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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

CFD Simulations of the IHF 13-Inch Nozzle Flow: 55° Sphere-Cone Model, Manufactured Fences and Gaps

This paper reports computational analyses of tests in a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted using 23.6-cm diameter, 55° sphere-cone models placed in a free jet downstream of the 33.0-cm diameter conical nozzle in the 60-MW Interaction Heating Facility. Some of the sphere-cone models include surface features such as manufactured fences and gaps intended to simulate effects of differential recession, all of which disturb the flow, producing augmented heating locally and downstream. Test calibration data were obtained using slug and Gardon gage stagnation calorimeters, and a sphere-cone calorimeter model with six Gardon heat flux gages and five pressure gages. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested, and comparisons with the experimental measurements. Various issues related to testing are considered: diffuser flow capture, flow characterization based on the calorimeter data, effects of the model surface recession, and prediction of surface quantities for the models with surface features. These simulations take into account nonuniform total enthalpy profiles at the nozzle inlet as well as the expansion waves emanating from the nozzle exit and their effects on the model flowfields.

Arc-jets↗
DOE OSTI2024

Heat transfer through a box beam from an impinging hydrogen flame

An analysis was performed to determine whether a hydrogen jet flame impinging on a tunnel ceiling composed of multiple prestressed steel reinforced concrete box beams could result in permanent damage to the tunnel. The lower layer of the concrete box beam was modeled to determine whether heat reaches the steel reinforcing bars and whether spalling could occur. Heat transfer analysis shows that the temperature remains constant at the location of the steel reinforcing bars after 1.3 minutes of impingement and reaches a maximum of 130°C after 5 minutes. However, assuming a constant impingement for 5 minutes is an over estimation due the existing fire model which includes conservative assumptions. Explosive spalling may occur at a thin layer (~0.05 in. at 50 seconds, 0.1 in. at 5 minutes) at the bottom surface of the concrete box beam, but the steel reinforcing bars will not be exposed to the hydrogen flame.

42 ENGINEERING↗
DOE OSTI2020

Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms

Here in this work we present a non-intrusive model reduction method to learn low-dimensional models of dynamical systems with non-polynomial nonlinear terms that are spatially local and that are given in analytic form. In contrast to state-of-the-art model reduction methods that are intrusive and thus require full knowledge of the governing equations and the operators of a full model of the discretized dynamical system, the proposed approach requires only the non-polynomial terms in analytic form and learns the rest of the dynamics from snapshots computed with a potentially black-box full-model solver. The proposed method learns operators for the linear and polynomially nonlinear dynamics via a least-squares problem, where the given non-polynomial terms are incorporated on the right-hand side. The least-squares problem is linear and thus can be solved efficiently in practice. The proposed method is demonstrated on three problems governed by partial differential equations, namely the diffusion–reaction Chafee–Infante model, a tubular reactor model for reactive flows, and a batch-chromatography model that describes a chemical separation process. The numerical results provide evidence that the proposed approach learns reduced models that achieve comparable accuracy as models constructed with state-of-the-art intrusive model reduction methods that require full knowledge of the governing equations.

42 ENGINEERING↗
DOE OSTI2016

Data-driven operator inference for nonintrusive projection-based model reduction

We presenta a nonintrusive projection-based model reduction method for full models based on time-dependent partial differential equations. Projection-based model reduction constructs the operators of a reduced model by projecting the equations of the full model onto a reduced space. Traditionally, this projection is intrusive, which means that the full-model operators are required either explicitly in an assembled form or implicitly through a routine that returns the action of the operators on a given vector; however, in many situations the full model is given as a black box that computes trajectories of the full-model states and outputs for given initial conditions and inputs, but does not provide the full-model operators. Our nonintrusive operator inference approach infers approximations of the reduced operators from the initial conditions, inputs, trajectories of the states, and outputs of the full model, without requiring the full-model operators. Our operator inference is applicable to full models that are linear in the state or have a low-order polynomial nonlinear term. The inferred operators are the solution of a least-squares problem and converge, with sufficient state trajectory data, in the Frobenius norm to the reduced operators that would be obtained via an intrusive projection of the full-model operators. Our numerical results reflect operator inference on a linear climate model and on a tubular reactor model with a polynomial nonlinear term of third order.

