Engineering Papers⌕ Search

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.

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

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Modeling of a Solid Oxide Fuel Cell as Part of a Predictive Functional Model for Aerospace Fuel-Cell Systems

This paper will discuss initial efforts at modeling a solid oxide fuel cell (SOFC) for aerospace applications. Fuel cells historically have been used in spacecraft from the Gemini to the Shuttle era for providing spacecraft power with the added benefit of producing water for crew use. However, there are many potential applications for fuel cells and electrolyzers in spaceflight, including oxygen generation, in-situ resource utilization (ISRU) and propellant production. This proof-of-concept model has been developed using a commercial multiphysics modeling software package. Two-dimensional and one-dimensional isothermal models were created based on a certain SOFC design and results were compared to test data from the real system. Local Butler-Volmer kinetic relations were adjusted, and an effective porous medium approach was taken in order to capture how the many interconnects between cells in the gas channels affected fluid flow. The model was able to reproduce polarization curves derived from test data within around 0.02 Volts for a given current density. This model could be adapted to model a solid oxide electrolyzer, proton exchange membrane fuel cell, or other type of fuel cell technology in order to understand how these types of technologies could fit into broader spacecraft designs and advance the capabilities of spaceflight systems.

Mary Lou Nadeau↗
NASA NTRSDate not supplied

Modeling of a Solid Oxide Fuel Cell as Part of a Predictive Functional Model for Aerospace Fuel-Cell Systems

This paper will discuss initial efforts at modeling a solid oxide fuel cell (SOFC) for aerospace applications. Fuel cells historically have been used in spacecraft from the Gemini to the Shuttle era for providing spacecraft power with the added benefit of producing water for crew use. However, there are many potential applications for fuel cells and electrolyzers in spaceflight, including oxygen generation, in-situ resource utilization (ISRU) and propellant production. This proof-of-concept model has been developed using a commercial multiphysics modeling software package. Two-dimensional and one-dimensional isothermal models were created based on a certain SOFC design and results were compared to test data from the real system. Local Butler-Volmer kinetic relations were adjusted, and an effective porous medium approach was taken in order to capture how the many interconnects between cells in the gas channels affected fluid flow. The model was able to reproduce polarization curves derived from test data within around 0.02 Volts for a given current density. This model could be adapted to model a solid oxide electrolyzer, proton exchange membrane fuel cell, or other type of fuel cell technology in order to understand how these types of technologies could fit into broader spacecraft designs and advance the capabilities of spaceflight systems.

Mary Lou Nadeau↗
NASA NTRSDate not supplied

Modeling of a Solid Oxide Fuel Cell as Part of a Predictive Functional Model for Aerospace Fuel-Cell Systems

This paper will discuss initial efforts at modeling a solid oxide fuel cell (SOFC) for aerospace applications. Fuel cells historically have been used in spacecraft from the Gemini to the Shuttle era for providing spacecraft power with the added benefit of producing water for crew use. However, there are many potential applications for fuel cells and electrolyzers in spaceflight, including oxygen generation, in-situ resource utilization (ISRU) and propellant production. This proof-of-concept model has been developed using a commercial multiphysics modeling software package. Two-dimensional and one-dimensional isothermal models were created based on a certain SOFC design and results were compared to test data from the real system. Local Butler-Volmer kinetic relations were adjusted, and an effective porous medium approach was taken in order to capture how the many interconnects between cells in the gas channels affected fluid flow. The model was able to reproduce polarization curves derived from test data within around 0.02 Volts for a given current density. This model could be adapted to model a solid oxide electrolyzer, proton exchange membrane fuel cell, or other type of fuel cell technology in order to understand how these types of technologies could fit into broader spacecraft designs and advance the capabilities of spaceflight systems.

Mary Lou Nadeau↗
NASA NTRSDate not supplied

Modeling of a Solid Oxide Fuel Cell as Part of a Predictive Functional Model for Aerospace Fuel-Cell Systems

This paper will discuss initial efforts at modeling a solid oxide fuel cell (SOFC) for aerospace applications. Fuel cells historically have been used in spacecraft from the Gemini to the Shuttle era for providing spacecraft power with the added benefit of producing water for crew use. However, there are many potential applications for fuel cells and electrolyzers in spaceflight, including oxygen generation, in-situ resource utilization (ISRU) and propellant production. This proof-of-concept model has been developed using a commercial multiphysics modeling software package. Two-dimensional and one-dimensional isothermal models were created based on a certain SOFC design and results were compared to test data from the real system. Local Butler-Volmer kinetic relations were adjusted, and an effective porous medium approach was taken in order to capture how the many interconnects between cells in the gas channels affected fluid flow. The model was able to reproduce polarization curves derived from test data within around 0.02 Volts for a given current density. This model could be adapted to model a solid oxide electrolyzer, proton exchange membrane fuel cell, or other type of fuel cell technology in order to understand how these types of technologies could fit into broader spacecraft designs and advance the capabilities of spaceflight systems.

