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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. This paper explores how we developed one of the HUNTER modules: namely, the Individual module for evaluating performance shaping factors (PSFs). A PSF is any factor that influences human performance (e.g., workload or complexity). In the existing HRA, they are used to highlight human errors and adjust error probabilities. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, a representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed the human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also designed the Individual module to consist of two functions: (1) the PSF qualification function for automatically or manually evaluating PSF levels, and (2) the PSF quantification function for dynamically or statically determining PSF multiplier values and integrating them to adjust human error probabilities (HEPs). How each function works in regard to the SPAR-H PSFs, and how the PSFs serve to adjust the HEPs, were investigated via literature review and are discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

TR-XPS Realtime Analysis Tool (ArroyoXPS) v0.1

The ALS has developed a Time-Resolved X-ray Photoelectron Spectroscopy (TR-XPS) technique, which involves applying a specific pattern of voltage curves to a sample while measuring XPS peaks. This pattern is repeated over multiple cycles, and changes in the material's response provide valuable scientific insights. Traditionally, file-based analysis workflows have been used: scans are run for a predetermined time, and after one or more scans are complete, calculations are made. ArroyoXPS changes this by offering in-experiment scan and analysis, allowing researchers to gain insights before a scan is finished. This enables them to adjust experimental parameters quickly, potentially saving valuable beamtime. ArroyoXPS includes tools for integrating with beamline control systems, performing analysis, and visualizing scan data in a web browser.

McReynolds, Dylan [Lawrence Berkeley National Labo↗
DOE OSTI2021

Integrated, Interoperable Software Environment for Fusion Simulation and Data Analysis Tools SBIR Phase II

This SBIR effort was focused on developing a production ready system to address the integration and interoperability challenges with analysis and visualization in fusion simulations. Our overarching technical objective was to minimize the code development simulation scientists incur when coupling their simulation codes with different analysis frameworks. To this end, we developed an open-source software library to make data exchange between application easier and a Web application to manage and display analysis extracts from simulations. We have also augmented existing libraries funded by DOE such as ADIOS and VTK-m. When used together, these make it significantly easier to integrate simulation and analysis capability. We demonstrated the flexibility of our approach using two common simulation codes in the fusion community, XGC1 and GTC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Coupling an External Plant Code

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) with the aim to develop standalone software to perform the dynamic HRA calculations. Within the HRA, human actions in nuclear power plants (NPPs) are predicated by plant states, and human actions influence the plant. In other words, plant operations are necessarily recursive, and it becomes challenging to model complex human-plant interactions. Consequently, we have linked two software simulations that complement those shortcomings. RELAP5-3D—the Reactor Excursion and Leak Analysis Program (RELAP; Aumiller, Tomlinson, and Bauer 2001) is the foundational thermal-hydraulic software used to model nuclear systems. Using RELAP5-3D, we have simulated the plant operations proceeding according to procedures developed to address emergent situations in NPPs. Plant operations include various actions such as the operator checking plant parameters, as well as actions that are continuously performed over time until a specific parameter reaches certain criteria. That means that HUNTER and RELAP5-3D exchange information with each other and should be carried out simultaneously over time. To simulate plant operations, which represent the actual operator checks of plant parameters and corresponding manual control actions, changes in plant status are identified through simulation and performed according to the criteria and order of the procedure. Thus, the goal of coupling HUNTER with RELAP5-3D is to facilitate synchronous coupling, where human and plant models provide iterative feedback loops that drive the course of actions. The advantage of coupling with RELAP5-3D to serve as the external environment module in HUNTER is the ability to customize the plant model and streamline for particular model applications. In this paper, we will address the key features of the coupling and the coupling structure built to perform the feedback loops.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Using feature importance as an exploratory data analysis tool on Earth system models

Abstract. Machine learning (ML) models are commonly used to generate predictions, but these models can also support the discovery of new science. Generating accurate predictions necessitates that a model captures the structure of the underlying data. If the structure is properly extracted, ML could be a useful exploratory and evidential tool. In this paper, we present a case study that demonstrates the use of ML for exploratory data analysis (EDA) in the climate space. We apply the ML explainability method of spatiotemporal zeroed feature importance (stZFI) to understand how climate-variable associations evolve over space and time. Our analyses focus on data from ensembles of Earth system models (ESMs) which provide data on different climate states and conditions. We elect to work with ESM ensembles since they allow us to compare feature importance across alternative scenarios not available with observed data. The ensembles also account for natural variability so that we can distinguish between signal and noise due to natural climate variability when computing feature importance. The use of perturbed initial condition ensembles introduces variability mimicking the natural variability in the atmosphere; thus the signals emerging using feature importance (FI) can be evaluated against the natural variability in the climate system. For our analyses, we consider the 1991 volcanic eruption of Mount Pinatubo, which was a large stratospheric aerosol injection. We explore the climate pathway associated with the eruption from aerosols to radiation to temperature at both the near-surface and stratospheric levels. In addition to applying the method to data generated from two different ESMs, we apply stZFI to reanalysis data to compare the associations identified by stZFI. We show how stZFI tracks the importance of aerosol optical depth over time on forecasting temperatures. This case study illustrates usefulness of an ML tool (stZFI) for EDA on a well-studied climate exemplar.

