Search NASA⌕ Search

SEARCH · Search NASA

Results for “driven”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Simulating Turbulence-aided Neutrino-driven Core-collapse Supernova Explosions in One Dimension

The core-collapse supernova (CCSN) mechanism is fundamentally 3D, with instabilities, convection, and turbulence playing crucial roles in aiding neutrino-driven explosions. Simulations of CCNSe including accurate treatments of neutrino transport and sufficient resolution to capture key instabilities remain among the most expensive numerical simulations in astrophysics, prohibiting large parameter studies in 2D and 3D. Studies spanning a large swath of the incredibly varied initial conditions of CCSNe are possible in 1D, though such simulations must be artificially driven to explode. We present a new method for including the most important effects of convection and turbulence in 1D simulations of neutrino-driven CCSNe, called Supernova Turbulence In Reduced-dimensionality, or STIR. Our new approach includes crucial terms resulting from the turbulent and convective motions of the flow. We estimate the strength of convection and turbulence using a modified mixinglength theory approach, introducing a few free parameters to the model that are fit to the results of 3D simulations. For sufficiently large values of the mixing-length parameter, turbulence-aided neutrino-driven explosions are obtained. We compare the results of STIR to high-fidelity 3D simulations and perform a parameter study of CCSN explosion using 200 solar-metallicity progenitor models from 9 to 120 M ⊙ . We find that STIR is a better predictor of which models will explode in multidimensional simulations than other methods of driving explosions in 1D. We also present a preliminary investigation of predicted observable characteristics of the CCSN population from STIR, such as the distributions of explosion energies and remnant masses.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Event-driven displays for manipulator control

The problem of constructing event-related information displays from multidimensional data generated by proximity, force-torque and tactile sensors integrated with the terminal device of a remotely controlled manipulator is considered. Event-driven displays are constructed by using appropriate algorithms acting on sensory data in real time. Event-driven information displays lessen the operator's workload and improve control performance. The paper describes and discusses several event-driven display examples that were implemented in the JPL teleoperator project, including a brief outline of the data handling system which drives the graphics display in real time. The paper concludes with a discussion of future plans to integrate event-driven displays with visual (TV) information.

Bejczy, A. K.↗
NASA NTRS1983

Comparison of the characteristics of potential drop and current-driven double layers

The characteristics of double layers driven by an applied potential drop and by an injected current into a plasma are compared. In the latter case the potential drop across the double layer appears because of the formation of a virtual cathode. The double layers formed by the two mechanisms show striking similarities with regard to their structure, temporal evolution, and dynamics. However, in the case of current-driven double layers a large energization of ions trapped in the virtual cathode region is observed. Such a large energization of trapped ions is not seen in the case of the potential-drop driven double layers. The interrelation between the field-aligned currents and potential drops for the auroral plasma is discussed. For current-driven double layers, it is found that the current density is proportional to the 1/2 power of the potential drop.

Singh, N.↗
NASA NTRS1984

Driven magnetic reconnection in three dimensions - Energy conversion and field-aligned current generation

The energy conversion processes occurring in three-dimensional driven reconnection is analyzed. In particular, the energy conversion processes during localized reconnection in a taillike magnetic configuration are studied. It is found that three-dimensional driven reconnection is a powerful energy converter which transforms magnetic energy into plasma bulk flow and thermal energy. Three-dimensional driven reconnection is an even more powerful energy converter than two-dimensional reconnection, because in the three-dimensional case, plasmas were drawn into the reconnection region from the sides as well as from the top and bottom. Field-aligned currents are generated by three-dimensional driven reconnection. The physical mechanism responsible for these currents which flow from the tail toward the ionosphere on the dawnside of the reconnection region and from the ionosphere toward the tail on the duskside is identified. The field-aligned currents form as the neutral sheet current is diverted through the slow shocks which form on the outer edge of the reconnected field lines (outer edge of the plasma sheet).

