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NASA NTRS2013

Recent Development in the CESE Method for the Solution of the Navier-Stokes Equations Using Unstructured Triangular or Tetrahedral Meshes With High Aspect Ratio

In the multidimensional CESE development, triangles and tetrahedra turn out to be the most natural building blocks for 2D and 3D spatial meshes. As such the CESE method is compatible with the simplest unstructured meshes and thus can be easily applied to solve problems with complex geometries. However, because the method uses space-time staggered stencils, solution decoupling may become a real nuisance in applications involving unstructured meshes. In this paper we will describe a simple and general remedy which, according to numerical experiments, has removed any possibility of solution decoupling. Moreover, in a real-world viscous flow simulation near a solid wall, one often encounters a case where a boundary with high curvature or sharp corner is surrounded by triangular/tetrahedral meshes of extremely high aspect ratio (up to 106). For such an extreme case, the spatial projection of a space-time compounded conservation element constructed using the original CESE design may become highly concave and thus its centroid (referred to as a spatial solution point) may lie far outside of the spatial projection. It could even be embedded beyond a solid wall boundary and causes serious numerical difficulties. In this paper we will also present a new procedure for constructing conservation elements and solution elements which effectively overcomes the difficulties associated with the original design. Another difficulty issue which was addressed more recently is the wellknown fact that accuracy of gradient computations involving triangular/tetrahedral grids deteriorates rapidly as the aspect ratio of grid cells increases. The root cause of this difficulty was clearly identified and several remedies to overcome it were found through a rigorous mathematical analysis. However, because of the length of the current paper and the complexity of mathematics involved, this new work will be presented in another paper.

Chang, Sin-Chung↗

NASA NTRS1985

Three dimensional flow phenomena in fluid machinery; Proceedings of the Winter Annual Meeting, Miami Beach, FL, November 17-22, 1985

For papers presented in this volume provide an overview of the latest developments in experimental measurements and analytical and numerical predictions of three-dimensional flows in fluid machinery. Topics discussed include three-dimensional cascade testing of turbine nozzles at high exit Mach number; the use of a secondary flow computation in the compressor design process; an experimental investigation of static propeller flow field; and calculation of three-dimensional boundary layers on rotating turbine blades. Papers are also presented on a three-dimensional solution method for turbomachinery analysis; analysis of rotational inviscid flows in curved passages; and a mathematical model for the analysis of fluid flow in a scroll.

Hamed, A.↗

DOE OSTI2024

TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD) Report, Release FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to the development, on-target assessment, and qualification of current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development. Under the TRUST work package, there are five testbeds and their associated engineering analysis baseline models (EABMs): 1. Contact Thermal Conductivity (CTC), 2. Nonlinear Dynamics (ND), 3. Sensors in Environments: Accelerometers (SE-A), 4. Sensors in Environments: Fiber Optic Displacement Gauges (SE-FOD), and 5. Sensors in Environments: Thermocouples (SE-TC). The TRUST project uses single-feature testbeds to quantify uncertainties in specific models and experiments and to identify capability development needs that can help to reduce these uncertainties. Each testbed is designed, configured, and tested in collaboration with groups with design and experimental capability: E-14 and MPA-CINT. The complementary simulations are conducted using W-13 analysis tools and stored in model repositories with plans for incremental progress toward EABM requirements. W-13 extends and exercises the testbed simulations in collaboration with experimentalists for uncertainty quantification of current and future materials, geometries, and environments. Additionally, TRUST is intended to provide engineers in W-13 and E-14 with experience in both numerical simulations and experimental methods through cross-discipline collaborations. Following the introduction to the TRUST project, the remainder of this report focuses on experimental, modeling and simulation, and analysis efforts conducted in FY24 relevant to the TRUST Sensors in Environments: Fiber Optic Displacement (SE-FOD) testbed.

