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The extension of the operation life of military and civilian aircraft rather than replacing them with new ones is increasing the probability of aircraft component failure as a result of aging. Aircraft that already have endured a long srvice life of more than 40 years are now being considered for another 40 years of service.
As software is maintained or reused, it undergoes an evolution which tends to increase the overall complexity of the code. To understand the effects of this, we brought in statistics experts and leading researchers in software complexity, reliability, and their interrelationships. These experts' project has resulted in our ability to statistically correlate specific code complexity attributes, in orthogonal domains, to errors found over time in the HAL/S flight software which flies in the Space Shuttle. Although only a prototype-tools experiment, the result of this research appears to be extendable to all other NASA software, given appropriate data similar to that logged for the Shuttle onboard software. Our research has demonstrated that a more complete domain coverage can be mathematically demonstrated with the approach we have applied, thereby ensuring full insight into the cause-and-effects relationship between the complexity of a software system and the fault density of that system. By applying the operational profile we can characterize the dynamic effects of software path complexity under this same approach We now have the ability to measure specific attributes which have been statistically demonstrated to correlate to increased error probability, and to know which actions to take, for each complexity domain. Shuttle software verifiers can now monitor the changes in the software complexity, assess the added or decreased risk of software faults in modified code, and determine necessary corrections. The reports, tool documentation, user's guides, and new approach that have resulted from this research effort represent advances in the state of the art of software quality and reliability assurance. Details describing how to apply this technique to other NASA code are contained in this document.
The GOES Product Generation System (GPGS) is a set of computer codes and scripts that enable the assimilation of real-time Geostationary Operational Environmental Satellite (GOES) data into regional-weather-forecasting mathematical models. The GPGS can be used to derive such geophysical parameters as land surface temperature, the amount of precipitable water, the degree of cloud cover, the surface albedo, and the amount of insolation from satellite measurements of radiant energy emitted by the Earth and its atmosphere. GPGS incorporates a priori information (initial guesses of thermodynamic parameters of the atmosphere) and radiometric measurements from the geostationary operational environmental satellites along with mathematical models of physical principles that govern the transfer of energy in the atmosphere. GPGS solves the radiative-transfer equation and provides the resulting data products in formats suitable for use by weather-forecasting computer programs. The data-assimilation capability afforded by GPGS offers the potential to improve local weather forecasts ranging from 3 hours to 2 days - especially with respect to temperature, humidity, cloud cover, and the probability of precipitation. The improvements afforded by GPGS could be of interest to news media, utility companies, and other organizations that utilize regional weather forecasts.
The probability density functions (pdfs) of the co- and cross-polarized phase differences are derived for backscatter from vegetation using the coherent and incoherent scattering theories. Unlike previous derivations, no assumptions or observations other than the applicability of the Central Limit Theorem (CLT), the low fractional volume of the medium, the reciprocity of the scatterers, and the azimuthal symmetry of the scatterer's orientation statistics are employed. Everything else follows logically via the mathematics. The difference between the coherent theory and the incoherent theory is referred to as the backscatter enhancement effect. The influence of this enhancement effect on the phase difference pdfs is examined and found to be important under combined conditions of scatterer anisotropy and appropriate reflection coefficient values.
The reaction between the radical C2H and the stable hydrocarbon C2H2 is one of the simplest neutral-neutral hydrocarbon reactions in chemical models of dense interstellar clouds and carbon-rich circumstellar shells. Although known to be rapid at temperatures > or = 300 K, the reaction has yet to be studied at lower temperatures. We present here ab initio calculations of the potential surface for this reaction and dynamical calculations to determine its rate at low temperature. Despite a small potential barrier in the exit channel, the calculated rate is large, showing that this reaction and, most probably, more complex analogs contribute to the formation of complex organic molecules in low-temperature sources.
