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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Uncertainty Modeling Via Frequency Domain Model Validation

Abstract The majority of literature on robust control assumes that a design model is available and that the uncertainty model bounds the actual variations about the nominal model. However, methods for generating accurate design models have not received as much attention in the literature. The influence of the level of accuracy of the uncertainty model on closed loop performance has received even less attention. The research reported herein is an initial step in applying and extending the concept of model validation to the problem of obtaining practical uncertainty models for robust control analysis and design applications. An extension of model validation called 'sequential validation' is presented and applied to a simple spring-mass-damper system to establish the feasibility of the approach and demonstrate the benefits of the new developments.

Waszak, Martin R.↗
DOE OSTI2025

Fuel Property Effects on Stochastic Preignition Events During Engine Load Transitions

Stochastic preignition (SPI) is an abnormal combustion phenomenon that can cause catastrophic engine damage. There have been several proposed mechanisms of SPI, where a uniform source is still not certain, however, SPI tendencies have been shown to be influenced by engine operating conditions, oil composition, engine age, and fuel chemical and physical properties. Laboratory research and testing for SPI propensity is challenging given the stochastic nature of events, as well as the potential for significant degradation of the engine platform and measuring equipment over time. Thus, SPI specific experiments are generally conducted under either sustained or cyclic patterning of steady-state operating conditions to avoid the influence of transient engine boundary conditions on test parameters of interest (e.g. oil additive package, fuel properties, engine speed/load, etc.). In this work a cyclically varying SPI test sequence involves a 5 min engine warmup period at a low engine load of around 4 bar gross indicated mean effective pressure (IMEPg), followed by a transition to high load (~20 bar IMEPg) at a constant 2000 rev/min engine speed for a total of 25 min. This individual test sequence load schedule is then sequentially repeated 10 times to generate significant statistical data for analysis. This work examines the influence of fuel chemical and physical properties on SPI tendency during the unsteady portion of the 10-cycle sequence (the first 5 min of the high load operation in each sequence of the loading cycle) which has been discarded from previous analyses due to the uncertainty in engine operating and thermal boundary conditions. Results from this analysis suggest an increasing trend in the ratio of SPI events during the unsteady test period relative to the steady test period with increasing fuel Reid Vapor Pressure (RVP), implying differences in uncontrolled ignition source terms, possibly from, fuel wall interactions and retention during the load transition phase of the test.

Splitter, Derek [ORNL] (ORCID:0000000174044047)↗
NASA NTRS2006

Nonlinear consider covariance analysis using a sigma-point filter formulation

The research reported here extends the mathematical formulation of nonlinear, sigma-point estimators to enable consider covariance analysis for dynamical systems. This paper presents a novel sigma-point consider filter algorithm, for consider-parameterized nonlinear estimation, following the unscented Kalman filter (UKF) variation on the sigma-point filter formulation, which requires no partial derivatives of dynamics models or measurement models with respect to the parameter list. It is shown that, consistent with the attributes of sigma-point estimators, a consider-parameterized sigma-point estimator can be developed entirely without requiring the derivation of any partial-derivative matrices related to the dynamical system, the measurements, or the considered parameters, which appears to be an advantage over the formulation of a linear-theory sequential consider estimator. It is also demonstrated that a consider covariance analysis performed with this 'partial-derivative-free' formulation yields equivalent results to the linear-theory consider filter, for purely linear problems.

covariance↗
DOE OSTI2026

Temperature‐Dependent Crystallization in Two‐Step Perovskite Deposition Revealed by In Situ GIWAXS and Machine Learning‐Guided Analysis

The performance and stability of perovskite solar cells are strongly governed by the crystallization behavior of their active layer. In two-step sequential deposition, early-stage film formation plays a decisive role in determining final phase purity and device quality. Guided by a data-driven analysis of nearly 39 000 devices in the FAIR perovskite database, we identified solvent-mediated quenching and thermal processing as key variables affecting power conversion efficiency (PCE), particularly in two-step fabrication. Here, to investigate these effects in real time, we designed and implemented a custom-built, temperature-controlled spin-coating system, enabling precise thermal modulation during precursor deposition. Using this platform, we performed in situ GIWAXS measurements to study the crystallization dynamics of FA 0.5 MA 0.5 PbI 3 films over a temperature range of 30°C–90°C. Our results reveal a non-monotonic relationship between spin-coating temperature and α-phase formation, governed by the interplay between precursor interdiffusion, PbI 2 crystallinity, and δ-phase suppression. The custom thermal control enabled us to isolate and quantify these competing effects during the earliest stages of film formation, providing mechanistic insight into how spin-coating temperature governs both phase purity and kinetic pathways in two-step perovskite systems. Temperature-dependent SEM and photovoltaic device measurements further demonstrate that early-stage crystallization pathways directly translate into differences in morphology, charge-transport continuity, and device performance. These findings inform targeted strategies for optimizing deposition protocols to balance rapid nucleation, phase stability, and device performance.

