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Optical systems integrated modeling

An integrated modeling capability that provides the tools by which entire optical systems and instruments can be simulated and optimized is a key technology development, applicable to all mission classes, especially astrophysics. Many of the future missions require optical systems that are physically much larger than anything flown before and yet must retain the characteristic sub-micron diffraction limited wavefront accuracy of their smaller precursors. It is no longer feasible to follow the path of 'cut and test' development; the sheer scale of these systems precludes many of the older techniques that rely upon ground evaluation of full size engineering units. The ability to accurately model (by computer) and optimize the entire flight system's integrated structural, thermal, and dynamic characteristics is essential. Two distinct integrated modeling capabilities are required. These are an initial design capability and a detailed design and optimization system. The content of an initial design package is shown. It would be a modular, workstation based code which allows preliminary integrated system analysis and trade studies to be carried out quickly by a single engineer or a small design team. A simple concept for a detailed design and optimization system is shown. This is a linkage of interface architecture that allows efficient interchange of information between existing large specialized optical, control, thermal, and structural design codes. The computing environment would be a network of large mainframe machines and its users would be project level design teams. More advanced concepts for detailed design systems would support interaction between modules and automated optimization of the entire system. Technology assessment and development plans for integrated package for initial design, interface development for detailed optimization, validation, and modeling research are presented.

Shannon, Robert R.↗

The H-Metaphor as a Guideline for Vehicle Automation and Interaction

Good design is not free of form. It does not necessarily happen through a mere sampling of technologies packaged together, through pure analysis, or just by following procedures. Good design begins with inspiration and a vision, a mental image of the end product, which can sometimes be described with a design metaphor. A successful example from the 20th century is the desktop metaphor, which took a real desktop as an orientation for the manipulation of electronic documents on a computer. Initially defined by Xerox, then refined by Apple and others, it could be found on almost every computer by the turn of the 20th century. This paper sketches a specific metaphor for the emerging field of highly automated vehicles, their interactions with human users and with other vehicles. In the introduction, general questions on vehicle automation are raised and related to the physical control of conventional vehicles and to the automation of some late 20th century vehicles. After some words on design metaphors, the H-Metaphor is introduced. More details of the metaphor's source are described and their application to human-machine interaction, automation and management of intelligent vehicles sketched. Finally, risks and opportunities to apply the metaphor to technical applications are discussed.

Flemisch, Frank O.↗

A multidimensional model for aerosols - Description of computational analogs

The numerical algorithms used to simulate the advection, diffusion, sedimentation, coagulation, and condensational growth of atmospheric aerosols are described. The model can be used in one, two, or three spatial dimensions. The continuity equation in a generalized horizontal and vertical coordinate system is developed, which allows the model to be quickly adapted to a wide variety of dynamical models of global or regional scale. Algorithms are developed to treat the various physical processes, and the results of simulations are presented, which show the strengths and weaknesses of these algorithms. Although the emphasis is on the modeling of aerosols, the work is also applicable to the simulations of the transport of gases.

Toon, O. B.↗

Delineating the Impact of Weightlessness on Human Physiology Using Computational Models

Microgravity environment has profound effects on several important human physiological systems. The impact of weightlessness is usually indirect as mediated by changes in the biological fluid flow and transport and alterations in the deformation and stress fields of the compliant tissues. In this context, Fluid-Structural and Fluid-Solid Interaction models provide a valuable tool in delineating the physical origins of the physiological changes so that systematic countermeasures can be devised to reduce their adverse effects. In this presentation, impact of gravity on three human physiological systems will be considered. The first case involves prediction of cardiac shape change and altered stress distributions in weightlessness. The second, presents a fluid-structural-interaction (FSI) analysis and assessment of the vestibular system and explores the reasons behind the unexpected microgravity caloric stimulation test results performed aboard the Skylab. The last case investigates renal stone development in microgravity and the possible impact of re-entry into partial gravity on the development and transport of nucleating, growing, and agglomerating renal calculi in the nephron. Finally, the need for model validation and verification and application of the FSI models to assess the effects of Artificial Gravity (AG) are also briefly discussed.

