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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Aftbody Closure Model Design: Lessons Learned

An Aftbody Closure Test Program is necessary in order to provide aftbody drag increments that can be added to the drag polars produced by testing the performance models (models 2a and 2b). These models had a truncated fuselage, thus, drag was measured for an incomplete configuration. In addition, trim characteristics cannot be determined with a model with a truncated fuselage. The stability and control tests were conducted with a model (model 20) having a flared aftbody. This type aftbody was needed in order to provide additional clearance between the base of the model and the sting. This was necessary because the high loads imposed on the model for stability and control tests result in large model deflections. For this case, the aftbody model will be used to validate stability and control performance.

Capone, Francis J.↗
DOE OSTI2019

Mathematical Modeling of Fracture Processes in Plates with Systems of Cracks Under the Action of Long-Term Loads, High Temperatures, and Corrosive Media

We formulate mathematical models for the evaluation of the lifetime of plates with systems of cracks under the action of long-term force loads in the presence of high temperatures and corrosive media. These models are based on the use of the well-known main mechanisms of propagation of creep cracks, corrosion fracture, and the first law of thermodynamics (balance of energy components and rates of their changes) for a metal plate containing a system of macrocracks and subjected to the action of long-term tension and corrosive media at high temperatures. We consider the case of a double-periodic system of cracks.

42 ENGINEERING↗
DOE OSTI2025

Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials

Predicting mechanical responses of heterogeneous materials across scales remains a significant challenge. Traditional computational methods often struggle with complex and multiscale nature of these materials, limiting their effectiveness in real-world applications. Here, in this paper, we introduce Micrometer, a vision transformer based deep learning model designed to predict full field mechanical responses of heterogeneous materials, bridging the gap between computer vision and solid mechanics problems. We show that Micrometer, trained on a large-scale high-resolution dataset of 2D fiber-reinforced composites, can achieve state-of-the-art performance in predicting microscale strain fields across a wide range of material properties and loading conditions. Our model demonstrates accuracy and computational efficiency in applications such as computational homogenization and multiscale modeling, reducing computational time by up to two orders of magnitude compared to conventional numerical solvers while maintaining less than 1 % errors in predicting macroscale stress fields. Furthermore, we showcase Micrometer’s adaptability through transfer learning experiments on new materials with limited data, highlighting its potential to tackle diverse scenarios in computational solid mechanics. These results represent a significant step towards AI-driven innovation in materials science, addressing the limitations of traditional numerical methods and paving the way for more efficient simulations of heterogeneous materials across various industrial applications.

Composite materials↗
DOE OSTI2025

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads in extreme idling conditions

Abstract. Floating offshore wind turbine (FOWT) systems are subject to complex environmental loads, with significant potential for damage in extreme storm conditions. Design simulations in these conditions are required to assess the survivability of the device with some level of confidence. Aero-hydro-servo-elastic engineering tools can be used with a reasonable balance of accuracy and computational efficiency. The models require many input parameters to describe the air and water conditions, the system properties, and the load calculations. Each of these parameters has some possible range, due to either statistical uncertainty or variations with time. Variation in the input parameters can have important effects on the uncertainty in the resulting loads, but it is not practical to perform detailed assessments of the impact of this uncertainty for every input parameter. This work demonstrates a method to identify the input parameters that have the most impact on the loads to focus further inspection. The process is done specifically for extreme storm load cases defined in the International Electrotechnical Commission design requirements for floating offshore wind turbines. The analysis was performed using the International Energy Agency Wind 15 MW offshore reference wind turbine atop the University of Maine VolturnUS-S reference platform in two US offshore wind regions, the Gulf of Maine and Humboldt Bay. It was found that the direction of incident waves and current, yaw misalignment, and the length of mooring line sections were among the primary sensitivities.

