Results for “Power Iteration” — Page 16

NASA NTRS1992

A transient FETI methodology for large-scale parallel implicit computations in structural mechanics

Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because explicit schemes are also easier to parallelize than implicit ones. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet -- and perhaps will never -- be offset by the speed of parallel hardware. Therefore, it is essential to develop efficient and robust alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating low-frequency dynamics. Here we present a domain decomposition method for implicit schemes that requires significantly less storage than factorization algorithms, that is several times faster than other popular direct and iterative methods, that can be easily implemented on both shared and local memory parallel processors, and that is both computationally and communication-wise efficient. The proposed transient domain decomposition method is an extension of the method of Finite Element Tearing and Interconnecting (FETI) developed by Farhat and Roux for the solution of static problems. Serial and parallel performance results on the CRAY Y-MP/8 and the iPSC-860/128 systems are reported and analyzed for realistic structural dynamics problems. These results establish the superiority of the FETI method over both the serial/parallel conjugate gradient algorithm with diagonal scaling and the serial/parallel direct method, and contrast the computational power of the iPSC-860/128 parallel processor with that of the CRAY Y-MP/8 system.

Farhat, Charbel↗

NASA NTRS2020

Predicting Gate Conflicts using NASA ATD-2 Fused Data Sources

The modern day National Airspace System (NAS) is powered by System Wide Information Management (SWIM) which is a real-time digital data sharing infrastructure that provides a high fidelity view of the lifecycle of a flight. The newly available data within the SWIM feeds can be leveraged to help drive efficiencies in the NAS. In this talk, we investigate the gate conflict prediction problem as a concrete use case which could help drive efficiencies. We begin with a high level description of NASA's Airspace Technology Demonstration 2 which is built upon the real-time SWIM feeds and produces the data used in our investigation. We model gate conflicts as a regression problem and describe the iterative process of model building, model validation, and evaluation used to assess the efficacy of our approach.

Coupe, William J.↗

NASA NTRS2020

Enabled International Collaborations in EDL: Lessons Learned and Recommendations

The modern day National Airspace System (NAS) is powered by System Wide Information Management (SWIM) which is a real-time digital data sharing infrastructure that provides a high fidelity view of the lifecycle of a flight. The newly available data within the SWIM feeds can be leveraged to help drive efficiencies in the NAS. In this talk, we investigate the gate conflict prediction problem as a concrete use case which could help drive efficiencies. We begin with a high level description of NASA's Airspace Technology Demonstration 2 which is built upon the real-time SWIM feeds and produces the data used in our investigation. We model gate conflicts as a regression problem and describe the iterative process of model building, model validation, and evaluation used to assess the efficacy of our approach.

