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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Shuttle ascent trajectory optimization with function space quasi-Newton techniques

A Space Shuttle ascent trajectory optimization problem from lift-off to orbital insertion is solved with a function space version of a quasi-Newton parameter optimization method developed by Broyden. The problem includes five parameter and one bounded-function controls, two state-variable constraints, and four terminal conditions. The bounded controls are treated directly, while the remaining constraints are adjoined to the performance index (maximum payload) with penalty functions. The problem is formulated as a four-phase variational problem (liftoff, pitch-over, gravity-turn, linear tangent steering), and the appropriate gradients are developed by first variation theory. A projection operator is introduced to aid in the interpretation of the algorithm with mixed parameter and function controls.

Edge, E. R.↗
NASA NTRS1985

Self-Tuning Adaptive-Controller Using Online Frequency Identification

A real time adaptive controller was designed and tested successfully on a fourth order laboratory dynamic system which features very low structural damping and a noncolocated actuator sensor pair. The controller, implemented in a digital minicomputer, consists of a state estimator, a set of state feedback gains, and a frequency locked loop (FLL) for real time parameter identification. The FLL can detect the closed loop natural frequency of the system being controlled, calculate the mismatch between a plant parameter and its counterpart in the state estimator, and correct the estimator parameter in real time. The adaptation algorithm can correct the controller error and stabilize the system for more than 50% variation in the plant natural frequency, compared with a 10% stability margin in frequency variation for a fixed gain controller having the same performance at the nominal plant condition. After it has locked to the correct plant frequency, the adaptive controller works as well as the fixed gain controller does when there is no parameter mismatch. The very rapid convergence of this adaptive system is demonstrated experimentally, and can also be proven with simple root locus methods.

Chiang, W. W.↗
NASA NTRS1991

A finite element model of conduction, convection, and phase change near a solid/melt interface

Detailed understanding of heat transfer and fluid flow is required for many aerospace thermal systems. These systems often include phase change and operate over a range of accelerations or effective gravitational fields. An approach to analyzing such systems is presented which requires the simultaneous solution of the conservation laws of energy, momentum, and mass, as well as an equation of state. The variable property form of the governing equations are developed in two-dimensional Cartesian coordinates for a Newtonian fluid. A numerical procedure for solving the governing equations is presented and implemented in a computer program. The Galerkin form of the finite element method is used to solve the spatial variation of the field variables, along with the implicit Crank-Nicolson time marching algorithm. Quadratic Langrangian elements are used for the internal energy and the two components of velocity. Linear Lagrangian elements are used for the pressure. The location of the solid/liquid interface as well as the temperatures are determined form the calculated internal energy and pressure. This approach is quite general in that it can describe heat transfer without phase change, phase change with a sharp interface, and phase change without an interface. Analytical results from this model are compared to those of other researchers studying transient conduction, convection, and phase change and are found to be in good agreement. The numerical procedure presented requires significant computer resources, but this is not unusual when compared to similar studies by other researchers. Several methods are suggested to reduce the computational times.

Viterna, Larry A.↗
NASA NTRS2002

Computational Study of Near-limit Propagation of Detonation in Hydrogen-air Mixtures

A computational investigation of the near-limit propagation of detonation in lean and rich hydrogen-air mixtures is presented. The calculations were carried out over an equivalence ratio range of 0.4 to 5.0, pressures ranging from 0.2 bar to 1.0 bar and ambient initial temperature. The computations involved solution of the one-dimensional Euler equations with detailed finite-rate chemistry. The numerical method is based on a second-order spatially accurate total-variation-diminishing (TVD) scheme, and a point implicit, first-order-accurate, time marching algorithm. The hydrogen-air combustion was modeled with a 9-species, 19-step reaction mechanism. A multi-level, dynamically adaptive grid was utilized in order to resolve the structure of the detonation. The results of the computations indicate that when hydrogen concentrations are reduced below certain levels, the detonation wave switches from a high-frequency, low amplitude oscillation mode to a low frequency mode exhibiting large fluctuations in the detonation wave speed; that is, a 'galloping' propagation mode is established.

