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Results for “Thermal System Identification”

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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At least 19 records

Thermal Signature Identification System (TheSIS)

We characterize both nonlinear and high order linear responses of fiber-optic and optoelectronic components using spread spectrum temperature cycling methods. This Thermal Signature Identification System (TheSIS) provides much more detail than conventional narrowband or quasi-static temperature profiling methods. This detail allows us to match components more thoroughly, detect subtle reversible shifts in performance, and investigate the cause of instabilities or irreversible changes. In particular, we create parameterized models of athermal fiber Bragg gratings (FBGs), delay line interferometers (DLIs), and distributed feedback (DFB) lasers, then subject the alternative models to selection via the Akaike Information Criterion (AIC). Detailed pairing of components, e.g. FBGs, is accomplished by means of weighted distance metrics or norms, rather than on the basis of a single parameter, such as center wavelength.

Laser↗

Towards Thermal Protection System Certification by Analysis: Identification and Implication of Features

The thermal protection systems (TPS) to be used for upcoming sample return missions (e.g., Mars Sample Return) and future crewed missions to the Moon and Mars are subject to stringent reliability criteria. The certification of TPS is conducted through extensive testing, which can include Arc Jet testing to understand ablative behavior and non-destructive evaluation (NDE) to identify features that could lead to sub-optimal performance during entry. Unexpected features observed during fabrication of large-scale articles often require additional testing to certify, which in the very worst cases can impact schedule and contribute to cost.

J. B. Haskins↗

Greybox Thermal Parameter Identification of Electric Machine Stators

The parameters of electric machine thermal equivalent circuit networks are difficult to predict due to material and manufacturing uncertainties. In this paper, a Greybox system identification approach is used to identify parameters of electric machine stator lumped parameter thermal networks (LPTNs). LPTNs provide a low order, computationally efficient, dynamic model of temperatures at specific locations. Second and third order LPTN model structures are defined as state space equations with stator thermal parameters to be identified. To test the Greybox electric machine stator thermal system identification, five stator motorette prototypes were constructed with controlled variations in slot fill and slot liner thickness. The variation in the motorette thermal parameters and thermal time constants are detected using the Greybox identification. Special attention is given to the impact of sampling rate and Greybox data record length on parameter estimation accuracy.

33 ADVANCED PROPULSION SYSTEMS↗

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Design, Optimization, and Control of a 100 kW Electric Traction Motor Meeting or Exceeding DOE 2025 Targets

The overall objective of the electric motor portion of the Electric Drives Technology consortium is to research, develop, and test electric motors for use in electric vehicle applications capable of a peak power greater than 100 kW, power density greater than or equal to 50 kW/l, and a cost less than 3.3 $/kW. To meet the electric traction motor power density and cost targets a number of approaches were pursued simultaneously throughout the course of this project which address all of the major volumetric power density variables. The specific research thrusts at the Illinois Institute of Technology (IIT) are the following: multiphysics design for increased power density through maximum utilization of active materials, synthesis of electric machine windings and PM flux barriers with controlled space harmonics, high slot fill windings for increased current loadings or efficiency, aggressive cooling strategies, and design studies and prototype construction of candidate electric machines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dynamic Control of Sodium Cold Trap Purification Temperature Using LSTM System Identification

This study investigates the dynamic regulation of the sodium cold trap purification temperature at Argonne National Laboratory’s liquid sodium test facility, employing long short-term memory (LSTM) system identification techniques. The investigation introduces an innovative hybrid approach by integrating model predictive control (MPC) based on first principles dynamic models with a multi-step time–frequency LSTM model in predicting the temperature profiles of a sodium cold trap purification system. The long short-term memory–model predictive controller (LSTM-MPC) model employs a sliding window scheme to gather training samples for multi-step prediction, leveraging historical data to construct predictive models that capture the non-linearities of the complex system dynamics without explicitly modeling the underlying physical processes. The performance of the LSTM-MPC and MPC were evaluated through simulation experiments, where both models were assessed on their capacity to maintain the cold trap temperature within predefined set-points while minimizing deviations and overshoots. Results obtained show how the data-driven LSTM-MPC model demonstrates stability and adaptability. In contrast, the traditional MPC model exhibits irregularities, particularly evident as overshoots around set-point limits, which can potentially compromise its effectiveness over long prediction time intervals. The findings obtained offer valuable insights into integrating data-driven techniques for enhancing real-time monitoring systems.

