Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Generative models”

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 1,171 records · Page 65

Towards a New Generation of Agricultural System Data, Models and Knowledge Products: Design and Improvement

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

Agricultural systems↗

Enhancing power grid resilience to winter storms via generator winterization with equity considerations

Here we develop two-stage stochastic programming models for generator winterization that enhance power grid resilience while incorporating social equity. The first stage in our models captures the investment decisions for generator winterization, and the second stage captures the operation of a degraded power grid, with the objective of minimizing load shed and social inequity. To incorporate equity into our models, we propose a concept called adverse effect probability that captures the disproportionate effects of power outages on communities with varying vulnerability levels. Grid operations are modeled using DC power flow, and equity is captured through mean or maximum adverse effects experienced by communities. We apply our models to a synthetic Texas power grid, using winter storm scenarios created from the generator outage data from the 2021 Texas winter storm. Our extensive numerical experiments show that more equitable outcomes, in the sense of reducing adverse effects experienced by vulnerable communities during power outages, are achievable with no impact on total load shed through investing in winterization of generators in different locations and capacities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Magnetic Circuit Model of PM Motor-Generator to Predict Radial Forces

A magnetic circuit model is developed for a PM motor for flywheel applications. A sample motor is designed and modeled. Motor configuration and selection of materials is discussed, and the choice of winding configuration is described. A magnetic circuit model is described, which includes the stator back iron, rotor yoke, permanent magnets, air gaps and the stator teeth. Iterative solution of this model yields flux linkages, back EMF, torque, power, and radial force at the rotor caused by eccentricity. Calculated radial forces are then used to determine motor negative stiffness.

McLallin, Kerry↗

Integrated Modeling for the Next Generation Space Telescope "Yardstick" Concept

The so-called NASA "Yardstick" design concept for the Next Generation Space Telescope presents unique challenges for systems-level analysis. Simulations that integrate controls, optics, thermal, and structural models are required to evaluate baseline performance, study design sensitivities, and perform design optimization. An integrated modeling approach was chosen using a combination of commercial off-the-shelf and "in-house" developed codes. The resulting capability provides a foundation for linear and non-linear analysis, using both the time and frequency-domain methods. It readily allows various combinations of design parameters and environmental loads to be evaluated directly in terms of key science-related metrics, in this case the scalar RMS (root mean square) line-of-sight and RMS wavefront errors. This presentation first addresses the development of the component, or discipline, models for the Yardstick design. It will then proceed to present the integration of the component models, using linear-systems approaches, in order to support two of the most critical baseline performance analyses: jitter and thermal-elastic stability of the optical telescope assembly (OTA). The results of the jitter analysis indicate that disturbances from the reaction wheels coupled with the lightly-damped and highly-flexible structure present significant challenges to the baseline line-of-sight control architecture. Vibration isolation will be required to meet jitter error requirements. The results of the thermal-elastic analysis indicate that the mirror segment displacements due to ground-to-orbit cool-down of the telescope are within the expected capture range of the segment rigid-body control actuators. This means we will be able to align and phase the primary mirror. However, the results for the analysis of the thermal transient response following an attitude maneuver (slew) show that this telescope design is not sufficiently stable, passively, to meet the wavefront error requirements. Structural re-design is one possibility; alternatively, active thermal control of the OTA may be considered. The Yardstick integrated models were successfully used to demonstrate the feasibility of two thermal control strategies.

Mosier, Gary E.↗

An Empirical Model for Vane-Type Vortex Generators in a Navier-Stokes Code

An empirical model which simulates the effects of vane-type vortex generators in ducts was incorporated into the Wind-US Navier-Stokes computational fluid dynamics code. The model enables the effects of the vortex generators to be simulated without defining the details of the geometry within the grid, and makes it practical for researchers to evaluate multiple combinations of vortex generator arrangements. The model determines the strength of each vortex based on the generator geometry and the local flow conditions. Validation results are presented for flow in a straight pipe with a counter-rotating vortex generator arrangement, and the results are compared with experimental data and computational simulations using a gridded vane generator. Results are also presented for vortex generator arrays in two S-duct diffusers, along with accompanying experimental data. The effects of grid resolution and turbulence model are also examined.

Dudek, Julianne C.↗

Some useful innovations with TRASYS and SINDA-85

Several innovative methods were used to allow more efficient and accurate thermal analysis using SINDA-85 and TRASYS, including model integration and reduction, planetary surface calculations, and model animation. Integration with other modeling and analysis codes allows an analyst to import a geometry from a solid modeling or computer-aided design (CAD) software package, rather than building the geometry 'by hand.' This is more efficient as well as potentially more accurate. However, the use of solid modeling software often generates large analytical models. The problem of reducing large models was elegantly solved using the response of the transient derivative to a forcing step function. The thermal analysis of a lunar rover implemented two unusual features of the TRASYS/SINDA system. A little-known TRASYS routine SURFP calculates the solar heating of a rover on the lunar surface for several different rover positions and orientations. This is used not only to determine the rover temperatures, but also to automatically determine the power generated by the solar arrays. The animation of transient thermal results is an effective tool, especially in a vivid case such as the 14-day progress of the sun over the lunar rover. An animated color map on the solid model displays the progression of temperatures.

