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Results for “Thermal network model”

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
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Thermal Network Modelling Handbook

Thermal mathematical modelling is discussed in detail. A three-fold purpose was established: (1) to acquaint the new user with the terminology and concepts used in thermal mathematical modelling, (2) to present the more experienced and occasional user with quick formulas and methods for solving everyday problems, coupled with study cases which lend insight into the relationships that exist among the various solution techniques and parameters, and (3) to begin to catalog in an orderly fashion the common formulas which may be applied to automated conversational language techniques.

Source record↗
DOE OSTI2026

Machine learning-enhanced hybrid modeling approach for better identification of a building thermal network model and improved prediction

The gray-box modeling approach, which uses a semi-physical thermal network model, has been widely used in building prediction applications, such as model predictive control (MPC). However, unmeasured disturbances, such as occupants, lighting, and in/exfiltration loads, make it challenging to apply this approach to practical buildings. In this word, we propose a hybrid modeling approach that integrates the gray-box model with a model for unmeasured disturbance. After reviewing several system identification approaches, we systematically designed the unmeasured disturbance model with a model selection process based on statistical tests to make it robust. We generated data based on the building model calibrated by real operational data and then trained the hybrid model for two different weather conditions. The hybrid model approach demonstrates an RMSE reduction of approximately 0.2–0.9 °C and 0.3–2 °C on 1-day ahead temperature prediction compared to the Conventional approach for mild (Berkeley, CA) and cold (Chicago, IL) climates, respectively. In addition, this approach was applied to experimental data obtained from the laboratory building to be used for the MPC application, showing superior prediction performances.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1988

Evolution and use of combined mechanical and thermal codes for cryogenic turbopump bearings

Shaft bearing system analysis codes were developed, improved, and used to investigate Space Shuttle Main Engine (SSME) Liquid Oxygen (LOX) turbopump bearing problems, and to support the Marshall Space Flight Center Bearing and Seal Materials Test (BSMT) program. Thermal network modeling uses the SINDA thermal code, and the modeling of bearing quasi-dynamic characteristics uses the SHABERTH bearing/shaft code. These codes are solved concurrently for a bearing/shaft system using software developed for this purpose. Simulation of the SSME LOX turbopump turbine and pump end bearings and the MSFC BSMT operating in liquid nitrogen (LN sub 2) and LOX was done. The thermal network models include the bearing components, bearing carriers, shaft, housing, frictional heat, and viscous fluid energy. A cage model was included to account for heat generation between the cage and rolling elements. Since most bearing surfaces operate at temperatures well above the coolant saturation temperature, and move at high speed relative to the coolant, forced convection boiling is the dominant mechanism for heat removal. Improved modeling of forced convection film boiling was incorporated to take into account the local vapor generation at the high temperature surfaces. Rearing preloads in the pump and tester are provided by preload springs. As bearing operating clearances and contact angles change due to thermal effects and loading, the bearing preload changes with these varying conditions. These characteristics were modeled and are included in the overall system models. Results from these models indicate an operational limit which, if exceeded, predicts a thermal excursion.

Cody, Joe C.↗
DOE OSTI2024

Coal-derived conductive pavement for winter de-icing: prototype, modeling, and simulation

Existing pavement de-icing methods result in high installation and maintenance costs, traffic delays, excessive weariness and corrosion, and negative environmental and safety impacts. To overcome these challenges, this paper presents an innovative pathway to designing and constructing smart self-heating pavements using a low-cost coal-char bearing asphalt material. The conductive asphalt incorporates coal char, i.e., a key byproduct of the coal pyrolysis process, into the Stone Mastic Asphalt (SMA) mixture. This asphalt containing coal-derived solid carbon exhibits highly tailorable electrical conductivity, satisfactory mechanical and thermophysical properties, and superior cost-efficiency as compared to other conductive pavement materials. The de-icing performance was also demonstrated by laboratory experiments on a bench-scale prototype. Furthermore, an efficient thermal network model was developed and validated by experiments to investigate the transient thermal behavior and energy performance of the Ohmic heating pavement system. Furthermore, the whole-year energy simulation case studies were conducted on a bridge pavement with an annual energy use of 24.6–1444.8 kWh/m 2 , showcasing its potential in field applications across cool humid, cold humid, and subarctic/arctic climate zones.

42 ENGINEERING↗
NASA NTRS1973

Spacecraft thermal environments.

