Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Performance Prediction Package”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

pnnl/emp-gnn

Efficient Graph Neural Network for Predicting Molecular Properties software can compare the prediction quality with ab initio DFT results reported by the high-performance state-of-theart NWChem quantum chemistry package [1] through Mean Absolute Error (MAE) obtained by the fitting between DFT and model predictions i.e, MPNN [2]. We also demonstrated the performance benefits by grouping large molecules by atom sizes, and executing GNN models on different types of resources. Since the training times depend on the number of atoms, we demonstrate the impact of distributing the workloads on two GPUs with varying capabilities (e.g., NVIDIA A100 vs. GeForce RTX 2080 Ti) to optimize the efficiency. We are at the precipice of broad adoption of GNNs for molecular property prediction tasks; hence, our work is timely by comparing model prediction against classical approaches with the intent of providing initial screening for specific classes of molecules.

Lee, Hyungro↗
DOE OSTI2025

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗
DOE OSTI2021

A Scoping Study to Develop a Computational Fluid Dynamics Based Model to Predict Radiological Materials Packaging Temperatures within a Generic Staging Building

The objective of this work is to perform computational fluid dynamics simulations of a ventilated radiological-material-package staging building to determine the effect of including or excluding a variety of physical effects and computational methods on both the predicted package temperatures and required computational resources. The generic building contains 640 drum-packages containing heat-generating, radiological material supported on four racks that are eight levels tall. Additionally, there is a forced ventilation system, lighting, and insulated walls. Computational models were constructed that included or excluded (a) shelving, (b) effects of unsteadiness, and (c) radiation heat transfer. Simulations with each drum modeled separately were compared to simpler simulations with sets of four drums represented by an equivalent box-package. These models employed between 106 to 107 elements. Steady state simulations predicted package temperatures that were within 0.1°C of simulations that included transient effects and required only one-eighth the computational resources. Calculations that excluded shelving predicted temperatures within 0.6°C of simulations that included shelving and required one-fourth the computational resources. Excluding radiation heat transfer systematically increased temperatures by around 1.5°C but reduced computational resources by a factor of four. The box-package model reduced the computational resources by a factor of 3, but systematically predicted higher temperatures by around 1.1°C. These results will be used to develop an efficient computational fluid dynamics model to assess the ability of different staging building designs to prevent the temperature of package components from exceeding specified limits.

42 ENGINEERING↗
NASA NTRS2005

Evaluation of a Shuttle Derived Vehicle (SDV) for Cargo Transportation

In this new era of space exploration, a host of launch vehicles are being examined for possible use in transporting cargo and crew to low Earth orbit and beyond. Launch vehicles derived from the Space Shuttle Program (SSP), known as Shuttle Derived Vehicles (SDVs), are prime candidates for heavy-lift duty because of their potential to minimize non-recurring costs and because the Shuttle can leverage off proven high-performance flight systems with established ground and flight support. To determine the merits of SDVs, a detailed evaluation was performed. This evaluation included a trade study and risk assessment of options based on performance, safety reliability, cost, operations, and evolution. The purpose of this paper is to explain the approach, processes, and tools used to evaluate launch vehicles for heavy lift cargo transportation. The process included defining the trade space, characterizing the concepts, analyzing the systems, and scoring the options. The process also included a review by subject experts from NASA and industry to compare past and recent study data and assess the risks. A set of technical performance measures (TPMs) was generated based on the study requirements and constraints. Tools such as INTROS and POST were used to calculate performance, FIRST was used for prediction of reliability, and other software packages, both commercial and NASA-owned, were applied to study the trade space. By following a clear process and using the right tools a thorough assessment was performed. An SDV can be classified as either a side-mount vehicle (SMV) or an in-line vehicle OLV). An SMV is a Space Shuttle where the Orbiter is replaced by a cargo carrier. An ILV is comprised of a modified Shuttle External Tank (ET) with engines mounted to the bottom and cargo mounted atop. For both families of vehicles, Solid Rocket Boosters (SRBs) are attached to the ET. The first derivate of Shuttle is defined as the vehicle with minimum changes necessary to transform the Space Shuttle into an SDV. Deltas from the first derivate were also formulated to study more SDV options. Examples of deltas include replacing the SRBs with larger and/or more SRBs, adding an upper stage, increasing the size of the ET, changing the engines, and modifying the elements. Challenges for SDV range from tailoring infrastructure to meeting the exploration schedule. Although SDV is based on the Space Shuttle, it still includes development risk for designing and building a Cargo Carrier. There are also performance challenges in that Shuttle is not optimized for cargo-only missions, but it is a robust system built on reusability. Balancing the strengths and weaknesses of the Shuttle to meet Lunar and Mars mission objectives provides the framework for an informative trade study. SDV was carefully analyzed and the results of the study provide invaluable data for use in the new exploration initiative.

