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This viewgraph presentation gives an overview of the architecture of the James Webb Space Telescope, and explains how integrated modeling is useful for analyzing wavefront, thermal distortion, subsystems, and image motion/jitter for the telescope design.
The James Web Space Telescope (JWST) is a large, infrared-optimized space telescope scheduled for launch in 2011. This is a continuation of a series of papers on modeling activities for JWST. The structural-thermal-optical, often referred to as STOP, analysis process is used to predict the effect of thermal distortion on optical performance. The benchmark STOP analysis for JWST assesses the effect of an observatory slew on wavefront error. Temperatures predicted using geometric and thermal math models are mapped to a structural finite element model in order to predict thermally induced deformations. Motions and deformations at optical surfaces are then input to optical models, and optical performance is predicted using either an optical ray trace or a linear optical analysis tool. In addition to baseline performance predictions, a process for performing sensitivity studies to assess modeling uncertainties is described.
The James Web Space Telescope (JWST) is a large, infrared-optimized space telescope scheduled for launch in 2011. System-level verification of critical optical performance requirements will rely on integrated modeling to a considerable degree. In turn, requirements for accuracy of the models are significant. The size of the lightweight observatory structure, coupled with the need to test at cryogenic temperatures, effectively precludes validation of the models and verification of optical performance with a single test in 1-g. Rather, a complex series of steps are planned by which the components of the end-to-end models are validated at various levels of subassembly, and the ultimate verification of optical performance is by analysis using the assembled models. This paper describes the critical optical performance requirements driving the integrated modeling activity, shows how the error budget is used to allocate and track contributions to total performance, and presents examples of integrated modeling methods and results that support the preliminary observatory design. Finally, the concepts for model validation and the role of integrated modeling in the ultimate verification of observatory are described.
The James Web Space Telescope (JWST) is a large, infrared-optimized, space telescope scheduled for launch to L2 in 2011. It must meet rigorous thermal stability requirements, almost all of which will be verified through analysis. Terrestrial testing will be performed but even that will require significant analytical interpretation of results. Preliminary analysis indicates that traditional second-order effects could cause the telescope to exceed established performance requirements. This leads to very large detailed models, primarily since composite tubes are being modeled using solid elements. To minimize differences between the current baseline and the model the project is using a number of rapid analysis cycles. The large size of the telescope models and the short cycle time creates a demanding multidisciplinary analysis environment.
Remote sensing of rotational transitions in the Earth's atmosphere has become an important method for the retrieval of geophysical temperatures, pressures and chemical composition profiles that requires accurate spectral information. This paper highlights the current status of rotational data that are useful for atmospheric measurements, with a discussion of the types the rotational lineshape measurements that are not generally available in either online repository.
The Apollo and Russian missions during 1970's were reviewed to rediscover the type and distribution of minerals on the Moon. This study revealed that the Moon is a relatively barren place in mineral content when compared with the Earth. Results from the Lunar minerals brought back to Earth, indicate that the Moon lacks water, hydroxyl ions, and carbon based minerals. Our approach to prospecting utilizes a vehicle with sensors embedded in a wheel that allow measurements while the vehicle is in motion. Once a change in soil composition is detected, decision making software stops the vehicle and analytical instruments perform a more definitive analysis of the soil. The focus of this paper is to describe the instrumentation and data from the wheel-based sensors.
A computer program in the guidance system of a mobile robot generates estimates of the position and attitude of the robot, using features of the terrain on which the robot is moving, by processing digitized images acquired by a stereoscopic pair of electronic cameras mounted rigidly on the robot. Developed for use in localizing the Mars Exploration Rover (MER) vehicles on Martian terrain, the program can also be used for similar purposes on terrestrial robots moving in sufficiently visually textured environments: examples include low-flying robotic aircraft and wheeled robots moving on rocky terrain or inside buildings. In simplified terms, the program automatically detects visual features and tracks them across stereoscopic pairs of images acquired by the cameras. The 3D locations of the tracked features are then robustly processed into an estimate of overall vehicle motion. Testing has shown that by use of this software, the error in the estimate of the position of the robot can be limited to no more than 2 percent of the distance traveled, provided that the terrain is sufficiently rich in features. This software has proven extremely useful on the MER vehicles during driving on sandy and highly sloped terrains on Mars.