17 WIND ENERGY↗
NASA NTRS2010

Cruise-Efficient Short Takeoff and Landing (CESTOL): Potential Impact on Air Traffic Operations

The National Aeronautics and Space Administration (NASA) is investigating technological and operational concepts for introducing Cruise-Efficient Short Takeoff and Landing (CESTOL) aircraft into a future US National Airspace System (NAS) civil aviation environment. CESTOL is an aircraft design concept for future use to increase capacity and reduce emissions. CESTOL provides very flexible takeoff, climb, descent and landing performance capabilities and a high-speed cruise capability. In support of NASA, this study is a preliminary examination of the potential operational impact of CESTOL on airport and airspace capacity and delay. The study examines operational impacts at a subject site, Newark Liberty Intemational Airport (KEWR), New Jersey. The study extends these KEWR results to estimate potential impacts on NAS-wide network traffic operations due to the introduction of CESTOL at selected major airports. These are the 34 domestic airports identified in the Federal Aviation Administration's Operational Evolution Plan (OEP). The analysis process uses two fast-time simulation tools to separately model local and NAS-wide air traffic operations using predicted flight schedules for a 24-hour study period in 2016. These tools are the Sen sis AvTerminal model and NASA's Airspace Concept Evaluation System (ACES). We use both to simulate conventional-aircraft-only and CESTOL-mixed-with-conventional-aircraft operations. Both tools apply 4-dimension trajectory modeling to simulate individual flight movement. The study applies AvTerminal to model traffic operations and procedures for en route and terminal arrival and departures to and from KEWR. These AvTerminal applications model existing arrival and departure routes and profiles and runway use configurations, with the assumption jet-powered, large-sized civil CESTOL aircraft use a short runway and standard turboprop arrival and departure procedures. With these rules, the conventional jet and CESTOL aircraft are procedurally separated from each other geographically and in altitude during tenninal airspace approach and departure operations, and each use a different arrival runway. AvTeminal implements its unique Focal-point Scheduling Process to sequence, space and delay aircraft to resolve spacing and overtake conflicts among flights in the airspace and airport system serving KEWR. This Process effectively models integrated arrival and departure operations. AvTerminal assesses acceptance rates and delay magnitude and causality at selected locations, including en route outer boundary fixes, tenninal airspace arrival and departure boundary fixes, terminal airspace arrival merge and departure diverge fixes, and runway landing and takeoff runways. The analysis compares the resulting capacity impacts, flight delays and delay sources between CESTOL and conventional KEWR operations. AvTerminal quantitative results showed that CESTOL has significant capability to increase airport arrival acceptance rates (35-40% at KEWR) by taking advantage of otherwise underused airspace and runways where available. The study extrapolates the AvTerminal-derived KEWR peak arrival and departure acceptance rates to estimate capacity parameter values for each of the OEP airports in the ACES modeling of traffic through the entire NAS network. The extrapolations of acceptance rates allow full, partial or no achievement of CESTOL capacity gains at an OEP airport as determined by assessments of the degree to which local procedures allow leveraging of CESTOL capabilities. These assessments consider each OEP airport's runway geometries, runway system configurations, airport and airspace operations, and potential CESTOL traffic loadings. The ACES modeling, simulates airport and airspace spacing constraints imposed by airport runway system, terminal and en route air traffic control and traffic flow management operations using airport acceptance rates representing conventional-aircraft-only and CESTOL-mixed operations. CEOL aircraft are assumed to have Mach 0.8, and alternatively Mach 0.7, cruise speeds to examine compatibility with conventional aircraft operations in common airspace. The ACES results provides estimates of CESTOL delay impact NAS-wide and at OEP airports due to changes in OEP airport acceptance rates and changes in en route airspace potential conflict rates. Preliminary results show meaningful nationwide delay reductions (20%) due to CESTOL operations at 34 major domestic airports.

Couluris, G. J.↗
NASA NTRSDate not supplied

Single and Multi-Node Modeling of Direct, Submerged, and Self-Pressurization of A Cryogenic Propellant Tank Using Nodal Tools

