Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “accelerator physics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

An Electric Propulsion "Shepherd" for Active Debris Removal that Utilizes Ambient Gas as Propellant

There is a growing consensus among the space debris technical community that limiting the long ]term growth of debris in Low-Earth Orbit (LEO) requires that space users limit the accumulation of mass in orbit. This is partially accomplished by mitigation measures for current and future LEO systems, but there is now interest in removing mass that has already accumulated in LEO from more than 50 years of space activity (termed "Active Debris Removal", or ADR). Many ADR proposals face complex technical issues of how to grapple with uncooperative targets. Some researchers have suggested the use of conventional ion thrusters to gently "blow" on objects to gradually change their orbits, without ever having to come into physical contact with the target. The chief drawback with these methods is the cost per object removed. Typically, a space "tug" or an ion-drive "shepherd" can only remove a few objects per mission due to limited propellant. Unless a costeffective way that removes tens of objects per mission can be found, it is not clear that any of the ideas so far proposed will be economically viable. In this paper, a modified version of the ion-drive "shepherd" is proposed that uses ambient atmospheric gases in LEO as propellant for the ion drives. This method has the potential to greatly extend the operational lifetime of an ADR mission, as the only mission limit is the lifetime of the components of the satellite itself, not on its fuel supply. An ambient-gas ion-drive "shepherd" would the local atmospheric drag on an object by ionizing and accelerating the ambient gas the target would have encountered anyway, thereby hastening its decay. Also, the "shepherd" satellite itself has a great deal of flexibility to maneuver back to high altitude and rendezvous with its next target using the ion drive not limited by fuel supply. However, the amount of available ambient gas is closely tied to the altitude of the spacecraft. It may be possible to use a "hybrid" approach that supplements high-altitude ion-drive operations with stored gas, and transitions to ambient gas at lower altitudes. This paper will include realistic numbers on the estimated times needed to deorbit objects from different orbit regimes using drives that either partially or completely take advantage of ambient gas. It will conclude with recommendations on whether this is a viable candidate for future ADR efforts.

Matney, Mark J.↗
NASA NTRS2023

Prediction of Stiffness and Fatigue Lives of Polymer Matrix Composite Laminates Using Artificial Neural Networks

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, both Python and MATLAB-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been developed for both platforms. Results show that the both neural net types can provide an excellent estimate of initial stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminate. RNNs are better able to capture the shape of the fatigue curve of a laminate. This tool can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. The associated surrogate models could also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make multiscale analyses a viable industrial tool for large scale structural problems.

Composite↗
NASA NTRSDate not supplied

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗
NASA NTRS2023

Stiffness and Fatigue Life Estimator for Polymer Composite Laminates Using Machine Learning

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, Python-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been established. Results show that both neural net type algorithms can provide an excellent estimate of initial laminate stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminates (PMCs). RNNs are better able to capture the shape of the fatigue curve of a laminate. The resulting tool and GUI can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. Further, the associated surrogate models can also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make micromechanics-based multiscale analyses a viable industrial tool for large scale structural problems.

multiscale analysis↗
NASA NTRS1985

Computer-assisted image analysis of plant growth, thigmomorphogenesis and gravitropism

A nonintrusive auxonometric system, based on the DARWIN image processor (Telewski et al. 1983 Plant Physiol 72: 177-181), is described and demonstrated in the analysis of gravitropism and thigmomorphogenesis in corn seedlings (Zea mays). Using this system, growth and bending of regularly shaped plants or organs can be quickly and accurately measured without, in any way, interfering with the plant. Furthermore, the growth and bending curves are automatically plotted. Thigmomorphogenesis in the aerial part of corn seedlings involves growth promotion at a low force load and growth retardation at higher force loads. The time courses of the two kinds of response are somewhat different, with retardation occurring immediately after mechanical perturbation and growth promotion taking somewhat longer to begin. Gravitropic experiments show that when dark-grown corn seedlings are placed on their side in the light, the resulting curvature is due to two consecutive morphological mechanisms. In the first instance, lasting for about 15 minutes, the elongation of the bottom edge of the plant accelerates, while the elongation of the top edge remains constant. After that, for the next 1.75 hours, the elongation of the top edge decelerates and stops while that of the bottom edge remains constant at the increased rate for most of the period. The measurements taken from both experiments at relatively high resolution (0.08-0.1 millimeter) show that the growth curves are not smooth but show many small irregularities which may or may not involve micronutations.

