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At least 1,189 records · Page 66

A Novel Active Optimization Approach for Rapid and Efficient Design Space Exploration Using Ensemble Machine Learning

In this work, a novel design optimization technique based on active learning, which involves dynamic exploration and exploitation of the design space of interest using an ensemble of machine learning algorithms, is presented. In this approach, a hybrid methodology incorporating an explorative weak learner (regularized basis function model) that fits high-level information about the response surface and an exploitative strong learner (based on committee machine) that fits finer details around promising regions identified by the weak learner is employed. For each design iteration, an aristocratic approach is used to select a set of nominees, where points that meet a threshold merit value as predicted by the weak learner are selected for evaluation. In addition to these points, the global optimum as predicted by the strong learner is also evaluated to enable rapid convergence to the actual global optimum once the most promising region has been identified by the optimizer. Additionally, this methodology is first tested by applying it to the optimization of a two-dimensional multi-modal surface and, subsequently, to a complex internal combustion (IC) engine combustion optimization case with nine control parameters related to fuel injection, initial thermodynamic conditions, and in-cylinder flow. It is found that the new approach significantly lowers the number of function evaluations that are needed to reach the optimum design configuration (by up to 80%) when compared to conventional optimization techniques, such as particle swarm and genetic algorithm-based optimization techniques.

24 POWER TRANSMISSION AND DISTRIBUTION↗

the role of shock waves in modulation of galactic cosmic rays

The understanding of modulation of the galactic cosmic rays has considerably progressed by the exploration by space probes of major heliospheric structures, such as the Corotating Interaction Regions, the neutral sheet, and the compression regions of intense heliospheric magnetic fields. Also relevant in this context were the detections in the outer heliosphere of long lasting Forbush type decreases of cosmic ray intensity. The results of recent theoretical studies on the changes in intensity and energy, at different location from the Sun, induced by the passage of shocks across the heliosphere are presented. In this version of the research, the simplest cases of modulation of uGV and 2GV particles by single or several shocks during periods of positive and negative solar field polarity are reviewed. The results of the theoretical aspects of the search is reported. The comparison of the theoretical predictions with space probe data allows conclusions to be drawn on the role of shocks on the modulation on both the 11 and 22 year galactic cosmic ray cycles in the outer heliosphere and on the plausibility of the models and parameters used.

Gall, R.↗

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

Statistical emulation↗

TPSAS-NF1676L-13013-DND

Description, capabilities and utilization of the NASA Langley Aerothermodynamics Laboratory (LAL) are presented. The LAL consists of four hypersonic, blow-down-to-vacuum wind tunnels that collectively provide a range of Mach number from 6 to 10 (18 simulation), unit Reynolds number from 0.05 to 8 million per foot and, most importantly for blunt configurations, normal shock density ratio from 4 to 12. These wide ranges of hypersonic simulation parameters are due, in part, to the use of two different test gases (air and tetrafluoromethane, CF4), thereby making the facilities unique. The complex represents half of the conventional (as opposed to impulse) -type hypersonic wind tunnels operational in this country. LAL facilities are used to assess and optimize the hypersonic aerodynamic performance and aeroheating characteristics of aerospace vehicle concepts and to provide benchmark aerodynamic/aeroheating data for generating the flight aerodynamic databook and final design of the thermal protection system (TPS). Modifications and enhancements of LAL hardware components and instrumentation have been pursued to increase capability, reliability, and productivity in support of programmatic goals. The facilities are utilized to generate essentially all of the experimental hypersonic aerodynamic and aeroheating information for high-priority, fast-paced Agency programs and were a major contributor to the Shuttle Columbia Accident Investigation, space shuttle Return-to-Flight program and Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) project. The LAL has also contributed to the development of the Orion Crew Exploration Vehicle, Ares launch system, Mars Science Laboratory, Genesis Sample Return Capsule and supported DOD programs including HIFiRE, X-37, Falcon HTV-2 and X-51A.

