Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “analytics”

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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Using Big Data Analytics to Advance Precision Radiation Oncology

Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of genomics and radiomics research. A learning health system (LHS) is conceptualized that uses clinically acquired data with machine learning to advance the initiatives of precision medicine. The LHS is comprehensive and can be used for clinical decision support, discovery, and hypothesis derivation. These developing uses can positively impact the ultimate management and therapeutic course for patients. The conceptual model for each use of clinical data, however, is different, and an overview of the implications is discussed. With advancements in technologies and culture to improve the efficiency, accuracy, and breadth of measurements of the patient condition, the concept of an LHS may be realized in precision radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

A Novel Analytical Population Tumor Control Probability Model Includes Cell Density and Volume Variations: Application to Canine Brain Tumor

Tumor control probability (TCP) models based on Poisson statistics characterize the distribution of surviving clonogens. Thus enabling the calculation of TCP for individuals. To mathematically describe clinically observed survival data of patient cohorts it is necessary to extend the Poisson TCP model. This is typically done by either incorporating variations of model parameters or by using an empirical logistic model. The purpose of this work is the development of an analytical population TCP model by mechanistic extension of the Possion model.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Analytical simulation of meander morphology from equilibrium to long-term evolution: Impacts of channel geometry and vegetation-induced coarsening

This study introduces an innovative approach to modeling meandering river morphology, integrating and investigating the effects of geometric characteristics and vegetation-induced channel coarsening. The developed comprehensive framework combines several advanced techniques: Genetic Programming for refining the scour factor of transverse bed slope, a Leaf Area Index (LAI)-enhanced analytical model for quantifying vegetative flow resistance, and an upstream-weighted moving average method for efficient approximation of the convolution integral in meander migration calculations. The model is validated against both an idealized Kinoshita meander and a natural bend of the Tumen River (China) in equilibrium, demonstrating its robustness across diverse scales and conditions. The model's ability to simulate the long-term evolution, including cutoff events, provides valuable insight for river management strategies. The current findings demonstrate that channel geometry, particularly width-to-depth ratio, plays a dominant role in meander evolution, with wider channels prone to more complex and rapid morphological changes. Vegetation effects are most pronounced in channels with moderate width-to-depth ratios, where they can significantly influence migration rates and bed topography. A combination of channel widening and deepening, coupled with strategic vegetation management, can effectively enhance navigability while maintaining channel stability in the studied Tumen River reach. Sensitivity analyses highlight the complex interplay between hydraulic conditions, sediment characteristics, and vegetation in shaping river morphology. This research advances understanding of the multifaceted nature of meandering river systems and offers practical tools for informed decision-making in river engineering and environmental management, particularly in the context of climate change and increasing anthropogenic pressures on fluvial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Numerical stability analysis of the pseudo-spectral analytical time-domain PIC algorithm

The pseudo-spectral analytical time-domain (PSATD) particle-in-cell (PIC) algorithm solves the vacuum Maxwell's equations exactly, has no Courant time-step limit (as conventionally defined), and offers substantial flexibility in plasma and particle beam simulations. It is, however, not free of the usual numerical instabilities, including the numerical Cherenkov instability, when applied to relativistic beam simulations. This paper derives and solves the numerical dispersion relation for the PSATD algorithm and compares the results with corresponding behavior of the more conventional pseudo-spectral time-domain (PSTD) and finite difference time-domain (FDTD) algorithms. In general, PSATD offers superior stability properties over a reasonable range of time steps. More importantly, one version of the PSATD algorithm, when combined with digital filtering, is almost completely free of the numerical Cherenkov instability for time steps (scaled to the speed of light) comparable to or smaller than the axial cell size.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Predicting boron coordination in multicomponent borate and borosilicate glasses using analytical models and machine learning

Accurate prediction of boron coordination in multicomponent glasses is critical in glass science and technology as it strongly affects the properties of borate and borosilicate glasses. We have collected a dataset containing 657 glasses from literature with boron coordination values and developed models using analytical functions based on the well accepted Dell, Xiao and Bray model. Good prediction of boron coordination with a R 2 value higher than 0.8 was obtained. The large variation of boron coordination from experiments, originated from sample preparations and characterizations, led to difficulties in obtaining models with better prediction performance. Various machine learning (ML) algorithms were evaluated and slightly better prediction performance was observed; however, interpretation of the ML models is less straight forward. In conclusion, this study developed various models capable of providing quantitative boron coordination predictions, providing insights into its structural roles in multi-component glasses, and suggesting fruitful areas for future research.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Streaming data analytics via message passing with application to graph algorithms

