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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 217 records · Page 12

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NASA NTRSDate not supplied

Statistical Classification of Biosignature Information using Multiple Instrument Observations

The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.

Statistical↗

NASA NTRS1992

A transport equation for eddy viscosity

A transport equation for eddy viscosity is proposed for wall bounded turbulent flows. The proposed model reduces to a quasi-homogeneous form far from surfaces. Near to a surface, the nonhomogeneous effect of the wall is modeled by an elliptic relaxation model. All the model terms are expressed in local variables and are coordinate independent; the model is intended to be used in complex flows. Turbulent channel flow and turbulent boundary layer flows with/without pressure gradient are calculated using the present model. Comparisons between model calculations and direct numerical simulation or experimental data show good agreement.

Durbin, P. A.↗

NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R(exp 2) = 0.75) and gross primary productivity (R(exp 2) = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

Ecosystem model↗

NASA NTRS1991

Error associated with a reduced order linear model of a spur gear pair

The paper proposes a reduced-order analytical model of a spur gear pair which consists of two identical spur gears, two identical flexible shafts, and four identical rolling element bearings of a given radial stiffness. The error associated with the undamped eigensolution is estimated by a comparison with a benchmark finite element model.

Kahraman, A.↗

NASA NTRS1974

Chain pooling to minimize prediction error in subset regression

Monte Carlo studies using population models intended to represent response surface applications are reported. Simulated experiments were generated by adding pseudo random normally distributed errors to population values to generate observations. Model equations were fitted to the observations and the decision procedure was used to delete terms. Comparison of values predicted by the reduced models with the true population values enabled the identification of deletion strategies that are approximately optimal for minimizing prediction errors.

Holms, A. G.↗

NASA NTRS2010

Assessment of Biases in MODIS Surface Reflectance Due to Lambertian Approximation

Using MODIS data and the AERONET-based Surface Reflectance Validation Network (ASRVN), this work studies errors of MODIS atmospheric correction caused by the Lambertian approximation. On one hand, this approximation greatly simplifies the radiative transfer model, reduces the size of the look-up tables, and makes operational algorithm faster. On the other hand, uncompensated atmospheric scattering caused by Lambertian model systematically biases the results. For example, for a typical bowl-shaped bidirectional reflectance distribution function (BRDF), the derived reflectance is underestimated at high solar or view zenith angles, where BRDF is high, and is overestimated at low zenith angles where BRDF is low. The magnitude of biases grows with the amount of scattering in the atmosphere, i.e., at shorter wavelengths and at higher aerosol concentration. The slope of regression of Lambertian surface reflectance vs. ASRVN bidirectional reflectance factor (BRF) is about 0.85 in the red and 0.6 in the green bands. This error propagates into the MODIS BRDF/albedo algorithm, slightly reducing the magnitude of overall reflectance and anisotropy of BRDF. This results in a small negative bias of spectral surface albedo. An assessment for the GSFC (Greenbelt, USA) validation site shows the albedo reduction by 0.004 in the near infrared, 0.005 in the red, and 0.008 in the green MODIS bands.

Wang, Yujie↗

NASA NTRS1991

Modeling of Space Station power system components and their interactions

The authors demonstrate that the functional modeling approach is feasible in modeling large-scale spacecraft power systems such as the Space Station electric power system (EPS). The functional models for the solar array sequential shunt unit and the battery charging/discharging unit are presented. The functional modeling approach has also been applied to simulate other major EPS components. The usefulness of this approach in system-level studies has been demonstrated by incorporating these models into a power system model and simulating the system behavior under various conditions. The simulation results are consistent with those obtained experimentally. With larger time step size and reduced model complexity, the computation time required by the functional modeling approach is short. Functional models are effective in simulation studies of system-level issues, especially for large-scale power systems including many power electronic components.

