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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A quantitative analysis of the F18 flight control system

This paper presents an informal quantitative analysis of the F18 flight control system (FCS). The analysis technique combines a coverage model with a fault tree model. To demonstrate the method's extensive capabilities, we replace the fault tree with a digraph model of the F18 FCS, the only model available to us. The substitution shows that while digraphs have primarily been used for qualitative analysis, they can also be used for quantitative analysis. Based on our assumptions and the particular failure rates assigned to the F18 FCS components, we show that coverage does have a significant effect on the system's reliability and thus it is important to include coverage in the reliability analysis.

Doyle, Stacy A.↗
NASA NTRS1998

A Gas-Kinetic Scheme for Reactive Flows

In this paper, the gas-kinetic BGK scheme for the compressible flow equations is extended to chemical reactive flow. The mass fraction of the unburnt gas is implemented into the gas kinetic equation by assigning a new internal degree of freedom to the particle distribution function. The new variable can be also used to describe fluid trajectory for the nonreactive flows. Due to the gas-kinetic BGK model, the current scheme basically solves the Navier-Stokes chemical reactive flow equations. Numerical tests validate the accuracy and robustness of the current kinetic method.

Lian,Youg-Sheng↗
NASA NTRS2000

An Analysis of the Torsion-Rotation-Vibration Rotational Spectrum of the Lowest In-Plane Bend and First Excited Torsional State of the C(3V) Internal Rotor C2H5CN

C2H5CN (Propionitrile or ethyl cyanide) is a well known interstellar species abundantly observed in hot cores during the onset of star formation. The onset of star formation generally results in elevated temperature, which thermally populates may low lying vibrational states such as the 206/cm in-plane bend and the 212/cm first excited torsional state in C2H5CN. Unfortunately, these two states are strongly coupled through a complex series of torsion-vibration-rotation interactions, which dominate the spectrum. In order to understand the details of these interactions and develop models capable of predicting unmeasured transitions for astronomical observations in C2H5CN and similar molecules, several thousand rotational transitions in the lowest excited in-plane bend and first excited torsional state have been recorded, assigned and analyzed. The analysis reveals very strong a- and b-type Coriolis interactions and a number of other smaller interactions and has a number of important implications for other C3V torsion-rotation-vibration systems. The relative importance and the physical origins of the coupling among the rotational, vibrational and torsional motions will be presented along with a full spectroscopic analysis and supporting astronomical observations.

Pearson, J. C.↗
NASA NTRS2003

Non-Genomic Origins of Proteins and Metabolism

It is proposed that evolution of inanimate matter to cells endowed with a nucleic acid- based coding of genetic information was preceded by an evolutionary phase, in which peptides not coded by nucleic acids were able to self-organize into networks capable of evolution towards increasing metabolic complexity. Recent findings that truly different, simple peptides (Keefe and Szostak, 2001) can perform the same function (such as ATP binding) provide experimental support for this mechanism of early protobiological evolution. The central concept underlying this mechanism is that the reproduction of cellular functions alone was sufficient for self-maintenance of protocells, and that self- replication of macromolecules was not required at this stage of evolution. The precise transfer of information between successive generations of the earliest protocells was unnecessary and, possibly, undesirable. The key requirement in the initial stage of protocellular evolution was an ability to rapidly explore a large number of protein sequences in order to discover a set of molecules capable of supporting self- maintenance and growth of protocells. Undoubtedly, the essential protocellular functions were carried out by molecules not nearly as efficient or as specific as contemporary proteins. Many, potentially unrelated sequences could have performed each of these functions at an evolutionarily acceptable level. As evolution progressed, however proteins must have performed their functions with increasing efficiency and specificity. This, in turn, put additional constraints on protein sequences and the fraction of proteins capable of performing their functions at the required level decreased. At some point, the likelihood of generating a sufficiently efficient set of proteins through a non-coded synthesis was so small that further evolution was not possible without storing information about the sequences of these proteins. Beyond this point, further evolution required coupling between proteins and informational polymers that is characteristic to all known forms of life. The emergence of such coupling must be postulated in any scenario of the origin of life, no matter whether it starts with RNA or proteins. To examine the evolutionary potential of non-genomic systems, a simple, computationally tractable model, which is still capable of capturing the essential features of the real system, has been studied computationally. Both constructive and destructive processes have been introduced into the model in a stochastic manner. Instead of assuming random reaction sets, only a suite of protobiologically plausible reactions has been considered. Peptides have been explicitly considered as protoenzymes and their catalytic efficiencies have been assigned on the basis of biochemical principles and experimental estimates. Simulations have been carried out using a novel approach (The Next Reaction Method) that is appropriate even for very low concentrations of reactants. Studies have focused on global autocatalytic processes and their diversity.