The need to process streaming data, which arrives continuously at high-volume in real-time, arises in a variety of contexts including data produced by experiments, collections of environmental or network sensors, and running simulations. Streaming data can also be formulated as queries or transactions which operate on a large dynamic data store, e.g. a distributed database. We describe a lightweight, portable framework named PHISH which enables a set of independent processes to compute on a stream of data in a distributed-memory parallel manner. Datums are routed between processes in patterns defined by the application. PHISH can run on top of either message-passing via MPI or sockets via ZMQ. The former means streaming computations can be run on any parallel machine which supports MPI; the latter allows them to run on a heterogeneous, geographically dispersed network of machines. We illustrate how PHISH can support streaming MapReduce operations, and describe streaming versions of three algorithms for large, sparse graph analytics: triangle enumeration, subgraph isomorphism matching, and connected component finding. Lastly, we also provide benchmark timings for MPI versus socket performance of several kernel operations useful in streaming algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A two-dimensional analytical unit cell model for redox flow battery evaluation and optimization

Cell performance optimization is important for improving the overall system efficiency of a redox flow battery. To gain better insights into key controlling factors of system efficiency, this work first proposed a theoretical model for a unit flow battery cell by extending a two-dimensional analytic model to a full battery cell. Such a model is then used for cell performance optimization after validating it with experimental and numerical modeling data. With the model results, the activation, equilibrium, and pump energy losses are identified as the dominant sources of battery energy losses. Further, a guideline for reducing these sources is also proposed. Following the guideline, the mass transport coefficient is shown as a key control factor of the equilibrium energy loss and Coulombic efficiency (CE). Approaches are then proposed to improve CE and the overall system efficiency. The mass transport is also revealed as the mechanism of pump rate optimization where an optimal pump rate significantly reduces the equilibrium energy loss. With both low equilibrium and pump energy losses, an optimal electrode porosity or specific area design can further improve a battery's system efficiency based on an optimal porosity predicted by the present model. The model also demonstrates distinct behaviors and overestimation in the system efficiency when reduced to a zero-dimensional model with neglected mass transport resistance. With the new model, the guideline, and new insights, this work provides a reliable and efficient tool for the evaluation and optimization of redox flow battery design in practical applications.

25 ENERGY STORAGE↗
DOE OSTI2015

A high-resolution analytical scanning transmission electron microscopy study of the early stages of spinodal decomposition in binary Fe–Cr

Spinodal decomposition (SD) is an important phenomenon in materials science and engineering. For example, it is considered to be responsible for the 475 °C embrittlement of stainless steels comprising the bcc (ferrite) or bct (martensite) phases. Structural characterization of the evolving minute nano-scale concentration fluctuations during SD in the Fe–Cr system is, however, a notable challenge, and has mainly been considered accessible via atom probe tomography (APT) and small-angle neutron scattering. The standard tool for nanostructure characterization, viz. transmission electron microscopy (TEM), has only been successfully applied to late stages of SD when embrittlement is already severe. However, we here demonstrate that the structural evolution in the early stages of SD in binary Fe–Cr, and alloys based on the binary, are accessible via analytical scanning TEM. An Fe–36 wt% Cr alloy aged at 500 °C for 1, 10 and 100 h is investigated using an aberration-corrected microscope and it is found that highly coherent and interconnected Cr-rich regions develop. The wavelength of decomposition is rather insensitive to the sample thickness and it is quantified to 2, 3 and 6 nm after ageing for 1, 10 and 100 h, which is in reasonable agreement with prior APT analysis. The concentration amplitude is more sensitive to the sample thickness and acquisition parameters but the TEM analysis is in good agreement with APT analysis for the longest ageing time. These findings open up for combinatorial TEM studies where both local crystallography and chemistry is required. - Highlights: • STEM-EELS analysis was successfully applied to resolve early stage SD in Fe–Cr. • Compositional wavelength measured with STEM-EELS compares well to previous ATP studies. • Compositional amplitude measured with STEM-EELS is a function of experimental parameters. • STEM-EELS allows for combinatorial studies of SD using complementary techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Differences in dose-volumetric data between the analytical anisotropic algorithm and the x-ray voxel Monte Carlo algorithm in stereotactic body radiation therapy for lung cancer