Amundsen, Ruth M.↗

Some Useful Innovations with Trasys and Sinda-85

Several innovative methods have been used to allow more efficient and accurate thermal analysis using SINDA-85 and TRASYS, including model integration and reduction, planetary surface calculations, and model animation. Integration with other modeling and analysis codes allows an analyst to import a geometry from a solid modeling or computer-aided design (CAD) software package, rather than building the geometry "by hand." This is more efficient as well as potentially more accurate. However, the use of solid modeling software often generates large analytical models. The problem of reducing large models has been elegantly solved using the response of the transient derivative to a forcing step function. The thermal analysis of a lunar rover implemented two unusual features of the TRASYS/SINDA system. A little-known TRASYS routine SURFP calculates the solar heating of a rover on the lunar surface for several different rover positions and orientations. This is used not only to determine the rover temperatures, but also to automatically determine the power generated by the solar arrays. The animation of transient thermal results is an effective tool, especially in a vivid case such as the 14-day progress of the sun over the lunar rover. An animated color map on the solid model displays the progression of temperatures.

Amundsen, Ruth M.↗

Controls/CFD Interdisciplinary Research Software Generates Low-Order Linear Models for Control Design From Steady-State CFD Results

The NASA Lewis Research Center is developing analytical methods and software tools to create a bridge between the controls and computational fluid dynamics (CFD) disciplines. Traditionally, control design engineers have used coarse nonlinear simulations to generate information for the design of new propulsion system controls. However, such traditional methods are not adequate for modeling the propulsion systems of complex, high-speed vehicles like the High Speed Civil Transport. To properly model the relevant flow physics of high-speed propulsion systems, one must use simulations based on CFD methods. Such CFD simulations have become useful tools for engineers that are designing propulsion system components. The analysis techniques and software being developed as part of this effort are an attempt to evolve CFD into a useful tool for control design as well. One major aspect of this research is the generation of linear models from steady-state CFD results. CFD simulations, often used during the design of high-speed inlets, yield high resolution operating point data. Under a NASA grant, the University of Akron has developed analytical techniques and software tools that use these data to generate linear models for control design. The resulting linear models have the same number of states as the original CFD simulation, so they are still very large and computationally cumbersome. Model reduction techniques have been successfully applied to reduce these large linear models by several orders of magnitude without significantly changing the dynamic response. The result is an accurate, easy to use, low-order linear model that takes less time to generate than those generated by traditional means. The development of methods for generating low-order linear models from steady-state CFD is most complete at the one-dimensional level, where software is available to generate models with different kinds of input and output variables. One-dimensional methods have been extended somewhat so that linear models can also be generated from two- and three-dimensional steady-state results. Standard techniques are adequate for reducing the order of one-dimensional CFD-based linear models. However, reduction of linear models based on two- and three-dimensional CFD results is complicated by very sparse, ill-conditioned matrices. Some novel approaches are being investigated to solve this problem.

Melcher, Kevin J.↗

Generation of Mars Helicopter Rotor Model for Comprehensive Analyses

The present research is aimed at providing a performance model for the Mars Helicopter (MH), to understand the complexity of the flow, and identify future regions of improvement. The low density of the Martian atmosphere and the relatively small MH rotor, result in very low chord-based Reynolds number flows. The low density and Reynolds numbers reduce the lifting force and lifting efficiency, respectively. The high drag coefficients in subcritical flow, especially for thicker sections, are attributed to laminar separation from the rear of the airfoil. In the absence of test data, efforts have been made to explore these effects using prior very low Reynolds number research efforts. The rotor chord-based Reynolds number range is observed to be subcritical, which makes boundary layer transition unlikely to occur. The state of the two-dimensional rotor boundary layer in hover is approximated by calculating the instability point, laminar separation point, and the transition location to provide understanding of the flow state in the high Mach-low Reynolds number regime. The results are used to investigate the need for turbulence modeling in Computational Fluid Dynamics (CFD) calculations afterwards. The goal is to generate a performance model for the MH rotor for a free wake analysis, because the computational budget for a complete Navier-Stokes solution for a rotating body-fitted rotor is substantial. In this study, a Reynolds-Averaged Navier-Stokes (RANS) based approach is used to generate the airfoil deck using C81Gen with stitched experimental data for very high angles of attack. A full Grid Resolution Study is performed and over 4,500 cases are completed to create the full airfoil deck. The laminar separation locations are predicted within the accuracy of the approximate method when compared with the CFD calculations. The model is presented through airfoil data tables (c81 files) that are used by comprehensive rotor analysis codes such as CAMRADII, or the mid-fidelity CFD solver RotCFD. Finally, the rotor performance is compared with experimental data from the 25ft Space Simulator at the NASA Jet Propulsion Laboratory (JPL) and shows good correlation for the rotor Figure of Merit over the available thrust range.