We develop a constructive approach to generate quantum neural networks capable of representing the exact thermal states of all many-body qubit Hamiltonians. The Trotter expansion of the imaginary time propagator is implemented through an exact block encoding by means of a unitary, restricted Boltzmann machine architecture. Marginalization over the hidden-layer neurons (auxiliary qubits) creates the nonunitary action on the visible layer. Then, we introduce a unitary deep Boltzmann machine architecture in which the hidden-layer qubits are allowed to couple laterally to other hidden qubits. We prove that this wave-function is closed under the action of the imaginary time propagator and, more generally, can represent the action of a universal set of quantum gate operations. We provide analytic expressions for the coefficients for both architectures, thus enabling exact network representations of thermal states without stochastic optimization of the network parameters. In the limit of large imaginary time, the yields the ground state of the system. The number of qubits grows linearly with the number of interactions and total imaginary time for a fixed interaction order. Both networks can be readily implemented on quantum hardware via midcircuit measurements of auxiliary qubits. If only one auxiliary qubit is measured and reset, the circuit depth scales linearly with imaginary time and number of interactions, while the width is constant. Alternatively, one can employ a number of auxiliary qubits linearly proportional to the number of interactions, and circuit depth grows linearly with imaginary time only. Every midcircuit measurement has a postselection success probability, and the overall success probability is equal to the product of the probabilities of the midcircuit measurements.
Much like the better-known EI Nino-Southern Oscillation, the Madden-Julian Oscillation (MJO) is a global-scale atmospheric phenomenon. The MJO involves periodic, systematic changes in the distribution of clouds and precipitation over the western Pacific and Indian oceans, along with differences in wind intensity over even more extensive areas, including the north and subtropical Atlantic Ocean. The lead authors of this paper developed a sophisticated mathematical technique for mapping the spatial and temporal behavior of changes in the atmosphere produced by the MJO. In a previous paper, we applied this technique to search for modulation of airborne particle amount in the eastern hemisphere associated with the "wet" (cloudy) vs. "dry" phases of the MJO. The study used primarily AVHRR, MODIS, and TOMS satellite-retrieved aerosol amount, but concluded that other factors, such as cloud contamination of the satellite signals, probably dominated the observed variations. The current paper looks at MJO modulation of desert dust transport eastward across the Atlantic from northern Africa, a region much less subject to systematic cloud contamination than the eastern hemisphere areas studied previously. In this case, a distinct aerosol signal appears, showing that dust is transported westward much more effectively during the MJO phase that favors westward-flowing wind, and such transport is suppressed when the MJO reduces these winds. Aside form the significant achievement in identifying such an effect, the result implies that an important component of global dust transport can be predicted based on the phase of the MJO. As a consequence, the impact of airborne dust on storm development in the Atlantic, and on dust deposition downwind of the desert sources, can also be predicted and more accurately modeled.
A technique for word timing recovery in a direct-detection optical PPM communication system is described. It tracks on back-to-back pulse pairs in the received random PPM data sequences with the use of a phase locked loop. The experimental system consisted of an 833-nm AlGaAs laser diode transmitter and a silicon avalanche photodiode photodetector, and it used Q = 4 PPM signaling at source data rate 25 Mb/s. The mathematical model developed to describe system performance is shown to be in good agreement with the experimental measurements. Use of this recovered PPM word clock with a slot clock recovery system caused no measurable penalty in receiver sensitivity. The completely self-synchronized receiver was capable of acquiring and maintaining both slot and word synchronizations for input optical signal levels as low as 20 average detected photons per information bit. The receiver achieved a bit error probability of 10 to the -6th at less than 60 average detected photons per information bit.
Here, we propose a multistart algorithm to identify all local minima of a constrained, nonconvex stochastic optimization problem. The algorithm uniformly samples points in the domain and then starts a local stochastic optimization run from any point that is the "probabilistically best" point in its neighborhood. Under certain conditions, our algorithm is shown to asymptotically identify all local optima with high probability; this holds even though our algorithm is shown to almost surely start only finitely many local stochastic optimization runs. We demonstrate the performance of an implementation of our algorithm on nonconvex stochastic optimization problems, including identifying optimal variational parameters for the quantum approximate optimization algorithm.
The fast-paced growth in digitization of smart grid components enhances system observability and remote-control capabilities through efficient communication. However, enhanced connectivity results in heightened system vulnerability towards cybersecurity risks in the cyber-physical power system. Coordinated cyber-attacks (CCA), when undetected, lead to system-wide impact in terms of large disturbances or widespread outages. Detecting CCA in the cyber layer is critical to thwart cyber-attacks in real-time before the attack impacts the physical system. The challenge of locating CCA stems from the complex grid dynamics, making it difficult to distinguish between normal operational variations and cyber-attack impact. CCA often employs multiple attack vectors targeting geographically distributed components, further complicating CCA identification. Existing research in intrusion detection is primarily focused on the transmission network and limited to detecting individual attacks. In this paper, a novel proactive DCA strategy is proposed for early detection of CCA by establishing correlations among distinct attack events through model-based reinforcement learning that utilizes abductive reasoning to conclude the attacker goal. The solution includes understanding the system model, learning the system dynamics, and correlating individual cyber-attacks to extract the attacker’s objective. The developed learning algorithm identifies the most probable attack path to reach the attacker’s objective by predicting the next attack steps. A DNP3-based cyber-physical co-simulation testbed is developed to test the proposed algorithm using the IEEE 13-node test feeder.