William J. Coupe↗

NASA NTRSDate not supplied

Metallic Powder Core Tubular Wire (PCTW) Development for Additive Manufacturing

NASA Langley Research Center (LaRC) in Hampton, VA, and the Center for Welding, Joining, and Coating Research (CWJCR) in the Department of Metallurgical and Materials Engineering at the Colorado School of Mines (CSM) in Golden, CO, have collaborated for nearly fifteen years to develop metallic powder core tubular wire (PCTW) feedstock for additive manufacturing (AM) using electron beam deposition. The motivation for this development was to offset dealloying observed during deposition of titanium and aluminum alloy solid wire feedstock in the LaRC electron beam freeform fabrication (EBF3) system and to explore novel alloy compositions by tailoring the powder fill. EBF3 is a fusion-based AM process that is performed under vacuum and is consequently prone to vaporization loss of low vapor pressure alloying elements. Research spanning four graduate student research projects succeeded in developing the basic methodology to fabricate PCTW, the mass balance equations used to define the powder fill, microstructure control through particulate inoculation, and the feasibility of producing metal matrix composite materials. Metallic PCTW is comprised of a thin foil sheath wrapped around a powder blend. Fabrication of PCTW at CSM was accomplished using a tubular wire mill system to first bend a flat strip into a u-shaped cross section, deposit a powder fill, create a lap joint to seal the wire, and draw to final diameter. Powder management systems were developed to ensure uniform mixing of powder constituents and identify feed rates for optimum fill ratios. Processing parameters were successfully developed for titanium and aluminum alloy sheaths to account for material work hardening during drawing. Mass balance equations were developed to account for compositional contributions of the sheath and powder fill. PCTW composition can be adjusted through selection of the sheath or powder materials. PCTWs were successfully developed to offset Al loss in deposits of Ti-6-4 and Mg loss in Al 6061, resulting in deposits that were within the composition limits for each material. Ti-6-4 deposits were fabricated using PCTW comprised of commercially pure (CP) titanium sheath and a fill of pre-alloyed Ti-6-4 powder with additions of elemental Al and V powders. Additions of both elements were required to account for the CP Ti from the sheath, and Al was further enhanced to offset documented losses in EBF3 deposits. For Al 6061 deposits, composition was modulated through the choice of sheath material. The PCTW was made using an Al 5052 sheath to supplement Mg content and a fill composition of pre-alloyed 6061 powder with additions of Si and Cu.The slower solidification rate of the EBF3 process compared with laser powder bed fusion processes can lead to coarse-grained microstructures and mechanical property anisotropy. EBF3deposits of Ti-6-4 exhibited large epitaxially grown β grains, which result in degraded mechanical properties in the deposition direction. Microstructure refinement was achieved through a combination of electron beam modulation and the use of a PCTW designed for Ti-6-4 deposits and modified by the addition of powder made from Fe and B. Resulting deposits exhibited reductions in β grain size, α phase colony intercept length and lath width, and an increased volume fraction of β phase. The mechanism of microstructure refinement was related to precipitation of boride particles. Hardness testing confirmed that mechanical property anisotropy was reduced and an overall increase in hardness was achieved.Metal matrix composite (MMC) materials offer strength and stiffness benefits over unreinforced materials. Two methods were investigated using PCTW technology for producing Al 6061 basedMMC materials; the direct addition of SiC reinforcing particles and the in-situ generation of reinforcements through reaction synthesis of precursor powders. Al 6061 based MMCs reinforced with SiC exhibited particle clustering and formation of aluminum carbides during deposition. The application of a Ni coating to the SiC particles prior to incorporation into the powder fill eliminated aluminum carbide formation and aided particle distribution during deposition. Modulation of beam focus and power further reduced aluminum carbide formation and aided particle distribution. In reaction synthesis, precursor additions undergo an exothermic reaction during deposition to form new ceramic products, generally of finer scale than the initial precursor components. The product phases provide reinforcement in the MMC and act as nucleation sites during solidification, resulting in grain refinement, improved mechanical properties, and reduced susceptibility to solidification cracking. Higher tensile strength and stiffness were demonstrated in Al 6061 based MMCs with 2 vol% reinforcement. These combined research efforts demonstrate the potential of PCTW technology for customizing of alloy composition and achieving microstructure control. A manufacturing process for titanium- and aluminum-based PCTWs was developed based on iterative design, theoretical calculations, and empirical data. PCTW technology successfully mitigated Al loss from Ti-6-4 and Mg loss in Al 6061, resulted in grain refinement in Ti-6-4, and demonstrated fabrication of Al based MMCs

