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Radiation Hardness Assurance (RHA) is the process of ensuring space system performance in the presence of a space radiation environment. Herein, we present an updated NASA methodology for RHA focusing on content, deliverables and timeframes.
The NEPP Program focuses on the reliability aspects of electronic devices (integrated circuits such as a processor in a computer). There are three principal aspects of this reliability: 1) Lifetime, inherent failure and design issues related to the EEE parts technology and packaging; 2) Effects of space radiation and the space environment on these technologies, and; 3) Creation and maintenance of the assurance support infrastructure required for mission success. The NEPP mission is to provide guidance to NASA for the selection and application of microelectronics technologies, to improve understanding of the risks related to the use of these technologies in the space environment, and to ensure that appropriate EEE parts research is performed to meet NASA mission assurance needs. NEPPs FY15 goals are to represent the NASA voice to the greater aerospace EEE parts community including supporting anti-counterfeit and trust, provide relevant guidance to cost-effective missions, aid insertion of advanced (and commercial) technologies, resolve unexpected parts issues, ensure access to appropriate radiation test facilities, and collaborate as widely as possible with external entities. In accordance with the changing mission profiles throughout NASA, the NEPP Program has developed a balanced portfolio of efforts to provide agency-wide assurance for not only traditional spacecraft developments, but also those in-line with the new philosophies emerging worldwide. In this presentation, we shall present an overview of this program and considerations for EEE parts assurance as applied to cost conscious missions.
Heliophysics (the study of the Sun and its effects on the Solar System, especially the Earth) has an interesting data environment in that the data are often to be found in relatively small data sets widely scattered in archives around the world. Within the last decade there have been more concentrated efforts to organize the data access methods and create a Heliophysics Data and Model Consortium (HDMC). To provide data search and access capability a number of Virtual Observatories (VO's) have been established both via funding from the U.S. National Aeronautics and Space Administration (NASA) and through other funding agencies in the U.S. and worldwide. At least 15 systems can be labeled as Heliophysics Virtual Observatories, 9 of them funded by NASA. Other parts of this data environment include Resident Archives, and the final, or "deep" archive at the National Space Science Data Center (NSSDC). The problem is that different data search and access approaches are used by all of these elements of the HDMC and a search for data relevant to a particular research question can involve consulting with multiple VO's - needing to learn a different approach for finding and acquiring data for each. The Space Physics Archive Search and Extract (SPASE) project is intended to provide a common data model for Heliophysics data and therefore a common set of metadata for searches of the VO's and other data environment elements. The SPASE Data Model has been developed through the common efforts of the HDMC representatives over a number of years. We currently have released Version 2.1. of the Data Model. The advantages and disadvantages of the Data Model will be discussed along with the plans for the future. Recent changes requested by new members of the SPASE community indicate some of the directions for further development.
The topology of photons in vacuum is interesting because there are no photons with k = 0, creating a hole in momentum space. We show that while the set of all photons forms a trivial vector bundle $γ$ over this momentum space, the R and L photons form topologically nontrivial subbundles $γ±$ with first Chern numbers ∓2. In contrast, $γ$ has no linearly polarized subbundles, and there is no Chern number associated with linear polarizations. It is a known difficulty that the standard version of Wigner’s little group method produces singular representations of the Poincaré group for massless particles. By considering representations of the Poincaré group on vector bundles we obtain a version of Wigner’s little group method for massless particles which avoids these singularities. Here we show that any massless bundle representation of the Poincaré group can be canonically decomposed into irreducible bundle representations labeled by helicity, which in turn can be associated to smooth irreducible Hilbert space representations. This proves that the R and L photons are globally well defined as particles and that the photon wave function can be uniquely split into R and L components. This formalism offers a method of quantizing the electromagnetic field without invoking discontinuous polarization vectors as in the traditional scheme. We also demonstrate that the spin-Chern number of photons is not a purely topological quantity. Lastly, there has been an extended debate on whether photon angular momentum can be split into spin and orbital parts. Our work explains the precise issues that prevent this splitting. Photons do not admit a spin operator; instead, the angular momentum associated with photons’ internal degree of freedom is described by a helicity-induced subalgebra corresponding to the translational symmetry of $γ$.
