Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “computational reflection”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

First principles treatment of structural, optical, and thermoelectric properties of Li{sub 7}MnN{sub 4} as electrode for a Li secondary battery

The electronic structure, electronic charge density and linear optical properties of the metallic Li{sub 7}MnN{sub 4} compound, having cubic symmetry, are calculated using the full potential linearized augmented plane wave (FP-LAPW) method. The calculated band structure and density of states using the local density, generalized gradient and Engel–Vosko approximations, depict the metallic nature of the cubic Li{sub 7}MnN{sub 4} compound. The bands crossing the Fermi level in the calculated band structure are mainly from the Mn-d states with small support of N-p states. In addition, the Mn-d states at the Fermi level enhance the density of states, which is very useful for the electronic transport properties. The valence electronic charge density depicts strong covalent bond between Mn and two N atoms and polar covalent bond between Mn and Li atoms. The frequency dependent linear optical properties like real and imaginary part of the dielectric function, optical conductivity, reflectivity and energy loss function are calculated on the basis of the computed band structure. Both intra-band and inter-band transitions contribute to the calculated optical parameters. Using the BoltzTraP code, the thermoelectric properties like electrical and thermal conductivity, Seebeck coefficient, power coefficient and heat capacity of the Li{sub 7}MnN{sub 4} are also calculated as a function of temperature and studied.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Incorporating the effects of objects in an approximate model of light transport in scattering media

A computationally efficient radiative transport model is presented that predicts a camera measurement and accounts for the light reflected and blocked by an object in a scattering medium. The model is in good agreement with experimental data acquired at the Sandia National Laboratory Fog Chamber Facility (SNLFC). The model is applicable in computational imaging to detect, localize, and image objects hidden in scattering media. Here, a statistical approach was implemented to study object detection limits in fog.

42 ENGINEERING↗
DOE OSTI2012

The discrete Kalman filtering approach for seismic signals deconvolution

Seismic signals are a convolution of reflectivity and seismic wavelet. One of the most important stages in seismic data processing is deconvolution process; the process of deconvolution is inverse filters based on Wiener filter theory. This theory is limited by certain modelling assumptions, which may not always valid. The discrete form of the Kalman filter is then used to generate an estimate of the reflectivity function. The main advantage of Kalman filtering is capability of technique to handling continually time varying models and has high resolution capabilities. In this work, we use discrete Kalman filter that it was combined with primitive deconvolution. Filtering process works on reflectivity function, hence the work flow of filtering is started with primitive deconvolution using inverse of wavelet. The seismic signals then are obtained by convoluting of filtered reflectivity function with energy waveform which is referred to as the seismic wavelet. The higher frequency of wavelet gives smaller wave length, the graphs of these results are presented.

58 GEOSCIENCES↗
DOE OSTI2015

Quantifying Damage Accumulation During Ductile Plastic Deformation Using Synchrotron Radiation

Under this grant, we have developed and demonstrated the ability of near-field High Energy Diffraction Microscopy (nf-HEDM) to map crystal orientation fields over three dimensions in deformed polycrystalline materials. Experimental work was performed at the Advanced Photon Source (APS) at beamline 1-ID. Applications of this new capability to ductile deformation of copper and zirconium samples were demonstrated as was the comparison of the experimental observations to computational plasticity models using a fast Fourier transform based algorithm that is able to handle the large experimental data sets. No such spatially resolved, direct comparison between measured and computed microstructure evolutions had previously been possible. The impact of this work is reflected in numerous publications and presentations as well as in the investments by DOE and DOD laboratories of millions of dollars in applying the technique, developing sophisticated new hardware that allows the technique to be applied to a wide variety of materials and materials problems, and in the use of the technique by other researchers. In essence, the grant facilitated the development of a new form of three dimensional microscopy and its application to technologically critical states of polycrystalline materials that are used throughout the U.S. and world economies. On-going collaborative work is further optimizing experimental and computational facilities at the APS and is pursuing expanded facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Neutron imaging with lithium indium diselenide: Surface properties, spatial resolution, and computed tomography

