Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Analysis Tool”

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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Tool Kit for Generating Simulated Radiation Measurements for Advanced Reactor Safeguards and Security

A tool kit was developed to simulate and analyze passive radiation measurements of molten salt reactor (MSR) operations to support development of nuclear safeguards approaches for this emerging reactor technology. A Transient Simulation Framework of Reconfigurable Modules (TRANSFORM) multiphysics simulation of an MSR produces time-dependent isotopic inventories at user-selected locations within the model. The tool kit implements the Gamma Detector Response and Analysis Software (GADRAS) application programming interface to inject the TRANSFORM isotopic inventories extracted/processed by a Python pipeline into GADRAS models of user-defined geometries. The TRANSFORM inventories are the source terms used to obtain synthetic measurements from GADRAS-defined detectors. The speed of TRANSFORM and GADRAS simulations enables surveying the large design space of MSRs (e.g., fuel type, fuel salt composition, number of loops) and the plethora of measurements (e.g., location, detector type, and collimation) within the reactor. This has enabled timely assessment of the various measurement locations and detectors to identify the most effective and efficient safeguards approach for a specific MSR design. Lastly, the tool kit also simulates extracted samples that can be aged to a desired dose, enabling stakeholders to optimize a measurement plan to use sample analysis as an element within a broader material accountancy plan.

Westphal, Greg↗
DOE OSTI2026

Accurate measurement of porosity size and morphology in aluminium alloy laser welds

Conventional two-dimensional optical microscopy is the most common tool for capturing and quantifying keyhole collapse porosity and other defects formed during the laser welding of aluminium alloys. This approach is of limited utility since only a single longitudinal or transverse metallographic cross-section, comprising only a small fraction of the overall weld volume, can be extracted or analysed at a time. X-ray computed tomography tools, on the other hand, enable three-dimensional visualisation and analysis of porosity and defects to be made across the full weld volume. When comparing these two measurement techniques, two-dimensional microscopy tools significantly underestimated the fraction of defects present within the weld at levels between 50% and 80%. Three-dimensional x-ray computed tomography tools also provide a means for accurately characterising the location, size and morphology of irregularly shaped defects. By categorising the defect shapes using a Zingg's shape analysis, in which the distribution of defect morphologies could be quantified as disk, rod and spherical shapes, a transition in defect morphology moving from stationary beam to oscillating beam welds was detected and quantified.

36 MATERIALS SCIENCE↗
DOE OSTI2022

NPD Classification Tools – User Guide NPD Explorer and NPDamCAT Apps

The existing infrastructure at non-powered dams (NPDs) presents a variety of opportunities from generating electricity and economic value to the myriad services they provide. However, it also presents a significant challenge because aging structures must be maintained, and changes to the ecosystems and river systems by NPDs must be managed. The various stakeholders interested in these opportunities and challenges require varying information about NPDs; in many cases, interest in NPDs can extend across the entire population of dams. Even when interest is more narrowly focused on an individual dam or a small subset of dams, understanding how these dams relate to the broader context of NPD infrastructure can be important. As noted in TM 2021/2155, “Each NPD has unique characteristics describing its design, operation, environmental impacts, social impacts, and economic potential. The large number of dams, the diversity of interests related to dams, the variety of dam characteristics, and the types of data required to describe dams all pose major challenges to an analysis of the entire dam population." This user guide describes two web-based tools that facilitate exploration of dams from a variety of perspectives: the NPD Explorer and the NPD Custom Analysis and Taxonomy (NPDamCAT). These tools facilitate access to information about dams and help users interact with the information, making small- to large-scale analyses more convenient for a broad set of stakeholders.

