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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine learning based simultaneous control of air handling unit discharge air and condenser water temperatures set-point for minimized cooling energy in an office building

In this study, an artificial intelligence based real-time prediction and control model to optimize condenser water temperature and discharge air temperature (DAT) set-points in water-cooled air handling unit (AHU) system has been developed. EnergyPlus-MATLAB co-simulation has been conducted to analyze the developed model's effectiveness. Here, to develop artificial neural networks (ANN) model, embedded neural network objects in MATLAB was utilized. The developed model could decide an optimal temperature set-points based on outdoor air wet-bulb temperature to reflect the Korean climate context. As a result, the developed ANN prediction model showed the predictive performance of Cv(RMSE) of approximately 21%. Compared to the conventional fixed temperature algorithm, which fixes AHU DAT at 14°C and condenser water temperature at 32°C, the ANN based optimized control showed a 22% total cooling energy reduction. These results show that significant energy savings can be achieved by simultaneously controlling condenser water temperature and AHU DAT set-points considering Korean climatic characteristics using AI technologies such as ANN models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Large eddy simulation of a reacting spray flame with multiple realizations under compression ignition engine conditions

An n-dodecane spray flame (Spray A from Engine Combustion Network) was simulated using a detailed combustion model along with a dynamic structure LES model to evaluate its performance at engine-relevant conditions and understand the transient behavior of this turbulent flame. The liquid spray was treated with a traditional Lagrangian method and the gas-phase reaction was modeled using a detailed combustion model. A 103-species skeletal mechanism was used for the n-dodecane chemical kinetic model. Significantly different flame structures and ignition processes are observed for the LES compared to those of RANS predictions. The LES data suggests that the first ignition initiates in lean mixture and propagates to rich mixture, and the main ignition happens in rich mixture, preferable less than 0.14 in mixture fraction space. LES was observed to have multiple ignition spots in the mixing layer simultaneously while the main ignition initiates in a clearly asymmetric fashion. The temporal flame development also indicates the flame stabilization mechanism is auto-ignition controlled and modulated by flame propagation. Soot predictions by LES present much better agreement with experiments compared to RANS both qualitatively and quantitatively. Multiple realizations for LES were performed to understand the realization to realization variation and to establish best practices for ensemble-averaging diesel spray flames. The relevance index analysis suggests that an average of 2 and 5 realizations can reach 99\% of similarity to the target average of 16 realizations on the temperature and mixture fraction fields, respectively. However, more realizations are necessary for OH and soot mass fraction due to their high fluctuations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

UV patternable thin film chemistry for shape and functionally versatile self-oscillating gels

We describe a new planar processing chemistry that allows the synthesis and patterning of dynamically self-actuating gels of diverse form. The chemical reaction covalently incorporates a methacrylate-modified ruthenium trisbipyridine monomer within a poly acrylamide (PAAm) gel, modified to provide a flexible chemistry for UV-curable, self-oscillating Belousov–Zhabotinsky (BZ) gels. The photoinitiated polymerization offers significant advantages over previously reported BZ gel chemistries – fast polymerization rates, broad flexibility in the structural and functional attributes that impact the BZ reaction driven mechanics, and a facility for net shape fabrication via projection mode photo lithographic exposure. The facility of the synthetic method enabled an opportunity to broadly explore the structure/property and structure/rate correlations characterizing the dynamics of these gels and develop means to both control and predict the detailed features of the self-oscillating chemical waves they embed. The PAAm systems initiate under the control of transport-dominated influences weighted heavily by the diffusion/depletion of reagents present in the ambient contacting fluid medium. These initiating modes of oscillation are generally unstable temporally, showing shape- and property-sensitive conversions to oscillating modes controlled by the attributes of the gel-phase environment. The present work establishes the nature of these sensitivities, developing insights related to such features in patterned gel objects or films as composition, size, thickness, shape, degree of crosslinking, and gradient forms of structure within the gel. We observed in this work that, across a broad design-rule and compositional space, the PAAm based BZ gel systems exhibit contractions in dimension for regions in which the Ru catalyst is present in the +3 oxidation state (PNIPAAm BZ gels expand in this state). The chemomechanics of the PAAm system are further differentiated from those of PNIPAAm in the generally (and relatively) fast oscillatory rates it can sustain. Furthermore, this work suggests the dynamics in the PAAm gels do not reflect a simple osmotic force driven by differences in the solvation of Ru(II/III) centers. Computational modeling supports a mechanism in which the charge state of Ru centers mediate a differential degree of intra/inter-chain segmental interactions – dynamics that mediate a temporally varying degree of reversibly formed association crosslinks within the gel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Mobile range control center/range safety command destruct and real-time instantaneous impact prediction system

The mobile range control center/range safety command destruct and real time instantaneous impact prediction system (MRCCS), designed for launching sounding rockets and expendable launch vehicles, is described. The MRCCS provides mission control and range safety support for remote launch sites and is equipped with telemetry and radar data acquisition systems, real time data computation systems, range safety display systems, and command destruct transmitters.