Sato, T.↗
NASA NTRS2000

Diffusion Driven Combustion Waves in Porous Media

Filtration of gas containing oxidizer, to the reaction zone in a porous medium, due, e.g., to a buoyancy force or to an external pressure gradient, leads to the propagation of Filtration combustion (FC) waves. The exothermic reaction occurs between the fuel component of the solid matrix and the oxidizer. In this paper, we analyze the ability of a reaction wave to propagate in a porous medium without the aid of filtration. We find that one possible mechanism of propagation is that the wave is driven by diffusion of oxidizer from the environment. The solution of the combustion problem describing diffusion driven waves is similar to the solution of the Stefan problem describing the propagation of phase transition waves, in that the temperature on the interface between the burned and unburned regions is constant, the combustion wave is described by a similarity solution which is a function of the similarity variable x/square root of(t) and the wave velocity decays as 1/square root of(t). The difference between the two problems is that in the combustion problem the temperature is not prescribed, but rather, is determined as part of the solution. We will show that the length of samples in which such self-sustained combustion waves can occur, must exceed a critical value which strongly depends on the combustion temperature T(sub b). Smaller values of T(sub b) require longer sample lengths for diffusion driven combustion waves to exist. Because of their relatively small velocity, diffusion driven waves are considered to be relevant for the case of low heat losses, which occur for large diameter samples or in microgravity conditions, Another possible mechanism of porous medium combustion describes waves which propagate by consuming the oxidizer initially stored in the pores of the sample. This occurs for abnormally high pressure and gas density. In this case, uniformly propagating planar waves, which are kinetically controlled, can propagate, Diffusion of oxidizer decreases the wave velocity. In addition to the reaction and diffusion layers, the uniformly propagating wave structure includes a layer with a pressure gradient, where the gas motion is induced by the production or consumption of the gas in the reaction as well as by thermal expansion of the gas. The width of this zone determines the scale of the combustion wave in the porous medium.

Aldushin, A. P.↗
NASA NTRS2004

Numerical Simulation of Waves Driven by Plasma Currents Generated by Low-Frequency Alfven Waves in a Multi-Ion Plasma

When multi-ion plasma consisting of heavy and light ions is permeated by a low-frequency Alfven (LFA) wave, the crossed-electric-and-magnetic field (E x B), and the polarization drifts of the different ion species and the electrons could be quite different. The relative drifts between the charged-particle species drive waves, which energize the plasma. Using 2.5-dimensional (2.5-D) particle-in-cell simulations, we study this process of wave generation and its nonlinear consequences in terms of acceleration and heating plasma. Specifically, we study the situation for LFA wave frequency being lower than the heavy-ion cyclotron frequency in a multi-ion plasma. We impose such a wave to the plasma assuming that its wavelength is much larger than that of the waves generated by the relative drifts. For better understanding, the LFA-wave driven simulations are augmented by those driven by initialized ion beams. The driven high-frequency (HF) wave modes critically depend on the heavy ion density nh; for small values of nh, the lower hybrid (LH) waves dominate. On the other hand, for large nh a significantly enhanced level of waves occurs over a much broader frequency spectrum below the LH frequency and such waves are interpreted here as the ion Bernstein (IB) mode near the light ion cyclotron harmonics. Irrespective of the driven wave modes, both the light and heavy ions undergo significant transverse acceleration, but for the large heavy-ion densities, even the electrons are significantly accelerated in the parallel direction by the waves below the LH frequency. Even when the LFA wave drive is maintained, the ion heating leads to the cessation of HF wave excitation just after a few cycles of the former wave. On the basis of marginal stability seen in the simulations, an empirical relation for LFA wave amplitude, frequency and ion temperature is given.