13 HYDRO ENERGY↗
DOE OSTI2025

Open-Source and FAIR Research Software for Proteomics

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

SIMS Analysis of d18O and d13C of Carbonate Cements in Shale & Mudstone. Final report

This project has had two primary goals: 1) improving new technology for in situ microanalysis of stable isotope ratios by SIMS (secondary ion mass spectrometry) and 2) evaluating the importance of in situ analysis for studies of carbonate cements within shales of the Bakken Petroleum System. The systematic relations of stable isotope ratios provide an important tool to help resolve critical questions in geology. Stable isotope analysis of carbonate cements in shale constrain many topics of interest to DOE including: CO2 sequestration, climate change, and the genesis and quality of rock reservoirs for petroleum, natural gas, and water. However, this evidence is often preserved as fine-scale zonation, which is homogenized by conventional bulk analysis of powders. Recently, analysis of ultra-small spots in polished samples at the University of Wisconsin WiscSIMS Lab. has documented stable isotope zoning in carbonates and other diagenetic cements at smaller scales than previously possible. We have made detailed studies of oxygen and carbon isotope ratios in diagenetic cements from shales of the Bakken Formation from the Williston basin and elsewhere. The Bakken contains both reservoir and source rocks for petroleum. Hydrofracturing has greatly enhanced production of oil in these tight reservoirs. The sediments contain zoned carbonate cements with growth textures that record multiple events. The growth of carbonate (dolomite) cements has been proposed to control reservoir quality, but previous stable isotope studies of homogenized powders could not resolve individual generations of cement and this proposal remains untested. Our better characterization of the multiple growth zones in these carbonates will aid in understanding the genesis of these tight reservoirs and the production of unconventional oil and gas. This study has also developed SIMS standards for analysis of all compositions of Ca-Mg-Fe carbonate and selected Mn-carbonates and hydromagnesite. We have refined techniques for improved accuracy of SIMS stable isotope analysis, and for sub-1-micron spot sizes. We have established protocols for mapping and correlating sample analyses at micron-scale using QGIS software.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2022

Software Verification Toolkit (SVT): Survey on Available Software Verification Tools and Future Direction

Writing software is difficult. However, writing complex, well tested and designed, and functionally correct software is incredibly difficult. An entire field of study is devoted to the validation and verification of software to address this problem, and in this paper we analyze the landscape of currently available third party software. We have divided our analyses into three separate subsections with regards to software validation: formal methods, static analysis, and test generation. Formal verification is the most complex method in which to validate software correctness, but also the most thorough as it truly validates the mathematical validity of the source code. Static analysis generally is relegated to abstract syntax tree traversal techniques to find errors related to faulty software such as memory leaks or stack overflow issues. Automatic test generation is similar in implementation to static analysis, but pushes a bit further in verifying the boundedness of function inputs and outputs with regards to annotated or parsed criteria. The crux of this report is to analyze and describe the software tools that implement these techniques to validate and verify software. Pros and cons related to installation, utilization, and capabilities of the frameworks are described, and reproducible examples are provided with a focus on usability. The initial survey concluded that the most interesting tools of note are Z3, Isabelle/HOL, and TLA+ with regards to formal verification; and Infer, Frama-C, and SonarQube with regards to static analysis. With these tools in mind, a final conjecture is provided that describes future avenues of utilizing these tools for developing a verification framework to assist in validating existing software at Sandia National Laboratories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Reflectometry with Polarized Neutrons on In Situ Grown Thin Films

Originating from the demand for obtaining depth-resolved magnetization profiles from thin films and heterostructures, polarized neutron reflectometry (PNR) has developed into a unique research tool, which also finds application in the analysis of superconducting or soft matter thin films. While certain in situ sample environments such as gas-loading or humidity cells were quickly realized after PNR first emerged, preparing and growing thin magnetic films directly in the neutron beam could only be realized in recent years. Herein, a dedicated insight is given on the history and development of in situ thin film growth capabilities for PNR, from early pioneering experiments to the present day. The scientific and technological challenges as well as the advances of neutron sources, neutronics, and data treatment that have led to its realization are highlighted together with the unique research opportunities that it provides and recently obtained experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV- 2 main protease