The objective of this study was to evaluate the differences in dose-volumetric data obtained using the analytical anisotropic algorithm (AAA) vs the x-ray voxel Monte Carlo (XVMC) algorithm for stereotactic body radiation therapy (SBRT) for lung cancer. Dose-volumetric data from 20 patients treated with SBRT for solitary lung cancer generated using the iPlan XVMC for the Novalis system consisting of a 6-MV linear accelerator and micro-multileaf collimators were recalculated with the AAA in Eclipse using the same monitor units and identical beam setup. The mean isocenter dose was 100.2% and 98.7% of the prescribed dose according to XVMC and AAA, respectively. Mean values of the maximal dose (D{sub max}), the minimal dose (D{sub min}), and dose received by 95% volume (D{sub 95}) for the planning target volume (PTV) with XVMC were 104.3%, 75.1%, and 86.2%, respectively. When recalculated with the AAA, those values were 100.8%, 77.1%, and 85.4%, respectively. Mean dose parameter values considered for the normal lung, namely the mean lung dose, V{sub 5}, and V{sub 20}, were 3.7 Gy, 19.4%, and 5.0% for XVMC and 3.6 Gy, 18.3%, and 4.7% for the AAA, respectively. All of these dose-volumetric differences between the 2 algorithms were within 5% of the prescribed dose. The effect of PTV size and tumor location, respectively, on the differences in dose parameters for the PTV between the AAA and XVMC was evaluated. A significant effect of the PTV on the difference in D{sub 95} between the AAA and XVMC was observed (p = 0.03). Differences in the marginal doses, namely D{sub min} and D{sub 95}, were statistically significant between peripherally and centrally located tumors (p = 0.04 and p = 0.02, respectively). Tumor location and volume might have an effect on the differences in dose-volumetric parameters. The differences between AAA and XVMC were considered to be within an acceptable range (<5 percentage points)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

A comparison between anisotropic analytical and multigrid superposition dose calculation algorithms in radiotherapy treatment planning

Monte Carlo (MC) simulation is currently the most accurate dose calculation algorithm in radiotherapy planning but requires relatively long processing time. Faster model-based algorithms such as the anisotropic analytical algorithm (AAA) by the Eclipse treatment planning system and multigrid superposition (MGS) by the XiO treatment planning system are 2 commonly used algorithms. This study compared AAA and MGS against MC, as the gold standard, on brain, nasopharynx, lung, and prostate cancer patients. Computed tomography of 6 patients of each cancer type was used. The same hypothetical treatment plan using the same machine and treatment prescription was computed for each case by each planning system using their respective dose calculation algorithm. The doses at reference points including (1) soft tissues only, (2) bones only, (3) air cavities only, (4) soft tissue-bone boundary (Soft/Bone), (5) soft tissue-air boundary (Soft/Air), and (6) bone-air boundary (Bone/Air), were measured and compared using the mean absolute percentage error (MAPE), which was a function of the percentage dose deviations from MC. Besides, the computation time of each treatment plan was recorded and compared. The MAPEs of MGS were significantly lower than AAA in all types of cancers (p<0.001). With regards to body density combinations, the MAPE of AAA ranged from 1.8% (soft tissue) to 4.9% (Bone/Air), whereas that of MGS from 1.6% (air cavities) to 2.9% (Soft/Bone). The MAPEs of MGS (2.6%±2.1) were significantly lower than that of AAA (3.7%±2.5) in all tissue density combinations (p<0.001). The mean computation time of AAA for all treatment plans was significantly lower than that of the MGS (p<0.001). Both AAA and MGS algorithms demonstrated dose deviations of less than 4.0% in most clinical cases and their performance was better in homogeneous tissues than at tissue boundaries. In general, MGS demonstrated relatively smaller dose deviations than AAA but required longer computation time.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2018