John R Micol↗

Initial Sensorimotor and Cardiovascular Data Acquired from Soyuz Landings: Establishing a Functional Performance Recovery Time Constant

INTRODUCTION Testing of crew responses following long-duration flights has not been previously possible until a minimum of more than 24 hours after landing. As a result, it has not been possible to determine the trend of the early recovery process, nor has it been possible to accurately assess the full impact of the decrements associated with long-duration flight. To overcome these limitations, both the Russian and U.S. programs have implemented joint testing at the Soyuz landing site. This International Space Station research effort has been identified as the functional Field Test, and represents data collect on NASA, Russian, European Space Agency, and Japanese Aerospace Exploration Agency crews. RESEARCH The primary goal of this research is to determine functional abilities associated with long-duration space flight crews beginning as soon after landing as possible on the day of landing (typically within 1 to 1.5 hours). This goal has both sensorimotor and cardiovascular elements. To date, a total of 15 subjects have participated in a 'pilot' version of the full 'field test'. The full version of the 'field test' will assess functional sensorimotor measurements included hand/eye coordination, standing from a seated position (sit-to-stand), walking normally without falling, measurement of dynamic visual acuity, discriminating different forces generated with the hands (both strength and ability to judge just noticeable differences of force), standing from a prone position, coordinated walking involving tandem heel-to-toe placement (tested with eyes both closed and open), walking normally while avoiding obstacles of differing heights, and determining postural ataxia while standing (measurement of quiet stance). Sensorimotor performance has been obtained using video records, and data from body worn inertial sensors. The cardiovascular portion of the investigation has measured blood pressure and heart rate during a timed stand test in conjunction with postural ataxia testing (quiet stance sway) as well as cardiovascular responses during sensorimotor testing on all of the above measures. We have also collected motion sickness data associated with each of the postflight tests. When possible rudimentary cerebellar assessment was undertaken. In addition to the immediate post-landing collection of data, postflight data has been acquired twice more within 24 hours after landing and measurements continue until sensorimotor and cardiovascular responses have returned to preflight normative values (approximately 60 days postflight). SUMMARY The level of functional deficit observed in the crew tested to date is more severe than expected, clearly triggered by the acquisition of gravity loads immediately after landing when the demands for crew intervention in response to emergency operations will be greatest. Measureable performance parameters such as ability to perform a seat egress, recover from a fall or the ability to see clearly when walking, and related physiologic data (orthostatic responses) are required to provide an evidence base for characterizing programmatic risks and the degree of variability among crewmembers for exploration missions where the crew will be unassisted after landing. Overall, these early functional and related physiologic measurements will allow the estimation of nonlinear sensorimotor and cardiovascular recovery trends that have not been previously captured.

Reschke, M. F.↗

Detailed analysis of excited-state systematics in a lattice QCD calculation of 𝑔 𝐴

Excited state contamination remains one of the most challenging sources of systematic uncertainty to control in lattice QCD calculations of nucleon matrix elements and form factors: early time separations are contaminated by excited states and late times suffer from an exponentially bad signal-to-noise problem. High-statistics calculations at large time separations ≳ 1 fm are commonly used to combat these issues. In this work, focusing on g A , we explore the alternative strategy of utilizing a large number of relatively low-statistics calculations at short to medium time separations (0.2–1 fm), combined with a multistate analysis. On an ensemble with a pion mass of approximately 310 MeV and a lattice spacing of approximately 0.09 fm, we find this provides a more robust and economical method of quantifying and controlling the excited state systematic uncertainty. A quantitative separation of various types of excited states enables the identification of the transition matrix elements as the dominant contamination. The excited state contamination of the Feynman-Hellmann correlation function is found to reduce to the 1% level at approximately 1 fm while, for the more standard three-point functions, this does not occur until after 2 fm. Critical to our findings is the use of a global minimization, rather than fixing the spectrum from the two-point functions and using them as input to the three-point analysis. We find that the ground state parameters determined in such a global analysis are stable against variations in the excited state model, the number of excited states, and the truncation of early-time or late-time numerical data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High power diode laser Master Oscillator-Power Amplifier (MOPA)