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) approaches followed by experimental validation. Generative deep learning models have been recently developed that can generate thousands of new candidates, but their physiochemical properties are typically not optimized. Using our deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 M pro that preserve the core scaffold. Here we utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure–activity relationships, multi-parameter optimization, and graph neural networks on libraries of generated candidates to predict biological activity and binding affinity a priori. From these collective computational results, eight promising candidates were identified and tested experimentally using Native Mass Spectrometry (MS) and FRET-based functional assays. Two compounds, with quinazoline-2-thiol and acetylpiperidine core moiety showed IC 50 values in the low micromolar range: 2.95±0.0017 µM and 3.41±0.0015 µM, respectively. The molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations in the chain B and the interface domains of the M pro . The key fragments from these top hits can be used as input for closed loop lead optimization in the integrated pipeline.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Dendritic cells focus CTL responses toward highly conserved and topologically important HIV-1 epitopes

During early HIV-1 infection, immunodominant T cell responses to highly variable epitopes lead to the establishment of immune escape virus variants. Here we assessed a type 1-polarized monocyte-derived dendritic cell (MDC1)-based approach to selectively elicit cytotoxic T lymphocyte (CTL) responses against highly conserved and topologically important HIV-1 epitopes in HIV-1-infected individuals from the Thailand RV254/SEARCH 010 cohort who initiated antiretroviral therapy (ART) during early infection (Fiebig stages I-IV). Autologous MDC1 were used as antigen presenting cells to induce in vitro CTL responses against HIV-1 Gag, Pol, Env, and Nef as determined by flow cytometry and ELISpot assay. Ultra-conserved or topologically important antigens were respectively identified using the Epigraph tool and a structure-based network analysis approach and compared to overlapping peptides spanning the Gag proteome. MDC1 presenting either the overlapping Gag, Epigraph, or Network 14-21mer peptide pools consistently activated and expanded HIV-1-specific T cells to epitopes identified at the 9-13mer peptide level. Interestingly, some CTL responses occurred outside known or expected HLA associations, providing evidence of new HLA-associated CTL epitopes. Comparative analyses demonstrated more sequence conservation among Epigraph antigens but a higher magnitude of CTL responses to Network and Gag peptide groups. Importantly, CTL responses against topologically constrained Gag epitopes contained in both the Network and Gag peptide pools were selectively enhanced in the Network pool-initiated cultures. Our study supports the use of MDC1 as a therapeutic strategy to induce and focus CTL responses toward putative fitness-constrained regions of HIV-1 to prevent immune escape and control HIV-1 infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Exploring MDSplus data-acquisition software and custom devices

MDSplus is a software tool designed for data acquisition, storage, and analysis of complex scientific experiments. Over the years, MDSplus has primarily been used for data management for fusion experiments. This paper demonstrates that MDSplus can be used for a much wider variety of systems and experiments. We present a step-by-step tutorial describing how to create a simple experiment, manage the data, and analyze it using MDSplus and Python. To this end, a custom example device was developed to be used as the data source. This device was built on an open-source electronic hardware platform, and it consists of a microcontroller and two sensors. Finally, we read data from these sensors, store it in MDSplus, and use JupyterLab to visualize and process it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Radiocesium ( 137 Cs) concentrations in the two-toed amphiuma (Amphiuma means) and the lesser siren (Siren intermedia)

This study sought to determine radiocesium ( 137 Cs) concentrations in two species of aquatic salamanders – the two-toed amphiuma (Amphiuma means) and the lesser siren (Siren intermedia) on the Savannah River Site. Concentrations ( 137 Cs Bq/g, dry wt) of the two species were similar at both 137 Cs-contaminated (A. means = 0.733 ± 0.242, n = 5; S. intermedia = 0.839 ± 0.722, n = 5) and reference sites (A. means = 0.028 ± 0.020, n = 5; S. intermedia = 0.042 ± 0.027, n = 11). Salamanders captured in areas impacted by 137 Cs contamination exhibited significantly higher 137 Cs concentrations than individuals captured at reference sites (U = 146, p < 0.001). Salamander size (snout-vent length) was not correlated with whole-body 137 Cs. An analysis of our data using the ERICA tool suggests that negative impacts due to 137 Cs exposure are unlikely in these species. Overall, these data indicate that A. means and S. intermedia inhabiting contaminated sites bioaccumulate but do not biomagnify 137 Cs.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗
DOE OSTI2020

