analyses, 18 months apart, of five V30M ATTRv amyloidosis patients using a 12-camera, marker based, optical system as well as six force platforms. Linear kinematics, ground reaction forces, and angular kinematics results are analyzed for all patients. All patients, except one, showed a delayed toe-off in the second assessment, as well as excessive pelvic rotation, hip extension and external transverse rotation and knee flexion (in stance and swing phases), along with reduced vertical and mediolateral ground reaction forces. The described gait anomalies are not clinically quantified; thus, gait analysis may contribute to the assessment of possible disease progression along with the clinical evaluation.

Vilas-Boas, Maria do Carmo (ORCID:000000025012789X↗

Process–Property–Performance Mapping of Additively Manufactured 316H Stainless Steel Components

The Advanced Materials and Manufacturing Technologies Program is focused on accelerating the development of advanced materials and components fabricated via additive manufacturing, and is using laser powder bed fusion (LPBF) of 316H stainless steel as an initial case study. In the previous fiscal year, miniature high-throughput specimens were printed on multiple LPBF systems to provide initial processing windows to minimize porosity and limit epitaxial grain growth during prints. This fiscal year, scaled builds were completed on three different LPBF systems at ORNL: a GE Concept Laser M2, a Renishaw AM400, and an EOS M290. Builds on the Concept Laser were conducted on multiple powder lots and processing parameter ranges to provide microstructure effects on time-independent and time-dependent mechanical properties. Builds on the Renishaw were produced using Oak Ridge National Laboratory (ORNL)-optimized printing parameters and Argonne National Laboratory (ANL)-optimized printing parameters to compare outcomes of parallel process optimization efforts at different national laboratories on the same LPBF system. Similarly, the build completed on the EOS M290 replicated the processing parameters of builds completed at Los Alamos National Laboratory (LANL). Optical microscopy and electron backscatter diffraction characterization was completed on all builds. In addition to the general round robin characterization, this work-package generated time-independent data, including tensile and fracture toughness test data on scaled Concept Laser builds as a function of processing parameters and post-build heat treatment. This analysis is complimentary to work in parallel work packages aiming to establish heat treatment and processing effects on time-dependent properties. It was found that although the stress-relief heat treatment provides the highest strength at lower-temperatures, tensile strength begins to converge at higher temperatures regardless of heat treatment condition. In addition, the more rigorous solution annealing and hot-isostatic pressing post-build heat treatments result in higher fracture toughness than the stress-relieved condition. The root-causes of the lower fracture toughness of the stress-relieved LPBF 316H material was informed via a stress-relief optimization study on a scaled concept laser print, where it was found that although dislocation recovery was largely complete after only a couple hours at 650°C, the extended hold of the current 24h heat treatment employed on scaled builds likely caused increased carbide volume fractions along the LPBF 316H grain boundaries, thereby deteriorating crack propagation resistance. This trend was seen to become more deleterious with additional increases of stress-relief temperature to 750°C or 850°C. These results have helped inform a new optimal stress-relief annealing condition for LPBF 316H for future campaign testing (650°C for 2h).

36 MATERIALS SCIENCE↗