Marcia S Domack↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. These ambitious goals will require significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities. These constraints make it absolutely necessary to develop transformative solutions using new technologies. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses the gap Medical-701 within the Inflight Medical Conditions risk: Enhance medical capabilities within an exploration medical system. For long-duration, deep space missions, computational and data resources will play an important role in maintaining crew health, wellness and performance where the crew will need to be more self-reliant. The aim of the CDS project is to develop and provide recommended requirements for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. The CDSS is envisioned as a software-based tool that will augment a crewmembers’ knowledge, skills and abilities to assist in decision-making and crew health and performance (CHP) management thus increasing CHP systems capabilities. The human interface will be context aware and lessen the cognitive load to assimilate and use information as well as combine large disparate data sets in such a manner that provides the crew with actionable insight to decisions related to crew medical, health and performance management. Crew autonomy will be provided through a CDS that presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. The CDS project addresses the need for crew members to operate independently during long duration space exploration missions that require medical Levels of Care (LoC) V, the highest level specified by NASA-STD-3001 and described in more detail by the ExMC interpretation of LoC document (NASA/TM-2017-219290), where significant changes to in-flight and habitat medical care necessitate increasing crew autonomy in decision making and task performance. The CDS project will develop and test a series of iterative and increasingly more complex system prototypes. These annual demonstrations of the data system integration with the crew health and performance domain will inform exploration medical system requirements for an on-board Clinical Decision Support System (CDSS) through a series of use cases that guide CDS prototype functionality. CDS concepts are based on ExMC Concept of Operations documents (presented separately) and will highlight architecture extensibility to other more complex analyses and tests using core crew health and performance integrated data management, processing and visualization capabilities. This approach also establishes how externally developed analyses and approaches could be added to expand a clinical decision support system and thus highlight how a comprehensive system can be commercially and/or globally developed. The CDS project will build upon the concept of an integrated data management approach based on the Medical Data Architecture (MDA) project to more fully address challenges associated with in-flight and habitat medical, health and performance care due to constraints on mass, volume, power, crew time and medical evacuation capabilities required for medical LoC V. These requirements will be derived through systems engineering approaches and software prototype developments over the course of the multi-year CDS project to address crew health and performance decision-making and task performance, often autonomously executed by the crew, in a manner that is consistent with the appropriate medical level of care for the mission. This presentation will provide an overview of the vision for the CDS project and highlight the initial accomplishments in project planning, implementation and requirements identification in fiscal year 2020.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support - Overview and Update

We are entering a new era in space exploration to return to the moon and explore Mars. These ambitious goals will require significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities. These constraints make it absolutely necessary to develop transformative solutions using new technologies. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses the gap Medical-701 within the Inflight Medical Conditions risk: Enhance medical capabilities within an exploration medical system. For long-duration, deep space missions, computational and data resources will play an important role in maintaining crew health, wellness and performance where the crew will need to be more self-reliant. The aim of the CDS project is to develop and provide recommended requirements for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. The CDSS is envisioned as a software-based tool that will augment a crewmembers’ knowledge, skills and abilities to assist in decision-making and crew health and performance (CHP) management thus increasing CHP systems capabilities. The human interface will be context aware and lessen the cognitive load to assimilate and use information as well as combine large disparate data sets in such a manner that provides the crew with actionable insight to decisions related to crew medical, health and performance management. Crew autonomy will be provided through a CDS that presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. The CDS project addresses the need for crew members to operate independently during long duration space exploration missions that require medical Levels of Care (LoC) V, the highest level specified by NASA-STD-3001 and described in more detail by the ExMC interpretation of LoC document (NASA/TM-2017-219290), where significant changes to in-flight and habitat medical care necessitate increasing crew autonomy in decision making and task performance. The CDS project will develop and test a series of iterative and increasingly more complex system prototypes. These annual demonstrations of the data system integration with the crew health and performance domain will inform exploration medical system requirements for an on-board Clinical Decision Support System (CDSS) through a series of use cases that guide CDS prototype functionality. CDS concepts are based on ExMC Concept of Operations documents (presented separately) and will highlight architecture extensibility to other more complex analyses and tests using core crew health and performance integrated data management, processing and visualization capabilities. This approach also establishes how externally developed analyses and approaches could be added to expand a clinical decision support system and thus highlight how a comprehensive system can be commercially and/or globally developed. The CDS project will build upon the concept of an integrated data management approach based on the Medical Data Architecture (MDA) project to more fully address challenges associated with in-flight and habitat medical, health and performance care due to constraints on mass, volume, power, crew time and medical evacuation capabilities required for medical LoC V. These requirements will be derived through systems engineering approaches and software prototype developments over the course of the multi-year CDS project to address crew health and performance decision-making and task performance, often autonomously executed by the crew, in a manner that is consistent with the appropriate medical level of care for the mission. This presentation will provide an overview of the vision for the CDS project and highlight the initial accomplishments in project planning, implementation and requirements identification in fiscal year 2020.

clinical decision support system↗

NASA NTRS2002

Process for a High Efficiency Class D Microwave Power Amplifier Operating in the S-Band

A process and product providing a High Efficiency Microwave Power Amplifier (HEMPA) which propagates S-Band microwave frequency square waves; utilizing a program simulating FETs at high DC-to-RF efficiencies, which analyses linear elements of selected FETs in a frequency domain, and non-linear elements of the FETs in a time domain, and converts the time domain values into the frequency domain, and performs DC and S-parameter simulated measurements based on predefined data for each FET. Individual FET parameters are extracted and isolated by converting the S-parameters to admittance or impedance parameters to derive FET models for each FET, which the program uses to provide a final output of a HEMPA circuit based on iterative simulations of an amplification circuit utilizing microwave topology and frequencies. Iterative simulations of the amplification circuit analyze output values of a plurality of cascaded stages of the FETs, which are arranged in a push-pull configuration.