LSTM-MPC↗

Identification and Evaluation of Thermal Transport Components for Integrated Energy Systems

A proper evaluation and selection of component technologies is a critical aspect in the development of Integrated Energy System (IES). This study aims to investigate the key components and associated technologies required to build high-temperature heat transport systems for IES. Of particular interest is the component technologies needed to design and construct IES that combines advanced nuclear reactors with high-temperature industrial processes. This study particularly delved into knowledge base, evaluation metrics, and state-of-the-art commercial technologies, aiming to facilitate the evaluation and selection process of various thermal transport components. In addition, an evaluation process was proposed in order to assist in the optimal selection of the thermal transport components based on the knowledge base and evaluation metrics investigated through this study.

42 ENGINEERING↗

Online Dynamic Mode Decomposition Based System Identification of Multi-Zone Building HVAC Systems

Many works have recently been conducted to reduce the electricity consumption of smart buildings and allow them to support various grid services. Most of these works require accurate system models for the various appliances in the building including heating, ventilation, and air conditioning (HVAC) units. In this paper, we investigate a recursive data-driven system identification strategy to construct the thermal model for a time-varying building with a multi-zone HVAC unit. The online dynamic mode decomposition (DMD)-based strategy is employed to identify the multi-zone thermal building dynamics, where a simple information update (rank-1) is selected to avoid computational complexity. The DMD-based identification strategy is validated using a real gymnasium building equipped with a 4-zone HVAC unit, and its performance is compared with that of the traditional nuclear-norm subspace identification (N2SID) strategy.

Wu, Tumin [University of Tennessee, Knoxville (UTK↗

Physics vs structure: A systematic benchmark of learning strategies for multi-zone building thermal dynamics

Recent advances in physics-informed and data-driven machine learning promise improved thermal models for advanced building control, yet there is limited quantitative evidence on when added physics structure and architectural complexity are beneficial. Here, this work presents a systematic benchmark of five representative system identification methods for modeling multi-zone building thermal dynamics: linear state-space models, multi-layer perceptrons, neural state-space models, neural ordinary differential equations, and physically-consistent neural networks. The methods are evaluated across multiple data regimes and zone coupling strategies. Using a high-fidelity multi-zone commercial building emulator, we examine short-term and long-term prediction accuracy, computational efficiency, and ease of development. Our results reveal critical trade-offs between prediction performance, model complexity, and physical consistency. We demonstrate that decoupled, nonlinear black-box models consistently outperform coupled physics-constrained architectures in both predictive accuracy and out-of-distribution robustness in majority of the test cases for the building type considered in the study. Our findings quantify the cost of complexity in building thermal modeling and provide concrete, actionable, scenario-based guidelines for selecting model classes for control-oriented applications.

Building thermal modeling↗

High resolution spectrograph

The high resolution spectrograph (HRS) is designed to be used with the Large Space Telescope (LST) for the study of spectra of point and extended targets in the spectral range 110 to 410 nm. It has spectral resolutions of 1,000; 30,000; and 100,000 and has a field of view as large as 10 arc sec. The spectral range and resolution are selectable using interchangeable optical components and an echelle spectrograph is used to display a cross dispersed spectrum on the photocathode of either of 2 SEC orthicon image tubes. Provisions are included for wavelength calibration, target identification and acquisition and thermal control. The system considerations of the instrument are described.

