Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “RESIDUES”

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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Effects of deep superconducting gap minima and disorder on residual thermal transport in Sr 2 RuO 4

Recent thermal conductivity measurements on Sr 2 RuO 4 were interpreted as favoring a pairing gap function with vertical line nodes while conflicting with chiral p-wave pairing. Motivated by this work we study the effects of deep superconducting gap minima on impurity induced quasiparticle thermal transport in chiral p-wave models of Sr 2 RuO 4 . Combining a self-consistent T-matrix analysis and self-consistent Bogoliubov–de Gennes calculations, we show that the dependence of the residual thermal conductivity on the normal state impurity scattering rate can be quite similar to the d-wave pairing state that was shown to fit the thermal conductivity measurements, provided the normal state impurity scattering rate is large compared with the deep gap minima. Furthermore, thermal conductivity measurements on Sr 2 RuO 4 can be reconciled with a chiral p-wave pairing state with deep gap minima. However, the data impose serious constraints on such models and these constraints are examined in the context of several different chiral p-wave models.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Effects of triaxiality and residual n p interaction in the proton emission from Ho 140

Here we present a detailed theoretical investigation of proton emission from 140 Ho within the nonadiabatic quasiparticle approach. The calculated proton emission half-life reproduces well the measured data. The importance of triaxiality and of the residual np interaction are studied. The ground state spin and parity of 139 Dy (daughter) and 140 Ho (parent) are ascertained unambiguously as 7/2 + and 3 – , respectively, by analyzing the rotational energies, half-lives, and branching ratios.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Neutron transfer in the C 13 + Au 197 reaction from gold isotope residuals

Residual gold nuclei were produced in this paper via neutron transfer at multiple energies using a 130-MeV 13 C beam incident on a stacked-foil target consisting of alternating layers of 197 Au and 27 Al. Production cross sections, over an energy range of 56 to 129 MeV, for seven gold isotopes and two gold isomers were determined through activation analysis. By using the Wilczynski binary transfer model with a modified version of the recoil formula and a standard evaporation model, we were able to reproduce the isotopic production cross sections at high beam energy, with some disagreement at lower beam energies. Finally, this limiting angular momentum model does not predict the transfer of sufficient angular momentum to reproduce the observed isomeric populations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Galaxy deblending using residual dense neural networks

We present a new neural network approach for deblending galaxy images in astronomical data using Residual Dense Neural network (RDN) architecture. We train the network on synthetic galaxy images similar to the typical arrangements of field galaxies with a finite point spread function (PSF) and realistic noise levels. The main novelty of our approach is the usage of two distinct neural networks: i) a deblending network which isolates a single galaxy postage stamp from the composite and, ii) a classifier network which counts the remaining number of galaxies. The deblending proceeds by iteratively peeling one galaxy at a time from the composite until the image contains no further objects as determined by the classifier, or by other stopping criteria. By looking at the consistency in the outputs of the two networks, we can assess the quality of the deblending. Further, we characterize the flux and shape reconstructions in different quality bins and compare our deblender with the industry standard, SExtractor. We also discuss possible future extensions for the project with variable PSFs and noise levels.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2011

Residue theorem and summing over Kaluza-Klein excitations

Applying the equations of motion together with corresponding boundary conditions of bulk profiles at infrared and ultraviolet branes, we verify some lemmas on the eigenvalues of Kaluza-Klein modes in extension of the standard model with a warped extra dimension and the custodial symmetry SU(3){sub c}xSU(2){sub L}xSU(2){sub R}xU(1){sub X}xP{sub LR}. Using the lemmas and performing properly analytic extensions of bulk profiles, we present the sufficient condition for a convergent series of Kaluza-Klein excitations and sum over the series through the residue theorem. The method can also be applied to sum over the infinite series of Kaluza-Klein excitations in a universal extra dimension. Furthermore, we analyze the possible connection between the propagators in five-dimensional full theory and the product of bulk profiles with corresponding propagators of exciting Kaluza-Klein modes in four-dimensional effective theory, and recover some relations presented in the literature for warped and universal extra dimensions, respectively. As an example, we present the correction from new physics to the branching ratio of B{yields}X{sub s{gamma}} to the order O({mu}{sub EW}{sup 2}/{Lambda}{sub KK}{sup 2}) in extension of the standard model with a warped extra dimension and the custodial symmetry, where {Lambda}{sub KK} denotes the energy scale of low-lying Kaluza-Klein excitations and {mu}{sub EW} denotes the electroweak energy scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