Definitions are given for spacecraft-surface thermal environment characteristics. Lumped-parameter thermal network modeling techniques are derived for spacecraft thermal environment analysis. The application of these techniques to thermal/vacuum testing is described. A major computer program required by these techniques is outlined. It is noted that this approach has been used to determine thermal environments for the Skylab ATM.

Chapter, J. J.↗
DOE OSTI2025

Development of a data-driven neural network model for electron thermal transport in NSTX

A data-driven electron thermal transport neural network (ETT-NN) model, trained on TRANSP interpretative analysis results of National Spherical Torus Experiment (NSTX), was developed to enable faster and more accurate ETT computation for spherical tokamaks (STs). The model incorporates both convolutional NNs and recurrent NNs, allowing it to simultaneously account for the spatial and temporal non-localities and multi-scale features of turbulent transport, which have been considered only in a limited manner in conventional models. The model was validated through interpretative analysis and predictive simulations using Tokamak Reactor Integrated Automated Suite for Simulation and Computation, demonstrating relatively high accuracy. Additionally, parameter scans were performed on test discharges known to exhibit specific turbulent modes, such as microtearing mode, trapped electron mode, kinetic ballooning mode, and electron temperature gradient mode. The scanning results revealed that the ETT-NN model exhibits the same trends as those observed in conventional gyrokinetic simulations or theories, while also capturing the global nature of turbulent transport, indicating that the data-driven model accurately reflects the underlying physical characteristics. Furthermore, due to the dimensionless nature of the model, we can feasibly expand its applicability by incorporating data from other devices and uncovering the characteristics of ETT in STs in the future.

NSTX↗
NASA NTRS2011

Numerical Modeling of the Chilldown of Cryogenic Transfer Lines Using a Sinda/GFSSP Integrated Solver

An important first step in cryogenic propellant loading is the chilldown of transfer lines. During the chilldown of the transfer line, the flow is two-phase and unsteady, with solid to fluid heat transfer and therefore a coupled thermo-fluid analysis is necessary to model the system. This paper describes a numerical model of pipe chilldown that utilizes the Sinda/GFSSP Conjugate Integrator (SGCI). SGCI is a new analysis tool developed at NASA's Marshall Space Flight Center (MSFC). SGCI facilitates the solution of thermofluid problems in interconnected solid-fluid systems. The solid component of the system is modeled in MSC Patran and translated into an MSC Sinda thermal network model. The fluid component is modeled in GFSSP, the Generalized Fluid System Simulation Program. GFSSP is a general network flow solver developed at NASA/MSFC. GFSSP uses a finite-volume approach to model fluid systems that can include phase change, multiple species, fluid transients, and heat transfer to simple solid networks. SGCI combines the GFSSP Fortran code with the Sinda input file and compiles the integrated model. Sinda solves for the temperatures of the solid network, while GFSSP simultaneously solves the fluid network for pressure, temperature, and flow rate. The two networks are coupled by convection heat transfer from the solid wall to the cryogenic fluid. The model presented here is based on a series of experiments conducted in 1966 by the National Bureau of Standards (NBS). A vacuum-jacketed, 200 ft copper transfer line was chilled by liquid nitrogen and liquid hydrogen. The predictions of transient temperature profiles and chilldown time of the integrated Sinda/GFSSP model will be compared to the experimental measurements.

LeClair, Andre↗
DOE OSTI2026

Geothermal-integrated thermally anisotropic building envelope for energy and peak-demand reduction

Buildings consume large amounts of energy for heating and cooling, while peak electricity demand places significant stress on the power grid. This paper presents a reduced-order co-simulation framework and load-oriented supervisory control strategy for a geothermal-integrated thermally anisotropic building envelope with a ground loop (TABE+GL). In TABE+GL, a hydronic loop embedded in the building envelope is directly coupled with a geothermal ground loop, allowing for bidirectional heat exchange between the envelope, the ground, and the indoor environment. A hybrid co-simulation framework was established by coupling a reduced-order resistor–capacitor (RC) thermal network model with EnergyPlus augmented with GHEDesigner modules. The RC model generated feasible heat flux options under three operating modes, and EnergyPlus predicted sensible loads, energy use, and pump energy demand. At each simulation step, a supervisory control algorithm selected the optimal loop configuration and duty factor that maximizes useful TABE geothermal utilization without exceeding the predicted sensible load, thereby avoiding overheating or cooling. Case studies were conducted for Los Angeles, California, Charleston, South Carolina, and Denver, Colorado. Results showed that the proposed framework reduced HVAC electricity consumption by 43%–67%, natural gas use for space heating by 11%–38%, and peak electricity demand by 43%–88%. These results highlight the potential of combining reduced-order envelope modeling, direct geothermal coupling, and load-oriented supervisory control to improve whole building energy performance and reduce peak demand across diverse weather conditions.

