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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly. Both the visible and infrared subsystems scan in pushbroom mode: that is, an aircraft carrying the system moves along a ground track, the system is aimed downward, and image data are acquired in across-track linear arrays of pixels. Both subsystems operate at a frame rate of 30 Hz. The infrared and visible-light optics are adjusted so that both subsystems are aimed at the same moving swath, which has across-track angular width of 15 . Data from the infrared and visible imaging subsystems are stored in the same file along with aircraft- position data acquired by a Global Positioning System receiver. The combination of the three sets of data is used to construct infrared and hyperspectral maps of scanned areas (see figure). The visible subsystem is based on a grating spectrograph and a rapid-readout charge-coupled-device camera. Images of the swatch are acquired in 256 spectral bands at wavelengths from 400 to 800 nm. The infrared subsystem, which is sensitive in a single wavelength band of 8 to 10 m, is based on a focal-plane array of HgCdTe photodetectors that are cooled to an operating temperature of 77 K by use of a closed-Stirling-cycle mechanical cooler. The nonuniformities of the HgCdTe photodetector array are small enough that the raw pixel data from the infrared subsystem can be used to recognize temperature differences on the order of 1 C. By use of a built-in blackbody calibration source that can be switched into the field of view, one can obtain bias and gain offset terms for individual pixels, making it possible to offset the effects of nonuniformities sufficiently to enable the measurement of temperature differences as small as 0.1 C.

Lucey, Paul G.↗
NASA NTRS2005

Full-Circle Resolver-to-Linear-Analog Converter

A circuit generates sinusoidal excitation signals for a shaft-angle resolver and, like the arctangent circuit described in the preceding article, generates an analog voltage proportional to the shaft angle. The disadvantages of the circuit described in the preceding article arise from the fact that it must be made from precise analog subcircuits, including a functional block capable of implementing some trigonometric identities; this circuitry tends to be expensive, sensitive to noise, and susceptible to errors caused by temperature-induced drifts and imprecise matching of gains and phases. These disadvantages are overcome by the design of the present circuit. The present circuit (see figure) includes an excitation circuit, which generates signals Ksin(Omega(t)) and Kcos(Omega(t)) [where K is an amplitude, Omega denotes 2(pi)x a carrier frequency (the design value of which is 10 kHz), and t denotes time]. These signals are applied to the excitation terminals of a shaft-angle resolver, causing the resolver to put out signals C sin(Omega(t)-Theta) and C cos(Omega(t)-Theta). The cosine excitation signal and the cosine resolver output signal are processed through inverting comparator circuits, which are configured to function as inverting squarers, to obtain logic-level or square-wave signals .-LL[cos(Omega(t)] and -LL[cos(Omega(t)-Theta)], respectively. These signals are fed as inputs to a block containing digital logic circuits that effectively measure the phase difference (which equals Theta between the two logic-level signals). The output of this block is a pulse-width-modulated signal, PWM(Theta), the time-averaged value of which ranges from 0 to 5 VDC as Theta ranges from .180 to +180deg. PWM(Theta) is fed to a block of amplifying and level-shifting circuitry, which converts the input PWM waveform to an output waveform that switches between precise reference voltage levels of +10 and -10 V. This waveform is processed by a two-pole, low-pass filter, which removes the carrier-frequency component. The final output signal is a DC potential, proportional to Theta that ranges continuously from -10 V at Theta = -180deg to +10 V at Theta = +180deg..