High stereographic resolution texture and residual stress evaluation using time-of-flight neutron diffraction

Neutron diffraction texture measurements provide bulk averaged textures with excellent grain orientation statistics, even for large-grained materials, owing to the probed volume being of the order of 1 cm 3 . Furthermore, crystallographic parameters and other valuable microstructure information such as phase fraction, coherent crystallite size, root-mean-square microstrain, macroscopic or intergranular strain and stress, etc. can be derived from neutron diffractograms. A procedure for combined high stereographic resolution texture and residual stress evaluation was established on the pulsed-neutron-source-based engineering materials diffractometer TAKUMI at the Materials and Life Science Experimental Facility of the Japan Proton Accelerator Research Center, through division of the neutron detector panel regions. Pole figure evaluation of a limestone standard sample with a well known texture suggested that the precision obtained for texture measurement is comparable to that of the established neutron beamlines utilized for texture measurement, such as the HIPPO diffractometer at the Los Alamos Neutron Science Center (New Mexico, USA) and the D20 angle-dispersive neutron diffractometer at the Institut Laue–Langevin (Grenoble, France). A high-strength martensite–austenite multilayered steel was employed for further verification of the reliability of simultaneous Rietveld analysis of multiphase textures and macro stress tensors. By using a texture-weighted geometric mean micromechanical (BulkPathGEO) model, a macro stress tensor analysis with a plane stress assumption showed a rolling direction–transverse direction (RD–TD) in-plane compressive stress (about –330 MPa) in the martensite layers and an RD–TD in-plane tensile stress (about 320 MPa) in the austenite layers. The phase stress partitioning was ascribed mainly to the additive effect of the volume expansion during martensite transformation and the linear contraction misfit between austenite layers and newly transformed martensite layers during the water quenching process.

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

Room-temperature X-ray crystallography reveals the oxidation and reactivity of cysteine residues in SARS-CoV-2 3CL Mpro: insights into enzyme mechanism and drug design

The emergence of the novel coronavirus SARS-CoV-2 has resulted in a worldwide pandemic not seen in generations. Creating treatments and vaccines to battle COVID-19, the disease caused by the virus, is of paramount importance in order to stop its spread and save lives. The viral main protease, 3CL M pro , is indispensable for the replication of SARS-CoV-2 and is therefore an important target for the design of specific protease inhibitors. Detailed knowledge of the structure and function of 3CL M pro is crucial to guide structure-aided and computational drug-design efforts. Here, the oxidation and reactivity of the cysteine residues of the protease are reported using room-temperature X-ray crystallography, revealing that the catalytic Cys145 can be trapped in the peroxysulfenic acid oxidation state at physiological pH, while the other surface cysteines remain reduced. Only Cys145 and Cys156 react with the alkylating agent N -ethylmaleimide. It is suggested that the zwitterionic Cys145–His45 catalytic dyad is the reactive species that initiates catalysis, rather than Cys145-to-His41 proton transfer via the general acid–base mechanism upon substrate binding. The structures also provide insight into the design of improved 3CL M pro inhibitors.