Saadawy, Ahmed [King Fahd University of Petroleum ↗
DOE OSTI2021

Design of a 3.4-MW wind turbine with integrated plasma actuator-based load control

Historically, cost reduction in wind energy has been accomplished by increasing hub heights and rotor diameters to capture more energy per turbine. The growth in rotor and turbine costs with increasing turbine sizes is also driven by the additional structure that must be added to withstand unsteady aerodynamic loads caused by turbulence, gusts, wind shear, misaligned yaw, upwind wakes, and the tower shadow. In this paper, we present a holistic design solution to integrate active load control using a controllable Gurney flap based on plasma actuators. We illustrate the design solution for a land-based 3.4-MW wind turbine rotor. Comparisons to a baseline reference 3.4-MW wind turbine show significant load reduction (15–18% DEL reduction for flap-wise blade root moments), rotor mass reduction (5–8%), and LCOE reduction (1.16–3.11%). To achieve these results, a comprehensive sequential-iterative design procedure is introduced to integrate the controllable Gurney flap into the turbine design and to drive the design solution toward the best LCOE reduction solution. Results are presented for mapping fatigue load reductions into cost reductions. In addition, an evaluation of active load control extended from Region-III to also include Region-II showed a further 34% reduction in DEL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1998

Multiphysics Code Demonstrated for Propulsion Applications

The utility of multidisciplinary analysis tools for aeropropulsion applications is being investigated at the NASA Lewis Research Center. The goal of this project is to apply Spectrum, a multiphysics code developed by Centric Engineering Systems, Inc., to simulate multidisciplinary effects in turbomachinery components. Many engineering problems today involve detailed computer analyses to predict the thermal, aerodynamic, and structural response of a mechanical system as it undergoes service loading. Analysis of aerospace structures generally requires attention in all three disciplinary areas to adequately predict component service behavior, and in many cases, the results from one discipline substantially affect the outcome of the other two. There are numerous computer codes currently available in the engineering community to perform such analyses in each of these disciplines. Many of these codes are developed and used in-house by a given organization, and many are commercially available. However, few, if any, of these codes are designed specifically for multidisciplinary analyses. The Spectrum code has been developed for performing fully coupled fluid, thermal, and structural analyses on a mechanical system with a single simulation that accounts for all simultaneous interactions, thus eliminating the requirement for running a large number of sequential, separate, disciplinary analyses. The Spectrum code has a true multiphysics analysis capability, which improves analysis efficiency as well as accuracy. Centric Engineering, Inc., working with a team of Lewis and AlliedSignal Engines engineers, has been evaluating Spectrum for a variety of propulsion applications including disk quenching, drum cavity flow, aeromechanical simulations, and a centrifugal compressor flow simulation.

Lawrence, Charles↗
NASA NTRS1980

Performance analysis of the Spaceborne Laser Ranging System

The performance of the Spaceborne Laser Ranging System in the determination of distances between ground-based targets is discussed. The system consists of an orbiting pulsed laser distance measurement system that sequentially measures the distance to retroreflector arrays on the ground. Intersite distances are then determined from an analysis of the vertical distance data and the spacecraft orbital dynamics. Results of computer simulations indicate that for a six-day observing period with 50 percent cloud cover, uncertainties of 1 to 3 cm are expected for intertarget separations of 50 to 1200 km, with vertical uncertainties from 1 to 12 cm. Furthermore, it is found that by redetermining relative target positions, precision can be increased to less than 0.3 cm to 1 cm in the baseline and to 0.4 to 4 cm in vertical distance. It is concluded that with these precisions, strain and strain rate can be determined for crustal dynamics and earthquake studies, and geodetic surveys can be performed.