Tam, Kwa-Sur↗

NASA NTRS2000

Adding In-Plane Flexibility to the Equations of Motion of a Single Rotor Helicopter

This report describes a way to add the effects of main rotor blade flexibility in the in- plane or lead-lag direction to a large set of non-linear equations of motion for a single rotor helicopter with rigid blades(l). Differences between the frequency of the regressing lag mode predicted by the equations of (1) and that measured in flight (2) for a UH-60 helicopter indicate that some element is missing from the analytical model of (1) which assumes rigid blades. A previous study (3) noted a similar discrepancy for the CH-53 helicopter. Using a relatively simple analytical model in (3), compared to (1), it was shown that a mechanical lag damper increases significantly the coupling between the rigid lag mode and the first flexible mode. This increased coupling due to a powerful lag damper produces an increase in the lowest lag frequency when viewed in a frame rotating with the blade. Flight test measurements normally indicate the frequency of this mode in a non-rotating or fixed frame. This report presents the additions necessary to the full equations of motion, to include main rotor blade lag flexibility. Since these additions are made to a very complex nonlinear dynamic model, in order to provide physical insight, a discussion of the results obtained from a simplified set of equations of motion is included. The reduced model illustrates the physics involved in the coupling and should indicate trends in the full model.

Curtiss, H. C., Jr.↗

NASA NTRS2010

Fundamental Travel Demand Model Example

Instances of transportation models are abundant and detailed "how to" instruction is available in the form of transportation software help documentation. The purpose of this paper is to look at the fundamental inputs required to build a transportation model by developing an example passenger travel demand model. The example model reduces the scale to a manageable size for the purpose of illustrating the data collection and analysis required before the first step of the model begins. This aspect of the model development would not reasonably be discussed in software help documentation (it is assumed the model developer comes prepared). Recommendations are derived from the example passenger travel demand model to suggest future work regarding the data collection and analysis required for a freight travel demand model.

Hanssen, Joel↗

NASA NTRS1992

Integrated modeling and design of advanced optical systems

A new modeling, analysis and design environment for precision optical spacecraft being developed at JPL is described in terms of its language, implementation and data organization. The computer program IMOS (Integrated Modeling of Optical Systems) will provide an integrated end-to-end modeling and design environment for spacecraft missions requiring multidisciplinary system performance evaluation. IMOS discipline modules will be coded in an Ada-like language to reduce model development and evaluation time, and new hierarchical data base concepts will be included to facilitate system trade studies and tracking of system requirements. The development will support a growing community of engineers involved in integrated modeling of current and future NASA missions.

Briggs, Hugh C.↗

NASA NTRS1991

Modeling and simulations of the DSS 13 antenna control system

A model of the antenna control system for the azimuth and elevation axes of the Deep Space Station (DSS) 13 antenna is developed. This model is used for simulation of elevation and azimuth dynamics, cross-coupled dynamics, and radio-frequency pointing error due to both input commands and wind disturbances. This model also serves as a tool for the antenna controller design. A modal state-space model of the antenna structure was obtained from its finite-element model with a free-rotating tipping structure and alidade. Model reduction techniques applied separately for the antenna structure, elevation, and azimuth drives, and rate-loop model reduce the system order to one-third of that of the original, while preserving its significant dynamic properties. Extensive simulation results illustrate properties of the model.

Gawronski, W.↗

NASA NTRS1992

Krylov vector methods for model reduction and control of flexible structures

Krylov vectors and the concept of parameter matching are combined here to develop model-reduction algorithms for structural dynamics systems. The method is derived for a structural dynamics system described by a second-order matrix differential equation. The reduced models are shown to have a promising application in the control of flexible structures. It can eliminate control and observation spillovers while requiring only the dynamic spillover terms to be considered. A model-order reduction example and a flexible structure control example are provided to show the efficacy of the method.

Su, Tzu-Jeng↗

NASA NTRS1989

The determination of third order linear models from a seventh order nonlinear jet engine model

Results are presented that demonstrate how good reduced-order models can be obtained directly by recursive parameter identification using input/output (I/O) data of high-order nonlinear systems. Three different methods of obtaining a third-order linear model from a seventh-order nonlinear turbojet engine model are compared. The first method is to obtain a linear model from the original model and then reduce the linear model by standard reduction techniques such as residualization and balancing. The second method is to identify directly a third-order linear model by recursive least-squares parameter estimation using I/O data of the original model. The third method is to obtain a reduced-order model from the original model and then linearize the reduced model. Frequency responses are used as the performance measure to evaluate the reduced models. The reduced-order models along with their Bode plots are presented for comparison purposes.