The problem of global maxima of functionals has been examined. Mathematical roots of local maxima are the same as those for a much simpler problem of finding global maximum of a multi-dimensional function. The second problem is instability even if an optimal trajectory is found, there is no guarantee that it is stable. As a result, a fundamentally new approach is introduced to optimal control based upon two new ideas. The first idea is to represent the functional to be maximized as a limit of a probability density governed by the appropriately selected Liouville equation. Then, the corresponding ordinary differential equations (ODEs) become stochastic, and that sample of the solution that has the largest value will have the highest probability to appear in ODE simulation. The main advantages of the stochastic approach are that it is not sensitive to local maxima, the function to be maximized must be only integrable but not necessarily differentiable, and global equality and inequality constraints do not cause any significant obstacles. The second idea is to remove possible instability of the optimal solution by equipping the control system with a self-stabilizing device. The applications of the proposed methodology will optimize the performance of NASA spacecraft, as well as robot performance.
The effect of radiogenic heating on the thermal evolution of spherical icy bodies with radii 1 km < R < 100 km was investigated. The radioisotopes considered were 26Al, 40K, 232Th, 235U, and 238U. Except for the 26Al abundance, which was varied, the other initial abundances were kept fixed, at values derived from those of chondritic meteorites and corresponding to a gas-to-dust ratio of 1. The initial models were homogeneous and isothermal (To = 10 K) amorphous ice spheres, in a circular orbit at 10(4) AU from the Sun. The main object of this study was to examine the conditions under which the transition temperature from amorphous into cubic ice (Ta = 137 K) would be reached. It was shown that the influence of the short-lived radionuclide 26Al dominates the effect of other radioactive species for bodies of radii up to approximately 50 km. Consequently, if we require comets to retain their ice in amorphous form, as suggested by observations, an upper limit of approximately 4 x 10(-9) is obtained for the initial 26Al abundance in comets, a factor of 100 lower than that of the inclusions in the Allende meteorite. A lower limit for the formation time of comets may thus be derived. The possibility of a coexistence of molten cometary cores and extended amorphous ice mantles is ruled out. Larger icy spheres (R > 100 km) reached Ta even in the absence of 26Al, due to the decay of the other radionuclides. As a result, a crystalline core formed whose relative size depended on the composition assumed. Thus the outermost icy satellites in the solar system, which might have been formed of ice in the amorphous state, have probably undergone crystallization and may have exhibited eruptive activity when the gas trapped in the amorphous ice was released (e.g., Miranda).
Quantifying the effects of uncertainty in a reactive burn model on the run-to-detonation time in high explosives (HEs) provides a robust methodology for assessing the probability of an HE failing the IHE qualification standard. Moreover, uncertainty quantification helps evaluate whether the model calibration accurately represents data outside the calibration set. This study uses a specialized hydrodynamic simulation code for modeling detonation to determine the run-to-detonation time of the HE PBX 9502 for various impact velocities. To quickly approximate uncertainties in the model, a surrogate was constructed using a Taylor series expansion centered at the mean of the input parameters. To obtain the sensitivities required for constructing the Taylor series, HYP-percomplex Automatic Differentiation (HYPAD) was implemented. HYPAD is a methodology for infusing existing codes with automatic differentiation capabilities by augmenting variables with one or more imaginary units to compute step-size independent partial derivatives. These derivatives are accurate to machine precision with respect to the implemented numerical algorithm, meaning their accuracy reflects that of the underlying method (e.g., integration or discretization schemes). Using reduced order modeling techniques, the mean and standard deviation of the run-to-detonation time of a shock within PBX 9502 were computed for a number of initial impact velocities. A weighted least squares regression was then performed to obtain a best fit curve and prediction interval for the computed statistics. Historical data points from explosively driven wedge tests were utilized to validate the prediction interval, ensuring its reliability in predicting future outcomes. With this prediction interval and a known safety constraint curve, the most probable point of failure and the probability of failure for the HE PBX 9502 were determined.