Zea mays/growth & development/physiology↗
NASA NTRS1998

Microgravity Science in Space Flight Gloveboxes

Microgravity science studies the influences of gravity on phenomena in fluids, materials processes, combustion, and human cell growth in the low acceleration environment of space flight. During the last decade, the accomplishment of the flight research in the field has evolved into an effective cooperation between the flight crew in the Shuttle and the ground-based investigator using real-time communication via voice and video links. This team structure has led to interactive operations in which the crew performs the experimentation while guided, as necessary, by the science investigator who formulated the investigation and who will subsequently interpret and analyze the data. One of the primary challenges to implementing this interactive research has been the necessity of structuring a means of handling fluids, gases, and hazardous materials in a manned laboratory that exhibits the novelty of weightlessness. Developing clever means of designing experiments in closed vessels is part of the solution- but the space flight requirement for one and two failure-tolerant containment systems leads to serious complications in the physical handling of sample materials. In response to the conflict between the clear advantage of human operation and judgment, versus the necessity to isolate the experiment from the crewmember and the spacecraft environment, the Microgravity Research Program has initiated a series of Gloveboxes in the various manned experiment carriers. These units provide a sealed containment vessel whose interior is under a negative pressure with respect to the ambient environment but is accessible to a crewmember through the glove ports.

Baugher, Charles↗
NASA NTRS1994

Inter-Agency Consultative Group for Space Science (IACG): Handbook of Missions and Payloads

The ACE spacecraft design is based on the Charge Composition Explorer (CCE) built by Johns Hopkins University (JHU) and the Applied Physics Lab (APL) for the AMPTE program. ACE is designed as a spinning spacecraft with its spin axis aligned to the Earth-Sun axis. The ACE launch weight will be approx. 633 kg, including 105 kg of scientific instruments and 184 kg of propellant. Using a Delta-class expendable launch vehicle, ACE will be launched into an L1 libration point (240 R(sub e)) orbit. Telemetry will be 6.7 kbps average, using tape recorder storage with daily readout to DSN. The experiment power requirement is approximately 76 W nominal and 96 W peak. The prime objective of the ACE mission is: (1) to determine accurate elemental and isotropic abundances including solar matter, local interstellar matter and local galactic matter; (2) to study the origin of elements and evolutionary processing in galactic nucleosynthesis, galactic evolution, origin and evolution of the solar system; (3) to study coronal formation and solar-wind acceleration processes; and (4) to study particle acceleration and transport, including coronal shock acceleration, stochastic flare acceleration, interplanetary shock acceleration, and interstellar acceleration and propagation. To accomplish this objective, ACE will perform comprehensive and coordinated determinations of the elemental and isotopic composition of energetic nuclei accelerated on the Sun, in interplanetary space, and from galactic sources. These observations will span five decades in energy, from solar wind to galactic cosmic ray energies, and will cover the element range from H-1 to Zr-40. Comparison of these samples of matter will be used to study the origin and subsequent evolution of both solar system and galactic material by isolating the effects of fundamental processes that include nucleosynthesis, charged and neutral particle separation, bulk plasma acceleration, and the acceleration of suprathermal and high-energy particles.

Source record↗
NASA NTRS2013

An Electric Propulsion "Shepherd" for Active Debris Removal that Utilizes Ambient Gas as Propellant

