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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Computational modeling and validation of a modified Marple cascade impactor

Oak Ridge National Laboratory (ORNL) is investigating respirable aerosol fractions from failed high-burnup (HBU) commercial spent nuclear fuel (CSNF) rods (Montgomery et al., 2022). The work aims to characterize the source term of radioactive aerosols that could result from mechanical failure and handling of failed fuel rods during storage and/or transportation. The experiment involves capturing and characterizing aerosols from a four-point bending experiment of fueled rod segments at ORNL’s Irradiated Fuels Examination Laboratory (IFEL). For this, a Marple cascade impactor (Series 290) with the ability to collect particles up to aerodynamic equivalent diameters of ~15 μm was tested for feasibility. The commercially available Marple cascade impactor design was modified for the experiment, where the cascade inlet was replaced with a 3D printed inlet nozzle. Collection efficiency curves were then generated with the modified impactor, and the cascade’s performance was tested using ISO dust capture experiments followed by SEM analysis of the collection and computational modeling. The current work highlights the performance testing and experimental validation of this modified Marple Impactor for spent nuclear fuel aerosol collection.

Kumar, Vineet↗
DOE OSTI2025

Long‐Term Impacts of Global Solid Biofuel Emissions on Ambient Air Quality and Human Health for 2000–2019

Globally, solid biofuels (SB) have been widely used for household cooking and energy production for decades due to electricity shortages and socio-economic barriers to adopting renewable energy alternatives. This has detrimental effects on air quality, human health, and climate through trace gas and aerosol emissions. Despite numerous studies, the long-term consequences of SB emissions remain poorly understood. Here, we use the Community Earth System Model and the Community Emissions Data System emission inventory to investigate the SB emission impacts on air quality and human health for 2000–2019. Global SB emission increased the ambient PM 2.5 (particulate matter with aerodynamic diameters ≤2.5 μm) and ozone (O 3 ) concentrations up to 23.61 μg/m 3 and 13.69 ppbv, with significant effects found in India, China, and the Rest of Asia (ROA). Our study estimates total annual premature deaths (APDs) associated with global SB-attributable PM 2.5 and O 3 exposure as 1.11 million [95% confidence interval (95% CI): 1.00–1.22 million] in 2000 up to 1.43 million (95% CI: 1.30–1.56 million) in 2019. China's SB emissions and associated APDs have reduced substantially, whereas India and ROA had a major leap in both estimates in 2019 compared to 2000. China's progress in cutting residential SB emissions accounts for its improvements. Our study urges the reduction of SB usage and emissions to potentially improve overall air quality and human health conditions, especially in highly populated, low- and middle-income countries, where the poor air quality and associated health burden attributable to SB emissions are estimated to be higher.

O 3↗
DOE OSTI2026

Autonomie Simulation Datasets in Support of U.S. DOT-NHTSA Advanced Vehicle Technology Research

Understanding how new vehicle technologies affect fuel economy and energy use is critical to the regulatory work performed by the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA), which sets Corporate Average Fuel Economy (CAFE) standards under the Energy Policy and Conservation Act of 1975. In order to support this work, Argonne National Laboratory uses Autonomie, a full-vehicle simulation tool, to evaluate advanced powertrain architectures and their effects on vehicle energy consumption and performance. A wide range of vehicle classes has been assessed (i.e., internal combustion engine vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, battery-electric vehicles, and fuel cell electric vehicles), as well as the effects of various technology improvements such as lightweighting, aerodynamic refinements, and low-rolling-resistance tires. Simulations have been run across multiple drive cycles to capture fuel and electricity use under realistic operating conditions. The resulting datasets include detailed vehicle-level results, model assumptions, and validation reports, all of which have been made publicly available through NHTSA in support of the 2023 notice of proposed rulemaking covering light-duty vehicles for model years 2027 to 2035. These data are critical to stakeholders working in fuel economy regulation, vehicle technology assessment, and energy policy analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

OpenTurbine [SWR-23-07]

OpenTurbine is an open-source code designed for the simulation of wind turbine structural dynamics. It is a flexible multi-body dynamics solver wherein the wind turbine is modeled as a collection of beam finite elements, rigid bodies, and constraints. OpenTurbine is equipped with an application programming interface primarily designed for coupling to computational fluid dynamics codes, but it is also suited for coupling to aerodynamics solvers based on blade element momentum theory.