3CL Mpro↗
DOE OSTI2024

Deep residual networks for crystallography trained on synthetic data

The use of artificial intelligence to process diffraction images is challenged by the need to assemble large and precisely designed training data sets. To address this, a codebase called Resonet was developed for synthesizing diffraction data and training residual neural networks on these data. Here, two per-pattern capabilities of Resonet are demonstrated: (i) interpretation of crystal resolution and (ii) identification of overlapping lattices. Resonet was tested across a compilation of diffraction images from synchrotron experiments and X-ray free-electron laser experiments. Crucially, these models readily execute on graphics processing units and can thus significantly outperform conventional algorithms. While Resonet is currently utilized to provide real-time feedback for macromolecular crystallography users at the Stanford Synchrotron Radiation Lightsource, its simple Python-based interface makes it easy to embed in other processing frameworks. This work highlights the utility of physics-based simulation for training deep neural networks and lays the groundwork for the development of additional models to enhance diffraction collection and analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Model Residuals as Shields: A Two-Level Formulation to Defend Smart Grids From Poisoning Attacks

The advancement of smart grids presents both vast opportunities and heightened cybersecurity risks. Data-driven defense mechanisms, though designed as a shield against these threats, can fall prey to poisoning attacks. We delve into regression settings, underscoring the imperative to fortify defenses against a spectrum of poison ratios, notably those above 0.5—an issue scarcely addressed in prior studies. Recognizing the susceptibilities of smart grids and their manipulable sensors, we exploit the very intent of poisoning attacks, compromising model accuracy, as our defense mechanism. Our proposed two-level optimization framework discerns between poisoned and authentic data based on model residuals, outperforming or matching existing methods in 72% to 77% of precision and 75% to 80% of recalls across various poisoning attacks, poison ratios, and datasets. Once the authentic data are identified, the trained model is adaptable for a variety of applications. Comprehensive evaluations on different smart grid datasets, pitted against myriad poisoning schemes, validate our methodology’s edge over existing methods. Here, we also shed light on the implications of model misspecification originating from temporal auto-correlation, a common feature in Internet of Things and smart grid data.

Adversarial machine learning (ML)↗
DOE OSTI2017

Performance Analysis of Electrodynamic Screens Based on Residual Particle Size Distribution

Dust accumulation on the optical surfaces of solar collectors causes significant losses in their energy yield. Fine dust particles, compared with coarse ones, contribute significantly more in the performance loss, assuming identical surface mass concen- tration. This study examines the performance of different electro- dynamic screen (EDS) prototypes, operated under different con- ditions, in removing fine dust particles in the laboratory environ- ment. After going through several cycles of dust deposition and cleaning using EDS, the dust residue left on each EDS prototype is collected and analyzed using a Horiba particle size distribution (PSD) analyzer. The PSD analyses determine which EDS design has performed superior in removing a given size range and in which operational condition. Here, the results are advantageous in the optimization procedure of EDS to attain maximum dust removal efficiency and minimum optical interference.

14 SOLAR ENERGY↗
DOE OSTI2026

ResSR: A Computationally Efficient Residual Approach to Super-Resolving Multispectral Images

Multispectral imaging (MSI) plays a critical role in material classification, environmental monitoring, and remote sensing. However, MSI sensors typically have wavelength-dependent resolution, which limits downstream analysis. MSI super-resolution (MSI-SR) methods address this limitation by reconstructing all bands at a common high spatial resolution. Existing methods can achieve high reconstruction quality but often rely on spatially-coupled optimization or large learning-based models, leading to significant computational cost and limiting their use in large-scale or time-critical settings. In this paper, we introduce ResSR, a computationally efficient, model-based MSI-SR method that achieves high-quality reconstruction without supervised training or spatially-coupled optimization. Notably, ResSR decouples spectral and spatial processing into two sequential steps. ResSR first computes a spectrally-informed high-resolution estimate of the MSI using singular value decomposition together with a spatially-decoupled approximate forward model. It then applies a residual correction step to restore low-frequency spatial consistency while preserving high-frequency detail recovered by the spectral reconstruction. ResSR achieves comparable or improved reconstruction quality relative to existing MSI-SR methods while being

Sullivan, Haley [ORNL] (ORCID:0000000274069217)↗
DOE OSTI2024

Design Considerations to Ensure Robustness of the ITER Diagnostics Residual Gas Analyzer

