SEARCH · Engineering Papers

Results for “Sensitivity Matrix”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

Estimation of 3D Woven Design Sensitivities Using a Rapid Multiscale Analysis Technique

Highly-refined finite element models of three-dimension (3D) woven composite systems currently require excessive computational demands that limit their use in sensitivity analysis, uncertainty quantification, and optimization. An alternative analysis methodology was developed using the NASA Multiscale Analysis Tool (NASMAT) where multiscale models of a 3D woven composite (including inter-tow matrix voids and constituent failure) can be completed on a single central processing unit(CPU)on the order of ~30 s. To develop inputs and validation data for the NASMAT model, coupon and acid-digesting testing and x-ray computed tomography were performed. The NASMAT inputs were parameterized using a set of 25 input variables and distributions. These inputs were randomly sampled to generate a total of 100,000 NASMAT analyses that could be used to understand the influence of different material and geometric properties on the warp and weft-direction stiffness and strength. These analyses (including pre/post-processing) were performed in less than eight hours on a 120 CPU cluster. The computational efficiency of the NASMAT model enabled a sensitivity analysis to be performed, and dominant input variables were able to be identified. Key results were consistent with theoretical and experimental observations for the specific 3D woven system studied in this work.

NASMAT↗

DOE OSTI2025

A structured framework for predicting sustainable aviation fuel properties using liquid-phase FTIR and machine learning

Sustainable aviation fuels have the potential to improve efficiency, reduce emissions, and enhance energy security. To help identify viable sustainable aviation fuels and accelerate research, machine learning models have been developed to predict relevant physicochemical properties. However, many models have limited applicability, leverage data from complex analytical techniques with confined spectral ranges, or use feature decomposition methods that offer limited interpretability. Using liquid-phase Fourier Transform Infrared (FTIR) spectra, this study presents a structured method for creating accurate and interpretable property prediction models for neat molecules, aviation fuels, and blends. Liquid FTIR spectra can be collected quickly and consistently, offering high reliability, sensitivity, and component specificity using less than 2 ml of sample. The method first decomposes FTIR spectra into fundamental building blocks using non-negative matrix factorization (NMF) to enable scientific analysis of FTIR spectra attributes and fuel properties. The NMF features are then used to create five ensemble models for predicting final boiling point, flash point, freezing point, density at 15°C, and kinematic viscosity at -20°C. All models were trained using experimental property data from neat molecules, aviation fuels, and blends. The models accurately predict key properties across a broad range of neat molecules and representative fuels and blends, while enabling interpretation of relationships between compositional elements, such as functional groups or chemical classes, and their resulting properties. This demonstrates strong potential to support sustainable aviation fuel research and development. The models and data are available on an interactive web tool.

Fourier transform infrared spectroscopy↗

DOE OSTI2022

Nuclear data uncertainty propagation applied to the versatile test reactor conceptual design

We report the Versatile Test Reactor (VTR) currently under development is a 300 MWth sodium-cooled fast reactor (SFR) fueled with ternary metal alloy fuel, which aims to accelerate the testing of advanced nuclear fuels, materials, instrumentation, and sensors in high flux environments that are necessary to license the next generation of advanced reactor concepts. To support the VTR design process, uncertainties associated with the nuclear data has been propagated through the reactor core neutronics calculation to global parameters of interest, such as the core multiplication factor, kinetic parameters, and various reactivity feedback coefficients, following the sensitivity based uncertainty propagation approach. By folding the sensitivity coefficients, separately computed by the generalized perturbation theory code PERSENT and Monte Carlo code Serpent 2, with the variance-covariance matrices from COMMARA-2.0, we obtain the reaction-wise, isotope-wise, and overall uncertainties for each response of interest due to nuclear data uncertainty. With Serpent 2, the statistical error of the uncertainty is obtained by propagating the statistical error of the sensitivity coefficients through the same process using a newly developed uncertainty propagation method. From both codes, the overall top uncertainty contributors are found to be the cross section of Fe-56 elastic scattering, Na-23 elastic scattering, and U 238 inelastic scattering. The large contributions of the Fe-56 elastic scattering cross sections to global parameters are due to its relatively large relative uncertainty of 5–10% in nuclear data and the large volume of Fe-containing reflector assemblies in the fairly compact VTR core design. Both codes agreed well for the overall uncertainty estimates of all responses of interest, except the delayed neutron fraction, prompt neutron generation time, and the coolant density feedback coefficient, where Serpent 2 yielded a much larger value than PERSENT due to the large statistical error of sensitivity coefficients. The calculated uncertainties are also compared to those associated with other SFR cores. Another outcome of this study is a variance-covariance matrix of reactivity coefficients, which can be used in the subsequent uncertainty propagation to the system level to investigate the impact of identified uncertainties on system responses in the safety analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Three-dimensional high-content imaging of unstained soft tissue with subcellular resolution using a laboratory-based X-ray microscope

