Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Tools”

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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Preliminary verification of the MCNP perturbation and fixed-source tally sensitivity tools

Integral benchmark experiments are vital in the adjustment and validation of the nuclear data that govern predictive simulations across the nuclear community. The nuclear data sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®) transport code are currently limited; however, expanding sensitivity capabilities will allow benchmark experiments to be designed to resolve compensating errors and adjust nuclear data where previously prohibitively difficult. This paper provides details of a preliminary verification for the use of (i.) the recently revised perturbation and (ii.) developmental fixed-source sensitivity tools within MCNP to calculate sensitivities of tallied responses (such as current integrated over a surface, F1, and flux averaged over a cell, F4) to nuclear data in fixed-source simulations. Energy-binned and energy-integrated sensitivities calculated with these tools are compared against sensitivities calculated using a central-difference approximation. Here, the verification is completed for four configurations of a benchmarked system using a 4.5-kg plutonium sphere surrounded by varying amounts of copper and/or polyethylene. The results show that sensitivities calculated with the perturbation and fixed-source sensitivity tools agree with the central-difference-based approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

MADHAT: Model-Agnostic Dark Halo Analysis Tool

We present the Model-Agnostic Dark Halo Analysis Tool (MADHAT), a numerical tool which implements a Fermi-LAT data-driven, model-independent analysis of gamma-ray emission from dwarf satellite galaxies and dwarf galaxy candidates due to dark matter annihilation, dark matter decay, or other nonstandard or unknown astrophysics. This tool efficiently provides statistical upper bounds on the number of observed photons in excess of the number expected, based on empirical determinations of foregrounds and backgrounds, using a stacked analysis of any selected set of dwarf targets. It also calculates the resulting bounds on the properties of dark matter under any assumptions the user makes regarding dark sector particle physics or astrophysics. As an application, we determine new bounds on Sommerfeld-enhanced dark matter annihilation in a set of eight dwarfs. MADHAT v1.0 includes 58 dwarfs and dwarf candidate targets, and we discuss future planned developments. MADHAT is available and will be maintained at https://github.com/MADHATdm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Stakeholder perceptions of Environmental Management Plans as an environmental protection tool for major developments in the UK

Insufficient implementation and the lack of legislative requirements for follow-up measures following the approval of projects are consistently highlighted as major shortcomings of Environmental Impact Assessment (EIA). Although adopted over 15 years ago by the World Bank, Environmental Management Plans (EMPs) were only semi-formalised in the UK in 2008 and arguably provide a continuous link or ‘bridge’ between the EIA process pre-consent and an Environmental Management System (EMS) post-consent. Drawing on twenty-one semi-structured interviews with stakeholders and thematic analysis of their responses, and a broad-scale practitioner survey, this study aimed to assess the effectiveness of EMPs as an environmental protection tool across the project lifecycle for major developments. The findings revealed a mixed picture of EMP effectiveness in practice, with EMPs only partially fulfilling a bridging role between EIA and EMS. There is no ‘gold standard’ terminology for EMPs, all having slightly different uses, thus presenting different focuses to different stakeholders and further enhancing variation in practice. For many stakeholders, the effectiveness was simply not known, due to the lack of communication and follow-up that still exists. EMP–EMS linkages were shown to be effective from the developer's perspective when a single organisation has involvement across all project phases, though weaknesses occur when multiple parties are involved. Among other stakeholders, knowledge varied significantly; whilst some were in agreement that the linkages worked, many were unaware of the connections and thought of them as two quite separate tools. Stakeholders advocated for the need to make EMPs a legal requirement; for improved communication between stakeholders during EMP implementation and increased documentation of project outcomes; and for EMPs to be consistently written by environmental professionals. Furthermore, weak links in the current process may be improved by providing detailed guidance for organisations on the potential for EMP–EMS linkages, with the additional aim of encouraging stakeholders to broaden their current specialist knowledge on environmental protection tools. - Highlights: • We assessed the effectiveness of Environmental Management Plans (EMPs) for major developments, focusing on delivery of mitigation and monitoring. • EIA and Environmental Management Systems (EMS) post-consent are weakly linked. • The use of EMPs varies significantly in practise, partly due to the range of terminology used. • Linkages are hampered by poor communication and follow-up • More detailed guidance on how EMPs can successfully link with EMS is required.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Overcoming low EIA performance - A diagnostic tool for the deliberate development of EIA system capacities in low and middle income countries

