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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
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 NTRS1985

An Overview of Latest Model Reduction and Control Methods of Large Flexible Space Structures

The latest trends and theoretical developments involved with the modeling and control of Large Flexible Space Structures (LFSS) are described. The paper addresses first the basic problems, characteristics, and difficulties inherent in modeling and control of LFSS. Major sources of difficulties and errors are the stiffness and damping operators of the dynamic model. Extensions of Linear Quadratic Gaussian (LQG) theory as applied to LFSS are presented, including frequency-shaped cost functionals and perturbation methods. The minimum data/maximum entropy approach which uses a stochastic design model to overcome difficulties found in the LQG-based methods is described. Latest trends in system theory including balanced realization and singular-value analysis are used to determine reduced order controllers and models. Ad hoc methods such as component cost analysis and modal cost analysis are discussed in context with the closed-loop reduction problem of controller order versus performance. The minimum data/maximum entropy approach also addresses controller order versus performance. Those areas of control science and large scale systems that appear to have an important role in understanding and solving LFSS modeling and control are also identified.

Santiago, J. M.↗
NASA NTRSDate not supplied

Full-Envelope Aero-Propulsive Model Identification for Lift+Cruise Aircraft Using Computational Experiments

This paper describes a process utilizing computational fluid dynamics experiments to develop a reduced-order, integrated propulsion-airframe aerodynamic model for a lift+cruise electric vertical takeoff and landing (eVTOL) reference aircraft concept. eVTOL configurations exhibit aerodynamic characteristics of both fixed-wing and rotary-wing aircraft as well as complex phenomena, such as propulsion-airframe interactions. Consequently, conventional aircraft aerodynamic modeling strategies require modification when applied to these unique aircraft. A novel aero-propulsive modeling approach using design of experiments techniques and computational fluid dynamics simulations is postulated for modeling a lift+cruise aircraft configuration. Aero-propulsive models are developed throughout the operational flight envelope to enable continuous flight dynamics simulations from hover through forward flight. The model adequacy is assessed using validation data acquired separately from data used to identify the model and indicates that the models have sufficient predictive capability. Research findings are presented with a discussion of unique lift+cruise aircraft aerodynamic characteristics and practical strategies to inform future aero-propulsive modeling and simulation efforts for eVTOL aircraft.

lift+cruise↗
NASA NTRS1982

Control technology development

The main objectives of the control technology development task are given in the slide below. The first is to develop control design techniques based on flexible structural models, rather than simple rigid-body models. Since large space structures are distributed parameter systems, a new degree of freedom, that of sensor/actuator placement, may be exercised for improving control system performance. Another characteristic of large space structures is numerous oscillatory modes within the control bandwidth. Reduced-order controller design models must be developed which produce stable closed-loop systems when combined with the full-order system. Since the date of an actual large-space-structure flight is rapidly approaching, it is vitally important that theoretical developments are tested in actual hardware. Experimental verification is a vital counterpart of all current theoretical developments.