Yungster, S.↗
NASA NTRS2004

Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health

Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate expected sensor values for targeted fault scenarios. Taken together, this information provides an efficient condensation of the engineering experience and engine flow physics needed for sensor selection. The systematic sensor selection strategy is composed of three primary algorithms. The core of the selection process is a genetic algorithm that iteratively improves a defined quality measure of selected sensor suites. A merit algorithm is employed to compute the quality measure for each test sensor suite presented by the selection process. The quality measure is based on the fidelity of fault detection and the level of fault source discrimination provided by the test sensor suite. An inverse engine model, whose function is to derive hardware performance parameters from sensor data, is an integral part of the merit algorithm. The final component is a statistical evaluation algorithm that characterizes the impact of interference effects, such as control-induced sensor variation and sensor noise, on the probability of fault detection and isolation for optimal and near-optimal sensor suites.

Source record↗
DOE OSTI2021

System and method for focal-plane illuminator/detector (FASID) design for improved graded index lenses

The present disclosure relates to a detector system for imaging an optical signal received by a graded index (GRIN) optical element to account for known variations in a graded index distribution of the GRIN optical element. The detector system incorporates a plurality of optical detector elements configured to receive optical rays received by the GRIN optical element at specific locations on a plane of the GRIN optical element. Ray tracing software is configured to receive and map the optical rays to a plurality of additional specific locations on the plane based on the known variations in the graded index distribution of the GRIN optical element. A processor uses algorithms for diagonalization of a linear system matrix to determine information on both an intensity and an angle of the received optical rays at each one of the plurality of specific locations on the plane.

Bude, Jeffrey Devin↗
DOE OSTI2022

Image Analysis for Rapid Assessment and Quality-Based Sorting of Corn Stover

Imaging in the visible spectrum is a low-cost tool that can be readily deployed for in-field or over-belt monitoring of biomass quality for bio-refining operations. Rapid image analysis coupled with innovative preprocessing may reduce the impacts of feedstock variability through identification of contaminants or other material attributes to guide selective sorting and quality management. Image analysis was employed to evaluate the quality of corn stover in red-green-blue (RGB) chromatic space. This study used controlled, bench-scale imaging as a proof-of-concept for rapid quality assessment of corn stover based on variations in material attributes, including chemical and physical attributes, that relate to biological degradation and soil contamination. Additionally, logistic regression-based classification algorithms were used to develop a method for biomass screening as a function of biological degradation or soil contamination. This study demonstrated the use of image analysis to extract features from RGB color space to investigate variations in critical material attributes from chemical composition of corn stover. Fourier transform infrared (FT-IR) suggested a correlation between red band intensity and biological degradation, while detailed surface texture analysis was found to distinguish among variations in ash. These insights offer promise for development of a rapid screening tool that could be deployed by farmers for in-field assessment of biomass quality or biorefinery operators for in-line sorting and process optimization.

09 BIOMASS FUELS↗
NASA NTRS1993

Surface net solar radiation estimated from satellite measurements - Comparisons with tower observations

A parameterization that relates the reflected solar flux at the top of the atmosphere to the net solar flux at the surface in terms of only the column water vapor amount and the solar zenith angle was tested against surface observations. Net surface fluxes deduced from coincidental collocated satellite-measured radiances and from measurements from towers in Boulder during summer and near Saskatoon in winter have mean differences of about 2 W/sq m, regardless of whether the sky is clear or cloudy. Furthermore, comparisons between the net fluxes deduced from the parameterization and from surface measurements showed equally good agreement when the data were partitioned into morning and afternoon observations. This is in contrast to results from an empirical clear-sky algorithm that is unable to account adequately for the effects of clouds and that shows, at Boulder, a distinct morning to afternoon variation. It is also demonstrated that the parameterization may be applied to irradiances at the top of the atmosphere that have been temporally averaged. The good agreement between the results of the parameterization and surface measurements suggests that the algorithm is a useful tool for a variety of climate studies.