High power multiple quantum well AlGaAs diode laser master oscillator - power amplifier (MOPA) systems were examined both experimentally and theoretically. For two pass operation, it was found that powers in excess of 0.3 W per 100 micrometers of facet length were achievable while maintaining diffraction-limited beam quality. Internal electrical-to-optical conversion efficiencies as high as 25 percent were observed at an internal amplifier gain of 9 dB. Theoretical modeling of multiple quantum well amplifiers was done using appropriate rate equations and a heuristic model of the carrier density dependent gain. The model gave a qualitative agreement with the experimental results. In addition, the model allowed exploration of a wider design space for the amplifiers. The model predicted that internal electrical-to-optical conversion efficiencies in excess of 50 percent should be achievable with careful system design. The model predicted that no global optimum design exists, but gain, efficiency, and optical confinement (coupling efficiency) can be mutually adjusted to meet a specific system requirement. A three quantum well, low optical confinement amplifier was fabricated using molecular beam epitaxial growth. Coherent beam combining of two high power amplifiers injected from a common master oscillator was also examined. Coherent beam combining with an efficiency of 93 percent resulted in a single beam having diffraction-limited characteristics. This beam combining efficiency is a world record result for such a system. Interferometric observations of the output of the amplifier indicated that spatial mode matching was a significant factor in the less than perfect beam combining. Finally, the system issues of arrays of amplifiers in a coherent beam combining system were investigated. Based upon experimentally observed parameters coherent beam combining could result in a megawatt-scale coherent beam with a 10 percent electrical-to-optical conversion efficiency.

Andrews, John R.↗

BioSentinel/Mars: Interplanetary Space Radiation Biosensor Experiment in Martian Transit on Mars 2020

Despite significant progress understanding biological radiation effects via terrestrial studies, no terrestrial source duplicates space’s unique radiation environment. Furthermore, no biological experiments have been conducted beyond low Earth orbit since Apollo. Understanding space’s fundamental biological effects requires overcoming these limitations. The BioSentinel 4U payload, under development for flight aboard Exploration Mission-1, measures biological responses to deep space radiation. Traveling to more than 1AU from Earth, BioSentinel/EM-1 will record DNA double-strand breaks (DSBs) repaired using a pathway common to humans and BioSentinel’s bioengineered yeast model organism, responding to as few as one biologically repaired DSB. The BioSentinel/Mars 4U instrument (6-8kg; 5-8W; 0.2-1MB/week) would include eighteen 16-well biosensor fluidic cards, activated biweekly during Mars 2020’s cruise phase, to provide a dose-dependent rate of DSB/repair. The instrument, which includes solid-state sensors for total ionizing dose and linear-energy-transfer spectra, addresses MEPAG SKG-B3 by simultaneously measuring both spectra and biological effects of space radiation. Biological measurements are rendered reliable by independent replicate experiments. The spatio-temporal uniformity of interplanetary galactic cosmic radiation makes BioSentinel/EM1 and BioSentinel/Mars approximate replicates, except for any major differences in solar particle events. Results will be compared to Earth and ISS controls to characterize the radiation/reduced-gravity parameter space by its biological impact.

BioSentinel↗

Surface Properties of Double-Fin Generated Shock-Wave/Boundary-Layer Interactions

Shock-Wave/Boundary-Layer Interaction (SBLI) is ubiquitous in high-speed air vehicles. SBLI surface flowfield properties of crossing shocks induced by symmetric Double-Fins (DFs) at fin angles of 8° and 10° at Mach 2 are experimentally investigated; a 10° Single-Fin (SF) is also explored as a comparison. Surface visualization is used to capture distinct flowfield structures such as separation and upstream influence. Steady and unsteady Pressure-Sensitive Paints (PSPs) are used to obtain global surface pressure fields. Characteristics of DF-SBLI surface topology are discussed by comparing the corresponding SF-SBLI. Here, the effect of fin angle on DF-SBLI is characterized, and unsteady dynamics of the pressure field are examined. Spectral Proper Orthogonal Decomposition (SPOD) is performed on unsteady PSP, and traveling surface pressure waves and their frequency-dependent behavior are discussed. Dispersion relation of surface pressure waves is revealed by performing two-dimensional space–time Fourier transform on unsteady PSP, and the results are compared with the phase velocity distributions obtained from SPOD. Accompanying group velocity behavior is examined for distinct SBLI regions wherein wave propagation is found dependent on its frequency. Steady surface pressures along the centerline are compared with previous experimental data. Fin-tip spacing is found to be an essential parameter for scaling of upstream influence length.