With increasing interest in studying biological systems across spatial scales—from centimeters down to nanometers—histology continues to be the gold standard for tissue imaging at cellular resolution, providing an essential bridge between macroscopic and nanoscopic analysis. However, its inherently destructive and two-dimensional nature limits its ability to capture the full three-dimensional complexity of tissue architecture. Here, we show that phase-contrast X-ray microscopy can enable three-dimensional virtual histology with subcellular resolution. This technique provides direct quantification of electron density without restrictive assumptions, allowing for direct characterization of cellular nuclei in a standard laboratory setting. By combining high spatial resolution and soft tissue contrast, with automated segmentation of cell nuclei, we demonstrated virtual Hematoxylin and Eosin (H&E) staining using machine learning-based style transfer, yielding volumetric datasets compatible with existing histopathological analysis tools. Furthermore, by integrating electron density and the sensitivity to nanometric features of the dark field contrast channel, we achieve stain-free, high-content imaging capable of distinguishing nuclei and extracellular matrix.

3D virtual histology↗

DOE OSTI2024

Ground-state phase diagram and superconductivity of the doped Hubbard model on six-leg square cylinders

Here, we have studied the ground state properties of Hubbard model on long six-leg square cylinders with doped hole concentration per site 5.55%≤δ≤12.5% using density-matrix renormalization group. By keeping a large number of states for long system sizes, we find that the nature of the ground state is remarkably sensitive to the presence of next-nearest-neighbor electron hopping t'. In the positive t' side, we find a robust d-wave superconducting (SC) phase characterized by coexisting quasi-long-range SC and charge density wave (CDW) correlations. Without t' the ground state forms an insulating stripe phase with long-range CDW order but short-range spin-spin and SC correlations. In stark contrast to four-leg cylinders, our results show that the lightly doped Hubbard model on six-leg cylinders remains insulating in the negative t' side where the SC correlations decay exponentially with short correlation lengths. In the larger negative t' side, the doped holes form a novel holon Wigner crystal with one doped hole per emergent unit cell and short-range spin-spin correlations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Supersymmetric proton decay revisited

Encouraged by the advent of a new generation of underground detectors – JUNO, DUNE and Hyper-Kamiokande – that are projected to improve significantly on the present sensitivities to various baryon decay modes, we revisit baryon decay in the minimal supersymmetric SU(5) GUT. We discuss the phenomenological uncertainties associated with hadronic matrix elements and the value of the strong coupling αs – which are the most important – the weak mixing angle θ W , quark masses including one-loop renormalization effects, quark mixing and novel GUT phases that are not visible in electroweak interaction processes. We apply our analysis to a variety of CMSSM, super- and sub-GUT scenarios in which soft supersymmetry-breaking parameters are assumed to be universal at, above and below the GUT scale, respectively. In many cases, we find that the next generation of underground detectors should be able to probe models with sparticle masses that are O(10) TeV, beyond the reach of the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1972

The role of process history, phase morphology and interface strength upon the mechanical properties of dispersion strengthened alloys

An analytical rationale for the sensitivity-insensitivity of dispersion-strengthened systems to process history is provided. In particular, the research was focussed upon the influence of the particle-matrix interface bond in TD-Nickel and TD-Nichrome, and the manner in which the differences in both elastic constants and thermal expansion coefficients between these phases stress this interface when these alloys are subjected to mechanical and thermal loads upon the mechanical properties of these alloys.