Alhorn, Dean C.↗
NASA NTRS2007

Increasing Linear Dynamic Range of a CMOS Image Sensor

A generic design and a corresponding operating sequence have been developed for increasing the linear-response dynamic range of a complementary metal oxide/semiconductor (CMOS) image sensor. The design provides for linear calibrated dual-gain pixels that operate at high gain at a low signal level and at low gain at a signal level above a preset threshold. Unlike most prior designs for increasing dynamic range of an image sensor, this design does not entail any increase in noise (including fixed-pattern noise), decrease in responsivity or linearity, or degradation of photometric calibration. The figure is a simplified schematic diagram showing the circuit of one pixel and pertinent parts of its column readout circuitry. The conventional part of the pixel circuit includes a photodiode having a small capacitance, CD. The unconventional part includes an additional larger capacitance, CL, that can be connected to the photodiode via a transfer gate controlled in part by a latch. In the high-gain mode, the signal labeled TSR in the figure is held low through the latch, which also helps to adapt the gain on a pixel-by-pixel basis. Light must be coupled to the pixel through a microlens or by back illumination in order to obtain a high effective fill factor; this is necessary to ensure high quantum efficiency, a loss of which would minimize the efficacy of the dynamic- range-enhancement scheme. Once the level of illumination of the pixel exceeds the threshold, TSR is turned on, causing the transfer gate to conduct, thereby adding CL to the pixel capacitance. The added capacitance reduces the conversion gain, and increases the pixel electron-handling capacity, thereby providing an extension of the dynamic range. By use of an array of comparators also at the bottom of the column, photocharge voltages on sampling capacitors in each column are compared with a reference voltage to determine whether it is necessary to switch from the high-gain to the low-gain mode. Depending upon the built-in offset in each pixel and in each comparator, the point at which the gain change occurs will be different, adding gain-dependent fixed pattern noise in each pixel. The offset, and hence the fixed pattern noise, is eliminated by sampling the pixel readout charge four times by use of four capacitors (instead of two such capacitors as in conventional design) connected to the bottom of the column via electronic switches SHS1, SHR1, SHS2, and SHR2, respectively, corresponding to high and low values of the signals TSR and RST. The samples are combined in an appropriate fashion to cancel offset-induced errors, and provide spurious-free imaging with extended dynamic range.

Pain, Bedabrata↗
NASA NTRS2000

Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks

Development of characteristic tissue patterns requires that individual cells be switched locally between different phenotypes or "fates;" while one cell may proliferate, its neighbors may differentiate or die. Recent studies have revealed that local switching between these different gene programs is controlled through interplay between soluble growth factors, insoluble extracellular matrix molecules, and mechanical forces which produce cell shape distortion. Although the precise molecular basis remains unknown, shape-dependent control of cell growth and function appears to be mediated by tension-dependent changes in the actin cytoskeleton. However, the question remains: how can a generalized physical stimulus, such as cell distortion, activate the same set of genes and signaling proteins that are triggered by molecules which bind to specific cell surface receptors. In this article, we use computer simulations based on dynamic Boolean networks to show that the different cell fates that a particular cell can exhibit may represent a preprogrammed set of common end programs or "attractors" which self-organize within the cell's regulatory networks. In this type of dynamic network model of information processing, generalized stimuli (e.g., mechanical forces) and specific molecular cues elicit signals which follow different trajectories, but eventually converge onto one of a small set of common end programs (growth, quiescence, differentiation, apoptosis, etc.). In other words, if cells use this type of information processing system, then control of cell function would involve selection of preexisting (latent) behavioral modes of the cell, rather than instruction by specific binding molecules. Importantly, the results of the computer simulation closely mimic experimental data obtained with living endothelial cells. The major implication of this finding is that current methods used for analysis of cell function that rely on characterization of linear signaling pathways or clusters of genes with common activity profiles may overlook the most critical features of cellular information processing which normally determine how signal specificity is established and maintained in living cells. Copyright 2000 Academic Press.

Review↗
NASA NTRSDate not supplied

Individual Variability and Predictive Biomarkers of Human Sensitivity to Ionizing Radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating personalized health risks from space radiation exposure requires understanding the factors underlying individual radiation sensitivity, which currently remain unknown. We started to address this challenge by identifying the genomic and demographic associations with sensitivity to low and high-LET ionizing radiation in the largest human sample cohort to date and by evaluating baseline DNA damage as a potential predictor of radiation responses. We have collected and irradiated peripheral blood mononuclear cells (PBMCs) from 768 healthy donors of matched ethnicity, 50/50 male/female, 18-70 years old. We have analyzed the responses of 576 donor PBMCs to irradiation with simulated galactic cosmic ray components: 350MeV/n 28Si, 350MeV/n 40Ar and 600MeV/n 56Fe, at 1.1 and 3 particles/100μm2 fluences, as well as 0.1Gy and 1Gy doses of gamma rays, at 4 and 24 hours post irradiation. We quantified post-irradiation DNA repair based on radiation-induced 53BP1+ foci formation, together with oxidative stress and cell death using a flow cytometry-based assay. We also assessed baseline levels of DNA repair in PBMCs at the time of sample collection prior to irradiation experiments. We observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing with LET, though oxidative stress being notably reduced by high-LET irradiation, potentially due to a switch between hydrogen peroxide and oxygen radical-based mechanisms. We also identified a relationship between few DNA repair foci at baseline and increased DNA repair after irradiation, accompanied by an alteration in immunoregulatory cytokine secretion, which might be adapted as biomarkers to predict ionizing radiation sensitivity. Among demographic variables, baseline foci levels were positively associated with age and latent cytomegalovirus infection. Finally, we have performed low-throughput whole genome sequencing of all samples and are currently in process of identifying the genes and pathways associated with low and high-LET ionizing radiation sensitivity in humans.