Singh, Nagendra↗
NASA NTRS2008

Database Driven 6-DOF Trajectory Simulation for Debris Transport Analysis

Debris mitigation and risk assessment have been carried out by NASA and its contractors supporting Space Shuttle Return-To-Flight (RTF). As a part of this assessment, analysis of transport potential for debris that may be liberated from the vehicle or from pad facilities prior to tower clear (Lift-Off Debris) is being performed by MSFC. This class of debris includes plume driven and wind driven sources for which lift as well as drag are critical for the determination of the debris trajectory. As a result, NASA MSFC has a need for a debris transport or trajectory simulation that supports the computation of lift effect in addition to drag without the computational expense of fully coupled CFD with 6-DOF. A database driven 6-DOF simulation that uses aerodynamic force and moment coefficients for the debris shape that are interpolated from a database has been developed to meet this need. The design, implementation, and verification of the database driven six degree of freedom (6-DOF) simulation addition to the Lift-Off Debris Transport Analysis (LODTA) software are discussed in this paper.

West, Jeff↗
NASA NTRS2009

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Bakhtiari-Nejad, Maryam↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments.

Iverson, David L.↗
NASA NTRS2009

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Bakhtiari-Nejad, Maryam↗
NASA NTRS2014

Data-Intensive Science meets Inquiry-Driven Pedagogy: Interactive Big Data Exploration, Threshold Concepts, and Liminality

Threshold concepts in any discipline are the core concepts an individual must understand in order to master a discipline. By their very nature, these concepts are troublesome, irreversible, integrative, bounded, discursive, and reconstitutive. Although grasping threshold concepts can be extremely challenging for each learner as s/he moves through stages of cognitive development relative to a given discipline, the learner's grasp of these concepts determines the extent to which s/he is prepared to work competently and creatively within the field itself. The movement of individuals from a state of ignorance of these core concepts to one of mastery occurs not along a linear path but in iterative cycles of knowledge creation and adjustment in liminal spaces - conceptual spaces through which learners move from the vaguest awareness of concepts to mastery, accompanied by understanding of their relevance, connectivity, and usefulness relative to questions and constructs in a given discipline. For example, challenges in the teaching and learning of atmospheric science can be traced to threshold concepts in fluid dynamics. In particular, Dynamic Meteorology is one of the most challenging courses for graduate students and undergraduates majoring in Atmospheric Science. Dynamic Meteorology introduces threshold concepts - those that prove troublesome for the majority of students but that are essential, associated with fundamental relationships between forces and motion in the atmosphere and requiring the application of basic classical statics, dynamics, and thermodynamic principles to the three dimensionally varying atmospheric structure. With the explosive growth of data available in atmospheric science, driven largely by satellite Earth observations and high-resolution numerical simulations, paradigms such as that of dataintensive science have emerged. These paradigm shifts are based on the growing realization that current infrastructure, tools and processes will not allow us to analyze and fully utilize the complex and voluminous data that is being gathered. In this emerging paradigm, the scientific discovery process is driven by knowledge extracted from large volumes of data. In this presentation, we contend that this paradigm naturally lends to inquiry-driven pedagogy where knowledge is discovered through inductive engagement with large volumes of data rather than reached through traditional, deductive, hypothesis-driven analyses. In particular, data-intensive techniques married with an inductive methodology allow for exploration on a scale that is not possible in the traditional classroom with its typical problem sets and static, limited data samples. In addition, we identify existing gaps and possible solutions for addressing the infrastructure and tools as well as a pedagogical framework through which to implement this inductive approach.

Ramachandran, Rahul↗
NASA NTRS2017

Managing Fire Risk During Drought: The Influence of Certification and El Nino on Fire-Driven Forest Conversion for Oil Palm in Southeast Asia