Sprague, MichaelA.↗
DOE OSTI2021

Advanced Multi-Tube Mixer Combustion for 65% Efficiency (Final Report)

This project targeted advanced low NOx combustion for advanced gas turbines capable of 65%, or greater, efficiency in combined cycle application. This technology advancement has further potential to benefit gas turbines used in coal based IGCC applications with pre-combustion carbon capture and hydrogen as the resulting fuel. The program developed and synthesized the most advanced combustion system capable of achieving low NOX emissions up to turbine inlet temperatures of 3100F while also supporting the load-following needs of a modern grid. The combustion system contributes to the overall gas turbine efficiency goal by setting the maximum cycle temperature achievable for a given NOX level and by minimizing the through-combustor air flow pressure drop. Focus areas for this project targeted maximizing the turbine inlet temperature entitlement, as constrained by emissions considerations. The design also minimized parasitic air flow pressure drop by using advanced cooling techniques and performance materials selections and by minimizing hot surface area. These two technology objectives (maximum, emissions-compliant cycle temperature and minimum air flow pressure drop) were integrated into a prototype design. The primarily analytical project sought to identify the most promising technologies to meet these objectives. Additional critical “jugular” data were obtained from multi-tube mixer tests to realize the potential of leveraging “micro flames” for minimizing overall hot surface area. This data was used, in conjunction with an understanding of advanced material and cooling design technologies, to analytically develop multiple design concepts. Phase I focused on in-depth engineering analysis and design, with minimal supporting laboratory testing to enable a selection of the top three combustion architectures for achieving these overall objectives. Phase II of the program developed the selected design through a combination of sub-scale testing and analytical efforts. Early tests included a cold-flow cascade to establish aerodynamic performance characteristics and a sub-scale fired test at GE Global Research in Niskayuna, NY, to establish cooling and heat transfer characteristics in conjunction with combustion performance. The data from these tests validated the analytical models to ultimately design a full-scale, test article to evaluate at prototypical pressure and temperature conditions at GE Gas Power’s Gas Turbine Technology Laboratory in Greenville, SC. GE Gas Power also developed, tested, and recommended a suitable seal design to be applied to the unique features of the combustor. To assess the technology challenges from prospective future production of the combustor from a ceramic matrix composite material, screening tests of Environmental Barrier Coatings were completed.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Flashback characterization of additively manufactured swirl-stabilized fuel injector with varying surface roughness

This work investigates the effects of as-built surface roughness on the flashback propensity in additively manufactured (AM) swirl-stabilized lean premixed (LPM) fuel injectors. Adoption of AM for rapid prototyping and fabrication of complex fuel-flexible injector designs requires investigating surface roughness effects on the flow and flame stability characteristics of the combustor. Wall roughness increases the near-wall shear, which could alter the boundary layer structure and change the propensity for flame flashback. Accounting for the realistic as-built surface roughness is crucial in carrying out computational modeling and experimental analysis to establish a feedback loop for the precision designing of fuel-flexible injectors. The presented numerical analysis of as-built AM injector is an essential consideration to optimize injector design for aerodynamics and additive manufacturability.

