Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “inversion methods”

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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Switchable resolution in soft x-ray tomography of single cells

The diversity of living cells, in both size and internal complexity, calls for imaging methods with adaptable spatial resolution. Soft x-ray tomography (SXT) is a three-dimensional imaging technique ideally suited to visualizing and quantifying the internal organization of single cells of varying sizes in a near-native state. The achievable resolution of the soft x-ray microscope is largely determined by the objective lens, but switching between objectives is extremely time-consuming and typically undertaken only during microscope maintenance procedures. Since the resolution of the optic is inversely proportional to the depth of focus, an optic capable of imaging the thickest cells is routinely selected. This unnecessarily limits the achievable resolution in smaller cells and eliminates the ability to obtain high-resolution images of regions of interest in larger cells. Here, we describe developments to overcome this shortfall and allow selection of microscope optics best suited to the specimen characteristics and data requirements. We demonstrate that switchable objective capability advances the flexibility of SXT to enable imaging cells ranging in size from bacteria to yeast and mammalian cells without physically modifying the microscope, and we demonstrate the use of this technology to image the same specimen with both optics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Rethinking the ill-posedness of the spectral function reconstruction — Why is it fundamentally hard and how Artificial Neural Networks can help

Reconstructing hadron spectral functions through Euclidean correlation functions are of the important missions in lattice QCD calculations. However, in a Källen–Lehmann (KL) spectral representation, the reconstruction is observed to be ill-posed in practice. It is usually ascribed to the fewer observation points compared to the number of points in the spectral function. In this paper, by solving the eigenvalue problem of continuous KL convolution, we show analytically that the ill-posedness of the inversion is fundamental and it exists even for continuous correlation functions. We discussed how to introduce regulators to alleviate the predicament, in which include the Artificial Neural Networks (ANNs) representations recently proposed by the Authors in another study. The uniqueness of solutions using ANNs representations is manifested analytically and validated numerically. Reconstructed spectral functions using different regularization schemes are also demonstrated, together with their eigen-mode decomposition. We observe that components with large eigenvalues can be reliably reconstructed by all methods, whereas those with low eigenvalues need to be constrained by regulators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A smart alarm for particle accelerator beamline operations

We present the initial results of a proof-of-concept 'smart alarm' for the Continuous Electron Beam Accelerator Facility injector beamline at Jefferson Lab. To minimize machine downtime and improve operational efficiency, an autonomous alarm system able to identify and diagnose unusual machine states is needed. Our approach leverages a trained neural network capable of alerting operators (a) when an anomalous condition exists in the beamline and (b) identifying the element setting that is the root cause. The tool is based on an inverse model that maps beamline readings (diagnostic readbacks) to settings (beamline attributes operators can modify). The model takes as input readings from the machine and computes machine settings which are compared to control setpoints. Instances where predictions differ from setpoints by a user-defined threshold are flagged as anomalous. Given data corresponding to 354 anomalous injector configurations, the model can narrow the root cause of an anomalous condition to three potential candidates with 94.6% accuracy. Furthermore, compared to the current method of identifying anomalous conditions which raises an alarm when machine parameters drift outside their normal tolerances, the data-driven model can identify 83% more anomalous conditions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Velocity Independent Constraints on Spin-Dependent DM-Nucleon Interactions from IceCube and PICO

Adopting the Standard Halo Model (SHM) of an isotropic Maxwellian velocity distribution for dark matter (DM) particles in the Galaxy, the most stringent current constraints on their spin-dependent scattering cross-section with nucleons come from the IceCube neutrino observatory and the PICO-60 $\hbox {C}_3\hbox {F}_8$ superheated bubble chamber experiments. The former is sensitive to high energy neutrinos from the self-annihilation of DM particles captured in the Sun, while the latter looks for nuclear recoil events from DM scattering off nucleons. Although slower DM particles are more likely to be captured by the Sun, the faster ones are more likely to be detected by PICO. Recent N-body simulations suggest significant deviations from the SHM for the smooth halo component of the DM, while observations hint at a dominant fraction of the local DM being in substructures. We use the method of Ferrer et al. (JCAP 1509: 052, 2015) to exploit the complementarity between the two approaches and derive conservative constraints on DM-nucleon scattering. Our results constrain $\sigma _{\mathrm{SD}} \lesssim 3 \times 10^{-39} \mathrm {cm}^2$ ($6 \times 10^{-38} \mathrm {cm}^2$) at $\gtrsim 90\%$ C.L. for a DM particle of mass 1 TeV annihilating into $\tau ^+ \tau ^-$ ($b\bar{b}$) with a local density of $\rho _{\mathrm{DM}} = 0.3~\mathrm {GeV/cm}^3$. The constraints scale inversely with $\rho _{\mathrm{DM}}$ and are independent of the DM velocity distribution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Brittle failure analysis and modeling of high-burnup PWR fuel cladding alloys

