SEARCH · Engineering Papers

Results for “Adaptation 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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

NASA NTRS2017

Adaptive Management Using Remote Sensing and Ecosystem Modeling in Response to Climate Variability and Invasive Aquatic Plants for the California Sacramento-San Joaquin Delta Water Resource

The California Sacramento-San Joaquin River Delta is the hub for California's water supply and supports important ecosystem services, agriculture, and communities in Northern to Southern California. Expansion of invasive aquatic plants in the Delta coupled with impacts of changing climate and long-term drought is detrimental to the San Francisco Bay/California Delta complex. NASA Ames Research Center and the USDA-ARS partnered with the State of California to develop science-based, adaptive-management strategies for invasive aquatic plant in the Sacramento-San Joaquin Delta. Specific mapping tools developed utilizing satellite and airborne platforms provide regular assessments of population dynamics on a landscape scale and support both strategic planning and operational decision making for resource managers. San Joaquin and Sacramento River watersheds water quality input to the Delta is modeled using the Soil-Water Assessment Tool (SWAT) and a modified SWAT tool has been customized to account for unique landscape and management of agricultural water supply and drainage within the Delta. Environmental response models for growth of invasive aquatic weeds are being parameterized and coupled with spatial distribution/biomass density mapping and water quality to study ecosystem response to climate and aquatic plant management practices. On the water validation and operational utilization of these tools by management agencies and how they are improving decision making, management effectiveness and efficiency will be discussed. The project combines science, operations, and economics related to integrated management scenarios for aquatic weeds to help land and water resource managers make science-informed decisions regarding management and outcomes.

Adaptive↗

DOE OSTI2024

WaterTAP-REFLO models of Solar Still, Solar Still ZLD, Enhanced Evaporation pond results for baseline analysis

This folder contains results from models that were adapted into WaterTAP-REFLO. The files contain inputs and outputs for solar still, solar still ZLD, and enhanced evaporation pond unit process models for 4 different locations in the USA: Phoenix, Miami, Houston, and Baltimore. The WaterTAP-REFLO implementation may be different and thus may have different results. The data structure and content are described in a ReadMe.txt file. For WaterTAP-REFLO documentation and/or contact the developers please see: https://github.com/watertap-org/watertap-reflo.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1994

Characterization of Metal Matrix Composites

Experimental methods were developed, adapted, and applied to the characterization of a metal matrix composite system, namely, silicon carbide/aluminim (SCS-2/6061 Al), and its constituents. The silicon carbide fiber was characterized by determining its modulus, strength, and coefficient of thermal expansion. The aluminum matrix was characterized thermomechanically up to 399 C (750 F) at two strain rates. The unidirectional SiC/Al composite was characterized mechanically under longitudinal, transverse, and in-plane shear loading up to 399 C (750 F). Isothermal and non-isothermal creep behavior was also measured. The applicability of a proposed set of multifactor thermoviscoplastic nonlinear constitutive relations and a computer code was investigated. Agreement between predictions and experimental results was shown in a few cases. The elastoplastic thermomechanical behavior of the composite was also described by a number of new analytical models developed or adapted for the material system studied. These models include the rule of mixtures, composite cylinder model with various thermoelastoplastic analyses and a model based on average field theory. In most cases satisfactory agreement was demonstrated between analytical predictions and experimental results for the cases of stress-strain behavior and thermal deformation behavior at different temperatures. In addition, some models yielded detailed three-dimensional stress distributions in the constituents within the composite.

Daniel, I. M.↗

DOE OSTI2020

Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections

Connected and Automated Vehicles (CAVs) can potentially improve the performance of the transportation system by reducing human errors. This paper investigates the safety impact of CAVs in a mixed traffic with conventional vehicles at intersections. Analyzing real-world AV crashes in California revealed that rear-end crashes at intersections are the dominant crash type. Therefore, to enhance our understanding of the future interactions between human-driven vehicles with CAVs at intersections, a simulation framework was developed to model the mixed traffic environment of Automated Vehicles (AV), cooperative AVs, and conventional human-driven vehicles. In order to model AVs driving behavior, Adaptive Cruise Control (ACC) and cooperative ACC (CACC) models are utilized. Particularly, this study explores system improvements due to automation and connectivity across varying CAV market penetration scenarios. ACC and CACC car following models are used to mimic the behavior of AVs and cooperative AVs. Real-world connected vehicle data are utilized to modify and tune the acceleration/deceleration regimes of the Wiedemann model. Next, the driving volatility concept capturing variability in vehicle speeds was utilized to calibrate the simulation to represent the safety performance of a real-world environment. Two surrogate safety measures are used to evaluate the safety performance of a representative intersection under different market penetration rate of CAVs: the number of longitudinal conflicts and driving volatility. At low levels of ACC market penetration, the safety improvements were found to be marginal, but safety improved substantially with more than 40% ACC penetration. Additional safety improvements can be achieved more quickly through the addition of cooperation and connectivity through CACC. Furthermore, ACC/CACC vehicles were found to improve mobility performance in terms of average speed and travel time at intersections.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1993

