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NASA NTRS2008

Optical Measurement of Mass Flow of a Two-Phase Fluid

An optoelectronic system utilizes wavelength-dependent scattering of light for measuring the density and mass flow of a two-phase fluid in a pipe. The apparatus was invented for original use in measuring the mass flow of a two-phase cryogenic fluid (e.g., liquid hydrogen containing bubbles of hydrogen gas), but underlying principles of operation can readily be adapted to non-cryogenic two-phase fluids. The system (see figure) includes a laser module, which contains two or more laser diodes, each operating at a different wavelength. The laser module also contains beam splitters that combine the beams at the various wavelengths so as to produce two output beams, each containing all of the wavelengths. One of the multiwavelength output beams is sent, via a multimode fiberoptic cable, to a transmitting optical coupler. The other multiwavelength output beam is sent, via another multimode fiber-optic cable, to a reference detector module, wherein fiber-optic splitters split the light into several multiwavelength beams, each going to a photodiode having a spectral response that is known and that differs from the spectral responses of the other photodiodes. The outputs of these photodiodes are digitized and fed to a processor, which executes an algorithm that utilizes the known spectral responses to convert the photodiode outputs to obtain reference laser-power levels for the various wavelengths. The transmitting optical coupler is mounted in (and sealed to) a hole in the pipe and is oriented at a slant with respect to the axis of the pipe. The transmitting optical coupler contains a collimating lens and a cylindrical lens that form the light emerging from the end of the fiber-optic cable into a fan-shaped beam in a meridional plane of the pipe. Receiving optical couplers similar to the transmitting optical couplers are mounted in the same meridional plane at various longitudinal positions on the opposite side of the pipe, approximately facing the transmitting optical coupler along the same slant. Light collected by each receiving optical coupler is sent, via a multimode fiber-optic cable, to a detector module similar to the reference detector module. The outputs of the photodiodes in each detector module are digitized and processed, similarly to those of the reference detector module, to obtain indications of the amounts of light of each wavelength scattered to the corresponding receiving position. The value for each wavelength at each position is also normalized to the reference laser-power level for that wavelength. From these normalized values, the density and the mass flow rate of the fluid are estimated.

Wiley, John↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
NASA NTRS2010

PLOT3D Export Tool for Tecplot

The PLOT3D export tool for Tecplot solves the problem of modified data being impossible to output for use by another computational science solver. The PLOT3D Exporter add-on enables the use of the most commonly available visualization tools to engineers for output of a standard format. The exportation of PLOT3D data from Tecplot has far reaching effects because it allows for grid and solution manipulation within a graphical user interface (GUI) that is easily customized with macro language-based and user-developed GUIs. The add-on also enables the use of Tecplot as an interpolation tool for solution conversion between different grids of different types. This one add-on enhances the functionality of Tecplot so significantly, it offers the ability to incorporate Tecplot into a general suite of tools for computational science applications as a 3D graphics engine for visualization of all data. Within the PLOT3D Export Add-on are several functions that enhance the operations and effectiveness of the add-on. Unlike Tecplot output functions, the PLOT3D Export Add-on enables the use of the zone selection dialog in Tecplot to choose which zones are to be written by offering three distinct options - output of active, inactive, or all zones (grid blocks). As the user modifies the zones to output with the zone selection dialog, the zones to be written are similarly updated. This enables the use of Tecplot to create multiple configurations of a geometry being analyzed. For example, if an aircraft is loaded with multiple deflections of flaps, by activating and deactivating different zones for a specific flap setting, new specific configurations of that aircraft can be easily generated by only writing out specific zones. Thus, if ten flap settings are loaded into Tecplot, the PLOT3D Export software can output ten different configurations, one for each flap setting.