Indonesia and Malaysia have emerged as leading producers of palm oil in the past several decades, expanding production through the conversion of tropical forests to industrial plantations. Efforts to produce "sustainable" palm oil, including certification by the Roundtable on Sustainable Palm Oil (RSPO), include guidelines designed to reduce the environmental impact of palm oil production. Fire-driven deforestation is prohibited by law in both countries and a stipulation of RSPO certification, yet the degree of environmental compliance isunclear, especially during El Niño events when drought conditions increase fire risk. Here, we used time series of satellite data to estimate the spatial and temporal patterns of fire-driven deforestation on and around oil palm plantations. In Indonesia, fire-driven deforestation accounted for one-quarter of total forest losses on both certified and noncertified plantations. After the first plantations in Indonesia received RSPO certification in 2009,forest loss and fire-driven deforestation declined on certified plantations but did not stop altogether. Oil palm expansion in Malaysia rarely involved fire; only 5 % of forest loss on certified plantations had coincident activefire detections. Interannual variability in fire detections was strongly influenced by El Nino and the timing of certification. Fire activity during the 2002, 2004, and 2006 El Nino events was similar among oil palm plantations in Indonesia that would later become certified, noncertified plantations, and surrounding areas. However, total fire activity was 75% and 66% lower on certified plantations than noncertified plantations during the 2009 and 2015 El Nino events, respectively. The decline in fire activity on certified plantations, including during drought periods, highlights the potential for RSPO certification to safeguard carbon stocks in peatlands and remaining forests in accordance with legislation banning fires. However, aligning certification standards with satellite monitoring capabilities will be critical to realize sustainable palm oil production and meet industry commitments to zero forestation.

Noojipady, Praveen↗
NASA NTRS2017

New Data-Driven Estimation of Terrestrial CO2 Fluxes in Asia Using a Standardized Database of Eddy Covariance Measurements, Remote Sensing Data, and Support Vector Regression

The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial carbon dioxide fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem carbon dioxide exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated carbon dioxide fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8 days are reproduced (e.g., r (exp 2) =0.73 and 0.42 for 8 day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r (exp 2)=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land carbon dioxide fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land carbon dioxide fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land carbon dioxide fluxes. These data-driven estimates can provide a new opportunity to assess carbon dioxide fluxes in Asia and evaluate and constrain terrestrial ecosystem models.

chlorophyll fluorescence↗
NASA NTRS2021

Magnetosphere-Ionosphere Coupling of Precipitated Electrons in Diffuse Aurora Driven by Time Domain Structures

Recent theoretical studies and the spacecraft conjugate observations between the Time History of Events and Macroscale Interactions during Substorms (THEMIS) mission and the low-altitude Enhanced Polar Outflow Probe (e-POP) spacecraft demonstrated the connections between broadband electrostatic fluctuations, the so called time domain structures (TDSs), and electron precipitation in the region of diffuse aurora. In this letter, we used the SuperThermal Electron Transport (STET) code to implement these theoretical and experimental results and analyze magnetosphere-ionosphere energy interplay of the precipitated electrons that are driven by TDSs. To put TDSs electron scattering processes in the context with other wave scattering activities, ECH and whistler chorus waves are taken into account. Integrated electron energy fluxes in the diffuse aurora driven by TDSs are comparable to those driven by whistler waves. We find that including Magnetosphere-Ionosphere coupling processes increases the integrated electron energy fluxes by more than two times than only driven by TDSs.

diffuse aurora↗
NASA NTRSDate not supplied

In Search of Data-Driven Improvements to RANS Models Applied to Separated Flows

The goal of this work is to improve the capability of Reynolds-averaged Navier-Stokes turbulence models for separated flows using data-driven enhancements. The resulting model should be “universal” in the sense that it can be used by anyone and applied to as many flows as possible without concern for unusual or detrimental behavior. At worst, the data-driven corrections should not degrade the accuracy of the baseline model (in this case the Spalart-Allmaras one-equation model), while preserving the Galilean invariance and similar theoretical qualities of the original model. In the literature, most current data-driven improvements to turbulence models are only applicable to very similar types of cases as those used to train the model for a specific class of flows. In this work, the impact of using a wide array of cases in the machine-learning training is described. Unwanted behaviors from trained neural networks are examined, and possible mitigation strategies are proposed. However, to date, consistent and broadly applicable data-driven improvements for separated flows have not been achieved.

turbulence modeling↗
DOE OSTI2021

Evaluate the impact of sensor accuracy on model performance in data-driven building fault detection and diagnostics using Monte Carlo simulation