42 ENGINEERING↗

NASA NTRS2007

NASA Tech Briefs, November 2007

Topics include: Wireless Measurement of Contact and Motion Between Contact Surfaces; Wireless Measurement of Rotation and Displacement Rate; Portable Microleak-Detection System; Free-to-Roll Testing of Airplane Models in Wind Tunnels; Cryogenic Shrouds for Testing Thermal-Insulation Panels; Optoelectronic System Measures Distances to Multiple Targets; Tachometers Derived From a Brushless DC Motor; Algorithm-Based Fault Tolerance for Numerical Subroutines; Computational Support for Technology- Investment Decisions; DSN Resource Scheduling; Distributed Operations Planning; Phase-Oriented Gear Systems; Freeze Tape Casting of Functionally Graded Porous Ceramics; Electrophoretic Deposition on Porous Non- Conductors; Two Devices for Removing Sludge From Bioreactor Wastewater; Portable Unit for Metabolic Analysis; Flash Diffusivity Technique Applied to Individual Fibers; System for Thermal Imaging of Hot Moving Objects; Large Solar-Rejection Filter; Improved Readout Scheme for SQUID-Based Thermometry; Error Rates and Channel Capacities in Multipulse PPM; Two Mathematical Models of Nonlinear Vibrations; Simpler Adaptive Selection of Golomb Power-of- Two Codes; VCO PLL Frequency Synthesizers for Spacecraft Transponders; Wide Tuning Capability for Spacecraft Transponders; Adaptive Deadband Synchronization for a Spacecraft Formation; Analysis of Performance of Stereoscopic-Vision Software; Estimating the Inertia Matrix of a Spacecraft; Spatial Coverage Planning for Exploration Robots; and Increasing the Life of a Xenon-Ion Spacecraft Thruster.

Source record↗

DOE OSTI2025

Neural Active Manifolds: Nonlinear Dimensionality Reduction for Uncertainty Quantification

We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a one-dimensional neural active manifold (NeurAM) capturing the model output variability, through the aid of a simultaneously learnt surrogate model with inputs on this manifold. Our method only relies on model evaluations and does not require the knowledge of gradients. The proposed dimensionality reduction framework can then be applied to assist outer loop many-query tasks in scientific computing, like sensitivity analysis and multifidelity uncertainty propagation. In particular, we prove, both theoretically under idealized conditions, and numerically in challenging test cases, how NeurAM can be used to obtain multifidelity sampling estimators with reduced variance by sampling the models on the discovered low-dimensional and shared manifold among models. Several numerical examples illustrate the main features of the proposed dimensionality reduction strategy and highlight its advantages with respect to existing approaches in the literature.

Autoencoders↗

DOE OSTI2025

Essential barrier height and a probabilistic approach in characterizing potential landscape

In this work we propose a probabilistic approach to investigate the shape of landscapes of multi-dimensional potential functions. Under a suitable coupling scheme, two copies of the overdamped Langevin dynamics associated with the potential function are coupled, and the coupling times are collected. Assuming a set of intuitive yet technically challenging conditions on the coupling scheme, it is shown that the tail distributions of the coupling times exhibit qualitatively different dependencies on the noise magnitude for single-well versus multi-well potential functions. More specifically, for convex single-well potentials, the negative tail exponent of the coupling time distribution is uniformly bounded away from zero by the convexity parameter and is independent of the noise magnitude. In contrast, for multi-well potentials, the negative tail exponent decreases exponentially as the noise vanishes, with the decay rate governed by the essential barrier height, a quantity introduced in this paper to characterize the non-convex nature of the potential function. Numerical investigations are conducted for a variety of examples, including the Rosenbrock function, interacting particle systems, and loss functions arising in artificial neural networks. These examples not only illustrate the theoretical results in various contexts but also provide crucial numerical validation of the conjectured assumptions, which are essential to the theoretical analysis yet lie beyond the reach of standard technical tools.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Quantum Circuit Cutting for Classical Shadows

Classical shadow tomography is a sample-efficient technique for characterizing quantum systems and predicting many of their properties. Circuit cutting is a technique for dividing large quantum circuits into smaller fragments that can be executed more robustly using fewer quantum resources. We introduce a divide-and-conquer circuit cutting method for estimating the expectation values of observables using classical shadows. We derive a general formula for making predictions using the classical shadows of circuit fragments from arbitrarily cut circuits and provide the sample complexity analysis for the case when observables factorize across fragments. Then, we numerically show that our divide-and-conquer method outperforms traditional uncut shadow tomography when estimating high-weight observables that act non-trivially on many qubits and discuss the mechanisms for this advantage.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Sierra/SD – Verification Test Manual – 5.22