42 ENGINEERING↗
NASA NTRS2008

Numerical Characterization of a Composite Bonded Wing-Box

The development of composite wing structures has focused on the use of mechanical fasteners to join heavily-loaded areas, while bonded joints have been used only for select locations. The focus of this paper is the examination of the adhesive layer in a generic bonded wing box that represents a "fastenerless" or unitized structure in order to characterize the general behavior and failure mechanisms. A global/local approach was applied to study the response of the adhesive layer using a global shell model and a local shell/solid model. The wing box was analyzed under load to represent a high-g up-bending condition such that the strains in the composite sandwich face sheets are comparable to an expected design allowable. The global/local analysis indicates that at these wing load levels the strains in the adhesive layer are well within the adhesive's elastic region, such that yielding would not be expected in the adhesive layer. The global/local methodology appears to be a promising approach to evaluate the structural integrity of the adhesively bonded structures.

Smeltzer, Stanley S., III↗
DOE OSTI2023

Test and Evaluation of Systems with Embedded Machine Learning Components

As Machine Learning (ML) continues to advance, it is being integrated into more systems. Often, the ML component represents a significant portion of the system that reduces the burden on the end user or significantly improves task performance. However, the ML component represents an unknown complex phenomenon that is learned from collected data without the need to be explicitly programmed. Despite the improvement in task performance, the models are often black boxes. Evaluating the credibility and the vulnerabilities of ML models poses a gap in current test and evaluation practice. For high consequence applications, the lack of testing and evaluation procedures represents a significant source of uncertainty and risk. To help reduce that risk, here we present considerations to evaluate systems embedded with an ML component within a red-teaming inspired methodology. We focus on (1) cyber vulnerabilities to an ML model, (2) evaluating performance gaps, and (3) adversarial ML vulnerabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Irradiation Testing of a SiC/SiC Channel Box in the High Flux Isotope Reactor

This report provides a summary of the experiment design and the neutronics and structural analyses of a miniature SiC/SiC channel box that will be irradiated in the High Flux Isotope Reactor (HFIR). The goal of this experiment is to evaluate the lateral bowing in the channel box during irradiation under a radial neutron flux gradient. The concern is that lateral bowing could potentially block coolant flow or interfere with control blade movements in boiling water reactors (BWRs). The experiments described in this work will help validate thermomechanical models of channel box bowing. The experiment design allows for one channel box specimen to be irradiated in the HFIR while being directly cooled by the reactor coolant. Monte Carlo neutronics analyses are performed to determine the three-dimensional profile of the dose rate in the channel box. Dose is then converted to volumetric swelling, using literature data, and the resulting swelling profile is used as an input to structural finite element calculations that predict lateral bowing.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗
DOE OSTI2023

An Electromagnetic Transient and Three-Phase Phasor Co-Simulation Platform for Studying Distribution System Transients with High Pentration of DERs

Inverter vendors usually have electro-magnetic transient (EMT) models of distributed energy resources (DERs) for validation purposes and these types of models are usually black-boxed considering intellectual property (IP) protection. Limited by small simulation time step for the entire power system network, studying the system-level responses of DERs in EMT simulators is more time-consuming as the network size increases. Meanwhile, vendors usually do not have inverter models that can be used in three-phase phasor-domain simulators. This paper proposes a platform that can dynamically co-simulate the EMT inverter models and three-phase phasor-domain distribution networks considering high penetration of inverter-based DERs. This platform is very useful for evaluating the impacts of vendor-provided black-box DER model on distribution system dynamics. The co-simulation platform is validated against the full EMT model using a simple two-inverter test system and tested using IEEE 34-node test feeder.

Liu, Yuan↗
NASA NTRS2017

Filter Tuning Using the Chi-Squared Statistic

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) performs orbit determination (OD) for the Aqua and Aura satellites. Both satellites are located in low Earth orbit (LEO), and are part of what is considered the A-Train satellite constellation. Both spacecraft are currently in the science phase of their respective missions. The FDF has recently been tasked with delivering definitive covariance for each satellite.The main source of orbit determination used for these missions is the Orbit Determination Toolkit developed by Analytical Graphics Inc. (AGI). This software uses an Extended Kalman Filter (EKF) to estimate the states of both spacecraft. The filter incorporates force modelling, ground station and space network measurements to determine spacecraft states. It also generates a covariance at each measurement. This covariance can be useful for evaluating the overall performance of the tracking data measurements and the filter itself. An accurate covariance is also useful for covariance propagation which is utilized in collision avoidance operations. It is also valuable when attempting to determine if the current orbital solution will meet mission requirements in the future.This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The Chi-square statistic is calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance.For the EKF to correctly calculate the covariance, error models associated with tracking data measurements must be accurately tuned. Over estimating or under estimating these error values can have detrimental effects on the overall filter performance. The filter incorporates ground station measurements, which can be tuned based on the accuracy of the individual ground stations. It also includes measurements from the NASA space network (SN), which can be affected by the assumed accuracy of the TDRS satellite state at the time of the measurement.The force modelling in the EKF is also an important factor that affects the propagation accuracy and covariance sizing. The dominant force in the LEO orbit regime is the drag force caused by atmospheric drag. Accurate accounting of the drag force is especially important for the accuracy of the propagated state. The implementation of a box and wing model to improve drag estimation accuracy, and its overall effect on the covariance state is explored.The process of tuning the EKF for Aqua and Aura support is described, including examination of the measurement errors of available observation types (Doppler and range), and methods of dealing with potentially volatile atmospheric drag modeling. Predictive accuracy and the distribution of the Chi-square statistic, calculated based of the ODTK EKF solutions, are assessed versus accepted norms for the orbit regime.