There is a growing consensus among the space debris technical community that limiting the long-term growth of debris in Low-Earth Orbit (LEO) requires that space users limit the accumulation of mass in orbit. This is partially accomplished by mitigation measures for current and future LEO systems, but there is now interest in removing mass that has already accumulated in LEO from more than 50 years of space activity (termed "Active Debris Removal", or ADR). Many ADR proposals face complex technical issues of how to grapple with uncooperative targets. Some researchers have suggested the use of conventional ion thrusters to gently "blow" on objects to gradually change their orbits, without ever having to come into physical contact with the target. The chief drawback with these methods is the cost per object removed. Typically, a space "tug" or an ion-drive "shepherd" can only remove a few objects per mission due to limited propellant. Unless a cost-effective way that removes tens of objects per mission can be found, it is not clear that any of the ideas so far proposed will be economically viable. In this paper, a modified version of the ion-drive "shepherd" is proposed that uses ambient atmospheric gases in LEO as propellant for the ion drives. This method has the potential to greatly extend the operational lifetime of an ADR mission, as the only mission limit is the lifetime of the components of the satellite itself, not on its fuel supply. An ambient-gas ion-drive "shepherd" would enhance the local atmospheric drag on an object by ionizing and accelerating the ambient gas the target would have encountered anyway, thereby hastening its decay. Also, the "shepherd" satellite itself has a great deal of flexibility to maneuver back to high altitude and rendezvous with its next target using the ion drive not limited by fuel supply. However, the amount of available ambient gas is closely tied to the altitude of the spacecraft. It may be possible to use a "hybrid" approach that supplements high-altitude ion-drive operations with stored gas, and transitions to ambient gas at lower altitudes. This paper will include realistic numbers on the estimated times needed to deorbit objects from different orbit regimes using drives that either partially or completely take advantage of ambient gas. It will conclude with recommendations on whether this is a viable candidate for future ADR efforts.

Matney, Mark↗
NASA NTRS2003

Silicon Detector System for Cross Section Measurements

In order to estimate the radiation shielding effectiveness of materials it is necessary to know cosmic ray particles are broken up as they pass though these materials. The breakup of cosmic ray particles is characterized by the nuclear fragmentation cross sections, i.e. an effective geometrical cross section assigned to each target nucleus that represents its apparent size for fragmenting the incident particle. The values of these cross sections depend on the details of nuclear physics and cannot be calculated from first principles owing to the many-body nature of the interactions. The only way to determine them is to measure them. Once a sufficient number of cross sections have been measured, the systematic nature of the interactions allows other cross-sections to be estimated. The number of cross sections that contribute to the estimation of shielding effectiveness is very large 10,000. Fortunately most make minor contributions. These can be estimated from nuclear systematics. Only those who's uncertainties make significant contributions to the error in the shielding effectiveness estimations need to be measured. In the past it has proven difficult to measure light fragment production cross sections from the interactions of heavy cosmic rays owing to the size of the detectors used. We have developed a highly pixilated silicon (Si) detector system that can individually identify these light fragments while making efficient use of costly accelerator time. This system is an outgrowth of detector technology developed under a CDDF and a Code S sponsored cosmic ray experiment.

Source record↗
NASA NTRS2002

Life-Extending Control for Aircraft Engines Studied

Current aircraft engine controllers are designed and operated to provide both performance and stability margins. However, the standard method of operation results in significant wear and tear on the engine and negatively affects the on-wing life--the time between cycles when the engine must be physically removed from the aircraft for maintenance. The NASA Glenn Research Center and its industrial and academic partners have been working together toward a new control concept that will include engine life usage as part of the control function. The resulting controller will be able to significantly extend the engine's on-wing life with little or no impact on engine performance and operability. The new controller design will utilize damage models to estimate and mitigate the rate and overall accumulation of damage to critical engine parts. The control methods will also provide a means to assess tradeoffs between performance and structural durability on the basis of mission requirements and remaining engine life. Two life-extending control methodologies were studied to reduce the overall life-cycle cost of aircraft engines. The first methodology is to modify the baseline control logic to reduce the thermomechanical fatigue (TMF) damage of cooled stators during acceleration. To accomplish this, an innovative algorithm limits the low-speed rotor acceleration command when the engine has reached a threshold close to the requested thrust. This algorithm allows a significant reduction in TMF damage with only a very small increase in the rise time to reach the commanded rotor speed. The second methodology is to reduce stress rupture/creep damage to turbine blades and uncooled stators by incorporating an engine damage model into the flight mission. Overall operation cost is reduced by an optimization among the flight time, fuel consumption, and component damages. Recent efforts have focused on applying life-extending control technology to an existing commercial turbine engine, and doing so without modifying the hardware or adding sensors. This approach makes it possible to retrofit existing engines with life-extending control technology by changing only the control software in the full-authority digital engine controller (FADEC). The significant results include demonstrating a 20- to 30-percent reduction in TMF damage to the hot section by developing and implementing smart acceleration logic during takeoff. The tradeoff is an increase, from 5.0 to 5.2 sec, in the time required to reach maximum power from ground idle. On a typical flight profile of a cruise at Mach 0.8 at an altitude of 41,000 ft, and cruise time of 104 min, the optimized system showed that a reduction in cruise speed from Mach 0.8 to 0.79 can achieve an estimated 25-to 35-percent creep/rupture damage reduction in the engine's hot section and a fuel savings of 2.1 percent. The tradeoff is an increase in flight time of 1.3 percent (1.4 min).