William Herbert Sims, III↗

NASA NTRSDate not supplied

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

NASA NTRSDate not supplied

Health Monitoring and Prognostics for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously approved and published information.

Systems Health Managent↗

NASA NTRS1993

Propagation of high frequency jet noise using geometric acoustics

Spherical directivity of noise radiated from a convecting quadrupole source embedded in an arbitrary spreading jet is obtained by ray-tracing methods of geometrical acoustics. The six propagation equations are solved in their general form in a rectangular coordinate system. The noise directivity in the far field is calculated by applying an iteration scheme that finds the required radiation angles at the source resulting in propagation through a given observer point. Factors influencing the zone of silence are investigated. The caustics of geometrical acoustics and the exact locations where it forms is demonstrated by studying the variation in ray tube area obtained from transport equation. For a ring source convecting along the center-axis of an axisymmetric jet, the polar directivity of the radiated noise is obtained by an integration with respect to azimuthal directivity of compact quadrupole sources distributed on the ring. The Doppler factor is shown to vary slightly from point to point on the ring. Finally the scaling of the directivity pattern with power -3 of Doppler factor is investigated and compared with experimental data.

Khavaran, A.↗

NASA NTRS1993

Propagation of high frequency jet noise using geometric acoustics

Spherical directivity of noise radiated from a convecting quadrupole source embedded in an arbitrary spreading jet is obtained by ray-tracing methods of geometrical acoustics. The six propagation equations are solved in their general form in a rectangular coordinate system. The noise directivity in the far field is calculated by applying an iteration scheme that finds the required radiation angles at the source resulting in propagation through a given observer point. Factors influencing the zone of silence are investigated. The caustics of geometrical acoustics and the exact locations where it forms is demonstrated by studying the variation in ray tube area obtained from transport equation. For a ring source convecting along the center-axis of an axisymmetric jet, the polar directivity of the radiated noise is obtained by an integration with respect to azimuthal directivity of compact quadrupole sources distributed on the ring. The Doppler factor is shown to vary slightly from point to point on the ring. Finally the scaling of the directivity pattern with power -3 of Doppler factor is investigated and compared with experimental data.

Khavaran, A.↗

NASA NTRS1998

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes

A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and sectionalization of trellises. Chapter 7 discusses trellis decomposition and subtrellises for low-weight codewords. Chapter 8 first presents well known methods for constructing long powerful codes from short component codes or component codes of smaller dimensions, and then provides methods for constructing their trellises which include Shannon and Cartesian product techniques. Chapter 9 deals with convolutional codes, puncturing, zero-tail termination and tail-biting.Chapters 10 through 13 present various trellis-based decoding algorithms, old and new. Chapter 10 first discusses the application of the well known Viterbi decoding algorithm to linear block codes, optimum sectionalization of a code trellis to minimize computation complexity, and design issues for IC (integrated circuit) implementation of a Viterbi decoder. Then it presents a new decoding algorithm for convolutional codes, named Differential Trellis Decoding (DTD) algorithm. Chapter 12 presents a suboptimum reliability-based iterative decoding algorithm with a low-weight trellis search for the most likely codeword. This decoding algorithm provides a good trade-off between error performance and decoding complexity. All the decoding algorithms presented in Chapters 10 through 12 are devised to minimize word error probability. Chapter 13 presents decoding algorithms that minimize bit error probability and provide the corresponding soft (reliability) information at the output of the decoder. Decoding algorithms presented are the MAP (maximum a posteriori probability) decoding algorithm and the Soft-Output Viterbi Algorithm (SOVA) algorithm. Finally, the minimization of bit error probability in trellis-based MLD is discussed.