The pressurization of cryogenic propellant tanks will always be an important process so long as cryogenic liquids are being considered as fuel sources or used for other in-space applications. Pressure control of the tank ullage is necessary for managing propellant flowrates to an engine or a receiver tank, and modeling of the process is used to predict the pressurant requirements and the amount of propellant boiloff. Direct ullage pressurization is the more traditional approach to tank pressurization, as the physics are straight-forward, and ample test (flight) data have been collected and analyzed over the past several decades. Submerged injection pressurization is an alternate method for tank pressurization and has been shown to reduce pressurant requirements, subcool the propellant, and reduce the risk of ullage collapse. Additionally, the pressurant gas entering the ullage is usually much colder when using the submerged pressurization approach, resulting in reduced propellant boiloff. These benefits are at the expense of vaporizing a small percentage of the propellent. Both tank pressurization methods are viable options for current and future space missions, and it is important to have the capability of analyzing the tank ullage conditions for both approaches. Our previous work has demonstrated the development of a Generalized Fluid System Simulation Program (GFSSP) model, which contains a thermodynamic equilibrium heat and mass transfer subroutine capable of effectively analyzing both direct and submerged pressurization systems [1-2]. This subroutine has most recently been enhanced to include the non-equilibrium effect of pressurant dissolution into the propellant. To date the ullage has always been represented as a single node, and although the simulated single-node temperatures have good comparison with the volume-averaged ullage temperatures computed from test data, the physics of the thermal stratification in the ullage were never captured, and adjustment factors in the model were required. The purpose of this paper is to introduce the development of a multi-node ullage model using GFSSP and to discuss the improvements of the simulated ullage temperature distribution and its resulting effects on ullage heat transfer processes. Test data from the Cryogenic Propellant Storage and Transfer Engineering Developmental Unit (CPST EDU) was used for model validation. For additional comparison, a Thermal Desktop (TD) model was also developed to analyze the CPST EDU direct ullage pressurization tests using both a single node and multi-node approach. The model includes the direct pressurant line, vent line, fill/drain line, and a TD FloCAD Compartment. The TD FloCAD Compartment is employed to represent the liquid and ullage as single volumes inside the tank, to include a liquid/vapor interface, and to generate network level objects such as lumps (analogous to nodes in GFSSP), paths, and ties between the fluid and thermal elements. An established heat load on the model tank was leveraged from a pre-existing higher-fidelity model correlated to CPST EDU test data.

pressurization↗
NASA NTRS1986

Anisotropic constitutive model for nickel base single crystal alloys: Development and finite element implementation

A tool for the mechanical analysis of nickel base single crystal superalloys, specifically Rene N4, used in gas turbine engine components is developed. This is achieved by a rate dependent anisotropic constitutive model implemented in a nonlinear three dimensional finite element code. The constitutive model is developed from metallurigical concepts utilizing a crystallographic approach. A non Schmid's law formulation is used to model the tension/compression asymmetry and orientation dependence in octahedral slip. Schmid's law is a good approximation to the inelastic response of the material in cube slip. The constitutive equations model the tensile behavior, creep response, and strain rate sensitivity of these alloys. Methods for deriving the material constants from standard tests are presented. The finite element implementation utilizes an initial strain method and twenty noded isoparametric solid elements. The ability to model piecewise linear load histories is included in the finite element code. The constitutive equations are accurately and economically integrated using a second order Adams-Moulton predictor-corrector method with a dynamic time incrementing procedure. Computed results from the finite element code are compared with experimental data for tensile, creep and cyclic tests at 760 deg C. The strain rate sensitivity and stress relaxation capabilities of the model are evaluated.

Dame, L. T.↗
NASA NTRS1984

A system-level mathematical model for evaluation of power train performance of load-leveled electric-vehicles

The power train performance of load leveled electric vehicles can be compared with that of nonload leveled systems by use of a simple mathematical model. This method of measurement involves a number of parameters including the degree of load leveling and regeneration, the flywheel mechanical to electrical energy fraction, and efficiencies of the motor, generator, flywheel, and transmission. Basic efficiency terms are defined and representative comparisons of a variety of systems are presented. Results of the study indicate that mechanical transfer of energy into and out of the flywheel is more advantageous than electrical transfer. An optimum degree of load leveling may be achieved in terms of the driving cycle, battery characteristics, mode of mechanization, and the efficiency of the components. For state of the art mechanically coupled flyheel systems, load leveling losses can be held to a reasonable 10%; electrically coupled systems can have losses that are up to six times larger. Propulsion system efficiencies for mechanically coupled flywheel systems are predicted to be approximately the 60% achieved on conventional nonload leveled systems.

Purohit, G. P.↗
NASA NTRS1973

Results of tests OA12 and IA9 in the Ames Research Center unitary plan wind tunnels on an 0.030-scale model of the space shuttle vehicle 2A to determine aerodynamic loads, volume 2

Tests were conducted in Unitary Plan wind tunnels on a 0.30 scale model of the space shuttle. Tests were conducted on the integrated configuration and on the isolated orbiter. The integrated vehicle was tested at angles of attack and sideslip from minus 8 degrees to plus 8 degrees. The isolated orbiter was tested at angles of attack from minus 15 degrees to plus 40 degrees and angles of sideslip from minus 10 degrees to plus 10 degrees as dictated by trajectory considerations. The effects of orbiter/external tank incidence angle and deflected control surfaces on aerodynamic loads were investigated.