Guo, Te-Huei↗
NASA NTRSDate not supplied

Development of Machine Learning Algorithms to Segment and Study Images of Astromaterial Samples

Introduction: Micrometer-scale chemical analyses of chondritic meteorites and mission-returned asteroid samples can reveal details of the physical and chemical processes operating in the early solar system, including processes that gave rise to planets, moons, and minor bodies. These primitive astromaterials are comprised of chondrules, calcium- and aluminum-rich inclusions (CAI), and many other silicates, oxides, metals, sulfides, and fine-grained materials. The chemical and mineralogical complexity of these samples, vast populations of different components, and heterogeneity across mm to km scales, all limit our understanding of the origin and evolution of these materials. Here, we describe recent efforts to use machine learning techniques to automate the segmentation of chemical maps of chondritic meteorites, designed to aid studies of asteroid samples returned by spacecraft. By automating the task of segmentation it will become possible to rapidly analyze and interpret the sizes, shapes, mineralogy, chemistry, and other properties of every chondrule, calcium- and aluminum-rich inclusion (CAI) and other clast within and between asteroid samples. Sample return missions significantly accelerate and heighten the need to develop such new data analysis techniques, and associated data repositories. Techniques: Neural networks require abundant training data, i.e. images which have been segmented by a human user. We have manually segmented data available from previous petrologic and chemical work at NASA Johnson Space Center and the American Museum of Natural History [1-4]. These data were derived from energy- and wavelength-dispersive X-ray spectroscopy (EDS, WDS) mapping of samples from many chondrite groups. The Deeplabv3+ [5] neural network architecture was trained on human-labeled masks and used to create machine-labeled masks. Several different algorithms were investigated, with inputs ranging from common RGB image formats through to hyperspectral datasets, with raw data comprising greyscale maps of Mg, Ca, and Al, with or without Si, Fe, Ti for both EDS and WDS data, and extending to other elements in EDS only. Each greyscale image was paired with a binary mask for each labelled particle type. Results: The trained algorithms can segment (Fig 1), classify, and measure the dimensions of thousands of particles in chemical maps of a standard 1-inch round petrographic section in seconds to minutes, rather than many hours needed by a human. Accuracy of the algorithms varied from chondrite to chondrite and across particle types. Further results and details of the algorithms will be presented at the workshop. Future directions: Machine learning has the potential to revolutionize our understanding of complex particle populations contained within primitive astromaterial, with segmentation being a critical first step. Example applications include better understanding of particle transport, nebular reservoirs, parent body accretion, and a deeper understanding of the relationships between particle populations and bulk rock elemental and isotopic compositions. In addition to benefits that machine learning can bring to individual researchers, building a community data repository of thousands to millions of particles across hundreds of samples will open up many other possibilities. For example, with a large enough dataset it will be possible to search for exceptionally closely matching particles across disparate samples. Such a capability would enable a single CAI from OSIRISREx or Hayabusa/II samples to be matched to chondritic CAIs that exhibit near-identical size, texture, and mineralogy, down to the level of similar core phenocrysts, zonation, and rim sequences. Such comparative analyses will help to disentangle precursor chemistry, chronology, gas/dust reservoirs during heating, and accretion. Such an endeavor would be impossible without machine learning and a large community data repository of astromaterial chemical/mineralogic maps.

Machine Learning↗
NASA NTRS2003

Unstructured LES of Reacting Multiphase Flows in Realistic Gas Turbine Combustors

As part of the Accelerated Strategic Computing Initiative (ASCI) program, an accurate and robust simulation tool is being developed to perform high-fidelity LES studies of multiphase, multiscale turbulent reacting flows in aircraft gas turbine combustor configurations using hybrid unstructured grids. In the combustor, pressurized gas from the upstream compressor is reacted with atomized liquid fuel to produce the combustion products that drive the downstream turbine. The Large Eddy Simulation (LES) approach is used to simulate the combustor because of its demonstrated superiority over RANS in predicting turbulent mixing, which is central to combustion. This paper summarizes the accomplishments of the combustor group over the past year, concentrating mainly on the two major milestones achieved this year: 1) Large scale simulation: A major rewrite and redesign of the flagship unstructured LES code has allowed the group to perform large eddy simulations of the complete combustor geometry (all 18 injectors) with over 100 million control volumes; 2) Multi-physics simulation in complex geometry: The first multi-physics simulations including fuel spray breakup, coalescence, evaporation, and combustion are now being performed in a single periodic sector (1/18th) of an actual Pratt & Whitney combustor geometry.