V-HAMSTeR is a bioinformatics software tool designed to predict the hosts of viruses directly from genomic sequences. It can be used by researchers to predict animal, prokaryotic, plant, protist or fungal viral hosts including viruses that may be fragmented or discovered in environmental metagenomic datasets. Features & Uses: The software employs a novel dual-stream deep learning architecture that dynamically fuses implicit sequence embeddings from a genomic foundation model with 13 explicit, handcrafted biological features (e.g., coding density and strand switch rates). To ensure maximum reliability, V=HAMSTeR deploys a 5-fold deep ensemble calibrated via Joint Temperature Scaling, providing users with statistically rigorous confidence probabilities. It also features an automated sequence chunking and mean-pooling module to seamlessly process variable-length contigs. Advantages Over Similar Technologies: Existing tools (e.g., IPEV, RNAVirHost) typically rely on either basic k-mers or isolated neural networks. V-HAMSTeR's hybrid architecture captures both broad genomic context and specific biological motifs that standalone foundation models often miss. Furthermore, unlike competitor tools that struggle with incomplete data or exhibit extreme overconfidence, V-HAMSTeR is explicitly benchmarked and mathematically calibrated for fragmented assemblies (1kb–10kb). This makes it uniquely robust, accurate, and trustworthy for the messy reality of real-world environmental viromics.
A simple argument is outlined leading to the result that the mass of mini black holes exploding today is 10 to the 15th power g. A mathematical model is discussed which indicates that the equation of state is greatly softened in the high-density regime and a phase transition may exist, such that any length (particularly very small sizes) will grow with time irrespective of its relation to the size of the particle horizon. It is shown that the effect of spin-2 mesons with respect to the equation of state is to soften the pressure and make it negative. An analytical expression is given for the probability that any particular region in a hot early universe will evolve into a black hole.
A mathematical model is used to analyze mutant spectra for large mutations induced by low-LET radiation. The model equations are based mainly on two-break misrejoining that leads to deletions or translocations. It is assumed, as a working hypothesis, that the initial damage induced by low-LET radiation is located randomly in the genome. Specifically, we analyzed data for two hemizygous loci: CD59- mutants, mainly very large-scale deletions (>3 Mbp), in human-hamster hybrid cells, and data from the literature on those HPRT- mutants which involve at least deletion of the whole gene, and often of additional flanking markers (approximately 50-kbp to approximately 4.4-Mbp deletions). For five data sets, we estimated f, the probability that two given breaks on the same chromosome will misrejoin to make a deletion, as a function of the separation between the breaks. We found that f is larger for nearby breaks than for breaks that are more widely separated; i.e., there is a "proximity effect". For acute irradiation, the values of f determined from the data are consistent with the corresponding break misrejoining parameters found previously in quantitative modeling of chromosome aberrations. The value of f was somewhat smaller for protracted irradiation than for acute irradiation at a given total dose; i.e., the mutation data show a decrease that was smaller than expected for dose protraction by fractionation or low dose rate.
PyFaults is an open-source Python library designed to model stacking fault disorder in crystalline materials and qualitatively assess the characteristic selective broadening effects in powder X-ray diffraction (PXRD). Here, the main capabilities of PyFaults are presented, including unit cell and supercell model construction, PXRD pattern calculation, assessment against experimental PXRD, and methods for rapid screening of candidate models within a set of possible stacking vectors and fault occurrence probabilities. This program aims to serve as a computationally inexpensive tool for identifying and screening potential stacking fault models in materials with planar disorder. Three diverse case studies, involving GaN, Li2MnO3 and Li3YCl6, are presented to illustrate the program functionality across a range of structure types and stacking fault modalities.