Numerical Simulation and Experimental Validation of Joint Performance in Aluminum-Steel Lap Welds Formed by Friction Stir Dovetailing

Friction stir dovetailing (FSD) is a new dissimilar material joining process that simultaneously forms a mechanical interlock and metallurgical bond at the dissimilar material interface. This work presents development of a modeling and simulation approach to predict mechanical performance of FSD thick section aluminum to steel joints. A finite element analysis (FEA) was carried out in order to predict the load-carrying capacity and failure location for aluminum thicknesses between 12.7 mm and 50.8 mm with different numbers of dovetails. The numerical results and corresponding experimental investigation are in agreement and suggest that the developed methods can be used effectively for design and analysis of FSD joints using standard FEA tools.

Friction stir dovetailing, Friction stir welding, ↗
DOE OSTI2022

An improved pressure drop correlation for modeling localized effects in a pebble bed reactor

Advances in the development of pebble bed reactors (PBRs) has created a desire for accurate and cost-effective simulation tools for design scoping studies and safety analysis. The current state-of-the-art for these simulations is the use of porous media models, although these models rely on correlations to capture the effects of flow features that are not explicitly modeled. One of the areas where correlation accuracy is currently lacking is in the near-wall region of the bed. In this region, the presence of the wall causes the pebbles to pack more orderly, drastically changing the geometry and flow behavior in this region. This work presents a new generalized pressure drop correlation for PBRs based on the KTA equation. A high-to-low methodology is applied, where large eddy simulation (LES) is performed on two beds of 1568 and 1700 pebbles to generate a high-fidelity dataset. The flow fields are then averaged in time and separated into concentric rings of 0.05 D peb width. Average porosity, velocity, and pressure drop are extracted for each ring and the friction and form losses are calculated. The Reynolds number range for this study is 625–10,000, and thus the form losses are dominant over the friction losses. The form losses across the rings are investigated, and a correction term for the form loss calculation is determined and applied to the KTA equation to drastically improve the capability of modeling localized porosity effects in a porous media code. Finally, the improved correlation reduces near-wall velocity prediction error from over 50% with the KTA correlation to around 5%. Agreement in pressure drop prediction between LES and porous media simulations is also improved.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Convective heat transfer and friction factor characteristics of molten salts in spirally fluted tubes

Spirally fluted tubes have been widely used for heat exchangers due to their superior heat transfer enhancement. However, most of the previous studies focused on the effects of a limited number of geometric parameters, i.e., the flute pitch and flute depth, on convective heat transfer and friction factor characteristics of low-Prandtl-number fluids, i.e., air and water. The correlations developed in these studies may not be accurate or applicable for medium-Prandtl-number fluids, such as molten salts. A numerical analysis using a Computational Fluid Dynamics (CFD) tool, STAR–CCM+, is therefore carried out in this study to systematically investigate the effects of four geometric parameters, including the flute pitch ρ, flute depth e, flute start number N s (or flute helix angle θ), and trough length L tr on convective heat transfer and friction factor characteristics of a medium-Prandtl-number fluid, FLiNaK (46.5LiF-11.5NaF-42KF mol %), in spirally fluted tubes. Additionally, the convective heat transfer and Darcy friction factor correlations are proposed and validated, with ± 20% uncertainties, for medium-Prandtl-number fluids under the following conditions: Re = 88–1600, Pr = 2.5–40, ρ/D c = 0.44–3.51, e/D c = 0.10–0.40, θ/90= 0.20–0.81, and L tr /D c = 0.71–2.16. The correlations proposed help improve the design of spirally fluted-tube heat exchangers.