Ham, Frank↗
NASA NTRS2010

Electron Beam Return-Current Losses in Solar Flares: Initial Comparison of Analytical and Numerical Results

Accelerated electrons play an important role in the energetics of solar flares. Understanding the process or processes that accelerate these electrons to high, nonthermal energies also depends on understanding the evolution of these electrons between the acceleration region and the region where they are observed through their hard X-ray or radio emission. Energy losses in the co-spatial electric field that drives the current-neutralizing return current can flatten the electron distribution toward low energies. This in turn flattens the corresponding bremsstrahlung hard X-ray spectrum toward low energies. The lost electron beam energy also enhances heating in the coronal part of the flare loop. Extending earlier work by Knight & Sturrock (1977), Emslie (1980), Diakonov & Somov (1988), and Litvinenko & Somov (1991), I have derived analytical and semi-analytical results for the nonthermal electron distribution function and the self-consistent electric field strength in the presence of a steady-state return-current. I review these results, presented previously at the 2009 SPD Meeting in Boulder, CO, and compare them and computed X-ray spectra with numerical results obtained by Zharkova & Gordovskii (2005, 2006). The phYSical significance of similarities and differences in the results will be emphasized. This work is supported by NASA's Heliophysics Guest Investigator Program and the RHESSI Project.

Holman, Gordon↗
NASA NTRS2013

Standard Practices for Usage of Inductive Magnetic Field Probes with Application to Electric Propulsion Testing

Inductive magnetic field probes (also known as B-dot probes and sometimes as B-probes or magnetic probes) are useful for performing measurements in electric space thrusters and various plasma accelerator applications where a time-varying magnetic field is present. Magnetic field probes have proven to be a mainstay in diagnosing plasma thrusters where changes occur rapidly with respect to time, providing the means to measure the magnetic fields produced by time-varying currents and even an indirect measure of the plasma current density through the application of Ampère's law. Examples of applications where this measurement technique has been employed include pulsed plasma thrusters and quasi-steady magnetoplasmadynamic thrusters. The Electric Propulsion Technical Committee (EPTC) of the American Institute of Aeronautics and Astronautics (AIAA) was asked to assemble a Committee on Standards (CoS) for Electric Propulsion Testing. The assembled CoS was tasked with developing Standards and Recommended Practices for various diagnostic techniques used in the evaluation of plasma thrusters. These include measurements that can yield either global information related to a thruster and its performance or detailed, local data related to the specific physical processes occurring in the plasma. This paper presents a summary of the standard, describing the preferred methods for fabrication, calibration, and usage of inductive magnetic field probes for use in diagnosing plasma thrusters. Inductive magnetic field probes (also called B-dot probes throughout this document) are commonly used in electric propulsion (EP) research and testing to measure unsteady magnetic fields produced by time-varying currents. The B-dot probe is relatively simple in construction, and requires minimal cost, making it a low-cost technique that is readily accessible to most researchers. While relatively simple, the design of a B-dot probe is not trivial and there are many opportunities for errors in probe construction, calibration, and usage, and in the post-processing of data that is produced by the probe. There are typically several ways in which each of these steps can be approached, and different applications may require more or less vigorous attention to various issues.

Polzin, Kurt A.↗
NASA NTRS1996

A Comparison of Tension and Compression Creep in a Polymeric Composite and the Effects of Physical Aging on Creep Behavior

Experimental and analytical methods were used to investigate the similarities and differences of the effects of physical aging on creep compliance of IM7/K3B composite loaded in tension and compression. Two matrix dominated loading modes, shear and transverse, were investigated for two load cases, tension and compression. The tests, run over a range of sub-glass transition temperatures, provided material constants, material master curves and aging related parameters. Comparing results from the short-term data indicated that although trends in the data with respect to aging time and aging temperature are similar, differences exist due to load direction and mode. The analytical model used for predicting long-term behavior using short-term data as input worked equally as well for the tension or compression loaded cases. Comparison of the loading modes indicated that the predictive model provided more accurate long term predictions for the shear mode as compared to the transverse mode. Parametric studies showed the usefulness of the predictive model as a tool for investigating long-term performance and compliance acceleration due to temperature.