The aim of this research is the development of methods for predicting mechanical behavior and identification of limiting conditions to prevent brittle failure of high-burnup (HBU) pressure water reactor (PWR) fuel cladding alloys. A finite element (FE) model of the ring compression test (RCT) was created to analyze the failure behavior of zirconium-based alloys with radial hydrides during the RCT. An elastic-plastic material model describes the zirconium alloy. The stress-strain curve needed for the elastic-plastic material model was derived by inverse finite element analyses. Cohesive zone modeling is used to reproduce sudden load drops during RCT loading. Based on the failure mechanism in non-irradiated ZIRLO (R) claddings, a micro-mechanical model was developed that distinguishes between brittle failure along hydrides and ductile failure of the zirconium matrix. Two different cohesive laws representing these types of failure are present in the same cohesive interface. The key differences between these constitutive laws are the cohesive strength, the stress at which damage initiates, and the cohesive energy, which is the damage energy dissipated by the cohesive zone. Statistically generated matrix-hydride distributions were mapped onto the cohesive elements and simulations with focus on the first load drop were performed. Computational results are in good agreement with the RCT results conducted on high-burnup M5 (R) samples. It could be shown that crack initiation and propagation strongly depend on the specific configuration of hydrides and matrix material in the fracture area.

Simbruner, Kai↗
DOE OSTI2022

Impact of the built, social, and food environment on long‐term weight loss within a behavioral weight loss intervention

Abstract Background Behavioral weight loss interventions can lead to an average weight loss of 5%–10% of initial body weight, however there is wide individual variability in treatment response. Although built, social, and community food environments can have potential direct and indirect influences on body weight (through their influence on physical activity and energy intake), these environmental factors are rarely considered as predictors of variation in weight loss. Objective Evaluate the association between built, social, and community food environments and changes in weight, moderate‐to‐vigorous physical activity (MVPA), and dietary intake among adults who completed an 18‐month behavioral weight loss intervention. Methods Participants included 93 adults (mean ± SD; 41.5 ± 8.3 years, 34.4 ± 4.2 kg/m 2 , 82% female, 75% white). Environmental variables included urbanicity, walkability, crime, Neighborhood Deprivation Index (includes 13 social economic status factors), and density of convenience stores, grocery stores, and limited‐service restaurants at the tract level. Linear regressions examined associations between environment and changes in body weight, waist circumference (WC), MVPA (SenseWear device), and dietary intake (3‐day diet records) from baseline to 18 months. Results Grocery store density was inversely associated with change in weight ( β = −0.95; p = 0.02; R 2 = 0.062) and WC ( β = −1.23; p < 0.01; R 2 = 0.109). Participants living in tracts with lower walkability demonstrated lower baseline MVPA and greater increases in MVPA versus participants with higher walkability (interaction p = 0.03). Participants living in tracts with the most deprivation demonstrated greater increases in average daily steps ( β = 2048.27; p = 0.02; R 2 = 0.039) versus participants with the least deprivation. Limited‐service restaurant density was associated with change in % protein intake ( β = 0.39; p = 0.046; R 2 = 0.051). Conclusion Environmental factors accounted for some of the variability (<11%) in response to a behavioral weight loss intervention. Grocery store density was positively associated with weight loss at 18 months. Additional studies and/or pooled analyses, encompassing greater environmental variation, are required to further evaluate whether environment contributes to weight loss variability.