Roman, Jose M.↗
DOE OSTI2018

Coupled Processes Modeling in Rock Salt and Crushed Salt Including Halite Solubility Constraints: Application to Disposal of Heat-Generating Nuclear Waste

This work presents numerical modeling of coupled thermal, hydraulic and mechanical processes in rock salt and crushed salt considering halite solubility constraints. The TOUGH-FLAC simulator is used, with a recently enhanced Equation-Of-State module that includes the thermodynamic properties of aqueous fluids of variable salinity. Laboratory and field scale tests performed on rock salt and crushed salt under temperature gradients are modeled first to evaluate the capabilities of the simulator to reproduce important features, such as porosity changes induced by halite dissolution/precipitation, and brine and heat migration. Since the results are quite satisfactory, the simulator is used to predict the long-term response of a generic salt repository for heat-generating nuclear waste. To evaluate the impacts of halite solubility on the predictions, two simulations that respectively consider or neglect solubility constraints are performed. In the scenario studied, the results are not significantly affected by dissolution/precipitation, and only some differences are observed due to changes in porosity, but the dominating processes remain the same. Finally, with the new provisions, TOUGH-FLAC is more complete in terms of processes occurring around a heat-releasing nuclear waste package and can therefore provide more accurate predictions of the long-term performance of a nuclear waste repository in salt formations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2003

Deployment Simulation Methods for Ultra-Lightweight Inflatable Structures

Two dynamic inflation simulation methods are employed for modeling the deployment of folded thin-membrane tubes. The simulations are necessary because ground tests include gravity effects and may poorly represent deployment in space. The two simulation methods are referred to as the Control Volume (CV) method and the Arbitrary Lagrangian Eulerian (ALE) method. They are available in the LS-DYNA nonlinear dynamic finite element code. Both methods are suitable for modeling the interactions between the inflation gas and the thin-membrane tube structures. The CV method only considers the pressure induced by the inflation gas in the simulation, while the ALE method models the actual flow of the inflation gas. Thus, the transient fluid properties at any location within the tube can be predicted by the ALE method. Deployment simulations of three packaged tube models; namely coiled, Z-folded, and telescopically-folded configurations, are performed. Results predicted by both methods for the telescopically-folded configuration are correlated and computational efficiency issues are discussed.

Wang, John T.↗
NASA NTRS1982

CLASS - A comprehensive satellite link simulation package

CLASS (Communications Link Analysis and Simulation System) is a software package developed for NASA to predict the communications and tracking performance of the Tracking and Data Relay Satellite System (TDRSS) services. This paper describes the capabilities of CLASS and the communications link model used and discusses typical applications for CLASS.

Braun, W. R.↗
NASA NTRS1985

Modeling techniques used in the communications link analysis and simulation system (CLASS)

CLASS (Communications Link Analysis and Simulation System) is a software package developed for NASA to predict the communication and tracking performance of the Tracking and Data Relay Satellite System (TDRSS) services. The modeling techniques used in CLASS are described. The components of TDRSS and the performance parameters to be computed by CLASS are too diverse to permit the use of a single technique to evaluate all performance measures. Hence, each CLASS module applies the modeling approach best suited for a particular subsystem and/or performance parameter in terms of model accuracy and computational speed.