Gates, Thomas S.↗
NASA NTRS1999

Current and Future Plans of the NASA Data Assimilation Office (DAO)

The mission of the Data Assimilation Office (DAO) is to advance the state of the art of data assimilation and produce research-quality assimilated data sets which make optimal use of space-based observations. Development efforts over the last few years have focused on delivering a production data assimilation system in support of NASA's Terra platform. That system, called the Goddard Earth Observing System - version 2 or GEOS-2, represents a major upgrade to the baseline GEOS-1 system employed in NASA's first reanalysis effort. GEOS-2 includes a physical-space three dimensional variational analysis algorithm (the Physical-space Statistical Analysis System or PSAS) and numerous improvements to the general circulation model. The latter include a Soil-Vegetation-Atmosphere Transfer (SVAT) land surface scheme, a level 2.5 moist turbulence scheme and new Short Wave (SW) and Long Wave (LW) radiation code. The system also includes an off-line ozone assimilation system, and the capability to assimilate scatterometer surface winds, and TIROS Operational Vertical Sounder (TOVS) and Special Sensor Microwave Imager (SSM/I) moisture data. GEOS-2 is currently run at 1 degree horizontal resolution and 48 levels extending to O.Olmb. Experimental versions of GEOS-2 are run with a global stretched grid allowing enhanced (e.g. 1/4 deg) regional resolution. Other capabilities being developed include, the assimilation of Tropical Rainfall Measuring Mission (TRMM) precipitation and Global Positioning System (GPS) data, an off-line land surface assimilation system, and a retrospective analysis scheme. The DAO is also engaged in a number of collaborative efforts to help accelerate the development of the next generation data assimilation system. These include, a joint modeling effort between the DAO and NCAR/CGDD to develop a new Global Circulation Model (GCM), and a Department of Energy Lawrence Livermore National Laboratory (DOE/LLNL) collaboration on model parallelization. Plans for the next reanalysis will be discussed in the context of current and near term system quality and computing capabilities, and the need for multiple reanalysis products.

Atlas, Robert↗
NASA NTRS1976

Flare build-up study; Proceedings of the Workshop, Falmouth, Mass., September 8-11, 1975

The papers deal with problems which might be common to solar flares and earth's magnetosphere, problems associated with the initial phases of the flare phenomenon, the acceleration processes that seem to occur in flares and the magnetosphere, as well as the buildup and storage of flare energy in magnetic-field structures. Topics include the active role of magnetic fields in providing flare energy, current-sheet models of solar flares, the role of plasma turbulence in flare development, similarities and differences between magnetospheric substorms and solar flares, observations of magnetic merging in earth's magnetotail during magnetospheric substorms, evidence for magnetic-energy storage in coronal active regions, the possible role of transition-zone instabilities in preflare energy buildup, and flare energy storage and deposition. Other papers discuss energy release through the interaction of coronal magnetic fields, photospheric electric currents as a source of flare energy, magnetic-energy buildup in the solar atmosphere, magnetic and velocity fields in an active region, flare onset at meter wavelengths, laboratory experiments on field-line reconnection, key problems in auroral flare processes, and the solar-physics Shuttle/Spacelab program. Individual items are announced in this issue.

Svestka, Z.↗
NASA NTRSDate not supplied

Resolving Wave-Particle Duality Could Accelerate the Mass Production of Quantum Computers