Mohanty, Pratikshya↗
DOE OSTI2025

Wind Turbine Rotor Design Using High-Fidelity Aerostructural Optimization

Large wind turbines yield more energy but demand careful aeroelastic blade design. Coupled multiphysics design strategies can reduce wind energy costs by exploiting fluid-structure interactions. This work presents the first high-fidelity aerostructural optimization study of a large wind turbine rotor. We use blade-resolved fluid dynamics and structural solvers in a monolithic gradient-based optimization framework to explore steady-state torque and blade mass tradeoffs. The coupled-adjoint approach computes gradients efficiently, enabling the optimization of over 100 structural and geometric parameters simultaneously. Our optimization study modifies a DTU 10 MW benchmark with a simplified structure and isotropic material properties. The tightly coupled optimizations increase torque by 14% while reducing rotor mass by 9% or reduce blade mass by 27% while maintaining torque. Blade-resolved models provide greater design freedom, enabling 5% higher mass reductions than conventional parameterizations at equal torque. This framework paves the way for more detailed high-fidelity optimization studies to complement conventional design approaches.

17 WIND ENERGY↗
DOE OSTI2024

Heliostat Consortium: Gap Analysis on State of the Art in Wind Load Design

Wind loads are a major driver of heliostat cost. Standardized methods and tools are needed for a more detailed understanding of the static and dynamic loads of a heliostat design. This will enable cost reduction of wind-dependent heliostats to avoid unnecessarily conservative heliostat designs and increase field efficiency and reliability to reduce the risk of component failures due to high-wind events. Gaps related to wind load include lack of site characterization for wind measurements, insufficient critical load cases for heliostat design, insufficient understanding of turbulence impacts on heliostat tracking error, lack of knowledge on wind load under various heliostat array configurations, and underexplored heliostat field wind-load reduction and operating strategies. Recommended pathway forward is to develop wind load and site characterization guidelines for heliostat design and develop heliostat field wind-load models with optical performance impacts.

aerodynamics↗
DOE OSTI2020

Aerodynamic Data Fusion Toward the Digital Twin Paradigm

This paper considers the fusion of two aerodynamic data sets originating from differing types of physical or computer experiments. This paper specifically addresses the fusion of 1) noisy and in-complete fields from wind-tunnel measurements and 2) deterministic but biased fields from numerical simulations. These two data sources are fused in order to estimate the true field that best matches measured quantities that serve as the ground truth. For example, two sources of pressure fields about an aircraft are fused based on measured forces and moments from a wind-tunnel experiment. A fundamental challenge in this problem is that the true field is unknown and cannot be estimated with 100% certainty. A Bayesian framework is employed to infer the true fields conditioned on measured quantities of interest; essentially a statistical correction to the data is performed. The fused data may then be used to construct more accurate surrogate models suitable for early stages of aerospace design. An extension of the proper orthogonal decomposition with constraints is also introduced to solve the same problem. In this work, both methods are demonstrated on fusing the pressure distributions for flow past the RAE2822 airfoil and the Common Research Model wing at transonic conditions. Comparison of both methods reveals that the Bayesian method is more robust when data are scarce and capable of also accounting for uncertainties in the data. Furthermore, given adequate data, the proper-orthogonal-decomposition-based and Bayesian approaches lead to surprisingly similar results.