Increasing robustness of the ITER diagnostic residual gas analyzer (DRGA) is critical for the potential control of plasma heating and fuel-cycle processing. Robustness is a requirement for a diagnostic to have a control function. The DRGA is a multisensor diagnostic system capable of resolving isotopic compositions of hydrogen and helium as well as other heavier elements and compounds. The divertor-specific DRGA system is intended to measure the composition of gases in the ITER subdivertor region and midplane. Its analysis station will be located in a port cell at the divertor level. From there, it will sample a slip stream of gas from the cryogenic pump duct. It will then exhaust into a shared roughing line where helium or other light gas impurities, some potentially from other diagnostic systems, are likely to be present. In order to provide reliable measurements, the DRGA must be robust in areas such as plasma optical emission source geometry for a compact design, mitigation of back-streaming from light gases and resilience to the ITER port cell environment, and radiation hardening of the DRGA electronics. By incorporating robustness into the design, areas of plasma heating and fuel-cycle control may be explored with the DRGA for ITER and next-generation fusion devices.

Quinlan, Brendan↗
DOE OSTI2024

A Data-Driven Methodology for Contextual Unit Commitment Using Regression Residuals

Day after day, system operators are faced with the challenge of taking unit commitment (UC) decisions under uncertain net load conditions. The standard operating procedure for taking UC decisions begins by leveraging auxiliary data on covariates (such as the day of the week or latest weather information) to generate a point prediction for net load, which is used in solving a deterministic UC problem. Such an approach, however, is known to deliver a notoriously poor out-of-sample (OOS) performance, as it completely disregards the stochastic nature of net load. While stochastic programming models explicitly represent uncertainty, they mostly do so using a generic set of scenarios that neglect covariate observations, squandering useful auxiliary data that could be harnessed to glean insights into uncertainty. In this article, we discuss a contextual stochastic optimization approach to UC, which effectively exploits covariate observations while explicitly assessing uncertainty so as to boost the OOS performance of UC decisions. The key thrust of our approach is to leverage regression models, along with their empirical residuals, to set up and solve sample average approximation problems. Not only do we prove that our approach satisfies the requisite conditions for asymptotic optimality and consistency laid out in (Kannan et al., 2022), but we also assess its performance on several case studies conducted using real-world data collected in California ISO and New York ISO grids. In conclusion, results show that the proposed approach can significantly improve OOS performance compared to alternative methods proposed in the literature under varying dataset sizes.

Yurdakul, Ogun↗
DOE OSTI2020

Nepheline crystallization and the residual glass composition: Understanding waste glass durability

The vast majority of High-Level Waste (HLW) originating from defense nuclear programs is sequestered and immobilized in borosilicate glass. Borosilicate glass is universally accepted for immobilizing HLW, but its efficiency has limitations based on the compositional makeup of the waste stream. The chemical durability of the glass is the most important factor in determining the longevity and usefulness of the final glass waste form. The primary detriment to this durability in glasses containing high levels of aluminum is nepheline (NaAlSiO 4 ) crystallization, as it is generally accompanied by a measurable decrease in the glass's chemical durability. This work seeks to understand nepheline crystallization, within the context of thermal history, and to elucidate the influence of compositional shifts in the residual glass (after crystallization) on the measured durability. The results presented within show a distinct deviation in leaching behavior as a function of structural makeup (calculated Q units). This understanding will provide practical information required for broadening glass compositional regions needed to more efficiently vitrify HLW.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Flaw Stability Considering Residual Stress for Aging Management of Spent Nuclear Fuel Multiple-Purpose Canisters

A typical multipurpose canister (MPC) is made of austenitic stainless steel and is loaded with spent nuclear fuel assemblies. Because heat treatment for stress relief is not required for the construction of the MPC, the canister is susceptible to stress corrosion cracking in the weld or heat affected zone regions under long-term storage conditions. Logic for flaw acceptance is developed should crack-like flaws be detected by Inservice Inspection. The procedure recommended by API 579-1/ASME FFS-1, Fitness-for-Service, is used to calculate the instability crack length or depth by failure assessment diagram. It is demonstrated that the welding residual stress has a strong influence on the results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A Generalized Stress Inversion Approach With Application to Residual Stress Estimation

