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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
NASA NTRS1985

Optimal output feedback design of systems with ill-conditioned dynamics

Singular perturbation concepts are exploited to develop a procedure for designing a constant gain, output feedback control system. It is assumed that the original system is ill-conditioned in the sense that the plant contains widely separated dynamics, and that an accurate description for the high frequency behavior may not be available. The design procedure attempts to stabilize the system by minimizing a quadratic cost function made up of the control and states associated with a reduced order (low frequency) model for the plant, and a measure of stability for the neglected fast dynamics. The resulting design procedure does not require knowledge of the fast dynamics.

Calise, A. J.↗
NASA NTRS1985

Computer aided modelling/compensator design for a flexible space antenna

Controller design algorithms are developed to produce simultaneously both a model of the plant and a compensator. The size of the model and properties of the compensator are driven by the performance requirements, the disturbance environment, and the location, number and type of sensors and actuators. The procedure is based on linear optimal control theory for distributed systems, and balanced realization theory is used to guide the development of the model and reduce the order of the compensator.

Gibson, J. S.↗
NASA NTRS2015

Noise Characteristics of a Four-Jet Impingement Device Inside a Broadband Engine Noise Simulator

The noise generation mechanisms for four directly impinging supersonic jets are investigated employing implicit large eddy simulations with a higher-order accurate weighted essentially non-oscillatory shock-capturing scheme. Impinging jet devices are often used as an experimental apparatus to emulate a broadband noise source. Although such devices have been used in many experiments, a detailed investigation of the noise generation mechanisms has not been conducted before. Thus, the underlying physical mechanisms that are responsible for the generation of sound waves are not well understood. The flow field is highly complex and contains a wide range of temporal and spatial scales relevant for noise generation. Proper orthogonal decomposition of the flow field is utilized to characterize the unsteady nature of the flow field involving unsteady shock oscillations, large coherent turbulent flow structures, and the sporadic appearance of vortex tubes in the center of the impingement region. The causality method based on Lighthill's acoustic analogy is applied to link fluctuations of flow quantities inside the source region to the acoustic pressure in the far field. It will be demonstrated that the entropy fluctuation term in the Lighthill's stress tensor plays a vital role in the noise generation process. Consequently, the understanding of the noise generation mechanisms is employed to develop a reduced-order linear acoustic model of the four-jet impingement device. Finally, three linear acoustic FJID models are used as broadband noise sources inside an engine nacelle and the acoustic scattering results are validated against far-field acoustic experimental data.

Broadband↗
NASA NTRS1983

A case for nonlinear model simplification in the design of flight control systems

An algorithm is presented for obtaining a reduced order or simplified nonlinear model of a nonlinear plant. The method provides a systematic approach for quickly finding the optimal simplified model of the system. Controllers are then designed around this nonlinear model and are used to control the original plant. An example design, for the F-8 aircraft, illustrates that the simplified model does indeed enable the design of a linear controller whose performance is indistinguishable from higher order optimal controllers for the original nonlinear plant. The net result is a simplified design procedure for effectively controlling complex nonlinear systems.

Desrochers, A. A.↗
DOE OSTI2021

Scalable modular dynamic molten salt reactor system model with decay heat

Nodal dynamic models allow rapid reduced-order simulations of complex systems. This paper presents a publicly available system dynamic model of a molten salt reactor system with a topology of the Molten Salt Reactor Experiment (MSRE), in MATLAB/Simulink, building upon a model previously published and validated with MSRE data. It adds scaling of nominal power, dynamic representation of decay heat generation, a generic decay heat removal system, improved documentation, modularity, and test cases. One hour of system transient runs in less than 10 min on a laptop. This model is intended for first order engineering calculations, developing insights into system transient behavior, equipment sizing, parameter sensitivity studies. The model contains an easy to use toolkit which can be customized and expanded to describe any molten salt reactor system. Finally, scenarios involving off-normal transients are presented. Relation between shutdown reactivity insertions, decay heat removal, core recriticality, and safe shutdown conditions are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions

Many materials of interest to Sandia transition from fluid to solid or have regions of both phases coexisting simultaneously. Currently there are, unfortunately, no material models that can accurately predict this material response. This is relevant to applications that "birth stress" related to geoscience, nuclear safety, manufacturing, energy production and bioscience. Accurately capturing solidification and residual stress enables fully predictive simulations of the evolving front shape or final product. Accurately resolving flow of proppants or blood could reduce environmental impact or lead to better treatments for heart attacks, thrombosis, or aneurism. We will address a science question in this proposal: When does residual stress develop during the critical transition from liquid to solid and how does it affect material deformation? Our hypothesis is that these early phases of stress development are critical to predictive simulation of material performance, net shape, and aging. In this project, we use advanced constitutive models with yield stress to represent both fluid and solid behavior simultaneously. The report provides an abbreviated description of the results from our LDRD "Stress Birth and Death: Disruptive Computational Mechanics and Novel Diagnostics for Fluid-to-Solid Transitions," since we have written four papers that document the work in detail and which we reference. We give highlights of the work and describe the gravitationally driven flow visualization experiment on a model yield stress fluid, Carbopol, at various concentrations and flow rates. We were able to collapse the data on a single master curve by showing it was self-similar. We also describe the Carbopol rheology and the constitutive equations of interest including the Bingham-Carreau-Yasuda model, the Saramito model, and the HB-Saramito model including parameter estimation for the shear and oscillatory rheology. We present several computational models including the 3D moving mesh simulations of both the Saramito models and Bingham-Carreau-Yasuda (BCY) model. We also show results from the BCY model using a 3D level set method and two different ways of handling reduced order Hele-Shaw modeling for generalized Newtonian fluids. We present some first ever two-dimensional results for the modified Jeffries Kamani-Donley-Rogers constitutive equation developed during this project. We include some recent results with a successful Saramito-level set coupling that allows us to tackle problems with complex geometries like mold filling in a thin gap with an obstacle, without the need for remeshing or remapping. We report on some experiments for curing systems where fluorescent particles are used to track material flow. These experiments were carried out in an oven on Sylgard 184 as a model polymerizing system. We conclude the report with a summary of accomplishments and some thoughts on follow-on work.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Reduced order methods for the improvement of control-oriented modelling of nuclear power plants - 185

In the development of the control system of a nuclear power plant, it is of primary importance to rely on simulation tools for its realization, testing and validation. These tools should provide an accurate description of the controlled response of the entire power plant in different scenarios. The classic control-oriented modelling based on 0D/1D approach is well suited for control purposes since it provides fast-running simulations and it is easy to linearize, but it may not be sufficient to deeply investigate the complexity of some systems, in particular when/where spatial phenomena have a remarkable impact on dynamics. Reduced Order Methods (ROMs) can offer the proper trade-off between computational cost and solution accuracy, combining the high-detail modelling (e.g., 3D modelling) usually adopted for design purposes with the requirements demanded for a control-oriented tool, firstly the computational efficiency. In this work, ROMs are used to improve a control-oriented plant simulator of a Lead-cooled Fast Reactor (LFR). In particular, the attention is focused on the reactor core neutronics, and on the thermal-hydraulics of the reactor pool as well. A test case regarding the design of a Kalman Filter is set up showing promising results for the application of ROM in the control context. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Two-tier model reduction of viscoelastically damped finite element models

Transient simulations of linear viscoelastically damped structures necessitate critical computational resources to directly integrate the full-order finite element model with time-stepping algorithms. Traditional modal reduction techniques are not directly applicable to these systems since viscoelastic materials depend on time and frequency. A more appropriate reduction basis is obtained from the nonlinear, complex eigenvalue problem, whose eigenvectors capture the appropriate kinematics and enable frequency-based mode selection; unfortunately, the computational cost is prohibitive for computing these modes from large-scale engineering models. To address this shortcoming, this work proposes a novel two-tier reduction procedure to reduce the upfront cost of solving the complex, nonlinear eigenvalue problem. The first reduction step reduces the full-order model with real mode shapes linearized about various centering frequencies to capture the kinematics over a full range of viscoelastic material behavior (glassy, rubbery, and glass-transition zones). This tier-one reduction preserves time-temperature superposition and allows the equations to depend parametrically on operating temperature. The second-level reduction then solves the complex, nonlinear eigenmode solutions in the tier-one reduced space about a fixed temperature to further reduce the equations-of-motion. The method is demonstrated on a cantilevered sandwich plate to display its accuracy and efficiency in comparison to full-order model predictions.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Reduced size first-order subsonic and supersonic aeroelastic modeling