Space radiation, human spaceflight, DNA damage↗
NASA NTRS1991

Nonlinear optical properties of organic materials: A theoretical study

Replacement of electronic switching circuits in computing and telecommunication systems with purely optical devices offers the potential for extremely high throughput and compact information processing systems. The potential application of organic materials containing molecules with large nonresonant nonlinear effects in this area have triggered intensive research during the last decade. Interest on this area was due to two facts: (1) that many organic materials show nonlinearities that are orders of magnitude larger than those of conventional inorganic materials such as lithium niobate and potassium dihydrogen phosphate; and (2) that organic materials show much flexibility in terms of molecular designs. Some of the desirable characteristics that these materials should have are that they be transparent to the frequency of the incident laser and its second or third harmonic, that they have a high damage threshold, and, in the case of second-order effects, that their crystal structure or molecular orientation be accentric. Since polymeric assemblages can enhance the nonlinear response of organic molecules severalfold, efforts have been directed toward the synthesis of thin films with interpenetrating lattices of electroactive molecules. The goal of this theoretical investigation is to predict the magnitude of the molecular polarizabilities of organic molecules that could be incorporated into films. These calculations are intended to become a powerful tool to assist material scientists in screening for the best candidates for optical applications. The procedure that was developed for the present calculations is based on the static-field approach, and is a modification to the method developed by Dewar and Stewart, 1984 for calculating molecular linear polarizabilities.

Cardelino, Beatriz H.↗
NASA NTRS2005

Single Event Transients in Linear Integrated Circuits

On November 5, 2001, a processor reset occurred on board the Microwave Anisotropy Probe (MAP), a NASA mission to measure the anisotropy of the microwave radiation left over from the Big Bang. The reset caused the spacecraft to enter a safehold mode from which it took several days to recover. Were that to happen regularly, the entire mission would be compromised, so it was important to find the cause of the reset and, if possible, to mitigate it. NASA assembled a team of engineers that included experts in radiation effects to tackle the problem. The first clue was the observation that the processor reset occurred during a solar event characterized by large increases in the proton and heavy ion fluxes emitted by the sun. To the radiation effects engineers on the team, this strongly suggested that particle radiation might be the culprit, particularly when it was discovered that the reset circuit contained three voltage comparators (LM139). Previous testing revealed that large voltage transients, or glitches appeared at the output of the LM139 when it was exposed to a beam of heavy ions [NI96]. The function of the reset circuit was to monitor the supply voltage and to issue a reset command to the processor should the voltage fall below a reference of 2.5 V [PO02]. Eventually, the team of engineers concluded that ionizing particle radiation from the solar event produced a negative voltage transient on the output of one of the LM139s sufficiently large to reset the processor on MAP. Fortunately, as of the end of 2004, only two such resets have occurred. The reset on MAP was not the first malfunction on a spacecraft attributed to a transient. That occurred shortly after the launch of NASA s TOPEX/Poseidon satellite in 1992. It was suspected, and later confirmed, that an anomaly in the Earth Sensor was caused by a transient in an operational amplifier (OP-15) [KO93]. Over the next few years, problems on TDRS, CASSINI, [PR02] SOHO [HA99,HA01] and TERRA were also attributed to transients. In some cases, such events produced resets by falsely triggering circuits designed to protect against over- voltage or over-current. On at least three occasions, transients caused satellites to switch into "safe mode" in which most of the systems on board the satellites were powered down for an extended period. By the time the satellites were reconfigured and returned to full operational state, much scientific data had been lost. Fortunately, no permanent damage occurred in any of the systems and they were all successfully re-activated.

