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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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DOE OSTI2021

OCHRE™ (Object-Oriented Controllable High-Resolution Residential Energy Model) [SWR-19-71]

OCHRE™: Object-Oriented Controllable High-Resolution Residential Energy Model A high-fidelity, high-resolution residential building model with behind-the-meter DERs and flexible load models that integrates with controllers and distribution models in building-to-grid co-simulation platforms. The full documentation for OCHRE can be found at https://ochre-docs-final.readthedocs.io/en/latest/

Maguire, Jeffrey↗

NASA NTRS1984

Thermal barrier coating life prediction model development

The objective of this program is to develop an integrated life prediction model accounting for all potential life-limiting Thermal Barrier Coating (TBC) degradation and failure modes including spallation resulting from cyclic thermal stress, oxidative degradation, hot corrosion, erosion, and foreign object damage (FOD). The mechanisms and relative importance of the various degradation and failure modes will be determined, and the methodology to predict predominant mode failure life in turbine airfoil application will be developed and verified. An empirically based correlative model relating coating life to parametrically expressed driving forces such as temperature and stress will be employed. The two-layer TBC system being investigated, designated PWA264, currently is in commercial aircraft revenue service. It consists of an inner low pressure chamber plasma-sprayed NiCoCrAlY metallic bond coat underlayer (4 to 6 mils) and an outer air plasma-sprayed 7 w/o Y2O3-ZrO2 (8 to 12 mils) ceramic top layer.

Demasi, J.↗

NASA NTRS2003

A New Objective Technique for Verifying Mesoscale Numerical Weather Prediction Models

This report presents a new objective technique to verify predictions of the sea-breeze phenomenon over east-central Florida by the Regional Atmospheric Modeling System (RAMS) mesoscale numerical weather prediction (NWP) model. The Contour Error Map (CEM) technique identifies sea-breeze transition times in objectively-analyzed grids of observed and forecast wind, verifies the forecast sea-breeze transition times against the observed times, and computes the mean post-sea breeze wind direction and speed to compare the observed and forecast winds behind the sea-breeze front. The CEM technique is superior to traditional objective verification techniques and previously-used subjective verification methodologies because: It is automated, requiring little manual intervention, It accounts for both spatial and temporal scales and variations, It accurately identifies and verifies the sea-breeze transition times, and It provides verification contour maps and simple statistical parameters for easy interpretation. The CEM uses a parallel lowpass boxcar filter and a high-order bandpass filter to identify the sea-breeze transition times in the observed and model grid points. Once the transition times are identified, CEM fits a Gaussian histogram function to the actual histogram of transition time differences between the model and observations. The fitted parameters of the Gaussian function subsequently explain the timing bias and variance of the timing differences across the valid comparison domain. Once the transition times are all identified at each grid point, the CEM computes the mean wind direction and speed during the remainder of the day for all times and grid points after the sea-breeze transition time. The CEM technique performed quite well when compared to independent meteorological assessments of the sea-breeze transition times and results from a previously published subjective evaluation. The algorithm correctly identified a forecast or observed sea-breeze occurrence or absence 93% of the time during the two- month evaluation period from July and August 2000. Nearly all failures in CEM were the result of complex precipitation features (observed or forecast) that contaminated the wind field, resulting in a false identification of a sea-breeze transition. A qualitative comparison between the CEM timing errors and the subjectively determined observed and forecast transition times indicate that the algorithm performed very well overall. Most discrepancies between the CEM results and the subjective analysis were again caused by observed or forecast areas of precipitation that led to complex wind patterns. The CEM also failed on a day when the observed sea- breeze transition affected only a very small portion of the verification domain. Based on the results of CEM, the RAMS tended to predict the onset and movement of the sea-breeze transition too early and/or quickly. The domain-wide timing biases provided by CEM indicated an early bias on 30 out of 37 days when both an observed and forecast sea breeze occurred over the same portions of the analysis domain. These results are consistent with previous subjective verifications of the RAMS sea breeze predictions. A comparison of the mean post-sea breeze winds indicate that RAMS has a positive wind-speed bias for .all days, which is also consistent with the early bias in the sea-breeze transition time since the higher wind speeds resulted in a faster inland penetration of the sea breeze compared to reality.

Case, Jonathan L.↗

NASA NTRS1997

Object-Oriented Control System Design Using On-Line Training of Artificial Neural Networks

This report deals with the object-oriented model development of a neuro-controller design for permanent magnet (PM) dc motor drives. The system under study is described as a collection of interacting objects. Each object module describes the object behaviors, called methods. The characteristics of the object are included in its variables. The knowledge of the object exists within its variables, and the performance is determined by its methods. This structure maps well to the real world objects that comprise the system being modeled. A dynamic learning architecture that possesses the capabilities of simultaneous on-line identification and control is incorporated to enforce constraints on connections and control the dynamics of the motor. The control action is implemented "on-line", in "real time" in such a way that the predicted trajectory follows a specified reference model. A design example of controlling a PM dc motor drive on-line shows the effectiveness of the design tool. This will therefore be very useful in aerospace applications. It is expected to provide an innovative and noval software model for the rocket engine numerical simulator executive.