Covariance Analysis↗
NASA NTRS1991

A comparison of classical mechanics models and finite element simulation of elastically tailored wing boxes

Structural tailoring concepts were developed to create wings with elastically produced camber for the purpose of increasing lift during takeoff conditions. Simple models based upon enhancements to the thin walled composite beam theory of Rehfield were developed to investigate prospects for elastic tailoring of the chordwise deformation of wing structures. The purpose here is to provide a comparison of the theoretical results with a finite element model for the bending method of producing camber. Finite element correlation studies were completed for two cases: a bonded unstiffened structural box, and a bolted unstiffened structural box. Results from these studies show an error of less than one percent for the bonded case and less than six percent for the bolted case in predicting camber curvature for the structural box. Examination of the results shows that the theory is very accurate for the cases studied and will provide an excellent basis for conducting further tailoring studies.

Rehfield, Lawrence W.↗
NASA NTRS2015

Computational Simulations of the 10-MW TP3 Arc-Jet Facility Flow

This paper reports computational simulations and analysis in support of calibration tests in a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted using stagnation calorimeters and two different blunted wedge models with calibration plates at a wide range of conditions in the NASA Ames 10-megawatt TP3 (Test Position 3) facility. Data were obtained using four different conical nozzles with the same test configuration in which the models were placed in a free jet downstream of the nozzle. Experimental surveys of arc-jet test flow with pitot and null-point heat flux probes were also performed at several arc-heater conditions, providing assessment of the flow uniformity and valuable data for the flow characterization. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested, and comparisons with the experimental measurements. These computational simulations provide estimates of the arc-jet test environment parameters that are not measured but are needed to evaluate the performance of thermal protection system materials, along with further valuable insights into the arc-jet testing environment. Simulation results are used to estimate centerline total enthalpy, surface shear, boundary layer thickness, and boundary layer edge Mach number and to verify that specific test requirements from the Orion program are met.

CFD↗
DOE OSTI2018

Marine Corps Base Camp Lejeune New River Estuary (NRE) Regions

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.The New River Estuary regions were digitized using desktop GIS and elevation data to determine the watershed boundaries and bathymetry data is determined by the water depth. Geographic representation of box and flow model produced by DCERP aquatic & esturaine module team, includes micro-watershed data. A spatial approximation of the areas defined in the Estuarine Simulation Model developed by Mark Brush.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Quantifying parameters for Bayesian prior assumptions when estimating the probability of failure of software

Software reliability has become increasingly important, especially in life-critical situations. The ability to measure the results of testing and to quantify software reliability is needed. If this is accomplished, a certain minimum amount of reliability for a piece of software can be specified, and testing and/or other analysis may be done until that minimum number has been attained. There are many models for estimating software reliability. The accuracy of these models has been challenged and many revisions for the models and recalibration techniques have been devised. Of particular interest is the method of estimating the probability of failure of software when no failures have yet occurred in its current version as described by Miller. This model uses black box testing with formulae based on Bayesian estimation. The focus is on three interrelated issues: estimating the probability of failure when testing has revealed no errors; modifying this estimation when the input use distribution does not match the test distribution; and combining the results from random testing with other relevant information to obtain a possibly more accurate estimate of the probability of failure. Obtaining relevant information about the software and combining the results for a better estimate for the Miller model are discussed.