Lalonde, Rick J.↗

NASA NTRS2001

A Powerful New Engine

Through Small Business Innovation Research (SBIR) funding from NASA's Glenn Research Center, Moller International created a new coating for rotary engines, which significantly improves the fuel consumption of a vehicle while reducing emissions. The new coatings are offered in the new Rotapower(R) engine, which is produced and distributed by Moller subsidiary, Freedom Motors, Inc. The coating allows the Rotapower engine to function smoother than other models, reducing wear and protecting the engine. The Rotapower engine has the ability to operate on a variety of fuels, including gasoline, natural gas, diesel, alcohol, and kerosene. A small and lightweight engine, it is projected to replace many of today's bulkier versions. The 10 horsepower model fits in the palm of one's hand, while the 160 horsepower model fits into a 5-gallon bucket. The clean running Rotapower engine is environmentally appealing, because it eliminates over 98 percent of the total emissions given off by traditional piston engines. Fewer pollutants are spewed into the air, making it especially attractive in areas where air pollution is a major problem. Due to the clean-burning nature of the engine, it meets the stringent standards set by the California Air Resources Board. The engine also has numerous commercial benefits in several types of recreational, industrial, and transportation applications, including personal watercraft, snowmobiles, portable generators. and pumps.

Source record↗

NASA NTRS2005

Flexible Models for Solar Sail Control

Solar sails employ a unique form of propulsion, gaining momentum from incident and reflected photons. However, the momentum transferred by an individual photon is extremely small. Consequently, a solar sail must have an extremely large surface area and also be extremely light. The flexibility of the sail then must be considered when designing or evaluating control laws. In this paper, solar sail flexibility and its influence on control effectiveness is considered using idealized two-dimensional models to represent physical phenomena rather than a specific design. Differential equations of motion are derived for a distributed parameter model of a flexible solar sail idealized as a rotating central hub with two opposing flexible booms. This idealization is appropriate for solar sail designs in which the vibrational modes of the sail and supporting booms move together allowing the sail mass to be distributed along the booms in the idealized model. A reduced analytical model of the flexible response is considered. Linear feedback torque control is applied at the central hub. Two translational disturbances and a torque disturbance also act at the central hub representing the equivalent effect of deflecting sail shape about a reference line. Transient simulations explore different control designs and their effectiveness for controlling orientation, for reducing flexible motion and for disturbance rejection. A second model also is developed as a two-dimensional "pathfinder" model to calculate the effect of solar sail shape on the resultant thrust, in-plane force and torque at the hub. The analysis is then extended to larger models using the finite element method. The finite element modeling approach is verified by comparing results from a two-dimensional finite element model with those from the analytical model. The utility of the finite element modeling approach for this application is then illustrated through examples based on a full finite element model.

Weaver Smith, Suzanne↗

NASA NTRS1988

Grammians and model reduction in limited time and frequency intervals

In this paper the controllability and observability grammians in limited time and frequency intervals are studied, and used for model reduction. In balanced and modal coordinates a near-optimal reduction procedure is developed, yielding the reduction error (norm of the difference between the output of the original system and the reduced model) almost minimal. Several examples are given to illustrate the concept for model reduction of continuous- and discrete-time systems, stable and unstable systems, in limited tim or/and frequency interval. Finally, the model reduction of a flexible truss structure is presented.

Gawronski, Wodek↗

NASA NTRS1985

A computational model for a regenerator

This paper concerns a numerical model of a regenerator running at very low temperatures. The model consists of the usual three equations for a compressible fluid with an additional equation for a matrix temperature. The main difficulty with the model is the very low Mach number (approximately 1.E-3). The divergence of the velocity is not small, the pressure divergence is small, and the pressure fluctuation in time is not small. An asymptotic expansion based on the bounded derivative method of Kreiss is used to give a reduced model which eliminates acoustic waves. The velocity is then determined by a two-point boundary value problem which does not contain a time derivative. The solution obtained from the reduced system is compared with the numerical solution of the original system.

Gary, J.↗

NASA NTRS1982

The residue-measure criterion for model reduction in the analysis of the NASA Space Shuttle's digital flight control system

A residue-measure criterion model reduction technique is applied to the vehicle dynamics model used in the design and analysis of the NASA Space Shuttle's digital flight control system. As implemented in this study the residue-measure technique involved an a priori residue calculation with control system biasing. The predictions of the reduced model are compared to vehicle level dynamic stability test data. These comparisons show an excellent correlation of the dominant spectral and response features between the model and test data. In addition, the application of the reduction technique to various Shuttle mission flight phases is demonstrated.

Gluch, D. P.↗