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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Non-random distribution of DNA double-strand breaks induced by particle irradiation

Induction of DNA double-strand breaks (dsbs) in mammalian cells is dependent on the spatial distribution of energy deposition from the ionizing radiation. For high LET particle radiations the primary ionization sites occur in a correlated manner along the track of the particles, while for X-rays these sites are much more randomly distributed throughout the volume of the cell. It can therefore be expected that the distribution of dsbs linearly along the DNA molecule also varies with the type of radiation and the ionization density. Using pulsed-field gel and conventional gel techniques, we measured the size distribution of DNA molecules from irradiated human fibroblasts in the total range of 0.1 kbp-10 Mbp for X-rays and high LET particles (N ions, 97 keV/microns and Fe ions, 150 keV/microns). On a mega base pair scale we applied conventional pulsed-field gel electrophoresis techniques such as measurement of the fraction of DNA released from the well (FAR) and measurement of breakage within a specific NotI restriction fragment (hybridization assay). The induction rate for widely spaced breaks was found to decrease with LET. However, when the entire distribution of radiation-induced fragments was analysed, we detected an excess of fragments with sizes below about 200 kbp for the particles compared with X-irradiation. X-rays are thus more effective than high LET radiations in producing large DNA fragments but less effective in the production of smaller fragments. We determined the total induction rate of dsbs for the three radiations based on a quantitative analysis of all the measured radiation-induced fragments and found that the high LET particles were more efficient than X-rays at inducing dsbs, indicating an increasing total efficiency with LET. Conventional assays that are based only on the measurement of large fragments are therefore misleading when determining total dsb induction rates of high LET particles. The possible biological significance of this non-randomness for dsb induction is discussed.

NASA Discipline Radiation Health↗
NASA NTRS2005

Nonlinear Reduced Order Random Response Analysis of Structures With Shallow Curvature

The goal of this investigation is to further develop nonlinear modal numerical simulation methods for application to geometrically nonlinear response of structures with shallow curvature under random loadings. For reduced order analysis, the modal basis selection must be capable of reflecting the coupling in both the linear and nonlinear stiffness. For the symmetric shallow arch under consideration, four categories of modal basis functions are defined. Those having symmetric transverse displacements (ST modes) can be designated as transverse dominated (ST-T) modes and in-plane dominated (ST-I) modes. Those having anti-symmetric transverse displacements (AT modes) can similarly be designated as transverse dominated (AT-T) modes and in-plane dominated (AT-I) modes. The response of an aluminum arch under a uniformly distributed transverse random loading is investigated. Results from nonlinear modal simulations made using various modal bases are compared with those obtained from a numerical simulation in physical degrees-of-freedom. While inclusion of ST-T modes is important for all response regimes, it is found that the ST-I modes become increasingly important in the nonlinear response regime, and that AT-T and AT-I modes are critical in the autoparametric regime.

Przekop, Adam↗
NASA NTRS1994

Non-volatile magnetic random access memory

Improvements are made in a non-volatile magnetic random access memory. Such a memory is comprised of an array of unit cells, each having a Hall-effect sensor and a thin-film magnetic element made of material having an in-plane, uniaxial anisotropy and in-plane, bipolar remanent magnetization states. The Hall-effect sensor is made more sensitive by using a 1 m thick molecular beam epitaxy grown InAs layer on a silicon substrate by employing a GaAs/AlGaAs/InAlAs superlattice buffering layer. One improvement avoids current shunting problems of matrix architecture. Another improvement reduces the required magnetizing current for the micromagnets. Another improvement relates to the use of GaAs technology wherein high electron-mobility GaAs MESFETs provide faster switching times. Still another improvement relates to a method for configuring the invention as a three-dimensional random access memory.

Katti, Romney R.↗
NASA NTRS2006

Nonlinear Reduced Order Random Response Analysis of Structures with Shallow Curvature

The goal of this investigation is to further develop nonlinear modal numerical simulation methods for application to geometrically nonlinear response of structures with shallow curvature under random loadings. For reduced order analysis, the modal basis selection must be capable of reflecting the coupling in both the linear and nonlinear stiffness. For the symmetric shallow arch under consideration, four categories of modal basis functions are defined. Those having symmetric transverse displacements (ST modes) can be designated as transverse dominated (ST-T) modes and in-plane dominated (ST-I) modes. Those having anti-symmetric transverse displacements (AT modes) can similarly be designated as transverse dominated (AT-T) modes and in-plane dominated (AT-I) modes. The response of an aluminum arch under a uniformly distributed transverse random loading is investigated. Results from nonlinear modal simulations made using various modal bases are compared with those obtained from a numerical simulation in physical degrees-of-freedom. While inclusion of ST-T modes is important for all response regimes, it is found that the ST-I modes become increasingly important in the nonlinear response regime, and that AT-T and AT-I modes are critical in the autoparametric regime.