Computational Models↗

Quad-Port Transceivers For A Dual-CRR LAN

Quad-port fiber-optic transceivers demonstrated successfully as physical-layer interface units in WhisperNet - local-area network (LAN) of computers and other devices in communication with each other. Each node of Dual-CRR LAN contains quad-port transceiver serving four pairs of optical fibers. Quad-port transceiver consists of two dual-port transceivers and ancillary equipment in compact package. Transceiver serves as interface between optical fibers and external computing devices. Because of high reliability, availability and "fail-soft" nature, network well suited to military and critical commercial applications.

Wiencko, Joseph A., Jr.↗

Welding arc plasma physics

The problems of weld quality control and weld process dependability continue to be relevant issues in modern metal welding technology. These become especially important for NASA missions which may require the assembly or repair of larger orbiting platforms using automatic welding techniques. To extend present welding technologies for such applications, NASA/MSFC's Materials and Processes Lab is developing physical models of the arc welding process with the goal of providing both a basis for improved design of weld control systems, and a better understanding of how arc welding variables influence final weld properties. The physics of the plasma arc discharge is reasonably well established in terms of transport processes occurring in the arc column itself, although recourse to sophisticated numerical treatments is normally required to obtain quantitative results. Unfortunately the rigor of these numerical computations often obscures the physics of the underlying model due to its inherent complexity. In contrast, this work has focused on a relatively simple physical model of the arc discharge to describe the gross features observed in welding arcs. Emphasis was placed of deriving analytic expressions for the voltage along the arc axis as a function of known or measurable arc parameters. The model retains the essential physics for a straight polarity, diffusion dominated free burning arc in argon, with major simplifications of collisionless sheaths and simple energy balances at the electrodes.

Cain, Bruce L.↗

Spillover, nonlinearity, and flexible structures

Many systems whose evolution in time is governed by Partial Differential Equations (PDEs) are linearized around a known equilibrium before Computer Aided Control Engineering (CACE) is considered. In this case, there are infinitely many independent vibrational modes, and it is intuitively evident on physical grounds that infinitely many actuators would be needed in order to control all modes. A more precise, general formulation of this grave difficulty (spillover problem) is due to A.V. Balakrishnan. A possible route to circumvention of this difficulty lies in leaving the PDE in its original nonlinear form, and adding the essentially finite dimensional control action prior to linearization. One possibly applicable technique is the Liapunov Schmidt rigorous reduction of singular infinite dimensional implicit function problems to finite dimensional implicit function problems. Omitting details of Banach space rigor, the formalities of this approach are given.

Bass, Robert W.↗

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Larson, Jay W.↗

A Log Logistic Survival Model Applied to Hypobaric Decompression Sickness

Decompression sickness (DCS) is a complex, multivariable problem. A mathematical description or model of the likelihood of DCS requires a large amount of quality research data, ideas on how to define a decompression dose using physical and physiological variables, and an appropriate analytical approach. It also requires a high-performance computer with specialized software. I have used published DCS data to develop my decompression doses, which are variants of equilibrium expressions for evolved gas plus other explanatory variables. My analytical approach is survival analysis, where the time of DCS occurrence is modeled. My conclusions can be applied to simple hypobaric decompressions - ascents lasting from 5 to 30 minutes - and, after minutes to hours, to denitrogenation (prebreathing). They are also applicable to long or short exposures, and can be used whether the sufferer of DCS is at rest or exercising at altitude. Ultimately I would like my models to be applied to astronauts to reduce the risk of DCS during spacewalks, as well as to future spaceflight crews on the Moon and Mars.