Verification and validation (V&V) of scientific computing programs are important at Sandia National Labs due to the expanding role of computational simulation in managing the United States nuclear stockpile. The complexities of structural response calculations used to analyze physical problems, the varieties of codes applied to the calculations, and the importance of accurate predictions when assessing field conditions demand confidence in the consistency and accuracy of computer codes. Confidence in the accuracy of the predictions arising from computer simulations must ultimately be gained through verification and validation. The Sierra salinas structural dynamics analysis code, Sierra/SD, is used at the DOE Laboratories, and in several DOD projects. The roles of Sierra/SD in the qualification of weapon systems and components for normal and hostile environments throughout the Stockpile-to-Target Sequence include to, • Redesign weapon components. • Certify weapon components and systems for target environments such as hypersonic vehicles. • Certify that components will survive the thermal mechanical shock loads associated with hostile environments. • Evaluate current stockpile issues, including issues associated with uncertainty quantification. • Address many other problems that are encountered in stockpile management. The Sierra/SD verification plan is described, and an evolving set of key verification tests are described in detail. The verification tests ensure the correctness of the mathematics and numerical algorithms associated with functionality describing engineering phenomena. Development is in accordance with a set of tailored Software Quality Engineering (SQE) practices. SQE practices guide the overall verification and validation effort.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Efficient Streaming Dynamic Mode Decomposition

We propose a reformulation of the streaming dynamic mode decomposition method that requires maintaining a single orthonormal basis, thereby reducing computational redundancy. The proposed efficient streaming dynamic mode decomposition method results in a constant-factor reduction in computational complexity and memory storage requirements. Numerical experiments on representative canonical dynamical systems show that the enhanced computational efficiency does not compromise the accuracy of the proposed method.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

Numerical image manipulation and display in solar astronomy

The paper describes the system configuration and data manipulation capabilities of a solar image display system which allows interactive analysis of visual images and on-line manipulation of digital data. Image processing features include smoothing or filtering of images stored in the display, contrast enhancement, and blinking or flickering images. A computer with a core memory of 28,672 words provides the capacity to perform complex calculations based on stored images, including computing histograms, selecting subsets of images for further analysis, combining portions of images to produce images with physical meaning, and constructing mathematical models of features in an image. Some of the processing modes are illustrated by some image sequences from solar observations.

Levine, R. H.↗

DOE OSTI2026

Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics

We present Diagrammatica, a symbolic computation extension to the HEPTAPOD agentic framework, which enables LLM agents to plan and execute multi-step theoretical calculations. Symbolic computation poses a distinctive reliability challenge for LLM agents, as correctness is governed by implicit mathematical conventions that are not encoded in a form that can be easily checked in the computational backend. We identify two complementary remedies, tool-constrained computation and targeted knowledge grounding, and pursue the first as the primary architecture. Concretely, we concentrate the agent's action distribution onto tool calls with convention-fixing semantics, in which the agent specifies a compact, human-auditable diagram specification and a trusted backend performs the symbolic or numerical manipulations exactly. The toolkit provides two complementary calculation paths consuming a shared diagram specification: Naive Dimensional Analysis (NDA) for order-of-magnitude rate estimates and Exact Diagrammatic Analysis (EDA) for tree-level symbolic calculations via automatic FeynCalc code generation, both supplemented by automatic Feynman diagram enumeration and a navigable theory knowledge base. The architecture is validated on two benchmarks: (1) an exhaustive catalog of all tree-level, single-vertex $1\to 2$ partial decay widths across scalar, fermion, and vector parents, with complete massless and threshold limits and Standard Model validation; and (2) an NDA sensitivity study of the muon decay multiplicity $μ^+ \to ν_μ\barν_e + n(e^+e^-) + e^-$, determining the maximum observable $n$ at current and planned muon experiments.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

NASA NTRS1994

Active magnetic bearing control loop modeling for a finite element rotordynamics code

A mathematical model of an active electromagnetic bearing which includes the actuator, the sensor and the control system is developed and implemented in a specialized finite element code for rotordynamic analysis. The element formulation and its incorporation in the model of the machine are described in detail. A solution procedure, based on a modal approach in which the number of retained modes is controlled by the user, is then shown together with other procedures for computing the steady-state response to both static and unbalance forces. An example of application shows the numerical results obtained on a model of an electric motor suspended on a five active-axis magnetic suspension. The comparison of some of these results with the experimental characteristics of the actual system shows the ability of the present model to predict its performance.