With the advancing computer processing capabilities, practical computer applications are mostly limited by the amount of human programming required to accomplish a specific task. This necessary human participation creates many problems, such as dramatically increased cost. To alleviate the problem, computers must become more autonomous. In other words, computers must be capable to program/reprogram themselves to adapt to changing environments/tasks/demands/domains. Evolutionary computation offers potential means, but it must be advanced beyond its current practical limitations. Evolutionary algorithms model nature. They maintain a population of structures representing potential solutions to the problem at hand. These structures undergo a simulated evolution by means of mutation, crossover, and a Darwinian selective pressure. Genetic programming (GP) is the most promising example of an evolutionary algorithm. In GP, the structures that evolve are trees, which is a dramatic departure from previously used representations such as strings in genetic algorithms. The space of potential trees is defined by means of their elements: functions, which label internal nodes, and terminals, which label leaves. By attaching semantic interpretation to those elements, trees can be interpreted as computer programs (given an interpreter), evolved architectures, etc. JSC has begun exploring GP as a potential tool for its long-term project on evolving dextrous robotic capabilities. Last year we identified representation redundancies as the primary source of inefficiency in GP. Subsequently, we proposed a method to use problem constraints to reduce those redundancies, effectively reducing GP complexity. This method was implemented afterwards at the University of Missouri. This summer, we have evaluated the payoff from using problem constraints to reduce search complexity on two classes of problems: learning boolean functions and solving the forward kinematics problem. We have also developed and implemented methods to use additional problem heuristics to fine-tune the searchable space, and to use typing information to further reduce the search space. Additional improvements have been proposed, but they are yet to be explored and implemented.
Rats were flown aboard the Soviet biosatellite Cosmos 936 for 18.5 d during August, 1977. Five rats were subjected to near-weightless space flight, as with Cosmos 782, and five rats were subjected to a 1-G force via an on-board centrifuge. These rats and three control groups were injected with 2-(C-14) glycine 19 d preflight. The flight rats were recovered from orbit after 18.5 d of space flight. Erythrocyte hemolysis and lifespan were evaluated in the five groups of rats by quantitation of radioactive carbon monoxide exhaled in the breath which arises from the breakdown of the previously labeled hemoglobin. The results support the previous findings wherein hemolysis was found to increase as a result of weightless space flight. A comparison to the centrifuged animals indicates that artificial gravity attenuates the effect of weightlessness on hemolysis and appears to normalize the hemolytic rate in the early postflight period.
Both OSHA medical and work place surveillance requirements and NIOSH recommendations were prepared as a desk reference to help occupational health professionals to perform their duties. The medical surveillance information focuses on frequency of physical examinations, specific problems that may arise as a result of exposure (e.g., decreased immunocompetence, weight loss, ets.), conditions that intensify the harmful effects of exposure (e.g., medication an exposed employee may be taking, cigarette smoking, etc.), the areas that should be scrutinized in medical and work histories and during the physical exam, and specific clinical tests that should be conducted. Recordkeeping requirements are also specified. The workplace surveillance information consists of monitoring requirements, personal protective equipment requirements, and recordkeeping requirements. Such details as the sampling devices that should be used, the type of respirators that should be worn, and the frequency of inspections are included. This document does not specify the training, labeling and posting, and safe work practice requirements and recommendations due to space considerations.
This viewgraph presentation addresses the integrated cycling and component selection technologies for aerospace systems. The topics include: 1) Semiconductors: The Evolution of ICs - Availability and Technology; 2) IC Selection Requirements - three fields of thought, "The Good", "The Bad" and "The Ugly"; 3) Reliability and Radiation; 4) Radiation Perspective-Four methods of selecting ICs for space systems, Guaranteed hardness, historical ground-based radiation data, historical flight usage, and unknown assurance; 5) Understanding Risk, including risk trade space and ASICs and FPGA sample selection criteria.