Kahn, W. D.↗
DOE OSTI2022

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis

Estimating probability of failure in aerospace systems is a critical requirement for flight certification and qualification. Failure probability estimation involves resolving tails of probability distributions, and Monte Carlo sampling methods are intractable when expensive high-fidelity simulations have to be queried. Here, we propose a method to use models of multiple fidelities that trade accuracy for computational efficiency. Specifically, we propose the use of multifidelity Gaussian process models to efficiently fuse models at multiple fidelity, thereby offering a cheap surrogate model that emulates the original model at all fidelities. Furthermore, we propose a novel sequential acquisition function based experiment design framework that can automatically select samples from appropriate fidelity models to make predictions about quantities of interest at the highest fidelity. We use our proposed approach in an importance sampling setting and demonstrate our method on the failure level set and probability estimation on synthetic test functions and two real-world applications, namely, the reliability analysis of a gas turbine engine blade using a finite element method and a transonic aerodynamic wing test case using Reynolds-averaged Navier-Stokes equations. We show that our method predicts the failure boundary and probability more accurately and at a fraction of the computational cost compared with using just a single expensive high-fidelity model. Finally, we show that our sequential approach is guaranteed to asymptotically converge to the true failure boundary with high probability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Integrating tactical planning, operational planning and scheduling using data-driven feasibility analysis

Supply chain operations and scheduling are well-studied problems in the literature. Although these problems are related, they are often solved sequentially. This uncoordinated approach usually leads to sub-optimal solutions. Here this paper proposes a methodology for integrating scheduling operations into the supply chain network, motivated by the available enterprise data, and feasibility analysis. Existing literature on integrated models for addressing the supply chain is reviewed and classified. Then the mathematical model formulation for each level is discussed, after which the proposed data-driven integrated framework is described. The methodology is tested on two different case studies of varying dimensions. For each case study, the solution solves a multi-objective problem with the overall aim of an optimal solution that is robust towards achieving optimal cost while keeping customer satisfaction in mind.

42 ENGINEERING↗
DOE OSTI2024

Mbin v1.0

The Mbin software, is a software toolkit that implements the IMG metagenome binning pipeline. The software allows the user to process input metagenome contigs, and produces metagenome assembled genomes (metagenome bins) and valuation metrics per bin including completion and contamination estimates, quality assignment, predicted lineage and eukaryotic potential. It is currently packed as a portable docker container and provides the advantage of running the process of binning and analysis of the bins generated, using a suite of tools run sequentially with controls in place to capture errors and optional arguments to run a modified version depending on individual needs and capabilities.

Varghese, Neha↗
DOE OSTI2026

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1981

The Fabry-Perot Interferometer on Dynamics Explorer

The Fabry-Perot Interferometer (FPI) on Dynamics Explorer is a remote sensing instrument designed to measure the temperature, meridional wind and density of the metastable atoms O(1S) and O(1D), and the ion O(plus)(2P) in the thermosphere. The measurements are made with a stable, high resolution Fabry-Perot etalon, which performs a wavelength analysis on the light detected from the thermospheric emission features by spatially scanning the interference fringe plane with a multichannel array detector. The wavelength analysis characterizes the Doppler line profile of the emitting species. A sequential altitude scan, performed by a commandable horizon scan mirror, provides a cross-sectional view of the thermodynamic and dynamic state of the thermosphere below the orbit of the Dynamics Explorer B satellite.

Hays, P. B.↗
NASA NTRS1986

The organic aerosols of Titan

A dark reddish organic solid, called tholin, is synthesized from simulated Titanian atmospheres by irradiation with high energy electrons in a plasma discharge. The visible reflection spectrum of this tholin is found to be similar to that of high altitude aerosols responsible for the albedo and reddish color of Titan. The real (n) and imaginary (k) parts of the complex refractive index of thin films of Titan prepared by continuous dc discharge through a 0.9 N2/0.1 CH4 gas mixture at 0.2 mb is determined from X-ray to microwave frequencies. Values of n (approx. 1.65) and k (approx. 0.004 to 0.08) in the visible are consistent with deductions made by groundbased and spaceborne observations of Titan. Many infrared absorption features are present in k(lambda), including the 4.6 micrometer nitrile band. Molecular analysis of the volatile components of this tholin was performed by sequential and nonsequential pyrolytic gas chromatography/mass spectrometry. More than one hundred organic compounds are released; tentative identifications include saturated and unsaturated aliphatic hydrocarbons, substituted polycylic aromatics, nitriles, amines, pyrroles, pyrazines, pyridines, pyrimidines, and the purine, adenine. In addition,acid hydrolysis produces a racemic mixture of biological and nonbiological amino acids. Many of these molecules are implicated in the origin of life on Earth, suggesting Titan as a contemporary laboratory environment for prebiological organic chemistry on a planetary scale.