Braun, W. R.↗
NASA NTRS1985

Validation of the communications link analysis and simulation system (CLASS)

CLASS (Communication Link Analysis and Simulation System) is a software package developed for NASA to predict the communication and tracking performance of the Tracking and Data Relay Satellite System (TDRSS) services. The methods used to verify CLASS are described. The usefulness of a software tool such as CLASS depends strongly on the reliability and accuracy of the results it produces. For this reason, considerable attention was paid to validation throughout the CLASS development.

Braun, W. R.↗
NASA NTRS2011

Supersonic Retropropulsion Flight Test Concepts

NASA's Exploration Technology Development and Demonstration Program has proposed plans for a series of three sub-scale flight tests at Earth for supersonic retropropulsion, a candidate decelerator technology for future, high-mass Mars missions. The first flight test in this series is intended to be a proof-of-concept test, demonstrating successful initiation and operation of supersonic retropropulsion at conditions that replicate the relevant physics of the aerodynamic-propulsive interactions expected in flight. Five sub-scale flight test article concepts, each designed for launch on sounding rockets, have been developed in consideration of this proof-of-concept flight test. Commercial, off-the-shelf components are utilized as much as possible in each concept. The design merits of the concepts are compared along with their predicted performance for a baseline trajectory. The results of a packaging study and performance-based trade studies indicate that a sounding rocket is a viable launch platform for this proof-of-concept test of supersonic retropropulsion.

Exploration Technology Development and Demonstrati↗
DOE OSTI2023

Data, scripts, and figures associated with a manuscript studying impact of climate and topography on post-fire vegetation recovery.

This data package is associated with the publication “Impact of Topography and Climate on Post-fire Vegetation Recovery Across Different Burn Severity and Land Cover Types through Machine Learning” submitted to Remote Sensing of Environment (Zahura et al. 2023). In this research, a machine learning algorithm, random forest (RF), was utilized to examine the impact of climate and topography on post-fire vegetation recovery. We used enhanced vegetation index (EVI) to examine varying burn severity and land cover types. The data package includes the input files for RF model training, outputs from model predictions and analysis, and python scripts to run the model, analyze the results to understand model performance and interpretability, and plot manuscript figures. This data package contains three folders (Data, Scripts, and Figures), a file-level metadata (FLMD) csv, and a data dictionary (dd) csv. Please see Postfire_recovery_flmd.csv for a list of all files contained in this data package and descriptions for each. The data dictionary (Postfire_recovery_dd.csv) describes the csv column headers. The “Data” folder provides all the inputs and outputs to train the RF model, evaluate performance, and interpret predictions. The “Scripts” folder contains python scripts and jupyter notebooks for model training and result analysis. The “Figures” folder includes the figures used in the manuscript in “.png” and “.jpg” format.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Solar Power Satellite antenna phase control system hardware simulation, phase 4. Volume 3: SOLARSIM users manual

Documentation of the interactive software package designed to predict the effect of certain electrical and mechanical imperfections on the performance of the SPS system is presented. The capabilities of the SOLARSIM program to quantify the spacetenna performance parameter values are described. The SOLARSIM package can compute the RMS pointing error, title effects, MPTX code tracking loop performance, MPTX carrier tracking loop performance, averaged power pattern, and the power transfer efficiency.

Lindsey, W. C.↗
DOE OSTI2015

Development and Evaluation of a Sandia Cooler-based Refrigerator Condenser

This report describes the first design of a refrigerator condenser using the Sandia Cooler, i.e. air - bearing supported rotating heat - sink impeller. The project included baseline performance testing of a residential refrigerator, analysis and design development of a Sandia Cooler condenser assembly including a spiral channel baseplate, and performance measurement and validation of this condenser system as incorporated into the residential refrigerator. Comparable performance was achieved in a 60% smaller volume package. The improved modeling parameters can now be used to guide more optimized designs and more accurately predict performance.