Quantum computers, hypothesized in 1980s, use concepts of superposition and entanglement phenomena. Although theoretical propositions and associated search algorithms for accurate measurements are being generated, the development of practical quantum computers themselves are advancing very slowly requiring enormous time and investments. The underlying concepts of a quantum computer are not new to the optical domain. However, the crucial enabling concepts of Entanglement and Superposition Principle are remaining clouded under the unresolved postulates, Wave-Particle Duality (WPD), and Wave Packet Reduction (WPR), implicating incompleteness in the interpretations of the mathematical formalism behind Quantum Mechanics. The WPD debate started during late1600 between Newton and Huygens. Young’s resolution of WPD through his double-slit experiment in 1802 was effectively overturned by Einstein’s interpretation of photoelectric effect as due to “indivisible light quanta”. However, Einstein disowned his “light quanta” postulate shortly before his death in1955, even though it had earned him the Nobel Prize. We resolve WPD by synthesizing Newton’s and Maxwell’s concepts and assume atoms do emit quanta but propagate as time-finite exponential pulses. This assumption also resolves WPR for light-matter interaction with the assumption that Schrodinger’s ψ represents atom’s internal dipolar amplitude stimulations. This over-turns Born’s interpretation that ψ only represents the abstract mathematical probability amplitude, rather than the physical “internal amplitude stimulation” of the quantum entity. However, our concept of atomic pulse emission forces us to re-derive the expression for the N-slit grating-spectrometer response since the classical derivation uses CW light, which does not exist. This pulsespectrometric response function strengthens our postulate since the grating response to the exponential pulse appears to be the convolution of a Lorentzian spectrum with the classical CW response function of the grating. The Fourier Transform of an exponential function is Lorentzian and QM predicts spontaneous emission line width to be Lorentzian. Then, conceptually one can extend the grating-expression (with N=2) to get the double-slit pattern. This approach preserves the classical causality that each of the two slits, like the N-signals out of a grating, are physically real and jointly stimulate the quantum detector array at the far field to generate the “Local” cosine fringes. The detector array executes the square modulus operation on its imposed dipolar amplitude stimulation and absorbs the necessary energy to fill up their quantum cups. Hence the double-slit pattern must also be “Local”, just as the N-slit grating spectrum is generated locally at the exit spectral-plane of the spectrometer. This removes the need to believe that “single photons” mysteriously generate the double slit pattern. Quantum computers, hypothesized in 1980s, use concepts of superposition and entanglement phenomena. Although theoretical propositions and associated search algorithms for accurate measurements are being generated, the development of practical quantum computers themselves are advancing very slowly requiring enormous time and investments. The underlying concepts of a quantum computer are not new to the optical domain. However, the crucial enabling concepts of Entanglement and Superposition Principle are remaining clouded under the unresolved postulates, Wave-Particle Duality (WPD), and Wave Packet Reduction (WPR), implicating incompleteness in the interpretations of the mathematical formalism behind Quantum Mechanics. The WPD debate started during late1600 between Newton and Huygens. Young’s resolution of WPD through his double-slit experiment in 1802 was effectively overturned by Einstein’s interpretation of photoelectric effect as due to “indivisible light quanta”. However, Einstein disowned his “light quanta” postulate shortly before his death in1955, even though it had earned him the Nobel Prize. We resolve WPD by synthesizing Newton’s and Maxwell’s concepts and assume atoms do emit quanta but propagate as time-finite exponential pulses. This assumption also resolves WPR for light-matter interaction with the assumption that Schrodinger’s ψ represents atom’s internal dipolar amplitude stimulations. This over-turns Born’s interpretation that ψ only represents the abstract mathematical probability amplitude, rather than the physical “internal amplitude stimulation” of the quantum entity. However, our concept of atomic pulse emission forces us to re-derive the expression for the N-slit grating-spectrometer response since the classical derivation uses CW light, which does not exist. This pulsespectrometric response function strengthens our postulate since the grating response to the exponential pulse appears to be the convolution of a Lorentzian spectrum with the classical CW response function of the grating. The Fourier Transform of an exponential function is Lorentzian and QM predicts spontaneous emission line width to be Lorentzian. Then, conceptually one can extend the grating-expression (with N=2) to get the double-slit pattern. This approach preserves the classical causality that each of the two slits, like the N-signals out of a grating, are physically real and jointly stimulate the quantum detector array at the far field to generate the “Local” cosine fringes. The detector array executes the square modulus operation on its imposed dipolar amplitude stimulation and absorbs the necessary energy to fill up their quantum cups. Hence the double-slit pattern must also be “Local”, just as the N-slit grating spectrum is generated locally at the exit spectral-plane of the spectrometer. This removes the need to believe that “single photons” mysteriously generate the double slit pattern.

Quantum Computer↗