Conkin, Johnny↗

The Fringe-Imaging Skin Friction Technique PC Application User's Manual

A personal computer application (CXWIN4G) has been written which greatly simplifies the task of extracting skin friction measurements from interferograms of oil flows on the surface of wind tunnel models. Images are first calibrated, using a novel approach to one-camera photogrammetry, to obtain accurate spatial information on surfaces with curvature. As part of the image calibration process, an auxiliary file containing the wind tunnel model geometry is used in conjunction with a two-dimensional direct linear transformation to relate the image plane to the physical (model) coordinates. The application then applies a nonlinear regression model to accurately determine the fringe spacing from interferometric intensity records as required by the Fringe Imaging Skin Friction (FISF) technique. The skin friction is found through application of a simple expression that makes use of lubrication theory to relate fringe spacing to skin friction.

Zilliac, Gregory G.↗

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government.

Frost, Susan↗

Research briefing on contemporary problems in plasma science

An overview is presented of the broad perspective of all plasma science. Detailed discussions are given of scientific opportunities in various subdisciplines of plasma science. The first subdiscipline to be discussed is the area where the contemporary applications of plasma science are the most widespread, low temperature plasma science. Opportunities for new research and technology development that have emerged as byproducts of research in magnetic and inertial fusion are then highlighted. Then follows a discussion of new opportunities in ultrafast plasma science opened up by recent developments in laser and particle beam technology. Next, research that uses smaller scale facilities is discussed, first discussing non-neutral plasmas, and then the area of basic plasma experiments. Discussions of analytic theory and computational plasma physics and of space and astrophysical plasma physics are then presented.

Source record↗

Aeroheating Design Issues for Reusable Launch Vehicles: A Perspective

An overview of basic aeroheating design issues for Reusable Launch Vehicles (RLV), which addresses the application of hypersonic ground-based testing, and computational fluid dynamic (CFD) and engineering codes, is presented. Challenges inherent to the prediction of aeroheating environments required for the successful design of the RLV Thermal Protection System (TPS) are discussed in conjunction with the importance of employing appropriate experimental/computational tools. The impact of the information garnered by using these tools in the resulting analyses, ultimately enhancing the RLV TPS design is illustrated. A wide range of topics is presented in this overview; e.g. the impact of flow physics issues such as boundary-layer transition, including effects of distributed and discrete roughness, shockshock interactions, and flow separation/reattachment. Also, the benefit of integrating experimental and computational studies to gain an improved understanding of flow phenomena is illustrated. From computational studies, the effect of low-density conditions and of uncertainties in material surface properties on the computed heating rates are highlighted as well as the significant role of CFD in improving the Outer Mold Line (OML) definition to reduce aeroheating while maintaining aerodynamic performance. Appropriate selection of the TPS design trajectories and trajectory shaping to mitigate aeroheating levels and loads are discussed. Lastly, an illustration of an aeroheating design process is presented whereby data from hypersonic wind-tunnel tests are integrated with predictions from CFD codes and engineering methods to provide heating environments along an entry trajectory as required for TPS design.

Zoby, E. Vincent↗

Aeroheating Design Issues for Reusable Launch Vehicles: A Perspective

An overview of basic aeroheating design issues for Reusable Launch Vehicles (RLV), which addresses the application of hypersonic ground-based testing, and computational fluid dynamic (CFD) and engineering codes, is presented. Challenges inherent to the prediction of aeroheating environments required for the successful design of the RLV Thermal Protection System (TPS) are discussed in conjunction with the importance of employing appropriate experimental/computational tools. The impact of the information garnered by using these tools in the resulting analyses, ultimately enhancing the RLV TPS design is illustrated. A wide range of topics is presented in this overview; e.g. the impact of flow physics issues such as boundary-layer transition, including effects of distributed and discrete roughness, shock-shock interactions, and flow separation/reattachment. Also, the benefit of integrating experimental and computational studies to gain an improved understanding of flow phenomena is illustrated. From computational studies, the effect of low-density conditions and of uncertainties in material surface properties on the computed heating rates a r e highlighted as well as the significant role of CFD in improving the Outer Mold Line (OML) definition to reduce aeroheating while maintaining aerodynamic performance. Appropriate selection of the TPS design trajectories and trajectory shaping to mitigate aeroheating levels and loads are discussed. Lastly, an illustration of an aeroheating design process is presented whereby data from hypersonic wind-tunnel tests are integrated with predictions from CFD codes and engineering methods to provide heating environments along an entry trajectory as required for TPS design.