42 ENGINEERING↗
DOE OSTI2025

Phosphoproteomics Modifications in Women with Rheumatoid Arthritis─Application of Web-Based Software to Enhance Data Visualization

Individuals with rheumatoid arthritis (RA) are at increased risk of functional disability, cardiovascular disease, and obesity, all of which are influenced by dysregulated skeletal muscle. Here, this pilot study aims to identify phosphoproteomics changes in RA skeletal muscle and visualize modifications through development of a web-based app designed to promote user-friendly data interpretation and visualization. NanoLC–MS/MS analysis was performed on vastus lateralis biopsies from three women with RA and matched healthy controls. Differential analysis was performed using the Limma R package. Kinase substrate enrichment analysis (KSEA) predicted changes in kinase activity. RA muscle displayed 35 upregulated and 60 downregulated phosphosites, including the cytoskeletal proteins TTN (Ser33201, Ser33013, Ser20925), NEB (Ser2219, Thr254, Ser33013, Ser20925), FLNA (Ser1459), and LASP1 (Ser146). Compared to healthy controls, KSEA predicted decreased activity of several kinases in RA muscle, including PRKACA and CDKs. All such changes were visualized by use of our web-based app. Overall, phosphoproteome analysis reveals signaling alterations in RA skeletal muscle linked to cytoskeletal proteins, representing candidate disease biomarkers; these modifications can be explored through use of our web-based software.

phosphoproteomics↗
DOE OSTI2017

Terminal Sinking Velocity for Waste Packages Falling in a Deep Borehole - 17063

This evaluation of terminal velocity for a waste package sinking in a deep borehole filled with emplacement fluid was done to support concept development for the Deep Borehole Field Test (DBFT). The DBFT objective is to evaluate the safety and feasibility of the deep borehole disposal (DBD) concept for certain radioactive wastes. The DBD concept calls for emplacing waste packages in the lower 2 km of a borehole drilled into crystalline basement rock to a depth of 5 km. Previous studies identified that accidentally dropping one or more waste packages during emplacement could be an important risk, particularly if a waste package is breached. This study evaluated the range of terminal sinking velocity, which can be used to design waste packages and impact limiters to ensure that breach does not occur. Based on an analytical model of a sinking container, a highly turbulent flow is expected to develop in the emplacement fluid. Turbulence is a complex three-dimensional phenomenon and the applicability of analytical models is limited. To backstop the analytical model and to extend predictions to other package dimensions and fluid properties, numerical simulation was performed using the ANSYS Fluent computational fluid dynamics code. Terminal velocity was calculated for downhole temperatures up to 1200 C, and three emplacement fluids (water, NaCl brine, and NaBr brine). Simulation results confirmed that flow around the sinking container is highly turbulent (Reynolds number 5.6 x 10{sup 4} to 7.3 x 10{sup 5}). Turbulence increases with temperature and decreases with density. Calculated terminal velocity ranges from 1.95 (200 C) to 2.13 m/s (1200 C) in water; 1.61 (200 C) to 1.79 m/s (1200 C) in NaCl; and 1.30 (200 C) to 1.46 m/s (1200 C) in NaBr. Terminal velocity is inversely related to fluid density, and the temperature effect on density appears to have a stronger effect on terminal velocity than the temperature effect on viscosity. The foregoing results are for non-perforated casing, but in practice the casing may be perforated to prepare for cementing, and to allow relief of fluid pressure from thermal expansion after emplacement of heat generating waste, and after final borehole closure. To represent the effect from perforations, the analytical solution was modified to include bypass flow through perforations and in the annulus. A workable perforation scheme is identified, consistent with borehole construction and closure requirements, using 2-cm and 5-cm diameter perforations. This scheme is estimated to limit the terminal velocity to 3 m/s, for reference waste packages falling in water at 400 C. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Constitutive Model Development for Aging Polymer Encapsulants (ASC P&EM FY2021 L2 Milestone 7836)