Peacock, K.↗

Identification of salt-alloy combinations for thermal energy storage applications in advanced solar dynamic power systems

Thermodynamic calculations based on the available data for flouride salt systems reveal that a number of congruently melting compositions and eutectics exist which have the potential to meet the lightweight, high energy storage requirements imposed for advanced solar dynamic systems operating between about 1000 and 1400 K. Compatibility studies to determine suitable containment alloys to be used with NaF-22CaF2-13MgF2, NaF-32CaF2, and NaF-23MgF2 have been conducted at the eutectic temperature + 25 K for each system. For these three NaF-based eutectics, none of the common, commercially available high temperature alloys appear to offer adequate corrosion resistance for a long lifetime; however mild steel, pure nickel and Nb-1Zr could prove useful. These latter materials suggest the possibility that a strong, corrosion resistant, nonrefractory, elevated temperature alloy based on the Ni-Ni3Nb system could be developed.

Whittenberger, J. D.↗

Wireless Subsurface Microsensors for Health Monitoring of Thermal Protection Systems on Hypersonic Vehicles

Health diagnostics is an area where major improvements have been identified for potential implementation into the design of new reusable launch vehicles in order to reduce life cycle costs, to increase safety margins, and to improve mission reliability. NASA Ames is leading the effort to develop inspection and health management technologies for thermal protection systems. This paper summarizes a joint project between NASA Ames and SRI International to develop 'SensorTags,' radio frequency identification devices coupled with event-recording sensors, that can be embedded in the thermal protection system to monitor temperature or other quantities of interest. Two prototype SensorTag designs containing thermal fuses to indicate a temperature overlimit are presented and discussed.

Milos, Frank S.↗

Electrical conduction in polymer dielectrics

The use of polymer dielectrics with moderate resistivities could reduce or eliminate problems associated with spacecraft charging. The processes responsible for conduction and the properties of electroactive polymers are reviewed, and correlations drawn between molecular structure and electrical conductivity. These structure-property relationships led to the development of several new electroactive polymer compositions and the identification of several systems that have the requisite thermal, mechanical, environmental and electrical properties for use in spacecraft.

Cotts, D. B.↗

Active airborne infrared laser system for identification of surface rock and minerals

Emissivity and reflectivity in the thermal infrared spectral region (8-13 microns) may be used to discriminate among rocks and minerals. Although considerable success has been achieved in remote sensing classification of rock types based on emissivity measurements made with NASA's Thermal Infreared Multispectral Scanner (TIMS), classification based on reflectivity offers several advantages: much narrower bandwidths are used, higher signal to noise ratios are possible, and measurements are little affected by surface temperature. As a demonstration, an airborne CO2 laser instrument was flown along the margin of Death Valley, California. Measurements of spectral reflectance collected with this device were compared with emissivity measurements made with the TIMS. Data from either instrument provided the means for recognizing boundaries between geologic units including different rock types and fan surfaces of different ages.