Hudson, Sandra Merritt↗
NASA NTRS1979

Reduction of computer usage costs in predicting unsteady aerodynamic loadings caused by control surface motions: Analysis and results

Results of theoretical and numerical investigations conducted to develop economical computing procedures were applied to an existing computer program that predicts unsteady aerodynamic loadings caused by leading and trailing edge control surface motions in subsonic compressible flow. Large reductions in computing costs were achieved by removing the spanwise singularity of the downwash integrand and evaluating its effect separately in closed form. Additional reductions were obtained by modifying the incremental pressure term that account for downwash singularities at control surface edges. Accuracy of theoretical predictions of unsteady loading at high reduced frequencies was increased by applying new pressure expressions that exactly satisified the high frequency boundary conditions of an oscillating control surface. Comparative computer result indicated that the revised procedures provide more accurate predictions of unsteady loadings as well as providing reduction of 50 to 80 percent in computer usage costs.

Rowe, W. S.↗
DOE OSTI2020

Characterizing Polyoxovanadate‐Alkoxide Clusters Using Vanadium K‐Edge X‐Ray Absorption Spectroscopy

Abstract A number of technologies would benefit from developing inorganic compounds and materials with specific electronic and magnetic exchange properties. Unfortunately, designing compounds with these properties is difficult because metal⋅⋅⋅metal coupling schemes are hard to predict and control. Fully characterizing communication between metals in existing compounds that exhibit interesting properties could provide valuable insight and advance those predictive capabilities. One such class of molecules are the series of Lindqvist iron‐functionalized and hexavanadium polyoxovanadate‐alkoxide clusters, which we characterized here using V K‐edge X‐ray absorption spectroscopy. Substantial changes in the pre‐edge peak intensities were observed that tracked with the V 3 d ‐electron count. The data also suggested substantial delocalization between the vanadium cations. Meanwhile, the Fe III cations were electronically isolated from the polyoxovanadate core.

Meyer, Rachel L.↗
DOE OSTI2012

From Quanta to the Continuum: Opportunities for Mesoscale Science

This report explores the opportunity and defines the research agenda for mesoscale science—discovering, understanding, and controlling interactions among disparate systems and phenomena to reach the full potential of materials complexity and functionality. The ability to predict and control mesoscale phenomena and architectures is essential if atomic and molecular knowledge is to blossom into a next generation of technology opportunities, societal benefits, and scientific advances.. The body of this report outlines the need, the opportunities, the challenges, and the benefits of mastering mesoscale science.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Acoustic methodology review

It is important for industry and NASA to assess the status of acoustic design technology for predicting and controlling helicopter external noise in order for a meaningful research program to be formulated which will address this problem. The prediction methodologies available to the designer and the acoustic engineer are three-fold. First is what has been described as a first principle analysis. This analysis approach attempts to remove any empiricism from the analysis process and deals with a theoretical mechanism approach to predicting the noise. The second approach attempts to combine first principle methodology (when available) with empirical data to formulate source predictors which can be combined to predict vehicle levels. The third is an empirical analysis, which attempts to generalize measured trends into a vehicle noise prediction method. This paper will briefly address each.

Schlegel, R. G.↗
NASA NTRS1991

Orbit determination support for Hiten's aerobraking in the Earth's atmosphere

Two passes of the ISAS (Japan's Institute of Space and Astronautical Science) Hiten spacecraft through the Earth's atmosphere, at perigee altitudes of 125 km and 120 km, during Mar. 1991 marked the first aerobraking technology demonstrations for an object in cis-lunar orbit traveling at near Earth escape velocity. Prediction and control of perigee altitude to better than 1 km was desired to assure spacecraft survival. Covariance analysis provided confidence that prediction accuracy better than 200 m for support of final trim maneuver design was achievable with NASA DSN (Deep Space Network) tracking support. ISAS used orbit determination results in their decisions to cancel final trim maneuvers. Post flight reconstructions, marking the first combined use of DSN and ISAS tracking data, yielded perigee altitude solutions which agree with the near real time mission operations support predictions to better than 50 m.

Efron, L.↗
DOE OSTI2024

Towards accurate prediction of configurational disorder properties in materials using graph neural networks

Abstract The prediction of configurational disorder properties, such as configurational entropy and order-disorder phase transition temperature, of compound materials relies on efficient and accurate evaluations of configurational energies. Previous cluster expansion methods are not applicable to configurationally-complex material systems, including those with atomic distortions and long-range orders. In this work, we propose to leverage the versatile expressive capabilities of graph neural networks (GNNs) for efficient evaluations of configurational energies and present a workflow combining attention-based GNNs and Monte Carlo simulations to calculate the disorder properties. Using the dataset of face-centered tetragonal gold copper without and with local atomic distortions as an example, we demonstrate that the proposed data-driven framework enables the prediction of phase transition temperatures close to experimental values. We also elucidate that the variance of the energy deviations among configurations controls the prediction accuracy of disorder properties and can be used as the target loss function when training and selecting the GNN models. The work serves as a fundamental step toward a data-driven paradigm for the accelerated design of configurationally-complex functional material systems.