Model↗

Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing

We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.

97 MATHEMATICS AND COMPUTING↗

Data and Code for Understanding Generative AI Content with Embedding Models

This repository contains code for the experiments in the paper "Understanding Generative AI Content with Embedding Models". Constructing high-quality features is critical to any quantitative data analysis. While feature engineering was historically addressed by carefully hand-crafting data representations based on domain expertise, deep neural networks (DNNs) now offer a radically different approach. DNNs implicitly engineer features by transforming their input data into hidden feature vectors called embeddings. For embedding vectors produced by foundation models -- which are trained to be useful across many contexts -- we demonstrate that simple and well-studied dimensionality-reduction techniques such as Principal Component Analysis uncover inherent heterogeneity in input data concordant with human-understandable explanations. Of the many applications for this framework, we find empirical evidence that there is intrinsic separability between real samples and those generated by artificial intelligence (AI).

Vargas, Max [Pacific Northwest National Laboratory↗

Beam-generated upper hybrid noise in Jupiter's outer magnetosphere

A model for generation of upper hybrid waves in Jupiter's outer magnetosphere is presented. Energetic electrons accelerated on high-latitude auroral field lines at 1 R(J) altitudes are assumed to stream outwards to the distant magnetosphere. The large decrease in the local magnetic field strength results in a highly collimated, field-aligned electron beam due to conservation of the particle's magnetic moment. As the beam travels outward it passes through the plasma sheet boundary layer region located on the edges of the plasma sheet. Because of the large field-aligned anisotropy of the beam, the distribution is unstable to the excitation of the upper hybrid waves which amplify and then undergo mode conversion at the f(p) layer to generate the Jovian continuum radiation. A novel feature of the model is the beam-anisotropic heat flux instability which drives UH waves unstable without the need for any positive slope on the electron distribution function.

Barbosa, D. D.↗

Hydropower Energy Storage Capacity (HESC) Dataset

The Hydropower Energy Storage Capacity (HESC) Dataset catalogs characteristics that are relevant to evaluating reservoir storage and estimates of energy storage capacity based on varying levels of detail. Hydropower dams and reservoirs were included based on information from the National Inventory of Dams (NID; USACE, 2021) and Global Reservoir and Dam (GRanD v1.3) and Existing Hydropower Assets datasets. These data provide a foundation for understanding available resources at existing hydropower facilities and their potential to provide storage of energy and more flexible generation. Estimates of energy storage capacity include: • Level 1 – nominal energy storage capacity based on maximum storage capacities and hydraulic head • Level 2 – nominal energy storage capacity based on historical models or observations of reservoir volume and hydraulic head. These estimates are provided based on capacity from the entire historical period as well as monthly values. • Level 3 – modeled energy generation based on volume-elevation relationships, historical storage, observed/modeled inflows, and hydraulic capacity of turbines and calculated both as overall and on a monthly basis. • Level 4 – modeled energy generation incorporating information from Level 3 and operational constraints. For facilities where installed capacity is known, there are also estimates for discharge duration (the length of time when a facility could provide generation at a given capacity).

13 HYDRO ENERGY↗

An experimental and modeling study on autoignition of 2-phenylethanol and its blends with n-heptane

2-Phenylethanol (2-PE) is an aromatic alcohol with high research octane number, high octane sensitivity, and a potential to be produced using biomass. Considering that 2-PE can be used as a fuel additive for boosting the anti-knocking quality of gasoline in spark-ignition engines and as the low reactivity fuel or fuel component in dual-fuel reactivity controlled compression ignition (RCCI) engines, it is of fundamental and practical interest to understand the autoignition chemistry of 2-PE, especially at low-to-intermediate temperatures (<1000 K). Based upon the experimental ignition delay time (IDT) results of neat 2-PE obtained from our previous rapid compression machine (RCM) investigation and the literature shock tube study, a detailed chemical kinetic model of 2-PE is developed herein, covering low-to-high temperature regimes. Besides, RCM experiments using binary fuel blends of 2-PE and n-heptane (nC7) are conducted in this work to investigate the nC7/2-PE blending effects, as they represent a dual-fuel system for RCCI operations. Furthermore, the newly developed 2-PE model is merged with a well-validated nC7 kinetic model to generate the current nC7/2-PE binary blend model. Overall, the consolidated model reasonably predicts the experimental IDT data of neat 2-PE and nC7/2-PE blends, as well as captures the experimental effects of pressure, equivalence ratio, and blending ratio on autoignition. Finally, model-based chemical kinetic analyses are carried out to understand and identify the controlling chemistry accounting for the observed blending effects in RCM experiments. In conclusion, the analyses reveal that nC7 enhances 2-PE autoignition via providing extra $\dot{O}$H radicals to the shared radical pool, while the diminished nC7 promoting effect on 2-PE autoignition with increasing temperature is due to the negative temperature coefficient characteristics of nC7.