Highlights: • A tool for rapid assessment of EIA performance is presented. • The tool focusses on EIA systems in low and middle income countries. • This tool aims to enhance the capacities of the main EIA organizations. • Mechanisms are identified to maintain and further develop the enhanced capacities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Bayes_Opt-SWMM: A Gaussian process-based Bayesian optimization tool for real-time flood modeling with SWMM

Real-time flood model plays a pivotal role in averting urban flood damage, particularly when there is minimal lead time for preparatory measures. However, urban flood modeling in real-time often contends with inherent uncertainties arising from input data uncertainty and parameter ambiguities. Here this study introduces a real-time calibration (RTC) tool called Bayes_Opt-SWMM, specifically tailored for real-time urban flood modeling and uncertainty optimization. This tool leverages the Gaussian process-based Bayesian optimization algorithm and interfaces seamlessly with the Stormwater Management Model (SWMM). It integrates real-time model forcing data and flood monitoring collected through sensors and gauges which are strategically placed within critical locations of urban drainage systems. Our approach hinges on the Surrogate Model based Uncertainty Optimization (SMUO) concept, providing an avenue for enhancing real-time flood modeling. Bayes_Opt-SWMM runs the optimization process using a surrogate model called Gaussian Process emulator with two inference methods: (1) the Gaussian Process (GP) model and (2) Markov Chain Monte Carlo (MCMC) algorithm in GP model (GP_MCMC). Furthermore, three acquisition functions, namely Expected Improvement (EI), Maximum Probability of Improvement (MPI), and Lower Confidence Bound (LCB), facilitate optimal parameter fitting within the surrogate models. The efficiency of GP-based surrogate models in learning SWMM model parameters, leads to an improved uncertainty quantification and accelerated real-time flood modeling in urban areas. Overall, Bayes_Opt-SWMM emerges as a cost-effective and valuable tool for real-time flood modeling and monitoring, with significant potential for managing intelligent storm water systems in urban environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A tool for assessing demand side management and operating strategies for isolated microgrids

Globally, power system operators are exploring ways to leverage the capabilities of smart meters to implement fine-grained demand side management (DSM). Here this paper presents a new simulation tool to evaluate operating strategies for smart-meter-enabled (SME) islanded microgrids being advanced for sustainable rural electrification in emerging economies. Based on MATLAB/Simulink, the tool's component-level models of small microgrids can be easily configured. Alternative rule-based operating strategies are implemented with controllable supply and storage components as well as other components driven by external factors (e.g., weather and time of day). To account for the wide range of possible operating conditions in real-world applications, statistical metrics can be evaluated using Monte Carlo (MC) methods based on user-defined, time-dependent probability distributions for demands, supplies, and environmental variables. Features of the tool are demonstrated with case studies for a representative microgrid in rural Rwanda.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

πScope: Python based scientific workbench with MDSplus data visualization tool

In this work, a newly developed python based scientific data analysis and visualization tool, πScope (http://piscope.psfc.mit.edu), is reported. The primary motivation is 1) to provide an updated tool to browse the MDSplus data beyond existing dwscope/jScope and 2) to realize a universal foundation to construct interface tools to perform computer modeling from experimental data. To visualize MDSplus data, πScope has many features including overplotting different signals and discharges, generating various plot types (line, contour, image, etc.), performing in-panel data analysis using python scripts, and producing publication quality graphics. The logic to generate multi-panel plots is designed to be backward compatible with dwscope, enabling smooth migration for users. πScope uses multi-threading in data loading, and is easy to modify and expand due to its object-oriented design. Furthermore, A user can access the data structure both from a GUI and a script, enabling relatively complex data analysis workflow built quickly on πScope.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

MITgcm-AD v2: Open source tangent linear and adjoint modeling framework for the oceans and atmosphere enabled by the Automatic Differentiation tool Tapenade