Ansell, G. S.↗

NASA NTRS1981

Closed form evaluation of symmetric two-sided complex integrals

Evaluation of two-sided complex integrals is often required when analyzing linear systems to determine signal variances resulting from stochastic inputs and system noise bandwidths. Algebraic solutions of integrals in a closed matrix equation form, using coefficients of the numerator and denominator polynomials, are presented. The closed forms provide the possibility of obtaining some insight into parameter sensitivity in addition to greatly reducing the computational complexity required by the normal method of evaluation by residues.

Winkelstein, R.↗

NASA NTRS1982

Sensitivity analysis results of the effects of various parameters on composite design

Sensitivity analysis results are presented to assess the effects of a multitude of important parameters on fiber composite design and structural response. These results were obtained by using optimum design procedures in conjunction with sensitivity analyses. Sensitivity analyses were performed to assess the effects on composite optimum design and structural response of parameters such fiber transverse and shear properties, in situ matrix elastic and strength properties, correlation coefficients used in composite micromechanics and in combined strength predictions, processing variables, and perturbations of loading conditions. The results show that matrix properties, fiber volume ratio and small perturbations of the loading conditions have significant effects on certain composite structural responses. The remaining parameters have negligible effect.

Chamis, C. C.↗

NASA NTRS1984

Concepts for improving the damage tolerance of composite compression panels

The residual strength of specimens with damage and the sensitivity to damage while subjected to an applied inplane compression load were determined for flatplate specimens and blade-stiffened panels. The results suggest that matrix materials that fail by delamination have the lowest damage tolerance capability. Alternate matrix materials or laminates which are transversely reinforced suppress the delamination mode of failure and change the failure mode to transverse shear crippling which occurs at a higher strain value. Several damage-tolerant blade-stiffened panel design concepts are evaluated. Structural efficiency studies conducted show only small mass penalties may result from incorporating these damage-tolerant features in panel design. The implication of test results on the design of aircraft structures was examined with respect to FAR requirements.

Rhodes, M. D.↗

NASA NTRS1999

Effects of Orbital Lifetime Reduction on the Long-Term Earth Satellite Population as Modeled by EVOLVE 4.0

The latest update of the NASA orbital debris environment model, EVOLVE 4.0, has been used to study the effect of various proposed debris mitigation measures, including the NASA 25-year guideline. EVOLVE 4.0, which includes updates of the NASA breakup, solar activity, and the orbit propagator models, a GEO analysis option, and non-fragmentation debris source models, allows for the statistical modeling and predicted growth of the particle population >1 mm in characteristic length in LEO and GEO orbits. The initial implementation of this &odel has been to study the sensitivity of the overall LEO debris environment to mitigation measures designed to limit the lifetime of intact objects in LEO orbits. The mitigation measures test matrix for this study included several commonly accepted testing schemes, i.e., the variance of the maximum LEO lifetime from 10 to 50 years, the date of the initial implementation of this policy, the shut off of all explosions at some specified date, and the inclusion of disposal orbits. All are timely studies in that all scenarios have been suggested by researchers and satellite operators as options for the removal of debris from LEO orbits.

Krisko, Paula H.↗

NASA NTRS1999

Enhanced Boiling on Micro-Configured Composite Surfaces Under Microgravity Conditions