Spangler, R. H.↗
DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗
NASA NTRS1977

Strain gage calibration of a complex wing

Modern complex structural arrangements have complicated the task of measuring flight loads with calibrated strain gages. This paper examines the use of a relatively simple structural model to characterize the load responses of strain gages located on various spars of a delta wing. Strains measured during a laboratory load calibration of a wing structure are compared with calculations obtained from a simplified NASA structural analysis (NASTRAN) model. Calculated and measured influence coefficient plots that show the shear, bending, and torsion characteristics of typical strain-gage bridges are presented. Typical influence coefficient plots are given for several load equations to illustrate the derivation of the equations from the component strain-gage bridges. A relatively simple structural model was found to be effective in predicting the general nature of strain distributions and influence coefficient plots. The analytical processes are shown to be useful in obtaining a good load calibration. The analytical processes cannot, however, be used in lieu of an actual load calibration of an aircraft wing.

Jenkins, J. M.↗
DOE OSTI2015

Elimination of metabolic pathways to all traditional fermentation products increases ethanol yields in Clostridium thermocellum

Clostridium thermocellum has the natural ability to convert cellulose to ethanol, making it a promising candidate for consolidated bioprocessing (CBP) of cellulosic biomass to biofuels. To further improve its CBP capabilities, we study a mutant strain of C. thermocellum that was constructed (strain AG553; C. thermocellum Δhpt ΔhydG Δldh Δpfl Δpta-ack ) to increase flux to ethanol by removing side product formation. Strain AG553 showed a two- to threefold increase in ethanol yield relative to the wild type on all substrates tested. On defined medium, strain AG553 exceeded 70% of theoretical ethanol yield on lower loadings of the model crystalline cellulose Avicel, effectively eliminating formate, acetate, and lactate production and reducing H 2 production by fivefold. On 5 g/L Avicel, strain AG553 reached an ethanol yield of 63.5% of the theoretical maximum compared with 19.9% by the wild type, and it showed similar yields on pretreated switchgrass and poplar. The elimination of organic acid production suggested that the strain might be capable of growth under higher substrate loadings in the absence of pH control. Final ethanol titer peaked at 73.4 mM in mutant AG553 on 20 g/L Avicel, at which point the pH decreased to a level that does not allow growth of C. thermocellum , likely due to CO 2 accumulation. In comparison, the maximum titer of wild type C. thermocellum was 14.1 mM ethanol on 10 g/L Avicel. In conclusion, with the elimination of the metabolic pathways to all traditional fermentation products other than ethanol, AG553 is the best ethanol-yielding CBP strain to date and will serve as a platform strain for further metabolic engineering for the bioconversion of lignocellulosic biomass.

09 BIOMASS FUELS↗
NASA NTRS1991

Quasi-linear pitch angle and energy diffusion of pickup ions near Comet Halley

The process of ion pickup in the environment of Halley's comet is studied in order to see if velocity diffusion driven by the observed level of turbulence can explain the observed development of the implanted ion distribution. The theoretical description used is based on a quasi-linear approach and considers the implantation and transport of cometary ions along solar wind flow lines. To make such a study requires some way of extrapolating the measurements on the Giotto trajectory into the upstream region; models for mass loading and turbulence are used. A simplified kinetic equation describing the source, convection, and quasi-linear velocity diffusion of the heavy cometary ions is solved numerically along flow lines parallel to the sun-comet line. Full two-dimensional (pitch angle and velocity) distributions are obtained at positions along the Giotto trajectory, which are compared with measurements. This study finds that quasi-linear theory, with the empirical model for the observed turbulence level, produces the right order of pitch angle diffusion.