Pohorille, Andrew↗
DOE OSTI2020

Description of the Three-Dimensional Large-Scale Forcing Data from the 3D Constrained Variational Analysis (VARANAL3D)

This technical report introduces a Three-Dimensional Constrained Variational Analysis (3DCVA) (Tang and Zhang 2015) and its product of three-dimensional large-scale forcing data to drive single-column models (SCM), cloud-resolving models (CRM), and large-eddy simulation (LES) models, and to evaluate model results. The 3DCVA algorithm is an extension of the original 1D constrained variational analysis (1DCVA) (Zhang and Lin 1997, Zhang et al. 2001). The three-dimensional structure of the forcing data allows studies of spatial variation of the large-scale forcing fields and tests of physical parameterizations across scales. In the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility, the 3D forcing data are assigned the datastream name varanal3d. In this technical report, 3DCVA will be used to refer to the algorithm, while VARANAL3D will be used to refer to the data product.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Salience Assignment for Multiple-Instance Regression

We present a Multiple-Instance Learning (MIL) algorithm for determining the salience of each item in each bag with respect to the bag's real-valued label. We use an alternating-projections constrained optimization approach to simultaneously learn a regression model and estimate all salience values. We evaluate this algorithm on a significant real-world problem, crop yield modeling, and demonstrate that it provides more extensive, intuitive, and stable salience models than Primary-Instance Regression, which selects a single relevant item from each bag.

regression↗
DOE OSTI2023

Parasitic Effects in Impedance Spectrum of PEM Water Electrolysis Cells: Case Study of High-Frequency Inductive Effects

Electrochemical impedance spectroscopy (EIS) is a powerful tool to characterize and distinguish electrochemical, electrical, and diffusive processes in an electrolysis cell. The EIS response with small impedance (mΩ) depends on components and materials of the cell, but often also on the electrical setup, cables, and connectors, leading to incorrect conclusions about the performance of the electrolysis cells. These parasitic effects are assessed via a short-circuit measurement and confirmed to be external from the membrane electrode assembly (MEA). In the setup, the inductive characteristic is described by a modified inductive reactance and must be included in the equivalent circuit model (ECM) which is fitting the cell EIS spectra in operation (in situ). If points of the spectra showing inductive characteristic (below x-axis in Nyquist plot) are excluded from the ECM evaluation, an artificially increased ohmic resistance at high frequencies is obtained. In addition, considerations on other components of the ECM can be misleading and significantly incorrect. The only way to avoid that inductive behavior caused by the external setup is incorrectly assigned to the ECM describing properties of the MEA is to include the inductive effects in the ECM analysis of in situ EIS measurements.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Application of recoil-imaging time projection chambers to directional neutron background measurements in the SuperKEKB accelerator tunnel

