Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory

It has been well documented that decisions made in the early stages of Conceptual and Pre-Conceptual design commit up to 80% of total Life-Cycle Cost (LCC) while engineers know the least about the product they are designing [1]. Once within Preliminary and Detailed design however, making changes to the design becomes far more difficult to enact in both cost and schedule. Primarily this has been due to a lack of detailed data usually uncovered later during the Preliminary and Detailed design phases. In our current budget-constrained environment, making decisions within Conceptual and Pre-Conceptual design which minimize LCC while meeting requirements is paramount to a program's success. Within the arena of launch vehicle design, optimizing the ascent trajectory is critical for minimizing the costs present within such concerns as propellant, aerodynamic, aeroheating, and acceleration loads while meeting requirements such as payload delivered to a desired orbit. In order to optimize the vehicle design its constraints and requirements must be known, however as the design cycle proceeds it is all but inevitable that the conditions will change. Upon that change, the previously optimized trajectory may no longer be optimal, or meet design requirements. The current paradigm for adjusting to these updates is generating point solutions for every change in the design's requirements [2]. This can be a tedious, time-consuming task as changes in virtually any piece of a launch vehicle's design can have a disproportionately large effect on the ascent trajectory, as the solution space of the trajectory optimization problem is both non-linear and multimodal [3]. In addition, an industry standard tool, Program to Optimize Simulated Trajectories (POST), requires an expert analyst to produce simulated trajectories that are feasible and optimal [4]. In a previous publication the authors presented a method for combatting these challenges [5]. In order to bring more detailed information into Conceptual and Pre-Conceptual design, knowledge of the effects originating from changes to the vehicle must be calculated. In order to do this, a model capable of quantitatively describing any vehicle within the entire design space under consideration must be constructed. This model must be based upon analysis of acceptable fidelity, which in this work comes from POST. Design space interrogation can be achieved with surrogate modeling, a parametric, polynomial equation representing a tool. A surrogate model must be informed by data from the tool with enough points to represent the solution space for the chosen number of variables with an acceptable level of error. Therefore, Design Of Experiments (DOE) is used to select points within the design space to maximize information gained on the design space while minimizing number of data points required. To represent a design space with a non-trivial number of variable parameters the number of points required still represent an amount of work which would take an inordinate amount of time via the current paradigm of manual analysis, and so an automated method was developed. The best practices of expert trajectory analysts working within NASA Marshall's Advanced Concepts Office (ACO) were implemented within a tool called multiPOST. These practices include how to use the output data from a previous run of POST to inform the next, determining whether a trajectory solution is feasible from a real-world perspective, and how to handle program execution errors. The tool was then augmented with multiprocessing capability to enable analysis on multiple trajectories simultaneously, allowing throughput to scale with available computational resources. In this update to the previous work the authors discuss issues with the method and solutions

An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues. The methodology is two-fold: first, capture the heuristics developed by human analysts over their many years of experience; and secondly, leverage the power of modern computing to evaluate multiple trajectories simultaneously and therefore enable the exploration of the trajectory's design space early during the pre- conceptual and conceptual phases of design. This methodology is coupled with design of experiments in order to train surrogate models, which enables trajectory design space visualization and parametric optimal ascent trajectory information to be available when early design decisions are being made

Anisotropic scattering and quantum magnetoresistivities of a periodically modulated 2D electron gas

We calculate the longitudinal conductivities of a two-dimensional noninteracting electron gas in a uniform magnetic field and a lateral electric or magnetic periodic modulation in one spatial direction, in the quantum regime. We consider the effects of the electron-impurity scattering anisotropy through the vertex corrections on the Kubo formula, which are calculated with the Bethe-Salpeter equation, in the self-consistent Born approximation. We find that due to the scattering anisotropy the band conductivity increases, and the scattering conductivities decrease and become anisotropic. Our results are in qualitative agreement with recent experiments.Comment: 19 pages, 8 figures, Revtex, to appear in Phys. Rev.

Neutrino Quasielastic Scattering on Nuclear Targets: Parametrizing Transverse Enhancement (Meson Exchange Currents)

We present a parametrization of the observed enhancement in the transverse electron quasielastic (QE) response function for nucleons bound in carbon as a function of the square of the four momentum transfer ($Q^2$) in terms of a correction to the magnetic form factors of bound nucleons. The parametrization should also be applicable to the transverse cross section in neutrino scattering. If the transverse enhancement originates from meson exchange currents (MEC), then it is theoretically expected that any enhancement in the longitudinal or axial contributions is small. We present the predictions of the "Transverse Enhancement" model (which is based on electron scattering data only) for the $\nu_\mu, \bar{\nu}_\mu$ differential and total QE cross sections for nucleons bound in carbon. The $Q^2$ dependence of the transverse enhancement is observed to resolve much of the long standing discrepancy in the QE total cross sections and differential distributions between low energy and high energy neutrino experiments on nuclear targets.Comment: Revised Version- July 21, 2011: 17 pages, 20 Figures. To be published in Eur. Phys. J.