Not long after the discovery of the Antarctic ozone hole, it was established that halogen compounds, supplied to the atmosphere mainly by anthropogenic activities, are the primary driver of polar ozone loss. We will briefly review the chemical mechanisms that cause polar ozone loss and the early evidence showing the key role played by anthropogenic halogens. Recently, stratospheric halogen loading has leveled off, due to adherence to the Montreal Protocol and its amendments that has essentially banned CFCs (chlorofluorocarbons) and other halocarbons. We will describe recent reports of the first stage of recovery of the Antarctic ozone hole (e.g., a statistically significant slowing of the downward trend), associated with the leveling off of stratospheric halogens. Despite this degree of understanding, we will discuss the tendency of photochemical models to underestimate the observed rate of polar ozone loss and a hypothesis that has recently been put forth that might resolve this discrepancy. Finally, we will briefly discuss chemical loss of Arctic ozone, which
A sensitive laser spectrometer, named IRIS (water isotope ratio infrared spectrometer), was developed for the in situ detection of the isotopic composition of water vapour in the upper troposphere and the lower stratosphere. Isotope ratio measurements can be used to quantify troposphere stratosphere exchange, and to study the water chemistry in the stratosphere. IRIS is based on the technique of optical feedback cavity-enhanced absorption spectroscopy. It uses a room temperature near-infrared laser, and does not require cryogenic cooling of laser or detectors. The instrument weighs 51 kg including its support structure. Airborne operation was demonstrated during three flights aboard the European M55-Geophysica stratospheric research aircraft, as part of the AMMA/SCOUT-03 (African Monsoon Multidisciplinary Analysis/Stratospheric Climate links with emphasis on the Upper Troposphere and lower stratosphere) campaign in Burkina Faso in August 2006. The data are discussed with reference to a Rayleigh distillation model. As expected, there is no indication of non-mass-dependent fractionation (also known as mass-independent fractionation) in the troposphere. Furthermore, improvements to the thermal management system and a move to a (cryogen-free) longer-wavelength laser source are discussed, which together should result in approximately two orders of magnitude improvement of the sensitivity
There are inherent uncertainties and errors associated with using Computational Fluid Dynamics (CFD) to predict the flow field and there is no standard method for evaluating uncertainty in the CFD community. This paper describes an approach to -validate the . uncertainty in using CFD. The method will use the state of the art uncertainty analysis applying different turbulence niodels and draw conclusions on which models provide the least uncertainty and which models most accurately predict the flow of a backward facing step.
The Damper Spring Unit (DSU, see Figure 1) has been designed to provide the damping required to control the deployment speed of the spring driven solar array deployment in an ARA Mk3 or FRED based Solar Array in situations where the standard application of a damper at the root-hinge is not feasible. The unit consists of four major parts: a main bracket, an eddy current damper, a spring unit, an actuation pulley which is coupled via Kevlar cables to a synchro-pulley of a hinge. The damper slows down the deployment speed and prevents deployment shocks at deployment completion. The spring unit includes 4 springs which overcome the resistances of the damper and the specific DSU control cable loop. This means it can be added to any spring driven deployment system without major modifications of that system. Engineering models of the Sentinel 1 solar array wing have been built to identify the deployment behavior, and to help to determine the optimal pulley ratios of the solar array and to finalize the DSU design. During the functional tests, the behavior proved to be very sensitive for the alignment of the DSU. This was therefore monitored carefully during the qualification program, especially prior to the TV cold testing. During TV "Cold" testing the measured retarding torque exceeded the max. required value: 284 N-mm versus the required 247 N-mm. Although this requirement was not met, the torque balance analysis shows that the 284 N-mm can be accepted, because the spring unit can provide 1.5 times more torque than required. Some functional tests of the DSU have been performed without the eddy current damper attached. It provided input data for the ADAMS solar array wing model. Simulation of the Sentinel-1 deployment (including DSU) in ADAMS allowed the actual wing deployment tests to be limited in both complexity and number of tests. The DSU for the Sentinel-1 solar array was successfully qualified and the flight models are in production.
Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact problem and uncertainties exist. There is a method to approximate the errors in CFD via Richardson's Extrapolation. This method is based off of progressive grid refinement. To estimate the errors, the analyst must interpolate between at least three grids. This paper describes a study to find an appropriate interpolation scheme that can be used in Richardson's extrapolation or other uncertainty method to approximate errors.
Computational Fluid Dynamics (CFD) is the standard numerical tool used by Fluid Dynamists to estimate solutions to many problems in academia, government, and industry. CFD is known to have errors and uncertainties and there is no universally adopted method to estimate such quantities. This paper describes an approach to estimate CFD uncertainties strictly numerically using inputs and the Student-T distribution. The approach is compared to an exact analytical solution of fully developed, laminar flow between infinite, stationary plates. It is shown that treating all CFD input parameters as oscillatory uncertainty terms coupled with the Student-T distribution can encompass the exact solution.
A tunable diode laser sensor was designed for in situ monitoring of temperature in the arc heater of the NASA Ames IHF arcjet facility (60 MW). An external cavity diode laser was used to generate light at 777.2 nm and laser absorption used to monitor the population of electronically excited oxygen atoms in an air plasma flow. Under the assumption of thermochemical equilibrium, time-resolved temperature measurements were obtained on four lines-of-sight, which enabled evaluation of the temperature uniformity in the plasma column for different arcjet operating conditions.