The Massachusetts Institute of Technology General Circulation Model (MITgcm) is widely used by the climate science community to simulate planetary atmosphere and ocean circulations. A defining feature of the MITgcm is that it has been developed to be compatible with an algorithmic differentiation (AD) tool, TAF, enabling the generation of tangent-linear and adjoint models. These provide gradient information which enables dynamics-based sensitivity and attribution studies, state and parameter estimation, and rigorous uncertainty quantification. Importantly, gradient information is essential for computing comprehensive sensitivities and performing efficient large-scale data assimilation, ensuring that observations collected from satellites and in-situ measuring instruments can be effectively used to optimize a large uncertain control space. As a result, the MITgcm forms the dynamical core of a key data assimilation product employed by the physical oceanography research community: Estimating the Circulation and Climate of the Ocean (ECCO) state estimate. Although MITgcm and ECCO are used extensively within the research community, the AD tool TAF is proprietary and hence inaccessible to a large proportion of these users. The new version 2 (MITgcm-AD v2) framework introduced here is based on the source-to-source AD tool Tapenade, which has recently been open-sourced. Another feature of Tapenade is that it stores required variables by default (instead of recomputing them) which simplifies the implementation of efficient, AD-compatible code. The framework has been integrated with the MITgcm model’s main branch and is now freely available.

Adjoints↗
DOE OSTI2019

Risk-based monitoring designs for detecting CO 2 leakage through abandoned wellbores: An application of NRAP’s WLAT and DREAM tools

We report that one suggested approach to managing the risk of geologic CO 2 storage projects is to perform risk-based subsurface monitoring targeting early leak detection. The challenge in risk-based monitoring is that leakage impacts are expected to be small in comparison with the footprint of the stored CO 2 plume and could be at depths ranging from the depth of storage (often ~1 km bgs) up to surficial aquifers. Addressing this challenge requires a multidisciplinary effort capable of characterizing potential subsurface leakage in terms of likelihood, location, magnitude, impacts to overlying aquifers, and uncertainty as well as innovative monitoring technology design and implementation. The National Risk Assessment Partnership (NRAP) was established to develop related risk assessment tools to provide guidance on such assessments. Here we demonstrate the application workflow of two of the NRAP computational tools, WLAT (Wellbore Leakage Analysis Tool) and DREAM (Designs for Risk Evaluation and Management), to a hypothetical CO 2 storage site based on a study area in the Midwestern United States. This workflow shows how CO 2 leakage may be estimated, evaluated, and monitored in terms of risk. Results provide guidance on monitoring configurations and technologies which minimize the time to leak detection, maximize the probability detection, and provide cost considerations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Qualitative Evaluation of a Novel 3D Volumetric Radiotherapy Segmentation Tool

A novel 3D volumetric segmentation tool allows the user to outline using a small number of points on a range of planes. Unique 3D volumetric “sculpting” tools enable editing of the resulting structures across multiple slices concurrently. This article reports the results of radiation oncologists' preclinical evaluation of the tool.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Evolution of carbides in cold-work tool steels

This study aimed to present the complete history of carbide evolution in a cold-work tool steel along its full processing route for fabrication and application. A sequence of processes from cast to final hardening heat treatment was conducted on an 8% Cr-steel to reproduce a typical commercial processing route in a small scale. The carbides found at each process step were then identified by electron diffraction with energy dispersive spectroscopy in a scanning or transmission electron microscope. After solidification, MC, M{sub 7}C{sub 3} and M{sub 2}C carbides were identified and the last one dissolved during hot compression at 1180 °C. In a subsequent annealing at 870 °C followed by slow cooling, M{sub 6}C and M{sub 23}C{sub 6} were added, while they were dissolved in the following austenitization at 1030 °C. After the final tempering at 520 °C, fine M{sub 23}C{sub 6} precipitated again, thus the final microstructure was the tempered martensite with MC, M{sub 7}C{sub 3} and M{sub 23}C{sub 6} carbide. The transient M{sub 2}C and M{sub 6}C originated from the segregation of Mo and finally disappeared due to attenuated segregation and the consequent thermodynamic instability. - Highlights: • The full processing route of a cold-work tool steel was simulated in a small scale. • The carbides in the tool steel were identified by chemical–crystallographic analyses. • MC, M{sub 7}C{sub 3}, M{sub 2}C, M{sub 6}C and M{sub 23}C{sub 6} carbides were found during the processing of the steel. • M{sub 2}C and M{sub 6}C finally disappeared due to thermodynamic instability.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Microstructure and mechanical behavior of hot-work tool steels processed by Selective Laser Melting