Gaseous time projection chambers (TPCs) with high readout segmentation are capable of reconstructing detailed 3D ionization distributions of nuclear recoils resulting from elastic neutron scattering. Here, using a system of six compact TPCs with pixel ASIC readout, filled with a 70:30 mixture of He:CO 2 gas, we analyze the first directional measurements of beam-induced neutron backgrounds in the tunnel regions surrounding the Belle II detector at the SuperKEKB e + e – collider. With the use of 3D recoil tracking, we show that these TPCs are capable of maintaining nearly 100% nuclear recoil purity to reconstructed ionization energies (E reco ) as low as 5 keV ee . Using a large sample of Monte-Carlo (MC)-simulated 4 He, 12 C, and 16 O recoil tracks, we find consistency between predicted and measured recoil energy spectra in five of the six TPCs, providing useful validation of the neutron production mechanisms modeled in simulation. Restricting this sample to 4 He recoil tracks with E reco > 40 keV ee , we further demonstrate axial angular resolutions within 8° and we introduce a procedure that under suitable conditions, correctly assigns the vector direction to 91% of these simulated 4 He recoils. Applying this procedure to assign vector directions to measured 4 He recoil tracks, we observe consistency between the angular distributions of observed and simulated recoils, providing first experimental evidence of localized neutron “hotspots” in the accelerator tunnel. Observed rates of nuclear recoils in these TPCs suggest that simulation overestimates the neutron flux from these hotspots. Despite this, we estimate these hotspots to produce the majority of neutron backgrounds in the accelerator tunnel at SuperKEKB’s target luminosity of 6.3 x 10 35 cm –2 s –1 , making them important regions to continue to monitor.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Operational Energy Life Cycle Data Development for the National Institute of Standards And Technology (NIST) Building Industry Reporting and Design for Sustainability (BIRDS) Neutral Environmental Software Tool (NEST)

For this analysis, regionalized life cycle assessment (LCA) results for environmental impacts (using the Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts [TRACI] 2.1) and cumulative energy demand (using the Federal Life Cycle Analysis Commons Elementary Flow List [FEDEFL] Inventory Methods v1.0.0) were evaluated for the production and utilization of electricity, natural gas, fuel oil, and propane as commodities within residential and commercial buildings. These results can used as a framework for future research into net zero, high-performance buildings, such as done here for the Building Industry Reporting and Design for Sustainability (BIRDS) database by the National Institute of Standards and Technology (NIST) Engineering Laboratory. The geographical results were assigned to each United States (U.S.) Zone Improvement Plan (ZIP) code based on the ZIP code location and corresponding Balancing Authority Area, natural gas basin, and Petroleum Administration for Defense Districts (PADDs). Additionally, previously developed models were utilized to develop future life cycle profiles. Projections were based on data available from the U.S. Energy Information Administration Annual Energy Outlook 2022 through 2050 (AEO 2022). Electricity LCA models were updated based on AEO 2022 projected annual generation mixes, while the natural gas baseline model was updated based on projected shares of natural gas types (conventional, shale, tight, and coalbed methane). Projections of crude oil production rates and export rates were applied to the petroleum baseline model in five-year increments to investigate their effects on the life cycle profile of fuel oil and propane. While only 100-year Global Warming Potential (GWP-100) with climate carbon feedback (CC-FB) and Cumulative Energy Demand are shown in Section 4: Results, the complete results, including Acidification Potential, Eutrophication Potential, Freshwater Ecotoxicity Potential, GWP-100 without inclusion of CC-FB, Human Health Impacts Potentials (Cancer, Non-Cancer), Ozone Depletion Potential, Particulate Matter Formation Potential, and Photochemical Smog Formation Potential, are tabulated for each ZIP code in the Excel worksheets that accompany this analysis. For the Excel spreadsheet tools associated with this report, please go to https://www.netl.doe.gov/energy-analysis/details?id=f8890fac-be55-44ac-aaa9-e2888bfabe93

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1989

A discrete decentralized variable structure robotic controller

A decentralized trajectory controller for robotic manipulators is designed and tested using a multiprocessor architecture and a PUMA 560 robot arm. The controller is made up of a nominal model-based component and a correction component based on a variable structure suction control approach. The second control component is designed using bounds on the difference between the used and actual values of the model parameters. Since the continuous manipulator system is digitally controlled along a trajectory, a discretized equivalent model of the manipulator is used to derive the controller. The motivation for decentralized control is that the derived algorithms can be executed in parallel using a distributed, relatively inexpensive, architecture where each joint is assigned a microprocessor. Nonlinear interaction and coupling between joints is treated as a disturbance torque that is estimated and compensated for.

Tumeh, Zuheir S.↗
NASA NTRS1991

Identification of linear multivariable systems from a single set of data by identification of observers with assigned real eigenvalues

A formulation is presented for identification of linear multivariable from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identifications, by extension of the repetition domain concept to include shifting time intervals. This method contrasts with existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate.