Buchner, Stephen↗
DOE OSTI2024

A magnetic diagnostic suite for the Pegasus-III experiment

Pegasus-III is an ultralow aspect ratio spherical tokamak providing a dedicated US experiment for comparative solenoid-free startup studies. A new magnetic diagnostic suite for equilibrium and low frequency (<200 kHz) magnetohydrodynamic mode analysis has been installed. These new diagnostics address the significant challenges of measuring magnetic field in a high noise environment with the majority constrained to fit in an 8 mm diagnostic gap on the high field side. Electrostatic switching noise generated by the 16 independent current feedback-controlled power supplies produces dV cm /dt ~ 1 kV/μs and volt level common mode noise on the magnetics. Immunity to this switching noise is accomplished through differential signal runs and signal processing, along with end-to-end electromagnetic interference shielding. The magnetic measurements are simultaneously digitized at 1 MHz and conditioned by precision 8 pole Butterworth filters with a corner frequency of 200 kHz to prevent aliasing down to the 16-bit level over the full passband. Ex-vessel calibrations of the B p coils were completed with a typical uncertainty of <0.5%. Stray toroidal field pickup from coil misalignment or positioning errors is corrected using a physics-based model. Comparisons of the corrected measurements to modeling agree to within 1.3% on average. This is within the 1.5% measurement uncertainty that a sensitivity analysis determined is needed for accurate fast boundary and equilibrium reconstruction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

Neurovascular Responses to Simulated Deep Space Radiation in a Human Organ-on-a-Chip Model

A major health risk for human deep space exploration is central nervous system (CNS) damage by galactic cosmic ray radiation. Simulated galactic cosmic rays or their components, especially the high-linear energy transfer (LET) particles such as 56Fe ions, have been shown to cause CNS damage, neuroinflammation and cognitive dysfunction in rodent models, but their effects on human CNS remain to be investigated. CNS damage from any insult, including ionizing radiation, is partially mediated by the blood-brain barrier (BBB), which regulates interactions between CNS and the rest of the body. The main cellular regulators of BBB permeability are astrocytes, which also modulate neuroinflammation. However, there have been few studies on BBB and astrocyte functions in regulating CNS responses, especially in human tissue analogs. Therefore, we utilized a high-throughput 3D organ-on-a-chip system, seeded with human induced pluripotent stem cell-derived astrocytes and brain endothelial cells, or brain endothelial cells alone, to study human neurovascular responses to simulated deep space radiation. We investigated the permeability and morphology of vascular structures formed by endothelial cells, as well as oxidative stress and secreted cytokines and chemokine levels over 1-7 days after irradiation with 0.25 – 0.5 Gy 5-ion simplified simulated galactic cosmic rays or 0.3 – 0.8 Gy high-LET 600 MeV/n 56Fe particles, and compared the outcomes to low-LET X-ray irradiation. We observed that simulated deep space radiation caused delayed astrocyte activation in a pattern resembling CNS responses to brain injury, caused oxidative stress and the production of inflammatory cytokines, and compromised BBB integrity by damaging tight junctions, thus increasing vascular permeability. Furthermore, our results indicate that astrocytes have a dual role in regulating radiation responses: they exacerbate blood-brain barrier permeability early after irradiation, followed by switching to a more protective scar-like phenotype by reducing oxidative stress and pro-inflammatory cytokine and chemokine secretion. In a follow-up study using the same platform, we investigated the dose-rate effects of ionizing radiation, by exposing our model to chronic, low dose-rate, gamma radiation. Our model was significantly improved by adding additional cell types composing the BBB, modelling immune cell infiltration into the brain, and studying the effect of an antioxidant, to measure more complex outcomes and model more closely the effect of deep space radiation on the human BBB. In summary, our results present a human neurovascular model for space radiation studies and potential future automated payload adaptation, and suggest astrocyte regulatory mechanisms as targets for countermeasures to mitigate human neurovascular impairments during deep space exploration.