Alter, Stephen↗
NASA NTRS2011

Source-Coupled, N-Channel, JFET-Based Digital Logic Gate Structure Using Resistive Level Shifters

A circuit topography is used to create usable, digital logic gates using N (negatively doped) channel junction field effect transistors (JFETs), load resistors, level shifting resistors, and supply rails whose values are based on the DC parametric distributions of these JFETs. This method has direct application to the current state-of-the-art in high-temperature (300 to 500 C and higher) silicon carbide (SiC) device production, and defines an adaptation to the logic gate described in U.S. Patent 7,688,117 in that, by removing the level shifter from the output of the gate structure described in the patent (and applying it to the input of the same gate), a source-coupled gate topography is created. This structure allows for the construction AND/OR (sum of products) arrays that use far fewer transistors and resistors than the same array as constructed from the gates described in the aforementioned patent. This plays a central role when large multiplexer constructs are necessary; for example, as in the construction of memory. This innovation moves the resistive level shifter from the output of the basic gate structure to the front as if the input is now configured as what would be the output of the preceding gate, wherein the output is the two level shifting resistors. The output of this innovation can now be realized as the lone follower transistor with its source node as the gate output. Additionally, one may leave intact the resistive level shifter on the new gate topography. A source-coupled to direct-coupled logic translator will be the result.

Krasowski, Michael J.↗
NASA NTRS2011

High-Voltage-Input Level Translator Using Standard CMOS

proposed integrated circuit would translate (1) a pair of input signals having a low differential potential and a possibly high common-mode potential into (2) a pair of output signals having the same low differential potential and a low common-mode potential. As used here, "low" and "high" refer to potentials that are, respectively, below or above the nominal supply potential (3.3 V) at which standard complementary metal oxide/semiconductor (CMOS) integrated circuits are designed to operate. The input common-mode potential could lie between 0 and 10 V; the output common-mode potential would be 2 V. This translation would make it possible to process the pair of signals by use of standard 3.3-V CMOS analog and/or mixed-signal (analog and digital) circuitry on the same integrated-circuit chip. A schematic of the circuit is shown in the figure. Standard 3.3-V CMOS circuitry cannot withstand input potentials greater than about 4 V. However, there are many applications that involve low-differential-potential, high-common-mode-potential input signal pairs and in which standard 3.3-V CMOS circuitry, which is relatively inexpensive, would be the most appropriate circuitry for performing other functions on the integrated-circuit chip that handles the high-potential input signals. Thus, there is a need to combine high-voltage input circuitry with standard low-voltage CMOS circuitry on the same integrated-circuit chip. The proposed circuit would satisfy this need. In the proposed circuit, the input signals would be coupled into both a level-shifting pair and a common-mode-sensing pair of CMOS transistors. The output of the level-shifting pair would be fed as input to a differential pair of transistors. The resulting differential current output would pass through six standoff transistors to be mirrored into an output branch by four heterojunction bipolar transistors. The mirrored differential current would be converted back to potential by a pair of diode-connected transistors, which, by virtue of being identical to the input transistors, would reproduce the input differential potential at the output

Yager, Jeremy A.↗
NASA NTRS2011

Fiber-Optic Magnetic-Field-Strength Measurement System for Lightning Detection

A fiber-optic sensor system is designed to measure magnetic fields associated with a lightning stroke. Field vector magnitudes are detected and processed for multiple locations. Since physical limitations prevent the sensor elements from being located in close proximity to highly conductive materials such as aluminum, the copper wire sensor elements (3) are located inside a 4-cubic-in. (.66-cubic-cm) plastic housing sensor head and connected to a fiber-optic conversion module by shielded cabling, which is limited to the shortest length feasible. The signal path between the conversion module and the avionics unit which processes the signals are fiber optic, providing enhanced immunity from electromagnetic radiation incident in the vicinity of the measurements. The sensors are passive, lightweight, and much smaller than commercial B-dot sensors in the configuration which measures a three-dimensional magnetic field. The system is expandable, and provides a standard-format output signal for downstream processing. Inside of the sensor head, three small search coils, each having a few turns on a circular form, are mounted orthogonally inside the non-metallic housing. The fiber-optic conversion module comprises three interferometers, one for each search coil. Each interferometer has a high bandwidth optical phase modulator that impresses the signal received from its search coil onto its output. The output of each interferometer travels by fiber optic cable to the avionics unit, and the search coil signal is recovered by an optical phase demodulator. The output of each demodulator is fed to an analog-to-digital converter, whose sampling rate is determined by the maximum expected rate of rise and peak signal magnitude. The output of the digital processor is a faithful reproduction of the coil response to the incident magnetic field. This information is provided in a standard output format on a 50-ohm port that can be connected to any number of data collection and processing instruments and/or systems. The measurement of magnetic fields using fiber-optic signal processing is novel because it eliminates limitations of a traditional B-dot system. These limitations include the distance from the sensor to the measurement device, the potential for the signal to degrade or be corrupted by EMI from lightning, and the size and weight of the sensor and associated plate.