Chemistry↗
DOE OSTI2017

Connected Vehicles and Powertrain Optimization

This article discusses the basic concept of connected and automated vehicles (CAV) technology. The common methods to improve fuel economy are also introduced. The effects of connectivity on vehicle/powertrain control and optimization are also elaborated. The Michigan Tech NEXTCAR project is also presented to provide a more detailed view of predictive vehicle/powertrain control enabled by CAV technologies. The U.S. Department of transportation (DOT) and other federal/state funding agencies have supported research and pilot deployment efforts to develop crosscutting CV technologies and evaluate the effectiveness of CV technologies in real-world transportation systems. The concurrent development of connected and automated vehicle technologies is anticipated to provide synergistic benefits to improve traffic safety, mobility, and energy efficiency. Here, it is observed that increased CAV technologies are being deployed in real-world transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1977

Prediction of jump phenomena in rotationally-coupled maneuvers of aircraft, including nonlinear aerodynamic effects

An analytical method has been developed for predicting critical control inputs for which nonlinear rotational coupling may cause sudden jumps in aircraft response. The analysis includes the effect of aerodynamics which are nonlinear in angle of attack. The method involves the simultaneous solution of two polynomials in roll rate, whose coefficients are functions of angle of attack and the control inputs. Results obtained using this procedure are compared with calculated time histories to verify the validity of the method for predicting jump-like instabilities.

Young, J. W.↗
NASA NTRS2001

2001 Flight Mechanics Symposium

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium held on June 19-21, 2001. Sponsored by the Guidance, Navigation and Control Center of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to attitude/orbit determination, prediction and control; attitude simulation; attitude sensor calibration; theoretical foundation of attitude computation; dynamics model improvements; autonomous navigation; constellation design and formation flying; estimation theory and computational techniques; Earth environment mission analysis and design; and, spacecraft re-entry mission design and operations. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Flight mechanics↗
DOE OSTI2017

A multi-mode state-space dynamic model for Pyrofusion neutron sources - 371

Pyrofusion neutron sources are compact, low power systems which may be capable of producing short intense pulses of neutrons from D-D fusion reactions. The neutron pulse duration has been too short for use as a continuous wave source, and too long for application in interrogation techniques. However, initial analysis of Pyrofusion dynamics has indicated the potential to manipulate the pulse characteristics through system control. This paper introduces the development of state-space multimode system models in MATLAB/Simulink that may be used to support the predictability and control of the neutron pulse. Preliminary examples of frequency-domain studies, stability analysis and time-domain simulations are reported. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Gravitational Test beyond the First Post-Newtonian Order with the Shadow of the M87 Black Hole

In this study, the 2017 Event Horizon Telescope (EHT) observations of the central source in M87 have led to the first measurement of the size of a black-hole shadow. This observation offers a new and clean gravitational test of the black-hole metric in the strong-field regime. We show analytically that spacetimes that deviate from the Kerr metric but satisfy weak-field tests can lead to large deviations in the predicted black-hole shadows that are inconsistent with even the current EHT measurements. We use numerical calculations of regular, parametric, non-Kerr metrics to identify the common characteristic among these different parametrizations that control the predicted shadow size. We show that the shadow-size measurements place significant constraints on deviation parameters that control the second post-Newtonian and higher orders of each metric and are, therefore, inaccessible to weak-field tests. The new constraints are complementary to those imposed by observations of gravitational waves from stellar-mass sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Machine learning to predict final fire size at the time of ignition

Fires in boreal forests of Alaska are changing, threatening human health and ecosystems. Given expected increases in fire activity with climate warming, insight into the controls on fire size from the time of ignition is necessary. Such insight may be increasingly useful for fire management, especially in cases where many ignitions occur in a short time period. Here we investigated the controls and predictability of final fire size at the time of ignition. Using decision trees, we show that ignitions can be classified as leading to small, medium or large fires with 50.4 ± 5.2% accuracy. This was accomplished using two variables: vapour pressure deficit and the fraction of spruce cover near the ignition point. The model predicted that 40% of ignitions would lead to large fires, and those ultimately accounted for 75% of the total burned area. Other machine learning classification algorithms, including random forests and multi-layer perceptrons, were tested but did not outperform the simpler decision tree model. Applying the model to areas with intensive human management resulted in overprediction of large fires, as expected. This type of simple classification system could offer insight into optimal resource allocation, helping to maintain a historical fire regime and protect Alaskan ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Nanoparticle Catalyst Formation and Subsequent Sintering: Size-Distribution Fundamental Understanding and Catalyst Control via Mechanism-Enabled Population Balance Modeling (Final Report)

The challenge of elucidating the chemical mechanisms by which nano- and other particles form, and then using those mechanisms to understand, analyze, and ideally predict particle-size and particle-size distributions, was undertaken. Thanks to multi-year, longer-term DOE support each of these challenges was successfully met. The community is now able to both predict, and control in cases where the underlying mechanism of particle formation has been determined, the key PS and PSD that are, in turn, critical properties that strongly influence the catalytic and other physical properties of nano- and larger particles across nature.

36 MATERIALS SCIENCE↗