42 ENGINEERING↗
DOE OSTI2021

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction

42 ENGINEERING↗
DOE OSTI2025

Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks

The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

The Fluid Dynamics Uncertainty Quantification Challenge Problem: XFOIL vs. MFOIL

Uncertainty quantification (UQ) has become more critical in aerospace engineering due to the growing dependence on computational tools for design optimization and performance analyses of aerospace vehicles. Even though the significance of UQ in assessing the credibility of computational analyses is well recognized, its costs and complexity impede its integration into standard practices, particularly in computational fluid dynamics (CFD) and other fluid analyses. This paper presents a UQ study for low-fidelity computational aerodynamics analyses with XFOIL and mfoil (i.e., the MATLAB version of XFOIL with several implementation modifications); these tools are utilized widely in both research and education. The main contributions of this paper are as follows: 1) improved precision in quantifying the uncertainty of the baseline Monte Carlo results used to benchmark surrogate modeling techniques for UQ, 2) quantification of the effect of the implementation differences between XFOIL and mfoil on solution quantities of interest (QoIs), such as lift and pitching moment coefficients, and 3) development of an open-source UQ library for use with XFOIL and mfoil, which has educational values and helps promote UQ for fluid analyses with aerospace applications. Results and discussions revolve around cases 1-4 of the challenge problem posed by the AIAA Fluid Dynamics Technical Committee’s Uncertainty Quantification Discussion Group (UQDG). In case 3, this work employs CFDverify, an open-source solution verification software, to quantify the discretization error and evaluate the extrapolated QoIs based on the grid convergence index (GCI). This UQ study differentiates itself from previous studies in the rigor of handling baseline Monte Carlo uncertainty and in including mfoil, which is a more accessible alternative to XFOIL. Finally, despite the growing computing power, low-fidelity computational tools remain valuable, such as for aerodynamic shape optimization at Mach numbers below 0.65 and low-to-mid Reynolds numbers.

Lay, Aidan S [University of Tennessee, Knoxville (↗
DOE OSTI2023

The structure of molten calcium ferrite under various redox conditions

Laser-heated melts based on the 43CaO–57Fe 2 O 3-x eutectic, close to the calcium ferrite (CF) composition, were measured with high-energy X-ray diffraction using aerodynamic levitation over a range of redox states controlled by CO/CO 2 gas atmospheres. The iron–oxygen coordination number was found to rise from 4.4 ± 0.3 at 15% Fe 3+ to 5.3 ± 0.3 at 87% Fe 3+ . Empirical potential structure refinement modelling was used to obtain the ferric and ferrous partial pair distribution functions. It was found that the Fe 2+ iron–oxygen coordination number is consistently approximately 10% higher in CF than in pure iron oxide, while Fe 3+ is essentially identical in all but the most oxygen-rich environments (where it is higher in CF compared with FeO x ). The model also shows calcium octahedra to be the dominant species across all redox environments, although the population of CaO 7 increases with the availability of oxygen at the expense of CaO 4 and CaO 5 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

RAFT (Response Amplitudes of Floating Turbines) [SWR-22-40]

RAFT is a Python code for frequency-domain analysis of floating wind turbines. RAFT works in the frequency domain to provide efficient computations of a floating wind system's response spectra accounting for platform hydrodynamics, quasi-static mooring reactions, rotor aerodynamics, and linearized control. It can be used to calculate response amplitude operators (RAO's), power spectral densities, mean/static properties, and response metrics based on mean and root-mean-square values of each output. RAFT serves as the Level 1 model in the WEIS (Wind Energy with Integrated Servo-control) toolkit, and features an OpenMDAO wrapper.

Hall, Matthew↗
DOE OSTI2022

NUMERICAL PREDICTIONS OF MEAN PERFORMANCE AND DYNAMIC BEHAVIOR OF A 10 MWe SCO2 COMPRESSOR WITH TEST DATA VALIDATION

High-fidelity aerodynamic analysis has been demonstrated for mean performance and unsteady dynamics in a sCO2 compressor designed by Hanwha Power Systems Americas for a 10 MWe Concentrating Solar Power plant. Simulations were performed with CRUNCH CFD® software tool that was matured to accurately model near critical real fluid effects in sCO2. Pre-test predictions for mean performance were validated with test data collected later. Performance predictions were accurate and captured sensitivity of the efficiency to inlet temperature of CO2 as well as steep drop-off at high flow rates due to condensation in the inlet throat. Detailed analysis was performed to understand the source of these performance losses at near critical conditions. Unsteady dynamic effects in the compressor at off-design conditions were also identified and quantified. In particular a system wide “condensation surge” condition was detected at high flow coefficients that results in large amplitude pulsations with accompanying mass flow fluctuations at low frequencies and has potential to cause damage in closed loop systems.