Ionizing radiation↗
DOE OSTI2023

Evaluation of Zero-Net-Rate Pumping Tests

Accurately estimating the distribution of aquifer properties is key to understanding contaminant movement in the subsurface. The distribution of aquifer properties is typically addressed using slug or constant-rate well tests, and the pros and cons of these tests are well known. Slug tests are appealing because they avoid removing contaminated water, but their results are affected by well skin and the small volume of displaced water limits the volume of aquifer that can be evaluated. Constant-rate well tests have the disadvantage of requiring disposal of potentially contaminated water, but they can generate properties that are more representative than slug tests, and they can be used to estimate well efficiency and storativity, which are difficult to characterize using slug tests. Periodic pumping tests are appealing because they have many of the advantages and few of the disadvantages of slug and constant-rate well tests. Periodic pumping tests involve cycling the pumping rate with a regular period and measuring the resulting response in monitoring wells. Some of these tests involve imposing a periodic rate on a constant mean rate. However, other tests involve moving water out and back into the well at rates that are balanced so the net rate after each period is zero. Some zero-net-rate (ZNR) well tests use rates that follow a sinusoidal pattern, whereas others use a square wave pattern that switches between a constant rate of pumping and a constant rate of injection to achieve a zero-net rate. ZNR well tests appear to be a useful compromise between slug and constant rate tests, but methods for conducting and analyzing the results from these tests have received limited evaluation. Periodic pumping tests are typically evaluated through recorded pressure responses to a disturbance source. Recent work has demonstrated that the strain field in the vadose zone shows a response to disturbances in the underlying aquifer. Various instrument designs are available that can record vertical and horizontal strain to very precise resolutions (10-9 ε). Measuring the strain in the vadose zone can present lower costs than measuring pressure in a monitoring well, so using strain could improve the resolution of ZNR tests, as well as make these tests potentially cheaper. A ZNR periodic pumping system was constructed and used to perform tests in the Clemson, South Carolina area. The system was designed to pump and inject with a periodic square-wave, so pumping occurs at a constant rate for half the period and is followed by injection at the same rate for half the period resulting in no net gain or loss of water from the aquifer. The system is designed to generate flow rates from 1 to 3.5 gallons per minute (gpm) with a capacity of 875-gallon per half period. Pressure and strain monitoring points are located in the vicinity of the pumping well. A series of 10 ZNR periodic pumping tests were conducted at the field site, with periods ranging from 2 to 540 minutes. Pressure data were collected and recorded in four monitoring wells in various locations around the pumping well. In addition, vertical and horizontal strain and tilt data were recorded in various locations around the pumping well. Traditional aquifer tests, including slug tests and constant-rate pumping tests were conducted at the field site to provide a baseline of aquifer parameter estimates that are compared the results of ZNR tests. Pressure data measured at monitoring wells during ZNR tests were analyzed utilizing an analytical solution (Streltsova, 1988) that assumes a confined aquifer and estimates hydraulic diffusivity and transmissivity using the time lag and amplitude of the pressure signal. The storativity can be separated out from the hydraulic diffusivity using the transmissivity estimate. The time-lag and amplitude of the pressure signals were estimated using a Fourier transform. The time-lag of the primary period of the pressure increases as a linear function of distance from the pumping well, and it increases as the square root of the period of the ZNR test over a range of periods spanning two orders of magnitudes. The first few harmonics follow similar trends, but the higher frequency harmonics diverge from this trend. Strain and tilt data from various instruments in the vadose and saturated zones are periodic during ZNR tests. The time lags of the strain components increase roughly linearly with distance from the well. Many of the time lags of the strain data from the vadose zone are similar to the time lags observed in the pressure data from a similar distance and pumping period. Theoretical experiments were performed to understand how pressure and strain responds to ZNR periodic pumping. The time-lags of the simulated pressure responses match the field data trends. The results were used to validate the Streltsova (1988) solution for periodic pumping to estimate hydraulic diffusivity. Hydraulic diffusivity was estimated to be 1.8 x 10-2 m2s-1 < Dh < 9.0 x 10-2 m2s-1 using pressure data from all the wells during ZNR tests. Transmissivity was estimated to be 0.8 x 10-4 m2s-1 < T < 4.3 x 10-4 m2s-1. Assuming Storativity = T/Dh gives 1.1 x 10-3 < S < 19 x10-3. Transmissivity is used to estimate the hydraulic conductivity, K, by dividing by the assumed aquifer thickness. Two constant-rate pumping tests were conducted and analyzed using two conceptual models: The Hantush (1961) solution was used to analyze data assuming confined conditions and the Neuman (1974) solution was used to analyze data assuming unconfined conditions. The Hantush (1961) solution estimated transmissivity to be 1.6 x 10-4 m2s-1 < T < 1.8 x 10-4 m2s-1 when using data from all the wells. Storativity was estimated to be 4.4 x 10-3 < S < 8.2 x 10-3. Assuming Dh = T/S gives 0.22 x 10-2 m2s-1 < Dh < 3.6 x 10-2 m2s-1. The Neuman (1974) solution estimated transmissivity to be 0.80 x 10-4 m2s-1 < T < 0.84 x 10-4 m2s-1. Total storativity (S + Sy) was estimated to be 22 x 10-3 < S < 110 x 10-3. Storativity excluding the Sy term was estimated to be 2.2 x 10-3 < S < 2.5 x 10-3. Assuming Dh = T/S gives 0.073 x 10-2 m2s-1 < S < 0.36 x 10-2 m2s-1. Two slug tests were performed on the pumping well, PW-2. The Bouwer and Rice (1976) solution for slug tests was used to analyze the data. This solution works for both confined and unconfined conditions, so both conceptual models were covered through the analysis. Hydraulic conductivity was estimated to be 1.95 x 10-6 ms-1 < K < 2.49 x 10-6 ms-1. Statistical comparison show generally no significant difference in the estimates of Dh, K, or S made using ZNR and conventional pumping tests.. However, the total storage estimated by the Neuman (1974) solution for unconfined settings is larger than that estimate using the Streltsove analysis applied to the ZNR tests. This is likely because the Neuman solution considers delayed yield from storage that the water table, whereas the Streltsova (1988) solution assumes confined conditions. The analysis also indicates that there is a statistically significant difference between parameters estimated with conventional slug tests and those measured with either constant-rate pumping tests or ZNR tests. Hydraulic diffusivity is estimated from the time-lag and the distance from the well. The time-lags of the strain data from the vadose zone are similar to the lags of the pressure data from a similar distance. This indicates that hydraulic diffusivities estimated from the strain data measured in the vadose zone would be similar to the estimates from the pressure data measured in the aquifer. There appear to be sign reversals in some of the strain data that were corrected to estimate the time lag. The dissolved oxygen (CO) concentration was measured during several ZNR tests to evaluate the feasibility of using the procedure to increase contaminant degradation kinetics that are related to DO. The results indicate that DO can be increased during the cycling of ZNR tests in some cases.