Schaechter, D. B.↗
NASA NTRS1991

System monitoring and diagnosis with qualitative models

A substantial foundation of tools for model-based reasoning with incomplete knowledge was developed: QSIM (a qualitative simulation program) and its extensions for qualitative simulation; Q2, Q3 and their successors for quantitative reasoning on a qualitative framework; and the CC (component-connection) and QPC (Qualitative Process Theory) model compilers for building QSIM QDE (qualitative differential equation) models starting from different ontological assumptions. Other model-compilers for QDE's, e.g., using bond graphs or compartmental models, have been developed elsewhere. These model-building tools will support automatic construction of qualitative models from physical specifications, and further research into selection of appropriate modeling viewpoints. For monitoring and diagnosis, plausible hypotheses are unified against observations to strengthen or refute the predicted behaviors. In MIMIC (Model Integration via Mesh Interpolation Coefficients), multiple hypothesized models of the system are tracked in parallel in order to reduce the 'missing model' problem. Each model begins as a qualitative model, and is unified with a priori quantitative knowledge and with the stream of incoming observational data. When the model/data unification yields a contradiction, the model is refuted. When there is no contradiction, the predictions of the model are progressively strengthened, for use in procedure planning and differential diagnosis. Only under a qualitative level of description can a finite set of models guarantee the complete coverage necessary for this performance. The results of this research are presented in several publications. Abstracts of these published papers are presented along with abtracts of papers representing work that was synergistic with the NASA grant but funded otherwise. These 28 papers include but are not limited to: 'Combined qualitative and numerical simulation with Q3'; 'Comparative analysis and qualitative integral representations'; 'Model-based monitoring of dynamic systems'; 'Numerical behavior envelopes for qualitative models'; 'Higher-order derivative constraints in qualitative simulation'; and 'Non-intersection of trajectories in qualitative phase space: a global constraint for qualitative simulation.'

Kuipers, Benjamin↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗
DOE OSTI2021

Signatures of Coherent Phonon Transport in Ultralow Thermal Conductivity Two-Dimensional Ruddlesden–Popper Phase Perovskites

An emerging class of methylammonium lead iodide (MAPbI 3 )-based Ruddlesden-Popper (RP) phase perovskites, BA 2 MA n-1 Pb n I 3n+1 (n = 1-7), exhibit enhanced stability to environmental conditions relative to MAPbI 3 , yet still degrade at elevated temperatures. Here, we experimentally determine the thermal conductivities of these layered RP phases for n = 1-6, where n defines the number of repeated perovskite octahedra per layer. We measure thermal conductivities of 0.37 ± 0.13/0.12, 0.17 ± 0.08/0.07, 0.21 ± 0.05/0.04, and 0.19 ± 0.04/0.03 W/m∙K in thin films of n = 1-4 and 0.08 ± 0.06/0.04, 0.06 ± 0.04/0.03, 0.06 ± 0.03/0.03, and 0.08 ± 0.07/0.04 W/m∙K in single crystals of n = 3-6. With the exception of n = 1, these thermal conductivities are lower than the range of 0.34-0.50 W/m∙K reported for single-crystal MAPbI 3 . Reduced-order lattice dynamics modeling suggests that the initially decreasing trend of thermal conductivity in similarly oriented perovskites with increasing n may result from the transport properties of coherent phonons, emergent from the superstructure, that do not scatter at the interfaces of organic butylammonium chains and perovskite octahedra. Reduced group velocity of coherent phonons in n = 3-6, a consequence of band flattening in the phonon dispersion, is primarily responsible for their ultralow thermal conductivities. Similar effects on thermal conductivity have been experimentally demonstrated in deposited superlattices, but never in naturally defined materials such as RP phases. GIWAXS measurements reveal that higher n RP phase thin films are less orientationally controlled and therefore possess apparently elevated thermal conductivities relative to single crystals of the same n.

2D perovskites↗
NASA NTRSDate not supplied

A Solar Sail Shape Modeling Approach for Attitude Control Design and Analysis

Solar sails operating in the space environment experience deformations in sail shape that result in relatively large disturbance torques which dictate the required performance of the spacecraft attitude control and momentum management systems. These deformations are driven by thermal loads on the booms (due to uneven solar heating), manufacturing and assembly tolerances, and variations in membrane tension. The Solar Cruiser spacecraft utilizes a four-quadrant sail design with four 30-meter length booms and four triangular sail membranes, creating a square sail structure of >1600 m2. Medium-fidelity mesh models were developed based on a characteristic deformed shape. A series of parametric studies were conducted using this shape paradigm to determine worst-case deformed sail shapes which produce bounding disturbance torques. A large database of shapes was produced, and the forces and moments induced by each individual shape were calculated using a Rios-Reyes reduced order generalized sail model. Two were selected as reference worst-case shapes for the Solar Cruiser mission: one which produced the highest pitch/yaw root-sum-squared (RSS) torque, and one which produced the highest roll torque. The results showed that the worst-case shapes at high solar incidence angles induce significantly higher (2-10x) disturbance torques than an ideal, flat-plate sail. Even with considerable safety margins, assuming an ideal sail is unlikely to sufficiently bound the disturbances, which is critical when designing the attitude control system and sizing actuators. Accurate sail shape modeling methodologies should therefore be employed on future solar sail missions.