Long, Jacquelyn E.↗
NASA NTRS2019

CFD Simulations of the IHF Arc-Jet Flow: 9-Inch Nozzle, Flow Surveys, LEAF Wedge Calibration Data

This paper reports computational analyses and flow characterization studies in a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted using a wedge model placed in a free jet downstream of new 9-inch diameter conical nozzle in the Ames 60-MW Interaction Heating Facility. Both the nozzle and wedge model were specifically designed for testing in the new Laser-Enhanced Arc-jet Facility. Data were obtained using stagnation calorimeters and wedge models placed downstream of the nozzle exit. Two instrumented wedge calibration plates were used: one water-cooled and the other RCG-coated tile plate. Experimental surveys of arc-jet test flow with pitot and heat flux probes were also performed at three arc-heater conditions, providing assessment of the flow uniformity and valuable data for the flow characterization. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested, and comparisons with the experimental measurements. By taking into account nonuniform total enthalpy and mass flux profiles at the nozzle inlet as well as the expansion waves emanating from the nozzle exit and their effects on the model flowfields, these simulations approximately reproduce the probe survey data and predict the wedge model surface pressure and heat flux measurements.

Arc-jets↗
NASA NTRS2019

Utilization of Airborne Observations to Assess Model Parametrizations of Critical RH Profiles in the Arctic Ocean

Observational paucity is a reality in the Arctic Ocean. This is especially true for near-surface variables such as temperature, moisture, heat fluxes and BL clouds. As a result, modeling has become one of the major avenues for understanding current and future Arctic trends. Reanalyses are frequently used to force global ocean circulation and sea-ice models. But in northern high latitudes, model integrations and reanalyses are known to have large uncertainties in temperature and humidity profiles, and in boundary layer cloudiness. These are common sources of error in the surface radiative budget terms.An important way to diagnose these biases spatially and temporally is by using satellite remote sensing data. However, remotely-sensed observations also have large uncertainties, especially in near-surface temperature and relative humidity profiles.In situ observational studies are important in bridging our knowledge gap in regions such as the Arctic Ocean. Here, we utilize airborne and ship observations from the ARISE, ACME-IV, and ASCOS campaigns to construct critical relative humidity (RH) profiles over the Beaufort Sea. Such profiles are used as parameterization inputs in the NASA GOES global model to derive the total water condensate in a model grid-box, which determines the cloud fraction. Currently, the critical RH profiles are derived by global AIRS data, relaying mostly on mid-latitude regions, which are not necessarily relevant to the Arctic.We derive campaign-wide mean, standard deviation, and critical RH values, for grid size of 50x50 km and altitude bins between 50 to 400 m, covering both open-ocean and sea-ice covered regions. We compare profiles over open ocean and sea-ice, and look at correlations between the observed critical RH values and water condensate (by cloud number concentration) from observations versus the modeled ones. We then input our calculated values of minimal critical RH values into a set of GEOS single column model (SCM) simulations over the ARISE and ASCOS regions and compare the differences between the predicted values of cloud liquid water path (LWP), ice water path (IWP) and surface fluxes with the observed ones under the range of input parameterizations. Finally, we discuss the implications on surface radiative budget predictions in this region.

Segal-Rozenhaimer, Michal↗
NASA NTRS1999

Stochastic Modeling of Airlines' Scheduled Services Revenue

Airlines' revenue generated from scheduled services account for the major share in the total revenue. As such, predicting airlines' total scheduled services revenue is of great importance both to the governments (in case of national airlines) and private airlines. This importance stems from the need to formulate future airline strategic management policies, determine government subsidy levels, and formulate governmental air transportation policies. The prediction of the airlines' total scheduled services revenue is dealt with in this paper. Four key components of airline's scheduled services are considered. These include revenues generated from passenger, cargo, mail, and excess baggage. By addressing the revenue generated from each schedule service separately, air transportation planners and designers are able to enhance their ability to formulate specific strategies for each component. Estimation results clearly indicate that the four stochastic processes (scheduled services components) are represented by different Box-Jenkins ARIMA models. The results demonstrate the appropriateness of the developed models and their ability to provide air transportation planners with future information vital to the planning and design processes.

Hamed, M. M.↗
NASA NTRS1999

Stochastic Modeling of Airlines' Scheduled Services Revenue

Airlines' revenue generated from scheduled services account for the major share in the total revenue. As such, predicting airlines' total scheduled services revenue is of great importance both to the governments (in case of national airlines) and private airlines. This importance stems from the need to formulate future airline strategic management policies, determine government subsidy levels, and formulate governmental air transportation policies. The prediction of the airlines' total scheduled services revenue is dealt with in this paper. Four key components of airline's scheduled services are considered. These include revenues generated from passenger, cargo, mail, and excess baggage. By addressing the revenue generated from each schedule service separately, air transportation planners and designers arc able to enhance their ability to formulate specific strategies for each component. Estimation results clearly indicate that the four stochastic processes (scheduled services components) are represented by different Box-Jenkins ARIMA models. The results demonstrate the appropriateness of the developed models and their ability to provide air transportation planners with future information vital to the planning and design processes.

Hamed, M. M.↗