An array of lithium indium diselenide (LISe) scintillators were investigated for application in neutron imaging. The sensors, varying in thickness and surface roughness, were tested using both reflective and anti-reflective mounting to the aluminum window. The spatial resolution of each LISe scintillator was calculated using the knife-edge test and a modulation transfer function analysis. It was found that the anti-reflective backing yielded a significantly higher spatial resolution over the reflective backing, and in most cases far exceeded the spatial resolution of a 50 μm-thick ZnS(Cu): 6 LiF scintillation screen. Further, an apparent relationship between the observed increase in spatial resolution when using an anti-reflective backing and the quotient of the surface roughness to the thickness of the LISe scintillator was observed. Lastly, the LISe scintillator array was used in neutron computational tomography to investigate the features of halyomorpha halys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Advanced Computing Annual Report 2025 [Slides]

In Fiscal Year (FY) 2025, the National Laboratory of the Rockies (NLR) continued to advance computing as a cornerstone of energy innovation, expanding the Kestrel high-performance computing (HPC) system to 56 peak petaflops. This growth strengthened Kestrel's role as a national asset for applied energy research, enabling larger, more complex simulations and accelerating the integration of artificial intelligence (AI) methods across the laboratory's computing portfolio. In FY 2025, AI was a component of most projects running on Kestrel, underscoring its central role in modern energy science and engineering. Kestrel supported a broad and diverse set of 507 modeling and simulation projects, engaging 855 researchers across the U.S. Department of Energy's (DOE's) Office of Critical Minerals and Energy Innovation (CMEI) portfolio and other offices, as well as partners from industry, academia, and utilities. These efforts span critical materials discovery, energy systems modeling, grid modernization, advanced manufacturing, and other areas essential to strengthening U.S. energy security and competitiveness. Together, these collaborations produced 708 technical outputs, including 293 peer-reviewed publications, reflecting both the depth and impact of the science enabled by NLR's computing capabilities. This year's report highlights the growing importance and benefit of AI throughout NLR's research programs and features work by early career researchers who are helping shape the future of computing-enabled energy innovation. Explore these sections and the many project successes captured in the pages that follow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Variational Nodal 2D/1D Transport/Diffusion Solutions of the C5G7 Benchmark Problems

This work is the continuation of our effort to generalize the variational nodal method (VNM) for application to pin resolved whole-core PWR problems. To this end, a 2D/1D VNM method without spatial homogenization is formulated and implemented in the PANX code. We employ diffusion theory in the axial direction combined with two-dimensional transport in the x-y plane. In our initial work, we employed the standard spherical harmonics method. To increase accuracy and reduce computational effort, we present two refinements: First, the even-parity integral method within the nodes reduces the computational effort required to form the response matrices. Second, the use of quasi-reflected interface conditions reduces the dimension of the resulting response matrices and therefore the CPU time required to solve the equations. We apply the method to the three-dimensional, unrodded C5G7 benchmark problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Optimal Portfolio Selection Under Concave Price Impact

In this paper we study an optimal portfolio selection problem under instantaneous price impact. Based on some empirical analysis in the literature, we model such impact as a concave function of the trading size when the trading size is small. The price impact can be thought of as either a liquidity cost or a transaction cost, but the concavity nature of the cost leads to some fundamental difference from those in the existing literature. We show that the problem can be reduced to an impulse control problem, but without fixed cost, and that the value function is a viscosity solution to a special type of Quasi-Variational Inequality (QVI). We also prove directly (without using the solution to the QVI) that the optimal strategy exists and more importantly, despite the absence of a fixed cost, it is still in a 'piecewise constant' form, reflecting a more practical perspective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Hierarchical deep reinforcement learning reveals a modular mechanism of cell movement