Lunar meteorites (LMs) are rocks found on Earth that were ejected from the Moon by impact of an asteroidal meteoroid. Three factors make the LMs important to remote-sensing studies: (1) Most are breccias composed of regolith or fragmental material; (2) all are rocks that resided (or breccias composed of material that resided) in the upper few meters of the Moon prior to launch and (3) most apparently come from areas distant from the Apollo sites. How Many Lunar Locations? At this writing (June 1999), there are 18 known lunar meteorite specimens. When unambiguous cases of terrestrial pairing are considered, the number of actual LMs reduces to 13. (Terrestrial pairing is when a single piece of lunar rock entered Earth's atmosphere, but multiple fragments were produced because the meteoroid broke apart on entry, upon hitting the ground or ice, or while being transported through the ice.) We have no reason to believe that LMs preferentially derive from any specific region(s) of the Moon; i.e., we believe that they are samples from random locations. However, we do not know how many different locations are represented by the LMs; mathematically, it could be as few as 1 or as many as 13. The actual maximum is < 13 because in some cases a single impact appears to have yielded more than one LM. Yamato 793169 and Asuka 881757 are considered "source-crater paired" or "launch paired" because they are compositionally and petrographically similar to each other and distinct from the others, and both have similar cosmic-ray exposure (CRE) histories. The same can be said of QUE 94281 and Y 793274. Thus the 13 meteorites probably represent a maximum of 11 locations on the Moon. The minimum number of likely source craters is debated and in flux as new data for different isotopic systems are obtained. Conservatively, considering CRE data only, a minimum of about 5 impacts is required. Compositional and petrographic data offer only probabilistic constraints. An extreme, but not unreasonable viewpoint, is that such data offer no constraint. For example, if one were to cut up the Apollo 17 landing site (which was selected for its diversity) into softball-sized pieces, some of those pieces (e.g., sample 70135) would be crystalline mare basalts like Y 793169 whereas others (e.g., sample 73131 would be feldspathic regolith breccias like MAC 88104/ 88105. However, nature is not so devious. Warren argues that LMs come from craters of only a few kilometers in diameter. If so, even though CRE data allow, for example, that ALHA 81005 and Y 791197) were launched simultaneously from the same crater, the probability is nevertheless low because the two meteorites are compositionally and mineralogically distinct. Thus, within the allowed range (5-11) for the number of locations represented by the LMs, values at the high end of the range are probably more likely. Mare Meteorites: Three LMs consist almost entirely of mare basalt. Two, Y 793169 and Asuka 881757, are unbrecciated, low-Ti, crystalline rocks that are compositionally and mineralogically similar (but not identical) to each other; they probably derive from a single lunar-mare location. The third, EET 87521/96008, is a fragmental breccia consisting predominantly of VLT mare basalt. Thus, these LMs probably represent only two lunar mare locations. The basaltic LMs have mineral and bulk compositions distinct from Apollo mare basalts. The petrography of Calcalong Creek has not been described in detail, but compositionally it is unique in that it corresponds to a mixture (breccia) of about one-half feldspathic material (i.e., the mean composition of the feldspathic lunar meteorites, below), one-fourth KREEP norite, one-fourth VLT mare basalt (like EET 87521), and 1% CI chondrite. With 4 micro g/g Th and correspondingly high concentrations of other incompatible elements, it is the only lunar meteorite that is likely to have come from within the Procellarum KREEP Terrane (PKT). Yamato 793274 and QUE 94281 are together distinct in being fragmental breccias containing subequal parts of feldspathic highland material and VLT mare basalt. Jolliff et al. estimate a mare to highland ratio of 54:46 for QUE 94281 and 62:38 for Y 793274; this difference is well within the range observed for soils collected only centimeters apart (in cores) at interface site like Apollo 15 and 17 [11]. Although the two meteorites were found on opposite sides of Antarctica, they are probably launch-paired. The strongest evidence is that the pyroclastic glass spherules that occur in both are of two compositional groups and the two groups are essentially the same in both meteorites. Yamato 791197 is nominally a feldspathic lunar meteorite (below), but among FLMs, it probably contains the highest abundance of clasts and glasses of mare derivation. As a consequence, its composition is at the high-Fe, low-Mg end of the range for FLMs and is not included in the FLM average of Table 1. Its composition is consistent with about 10% mare-derived material. Similarly, the two small (Y 82) pieces of Y 82192/82193186032 are more mafic than the large (Y 86) piece, probably as a result of about 7% mare-derived material. All Apollo missions went to areas in or near the PKT, and, consequently, all Apollo regolith samples are contaminated with Th-rich material from the PKT. At the nominally "typical" highland site, Apollo 16, about 30% of the regolith (<1-mm fines) is Th-rich ejecta from the Imbrium impact and about 6% is mare material probably derived from mare basins. Thus Apollo 16 regolith is not typical of the highlands. Among Apollo rocks, the compositions of the FLMs correspond most closely to the feldspathic granulitic breccias of Apollo 16 and 17. (Additional information is contained in original)