In order to accommodate the growing thermal management needs of future space platforms, several two-phase active thermal control systems (ATCSs) have evolved and were included in the designs of space stations. Compared to the pumped single-phase liquid loops used in the conventional Space Transportation System and Spacelab, ATCSs offer significant benefits that may be realized by adopting a two-phase fluid-loop system. Alternately, dynamic power systems (DPSs), based on the Rankine cycle, seem inevitably to be required to supply the electrical power requirements of expanding space activities. Boiling heat transfer is one of the key technologies for both ATCSs and DPSs. Nucleate boiling near critical heat flux (CHF) can transport very large thermal loads with much smaller device size and much lower pumping power. However, boiling performance deteriorates in a reduced gravity environment and operation in the CHF regime is precarious because any slight overload will cause the heat transfer to suddenly move to the film boiling regime, which in turn, will result in burnout of the heat transfer surfaces. New materials, such as micro-configured metal-graphite composites, can provide a solution for boiling enhancement. It has been shown experimentally that this type of material manifests outstanding boiling heat transfer performance and their CHF is also extended to higher values. Due to the high thermal conductivity of graphite fiber (up to 1,200 W/m-K in the fiber direction), the composite surfaces are non-isothermal during the boiling process. The composite surfaces are believed to have a much wider safe operating region (a more uniform boiling curve in the CHF regime) because non-isothermal surfaces have been found to be less sensitive to variations of wall superheat in the CHF regime. The thermocapillary forces formed by the temperature difference between the fiber tips and the metal matrix play a more important role than the buoyancy in the bubble detachment, for the bubble detachment manifests itself by a necking process which should not be weakened by reduced gravity. In addition, the composite surfaces introduce no extra pressure drop, no fouling and do not impose significant primary or maintenance costs. All of these suggest that this type of composite is an ideal material for the challenge of accounting for both reliability and economy of the relevant components applied in the ATCSs, the DPSs and other devices in future space missions. The aim of the proposed work is to experimentally investigate high nucleate pool boiling performance on a micro-configured metal-graphite composite surface and to determine the mechanisms of the nucleate boiling heat transfer both experimentally and theoretically. Freon-113 and water will be used as the test liquids to investigate wettability effects on boiling characteristics. The Cu-Gr and Al-Gr composites with various volume fractions of graphite fibers will be tested to obtain the heat transfer characteristic data in the nucleate boiling region and in the CHF regime. In the experiments, the bubble emission and coalescence processes will be recorded by a video camera with a magnifying borescope probe immersed in the working fluid. The temperature profile in the thermal boundary layer on the composite surfaces will be measured by a group of micro thermocouples consisting of four ultra fine micro thermocouples. This instrument was developed and successfully used to measure the temperature profile of evaporating liquid thin layers by the proposers in a study performed at the NASA/Lewis Research Center. A two tier model to explain the nucleate boiling process and the performance enhancement on the composite surfaces has been suggested by the authors. According to the model, the thicknesses of the microlayer and the macrolayer underneath the bubbles and mushrooms, can be estimated by the geometry of the composite surface. The experimental results will be compared to the predictions from the model, and in turn, to revise and improve it.

Zhang, Nengli↗

NASA NTRS2004

Water-Based Pressure Sensitive Paint

Preparation and performance of a water-based pressure sensitive paint (PSP) is described. A water emulsion of an oxygen permeable polymer and a platinum porphyrin type luminescent compound were dispersed in a water matrix to produce a PSP that performs well without the use of volatile, toxic solvents. The primary advantages of this PSP are reduced contamination of wind tunnels in which it is used, lower health risk to its users, and easier cleanup and disposal. This also represents a cost reduction by eliminating the need for elaborate ventilation and user protection during application. The water-based PSP described has all the characteristics associated with water-based paints (low toxicity, very low volatile organic chemicals, and easy water cleanup) but also has high performance as a global pressure sensor for PSP measurements in wind tunnels. The use of a water-based PSP virtually eliminates the toxic fumes associated with the application of PSPs to a model in wind tunnels.

Oglesby, Donald M.↗

DOE OSTI2024

Analytic Sensitivity Coefficients for General Multigroup Infinite Medium k-Eigenvalue Problems

The general multigroup infinite medium k-eigenvalue neutron transport equation is used to derive analytic expressions for the infinite medium k-eigenvalue, the scalar neutron flux and adjoint, and the sensitivity of $k$ ∞ to perturbations in the multigroup nuclear data of a single species isotropic elastic scattering material. In the appendix, we present the multigroup nuclear data for U-235 and U-238 along with the corresponding k-eigenvalue, flux, adjoint, and sensitivity profiles, which include the sensitivity of $k$ ∞ to the total, fission, capture, and scattering macroscopic cross sections as well as to the group-to-group scattering cross section matrix, group neutron production, and the unconstrained and constrained fission neutron energy distribution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Search for New Physics via EFT in collisions containing a top quark and a boosted Z or Higgs boson