Rubaai, Ahmed↗

DOE OSTI2023

Control oriented model order reduction for the hydraulic system of an autonomous wheel loader

Control design for an autonomous wheel loader requires a high-fidelity and low-order dynamics model. The objective of order reduction is to decrease the number of states in the model while maintaining performance comparable to the original model. Of all the power components in a wheel loader, the model order reduction for steering and working hydraulic systems is most demanding due to its nonlinear and stiff dynamical nature. This paper describes a physics-inspired model order reduction method that can reduce the model order by close to thirty percent. It is achieved by discarding orders with fast dynamics and consolidating multiple states into less new states. Furthermore, this method can also be extended to other types of off-road vehicles such as excavators, bulldozers, etc. Simulation results demonstrate that the reduced-order model exhibits very similar performance to the full-order model under typical operating conditions of wheel loaders, with an output error of less than six percent.

42 ENGINEERING↗

DOE OSTI2024

ForceGen: End-to-end de novo protein generation based on nonlinear mechanical unfolding responses using a language diffusion model

Through evolution, nature has presented a set of remarkable protein materials, including elastins, silks, keratins and collagens with superior mechanical performances that play crucial roles in mechanobiology. However, going beyond natural designs to discover proteins that meet specified mechanical properties remains challenging. Here, we report a generative model that predicts protein designs to meet complex nonlinear mechanical property-design objectives. Our model leverages deep knowledge on protein sequences from a pretrained protein language model and maps mechanical unfolding responses to create proteins. Via full-atom molecular simulations for direct validation, we demonstrate that the designed proteins are de novo, and fulfill the targeted mechanical properties, including unfolding energy and mechanical strength, as well as the detailed unfolding force-separation curves. Our model offers rapid pathways to explore the enormous mechanobiological protein sequence space unconstrained by biological synthesis, using mechanical features as the target to enable the discovery of protein materials with superior mechanical properties.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2013

On the Performance of Global Magnetohydrodynamic Models in the Earth's Magnetosphere

We study the performance of four magnetohydrodynamic models (BATS-R-US, GUMICS, LFM, Open GGCM) in the Earths magnetosphere. Using the Community Coordinated Modeling Centers Run-on-Request system, we compare model predictions with magnetic field measurements of the Cluster, Geotail and Wind spacecraft during a multiple substorm event. We also compare model cross polar cap potential results to those obtained from the Super Dual Auroral Radar Network(SuperDARN) and the model magnetopause standoff distances to an empirical magnetopause model. The correlation coefficient (CC) and prediction efficiency (PE) metrics are used to objectively evaluate model performance quantitatively. For all four models, the best performance outside geosynchronous orbit is found on the dayside. Generally, the performance of models decreases steadily down stream from the Earth. On the dayside most CCs are above 0.5 with CCs for Bx and Bz close to 0.9 for three out of four models. In the magnetotail at a distance of about -130 Earth radii from Earth, the prediction efficiency of all models is below that of using an average value for the prediction with the exception of Bz. Bx is most often best predicted and correlated both on the dayside and the nightside close to the Earth whereas in the far tail the CC and PE for Bz are substantially higher than other components in all models. We also find that increasing the resolution or coupling an additional physics module does notautomatically increase the model performance in the magnetosphere.

geomagnetic tail↗

DOE OSTI2024

Numerical Evaluation of Effective Thermal Conductivity of PCM with Metal Foam Incorporating Buoyancy Effects for Thermal Energy Storage

The thermal energy storage (TES) system has the capability to efficiently preserve thermal energy directly derived from the energy source, minimizing any conversion losses. Especially latent heat storage offers distinct advantages, including a substantial increase in energy storage density and minimization of temperature fluctuations within the plants. However, the phase change material (PCM) employed in latent heat storage has low thermal conductivity. Consequently, various studies are being conducted to enhance heat transfer. One approach to enhance heat transfer involves utilizing metal foam to maximize the heat transfer area. However, modeling metal foam with its intricate structure is a challenging task in numerical analysis. For this reason, ongoing research focuses on simplifying the modeling of metal foam. Nevertheless, fully encompassing all the characteristics of actual metal foam proves to be a challenging task for the simplified analytical model. The objective of this paper is to interpret the simple lattice metal foam analysis model from the perspective of behavior induced by buoyancy. When comparing the analysis results of solid PCM and liquid PCM with the same thermal conductivity under changes in porosity and gravity direction, we conducted an analysis to discern the trends in effective thermal conductivity that are overestimated due to convection. In the analysis, a constant heat flux of 10 kW and a constant surface boundary condition of 350 K were applied, and a sensitivity study regarding the mesh was conducted. The results indicate that, from the perspective of gravity in the simple lattice model, the solid analysis yields an effective thermal conductivity 29-47% higher compared to the liquid analysis. Additionally, as porosity increases, there is an observed increase of 24-33% in effective thermal conductivity.