Highlights: • H11 and a modified H11 hot work tool steels have been produced by SLM. • As-built alloys are characterized by α-Fe cells surrounded by C-rich γ-Fe regions. • Rapidly solidified structures revealed able to respond to precipitation hardening. • Mechanical behavior of AM H11 is similar to that obtained by conventional processes. - Abstract: The present study is aimed at identifying and testing high-strength alloys for tooling applications featuring suitable processability for laser-based additive manufacturing technologies. The microstructure and mechanical properties of the H11 hot-work tool steel and a leaner version of the same alloy (L-H11) processed by Selective Laser Melting were assessed as a function of specific microstructural conditions obtained by performing different heat treatments. Tempering was performed on quenched alloys or simply from as built material. The rapidly solidified microstructures revealed able to respond directly to precipitation hardening treatment without performing any prior solution annealing. The microstructure of the as-built alloys revealed characterized by α-Fe dendritic cells decorated at boundaries by C-rich γ-Fe regions. Air quenching was responsible for the transformation of the solidification cells into lath martensitic structures and for the formation of the M{sub 3}C phase, which transformed into more complex carbide species on tempering. The hardness of quenched and tempered H11 steel is similar to that obtained by processing the alloy with conventional routes, and the final hardness gap between the two SLM processed H11 and L-H11 alloys treated according to optimal tempered condition was limited to 62 HV.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Additive manufacturing of cobalt-based alloy on tool steel by directed energy deposition

Cladding hard-surfacing alloys on tool steel is an effective approach to enhance the surface properties of tool steel. In this study, a Co-based alloy was deposited on tool steel by Directed Energy Deposition (DED) following a three-factor three-level design of experiment matrix with varied laser power, scan speed, and powder flow rate. The microstructure of the deposits was characterized using scanning electron microscopy (SEM). The residual stress on the surface of the samples was measured by the X-ray diffraction (XRD) sin2? technique. The parameters that produced promising deposits were used to fabricate samples for tensile test, four-point bending test, Charpy impact test, and hardness measurement. Our result reveals that the processing parameters have a significant role in the residual stress of the coatings. Residual stress reduces with the increase of laser energy density. Cracks were found at samples with energy density below a threshold. Tensile testing of the coating/substrate combined structure reveals fracture at the coatings with an ultimate tensile strength of 633.9 ± 54.7 MPa. The bi-material interface survived the tensile test, indicating a strong interfacial bond. The four-point bending test of coating/substrate laminates shows an ultimate flexure strength of 860.6 ± 36.9 MPa. Cracks initiated from the coatings ignored the interface and penetrated the substrate, suggesting a solid bi-material bond. Charpy impact test shows the absorbed energy of coating/substrate laminates is more than doubled that of the substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Review and status of tool tip frequency response function prediction using receptance coupling

This paper provides a chronological review of publications that implement and advance the receptance coupling substructure analysis (RCSA) approach first applied to tool tip receptance (or frequency response function) prediction for milling applications in 2000. The review topics mimic the RCSA approach, where the tool, holder, and spindle-machine receptances are coupled analytically, and include: tool-holder receptance modeling; connection modeling; spindle-machine receptances; and applications. The review paper summarizes contributions from multiple, international authors (198 papers) to these topics. Additionally, it provides a comprehensive resource for those beginning an investigation into RCSA.

42 ENGINEERING↗
DOE OSTI2021

CyProduct: A software tool for accurately predicting the byproducts of human cytochrome P450 metabolism