Time-lapse images of cells and tissues contain rich information about dynamic cell behaviours, which reflect the underlying processes of proliferation, differentiation and morphogenesis. However, we lack computational tools for effective inference. Here we exploit deep reinforcement learning (DRL) to infer cell–cell interactions and collective cell behaviours in tissue morphogenesis from three-dimensional (3D) time-lapse images. We use hierarchical DRL (HDRL), known for multiscale learning and data efficiency, to examine cell migrations based on images with a ubiquitous nuclear label and simple rules formulated from empirical statistics of the images. When applied to Caenorhabditis elegans embryogenesis, HDRL reveals a multiphase, modular organization of cell movement. Imaging with additional cellular markers confirms the modular organization as a novel migration mechanism, which we term sequential rosettes. Furthermore, HDRL forms a transferable model that successfully differentiates sequential rosettes-based migration from others. Our study demonstrates a powerful approach to infer the underlying biology from time-lapse imaging without prior knowledge.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Dynamic compressive behavior of Pr-Nd alloy at high strain rates and temperatures

Based on compressive tests, static on 810 material test system and dynamic on the first compressive loading in split Hopkinson pressure bar (SHPB) tests for Pr-Nd alloy cylinder specimens at high strain rates and temperatures, this study determined a J-C type [G. R. Johnson and W. H. Cook, in Proceedings of Seventh International Symposium on Ballistics (The Hague, The Netherlands, 1983), pp. 541-547] compressive constitutive equation of Pr-Nd alloy. It was recorded by a high speed camera that the Pr-Nd alloy cylinder specimens fractured during the first compressive loading in SHPB tests at high strain rates and temperatures. From high speed camera images, the critical strains of the dynamic shearing instability for Pr-Nd alloy in SHPB tests were determined, which were consistent with that estimated by using Batra and Wei's dynamic shearing instability criterion [R. C. Batra and Z. G. Wei, Int. J. Impact Eng. 34, 448 (2007)] and the determined compressive constitutive equation of Pr-Nd alloy. The transmitted and reflected pulses of SHPB tests for Pr-Nd alloy cylinder specimens computed with the determined compressive constitutive equation of Pr-Nd alloy and Batra and Wei's dynamic shearing instability criterion could be consistent with the experimental data. The fractured Pr-Nd alloy cylinder specimens of compressive tests were investigated by using 3D supper depth digital microscope and scanning electron microscope.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Study of the Effective Refractive Index Profile in Self-Assembling Nanostructured ITO Films

The optical characteristics and structural features of self-assembling nanostructured indium–tin oxide (ITO) films deposited onto substrates heated above 400°C are studied. Estimations of the distribution profiles of the material and effective refractive index in the films under study are obtained by computer simulation of a medium having spectral dependences of light transmission and reflection coefficients closest to those observed in the experiment. These results are in good agreement with scanning electron microscopy data for these films and make it possible to not only confirm the gradient character of such coatings but also restore some of its features. The further overgrowth of voids in self-assembling nanostructured films by means of the deposition of an additional material amount by magnetron sputtering at room temperature leads to a variation in the effective refractive index profile in them. Thus, it is possible to form transparent conductive films with an efficient refractive index profile adjusted for specific tasks. Adjustment of the refractive index profile in self-assembled ITO films acquires a special value for designing coatings with specified properties by virtue of a limited set of transparent conductive materials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Anisotropic Thermal Expansion of Zirconium Diboride: An Energy-Dispersive X-Ray Diffraction Study