Ries, Daniel (ORCID:0000000250294647)↗
DOE OSTI2024

Reconductoring Economic and Financial Analysis Tool (REFA) v1.0

REFA is designed to help transmission planners better understand the financial, environmental and economic benefits of reconductoring upgrades, using traditional or advanced conductors. More specifically, the tool enables grid planners and utilities to demonstrate the entire lifetime value of reconductoring projects, providing potential justifications for projects with higher Capex - the purchase of long-term physical or fixed assets used in a business's operations. Existing tools are designed to compare technical aspects of different conductor applications. They typically do not allow a cost-benefit analysis over the lifetime of the conductor's operations.

Heleno, Miguel↗
DOE OSTI2021

Comparing the OpenSolar Remote Shading Analysis Tool to On-Site Shading Measurements

OpenSolar is a free of charge application built for solar installers that creates a fully articulated 3D model of the site and performs remote shading analysis, in order to produce highly accurate designs and interactive, customizable proposals. Under the National Renewable Energy Laboratory (NREL) Commercialization Assistance Program (NCAP), NREL independently verified the accuracy of OpenSolar's remote analysis of solar access percentage values (SAVs) on an annual basis for locations in Los Angeles, CA, and Denver, CO. In aggregate, the results of the analysis show that Open Solar-calculated annual SAV measurements were statistically equivalent within ±2.63 SAVs for Los Angeles locations and ±2.69 SAVs for Denver locations compared to those of on-site measurements made with SunEye devices.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗
DOE OSTI2022

Updated Waste Management System Analysis Tool Requirements and Enhancements

Draft presentation for presentation to Nuclear Waste Technical Review Board Winter/Spring Meeting March 2nd NOTE: FYI this presentation is almost the same as the presentation that will be uploaded soon entitled 'Next Generation System Analysis Model: Recently Added Features and Future Plans' for the Waste Management 2022 conference.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the

Bilheux, JeanChristophe [Oak Ridge National Labora↗
DOE OSTI2024

Flexible Technoeconomic Analysis Tools for Evaluating Emerging Power Generation Technologies in Hourly Electricity Markets using IDAES and Pyomo

Conference presentation leveraging the recently developed “price-taker class”. We use the tool to develop and showcase workflows that enable rapid technology evaluation for power generation technologies. This work shows a reimplementation of previous results that were conducted outside the price-taker class framework, indicating this workflow is indeed streamlining emerging technology analysis.

Laky, Daniel↗
DOE OSTI2024

Review of Life Cycle Cost Analysis Tools

Life cycle costing (LCC) is a vital aspect of decision-making in building retrofitting. It allows stakeholders to thoroughly assess all expenses involved throughout the lifespan of these retrofits, covering initial costs; ongoing operation, maintenance, and repair costs; and disposal costs of the system. The Federal Energy Management Program of the US Department of Energy has established clear guidelines for conducting LCC analysis, particularly for investments aimed at energy and water conservation, as well as renewable energy projects. These guidelines are detailed in the Code of Federal Regulations, 10 CFR 436, Subpart A, which outlines the methodology and procedure for LCC analysis (Department of Energy 1990). The National Institute of Standards and Technology (NIST) has developed the NIST Handbook 135 (Joshua Kneifel 2022) to standardize the process of LCC analysis within the building industry. Whereas the handbook is tailored to the needs of federal agencies, its principles and methodologies can be valuable for other organizations and industries interested in conducting life cycle costing analyses for their building projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

CEC Quest: Long Duration Energy Storage Impact Analysis Tool

SAND2025-14389O CEC Quest is a Python tool with a user interface designed to analyze the greenhouse gas impacts of long-duration energy storage projects in California. The tool automates data collection from public sources and uses an Application Programming Interface (API) to enable users to download photovoltaic resource availability, marginal operating emissions rate, and utility rate data. It guides users in inputting parameters for a battery energy storage model and uploading site electrical load data, while also prompting for relevant analysis parameters like timestep and grid limits. CEC Quest performs monthly optimization of one year of data to assess impacts on the site’s electrical bill and the grid’s greenhouse gas emissions. Finally, it conducts a lifecycle analysis to evaluate changes over a defined quantification period, with results aggregated through automated report generation. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rosewater, David [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2023

