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At least 1,747 records · Page 97

Studies of asteroids, comets, and Jupiter's outer satellites

Observational, theoretical, and computational research was performed, mainly on asteroids. Two principal areas of research, centering on astrometry and photometry, are interrelated in their aim to study the overall structure of the asteroid belt and the physical and orbital properties of individual asteroids. Two highlights are: detection of CN emission from Chiron; and realization that 1990 MB is the first known Trojan type asteroid of a planet other than Jupiter. A new method of asteroid orbital error analysis, based on Bayesian theory, was developed.

Bowell, Edward↗

Time trends of VAS satellite-derived soundings

Results are presented on evaluations of the accuracy of 3-, 6-, and 9-hr time trends of temperature and dew point derived from the VISSR Atmospheric Sounder (VAS), by comparing the VAS-derived trends with those from ground-truth radiosonde soundings. Results show that VAS soundings have only a limited ability to determine trends over 6-hr periods and shorter. It is suggested that a source of error in VAS is poor first-guess trends, which the algorithm seems to magnify. However, it is shown that trends over longer intervals or with greater magnitudes may be detected more accurately.

Breidenbach, Jay P.↗

Identification of propulsion systems

This paper presents a tutorial on the use of model identification techniques for the identification of propulsion system models. These models are important for control design, simulation, parameter estimation, and fault detection. Propulsion system identification is defined in the context of the classical description of identification as a four step process that is unique because of special considerations of data and error sources. Propulsion system models are described along with the dependence of system operation on the environment. Propulsion system simulation approaches are discussed as well as approaches to propulsion system identification with examples for both air breathing and rocket systems.

Merrill, Walter↗

Pseudocoherent Demodulation Of DPSK Radio Signals

Three schemes for pseudocoherent demodulation of differential-phase-shift keyed (DPSK) radio signals proposed for use in land-mobile/satellite communications. Enables fast reacquisition. Also amounts to compromise between two extremes of coherent demodulation and differentially coherent demodulation, for which bit-error rates greater than those of coherent demodulation by amounts corresponding to difference of about 1 dB in bit-energy/noise-energy ratio. Based on maximum-likelihood estimation and detection during N-symbol observation periods, where N integer typically chosen between 5 and 15.

Divsalar, Dariush↗

Discovery of a Nonblazar Gamma-Ray Transient Source Near the Galactic Plane: GRO J1838-04

We report the discovery of a remarkable gamma-ray transient source near the Galactic plane, GRO J1838-04. This source was serendipitously discovered by EGRET in 1995 June with a peak intensity of approx. (4 +/- 1) x 10(exp -6) photons/sq cm s (for photon energies larger than 100 MeV) and a 5.9 sigma significance. At that time, GRO J1838-04 was the second brightest gamma-ray source in the sky. A subsequent EGRET pointing in 1995 late September detected the source at a flux smaller than its peak value by a factor of approx. 7. We determine that no radio-loud spectrally flat blazar is within the error box of GRO J1838-04. We discuss the origin of the gamma-ray transient source and show that interpretations in terms of active galactic nuclei or isolated pulsars are highly problematic. GRO J1838-04 provides strong evidence for the existence of a new class of variable gamma-ray sources.

Tavani, M.↗

Infrared Communications for Small Spacecraft: From a Wireless Bus to Cluster Concepts

Nanosatellites operating singly or in clusters are anticipated for future space science missions. To implement this new communications paradigm, we are approaching cluster communications by first developing an infrared (IR) intra-craft wireless bus capability, following initially the MIL-STD-1553B protocol. Benefits of an IR wireless bus are low mass, size, power, and cost, simplicity of implementation, ease of use, minimum EMI, and efficient and reliable data transfer. Our goals are to maximize the reliable link margin in order to afford greater flexibility in receiver placement, which will ease technology insertion. We have developed a concept demonstration using a high-speed visible-band silicon PIN photodiode and a high-efficiency visible LED operating at a data rate up to 4 Mb/sec. In designing an internal IR wireless bus, we have characterized various candidate materials, emitters, and geometries, assuming a single reflection. Thus, we have measured the bidirectional reflectance distribution function (BRDF) for five different materials characteristic of typical spacecraft structures, which range from nearly Lambertian to highly specular. We have fit our data to empirical BRDF functions and modeled the detected irradiance anywhere in the plane of incidence for a divergent (LED) emitter. We have also determined the angular limits on the link geometry to remain within the required bit error rate by determining the received signal-to-noise ratio (SNR) for minimum values of irradiance received at the detector.