Zirconium diboride (ZrB 2 ) is an attractive material due to its thermal and electrical properties. In recent years, ZrB 2 has been investigated as a superior replacement for sapphire when used as a substrate for gallium nitride devices. Like sapphire, ZrB 2 has an anisotropic hexagonal structure which defines its directionally dependent properties. However, the anisotropic behavior of ZrB 2 is not well understood. In this paper, we use energy-dispersive synchrotron X-ray diffraction to measure the thermal expansion of polycrystalline ZrB 2 powder from 300 to 1150 K. Nine Bragg reflections are fit using Pseudo-Voigt peak profiles and used to compute the a and c lattice parameters using a nonlinear least-squares approximation. The temperature-dependent instantaneous thermal expansion coefficients are determined for each a -axis and c -axis direction and are described by the following equations: α a = ( 4.1507 × 10 - 6 + 5.1086 × 10 - 9 ( T - 293.15 ) )/( 1 + 4.1507 × 10 - 6 ( T - 293.15 ) + 2.5543 × 10 - 9 ( T - 293.15 ) 2 ) and α c = ( 4.5374 × 10 - 6 + 4.3004 × 10 - 9 ( T - 293.15 ) )/( 1 + 4.5374 × 10 - 6 ( T - 293.15 ) + 2.1502 × 10 - 9 ( T - 293.15 ) 2 ). Our results are within range of previously reported values but describe the temperature anisotropy in more detail. We show that anisotropic expansion coefficients converge to the same value at about 780 K and diverge at higher temperatures. Results are compared with other reported values.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scattering of Radio Frequency Waves by Density Filaments

The edge region and the scrape-off layer of magnetically confined fusion devices, like tokamaks and stellarators, are replete with turbulent plasma that is a mixture of coherent, blob or filament like, structures [1] and incoherent fluctuations [2]. The variation in the density due to turbulence can be comparable to or greater than the ambient density [2]. As part of an overall effort to optimize the efficiency of operation, radio frequency (RF) waves are commonly used for heating fusion plasmas and, in tokamaks, for generating plasma current needed for confinement and controlling instabilities. The RF waves are excited by antenna structures that are placed near the wall of a fusion device. In order to deliver energy and momentum to charged particles in the core of fusion plasmas, RF waves have to propagate through the turbulent plasma. In present fusion devices, the scrap-off layer and the edge plasma region is of the order of a few centimeters. In reactor type devices, like ITER, this region is expected to be of the order of tens of centimeters. Since the efficiency of operation of a fusion reactor is of prime importance, it is imperative that we understand the effect of turbulence on RF waves. The fluctuations in density lead to changes in the plasma permittivity. As in conventional electrodynamics, the propagation of RF waves through different dielectric media is subject to reflection, refraction, and diffraction. In this paper, we summarize our theoretical and computational studies on the propagation of RF waves through filamentary structures present in the scrape-off layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Variational Nodal 2D/1D Transport/Diffusion Solutions of the C5G7 Benchmark Problems

This work is the continuation of our effort to generalize the variational nodal method (VNM) for application to pin-resolved whole-core PWR problems. To this end, a 2D/1D VNM method without spatial homogenization is formulated and implemented in the PANX code. We employ diffusion theory in the axial direction combined with two-dimensional transport in the x-y plane. In our initial work, we employed the standard spherical harmonics method. To increase accuracy and reduce computational effort, we present two refinements: First, the even-parity integral method within the nodes reduces the computational effort required to form the response matrices. Second, the use of quasi-reflected interface conditions reduces the dimension of the resulting response matrices and therefore the CPU time required to solve the equations. We apply the method to the three-dimensional, un-rodded C5G7 benchmark problem. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

SBbadger: biochemical reaction networks with definable degree distributions

Abstract Motivation An essential step in developing computational tools for the inference, optimization and simulation of biochemical reaction networks is gauging tool performance against earlier efforts using an appropriate set of benchmarks. General strategies for the assembly of benchmark models include collection from the literature, creation via subnetwork extraction and de novo generation. However, with respect to biochemical reaction networks, these approaches and their associated tools are either poorly suited to generate models that reflect the wide range of properties found in natural biochemical networks or to do so in numbers that enable rigorous statistical analysis. Results In this work, we present SBbadger, a python-based software tool for the generation of synthetic biochemical reaction or metabolic networks with user-defined degree distributions, multiple available kinetic formalisms and a host of other definable properties. SBbadger thus enables the creation of benchmark model sets that reflect properties of biological systems and generate the kinetics and model structures typically targeted by computational analysis and inference software. Here, we detail the computational and algorithmic workflow of SBbadger, demonstrate its performance under various settings, provide sample outputs and compare it to currently available biochemical reaction network generation software. Availability and implementation SBbadger is implemented in Python and is freely available at https://github.com/sys-bio/SBbadger and via PyPI at https://pypi.org/project/SBbadger/. Documentation can be found at https://SBbadger.readthedocs.io. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