Developing new analysis tools for near surface radio-based neutrino detectors

The ARIANNA experiment is an Askaryan radio detector designed to measure high-energy neutrino induced cascades within the Antarctic ice. Ultra-high-energy neutrinos above 10 16 eV have an extremely low flux, so experimental data captured at trigger level need to be classified correctly to retain as much neutrino signal as possible. We first describe two new physics-based neutrino selection methods, or "cuts", (the updown and dipole cut) that extend the previously published analysis to a specialized ARIANNA station with 8 antenna channels, which is double the number used in the prior analysis. For a standard trigger with a threshold signal to noise ratio at 4.4, the new cuts produce a neutrino efficiency of > 95% per station-year of operation, while rejecting 99.93% of the background (corresponding to 53 remaining experimental background events). When the new cuts are combined with a previously developed cut using neutrino waveform templates, all background is removed at no change of efficiency. In addition, the neutrino efficiency is extrapolated to 1,000 station-years of operation, obtaining 91%. This work then introduces a new selection method (the deep learning cut) to augment the identification of neutrino events by using deep learning methods and compares the efficiency to the physics-based analysis. The deep learning cut gives 99% signal efficiency per station-year of operation while rejecting 99.997% of the background (corresponding to 2 remaining experimental background events), which are subsequently removed by the waveform template cut at no significant change in efficiency. Here the results of the deep learning cut were verified using measured cosmic rays which shows that the simulations do not introduce artifacts with respect to experimental data. The paper demonstrates that the background rejection and signal efficiency of near surface antennas meets the requirements of a large scale future array, as considered in baseline design of the radio component of IceCube-Gen2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1

Abstract. Groundwater plays a key role in meeting water demands, supplying over 40 % of irrigation water globally, with this role likely to grow as water demands and surface water variability increase. A better understanding of the future role of groundwater in meeting sectoral demands requires an integrated hydro-economic evaluation of its cost and availability. Yet substantial gaps remain in our knowledge and modeling capabilities related to groundwater availability, recharge, feasible locations for extraction, extractable volumes, and associated extraction costs, which are essential for large-scale analyses of integrated human–water system scenarios, particularly at the global scale. To address these needs, we developed Superwell, a physics-based groundwater extraction and cost accounting model that operates at sub-annual temporal and at the coarsest 0.5° (≈50 km × 50 km) gridded spatial resolution with global coverage. The model produces location-specific groundwater supply–cost curves that provide the levelized cost to access different quantities of available groundwater. The inputs to Superwell include recent high-resolution hydrogeologic datasets of permeability, porosity, aquifer thickness, depth to water table, recharge, and hydrogeological complexity zones. It also accounts for well capital and maintenance costs, as well as the energy costs required to lift water to the surface. The model employs a Theis-based scheme coupled with an amortization-based cost accounting formulation to simulate groundwater extraction and quantify the cost of groundwater pumping. The result is a spatiotemporally flexible, physically realistic, economics-based model that produces groundwater supply–cost curves. We show examples of these supply–cost curves and the insights that can be derived from them across a set of scenarios designed to explore model outcomes. The supply–cost curves produced by the model show that most (90 %) nonrenewable groundwater in storage globally is extractable at costs lower than USD 0.57 m−3, while half of the volume remains extractable at under USD 0.108 m−3. The global unit cost is estimated to range from a minimum of USD 0.004 m−3 to a maximum of USD 3.971 m−3. We also demonstrate and discuss examples of how these cost curves could be used by linking Superwell's outputs with other models to explore coupled human–environmental system challenges, such as water resources planning and management, or broader analyses of multisectoral feedbacks.

Global Change Analysis Model (GCAM)↗
DOE OSTI2021

Load Decomposition Analysis Tool

This project tests the application of Bennet Meyers' signal decomposition to the residential end-use load decomposition problem.

Chassin, David P.↗
DOE OSTI2023

Current-Voltage Analysis Tool for Solar Fuel Production (CATS) v0.1

The program is expected to be a useful tool during operation of a range of solar-driven electrochemical devices, such as PV-electrolyzers and photoelectrochemical (PEC) devices. It makes use of current-voltage data collected during operation, operation parameters that are easily accessible for many devices of interest. The program captures the time-dependence of loss mechanisms at play during PEC device operation and opens the door for real-time optimizations of operational parameters like the feed humidity to minimize performance losses. Currently, the program is useful for applications where the current-voltage polarization response of the photoabsorber and electrolyzer are pre-recorded, and changes over time can be estimated based on the pre-recorded current-voltage scans. More complicated scenarios that involve permanent degradation of the PV component or complex calculations of the electrolyzer current-voltage characteristics may be included in future versions of this software. Aside from the possibility of deconvoluting loss mechanisms, this software can also reveal possible performance benefits by convective PV cooling when the photoabsorber is integrated into the electrolysis cell. The latter can highlight why certain device architectures may be beneficial over others. No similar technologies are known to the developer.

Kistler, Tobias↗