Kahle, A. B.↗

Remote Thermal IR Spectroscopy of our Solar System

Indirect methods to detect extrasolar planets have been successful in identifying a number of stars with companion planets. No direct detection of an extrasolar planet has yet been reported. Spectroscopy in the thermal infrared region provides a potentially powerful approach to detection and characterization of planets and planetary systems. We can use knowledge of our own solar system, its planets and their atmospheres to model spectral characteristics of planets around other stars. Spectra derived from modeling our own solar system seen from an extrasolar perspective can be used to constrain detection strategies, identification of planetary class (terrestrial vs. gaseous) and retrieval of chemical, thermal and dynamical information. Emission from planets in our solar system peaks in the thermal infrared region, approximately 10 - 30 microns, substantially displaced from the maximum of the much brighter solar emission in the visible near 0.5 microns. This fact provides a relatively good contrast ratio to discriminate between stellar (solar) and planetary emission and optimize the delectability of planetary spectra. Important molecular constituents in planetary atmospheres have rotational-vibrational spectra in the thermal infrared region. Spectra from these molecules have been well characterized in the laboratory and studied in the atmospheres of solar system planets from ground-based and space platforms. The best example of such measurements are the studies with Fourier transform spectrometers, the Infrared Interferometer Spectrometers (IRIS), from spacecraft: Earth observed from NIMBUS 8, Mars observed from Mariner 9, and the outer planets observed from Voyager spacecraft. An Earth-like planet is characterized by atmospheric spectra of ozone, carbon dioxide, and water. Terrestrial planets have oxidizing atmospheres which are easily distinguished from reducing atmospheres of gaseous giant planets which lack oxygen-bearing species and are characterized by spectra containing hydrocarbons such as methane and ethane. Spectroscopic information on extrasolar planets thus can permit their classification. Spectra and spectral lines contain information on the temperature structure of the atmosphere. Line and band spectra can be used to identify the molecular constituents and retrieve species abundances, thereby classifying and characterizing the planet. At high enough spectral resolution characteristic planetary atmospheric dynamics and unique phenomena such as failure of local thermodynamic equilibrium can be identified. Dynamically induced effects such as planetary rotation and orbital velocity shift and change the shape of spectral features and must be modeled in detailed spectral studies. We will use our knowledge of the compositional, thermal and dynamical characteristics of planetary atmospheres in our own solar system to model spectra observed remotely on similar planets in extrasolar planetary systems. We will use a detailed radiative transfer and beam integration program developed for the modeling and interpretation of thermal infrared spectra measured from nearby planet planets to generate models of an extra-solar "Earth" and "Jupiter". From these models we will show how key spectral features distinguish between terrestrial and gaseous planets, what information can be obtained with different spectral resolution, what spectral features can be used to search for conditions for biogenic activity, and how dynamics and distance modify the observed spectra. We also will look at unique planetary phenomena such as atmospheric lasing and discuss their utility as probes for detection and identification of planets. Results of such studies will provide information to constrain design for instrumentation needed to directly detect extrasolar planets.

Kostiuk, Theodor↗

Airframe Icing Research Gaps: NASA Perspective

qCurrent Airframe Icing Technology Gaps: Development of a full 3D ice accretion simulation model. Development of an improved simulation model for SLD conditions. CFD modeling of stall behavior for ice-contaminated wings/tails. Computational methods for simulation of stability and control parameters. Analysis of thermal ice protection system performance. Quantification of 3D ice shape geometric characteristics Development of accurate ground-based simulation of SLD conditions. Development of scaling methods for SLD conditions. Development of advanced diagnostic techniques for assessment of tunnel cloud conditions. Identification of critical ice shapes for aerodynamic performance degradation. Aerodynamic scaling issues associated with testing scale model ice shape geometries. Development of altitude scaling methods for thermal ice protections systems. Development of accurate parameter identification methods. Measurement of stability and control parameters for an ice-contaminated swept wing aircraft. Creation of control law modifications to prevent loss of control during icing encounters. 3D ice shape geometries. Collection efficiency data for ice shape geometries. SLD ice shape data, in-flight and ground-based, for simulation verification. Aerodynamic performance data for 3D geometries and various icing conditions. Stability and control parameter data for iced aircraft configurations. Thermal ice protection system data for simulation validation.

Potapczuk, Mark↗

Boundary shape identification problems in two-dimensional domains related to thermal testing of materials

The identification of the geometrical structure of the system boundary for a two-dimensional diffusion system is reported. The domain identification problem treated here is converted into an optimization problem based on a fit-to-data criterion and theoretical convergence results for approximate identification techniques are discussed. Results of numerical experiments to demonstrate the efficacy of the theoretical ideas are reported.

Banks, H. T.↗

Boundary shape identification problems in two-dimensional domains related to thermal testing of materials

The identification of the geometrical structure of the system boundary for a two-dimensional diffusion system is reported. The domain identification problem treated here is converted into an optimization problem based on a fit-to-data criterion and theoretical convergence results for approximate identification techniques are discussed. Ressults of numerical experiments to demonstrate the efficacy of the theoretical ideas are reported.

Banks, H. T.↗