Solar Sail↗
NASA NTRSDate not supplied

A Solar Sail Shape Modeling Approach for Attitude Control Design and Analysis

Solar sails operating in the space environment experience deformations in sail shape that result in relatively large disturbance torques which dictate the required performance of the spacecraft attitude control and momentum management systems. These deformations are driven by thermal loads on the booms (due to uneven solar heating), manufacturing and assembly tolerances, and variations in membrane tension. The Solar Cruiser spacecraft utilizes a four-quadrant sail design with four 30-meter length booms and four triangular sail membranes, creating a square sail structure of >1600 m2. Medium-fidelity mesh models were developed based on a characteristic deformed shape. A series of parametric studies were conducted using this shape paradigm to determine worst-case deformed sail shapes which produce bounding disturbance torques. A large database of shapes was produced, and the forces and moments induced by each individual shape were calculated using a Rios-Reyes reduced order generalized sail model [1]. Two were selected as reference worst-case shapes for the Solar Cruiser mission: one which produced the highest pitch/yaw root-sum-squared (RSS) torque, and one which produced the highest roll torque. The results showed that the worst-case shapes at high solar incidence angles induce significantly higher (2-10x) disturbance torques than an ideal, flat-plate sail. Even with considerable safety margins, assuming an ideal sail is unlikely to sufficiently bound the disturbances, which is critical when designing the attitude control system and sizing actuators. Accurate sail shape modeling methodologies should therefore be employed on future solar sail missions. References [1] L. Rios-Reyes and D. J. Scheeres, “Generalized Model for Solar Sails,” Journal of Spacecraft and Rockets, Vol. 42, Jan. 2005, pp. 182–185, 10.2514/1.9054.

Solar Sail↗
DOE OSTI2023

Multiscale Reactive Model for 1,3,5-Triamino-2,4,6-trinitrobenzene Inferred by Reactive MD Simulations and Unsupervised Learning

When high-energy-density materials are subjected to thermal or mechanical insults at extreme conditions (shock loading), a coupled response between the thermo-mechanical and chemical behaviors is systematically induced. Herein we develop a reaction model for the fast chemistry of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) at the mesoscopic scale, where the chemical behavior is determined by underlying microscopic reactive simulations. The slow carbon cluster formation is not discussed in the present work. All-atom reactive molecular dynamics (MD) simulations are performed with the ReaxFF potential, and a reduced-order chemical kinetics model for TATB is fitted to isothermal and adiabatic simulations of single crystal chemical decomposition. Unsupervised machine learning techniques based on non-negative matrix factorization are applied to MD trajectories to model the decomposition kinetics of TATB in terms of a four-component model. The associated heats of reaction are fit to the temperature evolution from adiabatic decomposition trajectories. Using a chemical species analysis, we show that non-negative matrix factorization captures the main chemical decomposition steps of TATB and provides an accurate estimation of their evolution with temperature. The final analytical formulation, coupled to a diffusion term, is incorporated into a continuum formalism, and simulation results are compared one-to-one against MD simulations of 1D reaction propagation along different crystallographic directions and with different initial temperatures. A good agreement is found for both the temporal and spatial evolution of the temperature field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Modelling the Fluctuations of Reactive Shock Waves in Heterogeneous Solid Explosives as Stochastic Processes