33 ADVANCED PROPULSION SYSTEMS↗

Intravenous Fluid Mixing in Normal Gravity, Partial Gravity, and Microgravity: Down-Selection of Mixing Methods

The missions envisioned under the Vision for Space Exploration will require development of new methods to handle crew medical care. Medications and intravenous (IV) fluids have been identified as one area needing development. Storing certain medications and solutions as powders or concentrates can both increase the shelf life and reduce the overall mass and volume of medical supplies. The powders or concentrates would then be mixed in an IV bag with Sterile Water for Injection produced in situ from the potable water supply. Fluid handling in microgravity is different than terrestrial settings, and requires special consideration in the design of equipment. This document describes the analyses and down-select activities used to identify the IV mixing method to be developed that is suitable for ISS and exploration missions. The chosen method is compatible with both normal gravity and microgravity, maintains sterility of the solution, and has low mass and power requirements. The method will undergo further development, including reduced gravity aircraft experiments and computations, in order to fully develop the mixing method and associated operational parameters.

Niederhaus, Charles E.↗

Synergy of semiempirical models and machine learning in computational chemistry

Catalyzed by enormous success in the industrial sector, many research programs have been exploring data-driven, machine learning approaches. Performance can be poor when the model is extrapolated to new regions of chemical space, e.g., new bonding types, new many-body interactions. Another important limitation is the spatial locality assumption in model architecture, and this limitation cannot be overcome with larger or more diverse datasets. The outlined challenges are primarily associated with the lack of electronic structure information in surrogate models such as interatomic potentials. Given the fast development of machine learning and computational chemistry methods, we expect some limitations of surrogate models to be addressed in the near future; nevertheless spatial locality assumption will likely remain a limiting factor for their transferability. Here, we suggest focusing on an equally important effort—design of physics-informed models that leverage the domain knowledge and employ machine learning only as a corrective tool. In the context of material science, we will focus on semi-empirical quantum mechanics, using machine learning to predict corrections to the reduced-order Hamiltonian model parameters. The resulting models are broadly applicable, retain the speed of semiempirical chemistry, and frequently achieve accuracy on par with much more expensive ab initio calculations. These early results indicate that future work, in which machine learning and quantum chemistry methods are developed jointly, may provide the best of all worlds for chemistry applications that demand both high accuracy and high numerical efficiency.

36 MATERIALS SCIENCE↗

Making tomorrow's mistakes today: Evolutionary prototyping for risk reduction and shorter development time

In the early days of JPL's solar system exploration, each spacecraft mission required its own dedicated data system with all software applications written in the mainframe's native assembly language. Although these early telemetry processing systems were a triumph of engineering in their day, since that time the computer industry has advanced to the point where it is now advantageous to replace these systems with more modern technology. The Space Flight Operations Center (SFOC) Prototype group was established in 1985 as a workstation and software laboratory. The charter of the lab was to determine if it was possible to construct a multimission telemetry processing system using commercial, off-the-shelf computers that communicated via networks. The staff of the lab mirrored that of a typical skunk works operation -- a small, multi-disciplinary team with a great deal of autonomy that could get complex tasks done quickly. In an effort to determine which approaches would be useful, the prototype group experimented with all types of operating systems, inter-process communication mechanisms, network protocols, packet size parameters. Out of that pioneering work came the confidence that a multi-mission telemetry processing system could be built using high-level languages running in a heterogeneous, networked workstation environment. Experience revealed that the operating systems on all nodes should be similar (i.e., all VMS or all PC-DOS or all UNIX), and that a unique Data Transport Subsystem tool needed to be built to address the incompatibilities of network standards, byte ordering, and socket buffering. The advantages of building a telemetry processing system based on emerging industry standards were numerous: by employing these standards, we would no longer be locked into a single vendor. When new technology came to market which offered ten times the performance at one eighth the cost, it would be possible to attach the new machine to the network, re-compile the application code, and run. In addition, we would no longer be plagued with lack of manufacturer support when we encountered obscure bugs. And maybe, hopefully, the eternal elusive goal of software portability across different vendors' platforms would finally be available. Some highlights of our prototyping efforts are described.