Tewahade, Selam↗
DOE OSTI2025

Machine learning for improved current-density reconstruction from two-dimensional vector magnetic images

The reconstruction of electrical current densities from magnetic field measurements is an important technique with applications in materials science, circuit design, quality control, plasma physics, and biology. Analytic reconstruction methods exist for planar currents, but break down in the presence of high-spatial-frequency noise or large standoff distance, restricting the types of systems that can be studied. Here, we demonstrate the use of a deep convolutional neural network for current density reconstruction from two-dimensional images of vector magnetic fields acquired by a quantum diamond microscope . Trained network performance significantly exceeds analytic reconstruction for data with high noise or large standoff distances. This machine learning technique can perform quality inversions on lower-signal-to-noise-ratio data, significantly reducing the data collection time and permitting reconstructions of weaker and three-dimensional current sources. Published by the American Physical Society 2025

Reed, Niko R. (ORCID:0009000305222403)↗
DOE OSTI2023

The Crystal Structure of BaZn 2 Se 2 (OH) 2 Featuring Brownmillerite‐Type Layers

Abstract A bimetallic hydroxychalcogenide, BaZn 2 Se 2 (OH) 2 , was synthesized through hydrothermal pouch methods. The single crystal X‐ray diffraction and electron diffraction indicates that the phase crystallizes in the orthorhombic space group Pnma and is composed of anionic layers [ZnSe 3/3 (OH) 1/1 ] − that are separated and charged balanced by Ba 2+ cations. The [ZnSe 3/3 (OH) 1/1 ] – layer comprises two unique Zn sites, which form interpenetrating zigzag chains with an in‐plane dipole moment and adopts a brownmillerite‐type structural motif. The adjacent layers contain tetrahedrally coordinated Zn chains of opposite handedness related by an inversion center, which cancel the microscopic dipoles to minimize the macroscopic electric polarization. The adoption of a brownmillerite structural motif in BaZn 2 Se 2 (OH) 2 can be rationalized by the distinct charge difference between Se 2− and OH − anions, which creates a sufficient dipole moment in the ZnSe 3 (OH) tetrahedra to allow the occurrence of twisted chains. FTIR spectroscopy confirms the existence of OH − anions and DFT calculations indicate that BaZn 2 Se 2 (OH) 2 is a semiconductor with a direct band gap. This work expands the chemistry of the brownmillerite family from traditional homoanionic oxides to multianion hydroxychalcogenides, offering a new opportunity to explore tunable structural complexity for better design of functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A self-consistent field formulation of excited state mean field theory

In this work, we show that, as in Hartree-Fock theory, the orbitals for excited state mean field theory can be optimized via a self-consistent one-electron equation in which electron-electron repulsion is accounted for through mean field operators. In addition to showing that this excited state ansatz is sufficiently close to a mean field product state to admit a one-electron formulation, this approach brings the orbital optimization speed to within roughly a factor of two of ground state mean field theory. The approach parallels Hartree Fock theory in multiple ways, including the presence of a commutator condition, a one-electron mean-field working equation, and acceleration via direct inversion in the iterative subspace. When combined with a configuration interaction singles Davidson solver for the excitation coefficients, the self-consistent field formulation dramatically reduces the cost of the theory compared to previous approaches based on quasi-Newton descent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Upstreamness and downstreamness in input–output analysis from local and aggregate information

Abstract Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input–output (I–O) tables. In this work, we show that an accurate estimation of the role played by sectors and countries in supply chain networks can be achieved without full knowledge of the I–O tables, but only relying on local and aggregate information, e.g., the total intermediate demand per sector. Our method, based on a rank-1 approximation to the I–O table, shows consistently good performance in reconstructing rankings (i.e., upstreamness and downstreamness measures for countries and sectors) when tested on empirical data from the world input–output database. Moreover, we connect the accuracy of our approximate framework with the spectral properties of the I–O tables, which ordinarily exhibit relatively large spectral gaps. Our approach provides a fast and analytically tractable framework to rank constituents of a complex economy without the need of matrix inversions and the knowledge of finer intersectorial details.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Coherent diffractive imaging with twisted X-rays: Principles, applications, and outlook