In this work develop a generalized stress inversion technique (or the generalized inversion method) capable of recovering stresses in linear elastic bodies subjected to arbitrary cuts. Specifically, given a set of displacement measurements found experimentally from digital image correlation (DIC), we formulate a stress estimation inverse problem as a partial differential equation-constrained optimization problem. We use gradient-based optimization methods, and we accordingly derive the necessary gradient and Hessian information in a matrix-free form to allow for parallel, large-scale operations. By using a combination of finite elements, DIC, and a matrix-free optimization framework, the generalized inversion method can be used on any arbitrary geometry, provided that the DIC camera can view a sufficient part of the surface. We present numerical simulations and experiments, and we demonstrate that the generalized inversion method can be applied to estimate residual stress.

42 ENGINEERING↗
DOE OSTI2024

Iterative Stress Reconstruction Algorithm to Estimate Three-Dimensional Residual Stress Fields in Manufactured Components

Residual stress (RS) significantly impacts the mechanical performance of components. Measurement of RS often provides incomplete data in terms of components of stress and spatial density. Employing such fields in finite element simulations results in significant modification of the field to achieve equilibrium and compatibility among strains. To overcome this, an iterative stress reconstruction algorithm (ISRA) is developed to estimate 3D RS fields that satisfy equilibrium, are stress component-wise complete, and represent the characterized data sampled. An Al 7075-T651 plate and an additively manufactured (AM) A36 steel wall are considered for RS reconstruction using measurement data from the literature. A maximum variation of ~2.5 MPa in the Al plate, and ~10 MPa in the steel wall are observed between the reconstructed and measured stresses. Furthermore, unknown stress components emerge and reach significant magnitudes (upto ~2.3 MPa in the Al plate and ~45 MPa in the AM wall) during ISRA. Indeed, it is found that minor errors in measurement or data processing are eliminated through the physical requirements during ISRA. Employing a reconstructed RS field is hence not just more accurate given its compatibility, but it additionally corrects for minor errors in measurement. Furthermore, it is found that spatially dense measurement data result in convergence with fewer iterations. Finally, although ISRA yields a nonunique solution dependent on boundary conditions, measurement errors, fitting errors, and mesh density, it accommodates for uncertainties and inaccuracies in measurement, as opposed to failing to reach a physically realistic converged solution.

42 ENGINEERING↗
DOE OSTI2025

ASSESSING THE EFFECTIVENESS OF ULTRASONIC IMPACT TREATMENT ON RESIDUAL STRESS PROFILES IN DISSIMILAR WELDED JOINTS

Residual stresses (RS) induced during welding processes are a critical concern in materials engineering, as they can significantly impair the mechanical performance of components by reducing fatigue strength and tensile load capacity. This challenge is especially pronounced in dissimilar metal welds (DMWs), where variations in thermal expansion properties between the joined alloys exacerbate the formation of tensile RS. Conventional post-weld heat treatments, though effective for homogeneous materials, often require substantial energy, specialized equipment, and extensive processing time, making them less practical for DMW applications. Thus, there is a clear need for innovative, energy-efficient techniques to mitigate these detrimental stresses. This study investigates ultrasonic impact treatment (UIT) as a possible alternative for mitigating tensile RS in both similar and dissimilar metal welds. To evaluate UIT’s effectiveness, neutron diffraction (ND) was employed as a nondestructive technique to quantify RS in three orthogonal directions—longitudinal, transverse, and normal. The results showed that UIT significantly reduced peak tensile RS, particularly in the longitudinal direction, by up to 180 MPa in similar welds and up to 150 MPa in dissimilar welds. Given the limited literature on UIT application in DMWs, this work contributes valuable data on stress redistribution mechanisms and highlights UIT’s potential as a practical stress-relief method. The findings lay the groundwork for further investigations aimed at optimizing process parameters and understanding long-term performance in welded joints.

EisaZadeh, Hamid [Western Carolina University, Cul↗