Friedman, Gary↗

Assessment of SOI AND Gate, Type CHT-7408, for Operation in Extreme Temperature Environments

Electronic parts based on silicon-on-insulator (SOI) technology are finding widespread applications due to their ability to operate in harsh environments and the benefits they offer as compared to their silicon counterparts. Due to their construction, they are tailored for high temperature operation and show good tolerance to radiation events. In addition, their inherent design lessens the formation of parasitic junctions, thereby reducing leakage currents, decreasing power consumption, and enhancing speed. These devices are typically rated in temperature capability from -55 C to about +225 C, and their characteristics over this temperature range are documented in data sheets. Since electronics in some of NASA space exploration missions are required to operate under extreme temperature conditions, both cold and hot, their characteristic behavior within the full temperature spectrum must be determined to establish suitability for use in space applications. The effects of extreme temperature exposure on the performance of a new commercial-off-the-shelf (COTS) SOI AND gate device were evaluated in this work. The high temperature, quad 2-inputs AND gate device, which was recently introduced by CISSOID, is fabricated using a CMOS SOI process. Some of the specifications of the CHT-7408 chip are listed in a table. By supplying a constant DC voltage to one gate input and a 10 kHz square wave into the other associated gate input, the chip was evaluated in terms of output response, output rise (t(sub r)) and fall times (tf), and propagation delays (using a 50% level between input and output during low to high (tPLH) and high to low (tPHL) transitions). The supply current of the gate circuit was also obtained. These parameters were recorded at various test temperatures between -195 C and +250 C using a Sun Systems environmental chamber programmed at a temperature rate of change of 10 C/min. In addition, the effects of thermal cycling on this chip were determined by exposing it to a total of 12 cycles between -195 C and +250 C. Following the cycling activity, measurements were performed again at the test temperatures of -195 C, +21 C, and +250 C.

Patterson, Richard↗

Metallic Junction Thermoelectric Device Simulations

Thermoelectric junctions made of semiconductors have existed in radioisotope thermoelectric generators (RTG) for deep space missions, but are currently being adapted for terrestrial energy harvesting. Unfortunately, these devices are inefficient, operating at only 7% efficiency. This low efficiency has driven efforts to make high-figure-of-merit thermoelectric devices, which require a high electrical conductivity but a low thermal conductivity, a combination that is difficult to achieve. Lowered thermal conductivity has increased efficiency, but at the cost of power output. An alternative setup is to use metallic junctions rather than semiconductors as thermoelectric devices. Metals have orders of magnitude more electrons and electronic conductivities higher than semiconductors, but thermal conductivity is higher as well. To evaluate the viability of metallic junction thermoelectrics, a two dimensional heat transfer MATLAB simulation was constructed to calculate efficiency and power output. High Seebeck coefficient alloys, Chromel (90%Ni-10%Cr) and Constantan (55%Cu-45%Ni), produced efficiencies of around 20-30%. Parameters such as the number of layers of junctions, lateral junction density, and junction sizes for both series- and parallel-connected junctions were explored.

Duzik, Adam J.↗

Assessments of Physiology And Cognition in Hybrid-reality Environments (APACHE) – Physical Workload Approximation

The Human Physiology, Performance, Protection & Operations Laboratory (H-3PO) at NASA Johnson Space Center (JSC) is developing a hybrid reality exploration surface analog, “Assessments of Physiology And Cognition in Hybrid-reality Environments” (APACHE). The goal of APACHE is to create a planetary extravehicular activity (EVA) simulation environment that provides a representative physical and cognitive workload approximation using a combination of virtual reality (VR), physical reality, and hybrid reality (HR) techniques. To develop and characterize the physical workload approximation within the APACHE environment, a two-part approach was implemented. In part 1, baseline physical workload during ambulation within APACHE was evaluated and compared with that in other planetary EVA analog environments and with existing data sets from Apollo planetary EVAs and reduced gravity testing of prototype planetary spacesuits. For this evaluation, 10 subjects were asked to ambulate in three surface analog environments: a passive treadmill in APACHE, natural terrain in an outdoor field environment, and a standard motorized treadmill. Subjects’ heart rate and metabolic rate (VO2/VCO2)were measured and compared among the different test conditions and existing data sets. Gait parameters were also collected to compare with suited mechanics and to understand the role of gait kinematics in physical workload. In part 2, the aim is to evaluate the addition of a custom weighted body suit to the aforementioned surface analog environments and the ability to titrate the suit configuration to provide the best possible physical workload approximation for simulation of lunar and Martian EVAs.

