olca-tools
A GitHub repository with Python modules and notebooks that utilize, demonstrate, or support work for openLCA.
AS↗
SEARCH · Engineering Papers
Results for “tooling”
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.
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DEVELOPMENT OF PLASMA SIMULATION TOOL FOR THE ACCEL-ERATING CAVITIES
Plasma processing of superconducting radio frequency (SRF) cavities has shown an improvement in accelerating gradient by reducing the radiation due to field emission and multipacting. Plasma processing is a common tech-nique where the free oxygen produced by the plasma breaks down and removes hydrocarbons from surfaces. This increases the work function and reduces the second-ary emission coefficient. The hydrocarbon fragments of H2, CO, CO2, and H2O are removed from the system with the process gas which is flowing through the system. Here, we present COMSOL for the first time to simulate the plasma processing of an SRF cavity. In this work, we use Jefferson Lab's C75 SRF cavities design as our case study. Using simulation, we predict the condition of plasma ignition inside the SRF cavity. The simulation provides information about the optimal rf coupling to the cavity, mode for plasma ignition, choice of gas concen-tration, power, and pressure.
Senevirathne, I.↗
rfasst: An R tool to estimate air pollution impacts on health and agriculture
Existing scientific literature shows that health and agricultural impacts attributable to air pollution are significant and should be considered in the integrated analysis of human and Earth-system interactions. The implementation of policies that affect the power sector, the composition of the vehicle fleet or the investments and deployment of different energy sources will in turn result in different levels of air pollution. Even though the various methodologies for estimating the impacts of air pollution, such as exposure-response functions, are extensively applied by the scientific community, they are normally not included in integrated assessment modeling outputs.
97 MATHEMATICS AND COMPUTING↗
Pore2Chip: All-in-one python tool for soil microstructure analysis and micromodel design
The Pore2Chip Python package is designed to create 2D micromodels using extracted data from 3D X-ray computed tomography (XCT) images. This package helps analyze soil structure and function, allowing for the investigation of hydro-biogeochemical processes that impact mineral extraction and reactivity, oxygen concentrations, and nutrient availability in disturbed or managed soils. Key metrics encompass pore size distributions, pore throat size distributions, and connectivity (pore coordination numbers). The final output is a 2D scalable SVG design representing a core or aggregate. Designs can be fabricated with methods such as laser etching, 3D printing, and photolithography.
lab-on-chip↗
FAIRLinked: Data FAIRification Tools for Materials Data Science
FAIRLinked is a software package created to support the FAIRification of materials science data, ensuring proper alignment with FAIR principles: Findable, Accessible, Interoperable, and Reusable. It is built to be compatible with MDS-Onto, an ontology designed to capture the semantics of various types of materials data, enabling integration and sharing across different research workflows. The package is subdivided into three subpackages: InterfaceMDS, RDFTableConversion, and QBWorkflow. The first subpackage, InterfaceMDS allows users to search for terms using either string search or various filters, explore different domains and subdomains, and add terms to MDS-Onto. RDFTableConversion is used for serialization and deserialization of data from CSV into JSONLDs and vice versa in a way that captures the semantics of the data using MDS-Onto. Lastly, QBWorkflow is a serialization and deserialization workflow that incorporates RDF Data Cube vocabulary, useful for working with multidimensional datasets. By offering these packages, FAIRLinked lowers the barrier of creating FAIR, machine-actionable data for researchers in the materials science community.
FAIR↗
A screening tool for assessing feasibility of re-using existing oil and gas wells for CCUS operations
Explore the source record for details and available documents.
Earth Sciences↗
The Next-Generation Ecosystem Experiment Arctic Rainfall Simulator: a tool to understand the effects of changing rainfall patterns in the Arctic
Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R 2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments.
54 ENVIRONMENTAL SCIENCES↗
APS-TD Quality Facilities and Tools
In the Applied Physics and Superconducting Technology Division the quality function resides within the Quality & Materials Department (QMD). QMD employs staff with expertise in quality-related fields.
43 PARTICLE ACCELERATORS↗
Additive Manufacturing of Stamping Tools for Appliances
Oak Ridge National Laboratory (ORNL) worked with Whirlpool Corporation to demonstrate additive manufacturing (AM) of stamping dies for the appliance industry using a large-scale wire arc metal additive manufacturing system jointly developed between Lincoln Electric and ORNL. An appliance stamping die was successfully printed, machined, nitrided, and demonstrated in the last quarter of 2019.
42 ENGINEERING↗
Sample Management Tools for the Irradiation Test Area (ITA)
The ITA offers onsite radiation testing, and will be available starting Fall 2020. It is projected to have testing slots about 40x/year and a capacity to reach fluences of 1016 protons/cm2 in four hours. A 400 MeV proton beam is directed to samples in a concrete shielding cave, with variations in place available to the user’s preferences. The ITA regulates all its experiment data through ITA’s Data Manager (IDM).