Webb, Suzanne C.↗

Toward Synthesis, Analysis, and Certification of Security Protocols

Implemented security protocols are basically pieces of software which are used to (a) authenticate the other communication partners, (b) establish a secure communication channel between them (using insecure communication media), and (c) transfer data between the communication partners in such a way that these data only available to the desired receiver, but not to anyone else. Such an implementation usually consists of the following components: the protocol-engine, which controls in which sequence the messages of the protocol are sent over the network, and which controls the assembly/disassembly and processing (e.g., decryption) of the data. the cryptographic routines to actually encrypt or decrypt the data (using given keys), and t,he interface to the operating system and to the application. For a correct working of such a security protocol, all of these components must work flawlessly. Many formal-methods based techniques for the analysis of a security protocols have been developed. They range from using specific logics (e.g.: BAN-logic [4], or higher order logics [12] to model checking [2] approaches. In each approach, the analysis tries to prove that no (or at least not a modeled intruder) can get access to secret data. Otherwise, a scenario illustrating the &tack may be produced. Despite the seeming simplicity of security protocols ("only" a few messages are sent between the protocol partners in order to ensure a secure communication), many flaws have been detected. Unfortunately, even a perfect protocol engine does not guarantee flawless working of a security protocol, as incidents show. Many break-ins and security vulnerabilities are caused by exploiting errors in the implementation of the protocol engine or the underlying operating system. Attacks using buffer-overflows are a very common class of such attacks. Errors in the implementation of exception or error handling can open up additional vulnerabilities. For example, on a website with a log-in screen: multiple tries with invalid passwords caused the expected error message (too many retries). but let the user nevertheless pass. Finally, security can be compromised by silly implementation bugs or design decisions. In a commercial VPN software, all calls to the encryption routines were incidentally replaced by stubs, probably during factory testing. The product worked nicely. and the error (an open VPN) would have gone undetected, if a team member had not inspected the low-level traffic out of curiosity. Also, the use secret proprietary encryption routines can backfire, because such algorithms often exhibit weaknesses which can be exploited easily (see e.g., DVD encoding). Summarizing, there is large number of possibilities to make errors which can compromise the security of a protocol. In today s world with short time-to-market and the use of security protocols in open and hostile networks for safety-critical applications (e.g., power or air-traffic control), such slips could lead to catastrophic situations. Thus, formal methods and automatic reasoning techniques should not be used just for the formal proof of absence of an attack, but they ought to be used to provide an end-to-end tool-supported framework for security software. With such an approach all required artifacts (code, documentation, test cases) , formal analyses, and reliable certification will be generated automatically, given a single, high level specification. By a combination of program synthesis, formal protocol analysis, certification; and proof-carrying code, this goal is within practical reach, since all the important technologies for such an approach actually exist and only need to be assembled in the right way.

Schumann, Johann↗

The Segmented Aperture Interferometric Nulling Testbed (SAINT) III: Control Systems Analysis and Preliminary Results

This work presents a detailed current performance analysis for the telescope, pointing, and coronagraph com- ponent subsystems of the Segmented Aperture Interferometric Nulling Testbed (SAINT). The project pairs an active segmented mirror with the Visible Nulling Coronagraph (VNC) towards demonstrating capabilities for the future space observatories needed to directly detect and characterize Earth-sized worlds around nearby stars. We describe approaches to optimize subsystem wavefront sensing and control parameters, summarizing relevant scal- ing relations between these parameters, residual errors, and observed contrast measurements. Preliminary results from diagnostic testing under various control states are presented along with intermediate contrast measurements towards demonstrating the full system.

Hicks, Brian A.↗

Kepler Instrument Performance: An In-Flight Update

The Kepler Mission is designed to detect the 80 parts per million (ppm) signal from an Earth-Sun equivalent transit. Such precision requires superb instrument stability on time scales up to 2 days and systematic error removal to better than 20 ppm. The sole scientic instrument is the Photometer, a 0.95 m aperture Schmidt telescope that feeds the 94.6 million pixel CCD detector array, which contains both Science and Fine Guidance Sensor (FGS) CCDs. Since Kepler's launch in March 2009, we have been using the commissioning and science operations data to characterize the instrument and monitor its performance. We find that the in-flight detector properties of the focal plane, including bias levels, read noise, gain, linearity, saturation, FGS to Science crosstalk,and video crosstalk between Science CCDs, are essentially unchanged from their pre-launch values. Kepler'sunprecedented sensitivity and stability in space have allowed us to measure both short- and long- term effects from cosmic rays, see interactions of previously known image artifacts with starlight, and uncover several unexpected systematics that affect photometric precision. Based on these results, we expect to attain Kepler's planned photometric precision over 90% of the field of view.