Huddleston, D. E.↗
DOE OSTI2015

Three-Stage Production Cost Modeling Approach for Evaluating the Benefits of Intra-Hour Scheduling Between Balancing Authorities

This paper introduces a production cost modeling approach for evaluating the benefits of intra-hour scheduling among Balancing Authorities (BAs). System operation is modeled in a three-stage sequential manner: day ahead (DA)-hour ahead (HA) real time (RT). In addition to contingency reserve, each BA will need to carry out 'up' and 'down' load following and regulation reserve capacity requirements in the DA and HA time frames. In the RT simulation, only contingency and regulation reserves are carried out as load following is deployed. To model current RT operation with hourly schedules, a new constraint was introduced to force each BA net exchange schedule deviation from HA schedules to be within North American Electric Reliability Corporation (NERC) area control error (ACE) limits. Case studies that investigate the benefits of moving from hourly exchange schedules between Western Electricity Coordinating Council (WECC) BAs into 10-minute exchange schedules under two different levels of wind and solar penetration (11% and 33%) are presented.

17 WIND ENERGY↗
DOE OSTI2025

Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency

Prompt and effective corrective actions in response to unexpected contingencies are crucial for improving power system resilience and preventing cascading blackouts. The optimal load shedding (OLS) accounting for network limits has the potential to address the diverse system-wide impacts of contingency scenarios as compared to traditional local schemes. However, due to the fast cascading propagation of initial contingencies, real-time OLS solutions are challenging to attain in large systems with high computation and communication needs. In this paper, we propose a decentralized design that leverages offline training of a neural network (NN) model for individual load centers to autonomously construct the OLS solutions from locally available measurements. Our learning-for-OLS approach can greatly reduce the computation and communication needs during online emergency responses, thus preventing the cascading propagation of contingencies for enhanced power grid resilience. Numerical studies on both the IEEE 118-bus system and a synthetic Texas 2000-bus system have demonstrated the efficiency and effectiveness of our scalable OLS learning design for timely power system emergency operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Optimal Load Ensemble Control in Chance-Constrained Optimal Power Flow

Distribution system operators (DSOs) world-wide foresee a rapid roll-out of distributed energy resources. From the system perspective, their reliable and cost effective integration requires accounting for their physical properties in operating tools used by the DSO. This work describes an decomposable approach to leverage the dispatch flexibility of thermostatically controlled loads (TCLs) for operating distribution systems with a high penetration level of photovoltaic resources. Each TCL ensemble is modeled using the Markov Decision Process (MDP). The MDP model is then integrated with a chance constrained optimal power flow that accounts for the uncertainty of PV resources. Since the integrated optimization model cannot be solved efficiently by existing dynamic programming methods or off-the-shelf solvers, this paper proposes an iterative Spatio-Temporal Dual Decomposition algorithm (ST-D2). Finally, we demonstrate the merits of the proposed integrated optimization and ST-D2 algorithm on the IEEE 33-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Green's Function Wind Turbine Induction Model That Incorporates Complex Inflow Conditions

ABSTRACT In this work, we develop a new analytical turbine induction model that can incorporate complex inflow conditions including cases where the wind velocity and temperature profiles can vary as functions of height. This induction model is derived from the linearized Navier–Stokes and leads to a second‐order ODE that can be solved using a Green's function formulation. The corresponding Green's function for several configurations are found including the infinite domain, semi‐infinite domain with ground plane, and a power law velocity inflow profile. The results of this approach are then compared with simulations of the turbine induction field using the AMR‐Wind CFD solver with a uniformly loaded actuator disk model. These comparisons show that the Green's function approach captures the centerline blockage, three‐dimensional blockage flow field, and streamwise velocity slow down, with very good agreement for lower thrust conditions and at larger distances away from rotor disk. The effects of shear on the turbine blockage were also compared using a power law inflow profile, and we show that this approach matches the CFD predictions for the cases considered.

17 WIND ENERGY↗
DOE OSTI2021

Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters

Bayesian inference is used to calibrate a bottom-up home PLC network model with unknown loads and wires at frequencies up to 30 MHz. A network topology with over 50 parameters is calibrated using global sensitivity analysis and transitional Markov Chain Monte Carlo (TMCMC). The sensitivity-informed Bayesian inference computes Sobol indices for each network parameter and applies TMCMC to calibrate the most sensitive parameters for a given network topology. A greedy random search with TMCMC is used to refine the discrete random variables of the network. This results in a model that can accurately compute the transfer function despite noisy training data and a high dimensional parameter space. The model is able to infer some parameters of the network used to produce the training data, and accurately computes the transfer function under extrapolative scenarios.

42 ENGINEERING↗