An analytical solution of the solution-diffusion-electromigration equations reproduces trends in ion rejections during nanofiltration of mixed electrolytes

Here, this paper develops an analytical solution to the equations governing the solution-diffusion-electromigration transport of the ions from two salts that contain a common ion. The analytical expressions, which rely on constant ion permeances, readily enable simple spreadsheet computations of the permeate ion concentrations in nanofiltration (NF). Despite the model simplicity, calculations of ion rejections as a function of transmembrane volume fluxes, feed-solution compositions, and permeance values reproduce experimental trends, with ion permeances as the only adjustable parameters. For example, with solutions containing dissolved MA and M 2 B, when the membrane permeance to B 2– is much lower than the permeances to A – and M + , plots of A – rejection versus transmembrane volume flux show the negative minimum that is often characteristic of NF. Moreover, B 2– rejection increases with increasing MA in the feed solution, reflecting a decreasing electric field in the membrane. The analytical solution also enables spreadsheet computations of electric fields in membrane separation layers and effectively models experimental data for intrinsic rejections as a function of transmembrane volume flow. Interestingly, the model suggests that with sufficiently high permeances of A – (relative to M + ), at certain feed compositions the A – /B 2– selectivity may increase without bound as a function of volume flow. Otherwise, this selectivity does not vary greatly with feed composition and quickly reaches a limit as the volume flow increases. Despite the simplifying approximation of constant ion permeances, using only a few adjustable parameters this model readily reveals trends in NF ion rejections and may help to identify the desired ion permeances or solution compositions for specific separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The role of quantum computing in advancing scientific high-performance computing: A perspective from the ADAC institute

Quantum computing (QC) has gained significant attention over the past two decades due to its potential for speeding up classically demanding tasks. This transition from an academic focus to a thriving commercial sector is reflected in substantial global investments. While advancements in qubit counts and functionalities continue at a rapid pace, current quantum systems still lack the scalability for practical applications, facing challenges such as too high error rates and limited coherence times. Here, this perspective paper examines the relationship between QC and high-performance computing (HPC), highlighting their complementary roles in enhancing computational efficiency. It is widely acknowledged that even fully error-corrected QC will not be suited for all computational tasks. Rather, future compute infrastructures are anticipated to employ quantum acceleration within hybrid systems that integrate HPC and QC. While QC can enhance classical computing, traditional HPC remains essential for maximizing quantum acceleration. This integration is a priority for supercomputing centers and companies, sparking innovation to address the challenges of merging these technologies. The novelty of this work lies in its unique perspective, reflecting the collective insights of the Accelerated Data Analytics and Computing (ADAC) Institute, a global consortium of over 20 leading HPC centers. Recognizing the growing importance of QC, ADAC established a Quantum Computing Working Group in 2023 to foster collaboration and knowledge-sharing among its members. This paper synthesizes insights from the group’s collaborative efforts and incorporates findings from a member survey that captures shared experiences, ongoing projects, and strategic directions. By outlining the current landscape and challenges of QC integration into HPC ecosystems, this work offers HPC specialists practical and forward-looking guidance on the opportunities and implications of QC in computationally intensive endeavors.

Accelerated Data Analytics and↗
DOE OSTI2024

CP violation searches and distributed computing development with the Belle II Experiment at the University of Mississippi and Brookhaven National Laboratory (Final Report)

This report reflects the work performed at the University of Mississippi under the support of DOE EPSCoR grant DE‐SC0021274 during the period of September 2020 through August 2024, including a one-year, no-cost extension. A summary of the research outcomes is given, with reference to the project goals as stated in the proposal. This successful project supported the mission of the DOE High Energy Physics program by leveraging the complimentary expertise of researchers at the University of Mississippi and Brookhaven National Lab to search for CP violation in charmed baryon decays using data from the Belle II experiment and to provide vital support for Belle II distributed computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