25 ENERGY STORAGE↗

DOE OSTI2021

Cosmologically Coupled Compact Objects: A Single-parameter Model for LIGO–Virgo Mass and Redshift Distributions

Abstract We demonstrate a single-parameter route for reproducing higher mass objects as observed in the LIGO–Virgo mass distribution, using only the isolated-binary stellar evolution channel. This single parameter encodes the cosmological mass growth of compact stellar remnants that exceed the Tolman–Oppenheimer–Volkoff limit. Cosmological mass growth appears in known solutions to General Relativity with cosmological boundary conditions. We consider the possibility of solutions with cosmological boundary conditions, which reduce to Kerr on timescales short compared to the Hubble time. We discuss complementary observational signatures of these solutions that can confirm or invalidate their astrophysical relevance.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1986

Generalized three-dimensional experimental lightning code (G3DXL) user's manual

Information concerning the programming, maintenance and operation of the G3DXL computer program is presented and the theoretical basis for the code is described. The program computes time domain scattering fields and surface currents and charges induced by a driving function on and within a complex scattering object which may be perfectly conducting or a lossy dielectric. This is accomplished by modeling the object with cells within a three-dimensional, rectangular problem space, enforcing the appropriate boundary conditions and differencing Maxwell's equations in time. In the present version of the program, the driving function can be either the field radiated by a lightning strike or a direct lightning strike. The F-106 B aircraft is used as an example scattering object.

Kunz, Karl S.↗

NASA NTRS1993

Advanced Multi-Phase Flow CFD Model Development for Solid Rocket Motor Flowfield Analysis

It is known that the simulations of solid rocket motor internal flow field with AL-based propellants require complex multi-phase turbulent flow model. The objective of this study is to develop an advanced particulate multi-phase flow model which includes the effects of particle dynamics, chemical reaction and hot gas flow turbulence. The inclusion of particle agglomeration, particle/gas reaction and mass transfer, particle collision, coalescence and breakup mechanisms in modeling the particle dynamics will allow the proposed model to realistically simulate the flowfield inside a solid rocket motor. The Finite Difference Navier-Stokes numerical code FDNS is used to simulate the steady-state multi-phase particulate flow field for a 3-zone 2-D axisymmetric ASRM model and a 6-zone 3-D ASRM model at launch conditions. The 2-D model includes aft-end cavity and submerged nozzle. The 3-D model represents the whole ASRM geometry, including additional grain port area in the gas cavity and two inhibitors. FDNS is a pressure based finite difference Navier-Stokes flow solver with time-accurate adaptive second-order upwind schemes, standard and extended k-epsilon models with compressibility corrections, multi zone body-fitted formulations, and turbulence particle interaction model. Eulerian/Lagrangian multi-phase solution method is applied for multi-zone mesh. To simulate the chemical reaction, penalty function corrected efficient finite-rate chemistry integration method is used in FDNS. For the AL particle combustion rate, the Hermsen correlation is employed. To simulate the turbulent dispersion of particles, the Gaussian probability distribution with standard deviation equal to (2k/3)(exp 1/2) is used for the random turbulent velocity components. The computational results reveal that the flow field near the juncture of aft-end cavity and the submerged nozzle is very complex. The effects of the turbulent particles affect the flow field significantly and provide better prediction of the ASRM performance. The multi-phase flow analysis using the FDNS code in the present research can be used as a design tool for solid rocket motor applications.

Liaw, Paul↗

NASA NTRS1997

Building an Integrated Environment for Multimedia

Multimedia courseware on the solar system and earth science suitable for use in elementary, middle, and high schools was developed under this grant. The courseware runs on Silicon Graphics, Incorporated (SGI) workstations and personal computers (PCs). There is also a version of the courseware accessible via the World Wide Web. Accompanying multimedia database systems were also developed to enhance the multimedia courseware. The database systems accompanying the PC software are based on the relational model, while the database systems accompanying the SGI software are based on the object-oriented model.

Source record↗

NASA NTRS2018

Deepti: Deep Learning-Based Tropical Cyclone Intensity Estimation

We present the development of a deep learning model for objective estimation of tropical cyclone intensity at a higher temporal frequency, deployment of the model in production, design and implementation of the tropical cyclone monitoring and intensity estimation system and development of an interactive portal for situational awareness and evaluation of intensity estimation.