Mary Lou Nadeau↗
DOE OSTI2021

Adapting Existing Energy Models for Resilience Analysis

Resilience is a topic receiving much attention in relation to energy systems, with particular attention being paid to the supply of electricity. As a result of the growing interest in energy sector resilience, research communities have proposed a plethora of candidate resilience indicators and metrics, most of which remain immature at different scales and segments within the energy system. A necessary focus of the research community lies in implementing, testing, and validating resilience metrics and analysis approaches in energy sector models, which will be invaluable for informing resilience planning and investment decisions. Recognizing these challenges that need to be addressed, we explore how to effectively integrate resilience considerations into energy sector models and tools. The overarching goal of the effort was to evaluate the data needs, methodologies, and outcomes—including consequences and/or changes in investment or operational decisions due to avoided consequences—based on resilience analysis in a range of existing tools. In particular, we selected five models originally built at NREL to explore non-resilience energy research questions to implement and exercise resilience metrics and analysis approaches. To demonstrate the importance of perspective, we selected models that represent different segments of the energy sector, geographic scales, and modeling approaches. A second important aspect of our effort was the development of generalized power interruption scenarios. These scenarios were intended to help establish a framework for simulating the effects of real-world threats in terms of their impacts on system components and, in turn, power interruption.

ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2009

Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control

This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.

Nguyen, Nhan T.↗
NASA NTRS1987

Direct adaptive control of manipulators in Cartesian space

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.

Seraji, H.↗
DOE OSTI2025

Response functions and giant monopole resonances for light to medium-mass nuclei from the ab initio symmetry-adapted no-core–shell model

Using the ab initio symmetry-adapted no-core–shell model, we compute sum rules and response functions for light to medium-mass nuclei, starting from interactions that are derived in the chiral effective field theory. Specifically, we investigate electromagnetic transitions of monopole, dipole and quadrupole nature for 4 He, and explore dominant features of giant monopole resonances in symmetric nuclei such as the closed-shell 4 He and 16 O light nuclei, the intermediate-mass open-shell 20 Ne and the medium-mass closed-shell 40 Ca. Furthermore, for the NNLO opt chiral potential, we determine parameter-free monopole sum rules, which can provide information on the incompressibility of symmetric nuclear matter. Here, we report 213(10) MeV as an estimate for the compression modulus for infinite nuclear matter, which overlaps with the lower range of values often used in current astrophysical applications.

ab initio nuclear structure↗
NASA NTRS2009

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Bakhtiari-Nejad, Maryam↗
DOE OSTI2021

MACHINE LEARNING BASED CHEMICAL EXPLOSIVE MODE ANALYSIS (ML-CEMA)

The software consists of a Machine Learning based Chemical Explosive Mode Analysis (ML-CEMA) tool for advanced computational flame diagnostics. CEMA, originally based on eigen-analysis of the local thermochemical system, is capable of identifying reaction fronts and limit phenomena such as auto-ignition and extinction in practical combustion systems, such as internal combustion engines and gas turbine combustors. However, the original CEMA is computationally expensive for large reaction mechanisms that are typically needed to describe fuel chemistry of practical large-hydrocarbon fuels. This novel ML-CEMA tool employs a ML technique to accelerate the eigen-analysis of the basic CEMA approach by orders of magnitude, thus making it suitable for practical fuels. In ML-CEMA,zero-dimensional (0D) reactors and one-dimensional (1D) premixed flames are first used to generate a large number of data points for neural network based ML training. The trained ML model is then used to perform CEMA prediction. This ML-CEMA tool has been demonstrated in canonical 0D and 1D configurations as well as highly-transient three-dimensional spray flames exhibiting multi-mode turbulent combustion, showing promising results. ML-CEMA, as a standalone tool, can be used for computationally-efficient diagnostics of massive datasets generated from both experiments and simulations. For example, based on spatially resolved measurements of a small set of reactive scalars(such as temperature, hydroxyl radical and formaldehyde), ML-CEMA can effectively identify flame fronts and rare events. ML-CEMA also provides a robust online or offline flame feature detection tool. When used for on-the-fly simulations, ML-CEMA further enables zone-adaptive combustion modeling, in which the predicted eigenvalue is used as a robust mode indicator for judicious assignment of locally-valid combustion models. This ML-CEMA based zone-adaptive model can lead to substantial computational cost savings when used for large-scale simulations of multi-mode combustion systems. Third Party Code Web Page to Download Code Web Page Location of Third Party License

Xu, Chao↗
NASA NTRS1975

Parameter adaptive control of multivariable systems

Model reference adaptive controllers for multivariable plants are designed using only input and output signals rather than the complete state vector. The design is based on Liapunov's direct method, and the Meyer-Kalman-Yacubovich lemma. State variable filters are employed to avoid differentiating output signals. Augmented error signals are used in deriving stable adaptive control laws which assure that the normally used response error signals approach zero asymptotically.