FIER: Software for analytical modeling of delayed gamma-ray spectra

We report a new software package, the Fission Induced Electromagnetic Response (FIER) code, has been developed to analytically predict delayed γ-ray spectra following fission. FIER uses evaluated nuclear data and solutions to the Bateman equations to calculate the time-dependent populations of fission products and their decay daughters resulting from irradiation of a fissionable isotope. These populations are then used in the calculation of γ-ray emission rates to obtain the corresponding delayed γ-ray spectra. FIER output was compared to experimental data obtained by irradiation of a 235 U sample in the Godiva critical assembly. This investigation illuminated discrepancies in the input nuclear data libraries, showcasing the usefulness of FIER as a tool to address nuclear data deficiencies through comparison with experimental data. Finally, FIER provides traceability between γ-ray emissions and their contributing nuclear species, decay chains, and parent fission fragments, yielding a new capability for the nuclear science community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

$\mathrm{REX}$: An analytical tool for reactor operating envelope expansion through fuel-clad thermo-mechanics

Here REX, an analytical reactor design tool for the identification and expansion of reactor operating envelopes, is introduced and detailed. Written in MATLAB, REX takes core geometries and axially discretized detector and depletion output from the Serpent neutron transport code and performs full-core, pin-specific thermal-hydraulic and thermo-mechanical calculations. REX identifies the operating envelopes of advanced, solid-fuel nuclear reactors on the basis of their fuel-cladding, fuel-gas, and coolant-cladding interfacial thermo-mechanics. It iteratively pushes coolant inlet temperatures and modifies fuel pin geometries to induce mechanical failure in their original cladding materials at the fullest extent of their fuel cycle lengths and permissible coolant inlet temperatures. It then attempts to expand their operating envelopes by determining the mechanical responses of alternative cladding materials under the same geometric conditions. The result of the REX calculation sequence is a set of 5-D variables describing the temperatures, pressures, geometries, and mechanics of the core as functions of assembly, fuel pin, axial zone, depletion step, and coolant inlet temperature for each candidate cladding material with the limiting fuel pin geometry for the original material.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Universality driven analytic structure of QCD crossover: radius of convergence and QCD critical point

Recent lattice QCD calculations show strong indications that the crossover of QCD at zero baryon chemical potential (µB) is a remnant of the second order chiral phase transition. The non-universal parameters needed to map temperature T and µ B to the universal properties of the second order chiral phase transition were determined by lattice QCD calculations. Motivated by these advances, first, we discuss the analytic structure of the partition function - the so-called Yang-Lee edge singularity - in the QCD crossover regime, solely based on universal properties. Then, utilizing the lattice calculated non-universal parameters, we map this singularity to the real T and complex µ B plane, in order to find the radius of convergence for a Taylor series expansion of QCD partition function around µ B = 0 in the QCD crossover regime. Our most important findings are: (i) An universality-based estimate of the radius of convergence around µ B = 0; (ii) Universality and lattice QCD based constraints on the location of the QCD critical point in the T - µ B plane.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Simple analytical model for fitting QENS data from liquids

The advent of new generation of neutron spectrometers for quasielastic scattering measurements has demonstrated the need for multi-component (at least two-component) fitting of data collected from liquids. The narrowest component is associated with long-range translational diffusion, whereas the broader component originates from localized center-of-mass motions in the transient cage of the nearest neighbors. Intra-particle dynamics (e.g., of molecular side groups) may give rise to additional components besides the center-of-mass motions. We present a simple analytical model for two-component fits of quasielastic neutron scattering data collected from liquids. Here, the use of such models is optional (albeit helpful) in the traditional approach, where fits are performed sequentially and independently for the data collected at separate Q values, but imperative in the global fitting, where the data are fitted simultaneously at all Q values, which may be necessary to rationalize the data from increasingly complex systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Approximate analytic solutions to coupled nonlinear Dirac equations

Here, we consider the coupled nonlinear Dirac equations (NLDEs) in 1+11+1 dimensions with scalar–scalar self-interactions g 1 2 /2($\bar{ψ}$ψ) 2 + g 2 2 /2($\bar{Φ}$Φ) 2 + g 2 3 ($\bar{ψ}$ψ)($\bar{Φ}$Φ) as well as vector–vector interactions g 1 2 /2($\bar{ψ}$γμψ)($\bar{ψ}$γμψ) + g 2 2 /2($\bar{Φ}$γμΦ)($\bar{Φ}$γμΦ) + g 2 3 ($\bar{ψ}$γμψ)($\bar{Φ}$γμΦ). Writing the two components of the assumed rest frame solution of the coupled NLDE equations in the form ψ=e –iω1t R 1 cosθ,R 1 sinθΦ=e –iω2t R 2 cosη,R 2 sinη, and assuming that θ(x),η(x) have the same functional form they had when g3 = 0, which is an approximation consistent with the conservation laws, we then find approximate analytic solutions for Ri(x) which are valid for small values of g 3 2 /g 2 2 and g 3 2 /g 1 2 . In the nonrelativistic limit we show that both of these coupled models go over to the same coupled nonlinear Schrödinger equation for which we obtain two exact pulse solutions vanishing at x → ±∞.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