Li, Zhanqing↗
DOE OSTI2020

A Minimum Principle-Based Algorithm for Energy-Efficient Eco-Driving of Electric Vehicles in Various Traffic and Road Conditions

Our report presents an optimization algorithm for energy-efficient driving of electric vehicles. The algorithm is based on Pontryagin’s Minimum Principle by considering the driving mission as an optimal control problem. On a planned route, diverse application cases may occur due to various physical traits such as powertrain (e.g., switching between motor and generator operation), environmental variations (e.g., terrain grade change), traffic laws (e.g., speed limits), and safety concerns (e.g., headway to the leading vehicle). The proposed algorithm handles these real-world challenges by considering the perturbation to the system dynamics and the constraints to the control and state variables.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Proximal Galerkin: A Structure-Preserving Finite Element Method for Pointwise Bound Constraints

The proximal Galerkin finite element method is a high-order, low iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of pointwise bound constraints in infinite-dimensional function spaces. This paper introduces the proximal Galerkin method and applies it to solve free boundary problems, enforce discrete maximum principles, and develop a scalable, mesh-independent algorithm for optimal design with pointwise bound constraints. This paper also introduces the latent variable proximal point (LVPP) algorithm, from which the proximal Galerkin method derives. When analyzing the classical obstacle problem, we discover that the underlying variational inequality can be replaced by a sequence of second-order partial differential equations (PDEs) that are readily discretized and solved with, e.g., the proximal Galerkin method. Throughout this work, we arrive at several contributions that may be of independent interest. These include (1) a semilinear PDE we refer to as the entropic Poisson equation; (2) an algebraic/geometric connection between high-order positivity-preserving discretizations and certain infinite-dimensional Lie groups; and (3) a gradient-based, bound-preserving algorithm for two-field, density-based topology optimization. The complete proximal Galerkin methodology combines ideas from nonlinear programming, functional analysis, tropical algebra, and differential geometry and can potentially lead to new synergies among these areas as well as within variational and numerical analysis. Open-source implementations of our methods accompany this work to facilitate reproduction and broader adoption.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

The relation of scalability and execution time

Scalability has been used extensively as a de facto performance criterion for evaluating parallel algorithms and architectures. However, for many, scalability has theoretical interests only since it does not reveal execution time. In this paper, the relation between scalability and execution time is carefully studied. Results show that the isospeed scalability well characterizes the variation of execution time: smaller scalability leads to larger execution time, the same scalability leads to the same execution time, etc. Three algorithms from scientific computing are implemented on an Intel Paragon and an IBM SP2 parallel computer. Experimental and theoretical results show that scalability is an important, distinct metric for parallel and distributed systems, and may be as important as execution time in a scalable parallel and distributed environment.

Sun, Xian-He↗
NASA NTRS1999

Systematic Differences between Satellite-Based Presipitation Climatologies over the Tropical Oceans

Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. It is clear however that there still remain significant uncertainties with satellite precipitation retrievals which limit their usefulness for many purposes. Systematic differences i'A tropical precipitation estimates have been brought to light in comparison activities such as the GPCP Algorithm Intercomparison Project and more recent Wetnet Precipitation Intercomparison Project 3. These uncertainties are assuming more importance because of the demands for validation associated with global climate modeling and data assimilation methodologies. The objective of the present study is to determine the physical basis for systematic differences in spatial structure of tropical precipitation as portrayed by several different satellite-based data sets. The study is limited to oceanic regions only and deals primarily with aspects of spatial variability. We are specifically interested in why MSU channel 1 and GPI precipitation differences are so striking over the Eastern Pacific ITCZ and why they both differ from other microwave emission-based precipitation estimates from SSM/I and a scattering-based deep convective ice index from MSU channel 2. Our results to date have shown that MSU channel I precipitation estimates are biased high over the Eastern Pacific ITCZ because of two factors: (1) the hypersensitivity of this frequency to cloud water in contrast to falling rain drops, and (2) unaccounted for scattering effects by precipitation-size ice which depresses the signal of the liquid water emission. Likewise, cold cloud top climatologies such as the GPI show an excess (a deficit) in estimated rainfall over the E. Pacific ITCZ (Warm Pool region). We show that these algorithms need to account for regionally varying heights (or temperatures) at which tropical convection detrains to form cirrus shields. A second objective we pursue is to identify variations in the macroscale cloud physical and thermodynamic properties of precipitation regimes" and relate these differences to tropical dynamical mechanisms of tropical heat and moisture balance. Finally, we interpret the algorithm differences and their associations with tropical dynamics in terms of WCRP GPCP goals for constructing precipitation climatologies.