Howard, Daniel [Southern Adventist University]↗
NASA NTRS1973

Thruster array thermal control

This paper presents the results of a preliminary investigation of the thermal interactions between elements in the thruster array for a proposed Encke flyby mission. A clustered eight-thruster array was considered as the trial configuration in the current study. Electrically heated dummy thrusters were calibrated to represent the thruster thermal performance. The thermal behavior of the thruster array thermal mockup and the effects of thermal coating applications were investigated. Temperature measurements of the thruster array mockup were performed under various operational modes to substantiate the analytical results. A resultant analytical thermal network model was established to provide pertinent information for thruster array design tradeoff studies.

Wen, L.↗
NASA NTRS2019

Thermal Analysis of Potted Litz Wire for High-Power-Density Aerospace Electric Machines

Increasing the power density and efficiency of electric machines (motors and generators) is integral to bringing Electrified Aircraft (EA) to commercial realization. To that end an effort to create a High Efficiency Megawatt Motor (HEMM) with a goal of exceeding 98% efficiency and 1.46 MW of power has been undertaken at the NASA Glenn Research Center. Of the motor components the resistive losses in the stator windings are by far the largest contributor (34%) to total motor loss. The challenge is the linear relationship between resistivity and temperature, making machine operation sensitive to temperature increases. In order to accurately predict the thermal behavior of the stator the thermal conductivity of the Litz wire-potting-electrical insulation system must be known. Unfortunately, this multi material system has a wide range of thermal conductivities (0.1 W/m-K – 400 W/m-K) and a high anisotropy (axial vs transverse) making the prediction of the transverse thermal conductivity an in turn the hot spot temperatures in the windings is difficult. In order to do this a device that simulates the thermal environment found in the HEMM stator was designed. This device is not unlike the motorettes (little motors) that are described in IEEE standards for testing electrical insulation lifetimes or other electric motor testing. However, because the HEMM motor design includes significant rotor electrical and thermal considerations the term motorette was not deemed appropriate. Instead statorette (or little stator) was adopted as the term for this test device. This paper discussed the design, thermal heat conjugate analysis (thermal model), manufacturing and testing of HEMM's statorette. Analysis of the results is done by thermal resistance network model and micro thermal model and is compared to analytical predictions of thermal conductivity of the insulated and potted Litz wire system.

Motor↗
NASA NTRS1995

A Network Model for the Effective Thermal Conductivity of Rigid Fibrous Refractory Insulations

A procedure is described for computing the effective thermal conductivity of a rigid fibrous refractory insulation. The insulation is modeled as a 3-dimensional Cartesian network of thermal conductance. The values and volume distributions of the conductance are assigned to reflect the physical properties of the insulation, its constituent fibers, and any permeating gas. The effective thermal conductivity is computed by considering the simultaneous energy transport by solid conduction, gas conduction and radiation through a cubic volume of model insulation; thus the coupling between heat transfer modes is retained (within the simplifications inherent to the model), rather than suppressed by treating these heat transfer modes as independent. The model takes into account insulation composition, density and fiber anisotropy, as well as the geometric and material properties of the constituent fibers. A relatively good agreement, between calculated and experimentally derived thermal conductivity values, is obtained for a variety of rigid fibrous insulations.

Marschall, Jochen↗
NASA NTRS2003

Optimal Feedback Control of Thermal Networks

An improved approach to the mathematical modeling of feedback control of thermal networks has been devised. Heretofore software for feedback control of thermal networks has been developed by time-consuming trial-and-error methods that depend on engineers expertise. In contrast, the present approach is a systematic means of developing algorithms for feedback control that is optimal in the sense that it combines performance with low cost of implementation. An additional advantage of the present approach is that a thermal engineer need not be expert in control theory. Thermal networks are lumped-parameter approximations used to represent complex thermal systems. Thermal networks are closely related to electrical networks commonly represented by lumped-parameter circuit diagrams. Like such electrical circuits, thermal networks are mathematically modeled by systems of differential-algebraic equations (DAEs) that is, ordinary differential equations subject to a set of algebraic constraints. In the present approach, emphasis is placed on applications in which thermal networks are subject to constant disturbances and, therefore, integral control action is necessary to obtain steady-state responses. The mathematical development of the present approach begins with the derivation of optimal integral-control laws via minimization of an appropriate cost functional that involves augmented state vectors. Subsequently, classical variational arguments provide optimality conditions in the form of the Hamiltonian equations for the standard linear-quadratic-regulator (LQR) problem. These equations are reduced to an algebraic Riccati equation (ARE) with respect to the augmented state vector. The solution of the ARE leads to the direct computation of the optimal proportional- and integral-feedback control gains. In cases of very complex networks, large numbers of state variables make it difficult to implement optimal controllers in the manner described in the preceding paragraph.