Various aeroelastic, aeroservoelastic, dynamic-response, and sensitivity analyses are based on a time-domain first-order (state-space) formulation of the equations of motion. The formulation of this paper is based on the minimum-state (MS) aerodynamic approximation method, which yields a low number of aerodynamic augmenting states. Modifications of the MS and the physical weighting procedures make the modeling method even more attractive. The flexibility of constraint selection is increased without increasing the approximation problem size; the accuracy of dynamic residualization of high-frequency modes is improved; and the resulting model is less sensitive to parametric changes in subsequent analyses. Applications to subsonic and supersonic cases demonstrate the generality, flexibility, accuracy, and efficiency of the method.

Karpel, Mordechay↗
NASA NTRS1976

Simulation of a turbofan engine for evaluation of multivariable optimal control concepts

This paper describes the development and use of a real-time simulation of the F100-PW-100 turbofan engine. The simulation is being used in a multi-variable optimal controls research program using linear quadratic regulatory theory. The simulation is used to generate linear engine models at selected operating points and evaluate the control algorithm. The paper discusses a technique to reduce the order of the model and compares selected results between high and low order models.

Seldner, K.↗
NASA NTRS1991

Elevation control system model for the DSS 13 antenna

In order to meet the requirements for precision pointing of 34-m antennas, adequate control design and simulation software have to be developed along with a detailed description of the supporting analytical tools. This article describes a control system model for the elevation drive of the DSS 13 antenna. The model allows one to simulate elevation dynamics, cross-coupled dynamics in azimuth and elevation, and RF pointing error. A modal state-space model of the antenna structure was obtained from its finite-element model with a free rotating tipping structure. Model reduction techniques were applied separately for the antenna model and rate-loop model, thereby reducing the system order to one-third of the original one while preserving its dynamic properties. Extensive simulation results illustrate properties of the model.

Gawronski, W.↗
DOE OSTI2018

Reduced-order microstructure-sensitive protocols to rank-order the transition fatigue resistance of polycrystalline microstructures

We present that the transition fatigue regime between low cycle fatigue (LCF) and high cycle fatigue (HCF) is often addressed in the design and performance evaluation of load-bearing components used in many structural applications. Transition fatigue is characterized by elevated levels of local inelastic deformation in significant regions of the microstructure as compared to HCF. Typically, crystal plasticity finite element method (CPFEM) simulations are performed to model this phenomenon and to rank-order microstructures by their resistance to crack formation and early growth in the regime of transition fatigue. Unfortunately, these approaches require significant computational resources, inhibiting their use to explore novel materials for transition fatigue resistance. Reduced-order, microstructure-sensitive models are needed to accelerate the search for next-generation, fatigue-resistant materials. In a recent study, Paulson et al. (2018) extended the materials knowledge system (MKS) framework for rank-ordering the HCF resistance of polycrystalline microstructures. The efficacy of this approach lies in the reduced-dimensional representation of microstructures through 2-point spatial correlations and principal component analysis (PCA), in addition to the characterization of the HCF response with a small set of performance measures. In this work, these same protocols are critically evaluated for their applicability to rank-order the transition fatigue resistance of the same class of polycrystalline microstructures subjected to increased strain amplitudes. Success in this endeavor requires the formation of homogenization linkages that account for the significantly higher levels of local inelastic deformation and stress redistribution in transition fatigue as compared to HCF. Finally, a set of 12 α-titanium microstructures generated using the open access DREAM.3D software (Groeber and Jackson, 2014) are employed for this evaluation.