Khare, B. N.↗
NASA NTRS1990

Martian impact craters: Continuing analysis of lobate ejecta sinuosity

The lobate ejecta morphology surrounding most fresh Martian impact craters can be quantitatively analyzed to determine variations in ejecta sinuosity with diameter, latitude, longitude, and terrain. The results of such studies provide another clue to the question of how these morphologies formed: are they the results of vaporization of subsurface volatiles or caused by ejecta entrainment in atmospheric gases. Kargel provided a simple expression to determine the degree of non-circularity of an ejecta blanket. This measure of sinuosity, called 'lobateness', is given by the ratio of the ejecta perimeter to the perimeter of a circle with the same area as that of the ejecta. The Kargel study of 538 rampart craters in selected areas of Mars led to the suggestion that lobateness increased with increasing diameter, decreased at higher latitude, and showed no dependence on elevation or geologic unit. Major problems with the Kargel analysis are the limited size and distribution of the data set and the lack of discrimination among the different types of lobate ejecta morphologies. Bridges and Barlow undertook a new lobateness study of 1582 single lobe (SL) and 251 double lobe (DL) craters. The results are summarized. These results agree with the finding of Kargel that lobateness increases with increasing diameter, but found no indication of a latitude dependence for SL craters. The Bridges and Barlow study has now been extended to multiple lobe (ML) craters. Three hundred and eighty ML craters located across the entire Martian surface were studied. ML craters provide more complications to lobateness studies than do SL and DL craters - in particular, the ejecta lobes surrounding the crater are often incomplete. Since the lobateness formula compares the perimeter of the ejecta lobe to that of a circle, the analysis was restricted only to complete lobes. The lobes are defined sequentially starting with the outermost lobe and moving inward.

Barlow, Nadine G.↗
DOE OSTI2023

STAND Quickstart Guide

STAND is a flexible web application designed to identify and examine potentially feasible sites where advanced nuclear facilities might be welcomed by host communities. STAND allows the user to explore and provide insight on socioeconomic, proximity, and safety data, generate county reports, review regulatory data, and complete a comparative analysis across multiple sites by following several paths, either individually or sequentially based on the user’s needs and where they are in the deployment process. STAND is best used for the contiguous United States. STAND is not a substitute for the in-depth studies required to qualify a site for hosting a nuclear facility, nor is it a substitute for the necessary community engagement to build trust and seek consent. It can, however, be a valuable resource to aid in the siting process.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

STAND Quickstart Guide

STAND is a flexible web application designed to identify and examine potentially feasible sites where advanced nuclear facilities might be welcomed by host communities. STAND allows the user to explore and provide insight on socioeconomic, proximity, and safety data, generate county reports, review regulatory data, and complete a comparative analysis across multiple sites by following several paths, either individually or sequentially based on the user’s needs and where they are in the deployment process.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

Aerosol Observability and Predictability: From Research to Operations for Chemical Weather Forecasting. Lagrangian Displacement Ensembles for Aerosol Data Assimilation

A challenge common to many constituent data assimilation applications is the fact that one observes a much smaller fraction of the phase space that one wishes to estimate. For example, remotely sensed estimates of the column average concentrations are available, while one is faced with the problem of estimating 3D concentrations for initializing a prognostic model. This problem is exacerbated in the case of aerosols because the observable Aerosol Optical Depth (AOD) is not only a column integrated quantity, but it also sums over a large number of species (dust, sea-salt, carbonaceous and sulfate aerosols. An aerosol transport model when driven by high-resolution, state-of-the-art analysis of meteorological fields and realistic emissions can produce skillful forecasts even when no aerosol data is assimilated. The main task of aerosol data assimilation is to address the bias arising from inaccurate emissions, and Lagrangian misplacement of plumes induced by errors in the driving meteorological fields. As long as one decouples the meteorological and aerosol assimilation as we do here, the classic baroclinic growth of error is no longer the main order of business. We will describe an aerosol data assimilation scheme in which the analysis update step is conducted in observation space, using an adaptive maximum-likelihood scheme for estimating background errors in AOD space. This scheme includes e explicit sequential bias estimation as in Dee and da Silva. Unlikely existing aerosol data assimilation schemes we do not obtain analysis increments of the 3D concentrations by scaling the background profiles. Instead we explore the Lagrangian characteristics of the problem for generating local displacement ensembles. These high-resolution state-dependent ensembles are then used to parameterize the background errors and generate 3D aerosol increments. The algorithm has computational complexity running at a resolution of 1/4 degree, globally. We will present the result of assimilating AOD retrievals from MODIS (on both Aqua and TERRA satellites) from AERONET for validation. The impact on the GEOS-5 Aerosol Forecasting will be fully documented.

da Silva, Arlindo↗