Although current phenomenological burn models are useful for describing the average or bulk reactive flow behaviour of heterogeneous explosives, one fundamental weakness inherent to these models is the loss of detailed microstructural information at the scale of the calculation. In order to include the effects of the microstructure, and in particular the underlying material heterogeneities that influence the build-up to detonation, a new paradigm is put forth for modelling sub-grid, reaction-induced fluctuations (i.e. “hot spots”) at the continuum level. This modelling approach assumes that the reaction rate is stochastic, rather than deterministic, and it uses Langevin-type equations with a mathematical framework built upon Itô calculus and Lambourn's CIM model for shocked heterogeneous explosives. This approach follows directly from our previous letter, Ref. [1], and is inspired by the probability density function (pdf) methods used in turbulent reactive flows. Here, the stochastic burn model is derived, implemented, and exercised far beyond what has been shown in previous work. New hydrocode simulation results demonstrate the role of stochastic fluctuations during shock initiation; these fluctuations are approximated by collections of discrete particles, that evolve with drift (i.e. deterministic) and diffusion (i.e. stochastic) coefficients. Furthermore, the particle values are propagated and averaged to calculate the heat release, yield strength, and material impedance in each computational cell. Hydrocode simulation results further show how the fluctuating hot spot energy may or may not be transmitted to the wave front, and result in a detonation wave-like structure. The fundamental stochastic nature of this model permits simulations to have varying outcomes with the same initial conditions; this allows for go/no-go estimation (e.g., marginal or failed detonations), which might possibly be calibrated using the statistical distributions from real materials. Mesoscale calculations of shocked heterogeneous explosives also show that these fluctuations are physically justified (i.e., Ref. [2]), and it is hypothesized that the pdf functions provide a link between the meso(grain) and continuum scales for practical engineering calculations. Hence, our approach is a paradigm shift for building efficient, reduced order continuum burn models, that represent the sub-grid stochastic behaviour of shocked heterogeneous solid explosives.

42 ENGINEERING↗
DOE OSTI2025

Serpent - Bison - THM Preliminary Multiphysics Modeling of a Nuclear Thermal Propulsion System Fuel Assembly

This work demonstrates the Monte Carlo neutronic and Thermo-Hydraulic coupling scheme using the Serpent code and MOOSE application Bison and Thermo Hydraulic Module. The coupling scheme is then applied to the reference BWX Technologies Nuclear Ther- mal Propulsion system at he fuel assembly level where it’s used to perform an analysis of the isothermal material coefficients and potential material reactivity worth. A method is developed to isolate which feedback effects should be considered for proceeding with reduced order deterministic neutronic modeling where branch off analysis must be con- ducted. The convergence behavior of the coupling scheme is demonstrated where it fol- lows the standard Picard iteration approach. Verification studies for the method of deduc- ing relevant feedback effects is also demonstrated.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Three-dimensional flow model development for thermal mixing and stratification modeling in reactor system transients analyses

Mixing, thermal-stratification, and mass transport phenomena in large pools or enclosures play major roles for the safety of reactor systems. Depending on the fidelity requirement and computational resources, various modeling methods, from the 0-D perfect mixing model to 3-D Computational Fluid Dynamics (CFD) models, are available. Each is associated with its own advantages and shortcomings. It is very desirable to develop an advanced and efficient thermal mixing and stratification modeling capability embedded in a modern system analysis code to improve the accuracy of reactor safety analyses and to reduce modeling uncertainties. An advanced system analysis tool, SAM, is being developed at Argonne National Laboratory for advanced non-LWR reactor safety analysis. While SAM is being developed as a system-level modeling and simulation tool, a reduced-order three-dimensional module is under development to model the mull-dimensional flow and thermal mixing and stratification in large enclosures of reactor systems. This paper provides an overview of the three-dimensional finite element flow model in SAM, including the governing equations, stabilization scheme, and solution methods. Additionally, several verification and validation tests are presented, including lid-driven cavity flow, natural convection inside a cavity, laminar flow in a channel of parallel plates. Here, based on the comparisons with the analytical solutions and experimental results, it is demonstrated that the developed 3-D fluid model can perform very well for a wide range of flow problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Confirmation of a realistic reactor model for BNCT dosimetry at the TRIGA Mainz