Smith-Jones, Austin↗
NASA NTRS2000

Mars Global Surveyor Ka-Band Frequency Data Analysis

The Mars Global Surveyor (MGS) spacecraft, launched on November 7, 1996, carries an experimental space-to-ground telecommunications link at Ka-band (32 GHz) along with the primary X-band (8.4 GHz) downlink. The signals are simultaneously transmitted from a 1.5-in diameter parabolic high gain antenna (HGA) on MGS and received by a beam-waveguide (BWG) R&D 34-meter antenna located in NASA's Goldstone Deep Space Network (DSN) complex near Barstow, California. The projected 5-dB link advantage of Ka-band relative to X-band was confirmed in previous reports using measurements of MGS signal strength data acquired during the first two years of the link experiment from December 1996 to December 1998. Analysis of X-band and Ka-band frequency data and difference frequency (f(sub x)-f(sub ka)/3.8) data will be presented here. On board the spacecraft, a low-power sample of the X-band downlink from the transponder is upconverted to 32 GHz, the Ka-band frequency, amplified to I-W using a Solid State Power Amplifier, and radiated from the dual X/Ka HGA. The X-band signal is amplified by one of two 25 W TWTAs. An upconverter first downconverts the 8.42 GHz X-band signal to 8 GHz and then multiplies using a X4 multiplier producing the 32 GHz Ka-band frequency. The frequency source selection is performed by an RF switch which can be commanded to select a VCO (Voltage Controlled Oscillator) or USO (Ultra-Stable Oscillator) reference. The Ka-band frequency can be either coherent with the X-band downlink reference or a hybrid combination of the USO and VCO derived frequencies. The data in this study were chosen such that the Ka-band signal is purely coherent with the X-band signal, that is the downconverter is driven by the same frequency source as the X-band downlink). The ground station used to acquire the data is DSS-13, a 34-meter BWG antenna which incorporates a series of mirrors inside beam waveguide tubes which guide the energy to a subterranean pedestal room, providing a stable environment for the feed and electronics equipment. A dichroic plate is used to reflect the X-band energy and pass the Ka-band energy to another mirror. The RF energy for each band is then focused onto a feed horn and low-noise amplifier package. After amplification and RF/IF downconversion, the IF signals are sent to the Experimental Tone Tracker (ETT), a digital phase-lock-loop receiver, which simultaneously tracks both X-band and Ka-band carrier signals. Once a signal is detected, the ETT outputs estimates of the SNR in a I -Hz bandwidth (Pc/No), baseband phase and frequency of the signals every I -sec. Between December 1996 and December 1998, the Ka-band and X-band signals from MGS were tracked on a regular basis using the ETT. The Ka-band downlink frequencies described here were referenced to the spacecraft's on-board USO which was also the X-band frequency reference (f(sub ka)= 3.8 f(sub x)). The ETT estimates of baseband phase at I -second sampled time tags were converted to sky frequency estimates. Frequency residuals were then generated for each band by removing a model frequency from each observable frequency at each time tag. The model included Doppler and other effects derived from spacecraft trajectory files obtained from the MGS Navigation Team. A simple troposphere correction was applied to the data. In addition to residuals, the USO frequencies emitted by the spacecraft were estimated. For several passes, the USO frequencies were determined from X-band data and from Ka-band data (referred to X-band by dividing by 3.8) and were found to be in good agreement. In addition, X-band USO frequency estimates from MGS Radio Science data acquired from operational DSN stations were available for comparison and were found to agree within the I Hz level. The remaining sub-Hertz differences were attributed to the different models and software algorithms used by MGS Radio Science and KaBLE-11. A summary of the results of a linear fit of the USO frequency versus time (day of year) is presented in Table I for an initial segment of passes.