Recent technological breakthroughs in synchrotron and x-ray free electron laser facilities have revolutionized nanoscale structural and dynamic analyses in condensed matter systems. This review provides a comprehensive overview of the advancements in coherent scattering and diffractive imaging techniques, which are now at the forefront of exploring materials science complexities. These techniques, notably Bragg coherent diffractive imaging and x-ray photon correlation spectroscopy, x-ray magnetic dichroism, and x-ray correlation analysis leverage beam coherence to achieve volumetric three-dimensional imaging at unprecedented sub-nanometer resolutions and explore dynamic phenomena within sub-millisecond timeframes. Such capabilities are critical in understanding and developing advanced materials and technologies. Simultaneously, the emergence of chiral crystals—characterized by their unique absence of standard inversion, mirror, or other roto-inversion symmetries—presents both challenges and opportunities. These materials exhibit distinctive interactions with light, leading to phenomena such as molecular optical activity, chiral photonic waveguides, and valley-specific light emissions, which are pivotal in the burgeoning fields of photonic and spintronic devices. This review elucidates how novel x-ray probes can be leveraged to unravel these properties and their implications for future technological applications. A significant focus of this review is the exploration of new avenues in research, particularly the shift from conventional methods to more innovative approaches in studying these chiral materials. Inspired by structured optical beams, the potential of coherent scattering techniques utilizing twisted x-ray beams is examined. This promising direction not only offers higher spatial resolution but also opens the door to previously unattainable insights in materials science. By contextualizing these advancements within the broader scientific landscape and highlighting their practical applications, this review aims to chart a course for future research in this rapidly evolving field.

Physics↗
DOE OSTI2021

InversionNet3D: Efficient and Scalable Learning for 3-D Full-Waveform Inversion

Seismic full-waveform inversion (FWI) techniques aim to find a high-resolution subsurface geophysical model provided with waveform data. Some recent effort in data-driven FWI has shown some encouraging results in obtaining 2-D velocity maps. However, due to high computational complexity and large memory consumption, the reconstruction of 3-D high-resolution velocity maps via deep networks is still a great challenge. Here, in this article, we present InversionNet3D (InvNet3D), an efficient and scalable encoder–decoder network for 3-D FWI. The proposed method employs group convolution in the encoder to establish an effective hierarchy for learning information from multiple sources while cutting down unnecessary parameters and operations at the same time. The introduction of invertible layers further reduces the memory consumption of intermediate features during training and, thus, enables the development of deeper networks with more layers and higher capacity as required by different application scenarios. Experiments on the 3-D Kimberlina dataset demonstrate that InvNet3D achieves state-of-the-art reconstruction performance with lower computational cost and lower memory footprint compared to the baseline.

58 GEOSCIENCES↗
DOE OSTI2020

Hyper-Differential Sensitivity Analysis of Uncertain Parameters in PDE-Constrained Optimization

Many problems in engineering and sciences require the solution of large scale optimization constrained by partial differential equations (PDEs). Though PDE-constrained optimization is itself challenging, most applications pose additional complexity, namely, uncertain parameters in the PDEs. Uncertainty quantification (UQ) is necessary to characterize, prioritize, and study the influence of these uncertain parameters. Sensitivity analysis, a classical tool in UQ, is frequently used to study the sensitivity of a model to uncertain parameters. In this article, we introduce "hyper-differential sensitivity analysis" which considers the sensitivity of the solution of a PDE-constrained optimization problem to uncertain parameters. Our approach is a goal-oriented analysis which may be viewed as a tool to complement other UQ methods in the service of decision making and robust design. We formally define hyper-differential sensitivity indices and highlight their relationship to the existing optimization and sensitivity analysis literatures. Assuming the presence of low rank structure in the parameter space, computational efficiency is achieved by leveraging a generalized singular value decomposition in conjunction with a randomized solver which converts the computational bottleneck of the algorithm into an embarrassingly parallel loop. Two multi-physics examples, consisting of nonlinear steady state control and transient linear inversion, demonstrate efficient identification of the uncertain parameters which have the greatest influence on the optimal solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Cooling rate and dendrite spacing control in direct metal deposition printed Cu-Fe alloys

Over the last several decades, additive manufacturing (AM) has been primarily used for rapid prototyping or to create novel geometries that would be difficult or impossible to create by normal manufacturing methods. More recently, research has been focused on expanding the list of materials that can be made through additive manufacturing, opening a greater range of material properties for this manufacturing method. Due to the unusual conditions during AM, including the high cooling rates and voxel by voxel method of production, AM parts often have anisotropic material microstructures and properties. In this investigation, the laser power, composition, and nozzle head speed during direct metal deposition of copper-iron alloys was varied to understand how the grain structure within the printed parts could be changed and controlled. The resulting dendrite spacing was measured and compared to calculated cooling rates from Gaussian beams on flat plates under similar material and laser properties, which resulted in a cooling rate to dendrite spacing relationship following an inverse square root, as is found in other dendritic systems [Young and Kerkwood, Metall. Trans. A 6, 197–205 (1975)]. Thus, it is demonstrated that in the Cu-Fe system, dendrite spacing can be controlled through manipulation of printing parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A method to observe field-region oxide charge and inter-electrode isolation from CV-characteristics of n-on-p devices