We present a generator-level sensitivity study of physics beyond the Standard Model within the framework of Effective Field Theory (EFT). The targeted signal processes are single top quark production in association with a Lorentz-boosted Higgs or Z boson (tHq and tZq) in proton-proton collisions at a center-of-mass energy of 13.6 TeV. Event selection requires one electron or muon, a high-transverse-momentum, large-radius (AK8) jet reconstructing hadronic H → b̄b or Z → b̄b decays, at least two distinct, non-overlapping small-radius (AK4) jets with one originating from a b quark, and a missing transverse energy greater than 30 GeV. Signal and background samples are generated via Monte Carlo simulation using MadGraph with MadJax to perform EFT matrix-element calculations. Deviations from the Standard Model are parametrized through dimension-six EFT operators that probe modified top quark interactions. This generator-level study identifies kinematic observables with enhanced sensitivity to EFT operators and motivates future reconstruction-level analyses of tHq and tZq channels.

Meshramkar, Daniel [Baylor U., Waco]↗

DOE OSTI2026

Search for New Physics via EFT in collisions containing a top quark and a boosted Z or Higgs boson

Meshramkar, Daniel [Baylor U., Waco]↗

DOE OSTI2025

Sensitized Near-Infrared Emission of SiGe Nanocrystals via Heterostructuring with Quasi Two-Dimensional Perovskite

The near-infrared (NIR) emission of silicon–germanium alloy nanocrystals (SiGe NCs) was sensitized by heterostructuring with a quasi two-dimensional (Q-2D) perovskite (CsPbBr 3 blended with butylammonium bromide (BABr)). Colloidal SiGe NCs were synthesized by using a nonthermal plasma method with chloride precursors. As-synthesized SiGe NCs showed no detectable photoluminescence (PL). Embedding the SiGe NCs within the perovskite matrix via spin coating led to a heterostructure exhibiting dual emissions: green emission at 520 nm from the perovskite and NIR emission at 1035 nm from the SiGe NCs. Time-integrated and resolved PL measurements and transient absorption spectroscopy revealed energy transfer from the perovskite to the SiGe NCs, which sensitized the NIR emission from the SiGe NCs and quenched the green PL for the perovskite. These results demonstrate that Ge alloying can effectively tune the bandgap of Si NCs and highlight the feasibility of heterostructuring perovskites and photoluminescent NCs to enhance or activate their PL. In conclusion, this approach broadens their potential applications in the NIR region.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Active operator learning with predictive uncertainty quantification for partial differential equations

With the increased prevalence of neural operators being used to provide rapid solutions to partial differential equations (PDEs), understanding the accuracy of model predictions and the associated error levels is necessary for deploying reliable surrogate models in scientific applications. Existing uncertainty quantification (UQ) frameworks employ ensembles or Bayesian methods, which can incur substantial computational costs during both training and inference. Here, we propose a lightweight predictive UQ method tailored for Deep operator networks (DeepONets) that also generalizes to other operator networks. Numerical experiments on linear and nonlinear PDEs demonstrate that the framework’s uncertainty estimates are unbiased and provide accurate out-of-distribution uncertainty predictions with a sufficiently large training dataset. Our framework provides fast inference and uncertainty estimates that can efficiently drive outer-loop analyses that would be prohibitively expensive with conventional solvers. We demonstrate how predictive uncertainties can be used in the context of Bayesian optimization and active learning problems to yield improvements in accuracy and data-efficiency for outer-loop optimization procedures. In the active learning setup, we extend the framework to Fourier Neural Operators (FNO) and describe a generalized method for other operator networks. To enable real-time deployment, we introduce an inference strategy based on precomputed trunk outputs and a sparse placement matrix, reducing evaluation time by more than a factor of five. Our method provides a practical route to uncertainty-aware operator learning in time-sensitive settings.

97 MATHEMATICS AND COMPUTING↗