We use the NASA GEOS Chemistry Climate Model (GEOSCCM) to quantify the contribution of two most important brominated very short-lived substances (VSLS), bromoform (CHBr3) and dibromomethane (CH2Br2), to stratospheric bromine and its sensitivity to convection strength. Model simulations suggest that the most active transport of VSLS from the marine boundary layer through the tropopause occurs over the tropical Indian Ocean, the Western Pacific warm pool, and off the Pacific coast of Mexico. Together, convective lofting of CHBr3 and CH2Br2 and their degradation products supplies ∼8 ppt total bromine to the base of the Tropical Tropopause Layer (TTL, ∼150 hPa), similar to the amount of VSLS organic bromine available in the marine boundary layer (∼7.8-8.4 ppt) in the above active convective lofting regions. Of the total ∼8 ppt VSLS-originated bromine that enters the base of TTL at ∼150 hPa, half is in the form of source gas injection (SGI) and half as product gas injection (PGI). Only a small portion (< 10%) the VSLS-originated bromine is removed via wet scavenging in the TTL before reaching the lower stratosphere. On global and annual average, CHBr3 and CH2Br2, together, contribute ∼7.7 pptv to the present-day inorganic bromine in the stratosphere. However, varying model deep convection strength between maximum and minimum convection conditions can introduce a ∼2.6 pptv uncertainty in the contribution of VSLS to inorganic bromine in the stratosphere (BryVSLS). Contrary to the conventional wisdom, minimum convection condition leads to a larger BryVSLS as the reduced scavenging in soluble product gases, thus a significant increase in PGI (2-3 ppt), greatly exceeds the relative minor decrease in SGI (a few 10ths ppt.
A large proportion of reactive nitrogen loss from polar sediments is mediated by denitrification, but microorganisms mediating denitrification in polar environments remain poorly characterized. A combined approach of most-probable-number (MPN) enumeration, cultivation and physiological characterization was used to describe psychrophilic denitrifying bacterial communities in sediments of three Arctic fjords in Svalbard (Norway). A MPN assay showed the presence of 10(sup 3)−10(sup 6) cells of psychrophilic nitrate-respiring bacteria g(sup −1) of sediment. Fifteen strains within the Proteobacteria were isolated using a systematic enrichment approach with organic acids as electron donors and nitrate as an electron acceptor. Isolates belonged to five genera, including Shewanella, Pseudomonas, Psychromonas (Gammaproteobacteria), Arcobacter (Epsilonproteobacteria) and Herminiimonas (Betaproteobacteria). All isolates were denitrifiers, except Shewanella, which exhibited the capacity for dissimilatory nitrate reduction to ammonium (DNRA). Growth from 0 to 40 degC demonstrated that all genera except Shewanella were psychrophiles with optimal growth below 15 degC, and adaptation to low temperature was demonstrated as a shift from primarily C16:0 saturated fatty acids to C16:1 monounsaturated fatty acids at lower temperatures. This study provides the first targeted enrichment and characterization of psychrophilic denitrifying bacteria from polar sediments, and two genera, Arcobacter and Herminiimonas, are isolated for the first time from permanently cold marine sediments.
This paper deals with the accurate microscopic simulation and macroscopic modeling of extreme non-equilibrium phenomena, such as encountered during hypersonic entry into a planetary atmosphere. The state-to-state microscopic equations involving internal excitation, de-excitation, dissociation, and recombination of nitrogen molecules due to collisions with nitrogen atoms are solved time-accurately. Strategies to increase the numerical efficiency are discussed. The problem is then modeled using a few macroscopic variables. The model is based on reconstructions of the state distribution function using the maximum entropy principle. The internal energy space is subdivided into multiple groups in order to better describe the non-equilibrium gases. The method of weighted residuals is applied to the microscopic equations to obtain macroscopic moment equations and rate coefficients. The modeling is completely physics-based, and its accuracy depends only on the assumed expression of the state distribution function and the number of groups used. The model makes no assumption at the microscopic level, and all possible collisional and radiative processes are allowed. The model is applicable to both atoms and molecules and their ions. Several limiting cases are presented to show that the model recovers the classical twotemperature models if all states are in one group and the model reduces to the microscopic equations if each group contains only one state. Numerical examples and model validations are carried out for both the uniform and linear distributions. Results show that the original over nine thousand microscopic equations can be reduced to 2 macroscopic equations using 1 to 5 groups with excellent agreement. The computer time is decreased from 18 hours to less than 1 second.
There have been few discussions on using Computational Fluid Dynamics (CFD) without experimental validation. Pairing experimental data, uncertainty analysis, and analytical predictions provides a comprehensive approach to verification and is the current state of the art. With pressed budgets, collecting experimental data is rare or non-existent. This paper investigates and proposes a method to perform CFD uncertainty analysis only from computational data. The method uses current CFD uncertainty techniques coupled with the Student-T distribution to predict the heat transfer coefficient over a at plate. The inputs to the CFD model are varied from a specified tolerance or bias error and the difference in the results are used to estimate the uncertainty. The variation in each input is ranked from least to greatest to determine the order of importance. The results are compared to heat transfer correlations and conclusions drawn about the feasibility of using CFD without experimental data. The results provide a tactic to analytically estimate the uncertainty in a CFD model when experimental data is unavailable