Gurecki, Jay↗
NASA NTRS2006

Coherent Detection of High-Rate Optical PPM Signals

A method of coherent detection of high-rate pulse-position modulation (PPM) on a received laser beam has been conceived as a means of reducing the deleterious effects of noise and atmospheric turbulence in free-space optical communication using focal-plane detector array technologies. In comparison with a receiver based on direct detection of the intensity modulation of a PPM signal, a receiver based on the present method of coherent detection performs well at much higher background levels. In principle, the coherent-detection receiver can exhibit quantum-limited performance despite atmospheric turbulence. The key components of such a receiver include standard receiver optics, a laser that serves as a local oscillator, a focal-plane array of photodetectors, and a signal-processing and data-acquisition assembly needed to sample the focal-plane fields and reconstruct the pulsed signal prior to detection. The received PPM-modulated laser beam and the local-oscillator beam are focused onto the photodetector array, where they are mixed in the detection process. The two lasers are of the same or nearly the same frequency. If the two lasers are of different frequencies, then the coherent detection process is characterized as heterodyne and, using traditional heterodyne-detection terminology, the difference between the two laser frequencies is denoted the intermediate frequency (IF). If the two laser beams are of the same frequency and remain aligned in phase, then the coherent detection process is characterized as homodyne (essentially, heterodyne detection at zero IF). As a result of the inherent squaring operation of each photodetector, the output current includes an IF component that contains the signal modulation. The amplitude of the IF component is proportional to the product of the local-oscillator signal amplitude and the PPM signal amplitude. Hence, by using a sufficiently strong local-oscillator signal, one can make the PPM-modulated IF signal strong enough to overcome thermal noise in the receiver circuits: this is what makes it possible to achieve near-quantum-limited detection in the presence of strong background. Following quantum-limited coherent detection, the outputs of the individual photodetectors are automatically aligned in phase by use of one or more adaptive array compensation algorithms [e.g., the least-mean-square (LMS) algorithm]. Then the outputs are combined and the resulting signal is processed to extract the high-rate information, as though the PPM signal were received by a single photodetector. In a continuing series of experiments to test this method (see Fig. 1), the local oscillator has a wavelength of 1,064 nm, and another laser is used as a signal transmitter at a slightly different wavelength to establish an IF of about 6 MHz. There are 16 photodetectors in a 4 4 focal-plane array; the detector outputs are digitized at a sampling rate of 25 MHz, and the signals in digital form are combined by use of the LMS algorithm. Convergence of the adaptive combining algorithm in the presence of simulated atmospheric turbulence for optical PPM signals has already been demonstrated in the laboratory; the combined output is shown in Fig. 2(a), and Fig. 2(b) shows the behavior of the phase of the combining weights as a function of time (or samples). We observe that the phase of the weights has a sawtooth shape due to the continuously changing phase in the down-converted output, which is not exactly at zero frequency. Detailed performance analysis of this coherent free-space optical communication system in the presence of simulated atmospheric turbulence is currently under way.