Przekop, Adam↗
NASA NTRS2010

Alternative Modal Basis Selection Procedures for Nonlinear Random Response Simulation

Three procedures to guide selection of an efficient modal basis in a nonlinear random response analysis are examined. One method is based only on proper orthogonal decomposition, while the other two additionally involve smooth orthogonal decomposition. Acoustic random response problems are employed to assess the performance of the three modal basis selection approaches. A thermally post-buckled beam exhibiting snap-through behavior, a shallowly curved arch in the auto-parametric response regime and a plate structure are used as numerical test articles. The results of the three reduced-order analyses are compared with the results of the computationally taxing simulation in the physical degrees of freedom. For the cases considered, all three methods are shown to produce modal bases resulting in accurate and computationally efficient reduced-order nonlinear simulations.

Przekop, Adam↗
NASA NTRS2004

A New Process for Fabricating Random Silicon Nanotips

An improved process for the fabrication of random arrays of silicon nanotips has been demonstrated to be feasible. Relative to other such processes, this process offers advantages of low cost and simplicity. Moreover, this process can readily be combined with other processes used to fabricate integrated circuits and other monolithic silicon structures. Arrays of silicon nanotips are subjects of research and development efforts directed toward utilizing them as field emitters in flat-panel displays, vacuum microelectronics, and microwave devices. Other silicon-nanotip-fabrication processes developed thus far predominantly include lithography, etching, and/or elaborate deposition steps followed by oxide sharpening steps and are both process intensive as well as expensive. In addition to being cheaper and simpler, the present process can efficiently produce silicon nanotips that range in height from a few microns to several tens of microns and are distributed over large areas. The process mentioned here can be summarized as consisting of (1) the growth of micro-etch masks on a silicon substrate, followed by (2) etching away of the masks, along with some of the substrate, to make an array of sharp tips. In the first step of the process, a cleaned silicon substrate is subjected to reactive ion etching (RIE) in a certain mixture of oxygen and carbon tetrafluoride under radio-frequency excitation. This process step results in the growth of fluorine based compounds in the form of stumps randomly distributed on the substrate. These stumps are known in the art as polymer RIE grass. The dimensions of these stumps are of the order of hundreds of nanometers, the exact values depending on process time and gas composition. The areal density of the stumps decreases with increasing process time as they grow and merge with neighboring stumps. These stumps constitute the micro-etch masks for the next step of the process. In the second step of the process, the substrate covered with the microetch masks is subjected to deep reactive ion etching (DRIE) process, which consists of cycles of reactive ion etching alternating with passivation (the Bosch process). The gas used in the etching substeps is sulfur hexafluoride (SF6); the gas used in the passivation substeps is octafluorocyclobutane (C4F8). The portions of the substrate directly under the RIE grass stubs are etched more slowly than are the portions between the stubs. Hence, what remains at the end of the process, after the stubs and parts of the substrate have been etched away, are silicon spikes where the stubs were (see figure). In a variation of the process, one starts with a silicon or silicon-on-insulator substrate with the intent to etch through the full thickness of the substrate. That is to say, one chooses the thickness so that the DRIE step releases individual nanotips. Such individual silicon nanotips may have utility as microscopic probes in biomedical applications.

Manohara, Harish↗
NASA NTRS2011

Direct Simulation of Multiple Scattering by Discrete Random Media Illuminated by Gaussian Beams

The conventional orientation-averaging procedure developed in the framework of the superposition T-matrix approach is generalized to include the case of illumination by a Gaussian beam (GB). The resulting computer code is parallelized and used to perform extensive numerically exact calculations of electromagnetic scattering by volumes of discrete random medium consisting of monodisperse spherical particles. The size parameters of the scattering volumes are 40, 50, and 60, while their packing density is fixed at 5%. We demonstrate that all scattering patterns observed in the far-field zone of a random multisphere target and their evolution with decreasing width of the incident GB can be interpreted in terms of idealized theoretical concepts such as forward-scattering interference, coherent backscattering (CB), and diffuse multiple scattering. It is shown that the increasing violation of electromagnetic reciprocity with decreasing GB width suppresses and eventually eradicates all observable manifestations of CB. This result supplements the previous demonstration of the effects of broken reciprocity in the case of magneto-optically active particles subjected to an external magnetic field.

Mackowski, Daniel W.↗
NASA NTRS2011

Cloud Macroscopic Organization: Order Emerging from Randomness

Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.

Yuan, Tianle↗
NASA NTRS2011

A Procedure for Accurately Measuring the Shaker Overturning Moment During Random Vibration Tests

Motivation: For large system level random vibration tests, there may be some concerns about the shaker's capability for the overturning moment. It is the test conductor's responsibility to predict and monitor the overturning moment during random vibration tests. If the predicted moment is close to the shaker's capability, test conductor must measure the instantaneous moment at low levels and extrapolate to higher levels. That data will be used to decide whether it is safe to proceed to the next test level. Challenge: Kistler analog formulation for computing the real-time moment is only applicable to very limited cases in which we have 3 or 4 load cells installed at shaker interface with hardware. Approach: To overcome that limitation, a simple procedure was developed for computing the overturning moment time histories using the measured time histories of the individual load cells.