Phan, Minh↗
NASA NTRS1991

Identification of linear multivariable systems from a single set of data by identification of observers with assigned real eigenvalues

This paper presents a formulation for identification of linear multivariable systems from a single set of input-output data. The identification method is formulated with the mathematical framework of learning identification, by extension of the repetition domain concept to include shifting time intervals. This contrasts existing learning approaches that require data from multiple experiments. In this method, the system input-output relationship is expressed in terms of an observer, which is made asymptotically stable by an embedded real eigenvalue assignment procedure. Through this relationship, the Markov parameters of the observer are identified. The Markov parameters of the actual system are recovered from those of the observer, and then used to obtain a state space model of the system by standard realization techniques. The basic mathematical formulation is derived, and numerical examples presented to illustrate the proposed method.

Phan, Minh↗
NASA NTRS1992

Design of dissipative low-authority controllers using an eigensystem assignment technique

A novel method for the design of dissipative, low-authority controllers has been developed. The method uses a sequential approach along with eigensystem assignment to compute rate and position gain matrices that assign a number of closed-loop poles of the system to desired locations. Because the feedback gain matrices are symmetric and nonnegative definite, the closed-loop stability is always guaranteed regardless of the model order or parameter inaccuracies. The resulting (nominal) closed-loop system can have specified damping ratios for m modes, which makes the plant amenable to high-authority controller design, using methods such as LQG/LTR or H-infinity. A numerical example is worked out for a flexible structure in order to demonstrate the proposed technique.

Maghami, P. G.↗
NASA NTRS1990

Benzenoid hydrocarbons in space: The evidence and implications

Many different celestial objects emit an infrared spectrum which has been attributed to infrared fluorescence from a family of highly vibrationally excited benzenoid hydrocarbons referred to as polycyclic aromatic hydrocarbons (PAHs). The most intense emitters contain between 20 to 50 carbon atoms, although larger species also contribute to the emission. This assignment is based on a rough resemblance of the interstellar emission spectra to the vibrational spectra of PAHs and related materials such as chars and soots which contain PAH mixtures. The spectroscopic assignments of the features between 3200 and 700/cm are discussed in detail. Much laboratory work on PAHs which are larger than those previously studied, isolated, ionized and dehydrogenated is called for to fully exploit this model. As PAHs are thought to be ubiquitous throughout the interstellar medium and more abundant than all other known polyatomic, interstellar molecules, they possess great potential as important probes of conditions in many different kinds of astronomical objects. Conversely, astronomical observations are extending our knowledge of these exotic materials by probing regions in which some conditions may be impossible to duplicate in the laboratory.

Allamandola, Louis J.↗
NASA NTRS2010

Control of Risks Through the Use of Procedures: A Method for Evaluating the Change in Risk

This paper considers how procedures can be used to control risks faced by an organization and proposes a means of recognizing if a particular procedure reduces risk or contributes to the organization's exposure. The proposed method was developed out of the review of work documents and the governing procedures performed in the wake of the Columbia accident by NASA and the Space Shuttle prime contractor, United Space Alliance, LLC. A technique was needed to understand the rules, or procedural controls, in place at the time in the context of how important the role of each rule was. The proposed method assesses procedural risks, the residual risk associated with a hazard after a procedure's influence is accounted for, by considering each clause of a procedure as a unique procedural control that may be beneficial or harmful. For procedural risks with consequences severe enough to threaten the survival of the organization, the method measures the characteristics of each risk on a scale that is an alternative to the traditional consequence/likelihood couple. The dual benefits of the substitute scales are that they eliminate both the need to quantify a relationship between different consequence types and the need for the extensive history a probabilistic risk assessment would require. Control Value is used as an analog for the consequence, where the value of a rule is based on how well the control reduces the severity of the consequence when operating successfully. This value is composed of two parts: the inevitability of the consequence in the absence of the control, and the opportunity to intervene before the consequence is realized. High value controls will be ones where there is minimal need for intervention but maximum opportunity to actively prevent the outcome. Failure Likelihood is used as the substitute for the conventional likelihood of the outcome. For procedural controls, a failure is considered to be any non-malicious violation of the rule, whether intended or not. The model used for describing the Failure Likelihood considers how well a task was established by evaluating that task on five components. The components selected to define a well established task are: that it be defined, assigned to someone capable, that they be trained appropriately, that the actions be organized to enable proper completion and that some form of independent monitoring be performed. Validation of the method was based on the information provided by a group of experts in Space Shuttle ground processing when they were presented with 5 scenarios that identified a clause from a procedure. For each scenario, they recorded their perception of how important the associated rule was and how likely it was to fail. They then rated the components of Control Value and Failure Likelihood for all the scenarios. The order in which each reviewer ranked the scenarios Control Value and Failure Likelihood was compared to the order in which they ranked the scenarios for each of the associated components; inevitability and opportunity for Control Value and definition, assignment, training, organization and monitoring for Failure Likelihood. This order comparison showed how the components contributed to a relative relationship to the substitute risk element. With the relationship established for Space Shuttle ground processing, this method can be used to gauge if the introduction or removal of a particular rule will increase or decrease the .risk associated with the hazard it is intended to control.