As NASA and its space partners endeavor to develop a network of satellites capable of supporting humankind's needs for advanced space weather prediction and understanding, one of the key challenges is to design a space system to operate in the natural space radiation environment In this paper, we present a description of the natural space radiation environment, the effects of interest to electronic or photonic systems, and a sample of emerging technologies and their specific issues. We conclude with a discussion of operations in the space radiation hazard and considerations for risk management.
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.
Data analysis techniques can be powerful tools for rapidly analyzing data and extracting information that can be used in a latent space for categorizing observations between classes of data. Machine learning models that exploit learned data relationships can address a variety of nuclear nonproliferation challenges like the detection and tracking of shielded radiological material transfers. The high resource cost of manually labeling radiation spectra is a hindrance to the rapid analysis of data collected from persistent monitoring and to the adoption of supervised machine learning methods that require large volumes of curated training data. Instead, contrastive self-supervised learning on unlabeled spectra can enhance models that are built on limited labeled radiation datasets. This work demonstrates that contrastive machine learning is an effective technique for leveraging unlabeled data in detecting and characterizing nuclear material transfers demonstrated on radiation measurements collected at an Oak Ridge National Laboratory testbed, where sodium iodide detectors measure gamma radiation emitted by material transfers between the High Flux Isotope Reactor and the Radiochemical Engineering Development Center. Label-invariant data augmentations tailored for gamma radiation detection physics are used on unlabeled spectra to contrastively train an encoder, learning a complex, embedded state space with self-supervision. A linear classifier is then trained on a limited set of labeled data to distinguish transfer spectra between byproducts and tracked nuclear material using representations from the contrastively trained encoder. The optimized hyperparameter model achieves a balanced accuracy score of 80.30%. Any given model—that is, a trained encoder and classifier—shows preferential treatment for specific subclasses of transfer types. Regardless of the classifier complexity, a supervised classifier using contrastively trained representations achieves higher accuracy than using spectra when trained and tested on limited labeled data.
The computer program known as PLOTRW was custom made to satisfy some of the graphics requirements for the data collected in the Space Plasma Laboratory at the Johnson Space Center (JSC). The general requirements for the program were as follows: (1) all subroutines shall be callable through a FORTRAN source program; (2) all graphs shall fill one page and be properly labeled; (3) there shall be options for linear axes and logarithmic axes; (4) each axis shall have tick marks equally spaced with numeric values printed at the beginning tick mark and at the last tick mark; and (5) there shall be three options for plotting. These are: (1) point plot, (2) line plot and (3) point-line plot. The subroutines were written in FORTRAN IV for the LSI-11 Digital equipment Corporation (DEC) Computer. The program is now operational and can be run on any TEKTRONICX graphics terminal that uses a DEC Real-Time-11 (RT-11) operating system.
A crossed-beam apparatus is used to measure the product ion velocity and angular distributions for the following ion-molecule reactions in the relative energy range from 2 to 9 eV: CH4(+) + NH3 yields NH4(+) + CH3; CH4(+) + NH3 yields CNH5(+) + H2; NH2(+) + CH4 yields CNH4(+) + H2 (or 2H); and CH3(+) + NH3 yields CNH4(+) + H2 (or 2H). These reactions are also studied by means of deuterium labeling as a further probe of the detailed reaction dynamics. Probability contour plots for the four reactions are constructed in Cartesian velocity space, and product peaks in the plots are discussed. Relative cross sections and Q values are computed for two of the reactions as well as for the corresponding deuterium-labelled reactions. The results show that the present ion-neutral condensation reactions are highly exothermic with a deep well for the internal complex, that little hydrogen scrambling occurs, and that the energy of the reactions is released mainly as internal energy, even to the extent of producing two hydrogen atoms in some cases rather than one hydrogen atom or molecule.