Lin, Shu↗

NASA NTRS1975

Stepwise Iterative Fourier Transform: The SIFT

A program, designed specifically to study the respective effects of some common data problems on results obtained through stepwise iterative Fourier transformation of synthetic data with known waveform composition, was outlined. Included in this group were the problems of gaps in the data, different time-series lengths, periodic but nonsinusoidal waveforms, and noisy (low signal-to-noise) data. Results on sinusoidal data were also compared with results obtained on narrow band noise with similar characteristics. The findings showed that the analytic procedure under study can reliably reduce data in the nature of (1) sinusoids in noise, (2) asymmetric but periodic waves in noise, and (3) sinusoids in noise with substantial gaps in the data. The program was also able to analyze narrow-band noise well, but with increased interpretational problems. The procedure was shown to be a powerful technique for analysis of periodicities, in comparison with classical spectrum analysis techniques. However, informed use of the stepwise procedure nevertheless requires some background of knowledge concerning characteristics of the biological processes under study.

Benignus, V. A.↗

NASA NTRS1990

Fast secant methods for the iterative solution of large nonsymmetric linear systems

A family of secant methods based on general rank-1 updates was revisited in view of the construction of iterative solvers for large non-Hermitian linear systems. As it turns out, both Broyden's good and bad update techniques play a special role, but should be associated with two different line search principles. For Broyden's bad update technique, a minimum residual principle is natural, thus making it theoretically comparable with a series of well known algorithms like GMRES. Broyden's good update technique, however, is shown to be naturally linked with a minimum next correction principle, which asymptotically mimics a minimum error principle. The two minimization principles differ significantly for sufficiently large system dimension. Numerical experiments on discretized partial differential equations of convection diffusion type in 2-D with integral layers give a first impression of the possible power of the derived good Broyden variant.

Deuflhard, Peter↗

NASA NTRS1992

Thermal mechanical analysis of sprag clutches

Work done at Case Western Reserve University on the Thermal Mechanical analysis of sprag helicopter clutches is reported. The report is presented in two parts. The first part is a description of a test rig for the measurement of the heat generated by high speed sprag clutch assemblies during cyclic torsional loading. The second part describes a finite element modeling procedure for sliding contact. The test rig provides a cyclic torsional load of 756 inch-pounds at 5000 rpm using a four-square arrangement. The sprag clutch test unit was placed between the high speed pinions of the circulating power loop. The test unit was designed to have replaceable inner ad outer races, which contain the instrumentation to monitor the sprag clutch. The torque loading device was chosen to be a water cooled magnetic clutch, which is controlled either manually or through a computer. In the second part, a Generalized Eulerian-Lagrangian formulation for non-linear dynamic problems is developed for solid materials. This formulation is derived from the basic laws and axioms of continuum mechanics. The novel aspect of this method is that we are able to investigate the physics in the spatial region of interest as material flows through it without having to follow material points. A finite element approximation to the governing equations is developed. Iterative Methods for the solution of the discrete finite element equations are explored. A FORTRAN program to implement this formulation is developed and a number of solutions to problems of sliding contact are presented.

Mullen, Robert L.↗

NASA NTRSDate not supplied

ELISA: A Tool for Optimization of Rotor Hover Performance at Low Reynolds Number in the Mars Atmosphere

The Evolutionary aLgorithm for Iterative Studies of Aeromechanics (ELISA) was developed in support of the Rotorcraft Optimization for the Advancement of Mars eXploration (ROAMX) project. ELISA was developed to enable aerodynamic rotor hover optimization for low Reynolds number flows in the Mars atmosphere. The first objective of the algorithm allows for unconventional airfoil parameterization and multi-objective airfoil geometry optimization using OVERFLOW. The Pareto-optimal airfoil sets are converted to a set of Pareto-optimal airfoil decks, providing the lowest drag air foil geometry for each angle of attack, removing the need to arbitrarily select the airfoils to be used in the rotor optimization. The second objective allows for rotor geometry optimization with simultaneous maximization of blade loading and minimization of rotor power using the comprehensive analysis CAMRADII. The result is a Pareto-optimal rotor set, providing the lowest power rotor for each attainable blade loading, and one of the first tools for hover-optimized rotors for high-subsonic low Reynolds number conditions. The airfoil thickness can be modified after the airfoil optimization is complete, allowing for a post-airfoil-optimization adjustment of blade thickness to facilitate conforming to external structural analyses requirements. The relevance of the code is demonstrated with case studies for the ROAMX rotor optimization for Ingenuity-sized single rotors in the Mars atmosphere, a performance study optimizing the chord and twist of Ingenuity’s coaxial rotor resulting in the Sample Recovery Helicopters candidate rotor, and high-subsonic low Reynolds number airfoil optimization providing novel insights for higher-efficiency low Reynolds number airfoil geometries and flow physics.