Praino, Gregory T.↗
NASA NTRS1994

The Infrared Spectrum of H 2 S from 1 to 5 µm

The absorption spectra of H 2 S from 2000 to 11 147 cm -1 have been obtained with spectral resolutions of 0.006, 0.012, and 0.021 cm -1 and optical paths of 1.5 m to 433 m using the Fourier transform spectrometer at Kitt Peak National Observatory/National Solar Observatory. The 20 new vibrational bands have been assigned for the first time and 8 others re-analyzed so that accurate energy levels, band origins, and rotational parameters could be determined for a total of 29 states. Experimental band centers have been modeled by vibrational calculations. Line intensity measurements and analysis are in progress. A prediction of the 4 µm bands of H 2 S is currently available.

absorption↗
NASA NTRS2022

A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements

Precipitation type is a key parameter used for better retrieval of precipitation characteristics as well as to understand the cloud–convection–precipitation coupling processes. Ice crystals and water droplets inherently exhibit different characteristics in different precipitation regimes (e.g., convection, stratiform), which reflect on satellite remote sensing measurements that help us distinguish them. The Global Precipitation Measurement (GPM) Core Observatory’s microwave imager (GMI) and dual-frequency precipitation radar (DPR) together provide ample information on global precipitation characteristics. As an active sensor, the DPR provides an accurate precipitation type assignment, while passive sensors such as the GMI are traditionally only used for empirical understanding of precipitation regimes. Using collocated precipitation type flags from the DPR as the “truth”, this paper employs machine learning (ML) models to train and test the predictability and accuracy of using passive GMI-only observations together with ancillary information from a reanalysis and GMI surface emissivity retrieval products. Out of six ML models, four simple ones (support vector machine, neural network, random forest, and gradient boosting) and the 1-D convolutional neural network (CNN) model are identified to produce 90–94% prediction accuracy globally for five types of precipitation (convective, stratiform, mixture, no precipitation, and other precipitation), which is much more robust than previous similar effort. One novelty of this work is to introduce data augmentation (subsampling and bootstrapping) to handle extremely unbalanced samples in each category. A careful evaluation of the impact matrices demonstrates that the polarization difference (PD), brightness temperature (Tc) and surface emissivity at high-frequency channels dominate the decision process, which is consistent with the physical understanding of polarized microwave radiative transfer over different surface types, as well as in snow and liquid clouds with different microphysical properties. Furthermore, the view-angle dependency artifact that the DPR’s precipitation flag bears with does not propagate into the conical-viewing GMI retrievals. This work provides a new and promising way for future physics-based ML retrieval algorithm development.

machine learning/artificial intelligence↗
DOE OSTI2022

Devices and methods for increasing the speed and efficiency at which a computer is capable of modeling a plurality of random walkers using a particle method

A method for increasing a speed or energy efficiency at which a computer is capable of modeling a plurality of random walkers. The method includes defining a virtual space in which a plurality of virtual random walkers will move among different locations in the virtual space. The method also includes either assigning a corresponding set of ringed neurons in a spiking neural network to a corresponding virtual random walker, or assigning a corresponding set of ringed neurons to a point in the virtual space. Movement of a given virtual random walker is tracked by decoding differences between states of individual neurons in a corresponding given set of ringed neurons. A virtual random walk of the plurality of virtual random walkers is executed using the spiking neural network.

Aimone, James Bradley↗