Abstract N-on-psilicon sensors will be utilized in the Compact Muon Solenoid (CMS) detector's tracker and High Granularity Calorimeter (HGCAL) in the High Luminosity upgrade of the Large Hadron Collider (HL-LHC). Among their several advantages in terms of radiation hardness over the traditionalp-on-nsensors in the extreme radiation environment of the HL-LHC are electron collection instead of holes and overlapping maxima of weighting and electric fields at the charge-collecting electrodes. The disadvantage of the multi-channel SiO 2 -passivatedn-on-psensors is the generation of an inversion layer under the Si/SiO 2 -interface by a positive interface-oxide-charge (N ox ) that at high densities can compromise the position resolution by creating a conduction channel between the electrodes. This issue is typically addressed by including additional isolnts (p-stp,p-spray) between n + -electrodes. Focusing on the guard-ring regions ofn-on-psensors where no isolation implants are applied between the electrodes, a capacitance-voltage (CV) characterization study of both 6-inch wafer test diodes and 8-inch HGCAL prototype and pre-series sensors showed a distinct threshold voltage (V th,iso ) in theCV-characteristics of a biased n + -electrode when its enclosing guard-ring was left floating. When reproduced by simulations, the measuredV th,iso was found to contain information on the field-regionN ox and indicate the threshold where the two electrodes become electrically isolated by the influence of the reverse bias voltage. Together with previous studies on the inter-electrode isolation of irradiatedn-on-psensors, the results indicate that position sensitiven-on-psensors without isolation implants may be feasible in future HEP experiments.

Instruments & Instrumentation↗
DOE OSTI2026

Investigation of the isoscalar monopole response in the proton-rich nucleus 14 O

Deuteron inelastic scattering on 14 O was measured in inverse kinematics using an active-target time projection chamber and a magnetic spectrograph. The experimental technique enabled precise measurements of deuteron recoiling particles in coincidence with beam-like fragments detected in the spectrograph focal plane. The double differential cross section was reconstructed for scattering angles of 3–6 degrees and excitation energies up to 26 MeV. The monopole strength distribution was obtained from the data using a multipole decomposition analysis. The results were compared to quasiparticle random-phase approximation (QRPA) and generator coordinate method (GCM) calculations. The QRPA calculation accurately describes experimental data in the energy range of 13 to 26 MeV. GCM calculations assuming a 12 C (g . s .) + p + p cluster configuration were used to determine the 0 + strength in 14 O below 13 MeV. The monopole transition strength of these cluster states provides a good description of the experimental distribution in the 9–11 MeV region, while the 0$^{+}_{2}$ state accounts for only a small fraction of the experimental strength around 6 MeV.

Active target↗
DOE OSTI2021

Decoupled Fréchet kernels based on a fractional viscoacoustic wave equation

We formulate the Fréchet kernel computation using the adjoint-state method based on a fractional viscoacoustic wave equation. We first numerically prove that both the 1/2- and the 3/2-order fractional Laplacian operators are self-adjoint. Using this property, we show that the adjoint wave propagator preserves the dispersion and compensates the amplitude, while the time-reversed adjoint wave propagator behaves identically as the forward propagator with the same dispersion and dissipation characters. Without introducing rheological mechanisms, this formulation adopts an explicit Q parameterization, which avoids the implicit Q in the conventional viscoacoustic/viscoelastic full waveform inversion (Q-FWI). In addition, because of the decoupling of operators in the wave equation, the viscoacoustic Fréchet kernel is separated into three distinct contributions with clear physical meanings: lossless propagation, dispersion, and dissipation. Here, we find that the lossless propagation kernel dominates the velocity kernel, while the dissipation kernel dominates the attenuation kernel over the dispersion kernel.

58 GEOSCIENCES↗