2-phenlyethanol↗

Large Ensemble Exploration of Global Energy Transitions Under National Emissions Pledges

Global climate goals require a transition to a deeply decarbonized energy system. Meeting the objectives of the Paris Agreement through countries' nationally determined contributions and long-term strategies represents a complex problem with consequences across multiple systems shrouded by deep uncertainty. Robust, large-ensemble methods and analyses mapping a wide range of possible future states of the world are needed to help policymakers design effective strategies to meet emissions reduction goals. This study contributes a scenario discovery analysis applied to a large ensemble of 5,760 model realizations generated using the Global Change Analysis Model. Eleven energy-related uncertainties are systematically varied, representing national mitigation pledges, institutional factors, and techno-economic parameters, among others. The resulting ensemble maps how uncertainties impact common energy system metrics used to characterize national and global pathways toward deep decarbonization. Results show globally consistent but regionally variable energy transitions as measured by multiple metrics, including electricity costs and stranded assets. Larger economies and developing regions experience more severe economic outcomes across a broad sampling of uncertainty. The scale of CO 2 removal globally determines how much the energy system can continue to emit, but the relative role of different CO 2 removal options in meeting decarbonization goals varies across regions. Previous studies characterizing uncertainty have typically focused on a few scenarios, and other large-ensemble work has not (to our knowledge) combined this framework with national emissions pledges or institutional factors. Our results underscore the value of large-ensemble scenario discovery for decision support as countries begin to design strategies to meet their goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Case study of a bore wind-ramp event from lidar measurements and HRRR simulations over ARM Southern Great Plains

The rapid change of wind speed and direction on 21 August 2017 is studied using Doppler lidar measurements at five sites of the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility in north-central Oklahoma. The Doppler lidar data were investigated along with meteorological variables such as temperature, humidity, and turbulence available from the large suite of instrumentation deployed at the SGP Central Facility (C1) during the Land-Atmosphere Feedback Experiment in August 2017. Lidar measurements at five sites, separated by 55-70 km, allowed us to document the development and evolution of the wind flow over the SGP area, examine synoptic conditions to understand the mechanism that leads to the ramp event, and estimate the ability of the High-Resolution Rapid Refresh model to reproduce this event. The flow feature in question is an atmospheric bore, a small-scale phenomenon that is challenging to represent in models, that was generated by a thunderstorm outflow northwest of the ARM SGP area. The small-scale nature of bores, its impact on power generation, and the modeling challenges associated with representing bores are discussed in this paper. In conclusion, the results also provide information about model errors between sites of different surface and vegetation types.

54 ENVIRONMENTAL SCIENCES↗

Development of new baseline models for U.S. medium office buildings based on commercial buildings energy consumption survey data

Building energy estimation for the building sector under various scenarios are needed for building energy regulation and policy making. This often starts with representative baselines (either empirical baseline or modeled baseline). Commercial Buildings Energy Consumption Survey (CBECS) data is a widely used empirical baseline for U.S. commercial buildings, but none of the existing baseline model are developed to represent the CBECS data. This paper aims to develop new baseline models for the U.S. medium office buildings, which can produce modeled baselines consistent with the CBECS data. Here, we introduced the methodology to create baseline models and the criteria to evaluate the performance of baseline models. The methodology consists of three phases: (1) identification of model inputs, (2) model calibration, and (3) model validation with uncertainty analysis. The evaluation index is the coefficient of variation of the root-mean-square deviation (CV(RMSD)) of site energy use intensities (EUIs) between the modeled baseline and empirical baseline. Then 30 new baseline models for two vintages (pre- and post-1980) and 15 climate zones were created. The evaluation shows that the CV(RMSD) is lower than 0.05 for the modeled baselines produced by the new baseline models. As a comparison, the CV(RMSD) is higher than 0.1 for the existing modeled baselines generated by DOE Commercial Reference Building Models. Further analysis shows that the new baseline models are able to capture the uncertainties of the representative features of existing buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