Small satellite access of the Space Network

Small satellites have been perceived as having limited access to NASA's Space Network (SN). The potential for satellite access of the Space Network when the design utilizes a fixed antenna configuration and low-power, coded transmission is analyzed. From the analysis, satellites using this configuration in high-inclination orbits are shown to have a daily data throughput in the 100 to 1000 Mbit range using the multiple access communications service     

Design and analysis of a regulated peak-power tracking system

A regulated peak-power tracking (RPPT) system for space power application is proposed. Large-signal stability analysis is provided to understand the main four different modes of operations of the system, as well as the mode transitions. A simple and effective control scheme for the system is also proposed. Small-signal analysis is performed thereafter to provide design optimization, and the predictions are verified by computer simulations     

A Parallel Adaptive 3D MHD Scheme for Modeling Coronal and Solar Wind Plasma Flows

A parallel adaptive mesh refinement (AMR) scheme is described for solving the governing equations of ideal magnetohydrodynamics (MHD) in three space dimensions. This solution algorithm makes use of modern finite-volume numerical methodology to provide a combination of high solution accuracy and computational robustness. Efficient and scalable implementations of the method have been developed for massively parallel computer architectures and high performance achieved. Numerical results are discussed for a simplified model of the initiation and evolution of coronal mass ejections (CMEs) in the inner heliosphere. The results demonstrate the potential of this numerical tool for enhancing our understanding of coronal and solar wind plasma processes. This revised version was published online in June 2006 with corrections to the Cover Date.     

Industry application of behavioral science

One of the more significant errors in the history of science occurred during the “marginal revolution” in economics near the end of the nineteenth century. Rather than explicitly recognize in basic theory that the happiness we seek to maximize in life originates within oneself, the early theorists formulated their equations as though human satisfaction resided in external things-as in so much utility (economist's term for satisfaction) per pound of sugar. Over the past 125 years, economists have developed mainstream mathematical economics on this incorrect basis resulting in the ill-founded neoclassical Equilibrium Theory. Because of this error economic theory is fundamentally timeless. The present theory, in its canonical form, corrects the early marginalist's error by identifying utility (time-integrated pleasure) exclusively with the stream-of-consciousness attending (expected) mental and physical activity. Time is now explicit in basic theory, thereby allowing, for the first time, the substantive computer-modeling of time-dependent, small- and large-scale economic systems. Furthermore, this new approach is methodologically compatible with mainstream sociology and institutional economics, allowing increased interdisciplinary cooperation that may influence policy and thereby affect industry and markets. And safety engineering stands to benefit from the accommodation of neuropsychology in understanding human error in the supervision and control of technology     

Bridging the gap between ATLAS and C: an open-systems approach toTPS re-host

As the DoD focuses on commercialization and open-architecture standards, the need to migrate existing TPSs from proprietary ATLAS-based platforms to an Open Systems platform becomes more critical. This paper will focus on a solution which leverages COTS software tools and emerging industry standards and technologies to implement object-oriented database tools which enable the conversion of an ATLAS TPS to an ANSI C environment     

Lithium Depletion in the Sun: A Study of Mixing Based on Hydrodynamical Simulations

Based on radiation hydrodynamics modeling of stellar convection zones, a diffusion scheme has been devised describing the downward penetration of convective motions beyond the Schwarzschild boundary (overshoot) into the radiative interior. This scheme of exponential diffusive overshoot has already been successfully applied to AGB stars. Here we present an application to the Sun in order to determine the time scale and depth extent of this additional mixing, i.e. diffusive overshoot at the base of the convective envelope. We calculated the associated destruction of lithium during the evolution towards and on the main-sequence. We found that the slow-mixing processes induced by the diffusive overshoot may lead to a substantial depletion of lithium during the Sun's main-sequence evolution. This revised version was published online in June 2006 with corrections to the Cover Date.     

Critique of some neural network architectures and claims forcontrol and estimation

While there is great potential for successful use of neural network (NN) algorithms in automatic target recognition (ATR) and other pattern identification/classification applications, significant barriers have been encountered that, to date, defy rigorous use of NNs within feedback control designs. The status of several problems and contradictions involving NNs relating to control and estimation theory applications (and to practical failure detection within INS/GPS navigation systems) are summarized here. To give a positive spin and for a balanced perspective, we also mention many novel laudable NN results obtained by invoking the techniques and results of control and estimation theory     

Pareto-optimal solution of a two-objective problem in choosing conditions of monoimpeller milling

A problem of optimization of cutting parameters with respect to the criteria of maximum efficiency and maximum tool resistance is formulated. To solve the problem, a method is developed and applied for determining the Pareto-optimal values of machining conditions in milling the present-day GTE monoimpeller blade passages with a circular milling cutter.     

A cost driven predictive maintenance policy for structural airframe maintenance

Airframe maintenance is traditionally performed at scheduled maintenance stops.The decision to repair a fuselage panel is based on a fixed crack size threshold,which allows to ensure the aircraft safety until the next scheduled maintenance stop.With progress in sensor technology and data processing techniques,structural health monitoring (SHM) systems are increasingly being considered in the aviation industry.SHM systems track the aircraft health state continuously,lead ing to the possibility of planning maintenance based on an actual state of aircraft rather than on a fixed schedule.This paper builds upon a model-based prognostics framework that the authors developed in their previous work,which couples the Extended Kalman filter (EKF) with a first order perturbation (FOP) method.By using the information given by this prognostics method,a novel cost driven predictive maintenance (CDPM) policy is proposed,which ensures the aircraft safety while minimizing the maintenance cost.The proposed policy is formally derived based on the trade-off between probabilities of occurrence of scheduled and unscheduled maintenance.A numerical case study simulating the maintenance process of an entire fleet of aircrafts is imple mented.Under the condition of assuring the same safety level,the CDPM is compared in terms of cost with two other maintenance policies:scheduled maintenance and threshold based SHM maintenance.The comparison results show CDPM could lead to significant cost savings.