Vilnrotter, Victor↗
NASA NTRS2006

"One-Stop Shopping" for Ocean Remote-Sensing and Model Data

OurOcean Portal 2.0 (http:// ourocean.jpl.nasa.gov) is a software system designed to enable users to easily gain access to ocean observation data, both remote-sensing and in-situ, configure and run an Ocean Model with observation data assimilated on a remote computer, and visualize both the observation data and the model outputs. At present, the observation data and models focus on the California coastal regions and Prince William Sound in Alaska. This system can be used to perform both real-time and retrospective analyses of remote-sensing data and model outputs. OurOcean Portal 2.0 incorporates state-of-the-art information technologies (IT) such as MySQL database, Java Web Server (Apache/Tomcat), Live Access Server (LAS), interactive graphics with Java Applet at the Client site and MatLab/GMT at the server site, and distributed computing. OurOcean currently serves over 20 real-time or historical ocean data products. The data are served in pre-generated plots or their native data format. For some of the datasets, users can choose different plotting parameters and produce customized graphics. OurOcean also serves 3D Ocean Model outputs generated by ROMS (Regional Ocean Model System) using LAS. The Live Access Server (LAS) software, developed by the Pacific Marine Environmental Laboratory (PMEL) of the National Oceanic and Atmospheric Administration (NOAA), is a configurable Web-server program designed to provide flexible access to geo-referenced scientific data. The model output can be views as plots in horizontal slices, depth profiles or time sequences, or can be downloaded as raw data in different data formats, such as NetCDF, ASCII, Binary, etc. The interactive visualization is provided by graphic software, Ferret, also developed by PMEL. In addition, OurOcean allows users with minimal computing resources to configure and run an Ocean Model with data assimilation on a remote computer. Users may select the forcing input, the data to be assimilated, the simulation period, and the output variables and submit the model to run on a backend parallel computer. When the run is complete, the output will be added to the LAS server for

Li, P. Peggy↗
NASA NTRS2006

Four-Quadrant Analog Multipliers Using G4-FETs

Theoretical analysis and some experiments have shown that the silicon-on-insulator (SOI) 4-gate transistors known as G4-FETs can be used as building blocks of four-quadrant analog voltage multiplier circuits. Whereas a typical prior analog voltage multiplier contains between six and 10 transistors, it is possible to construct a superior voltage multiplier using only four G4-FETs. A G4-FET is a combination of a junction field-effect transistor (JFET) and a metal oxide/semiconductor field-effect transistor (MOSFET). It can be regarded as a single transistor having four gates, which are parts of a structure that affords high functionality by enabling the utilization of independently biased multiple inputs. The structure of a G4-FET of the type of interest here (see Figure 1) is that of a partially-depleted SOI MOSFET with two independent body contacts, one on each side of the channel. The drain current comprises of majority charge carriers flowing from one body contact to the other that is, what would otherwise be the side body contacts of the SOI MOSFET are used here as the end contacts [the drain (D) and the source (S)] of the G4-FET. What would otherwise be the source and drain of the SOI MOSFET serve, in the G4-FET, as two junction-based extra gates (JG1 and JG2), which are used to squeeze the channel via reverse-biased junctions as in a JFET. The G4-FET also includes a polysilicon top gate (G1), which plays the same role as does the gate in an accumulation-mode MOSFET. The substrate emulates a fourth MOS gate (G2). By making proper choices of G4-FET device parameters in conjunction with bias voltages and currents, one can design a circuit in which two input gate voltages (Vin1,Vin2) control the conduction characteristics of G4-FETs such that the output voltage (Vout) closely approximates a value proportional to the product of the input voltages. Figure 2 depicts two such analog multiplier circuits. In each circuit, there is the following: The input and output voltages are differential, The multiplier core consists of four G4- FETs (M1 through M4) biased by a constant current sink (Ibias), and The G4-FETs in two pairs are loaded by two identical resistors (RL), which convert a differential output current to a differential output voltage. The difference between the two circuits stems from their input and bias configurations. In each case, provided that the input voltages remain within their design ranges as determined by considerations of bias, saturation, and cutoff, then the output voltage is nominally given by Vout = kVin1Vin2, where k is a constant gain factor that depends on the design parameters and is different for the two circuits. In experimental versions of these circuits constructed using discrete G4- FETs and resistors, multiplication of voltages in all four quadrants (that is, in all four combinations of input polarities) was demonstrated, and deviations of the output voltages from linear dependence on the input voltages were found to amount to no more than a few percent. It is anticipated that in fully integrated versions of these circuits, the deviations from linearity will be made considerably smaller through better matching of devices.