Robertson, Frankin R.↗
NASA NTRS1990

Hardware-assisted software clock synchronization for homogeneous distributed systems

A clock synchronization scheme that strikes a balance between hardware and software solutions is proposed. The proposed is a software algorithm that uses minimal additional hardware to achieve reasonably tight synchronization. Unlike other software solutions, the guaranteed worst-case skews can be made insensitive to the maximum variation of message transit delay in the system. The scheme is particularly suitable for large partially connected distributed systems with topologies that support simple point-to-point broadcast algorithms. Examples of such topologies include the hypercube and the mesh interconnection structures.

Ramanathan, P.↗
DOE OSTI2025

Improved heavy-ion PID using scintillation light detector with neural network analysis: a Monte Carlo simulation study

The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle.

Heavy-ion detectors↗
NASA NTRSDate not supplied

Relationships Between Variability in the Stratospheric Polar Vortex, Upper Tropospheric Jets, Tropopauses, and UTLS Ozone

The impacts of stratospheric polar vortex variations on upper troposphere / lower stratosphere (UTLS) circulation and composition are not well understood. We use stratospheric polar vortex geometry / strength diagnostics combined with characterisation of tropopauses and UTLS jets to show links between stratospheric polar vortex variability and regional variations in UTLS jet and tropopause characteristics. Polar vortex diagnostics are from Characterization and Analysis of Vortex Evolution using Algorithms for Region Tracking (CAVE-ART), while UTLS diagnostics are from JEt and Tropopause Products for Analysis and Characterization (JETPAC). We will present results showing UTLS jet and tropopause characteristics for strong and weak stratospheric vortex states (defined using vortex-focused metrics that are less dependent on geometry and position than commonly used diagnostics), as well as regional variations in correlations between CAVE-ART and JETPAC diagnostics. Furthermore, we will focus on preliminary results extending the stratospheric vortex, UTLS jet, and tropopause relationships to assess their impacts on regional ozone variations diagnosed from the M2-SCREAM (MERRA-2 Stratospheric Composition Reanalysis of Aura Microwave Limb Sounder) composition reanalysis.

Gloria Manney↗
NASA NTRS1979

Density models for the upper atmosphere

Three contemporary atmospheric density models which are candidates for meeting the current orbit computation requirements are compared. The models considered are the analytic Jacchia-Roberts model, the modified Harris-Priester model, and the USSR Cosmos satellite derived density model. All of these models can be said to be quasi-dynamic representations of the atmospheric density. The time dependent variations in the model density profiles are determined by both the evaluation of explicit continuous functions of time and by the input of time varying parameters to algorithms. The computation characteristics of each of the models are compared and a modification to the modified Harris-Priester model is proposed which improves its ability to represent the diurnal variation in the atmospheric density.

Dowd, D. L.↗
DOE OSTI2026

Demystifying Piecewise and Localized Scatter Correction Methods

Multiplicative scatter is a common source of noise in near-infrared spectroscopy and other related instrumental techniques. A wide variety of methods are commonly used for the correction of multiplicative scatter. However, the majority of such methods assume that the parameters that describe the scatter are constant throughout the measured spectrum, which is often not the case. This work investigates a family of methods that perform scatter correction using local regions of neighboring wavelengths in order to better account for wavelength-dependent scattering. The methods in question are piecewise standard normal variate, localized standard normal variate, piecewise multiplicative scatter correction, and localized multiplicative scatter correction. This work describes the theoretical and algorithmic foundations of the family of local region-based scatter correction methods and compares their application and optimization at a qualitative and quantitative level using several datasets.

NIR spectroscopy↗
NASA NTRS2004

Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control modes that are selected according to some performance or operational criteria. As the engine degrades, parameters shift from their nominal values. Thus, when a new control mode is swapped in, a variable that is being brought under control might have an excessive initial error. The new adaptive algorithm adjusts the controller gains on the basis of the level of degradation to minimize the disruptive influence of the large error on other variables and to recover the desired thrust response.

Litt, Jonathan S.↗