The NASA/GISS Mars general circulation model: Preliminary experiments

The NASA/GISS Mars General Circulation Model (GCM) is an adapted version of the GISS Global Climate/Middle Atmosphere Model, specifically developed for the diagnostic validation and objective analysis of measured atmospheric temperatures from the Mars Observer Pressure Modulator Infrared Radiometer (PMIRR) experiment. The GISS Mars GCM has 23 vertical layers extending from the surface to approximately 80 km altitude, representing a vertical resolution of about 0.3 scale heights. The primitive (vertically hydrostatic) equations are solved in finite difference form on the Krakawa B grid, with a horizontal resolution of 8 deg x 10 deg (latitude-longitude). The model includes a diurnal solar cycle, heat transport within a two-layer ground, and a high-order 'slopes-scheme' for the advection of heat in the upper atmosphere. The radiative transfer scheme is based on the correlated k distribution method for the treatment of nongray gaseous absorption thermal emission, and multiple scattering, including options for suspended dust. A special feature of the model of particular importance for Mars is a parameterization of gravity-wave-induced drag incorporating orographic forcing, wind shear, convection, and radiative damping. The implementation of the GISS Mars model includes global maps of topography, roughness, and albedo.

Allison, Michael↗

NASA NTRS1998

The NASA-Langley Wake Vortex Modelling Effort in Support of an Operational Aircraft Spacing System

Two numerical modelling efforts, one using a large eddy simulation model and the other a numerical weather prediction model, are underway in support of NASA's Terminal Area Productivity program. The large-eddy simulation model (LES) has a meteorological framework and permits the interaction of wake vortices with environments characterized by crosswind shear, stratification, humidity, and atmospheric turbulence. Results from the numerical simulations are being used to assist in the development of algorithms for an operational wake-vortex aircraft spacing system. A mesoscale weather forecast model is being adapted for providing operational forecast of winds, temperature, and turbulence parameters to be used in the terminal area. This paper describes the goals and modelling approach, as well as achievements obtained to date. Simulation results will be presented from the LES model for both two and three dimensions. The 2-D model is found to be generally valid for studying wake vortex transport, while the 3-D approach is necessary for realistic treatment of decay via interaction of wake vortices and atmospheric boundary layer turbulence. Meteorology is shown to have an important affect on vortex transport and decay. Presented are results showing that wake vortex transport is unaffected by uniform fog or rain, but wake vortex transport can be strongly affected by nonlinear vertical change in the ambient crosswind. Both simulation and observations show that atmospheric vortices decay from the outside with minimal expansion of the core. Vortex decay and the onset three-dimensional instabilities are found to be enhanced by the presence of ambient turbulence.

Proctor, Fred H.↗

NASA NTRS2015

Simulation of Atmospheric-Entry Capsules in the Subsonic Regime

The accuracy of Computational Fluid Dynamics predictions of subsonic capsule aerodynamics is examined by comparison against recent NASA wind-tunnel data at high-Reynolds-number flight conditions. Several aspects of numerical and physical modeling are considered, including inviscid numerical scheme, mesh adaptation, rough-wall modeling, rotation and curvature corrections for eddy-viscosity models, and Detached-Eddy Simulations of the unsteady wake. All of these are considered in isolation against relevant data where possible. The results indicate that an improved predictive capability is developed by considering physics-based approaches and validating the results against flight-relevant experimental data.

Simulation↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.

Bucket Drum Excavators↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

bucket drum excavators↗

NASA NTRS1991

The AFIT gross motion control project

The objective of the Gross Motion Control project is to study alternative control approaches that will provide payload invariant high speed trajectory tracking for nonrepetitive motions in free space. The research has concentrated on modifications to the model-based control structure. Development and evaluation is being actively pursued of both adaptive primary (inner loop) and robust secondary (output loop) controllers. In-house developments are compared and contrasted to the techniques proposed by other researchers. The case study for the evaluation is the first three links of a PUMA-560. Incorporating the principals of multiple model adaptive estimation, artificial neural networks, and Lyapunov theory into the model based paradigm has shown the potential for enhanced tracking. Secondary controllers based on Quantitative Feedback Theory, or augmented with auxiliary inputs, significantly improve the robustness to payload variations and unmodeled drive system dynamics. An overview is presented of the different concepts under investigation and a sample is provided of the latest experimental results.