Purpose: In order to build up a reliable dose monitoring system for boron neutron capture therapy (BNCT) applications at the TRIGA reactor in Mainz, a computer model for the entire reactor was established, simulating the radiation field by means of the Monte Carlo method. The impact of different source definition techniques was compared and the model was validated by experimental fluence and dose determinations. Methods: The depletion calculation code ORIGEN2 was used to compute the burn-up and relevant material composition of each burned fuel element from the day of first reactor operation to its current core. The material composition of the current core was used in a MCNP5 model of the initial core developed earlier. To perform calculations for the region outside the reactor core, the model was expanded to include the thermal column and compared with the previously established ATTILA model. Subsequently, the computational model is simplified in order to reduce the calculation time. Both simulation models are validated by experiments with different setups using alanine dosimetry and gold activation measurements with two different types of phantoms. Results: The MCNP5 simulated neutron spectrum and source strength are found to be in good agreement with the previous ATTILA model whereas the photon production is much lower. Both MCNP5 simulation models predict all experimental dose values with an accuracy of about 5%. The simulations reveal that a Teflon environment favorably reduces the gamma dose component as compared to a polymethyl methacrylate phantom. Conclusions: A computer model for BNCT dosimetry was established, allowing the prediction of dosimetric quantities without further calibration and within a reasonable computation time for clinical applications. The good agreement between the MCNP5 simulations and experiments demonstrates that the ATTILA model overestimates the gamma dose contribution. The detailed model can be used for the planning of structural modifications in the thermal column irradiation channel or the use of different irradiation sites than the thermal column, e.g., the beam tubes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1993

Single-input/single-output transfer functions for a flexible slewing link

Truncated linear models based on constrained and unconstrained mode expansions for a flexible link with torque actuation at its hub led us to examine the behavior of the open-loop-zeros of five commonly used SISO transfer functions. We arrive at new conclusions with regard to minimum- and non-minimum-phase zeros, and passivity of the transfer functions. The flexible-to-rigid inertia (FRI) ratio plays an important role in the determination of these characteristics. This paper illustrates how the zero locations of some of the transfer functions are dramatically affected by the FRI ratio. We also investigate the performance of a hub angle, hub rate, and relative tip position static feedback controller based on a reduced-order constrained mode model when applied to both unconstrained and constrained mode models of the same dimension. Simulations indicate that the constrained model can be stable while the unconstrained model is not for high FRI ratios. Our findings can provide useful information to designers in cases where the controller is sensitive to the 1ocation of the plant's zeros.

Barbieri, Enrique↗
DOE OSTI2025

Low‐dimensional manifold learning for uncertainty quantification in complex multi‐scale stochastic systems

Broadly speaking, the goals of the project are to develop techniques to use manifold learning to develop reduced‐order and surrogate models for "hyper‐reduction" of very high‐dimensional complex multi‐scale systems. This is being achieved by employing a newly proposed form of manifold projection and learning that leverages recent advancements in computational geometry and data‐driven modeling. In particular, we are applying a manifold projection technique to project the solutions of very high‐dimensional systems onto the so‐called Grassmannmanifold, a Reimannian manifold comprised of orthonormal matrices. We then apply data‐driven machine learning techniques to classify the solutions on the manifold (e.g. clustering techniques) according to their proximity on the manifold and leverage a further nonlinear dimension reduction to organize the structured data on the manifold. Finally, we are developing novel techniques that enable us to directly interpolate the hyper‐reduced data such that we can predict the solution of the complex, high‐ dimensional system without need to call the full expensive computational model. Given their adherence to the underlying structure of the solution of the physical system, it is expected that these approximate solutions will be sufficiently constrained so as to (approximately) adhere to physical principles.

97 MATHEMATICS AND COMPUTING↗