Genta, Giancarlo↗

NASA NTRS1975

A nonlinear model for gas chromatograph systems

Fundamental engineering design techniques and concepts were studied for the optimization of a gas chromatograph-mass spectrometer chemical analysis system suitable for use on an unmanned, Martian roving vehicle. Previously developed mathematical models of the gas chromatograph are found to be inadequate for predicting peak heights and spreading for some experimental conditions and chemical systems. A modification to the existing equilibrium adsorption model is required; the Langmuir isotherm replaces the linear isotherm. The numerical technique of Crank-Nicolson was studied for use with the linear isotherm to determine the utility of the method. Modifications are made to the method eliminate unnecessary calculations which result in an overall reduction of the computation time of about 42 percent. The Langmuir isotherm is considered which takes into account the composition-dependent effects on the thermodynamic parameter, mRo.

Feinberg, M. P.↗

NASA NTRS2026

Mathematical Model of a Regenerative Fuel Cell for System Optimization

This thesis developed a system-level optimization model of a regenerative fuel cell (RFC) system for long-duration, off-world energy storage applications. Prior RFC design studies have typically been limited to reduced parameter sets and simplified constraints due to computational limitations relative to the number of relevant degrees of freedom. As a result, important nonlinear interactions between subsystems have not been fully captured. This work began to address that gap by developing a higher-fidelity, nonlinear optimization framework that incorporates a broader set of design variables and coupled constraints, enabling a multidimensional model that captures the coupled behavior of RFC subsystems and demonstrates the feasibility of applying optimization to such systems. An expanded system-level optimization approach was established that captures interactions between electrochemical performance, structural requirements, and storage design. This enabled a more comprehensive evaluation of trade-offs than conventional formulations. The model integrates four coupled subsystems: a fuel cell, an electrolyzer, reactant gas, and high-pressure storage tanks, and was formulated to accommodate a wide range of mission parameters, including operational time and required output power. It incorporates constraints on available solar array power, reactant mass balance between production and consumption, and pressure-dependent storage requirements. To enable reliable convergence, the optimization problem was reformulated to reduce dimensionality and improve numerical stability, with subsystem models organized for efficient evaluation. Problem dimensionality was reduced by consolidating lower-level design variables into higher-level representative quantities, and subsystem behavior was evaluated within the optimization loop. A multi-start initialization strategy was employed to mitigate sensitivity to local minima and improve solution quality, while nonlinear relationships were solved using robust numerical methods. The results showed that convergence was achieved across a range of required output power values. Specific energy reached a maximum at a critical mission power level, where the electrolyzer power matched the available solar input and operated near its voltage and current density limits. Beyond this point, further increases in required power resulted in less mass-efficient operation, increasing total system mass and reducing overall performance. The developed model represents an advancement in RFC system-level optimization by enabling analysis of a broader and more tightly coupled design space than previous considerations. While convergence behavior and computational cost remain challenges, the methods introduced improve solvability and allow inclusion of additional design variables with minimal loss of physical fidelity. However, the numerical results should not be interpreted as definitive design recommendations, as the model includes simplifying assumptions and omits several higher-order effects. Future work should extend this framework by incorporating additional subsystems and loss mechanisms, such as thermal management, parasitic power consumption, and reactant losses, to improve fidelity and ensure more representative design conclusions.

Electrochemistry↗

DOE OSTI2025

CFD modeling of turbulent air flow in self-heated gyroid TPMS structures: Thermal-hydraulic performance and validation