Mojarradi, Mohammad↗
NASA NTRS2011

High power RF solid state power amplifier system

A high power, high frequency, solid state power amplifier system includes a plurality of input multiple port splitters for receiving a high-frequency input and for dividing the input into a plurality of outputs and a plurality of solid state amplifier units. Each amplifier unit includes a plurality of amplifiers, and each amplifier is individually connected to one of the outputs of multiport splitters and produces a corresponding amplified output. A plurality of multiport combiners combine the amplified outputs of the amplifiers of each of the amplifier units to a combined output. Automatic level control protection circuitry protects the amplifiers and maintains a substantial constant amplifier power output.

Sims, III, William Herbert↗
NASA NTRS2004

Real-Time Adaptive Color Segmentation by Neural Networks

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

Duong, Tuan A.↗
NASA NTRS2003

164-GHz MMIC HEMT Frequency Doubler

A monolithic microwave integrated circuit (MMIC) that includes a high-electron-mobility transistor (HEMT) has been developed as a prototype of improved frequency doublers for generating signals at frequencies greater than 100 GHz. Signal sources that operate in this frequency range are needed for a variety of applications, notably including general radiometry and, more specifically, radiometric remote sensing of the atmosphere. Heretofore, it has been common practice to use passive (diode-based) frequency multipliers to obtain frequencies greater than 100 GHz. Unfortunately, diode-based frequency multipliers are plagued by high DC power consumption and low conversion efficiency. Moreover, multiplier diodes are not easily integrated with such other multiplier-circuit components as amplifiers and oscillators. The goals of developing the present MMIC HEMT frequency doubler were (1) to utilize the HEMT as an amplifier to increase conversion efficiency (more precisely, to reduce conversion loss), thereby increasing the output power for a given DC power consumption or, equivalently, reducing the DC power consumption for a given output power; and (2) to provide for the integration of amplifier and oscillator components on the same chip. The MMIC frequency doubler (see Figure 1) contains an AlInAs/GaInAs/InP HEMT biased at pinch-off to make it function as a class-B amplifier (meaning that it conducts in half-cycle pulses). Grounded coplanar waveguides (GCPWs) are used as impedance-matching transmission lines. Air bridges are placed at discontinuities to suppress undesired slot electromagnetic modes. Another combination of GCPWs also serves both as a low-pass filter to suppress undesired oscillations at frequencies below 60 GHz and as a DC blocker. Large decoupling capacitors and epitaxial resistors are added in the drain and gate lines to suppress bias oscillations. At the output terminal, the fundamental frequency is suppressed by a quarter-wave open stub, which presents a short circuit at the fundamental frequency and an open circuit at the second harmonic. At an input power of 7 mW, the output power and conversion loss at an output frequency of 164 GHz were found to be 5 dBm (approximately equal to 3.2 mW) and 2 dB, respectively, with a 3-dB output-power bandwidth of 14 GHz. This is the best performance reported to date for an MMIC HEMT frequency doubler above 100 GHz.

Samoska, Lorene↗
NASA NTRS2011

Flexible, reconfigurable, power efficient transmitter and method

A flexible, reconfigurable, power efficient transmitter device and method is provided. In one embodiment, the method includes receiving outbound data and determining a mode of operation. When operating in a first mode the method may include modulation mapping the outbound data according a modulation scheme to provide first modulation mapped digital data, converting the first modulation mapped digital data to an analog signal that comprises an intermediate frequency (IF) analog signal, upconverting the IF analog signal to produce a first modulated radio frequency (RF) signal based on a local oscillator signal, amplifying the first RF modulated signal to produce a first RF output signal, and outputting the first RF output signal via an isolator. In a second mode of operation method may include modulation mapping the outbound data according a modulation scheme to provide second modulation mapped digital data, converting the second modulation mapped digital data to a first digital baseband signal, conditioning the first digital baseband signal to provide a first analog baseband signal, modulating one or more carriers with the first analog baseband signal to produce a second modulated RF signal based on a local oscillator signal, amplifying the second RF modulated signal to produce a second RF output signal, and outputting the second RF output signal via the isolator. The digital baseband signal may comprise an in-phase (I) digital baseband signal and a quadrature (Q) baseband signal.