Morabito, D.↗
NASA NTRS2012

Metrology of Large Parts

As discussed in the first chapter of this book, there are many different methods to measure a part using optical technology. Chapter 2 discussed the use of machine vision to measure macroscopic features such as length and position, which was extended to the use of interferometry as a linear measurement tool in chapter 3, and laser or other trackers to find the relation of key points on large parts in chapter 4. This chapter looks at measuring large parts to optical tolerances in the sub-micron range using interferometry, ranging, and optical tools discussed in the previous chapters. The purpose of this chapter is not to discuss specific metrology tools (such as interferometers or gauges), but to describe a systems engineering approach to testing large parts. Issues such as material warpage and temperature drifts that may be insignificant when measuring a part to micron levels under a microscope, as will be discussed in later chapters, can prove to be very important when making the same measurement over a larger part. In this chapter, we will define a set of guiding principles for successfully overcoming these challenges and illustrate the application of these principles with real world examples. While these examples are drawn from specific large optical testing applications, they inform the problems associated with testing any large part to optical tolerances. Manufacturing today relies on micrometer level part performance. Fields such as energy and transportation are demanding higher tolerances to provide increased efficiencies and fuel savings. By looking at how the optics industry approaches sub-micrometer metrology, one can gain a better understanding of the metrology challenges for any larger part specified to micrometer tolerances. Testing large parts, whether optical components or precision structures, to optical tolerances is just like testing small parts, only harder. Identical with what one does for small parts, a metrologist tests large parts and optics in particular to quantify their mechanical properties (such as dimensions, mass, etc); their optical prescription or design (i.e. radius of curvature, conic constant, vertex location, size); and their full part shape. And, just as with small parts, a metrologist accomplishes these tests using distance measuring instruments such as tape measures, inside micrometers, coordinate measuring machines, distance measuring interferometers; angle measuring instruments such as theodolites, autocollimators; and surface measuring instruments including interferometers, stylus profilers, interference microscopes, photogrammetric cameras, or other tools. However, while the methodology may be similar, it is more difficult to test a large object for the simple reason that most metrologists do not have the necessary intuition. The skills used to test small parts or optics in a laboratory do not extrapolate to testing large parts in an industrial setting any more than a backyard gardener might successfully operate a farm. But first, what is a large part? A simple definition might be the part's size or diameter. For optics and diffuse surface parts alike, the driving constraint is ability to illuminate the part's surface. For reflective convex mirrors, large is typically anything greater than 1 meter. But, for refractive optics, flats or convex mirrors, large is typically greater than 0.5 meter. While a size definition is simple, it may be less than universal. A more nuanced definition might be that a large part is any component which cannot be easily tested in a standard laboratory environment, on a standard vibration isolated table using standard laboratory infrastructure. A micro-switch or a precision lens might be easily measured to nanometer levels under a microscope in a lab, but a power turbine spline or a larger telescope mirror will not fit under that microscope and may not even fit on the table.

Stahl, H. Philip↗