The application of mathematically derived geometries, such as triply periodic minimal surface (TPMS) lattices, has garnered significant interest across various fields, including the nuclear sector, due to their superior thermal-hydraulic characteristics for heat transfer compared to traditional plain or finned tubes. Here, this study validates a computational fluid dynamics (CFD) model, evaluates different turbulence models and CFD model settings, and performs uncertainty quantification to provide a comprehensive analysis. Despite extensive research on CFD modeling of TPMS lattices, such as gyroid and diamond geometries, there is a notable lack of publicly available literature providing comprehensive details on numerical analysis aspects, including convergence and methodological best practices. This study embarks on a benchmark analysis of a gyroid geometry to evaluate its thermal-hydraulic performance under turbulent flow conditions and scrutinize various CFD model configurations. The main contributions of this work include validating the CFD model, assessing and comparing different turbulence models, and enhancing pressure drop and temperature prediction capabilities. The results aim to support the development of methodologies needed to benchmark and enhance numerical analysis techniques for TPMS lattices. This work seeks to complement the existing body of knowledge, support the development of TPMS reactor concepts, and improve best practices for CFD modeling of TPMS lattices, ultimately advancing methodologies to support future applications in this domain.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1990

Introduction to the internal fluid mechanics research session

Internal fluid mechanics research at LeRC is directed toward an improved understanding of the important flow physics affecting aerospace propulsion systems, and applying this improved understanding to formulate accurate predictive codes. To this end, research is conducted involving detailed experimentation and analysis. The following three papers summarize ongoing work and indicate future emphasis in three major research thrusts: inlets, ducts, and nozzles; turbomachinery; and chemical reacting flows. The underlying goal of the research in each of these areas is to bring internal computational fluid mechanic to a state of practical application for aerospace propulsion systems. Achievement of this goal requires that carefully planned and executed experiments be conducted in order to develop and validate useful codes. It is critical that numerical code development work and experimental work be closely coupled. The insights gained are represented by mathematical models that form the basis for code development. The resultant codes are then tested by comparing them with appropriate experiments in order to ensure their validity and determine their applicable range. The ultimate user community must be a part of this process to assure relevancy of the work and to hasten its practical application. Propulsion systems are characterized by highly complex and dynamic internal flows. Many complex, 3-D flow phenomena may be present, including unsteadiness, shocks, and chemical reactions. By focusing on specific portions of a propulsion system, it is often possible to identify the dominant phenomena that must be understood and modeled for obtaining accurate predictive capability. The three major research thrusts serve as a focus leading to greater understanding of the relevant physics and to an improvement in analytic tools. This in turn will hasten continued advancements in propulsion system performance and capability.

Miller, Brent A.↗

NASA NTRS1983

User's manual for a TEACH computer program for the analysis of turbulent, swirling reacting flow in a research combustor

Described is a computer program for the analysis of the subsonic, swirling, reacting turbulent flow in an axisymmetric, bluff-body research combustor. The program features an improved finite-difference procedure designed to reduce the effects of numerical diffusion and a new algorithm for predicting the pressure distribution within the combustor. A research version of the computer program described in the report was supplied to United Technologies Research Center by Professor A. D. Gosman and his students, R. Benodeker and R. I. Issa, of Imperial College, London. The Imperial College staff also supplied much of the program documentation. Presented are a description of the mathematical model for flow within an axisymmetric bluff-body combustor, the development of the finite-difference procedure used to represent the system of equations, an outline of the algorithm for determining the static pressure distribution within the combustor, a description of the computer program including its input format, and the results for representative test cases.

Chiappetta, L. M.↗

DOE OSTI2024

Infinite quantum signal processing

Quantum signal processing (QSP) represents a real scalar polynomial of degree d using a product of unitary matrices of size 2 × 2 , parameterized by ( d + 1 ) real numbers called the phase factors. This innovative representation of polynomials has a wide range of applications in quantum computation. When the polynomial of interest is obtained by truncating an infinite polynomial series, a natural question is whether the phase factors have a well defined limit as the degree d → ∞ . While the phase factors are generally not unique, we find that there exists a consistent choice of parameterization so that the limit is well defined in the ℓ 1 space. This generalization of QSP, called the infinite quantum signal processing, can be used to represent a large class of non-polynomial functions. Our analysis reveals a surprising connection between the regularity of the target function and the decay properties of the phase factors. Our analysis also inspires a very simple and efficient algorithm to approximately compute the phase factors in the ℓ 1 space. The algorithm uses only double precision arithmetic operations, and provably converges when the ℓ 1 norm of the Chebyshev coefficients of the target function is upper bounded by a constant that is independent of d . This is also the first numerically stable algorithm for finding phase factors with provable performance guarantees in the limit d → ∞ .

Dong, Yulong [Department of Mathematics, Universit↗