43 PARTICLE ACCELERATORS↗
Power-to-Gas Tool: User's Guide
PNNL, working in collaboration with ITM Power and HG&E, has developed a suite of products to support analysis of P2G in Massachusetts. These products include: (a) P2G model that can be accessed at eset.pnnl.gov, (b) P2G system valuation report that describes in detail the methodology underpinning the P2G model and presents the results of 82 scenarios run using the model, and (c) a P2G model user’s guide. This user’s guide accompanies the other products and is designed to simplify the experience of each user, providing useful instructions while guiding users as they input data and interpret results.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Developing Sample Management Tools for the Irradiation Test Area (ITA)
The ITA Data Manager (IDM) has been ported from CERN’s Proton Irradiation Facility (IRRAD), where it was used previously as the IRRAD Data Manager (IDM), in order to meet the data management and sample tracking needs of the Irradiation Test Area (ITA), a newly developed facility at Fermilab (launching Fall 2020) operating under the Fermilab Test Beam Facility.
43 PARTICLE ACCELERATORS↗
CTT: Tools for Fine Alignment of Flash X-ray Systems
The CTT code is a compilation of the python code that was prototyped in the interest of making a method for fine alignment of Flash X-ray Systems at the lab. It contains python code for interacting with LTT and running optimization loops using LTT simulations or ray tracing with RaySpace. It Includes classes for creating phantom objects and modular geometry objects in the simulations. It allows one to generate a random phantom that has been optimized to stay with a certain cubic volume and maximize the minimum distance between any two ball phantom centers in all projections. It was primarily made to work on ball phantoms which were simulated as Teflon spheres. It allows the alignment from some nominal position to some displaced position to simulate recovery of a real geometry from the nominal geometry of the system. Fine alignment can be done with the projections in LTT while a rough alignment is faster using rayspace. If rayspace works well for the use case it should be preferred since it is considerably faster and less resource intensive in general. Some Notes about using this code is that one will have to edit the imports for the files to get to the correct LTT path, LTT GUI path and to the CTT path when importing. This was made by using anaconda with python 3 on windows 10. The LTT code was stored in a anaconda environment which seemed to help the python find the LTT although it shouldn’t be necessary if you append the path in your code using sys.path.append(r'add the path you want here’). The sys.path.append method is a quick way to give your python code access to a given folder when running it (such as LTT or CTT). Note that since the code was originally made with paths for a specific machine that a new user will have to edit those paths to make it work in all the files that use the old paths. This is somewhat tedious but will be required to run the code on a new machine. The methodology used to run and make these notebooks starts with opening a command prompt as administrator in windows 10. After this one would activate the anaconda environment in the appropriate directory using “conda activate myenv” in the command prompt. After this open a jupyter-notebook using the keyword “jupyter-notebook". After that a notebook should open in a browser. Note that some libraries used may not come with anaconda so those may have to be installed. There shouldn’t be much though since the main things used are scipy, numpy, matplotlib, and LTT. LTTQuicksetup also requires some paths that will be specific to the computer so that should be changed as well.
42 ENGINEERING↗
Developing Sample Management Tools for the Irradiation Test Area (ITA)
Explore the source record for details and available documents.
Logsdon, Morgan↗
Direction Raman spectroscopy: a surface-sensitive tool for measuring the chemical, optical, and physical properties of adsorbates on metal surfaces
Explore the source record for details and available documents.
Nyamekye, Charles↗
New Capabilities for Sampling Tools
This report will discuss new capabilities that have been added to the sample.py and uniform_sampler.py codes. The codes have been updated to allow for both log-uniform sampling and categorical variables. The categorical variables do not have to be numeric. The different values for a categorical variable are specified in a limits file by having spaces between them. The difference between sample.py and uniform_sampler.py is that sample.py is for generating random samples and uniform_sampler.py is for generating samples or points on a fixed grid. After sourcing a file to set the environment, execute the codes with the commands: sample.py and uniform sampler.py .
97 MATHEMATICS AND COMPUTING↗
Comparison of Polymer AM Technologies for Automotive Tooling for Composite Engines
Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with Polimotor to complete a set of molds for fabricating the oil pan for a composite engine. This project used multiple different AM processes to fabricate the mold set. The assembled parts were measured for tolerance and then sent to Polimotor to be used in the manufacture of engine components.
42 ENGINEERING↗
Strategic Performance Evaluation Measurement Plan (PEMP) Scorecard in QuickScore Training Tool (User Guide)
The Strategic Performance Evaluation Measurement Plan (PEMP) Scorecard, now housed in QuickScore, is an assurance and governance data scorecard which shows the health of the labs against the current fiscal year PEMP objectives. POC's for PEMP objective owners are requested to provide status of their PEMP objective, capture the top 6 cumulative accomplishments, top 6 issues, which include IFR issues and provide mitigation and or improvement action plans. Updated scorecards are used in OMR and BOM GS&S committee
29 ENERGY PLANNING, POLICY, AND ECONOMY↗