In silico metabolism prediction is a cheminformatic task of autonomously predicting the set of metabolic byproducts produced from a specified molecule and a set of enzymes or reactions. Here we describe a novel machine-learned in silico cytochrome P450 (CYP450) metabolism prediction suite, called CyProduct, that accurately predicts metabolic byproducts for a specified molecule and a human CYP450 isoform. It includes three modules: (1) CypReact, a tool that predicts if the query compound reacts with a given CYP450 enzyme; (2) CypBoM, a tool that accurately predicts the “bond site” of the reaction (i.e., which specific bonds within the query molecule react with the CYP isoform); and (3) MetaboGen, a tool that generates the metabolic byproducts based on CypBoM’s bond-site prediction. CyProduct predicts metabolic biotransformation products for each of the nine most important human CYP450 enzymes. CypBoM uses an important new concept called “Bond of Metabolism” (BoM), which extends the traditional “Site of Metabolism" (SoM) by specifying the information about the set of chemical bonds that is modified or formed in a metabolic reaction (rather than the specific atom). We created a BoM database for 3487 CYP450-mediated Phase I reactions, then used this to train the CypBoM Predictor to predict the reactive bond locations on substrate molecules. CypBoM Predictor’s cross-validated Jaccard score for reactive bond prediction ranged from 0.380 to 0.452 over the nine CYP450 enzymes. Over variants of a test set of 72 known CYP450 substrates and 30 non-reactants, CyProduct outperformed the other packages -- including ADMET Predictor, BioTransformer and GLORY -- by an average of 200% (wrt Jaccard score) in terms of predicting metabolites. The CyProduct suite and the datasets are freely available at https://bitbucket.org/wishartlab/cyproduct/src/master/.

Machine learning, Cytochrome P450, Metabolism pred↗
DOE OSTI2022

MZA: A Data Conversion Tool to Facilitate Software Development and Artificial Intelligence Research in Multidimensional Mass Spectrometry

Modern mass spectrometry-based workflows employing hybrid instrumentation and orthogonal separations collect multidimensional data, potentially allowing deeper understanding in omics studies through adoption of artificial intelligence methods. However, the large volume of these rich data challenges existing data storage and access technologies, therefore precluding informatics advancements. Here we present MZA™ (pronounced m-za), the mass-to-charge (m/z) generic data storage and access tool designed to facilitate software development and artificial intelligence research in multidimensional mass spectrometry measurements. Composed by a data conversion tool and a simple file structure based on the HDF5 format, MZA provides easy, cross-platform and efficient programmatic access to raw MS-data, enabling fast development of new tools in data science programming languages such as Python and R. The software executable and example Python and R scripts are freely available at https://github.com/PNNL-m-q/mza.

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

Crowd-Sourced Data and Analysis Tools for Advancing the Chemical Vapor Deposition of Graphene: Implications for Manufacturing

Industrial production of graphene by chemical vapor deposition (CVD) requires more than the ability to synthesize large domain, high-quality graphene in a lab reactor. The integration of graphene in the fabrication process of electronic devices requires the cost-effective and environmentally friendly production of graphene on dielectric substrates, but current approaches can only produce graphene on metal catalysts. Sustainable manufacturing of graphene should also conserve the catalyst and reaction gases, but today the metal catalysts are typically dissolved after synthesis. Progress toward these objectives is hindered by the hundreds of coupled synthesis parameters that can strongly affect CVD of low-dimensional materials and poor communication in the published literature of the rich experimental data that exists in individual laboratories. We report here on a platform, "graphene recipes for synthesis of high quality material" (Gr-ResQ: pronounced graphene rescue), which includes powerful new tools for data-driven graphene synthesis. At the core of Gr-ResQ is a crowd-sourced database of CVD synthesis recipes and associated experimental results. The database captures similar to 300 parameters ranging from synthesis conditions such as a catalyst material and preparation steps, to ambient lab temperature and reactor details, as well as resulting Raman spectra and microscopy images. These parameters are carefully selected to unlock the potential of machine-learning models to advance synthesis. A suite of associated tools enable fast, automated, and standardized processing of Raman spectra and scanning electron microscopy images. To facilitate community-based efforts, Gr-ResQ provides tools for cyber-physical collaborations among research groups, allowing experiments to be designed, executed, and analyzed by different teams. Gr-ResQ also allows publication and discovery of recipes via the Materials Data Facility, which assigns each recipe a unique identifier when published and collects parameters in a search index. We envision that this holistic approach to data-driven synthesis can accelerate CVD recipe discovery and production control and open opportunities for advancing not only graphene but also many other 1D and 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Structure and Property Guided Design in the Identification of PRMT5 Tool Compound EPZ015666

The recent publication of a potent and selective inhibitor of protein methyltransferase 5 (PRMT5) provides the scientific community with in vivo-active tool compound EPZ015666 (GSK3235025) to probe the underlying pharmacology of this key enzyme. Furthermore, we report the design and optimization strategies employed on an initial hit compound with poor in vitro clearance to yield in vivo tool compound EPZ015666 and an additional potent in vitro tool molecule EPZ015866 (GSK3203591).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