predict overturning↗
NASA NTRS2012

Alternative Modal Basis Selection Procedures For Reduced-Order Nonlinear Random Response Simulation

Three procedures to guide selection of an efficient modal basis in a nonlinear random response analysis are examined. One method is based only on proper orthogonal decomposition, while the other two additionally involve smooth orthogonal decomposition. Acoustic random response problems are employed to assess the performance of the three modal basis selection approaches. A thermally post-buckled beam exhibiting snap-through behavior, a shallowly curved arch in the auto-parametric response regime and a plate structure are used as numerical test articles. The results of a computationally taxing full-order analysis in physical degrees of freedom are taken as the benchmark for comparison with the results from the three reduced-order analyses. For the cases considered, all three methods are shown to produce modal bases resulting in accurate and computationally efficient reduced-order nonlinear simulations.

Przekop, Adam↗
NASA NTRS2011

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

Whiteman, David N.↗
NASA NTRS2012

Using Random Forest Models to Predict Organizational Violence

We present a methodology to access the proclivity of an organization to commit violence against nongovernment personnel. We fitted a Random Forest model using the Minority at Risk Organizational Behavior (MAROS) dataset. The MAROS data is longitudinal; so, individual observations are not independent. We propose a modification to the standard Random Forest methodology to account for the violation of the independence assumption. We present the results of the model fit, an example of predicting violence for an organization; and finally, we present a summary of the forest in a "meta-tree,"

Levine, Burton↗
NASA NTRS2013

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

vertical profiles↗
NASA NTRS2015

Random Vibration Testing of Advanced Wet Tantalum Capacitors

Advanced wet tantalum capacitors allow for improved performance of power supply systems along with substantial reduction of size and weight of the systems that is especially beneficial for space electronics. Due to launch-related stresses, acceptance testing of all space systems includes random vibration test (RVT). However, many types of advanced wet tantalum capacitors cannot pass consistently RVT at conditions specified in MIL-PRF-39006, which impedes their use in space projects. This requires a closer look at the existing requirements, modes and mechanisms of failures, specifics of test conditions, and acceptance criteria. In this work, different lots of advanced wet tantalum capacitors from four manufacturers have been tested at step stress random vibration conditions while their currents were monitored before, during, and after the testing. It has been shown that the robustness of the parts and their reliability are mostly due to effective self-healing processes and limited current spiking or minor scintillations caused by RVT do not increase the risk of failures during operation. A simple model for scintillations events has been used to simulate current spiking during RVT and optimize test conditions. The significance of scintillations and possible effects of gas generation have been discussed and test acceptance criteria for limited current spiking have been suggested.

cracking↗
NASA NTRS2015

Random Vibration Testing of Advanced Wet Tantalum Capacitors

Advanced wet tantalum capacitors allow for improved performance of power supply systems along with substantial reduction of size and weight of the systems that is especially beneficial for space electronics. Due to launch-related stresses, acceptance testing of all space systems includes random vibration test (RVT). However, many types of advanced wet tantalum capacitors cannot pass consistently RVT at conditions specified in MIL-PRF-39006, which impedes their use in space projects. This requires a closer look at the existing requirements, modes and mechanisms of failures, specifics of test conditions, and acceptance criteria. In this work, different lots of advanced wet tantalum capacitors from four manufacturers have been tested at step stress random vibration conditions while their currents were monitored before, during, and after the testing. It has been shown that the robustness of the parts and their reliability are mostly due to effective self-healing processes and limited current spiking or minor scintillations caused by RVT do not increase the risk of failures during operation. A simple model for scintillations events has been used to simulate current spiking during RVT and optimize test conditions. The significance of scintillations and possible effects of gas generation have been discussed and test acceptance criteria for limited current spiking have been suggested.

cracking↗
NASA NTRS2015

Random Vibration Testing of Advanced Wet Tantalum Capacitors

Advanced wet tantalum capacitors allow for improved performance of power supply systems along with substantial reduction of size and weight of the systems that is especially beneficial for space electronics. Due to launch-related stresses, acceptance testing of all space systems includes random vibration test (RVT). However, many types of advanced wet tantalum capacitors cannot pass consistently RVT at conditions specified in MIL-PRF-39006, which impedes their use in space projects. This requires a closer look at the existing requirements, modes and mechanisms of failures, specifics of test conditions, and acceptance criteria. In this work, different lots of advanced wet tantalum capacitors from four manufacturers have been tested at step stress random vibration conditions while their currents were monitored before, during, and after the testing. It has been shown that the robustness of the parts and their reliability are mostly due to effective self-healing processes and limited current spiking or minor scintillations caused by RVT do not increase the risk of failures during operation. A simple model for scintillations events has been used to simulate current spiking during RVT and optimize test conditions. The significance of scintillations and possible effects of gas generation have been discussed and test acceptance criteria for limited current spiking have been suggested.

wet tantalum capacitors↗
NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 2

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.

Crespo, Luis G.↗
NASA NTRS2015

Random Predictor Models for Rigorous Uncertainty Quantification: Part 1

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.

Crespo, Luis G.↗