Alexander J Baughman↗

Probabilistic Calibration of Expensive Models using Efficiently Trained Surrogates

Calibration of computational models in the presence of uncertainty is often cast as a Bayesian inference problem and solved via sampling methods, e.g., Markov chain Monte Carlo. When the computational model is expensive, this task becomes intractable due to the large number of samples required to accurately estimate the posterior distribution of the calibration parameters. A popular solution to this problem is to use machine learning to develop a faster-to-evaluate, lower-fidelity substitute for the original model to serve as a surrogate while solving the inference problem. Although considered an offline cost, generating training data to construct this surrogate model can still be an expensive task in practice. An active learning algorithm is presented that focuses training on improving surrogate accuracy specifically in and around the bulk of the posterior distribution, as this is where the model is exercised during calibration. Candidate samples are drawn from families of distributions related to an approximation of the posterior. The sample maximizing predictive variance is then selected for evaluation by the original computational model, yielding a label for the training point. Iterating this approach increases efficiency relative to space filling designs (e.g., Latin hypercube sampling) by avoiding low probability points. Practical considerations are discussed, including the benefits of using a sequential Monte Carlo sampling approach, convergence heuristics, and the importance of both exploration and exploitation given that the true posterior is unknown a priori.

uncertainty quantification↗

Fast and Flexible Inference Framework for Continuum Reverberation Mapping Using Simulation-based Inference with Deep Learning

Continuum reverberation mapping (CRM) of active galactic nuclei (AGN) monitors multiwavelength variability signatures to constrain accretion disk structure and supermassive black hole (SMBH) properties. The upcoming Vera Rubin Observatory’s Legacy Survey of Space and Time will survey tens of millions of AGN over the next decade, with thousands of AGN monitored with almost daily cadence in the deep drilling fields. However, existing CRM methodologies often require long computation time and are not designed to handle such large amounts of data. In this paper, we present a fast and flexible inference framework for CRM using simulation-based inference (SBI) with deep learning to estimate SMBH properties from AGN light curves. We use a long short-term memory summary network to reduce the high dimensionality of the light curve data and then use a neural density estimator to estimate the posterior of SMBH parameters. Using simulated light curves, we find SBI can produce more accurate SMBH parameter estimation with 10 3 –10 5 times speed up in inference efficiency compared to traditional methods. The SBI framework is particularly suitable for wide-field CRM surveys as the light curves will have identical observing patterns, which can be incorporated into the SBI simulation. We explore the performance of our SBI model on light curves with irregular-sampled, realistic observing cadence and alternative variability characteristics to demonstrate the flexibility and limitation of the SBI framework.

79 ASTRONOMY AND ASTROPHYSICS↗

The Extreme Ultraviolet Explorer and the local interstellar medium

The EUV Explorer (EUVE) mission is described, with emphasis on the overall capabilities of the instrumentation and the relevance of the mission to determining parameters of the local interstellar medium. The primary purpose of the mission is to search the celestial sphere for astronomical sources of EUV radiation (100-1000 A). The search will be accomplished with the use of three EUV telescopes, sensitive to different segments of the EUV band. A fourth telescope will perform a high-sensitivity search of a limited sample of the sky in the shortest-wavelength bands. The all-sky survey will be carried out in the first six months of the mission. The second six months of the mission, conducted entirely by Guest Investigators selected by NASA, will be devoted to spectroscopic observations of selected EUV sources. The instrumentation is now well developed. The best mirror has full-width/half-energy spread of 8 arcsec and a surface finish of 20 A. Prototype thin-film bandpass filters have been flown on the Space Shuttle and their performance optimized. Prototype detectors have been developed which have 600 by 600-pixel imaging capability and up to 80-percent quantum efficiency in parts of the EUV band.

Bowyer, Stuart↗