Monopoli, R. V.↗
DOE OSTI2023

EUI Benchmarks for Net-Zero Energy Buildings in India

In our study we present EUI benchmarks for NZEBs for six building types across residential and non-residential typologies and for India's five climate zones. This approach is similar to the simulation-based benchmarks used by the B3 program in Minnesota, the Cal-Arch methodology in California, and the US Solar Decathlon approach, which combine simulations with actual building data. Of the six building types we explore one in detail with a range of operation scenarios, specifically narrowing down the EUI benchmarks for mixed-mode building operation and for variable temperature set-points as prescribed in the National Building Code of India.The contribution of this work is to provide rigorous end-use level EUI benchmarks for six building types, and to describe a method for simulation-based EUI benchmarks for mixed-mode operation with variable setpoints to highlight the difference between the standard approach used for the five building types and the On-Site Construction Worker Housing which additionally has the mixed-mode variable setpoint approach.On-Site Construction Worker Housings are typically poorly constructed temporary structures, without adequate thermal comfort, It is critical to provide adequate thermal comfort to protect people from the warming effects of climate change, and to discover super efficient and cost-effective ways to do so.The methodology used for the On-Site Construction Worker Housing (CWH) results in an 80% acceptability according to the India Model for Adaptive Comfort in the National Building Code of India. EUIs of all six buildings are 60% lower than the minimum compliance with India's Energy Conservation Building Codes, providing benchmarks for efficiency levels. The end-use level EUI benchmarks are now provided to over 1800 Solar Decathlon India participants so that they can compare the performance of their NZEB designs.In particular, the CWH results provide an insight into the importance of the mixed-mode operation with variable temperature set-points. The results from the simulation study show that for an NZEB target, the EUI with standard thermal comfort model and without mixed operation is 58.26 kWh/m2*year, while that with the variable set-points of the adaptive model with mixed mode operation is 24.23 kWh/m2*year. This is a 58% reduction in EUI. Given that many building types including residential, and non-residential operate in mixed mode, it is important to take this work further to develop mixed-mode operation NZEB benchmarks so that the carbon intensity of these buildings could be lower than the standard thermal comfort model approach.

benchmarking↗
DOE OSTI2021

An adaptive granular representative volume element model with an evolutionary periodic boundary for hierarchical multiscale analysis

The hierarchical multiscale analysis normally utilizes a microscopic representative volume element (RVE) model to capture path/history-dependent macroscopic responses instead of using phenomenological constitutive models. However, for problems involving large deformation, the current RVE model used in geomechanics may lose representative properties due to the progressive distortion of the RVE box, unless a proper reinitialization is applied. This work develops an adaptive RVE model in conjunction with an evolutionary periodic boundary (EPB) algorithm for hierarchical multiscale analysis of granular materials undergoing large deformation based on a recent RVE model proposed for coupling molecular dynamics and the material point method. The proposed adaptive RVE model avoids the reinitialization of the RVE box that even undergoes extremely large shear deformation; meanwhile, it accounts for the deformation history of the RVE model and treats the interaction between boundary particles and other image particles in a more efficient way. Numerical examples with extremely large deformation are used to illustrate the adaptive granular RVE model enhanced by the proposed EPB algorithm. Furthermore, some key features of this new methodology are further discussed for clarification.

42 ENGINEERING↗
NASA NTRS2018

Autonomous Guidance Algorithms for NASA Learn-to-Fly Technology Development

Learn-to-Fly (L2F) is an advanced technology development effort under the NASA Transformative Aeronautics Concepts Program (TACP) that is aimed at assessing the feasibility of self-learning flight vehicles. Specifically, research has been conducted to demonstrate the potential to merge two enabling technologies; real-time aerodynamic modeling and adaptive controls, to substantially reduce the typical ground and flight testing requirements for air vehicle design. The approach to this effort involved development of unique airframes and on-board algorithms to demonstrate key L2F technologies on a fully autonomous flight test vehicle. This research, that included an aggressive flight test program, was intended to rapidly advance these technologies and demonstrate capabilities of the L2F approach. Key components of the L2F architecture include real-time aerodynamic modeling, adaptive controls and control allocation, and guidance. This paper provides an overview of the guidance algorithm which primarily served as an executive function to coordinate control commands for range navigation and the desired test conditions, provide autonomous envelope limiting/expansion and enable automatic landing to touchdown with no intervention from a human operator. A discussion of the L2F concept-of-operations and unique flight testing considerations, which influenced the guidance functional requirements, is included and results of recent flight testing are presented.

Foster, John V.↗