ELISA↗

NASA NTRS2013

Motorized Beam Alignment of a Commercial X-ray Diffractometer

X-ray diffraction (XRD) is a powerful analysis method that allows researchers to noninvasively probe the crystalline structure of a material. This includes the ability to determine the crystalline phases present, quantify surface residual stresses, and measure the distribution of crystallographic orientations. The Structures and Materials Division at the NASA Glenn Research Center (GRC) heavily uses the on-site XRD lab to characterize advanced metal alloys, ceramics, and polymers. One of the x-ray diffractometers in the XRD lab (Bruker D8 Discover) uses three different x-ray tubes (Cu, Cr, and Mn) for optimal performance over numerous material types and various experimental techniques. This requires that the tubes be switched out and aligned between experiments. This alignment maximizes the x-ray tube s output through an iterative process involving four set screws. However, the output of the x-ray tube cannot be monitored during the adjustment process due to standard radiation safety engineering controls that prevent exposure to the x-ray beam when the diffractometer doors are open. Therefore, the adjustment process is a very tedious series of blind adjustments, each followed by measurement of the output beam using a PIN diode after the enclosure doors are shut. This process can take up to 4 hr to perform. This technical memorandum documents an in-house project to motorize this alignment process. Unlike a human, motors are not harmed by x-ray radiation of the energy range used in this instrument. Therefore, using motors to adjust the set screws will allow the researcher to monitor the x-ray tube s output while making interactive adjustments from outside the diffractometer. The motorized alignment system consists of four motors, a motor controller, and a hand-held user interface module. Our goal was to reduce the alignment time to less than 30 min. The time available was the 10-week span of the Lewis' Educational and Research Collaborative Internship Project (LERCIP) summer internship program and the budget goal was $1200. In this report, we will describe our motorization design and discuss the results of its implementation.

Van Zandt, Noah R.↗

NASA NTRS2004

Serial-Turbo-Trellis-Coded Modulation with Rate-1 Inner Code

Serially concatenated turbo codes have been proposed to satisfy requirements for low bit- and word-error rates and for low (in comparison with related previous codes) complexity of coding and decoding algorithms and thus low complexity of coding and decoding circuitry. These codes are applicable to such high-level modulations as octonary phase-shift keying (8PSK) and 16-state quadrature amplitude modulation (16QAM); the signal product obtained by applying one of these codes to one of these modulations is denoted, generally, as serially concatenated trellis-coded modulation (SCTCM). These codes could be particularly beneficial for communication systems that must be designed and operated subject to limitations on bandwidth and power. Some background information is prerequisite to a meaningful summary of this development. Trellis-coded modulation (TCM) is now a well-established technique in digital communications. A turbo code combines binary component codes (which typically include trellis codes) with interleaving. A turbo code of the type that has been studied prior to this development is composed of parallel concatenated convolutional codes (PCCCs) implemented by two or more constituent systematic encoders joined through one or more interleavers. The input information bits feed the first encoder and, after having been scrambled by the interleaver, enter the second encoder. A code word of a parallel concatenated code consists of the input bits to the first encoder followed by the parity check bits of both encoders. The suboptimal iterative decoding structure for such a code is modular, and consists of a set of concatenated decoding modules one for each constituent code connected through an interleaver identical to the one in the encoder side. Each decoder performs weighted soft decoding of the input sequence. PCCCs yield very large coding gains at the cost of a reduction in the data rate and/or an increase in bandwidth.

Divsalar, Dariush↗