42 ENGINEERING↗
DOE OSTI2025

Predicting Large‐Scale Systematic Missing Pipe Attributes in Water Distribution Networks

Water distribution network (WDN) models are an essential tool used by water utilities for hydraulic analysis. Unfortunately, missing data and insufficient resources often make creating and maintaining these models unfeasible. Existing methods to address missing pipe properties, like sequential imputation for missing values and reconstruction using graph metrics, are designed to accommodate random patterns of missing information and require a significant percentage of the system's attributes to be known. However, these data completeness assumptions do not always align with real‐world scenarios where large sections of the WDN model have missing data. To address this challenge, this study proposes a data‐driven approach for estimating pipe diameter when considering different spatial patterns and degrees of data completeness (i.e., 0%–90%). Using data from 16 WDNs in Kentucky, this study compares the use of machine learning (ML) using topological and geospatial features against an existing deterministic approach. Results demonstrate that WDN models with pipe diameters predicted by the proposed ML method had comparable hydraulic performance to the ground truth models. Moreover, results showed that ML method performance varies between WDNs of differing topological classification. Insights from this study help advance the ability to leverage partial data to create and maintain WDN models amid uncertainty and inadequate resources.

Poff, Jason W. [Oregon State Univ., Corvallis, OR ↗
DOE OSTI2023

Decomposition of multi-particle azimuthal correlations in Q-cumulant analysis*

Abstract The method of Q -cumulants is a powerful tool for studying the fine details of azimuthal anisotropies in high energy nuclear collisions. This paper presents a new method, based on mathematical induction, to evaluate the analytical form of high-order Q -cumulants. The capability of this method is demonstrated via a toy model that uses the elliptic power distribution to simulate the anisotropic emission of particles, quantified in terms of Fourier flow harmonics . The method can help in studying the large amount of event statistics that can be collected in the future and allow measurements of the very high central moments of the distribution. This can, in turn, facilitate progress in understanding the initial geometry, the input to the hydrodynamic calculations of medium expansion in high energy nuclear collisions, and the constraints on it.

Physics↗
DOE OSTI2019

Radiation-damage investigation of a DNA 16-mer

In macromolecular crystallography, a great deal of effort has been invested in understanding radiation-damage progression. While the sensitivity of protein crystals has been well characterized, crystals of DNA and of DNA–protein complexes have not thus far been studied as thoroughly. Here, a systematic investigation of radiation damage to a crystal of a DNA 16-mer diffracting to 1.8 Å resolution and held at 100 K, up to an absorbed dose of 45 MGy, is reported. The RIDL ( Radiation-Induced Density Loss ) automated computational tool was used for electron-density analysis. Both the global and specific damage to the DNA crystal as a function of dose were monitored, following careful calibration of the X-ray flux and beam profile. The DNA crystal was found to be fairly radiation insensitive to both global and specific damage, with half of the initial diffraction intensity being lost at an absorbed average diffraction-weighted dose, D 1/2 , of 19 MGy, compared with 9 MGy for chicken egg-white lysozyme crystals under the same beam conditions but at the higher resolution of 1.4 Å. The coefficient of sensitivity of the DNA crystal was 0.014 Å 2 MGy -1 , which is similar to that observed for proteins. These results imply that the significantly greater radiation hardness of DNA and RNA compared with protein observed in a DNA–protein complex and an RNA–protein complex could be due to scavenging action by the protein, thereby protecting the DNA and RNA in these studies. In terms of specific damage, the regions of DNA that were found to be sensitive were those associated with some of the bound calcium ions sequestered from the crystallization buffer. In contrast, moieties farther from these sites showed only small changes even at higher doses.

Instruments & Instrumentation↗