2-point correlations↗
DOE OSTI2019

Reduced-order atomistic cascade method for simulating radiation damage in metals

Atomistic modeling of radiation damage through displacement cascades is deceptively non-trivial. Because of the high energy and stochastic nature of atomic collisions, individual primary knock-on atom (PKA) cascade simulations are computationally expensive and ill-suited for length and dose upscaling. Here, we propose a reduced-order atomistic cascade model capable of predicting and replicating radiation events in metals across a wide range of recoil energies. Our methodology approximates cascade and displacement damage production by modeling the cascade as a core-shell atomic structure composed of two damage production estimators, namely an athermal recombination corrected displacements per atom (arc-dpa) in the shell and a replacements per atom (rpa) representing atomic mixing in the core. These estimators are calibrated from explicit PKA simulations and a standard displacement damage model that incorporates cascade defect production efficiency and mixing effects. We highlight the predictability and accuracy of our reduced-order atomistic cascade method for the cases of copper and niobium by comparing its results with those from full PKA simulations in terms of defect production as well as the resulting cascade evolution and structure. We offer examples for simulating high energy cascade fragmentation and large dose ion-bombardment to demonstrate its possible applicability. Finally, we discuss the various practical considerations and challenges associated with this methodology especially when simulating subcascade formation and dose effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1988

Block-Krylov component synthesis method for structural model reduction

A new analytical method is presented for generating component shape vectors, or Ritz vectors, for use in component synthesis. Based on the concept of a block-Krylov subspace, easily derived recurrence relations generate blocks of Ritz vectors for each component. The subspace spanned by the Ritz vectors is called a block-Krylov subspace. The synthesis uses the new Ritz vectors rather than component normal modes to reduce the order of large, finite-element component models. An advantage of the Ritz vectors is that they involve significantly less computation than component normal modes. Both 'free-interface' and 'fixed-interface' component models are derived. They yield block-Krylov formulations paralleling the concepts of free-interface and fixed-interface component modal synthesis. Additionally, block-Krylov reduced-order component models are shown to have special disturbability/observability properties. Consequently, the method is attractive in active structural control applications, such as large space structures. The new fixed-interface methodology is demonstrated by a numerical example. The accuracy is found to be comparable to that of fixed-interface component modal synthesis.

Craig, Roy R., Jr.↗
DOE OSTI2024

Data-driven models of nonautonomous systems

Nonautonomous dynamical systems are characterized by time-dependent inputs, which complicates the discovery of predictive models describing the spatiotemporal evolution of the state variables of quantities of interest from their temporal snapshots. When dynamic mode decomposition (DMD) is used to infer a linear model, this difficulty manifests itself in the need to approximate the time-dependent Koopman operators. Our approach is to approximate the original nonautonomous system with a modified system derived via a local parameterization of the time-dependent inputs. The modified system comprises a sequence of local parametric systems, which are subsequently approximated by a parametric surrogate model using the DRIPS (dimension reduction and interpolation in parameter space) framework. The offline step of DRIPS relies on DMD to build a linear surrogate model, endowed with reduced-order bases for the observables mapped from training data. The online step interpolates on suitable manifolds to construct a sequence of iterative parametric surrogate models; the target/test parameter points on these manifolds are specified by a local parameterization of the test time-dependent inputs. Here, we use numerical experimentation to demonstrate the robustness of our method and compare its performance with that of deep neural networks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

A new approach to the formulation of scalar flux closure

This report shows that if a stochastic differential equation (Langevin equation) for velocity fluctuation vector is known, it is possible to derive the equations for scalar flux transport. Durbin and Speziale (1994) showed that the second moment of this stochastic differential equation gives an equation for the evolution of Reynolds stress tensor. Similarly, the stochastic equation will give an equation for scalar flux. Therefore, a coupling between these two is present. The basis for the present work is that there should be Langevin equations that can produce acceptable models for both the Reynolds stress tensor and the scalar flux vector. Having found this basic Langevin equation, the amount of work needed to model the second order closure problems is reduced; using the well developed models for Reynolds stress equations, it will be possible to derive corresponding models for scalar flux equation.

Shabany, Y.↗