Zoby, E. Vincent↗

Annual Research Briefs, 2004: Center for Turbulence Research

This report contains the 2004 annual progress reports of the Research Fellows and students of the Center for Turbulence Research in its eighteenth year of operation. Since its inception in 1987, the objective of the CTR has been to advance the physical understanding of turbulent flows and development of physics based predictive tools for engineering analysis and turbulence control. Turbulence is ubiquitous in nature and in engineering devices. The studies at CTR have been motivated by applications where turbulence effects are significant; these include a broad range of technical areas such as planetary boundary layers, formation of planets, solar convection, magnetohydrodynamics, environmental and eco systems, aerodynamic noise, propulsion systems and high speed transportation. Numerical simulation has been the predominant research tool at CTR which has required a critical mass of researchers in numerical analysis and computer science in addition to core disciplines such as applied mathematics, chemical kinetics and fluid mechanics. Maintaining and promoting this interdisciplinary culture has been a hallmark of CTR and has been responsible for the realization of the results of its basic research in applications. The first group of reports in this volume are directed towards development, analysis and application of novel numerical methods for ow simulations. Development of methods for large eddy simulation of complex flows has been a central theme in this group. The second group is concerned with turbulent combustion, scalar transport and multi-phase ows. The nal group is devoted to geophysical turbulence where the problem of solar convection has been a new focus of considerable attention recently at CTR.

Moin, Parviz↗

Development of a 32 Inch Diameter Levitated Ducted Fan Conceptual Design

The NASA John H. Glenn Research Center has developed a revolutionary 32 in. diameter Levitated Ducted Fan (LDF) conceptual design. The objective of this work is to develop a viable non-contact propulsion system utilizing Halbach arrays for all-electric flight, and many other applications. This concept will help to reduce harmful emissions, reduce the Nation s dependence on fossil fuels, and mitigate many of the concerns and limitations encountered in conventional aircraft propulsors. The physical layout consists of a ducted fan drum rotor with blades attached at the outer diameter and supported by a stress tuner ring at the inner diameter. The rotor is contained within a stator. This concept exploits the unique physical dimensions and large available surface area to optimize a custom, integrated, electromagnetic system that provides both the levitation and propulsion functions. The rotor is driven by modulated electromagnetic fields between the rotor and the stator. When set in motion, the time varying magnetic fields interact with passive coils in the stator assembly to produce repulsive forces between the stator and the rotor providing magnetic suspension. LDF can provide significant improvements in aviation efficiency, reliability, and safety, and has potential application in ultra-efficient motors, computers, and space power systems.

Eichenberg, Dennis J.↗

Physically-Informed Artificial Neural Networks for Atomistic Modeling of Materials

A new approach is presented for the development of classical interatomic potentials using physically-informed neural networks (PINN) combined with an analytical bond-order atomic interaction model. Due to the strong physical underpinnings, the PINN potentials demonstrate much better transferability than the existing machine-learning potentials while drastically improving the accuracy in comparison with traditional potentials. PINN potentials can be constructed for both metallic and covalent materials in a unified manner. A number of applications of PINN potentials to large-scale molecular dynamics and Monte Carlo simulations and calculation of thermal and mechanical properties of diverse materials are demonstrated. Some of the specific materials systems include silicon and aluminum, as well as alloys and compounds. Computational aspects of PINN potentials are discussed and future developments in this field are outlined.

J Hickman↗

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