Maskey, Manil↗

NASA NTRS1991

Software For Depiction Of Three-Dimensional Objects

HME (Hierarchical Modeling Environment) is three-dimensional computer-graphics software system designed to give user complete access to total hierarchical mathematical model. Enables user to build, manipulate, and display hierarchical three-dimensional objects dynamically. Also includes created polygons in hierarchy. Establishes and edits proper coordination of eye points, sources of light, and connectivity of model necessary for accurate depiction of model. Written in C language.

Taylor, Frank↗

DOE OSTI2021

Simplifying and Visualizing the Ontology of Systems Engineering Models

The credibility of an engineering model is of critical importance in large-scale projects. How concerned should an engineer be when reusing someone else's model when they may not know the author or be familiar with the tools that were used to create it? In this report, the authors advance engineers' capabilities for assessing models through examination of the underlying semantic structure of a model--the ontology. This ontology defines the objects in a model, types of objects, and relationships between them. In this study, two advances in ontology simplification and visualization are discussed and are demonstrated on two systems engineering models. These advances are critical steps toward enabling engineering models to interoperate, as well as assessing models for credibility. For example, results of this research show an 80% reduction in file size and representation size, dramatically improving the throughput of graph algorithms applied to the analysis of these models. Finally, four future problems are outlined in ontology research toward establishing credible models--ontology discovery, ontology matching, ontology alignment, and model assessment.

42 ENGINEERING↗

NASA NTRS2015

The JPL Uranian Radiation Model (UMOD)

The objective of this study is the development of a comprehensive radiation model (UMOD) of the Uranian environment for JPL mission planning. The ultimate goal is to provide a description of the high energy electron and proton environments and the magnetic field at Uranus that can be used for engineering design. Currently no model exists at JPL. A preliminary electron radiation model employing Voyager 2 data was developed by Selesnick and Stone in 1991. The JPL Uranian Radiation Model extends that analysis, which modeled electrons between 0.7 MeV and 2.5 MeV based on the Voyager Cosmic Ray Subsystem electron telescope, down to an energy of 0.022 MeV for electrons and from 0.028 MeV to 3.5 MeV for protons. These latter energy ranges are based on measurements by the Applied Physics Laboratory Low Energy Charged Particle Detector on Voyager 2. As in previous JPL radiation models, the form of the Uranian model is based on magnetic field coordinates and requires a conversion from spacecraft coordinates to Uranian-centered magnetic "B-L" coordinates. Two magnetic field models have been developed for Uranus: 1) a simple "offset, tilted dipole" (OTD), and 2) a complex, multi-pole expansion model ("Q3"). A review of the existing data on Uranus and a search of the NASA Planetary Data System (PDS) were completed to obtain the latest, up to date descriptions of the Uranian high energy particle environment. These data were fit in terms of the Q3 B-L coordinates to extend and update the original Selesnick and Stone electron model in energy and to develop the companion proton flux model. The flux predictions of the new model were used to estimate the total ionizing dose for the Voyager 2 flyby, and a movie illustrating the complex radiation belt variations was produced to document the uses of the model for planning purposes.

Garrett, Henry↗

NASA NTRS2017

The JPL Neptune Radiation Model (NMOD)

The objective of this study is the development of a comprehensive radiation model of the Neptunian environment for JPL mission planning. The ultimate goal is to provide a description of the high-energy electron and proton environments and the magnetic field at Neptune that can be used for engineering design. The JPL Neptune Radiation Model (NMOD) models the high-energy electrons and protons between 0.025 MeV and 5 MeV based on the California Institute of Technology's Cosmic Ray Subsystem and the Applied Physics Laboratory's Low Energy Charged Particle Detector on Voyager 2. As in previous JPL radiation models, the form of the Neptunian model is based on magnetic field coordinates and requires a conversion from spacecraft coordinates to Neptunian-centered magnetic "B-L" coordinates. Two types of magnetic field models have been developed for Neptune: 1) simple "offset, tilted dipoles" (OTD), and 2) a complex, multi-pole expansion model ("O8"). A review of the existing data on Neptune and a search of the NASA Planetary Data System (PDS) were completed to obtain the most current descriptions of the Neptunian high-energy particle environment. These data were fit in terms of the O8 B-L coordinates to develop the electron and proton flux models. The flux predictions of the new model were used to estimate the total ionizing dose (TID) rate along the Neptunian equator, meridional flux contours for the electrons and protons, and for flux and dose comparisons with the other radiation belts in the Solar System.

Garrett, Henry↗

NASA NTRS2017

The JPL Neptune Radiation Model (NMOD)

magnetic field↗