The performance of data-driven fault detection and diagnostics (FDD) is heavily dependent on sensors. However, sensor inaccuracy and sensor faults are pervasive in building operation: inaccurate and missing sensor readings deteriorate FDD performance; sensor inaccuracy will also affect the selection of sensor for data-driven FDD in the model training process, which is another key factor of data-driven FDD performance. Sensor accuracy and sensor selection individually are well-studied research topics in this field, but the impact of sensor accuracy on sensor selection and its further impact on FDD performance has not been evaluated and quantified. In this paper, we developed a novel analysis methodology that comprehensively evaluates sensor fault on sensor selection and FDD accuracy. Monte Carlo simulation is applied to deal with multiple stochastic sensor inaccuracy and provide probabilistic analysis results of the impact of sensor inaccuracy on sensor selection and FDD accuracy. This methodology focuses on the net impact of fault states across a full sensor set. The developed methodology can be used for the early-stage sensor design and operation-stage sensor maintenance. Furthermore, a case study is conducted to demonstrate the analysis methodology using a commercial building model crated to Flexible Research Platform located at Oak Ridge National Laboratory, USA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Data-driven variational multiscale reduced order models

We propose a new data-driven reduced order model (ROM) framework that centers around the hierarchical structure of the variational multiscale (VMS) methodology and utilizes data to increase the ROM accuracy at a modest computational cost. The VMS methodology is a natural fit for the hierarchical structure of the ROM basis: In the first step, we use the ROM projection to separate the scales into three categories: (i) resolved large scales, (ii) resolved small scales, and (iii) unresolved scales. In the second step, we explicitly identify the VMS–ROM closure terms, i.e., the terms representing the interactions among the three types of scales. In the third step, we use available data to model the VMS–ROM closure terms. Thus, instead of phenomenological models used in VMS for standard numerical discretizations (e.g., eddy viscosity models), we utilize available data to construct new structural VMS–ROM closure models. Specifically, we build ROM operators (vectors, matrices, and tensors) that are closest to the true ROM closure terms evaluated with the available data. We test the new data-driven VMS–ROM in the numerical simulation of four test cases: (i) the 1D Burgers equation with viscosity coefficient v = 10 -3 ; (ii) a 2D flow past a circular cylinder at Reynolds numbers, Re = 100, Re = 500, and Re= 1000; (iii) the quasi-geostrophic equations at Reynolds number Re = 450 and Rossby number Ro = 0.0036; and (iv) a 2D flow over a backward facing step at Reynolds number Re = 1000. The numerical results show that the data-driven VMS–ROM is significantly more accurate than standard ROMs.

42 ENGINEERING↗
DOE OSTI2020

Effect of the numerical discretization scheme in Shock-Driven turbulent mixing simulations

In this work, we evaluate the effects of distinct numerical strategies in simulations of shock-driven turbulent mixing. An air-SF 6 -air gas curtain subjected to Mach 1.2 shock-waves is computed with Implicit Large-Eddy Simulation based on three numerical schemes: directional-split with Harten-Lax-van Leer (HLL) solver; directional-unsplit using HLL-Contact (HLLC) solver; and directional-unsplit with HLLC solver and a Low Mach number Correction (LMC). The results illustrate the importance of the numerical strategy to the accuracy of the predictions. Whereas both split and unsplit schemes result in a similar spatial development of the initial shock-driven instability, only the unsplit schemes can predict the turbulent mixing transition after reshock observed by the laboratory experiments. Such feature increases the mixing rate of the two fluids, this being particularly pronounced when the LMC is active due to i) the reduced flow Mach number, and ii) the larger effective Reynolds number. Since the selected mixing problem is driven by the deposition of vorticity at the fluids’ interface, the resultant flow physics is analyzed by investigating the contribution of distinct inviscid mechanisms to the production of vorticity: baroclinicity, stretching, and dilatation. As expected, it is observed that the production of vorticity is initially dominated by the baroclinicity mechanism. Yet, the relevance of the remainder mechanisms is enhanced after the reshock and may even surpass the baroclinicity term.

42 ENGINEERING↗