CCD↗

Satellite Gravimetry Applied to Drought Monitoring

Near-surface wetness conditions change rapidly with the weather, which limits their usefulness as drought indicators. Deeper stores of water, including root-zone soil wetness and groundwater, portend longer-term weather trends and climate variations, thus they are well suited for quantifying droughts. However, the existing in situ networks for monitoring these variables suffer from significant discontinuities (short records and spatial undersampling), as well as the inherent human and mechanical errors associated with the soil moisture and groundwater observation. Remote sensing is a promising alternative, but standard remote sensors, which measure various wavelengths of light emitted or reflected from Earth's surface and atmosphere, can only directly detect wetness conditions within the first few centimeters of the land s surface. Such sensors include the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) C-band passive microwave measurement system on the National Aeronautic and Space Administration's (NASA) Aqua satellite, and the combined active and passive L-band microwave system currently under development for NASA's planned Soil Moisture Active Passive (SMAP) satellite mission. These instruments are sensitive to water as deep as the top 2 cm and 5 cm of the soil column, respectively, with the specific depth depending on vegetation cover. Thermal infrared (TIR) imaging has been used to infer water stored in the full root zone, with limitations: auxiliary information including soil grain size is required, the TIR temperature versus soil water content curve becomes flat as wetness increases, and dense vegetation and cloud cover impede measurement. Numerical models of land surface hydrology are another potential solution, but the quality of output from such models is limited by errors in the input data and tradeoffs between model realism and computational efficiency. This chapter is divided into eight sections, the next of which describes the theory behind satellite gravimetry. Following that is a summary of the GRACE mission and how hydrological information is gleaned from its gravity products. The fourth section provides examples of hydrological science enabled by GRACE. The fifth and sixth sections list the challenging aspects of GRACE derived hydrology data and how they are being overcome, including the use of data assimilation. The seventh section describes recent progress in applying GRACE for drought monitoring, including the development of new soil moisture and drought indicator products, and that is followed by a discussion of future prospects in satellite gravimetry based drought monitoring.

Rodell, Matthew↗

DIAL with heterodyne detection including speckle noise: Aircraft/shuttle measurements of O3, H2O, and NH3 with pulsed tunable CO2 lasers

Atmospheric trace constituent measurements with higher vertical resolution than attainable with passive radiometers are discussed. Infrared differential absorption lidar (DIAL), which depends on Mie scattering from aerosols, has special advantages for tropospheric and lower stratospheric applications and has great potential importance for measurements from shuttle and aircraft. Differential absorption lidar data reduction involves comparing large amplitude signals which have small differences. The accuracy of the trace constituent concentration inferred from DIAL measurements depends strongly on the errors in determining the amplitude of the signals. Thus, the commonly used SNR expression (signal divided by noise in the absence of signal) is not adequate to describe DIAL measurement accuracy and must be replaced by an expression which includes the random coherent (speckle) noise within the signal. A comprehensive DIAL computer algorithm is modified to include heterodyne detection and speckle noise. Examples for monitoring vertical distributions of O3, H2O, and NH3 using a ground-, aircraft-, or shuttle-based pulsed tunable CO2 laser DIAL system are given.

Brockman, P.↗

Virtual refrigerant charge sensing algorithm for residential CO₂ heat pumps

Natural refrigerants are increasingly adopted in next-generation heat pump systems, among which CO₂ heat pumps have attracted significant attention. However, due to their high operating pressures, the leakage risk is higher, resulting in undercharge conditions and degraded heat pump performance. Thus, developing an accurate refrigerant charge level detection technique is necessary to guarantee safe and efficient operation. Although virtual refrigerant charge (VRC) level calculation algorithms for CO₂ heat pumps exist, they typically rely on empirically selected features without a systematic selection framework, leading to multicollinearity and potential overfitting, which limit their prediction accuracy and generalizability. To address these issues, this study proposes a VRC algorithm framework with a systematic feature selection method that identifies physically meaningful and statistically significant features, and is applied using a residential CO₂ heat pump as a case study. The method is extended from previous work on conventional refrigerants to account for charge behavior in CO₂ gas coolers. The selected features include gas cooler outlet density, evaporator pressure, and superheat temperature. The results demonstrate that the proposed feature selection method significantly improves prediction accuracy compared to existing VRC approaches. A relatively small training dataset (∼30 samples) is sufficient for feature identification and model development. The developed algorithm achieves less than 3% prediction error under both undercharge and overcharge conditions, representing reductions of 46.7% and 35.3% compared to two recent reference VRC algorithms for transcritical CO₂ heat pumps reported in the literature. The proposed algorithm and feature selection method enhance leakage detection capability, facilitate the deployment of CO₂ heat pump systems, and contribute to reduced energy waste and maintenance costs.