This SAND report fulfills the completion requirements for the ASC Physics and Engineering Modeling Level 2 Milestone 7836 during Fiscal Year 2021. The Sandia Simplified potential energy clock (SPEC) non-linear viscoelastic constitutive model was developed to predict a whole host of polymer glass physical behaviors in order to provide a tool to assess the effects of stress on these materials over their lifecycle. Polymer glasses are used extensively in applications such as electronics packaging, where encapsulants and adhesives can be critical to device performance. In this work, the focus is on assessing the performance of the model in predicting material evolution associated with long-term physical aging, an area that the model has not been fully vetted in. These predictions are key to utilizing models to help demonstrate electronics packaging component reliability over decades long service lives, a task that is very costly and time consuming to execute experimentally. The initiating hypothesis for the work was that a model calibration process can be defined that enables confidence in physical aging predictions under ND relevant environments and timescales without sacrificing other predictive capabilities. To test the hypothesis, an extensive suite of calibration and aging data was assembled from a combination of prior work and collaborating projects (Aging and Lifetimes as well as the DoD Joint Munitions Program) for two mission relevant epoxy encapsulants, 828DGEBA/DEA and 828DGEBA/T403. Multiple model calibration processes were developed and evaluated against the entire set of data for each material. A qualitative assessment of each calibration's ability to predict the wide range of aging responses was key to ranking the calibrations against each other. During this evaluation, predictions that were identified as non-physical, i.e., demonstrated something that was qualitatively different than known material behavior, were heavily weighted against the calibration performance. Thus, unphysical predictions for one aspect of aging response could generate a lower overall rating for a calibration process even if that process generated better quantitative predictions for another aspect of aging response. This insurance that all predictions are qualitatively correct is important to the overall aim of utilizing the model to predict residual stress evolution, which will depend on the interplay amongst the different material aging responses. The DSC-focused calibration procedure generated the best all-around aging predictions for both materials, demonstrating material models that can qualitatively predict the whole host of different physical aging responses that have been measured. This step forward in predictive capability comes from an unanticipated source, utilization of calorimetry measurements to specify model parameters. The DSC-focused calibration technique performed better than compression-focused techniques that more heavily weigh measurements more closely related to the structural responses to be predicted. Indeed, the DSC-focused calibration procedure was only possible due to recent incorporation of the enthalpy and heat capacity features into SPEC that was newly verified during this L2 milestone. Fundamentally similar aspects of the two material model calibrations as well as parametric studies to assess sensitives of the aging predictions are discussed within the report. A perspective on the next steps to the overall goal of residual stress evolution predictions under stockpile conditions closes the report.

36 MATERIALS SCIENCE↗
NASA NTRS1993

Prediction of static performance for single expansion ramp nozzles

A multiblock three-dimensional Navier-Stokes method was utilized in a two-dimensional fully implicit mode to calculate the flowfield of a single expansion ramp nozzle configuration. The code has been shown previously to be fairly accurate in predicting three-dimensional nozzle flowfields and internal performance for several axisymmetric and nonaxisymmetric geometries. A two-dimensional implementation of the method was used to reduce the resources required to obtain preliminary performance parameters of nozzle concepts. A two-dimensional description of a single-expansion ramp nozzle configuration was analyzed to verify the applicability of the Navier-Stokes code and nozzle performance package to this class of nozzles. Internal static pressure distributions, discharge coefficient and thrust ratio quantities were calculated for a range of operating conditions. Comparisons of predicted performance parameters with experimental data were within 0.5 percent for mass flow, and typically within l.5 percent for thrust ratio.

Carlson, John R.↗
DOE OSTI2022

Determination of the spent fuel decay heat with the VERA core simulator

VERA core simulator capabilities to predict spent fuel decay heat have been explored. The comparison with the Serpent2 and NEWT/TRITON sequence from the SCALE package, performed on the NPP Krško fuel test cases, has enabled independent verification of the successful implementation of the VERA depletion/decay calculation sequence applied on the extended nuclide set. Since the VERA is a 3-D core simulator, the focus in the rest of the paper was on the investigation of the 3-D effects and non-linearity of the soluble boron concentration averaging process, which are difficult to assess with most of available computational tools. A difference in the decay heat prediction between the 3-D and 2-D model approaches was analyzed. In addition, the impact of the Inconel grids on the decay heat was determined. Averaging the concentration of soluble boron over the fuel irradiation period has been found to be a viable approach, since it results in slight decay heat overprediction, which is considered conservative for most applications. Finally, demonstration on the Watts Bar Unit 1 cycle 1 depletion has shown formidable VERA capabilities to accurately predict spent fuel decay heat.

Kromar, Marjan↗