Bishop, James W.↗
NASA NTRS2011

High-Efficiency Ka-Band Waveguide Two-Way Asymmetric Power Combiner

NASA is planning a number of Space Exploration, Earth Observation and Space Science missions where Ka-band solid-state power amplifiers (SSPAs) could have a role. Monolithic microwave integrated circuit (MMIC) based SSPAs with output powers on the order of 10 W at Ka-band frequencies would be adequate to satisfy the data transmission rate requirements at the distances involved. MMICs are a type of integrated circuit fabricated on a GaAs wafer, which operates at micro wave frequencies and performs the function of signal amplification. The highest power Ka-band (31.8 to 32.3 GHz) SSPA to have flown in space had an output power of 2.6 W with an overall efficiency of 14.3 percent. This SSPA was built around discrete GaAs pHEMT (high electron mobility transistor) devices and flew aboard the Deep Space One spacecraft. State-of-the-art GaAs pHEMT-based MMIC power amplifiers (PAs) can deliver RF power at Ka-band frequencies anywhere from 3 W with a power added efficiency (PAE) of 32 percent to 6 W with a PAE of 26 percent. However, to achieve power levels higher than 6 W, the output of several MMIC PAs would need to be combined using a high-efficiency power combiner. Conventional binary waveguide power combiners, based on short-slot and magic-T circuits, require MMIC PAs with identical amplitude and phase characteristics for high combining efficiency. However, due to manufacturing process variations, the output powers of the MMIC PAs tend to be unequal, and hence the need to develop unequal power combiners. A two-way asymmetric magic-T based power combiner for MMIC power amplifiers, which can take in unequal inputs, has been successfully designed, fabricated, and characterized over NASA s Deep Space Network (DSN) frequency range of 31.8 to 32.3 GHz. The figure is a transparent view of the a sym - metric combiner that shows the 4-port configuration and the internal structure. The rod, post, and iris are positioned by design to achieve the desired asymmetric power ratio, phase equality, and port isolation. Although the combiner was designed for an input power ratio of 2:1, it can be custom-designed for any arbitrary power ratio and frequency range. The manufactured prototype combiner was precision machined from aluminum and is less than 2 in.3 (32.8 cm3). Previously investigated rectangular waveguide unequal power combiners were based on shunt/series coupling slots, E-plane septums, or H-plane T-junctions. All the prior art unequal power combiners operated at or below X-band (10 GHz) frequencies and were primarily used in the feed network of antenna arrays. The only reported asymmetric magic-T was developed as a 2:1 power divider for operation at a much lower frequency, around 500 MHz. The measured power ratio when tested as a power divider was very close to 2 and the phase balance was within 2.6, resulting in near ideal performance. When tested as a combiner using two MMIC SSPAs with a 2:1 power output ratio, an efficiency greater than 90 percent was demonstrated over the 500 MHz DSN frequency range. The return loss at the combiner output port (1) was greater than 18 dB and the input port (2 and 3) isolation was greater than 22 dB. The results show the asymmetric combiner to be a good candidate for high-efficiency power combining of two or more SSPAs needed to achieve the 6 to 10 W required by space communications systems of future NASA missions.