A comparison of numerical and analytical predictions of the tidal stream power resource of Massachusetts, USA

The coastal waters of Massachusetts, USA encompass tidal phenomena that generate flows of sufficient magnitude for commercially viable power extraction. Here we examine the tidal power resource of the Massachusetts coastal region with two high-resolution hydrodynamic tidal models: a regional model encompassing the coastal waters of southeastern New England and a local domain model of Cape Cod Canal. Both models have been subject to comprehensive skill assessment using available surface elevation and ADCP measurements. Based on the model results, we identify five high-energy sites (Cape Cod Canal, Muskeget Channel, Quicks Hole, Robinson Hole and Woods Hole) for evaluation of the maximum extractable tidal power. The power extraction at these sites is modeled using linear momentum actuator disk theory applied to a cross-channel array of turbines. Of the sites evaluated, Muskeget Channel has the greatest resource, with an estimated maximum extractable power of 24 MW. The estimated total power available from all five sites is 44 MW. These estimates agree within 21% with predictions from analytical approaches at all sites. Potential applications for the models include: providing developers with an initial assessment of the resource, guiding observation programs for further study of the resource, and facilitating optimization of turbine array design.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

A Three-Dimensional, Analytical Wind Turbine Wake Model: Flow Acceleration, Empirical Correlations, and Continuity

A new, three-dimensional, analytical, steady-state wake model is presented that includes local flow acceleration near the rotor, improving the wake description compared to existing models. Wake structures such as the momentum deficit and regions of accelerated flow are concisely described with compound and normal Gaussian functions. Large-eddy simulations (LES) are used as training data to develop the model using two in-line turbines under various inflow conditions parameterized by hub-height wind speed and turbulence intensity. Mass conservation is considered by fixing two components of the wake velocity model and optimizing the third to best satisfy continuity; after which, the model performs comparably if not better than existing work with regards to both relative error and mass consistency. The final model demonstrates a high degree of flexibility, making use of empirical correlations to scale across different inflow conditions. The inclusion of these effects is capable of revealing unused opportunities for enhanced power generation by aligning wake trajectories with these regions of accelerated flow.

modeling↗
DOE OSTI2024

Analytical Tools to Assess Polymer Biodegradation: A Critical Review and Recommendations

Many petroleum-derived plastic materials are highly recalcitrant and persistent in the environment, posing significant threats to human and ecological receptors due to their accumulation in ecosystems. In recent years, research efforts have focused on advancing biological methods for polymer degradation. Enzymatic depolymerization has emerged as particularly relevant for biobased plastic recycling, potentially scalable for industrial use. Biodegradation involves adsorption to the plastic solid surface, followed by an interfacial reaction, resulting in cleavage of bonds of polymer chains exposed on the surface. Here, widely varying substrate-specific kinetics are observed, with the polymer’s properties possessing a significant impact on the rate of this interfacial catalysis. Thus, there is a critical need for sensitive and accurate characterization of the material surface during and after interfacial depolymerization to fully understand the reaction mechanisms. Here, we provide a critical review of a range of techniques used in the analysis of material surfaces to characterize the chemical, topological, and morphological features relevant to the study of enzymatic biocatalysis, including microscopy techniques, spectroscopic techniques (e.g., X-ray diffraction analysis, Fourier transform infrared attenuated total reflectance spectroscopy, and mass spectrometry detection of analytes associated with degradation). Techniques for evaluation of surface energy and topology in their relevancy for sensitive detection of biological surface modifications are also discussed. In addition, this paper provides an overview of the strengths of these techniques and compares their performance in both sensitivity and throughput, including emerging techniques, which can be useful, particularly for the rapid analysis of the surface properties of polymeric materials in high-throughput screening of candidate biocatalysts. This research serves as a starting point in selecting and applying appropriate methodologies that provide direct evidence to the ongoing biotic degradation of polymeric materials.

Colachis, Matthew↗