Papalexandris, Miltiadis↗
NASA NTRS1999

Thermal Analysis of the X-38 Aft Fin During Re-Entry

This document contains the details of the thermal analysis of the X-38 aft fin during re-entry. This analysis was performed in order to calculate temperature response of the aft fin components. This would be provided as input to a structural analysis and would also define the operating environment for the electromechanical actuator (EMA). The calculated structural temperature response would verify the performance of the thermal protection system (TPS). The geometric representation of the aft fin was derived from an I-DEAS finite element model that was used for structural analysis. The thermal mass network model was derived from the geometric representation.

Hong, Andrew E.↗
DOE OSTI2024

Design and evaluation of a dilute flow particle-to-air heat exchanger for energy storage applications

The use of inert and redox-active particles for high-temperature energy storage requires the development of components that can efficiently transfer energy to high-pressure working fluids like supercritical carbon dioxide (sCO 2 ). Dilute flow reactors can enable high working fluid outlet temperatures and minimal parasitic losses compared to moving packed bed and fluidized bed reactors. This research uses both computational and experimental methods to explore the design trade-offs and practical challenges of a novel component for transferring energy from dilute flows of hot, reduced metal oxide (MO x ) particles to sCO 2 in tubes. A discretized thermal resistance network model, which accounts for particle hydrodynamics, multi-mode heat transfer, and reaction equilibrium, guides the design of a prototype device. This device is experimentally tested with a surrogate heat transfer fluids and inert particle temperatures up to 400°C and a heat duty exceeding 1 kW. The data are used to validate the thermal hydraulic sub-models, allowing for the simulation of reacting particle scenarios. Under nominal design conditions, the flow rate of reactive particles is predicted to be 30% lower than that of inert particles for the same energy recovered, with over 70% of the stored particle energy transferred to the sCO 2 . Furthermore, these findings can inform the design of more efficient energy recovery reactors for particle-based systems and can be integrated into system-level concentrated solar power models with thermal storage to optimize operating conditions.

14 SOLAR ENERGY↗
NASA NTRS1982

Orbital performance of a one-year lifetime superfluid helium dewar based on ground testing and computer modelling

The ground-test results of the 550-liter superfluid-He dewar built for IRAS are presented and discussed, and a computer projection of its orbital performance life is developed. The ground-testing program included flow-swap, cold-flow, power-off, hot/cold-viewport, and strap-thermal-efficiency tests. After one set of trials, some design changes were made, and the thermal-network computer model of the system was modified as well. The driving boundary conditions of dewar orbital operation used in this model are vacuum-shell temperature = 170 K, aperture heating = 8.0 mW, and focal-plane power dissipation = 16.2 mW. An operational lifetime of 319 days and an He loss rate of 2.54 mg/sec are predicted.

Hopkins, R. A.↗
NASA NTRSDate not supplied

Scaling Electric Machines to a Megawatt and Material Options

Megawatt (MW) electric aircraft propulsion (EAP) is seen as a significant contributor toward achieving the goals set forth by the Sustainable Flight National Partnership. A large part of enabling MW EAP is developing specific-power-dense electric machines. As specific-power-dense electric machines are scaled up from kW to MW power levels, the thermal stresses on the machines increase in both magnitude and performance-affecting characteristics. This is particularly true for the stators of these machines. Analysis via thermal resistance network modeling and multiscale modeling reveals that increasing amounts of heat will be trapped in the stator windings as the power levels increase. The challenges this presents can be addressed through material advancements whereby materials gain multifunctionality. Specifically, the electrical insulation and potting materials, along with the electrical conductor, that compose the stator slot must work together (gain multifunctionality) to relieve the increased thermal stress. Materials research at the NASA Glenn Research Center points to some useful solutions in this trade space.

Electric Machine↗