Wintucky, E. G.↗
NASA NTRS2011

Acute Radiation Risk and BRYNTRN Organ Dose Projection Graphical User Interface

The integration of human space applications risk projection models of organ dose and acute radiation risk has been a key problem. NASA has developed an organ dose projection model using the BRYNTRN with SUM DOSE computer codes, and a probabilistic model of Acute Radiation Risk (ARR). The codes BRYNTRN and SUM DOSE are a Baryon transport code and an output data processing code, respectively. The risk projection models of organ doses and ARR take the output from BRYNTRN as an input to their calculations. With a graphical user interface (GUI) to handle input and output for BRYNTRN, the response models can be connected easily and correctly to BRYNTRN. A GUI for the ARR and BRYNTRN Organ Dose (ARRBOD) projection code provides seamless integration of input and output manipulations, which are required for operations of the ARRBOD modules. The ARRBOD GUI is intended for mission planners, radiation shield designers, space operations in the mission operations directorate (MOD), and space biophysics researchers. BRYNTRN code operation requires extensive input preparation. Only a graphical user interface (GUI) can handle input and output for BRYNTRN to the response models easily and correctly. The purpose of the GUI development for ARRBOD is to provide seamless integration of input and output manipulations for the operations of projection modules (BRYNTRN, SLMDOSE, and the ARR probabilistic response model) in assessing the acute risk and the organ doses of significant Solar Particle Events (SPEs). The assessment of astronauts radiation risk from SPE is in support of mission design and operational planning to manage radiation risks in future space missions. The ARRBOD GUI can identify the proper shielding solutions using the gender-specific organ dose assessments in order to avoid ARR symptoms, and to stay within the current NASA short-term dose limits. The quantified evaluation of ARR severities based on any given shielding configuration and a specified EVA or other mission scenario can be made to guide alternative solutions for attaining determined objectives set by mission planners. The ARRBOD GUI estimates the whole-body effective dose, organ doses, and acute radiation sickness symptoms for astronauts, by which operational strategies and capabilities can be made for the protection of astronauts from SPEs in the planning of future lunar surface scenarios, exploration of near-Earth objects, and missions to Mars.

Cucinotta, Francis A.↗
NASA NTRS2014

Interval Predictor Models with a Formal Characterization of Uncertainty and Reliability

This paper develops techniques for constructing empirical predictor models based on observations. By contrast to standard models, which yield a single predicted output at each value of the model's inputs, Interval Predictors Models (IPM) yield an interval into which the unobserved output is predicted to fall. The IPMs proposed prescribe the output as an interval valued function of the model's inputs, render a formal description of both the uncertainty in the model's parameters and of the spread in the predicted output. Uncertainty is prescribed as a hyper-rectangular set in the space of model's parameters. The propagation of this set through the empirical model yields a range of outputs of minimal spread containing all (or, depending on the formulation, most) of the observations. Optimization-based strategies for calculating IPMs and eliminating the effects of outliers are proposed. Outliers are identified by evaluating the extent by which they degrade the tightness of the prediction. This evaluation can be carried out while the IPM is calculated. When the data satisfies mild stochastic assumptions, and the optimization program used for calculating the IPM is convex (or, when its solution coincides with the solution to an auxiliary convex program), the model's reliability (that is, the probability that a future observation would be within the predicted range of outputs) can be bounded rigorously by a non-asymptotic formula.

Crespo, Luis G.↗
NASA NTRS2015

Multistage Force Amplification of Piezoelectric Stacks

Embodiments of the disclosure include an apparatus and methods for using a piezoelectric device, that includes an outer flextensional casing, a first cell and a last cell serially coupled to each other and coupled to the outer flextensional casing such that each cell having a flextensional cell structure and each cell receives an input force and provides an output force that is amplified based on the input force. The apparatus further includes a piezoelectric stack coupled to each cell such that the piezoelectric stack of each cell provides piezoelectric energy based on the output force for each cell. Further, the last cell receives an input force that is the output force from the first cell and the last cell provides an output apparatus force In addition, the piezoelectric energy harvested is based on the output apparatus force. Moreover, the apparatus provides displacement based on the output apparatus force.

Xu, Tian-Bing↗
NASA NTRSDate not supplied

Sensitivity Analysis of the Human Research Program’s Impact 1.0 Model

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Leave One Out (LOO) are methods of conducting sensitivity analysis on non-linear simulation models like the IMPACT Model. The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The “partial” part is due to the adjustments made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. LOO removes a medical condition from test suite and calculates the change in the outcome. This is used to identify the influence of the condition input in the model The inputs to the sensitivity procedures include the number of occurrences of each of the one hundred plus IMPACT medical conditions generated over the simulations, and the IMPACT outputs from the MEDPRAT mathematical model. The outputs total task time lost (TTL), number of return to definitive care (RTDC), and number of loss of crew lives (LOCL). The IMPACT team will report the results of using PRCC and LOO on IMPACT 1.0. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty, and input values could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMPACT 1.0.

Sensitivity Anaylsis↗