Investigation of the Finite Element Software Packages at KSC

The useful and powerful features of NASTRAN and three real world problems for the testing of the capabilities of different NASTRAN versions are discussed. The test problems involve direct transient analysis, nonlinear analysis, and static analysis. The experiences in using graphics software packages are also discussed. It was found that MSC/XL can be more useful if it can be improved to generate picture files of the analysis results and to extend its capabilities to support finite element codes other than MSC/NASTRAN. It was found that the current version of SDRC/I-DEAS (version VI) may have bugs in the module 'Data Loader'

Deflections of anisotropic sandwich beams with variable face sheets and core thicknesses

A sandwich construction consists of a low-density core material with high strength face sheets bounded to the top and bottom surfaces. The construction has been widely used in the aerospace and marine industries due to its outstanding characteristics such as noise absorption, weight minimization, heat insulation, and better bending stiffness. In sandwich structures used in high-performance aircraft, the face sheets are often made of fiber-reinforced composite materials and the core is made of honeycomb. The structures may also have variable thickness so as to satisfy aerodynamic requirements. In the stress analysis, the constant-thickness face sheets are usually considered as membrane and the core is assumed to be inextensible but deformable in the thickness direction. The static behavior of variable-thickness, isotropic and homogeneous sandwich beams was successfully studied by employing a constant-thickness theory but allowing stiffnesses to vary in accordance with local thickness variations. It has been recently found in a refined theory that the analyses based on the constant thickness theory locally can lead to significant errors in structural responses if the sandwich beam is thickness-tapered and the cores are deformable in transverse shear. The errors arise mainly from two factors: (1) the transverse shear components of the membrane forces in the face sheets alter the transverse shears carried by the core; and (2) the face-sheet membrane strains arise from transverse shear deformation of the core. In practice the variable thickness may not only exist in core but also in face sheets. The thickness-variations may even be a type of step function. In this case the transverse shear stress in the face sheets and bending stress in the core should be taken into account in the refined theory mentioned. In the present study, energy principles are employed in deriving governing equations for general bending of anisotropic sandwich beams with variable thickness in both face sheets and cores. Solutions to these equations are based on a finite difference scheme. As an example in application, a simply supported thickness-tapered sandwich beam subject to a concentrated load at its center is considered. Let W' be the maximum deflection of the beam in which face sheets are considered as membrane, while W'' is that based on using the modified refined theory. It is found that W' is always larger than W'', however, the magnitude of (W'- W'') appears to be insensitive to the change of the taper of the beam

Study of the available finite element software packages at KSC

The interaction among the three finite element software packages, SDRCI/I-DEAS, MSC/NASTRAN, and I/FEM, used at NASA, Kennedy Space Center is addressed. The procedures for using more than one of these application software packages to model and analyze a structure design are discussed. Design and stress analysis of a solid rocket booster fixture is illustrated by using four different combinations of the three software packages. Their results are compared and show small yet acceptable differences

Suppression of nickel out-diffusion from porous nickel-titanium shape memory alloy by plasma immersion ion implantation

Summary form only given. Porous nickel titanium is a promising material for medical application not only because of its super elasticity and shape memory effect but also the porous structure which may enhance bone growth due to the increased surface area. It is thus especially suitable for bone tissue in-growth and fixation of biomedical implants. However, like its dense counterpart, Ni leaching from the materials causes health concern. Thus, in order to suppress Ni diffusion from the materials to body fluids and tissues in humans, a diffusion barrier or similar structure must be introduced. In this work, we produced this diffusion barrier layer by oxygen or nitrogen plasma immersion ion implantation (PIII). In vitro tests were conducted by immersing the plasma-treated NiTi into simulated body fluid (SBF) at 37plusmn0.5degC for 5 weeks and the resulting SBF was analyzed for Ni and Ti using inductively-coupled plasma mass spectrometry (ICMPS). Our results show that Ni leaching is significantly mitigated by both nitrogen and oxygen PIII.published_or_final_versio

Nickel suppression in Ni-Ti alloys by plasma immersion ion implantation surface treatment: New materials for orthopaedic implantation

Conference Theme: Spinal Motion Segment: From Basic Science to Clinical Applicationpublished_or_final_versio

Dirac Quantization of Open Strings and Noncommutativity in Branes

We apply the Dirac bracket quantization to open strings attached to branes in the presence of background antisymmetric field and recover an inherent noncommutativity in the internal coordinates of the brane.Comment: 25 pp, typos corrected, minor change

Paradoxical roles of antioxidant enzymes:Basic mechanisms and health implications

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are generated from aerobic metabolism, as a result of accidental electron leakage as well as regulated enzymatic processes. Because ROS/RNS can induce oxidative injury and act in redox signaling, enzymes metabolizing them will inherently promote either health or disease, depending on the physiological context. It is thus misleading to consider conventionally called antioxidant enzymes to be largely, if not exclusively, health protective. Because such a notion is nonetheless common, we herein attempt to rationalize why this simplistic view should be avoided. First we give an updated summary of physiological phenotypes triggered in mouse models of overexpression or knockout of major antioxidant enzymes. Subsequently, we focus on a series of striking cases that demonstrate “paradoxical” outcomes, i.e., increased fitness upon deletion of antioxidant enzymes or disease triggered by their overexpression. We elaborate mechanisms by which these phenotypes are mediated via chemical, biological, and metabolic interactions of the antioxidant enzymes with their substrates, downstream events, and cellular context. Furthermore, we propose that novel treatments of antioxidant enzyme-related human diseases may be enabled by deliberate targeting of dual roles of the pertaining enzymes. We also discuss the potential of “antioxidant” nutrients and phytochemicals, via regulating the expression or function of antioxidant enzymes, in preventing, treating, or aggravating chronic diseases. We conclude that “paradoxical” roles of antioxidant enzymes in physiology, health, and disease derive from sophisticated molecular mechanisms of redox biology and metabolic homeostasis. Simply viewing antioxidant enzymes as always being beneficial is not only conceptually misleading but also clinically hazardous if such notions underpin medical treatment protocols based on modulation of redox pathways

Artificial Neural Networks for Short-Term Load Forecasting in Microgrids Environment Energy

The adaptation of energy production to demand has been traditionally very important for utilities in order to optimize resource consumption. This is especially true also in microgrids where many intelligent elements have to adapt their behaviour depending on the future generation and consumption conditions. However, traditional forecasting has been performed only for extremely large areas, such as nations and regions. This work aims at presenting a solution for short-term load forecasting (STLF) in microgrids, based on a three-stage architecture which starts with pattern recognition by a self-organizing map (SOM), a clustering of the previous partition via k-means algorithm, and finally demand forecasting for each cluster with a multilayer perceptron. Model validation was performed with data from a microgrid-sized environment provided by the Spanish company Iberdrola. (C) 2014 Elsevier Ltd. All rights reserved.Hernandez, L.; Baladron, C.; Aguiar, JM.; Carro, B.; Sanchez-Esguevillas, A.; Lloret, J. (2014). Artificial Neural Networks for Short-Term Load Forecasting in Microgrids Environment Energy. Energy. 75:252-264. doi:10.1016/j.energy.2014.07.065S2522647