High CRLF2 expression associates with IKZF1 dysfunction in adult acute lymphoblastic leukemia without CRLF2 rearrangement.

Overexpression of cytokine receptor-like factor 2 (CRLF2) due to chromosomal rearrangement has been observed in acute lymphoblastic leukemia (ALL) and reported to contribute to oncogenesis and unfavorable outcome in ALL. We studied B-ALL and T-ALL patients without CRLF2 rearrangement and observed that CRLF2 is significantly increased in a subset of these patients. Our study shows that high CRLF2expression correlates with high-risk ALL markers, as well as poor survival. We found that the IKZF1-encoded protein, Ikaros, directly binds to the CRLF2 promoter and regulates CRLF2 expression in leukemia cells. CK2 inhibitor, which can increase Ikaros activity, significantly increases Ikaros binding in ALL cells and suppresses CRLF2 expression in an Ikaros-dependent manner. CRLF2 expression is significantly higher in patients with IKZF1 deletion as compared to patients without IKZF1 deletion. Treatment with CK2 inhibitor also results in an increase in IKZF1 binding to the CRLF2 promoter and suppression of CRLF2 expression in primary ALL cells. We further observed that CK2 inhibitor induces increased H3K9me3 histone modifications in the CRLF2 promoter in ALL cell lines and primary cells. Taken together, our results demonstrate that high expression of CRLF2 correlates with high-risk ALL and short survival in patients without CRLF2 rearrangement. Our results are the first to demonstrate that the IKZF1-encoded Ikaros protein directly suppresses CRLF2 expression through enrichment of H3K9me3 in its promoter region. Our data also suggest that high CRLF2 expression works with the IKZF1 deletion to drive oncogenesis of ALL and has significance in an integrated prognostic model for adult high-risk ALL

Für wen gebe ich mein Urteil ab? Der systematische Einfluss des Fragebogenadressaten auf Kausalattributionsgewichtungen bei geschlossenen Antwortformaten

Die Fragebogenforschung belegt, dass Respondenten durch Kontextinformationen eines Fragebogens systematisch in ihrem Antwortverhalten beeinflusst werden. So zeigten Norenzayan und Schwarz (1999), dass Probanden bei freier Antwortmöglichkeit eher persönlichkeitsbezogene Ursachen zur Erklärung von Straftaten nennen, wenn der Fragebogen scheinbar von einem Institut für Persönlichkeitsforschung (verglichen mit einem Institut für Sozialforschung) erstellt wurde. Hierzu diskutierte Erklärungen sind einerseits Konversationsmaximen, die einen Bezug zwischen Adressat und Gesagtem induzieren, andererseits kognitive Primings, die selektive kognitive Aktivierungen und damit Verfügbarkeiten bedingen sollen. Die vorliegende Studie untersucht diese Erklärungsalternativen, indem sie erstmals in einem analogen Studiendesign persönlichkeitsbezogene und soziale Gründe in geschlossenen Antwortformaten vorgibt und gewichten lässt. Mögliche Gewichtungsunterschiede sind somit nicht mittels kognitiver Verfügbarkeit erklärbar. Eine Kovarianzanalyse (Alter, Geschlecht und die Big-Five-Persönlichkeitsdimensionen als Kovariaten) belegt im Einklang mit den Konversationsmaximen eine signifikant stärkere Bedeutungszuschreibung für persönlichkeitsbezogene Ursachen unter der Bedingung „Institut für Persönlichkeitsforschung“ im Vergleich zu „Institut für Sozialforschung“ und einer Kontrollbedingung („Institut für Kriminologie“)

Growth of Ga₂O₃ by furnace oxidation of GaN studied by perturbed angular correlations

Ga₂O₃ is a promising material for use in “solar-blind” UV-detectors which can be produced efficiently by oxidation of GaN. In this study we focus on the evolution of the oxide layer when GaN is heated in air. The experimental method applied is the perturbed angular correlation (PAC) spectroscopy of γ-rays emitted by radioactive nuclides, here ¹¹¹Cd and ¹⁸¹Ta, whose parent nuclei are ion implanted into films of GaN grown on sapphire. As the emission pattern for nuclei in GaN is clearly distinct from that of nuclei in Ga₂O₃, the fraction of probe nuclei in the oxide layer can be directly measured and allows to follow the time dependent growth of the oxide on a scale of less than 100 nm. Additional measurements were carried out with the oxidized sample held at fixed temperatures in the temperature range from 19 K to 973 K showing transitions between the hyperfine interactions of ¹¹¹Cd in the oxide matrix both at high and low temperatures. A model for these transitions is proposed.Instituto de Física La Plat