This note is concerned with the explicit symbolic computation of expressions involving differential operators and their actions on functions. The derivation of specialized numerical algorithms, the explicit symbolic computation of integrals of motion, and the explicit computation of normal forms for nonlinear systems all require such computations. More precisely, if R = k(x(sub 1),...,x(sub N)), where k = R or C, F denotes a differential operator with coefficients from R, and g member of R, we describe data structures and algorithms for efficiently computing g. The basic idea is to impose a multiplicative structure on the vector space with basis the set of finite rooted trees and whose nodes are labeled with the coefficients of the differential operators. Cancellations of two trees with r + 1 nodes translates into cancellation of O(N(exp r)) expressions involving the coefficient functions and their derivatives.
The purpose of this summer project was to develop a set of schematic drawings for redesign of the Space Shuttle flight deck from which three dimensional computer drawings can be built and viewed in a virtual environment. In order to achieve this goal, first recommendations for overall redesign of Space Shuttle previously made by experts in the field were reviewed and relevant information was extracted and delineated. Original drawings of the Space Shuttle made by Rockwell were obtained and carefully examined. In order to implement and assess any modifications in terms of space saving parameters, it was determined that the drawings alone could not achieve this objective. As a complement, physical measurements of the mockup of Space Shuttle flight deck were made and the information was categorized and properly labeled on the original drawings. Then, spacesaving redesign ideas, as motivated by expert recommendations on such things as information display panel upgrade by technologically advanced flat display units, were implemented. Next, the redesign ideas were executed on the Forward flight deck, Overhead Console, Right and Left Console, and Center Console. A new 3-D computer drawing of this was developed by modifying the existing drawing on the in-house developed software (PLAID). Finally, the drawing was transported to a Virtual Environment and observed.
Rats were subjected to 19.5 days of weightless space flight aboard the Soviet biosatellite, Cosmos 782. Based on the output of CO-14, survival parameters of a cohort of erythrocytes labeled 15.5 days preflight were evaluated upon return from orbit. These were compared to vivarium control rats injected at the same time. Statistical evaluation indicates that all survival factors were altered by the space flight. The mean potential lifespan, which was 63.0 days in the control rats, was decreased to 59.0 days in the flight rats, and random hemolysis was increased three-fold in the flight rats. The measured size of the cohort was decreased, lending further support to the idea that hemolysis was accelerated during some portion of the flight. A number of factors that might be contributory to these changes are discussed, including forces associated with launch and reentry, atmospheric and environmental parameters, dietary factors, radiation, and weightlessness.
With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature. Classifying SPI scattering patterns, or `speckles', to extract single-hits that are needed for real-time vetoing and three-dimensional reconstruction poses a challenge for high-data-rate facilities like the European XFEL and LCLS-II-HE. Here, we introduce SpeckleNN, a unified embedding model for real-time speckle pattern classification with limited labeled examples that can scale linearly with dataset size. Trained with twin neural networks, SpeckleNN maps speckle patterns to a unified embedding vector space, where similarity is measured by Euclidean distance. We highlight its few-shot classification capability on new never-seen samples and its robust performance despite having only tens of labels per classification category even in the presence of substantial missing detector areas. Without the need for excessive manual labeling or even a full detector image, our classification method offers a great solution for real-time high-throughput SPI experiments.
This presentation has been a brief snapshot discussing electronics and Exploration-related challenges. The vision for Space Exploration creates a new paradigm for NASA missions. This includes transport (Crew Exploration Vehicle-CEV), and lunar and Mars Exploration and human presence. If one considers the additional hazards faced by these concepts versus more traditional NASA missions, multiple challenges surface for reliable utilization of electronic parts. The true challenge is to provide a risk as low as reasonably achievable (ALARA-a traditional biological radiation exposure term), while still providing cost effective solutions. This presentation also discusses the hazard for electronic parts and exploration, the types of electronic parts for exploration, and the critical juncture for space usage of commercial changes in the electronics world.