hosangadi, ashvin↗
DOE OSTI2021

Aerodynamic effects on outer ash deposition rates in second generation atmospheric pressure oxy-coal combustion systems

Recent measurements in scenarios representative of second generation atmospheric pressure oxy-coal combustion systems have shown a significant increase in ash deposition rates in comparison to combustion in air. However, the causative mechanisms behind this increase have not been well understood. To fill this void, well-characterized experiments including fuel and deposit particle size distributions (PSDs) were coupled with highly resolved numerical simulations to isolate the aerodynamic effects impacting the deposition process such that mechanisms could be hypothesized. Three combustion scenarios (AIR, OXY27, OXY70) spanning a factor of three variation in flue gas volumetric flow rates were simulated and the deposition characteristics (impaction rates, deposit PSD, temperature, residence times, capture rates) tracked/predicted using a customized deposition module. The measured deposit PSD was significantly different from the PSD of the parent fuel indicating significant physio-chemical transformations (coalescence and particle growth in particular) at play. The use of simplistic modeling approaches (swelling parameter variations) to model particle growth led to inaccurate deposit ash PSD and rate predictions. A more satisfactory agreement between the measurements and simulations was obtained when the functional form of the parent fuel PSD (spread parameter) was modified to conform closely to the deposit PSD while still ensuring the fidelity of temperature and velocity predictions. Based on the measured ash compositions, identical capture criteria were employed across all three scenarios. Here this study further supports the theory that the ash deposition rates in these systems are dominated by aerodynamic effects with the ash PSD playing a dominant role.

42 ENGINEERING↗
DOE OSTI2026

Urban Land Surface Effects on Summertime Clouds and Moist Convection in Houston Under Different Synoptic Conditions

Urban landscapes modify cloud formation and convection through complex thermodynamic and aerodynamic processes; however, their influence under different synoptic regimes remains poorly understood. This study investigates the impact of the Houston metropolitan area on summertime cloud cover and convective cell characteristics using a combination of satellite observations, radar data, and high-resolution process-based modeling. We isolate urban effects by comparing model simulations with realistic urban land cover against hypothetical scenarios where all urban areas are replaced by rural vegetation. Results reveal that Houston's land cover consistently enhances cloud fraction and convective activity relative to surrounding rural areas, altered by large-scale meteorological forcing. Under weakly forced conditions, enhanced surface heat flux primarily contributes to driving low-level convergence and vertical ascent, leading to over 8% cloud fraction increase between 2 and 6 km over the city. Under strongly forced conditions, urban influences manifest differently depending on cloud type. For non-convective clouds, the city acts as a barrier that decelerates and lifts moist southerly inflow, increasing low cloud cover over the urban core, while decreasing it downwind the city. For convective clouds, both synoptic ascent and urbanization modulate moisture redistribution and cloud structure, producing modest cloud enhancement over the city and slight suppression over the downwind area. Urbanization exerts small changes in the intensity of the convective cells; however, it significantly decreases their duration and traveling distance. This work highlights the importance of accounting for land surface heterogeneity in modeling clouds and precipitation and demonstrates that urban impacts on clouds are highly regime-dependent.

Liu, Ye [Pacific Northwest National Laboratory (PN↗
DOE OSTI2023

Revisiting Reentry Roll Resonance

Here, this paper revisits the subject of reentry roll resonance, which occurs when the roll rate and pitch frequency become equal in a spinning reentry vehicle. A first-principles model is developed and analyzed numerically and by using a reduced-order pendulum model for the relative phase of the roll and pitch/yaw axes. The results show good qualitative agreement with recent flight data and provide a natural physical interpretation. Based on the model it is suggested that sustained roll resonance depends primarily on the initial phase relationship between the pitch and roll axes, in addition to the vehicle moments of inertia and the vehicle symmetry. Finally the model is used to propose a mechanism for sustained resonance in vehicles spinning about a major axis, a condition previously thought to be forbidden.

33 ADVANCED PROPULSION SYSTEMS↗