Leahy, M. B., Jr.↗

NASA NTRS1988

Adaptive wall research with two- and three-dimensional models in low speed and transonic tunnels

This paper summarises recent research at the University of Southampton into adaptive wall technology and outlines the direction of current efforts. The work is aimed at developing techniques for use in test sections where the top and bottom walls may be adjusted in single curvature. Wall streamlining eliminates, as far as experimentally possible, the top and bottom wall interference in low speed and transonic aerofoil testing. A streamlining technique has been developed for low speeds which allows the testing of swept wing panels in low interference environments. At higher speeds, a comparison of several two-dimensional transonic streamlining algorithms has been made and a technique for streamlining with a choked test section has also been developed. Three-dimensional work has mainly concentrated on tests of sidewall mounted half-wings and the development of the software packages required to assess interference and to adjust the flexible walls. It has been demonstrated that two-dimensional wall adaptation can significantly modify the level of wall interference around relatively large three-dimensional models. The residual interferences are small and are probably amenable to standard post-test correction methods. Tests on a calibrated wing-body model are planned in the near future to further validate the proposed streamlining technique.

Lewis, M. C.↗

DOE OSTI2022

Coupled Neutronic and Thermal Hydraulic Analysis of a Natural Circulation Based Small Modular Reactor (SMR) Using VERA-CS

As part of the work supported by a US Department of Energy (DOE) Office of Nuclear Energy Gateway for Accelerated Innovation in Nuclear FY 2020 Voucher, Holtec International subsidiary SMR LLC (hereinafter referred to as Holtec) and Oak Ridge National Laboratory entered into a cooperative research and development agreement (CRADA) to develop coupled multiphysics core models of the Holtec developed small modular reactor (SMR), SMR-160. The scope of the 1 year project was to use the DOE–developed tool set, VERA, to analyze several aspects of a representative SMR-160 core design. The goals of the project were to perform the code-to-code benchmarking and to provide Holtec with a confirmatory calculations to compare against the results with the codes used in the SMR-160 design, identify and resolve areas of discrepancy between the two models to give Holtec a basis for selecting certain tool and model options, and develop a workflow so that the VERA model could be adapted easily to any future changes in the design of the SMR-160 core. The work proceeded in four phases: 1. Developing the initial VERA model based on Holtec-provided core design information; 2. Comparing VERA results with Holtec-provided calculations for the first five cycles; 3. Developing a VERA transient model based on the prior model; and 4. Training Holtec personnel on VERA and hand-off the developed models. This report summarizes at a high level the completed tasks. Details of the tasks and results are reserved for the full report, which will not be publicly released for 5 years per the terms of the CRADA. The report is titled “Coupled Neutronic and Thermal Hydraulic Analysis of a Natural Circulation Based Small Modular Reactor (SMR) using VERA-CS” and has the ORNL technical report number ORNL/TM 2021/2303 (NFE-20-08305)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Terminus: A Versatile Simulator for Space-based Telescopes

Space-based telescopes offer unparalleled opportunities for characterizing exoplanets, solar system bodies, and stellar objects. However, observatories in low-Earth orbits (e.g., Hubble, CHaracterising ExOPlanets Satellite, Twinkle, and an ever-increasing number of cubesats) cannot always be continuously pointed at a target due to Earth obscuration. For exoplanet observations consisting of transit, or eclipse, spectroscopy, this causes gaps in the light curve, which reduces the information content and can diminish the science return of the observation. Terminus, a time-domain simulator, has been developed to model the occurrence of these gaps to predict the potential impact on future observations. The simulator is capable of radiometrically modeling exoplanet observations as well as producing light curves and spectra. Here, Terminus is baselined on the Twinkle mission, but the model can be adapted for any space-based telescope and is especially applicable to those in a low-Earth orbit. Terminus also has the capability to model observations of other targets such as asteroids or brown dwarfs.

47 OTHER INSTRUMENTATION↗

NASA NTRS1979

Supercritical tests of a self-optimizing, variable-Camber wind tunnel model

A testing procedure was used in a 16-foot Transonic Propulsion Wind Tunnel which leads to optimum wing airfoil sections without stopping the tunnel for model changes. Being experimental, the optimum shapes obtained incorporate various three-dimensional and nonlinear viscous and transonic effects not included in analytical optimization methods. The method is a closed-loop, computer-controlled, interactive procedure and employs a Self-Optimizing Flexible Technology wing semispan model that conformally adapts the airfoil section at two spanwise control stations to maximize or minimize various prescribed merit functions subject to both equality and inequality constraints. The model, which employed twelve independent hydraulic actuator systems and flexible skins, was also used for conventional testing. Although six of seven optimizations attempted were at least partially convergent, further improvements in model skin smoothness and hydraulic reliability are required to make the technique fully operational.

Levinsky, E. S.↗

NASA NTRS2011

Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

Frost, Susan A.↗

DOE OSTI2024

Neural Network Prediction of Strong Lensing Systems with Domain Adaptation and Uncertainty Quantification

Modeling strong gravitational lenses is computationally expensive for the complex data from modern and next-generation cosmic surveys. Deep learning has emerged as a promising approach for finding lenses and predicting lensing parameters, such as the Einstein radius. Mean-variance Estimators (MVEs) are a common approach for obtaining aleatoric (data) uncertainties from a neural network prediction. However, neural networks have not been demonstrated to perform well on out-of-domain target data successfully - e.g., when trained on simulated data and applied to real, observational data. In this work, we perform the first study of the efficacy of MVEs in combination with unsupervised domain adaptation (UDA) on strong lensing data. The source domain data is noiseless, and the target domain data has noise mimicking modern cosmology surveys. We find that adding UDA to MVE increases the accuracy on the target data by a factor of about two over an MVE model without UDA. Including UDA also permits much more well-calibrated aleatoric uncertainty predictions. Advancements in this approach may enable future applications of MVE models to real observational data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Thermodynamics-guided machine learning model for predicting convective boundary layer height and its multi-site applicability

Accurate estimation of convective boundary layer height (CBLH) is vital for weather, climate, and air quality modeling. Machine learning (ML) shows promise in CBLH prediction, but input parameter selection often lacks physical grounding, limiting generalizability. This study introduces a novel ML framework for CBLH prediction, integrating thermodynamic constraints and the diurnal CBLH cycle as an implicit physical guide. Boundary layer growth is modeled as driven by surface heat fluxes and atmospheric heat absorption represented with the low tropospheric stability, using the diurnal cycle as input and output. TPOT and AutoKeras are employed to select optimal models, validated against Doppler lidar-derived CBLH data, achieving an R 2 of 0.84 across untrained years. Comparisons of eddy covariance (ECOR) and energy balance Bowen ratio (EBBR) flux measurements show the same prediction capability. Models trained on the ARM SGP C1 site with ECOR data and tested at E37 and E39 yield R 2 values of 0.79 and 0.81, respectively, demonstrating their adaptability. The ML model trained with all sites' data slightly enhances the performance compared with ML models trained over single-site data. The interquartile range for predicted CBLH is consistently narrower than that for DL-derived CBLH, reflecting lower variability in predicted CBLH compared to DL-derived CBLH, which is influenced by additional factors, which are not well represented with the model inputs. The model's generalizability across multiple sites at the ARM SGP site demonstrates its potential for transfer to greater distances, offering a scalable approach for enhancing boundary layer parameterization in atmospheric models.

Chu, Yufei [Stony Brook Univ., NY (United States)]↗

NASA NTRS2011

Piloting Changes to Changing Aircraft Dynamics: What Do Pilots Need to Know?

An experiment was conducted to quantify the effects of changing dynamics on a subject s ability to track a signal in order to eventually model a pilot adapting to changing aircraft dynamics. The data will be used to identify primary aircraft dynamics variables that influence changes in pilot s response and produce a simplified pilot model that incorporates this relationship. Each run incorporated a different set of second-order aircraft dynamics representing short period transfer function pitch attitude response: damping ratio, frequency, gain, zero location, and time delay. The subject s ability to conduct the tracking task was the greatest source of root mean square error tracking variability. As for the aircraft dynamics, the factors that affected the subjects ability to conduct the tracking were the time delay, frequency, and zero location. In addition to creating a simplified pilot model, the results of the experiment can be utilized in an advisory capacity. A situation awareness/prediction aid based on the pilot behavior and aircraft dynamics may help tailor pilot s inputs more quickly so that PIO or an upset condition can be avoided.

Trujillo, Anna C.↗