Guo, Fangzhou [Lawrence Berkeley National Laborato↗

A Machine Learning Approach to Objective Identification of Dust in Satellite Imagery

Airborne dust has broad adverse effects on human activity, including aviation, human health, and agriculture. Remote sensing observations are used to detect dust and aerosols in the atmosphere using long established techniques. False color Red-Green-Blue (RGB) imagery using band differences sensitive to dust absorption (Dust RGB) is currently used operationally to assist forecasters and decision-makers in identifying dust at night, but there are still limitations, subjectivity, and nuances to image interpretation making night-time dust identification difficult even for experts. This study applies machine learning to the problem of night-time dust detection with a simple random forest (RF) model using Geostationary Operational Environmental Satellite-16 (GOES-16) Advanced Baseline Imager (ABI) infrared imagery, band differences sensitive to dust absorption, and Dust RGB color components as inputs to the model. The RF model achieves an Area-Under-Curve (AUC) of 0.97 with a standard deviation of 0.04 for dust cases. For images with dust present, the model correctly labels 85% of dust pixels and 99.96% of no-dust pixels for all dust images in the validation data set. The addition of a single null case to the training data set drastically reduces error in labeling no-dust pixels as dust from 45% to 14.5%. Application of the machine learning model to the April 13–14, 2019 dust event demonstrates the ability of the model to identify dust during night-time hours when visual dust detection is limited by the cooling ground surface characteristics.

dust↗

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗

The picasso map-making code: application to a simulation of the QUIJOTE northern sky survey

ABSTRACT Map-making is an important step for the data analysis of cosmic microwave background (CMB) experiments. It consists of converting the data, which are typically a long, complex, and noisy collection of measurements, into a map, which is an image of the observed sky. We present in this paper a new map-making code named picasso (Polarization and Intensity CArtographer for Scanned Sky Observations), which was implemented to construct intensity and polarization maps from the Multi Frequency Instrument (MFI) of the QUIJOTE (Q-U-I Joint TEnerife) CMB polarization experiment. picasso is based on the destriping algorithm, and is suited to address specific issues of ground-based microwave observations, with a technique that allows the fit of a template function in the time domain, during the map-making step. This paper describes the picasso code, validating it with simulations and assessing its performance. For this purpose, we produced realistic simulations of the QUIJOTE-MFI survey of the northern sky (approximately ∼20 000 deg2), and analysed the reconstructed maps with picasso, using real and harmonic space statistics. We show that, for this sky area, picasso is able to reconstruct, with high fidelity, the injected signal, recovering all the scales with ℓ > 10 in TT, EE, and BB. The signal error is better than 0.001 per cent at 20 < ℓ < 200. Finally, we validated some of the methods that will be applied to the real wide-survey data, like the detection of the CMB anisotropies via cross-correlation analyses. Despite that the implementation of picasso is specific for QUIJOTE-MFI data, it could be adapted to other experiments.

79 ASTRONOMY AND ASTROPHYSICS↗

Criticality Control Overpack Fire Testing (Phase III)

This report will describe the one test conducted during phase III of the Pipe Overpack Container (POC) test campaign, present preliminary results from these tests, and discuss implications for the Criticality Control Overpack (CCO). The goal of this test was to see if aerosol surrogate material inside the Criticality Control Container (CCC) gets released when the drum lid of the CCO comes off during a thirty-minute long, fully-engulfing, fire test. As expected from POC tests conducted in Phase I and II of this test campaign, the CCO drum lid is ejected about one minute after the drum is exposed to fully-engulfing flames. The remaining pressure inside the drum is high enough to eject the top plywood dunnage a considerable distance from the drum. Subsequently, most of the bottom plywood dunnage supporting the CCC burns off during and after the fire. High pressure buildup inside the CCC and inside two primary containers holding the surrogate powder also results in damage to the filter media of the CCC and the filter-house, thread attachment of the primary canisters. No discernable release of surrogate powder material was detected from the two primary containers when pre- and post-test average mass were compared. However, when the average masses are corrected to account for possible uncertainties in mass measurements, error overlap does not preclude the possibility that some surrogate powder mass may have been lost from these primary canisters. Still, post-test conditions of the secondary canisters enclosing these two primary canisters suggest it is very unlikely this mass loss would have escaped into the CCC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Utilization of ERTS-1 data to monitor and classify eutrophication of inland lakes

The author has identified the following significant results. Channel 7 is highly useful in surveying surface water in lakes, rivers, and large marshes. It is likely to miss detection of elliptically shaped bodies of 4 acres or less. Further, it is possible that the bodies are distorted and displaced because of lack of correction for sensor response time. These errors might not be critical because:(1) location accuracy is not essential to a surface water survey; and (2) an obviously distorted image is often not in error in excess of 5% The finding that Orchard Lake and other lakes in Oakland County have different densities in channels 4, 5, 6, and 7 is important because it implies that the lake wide water color average is different in the separate channels. Channels 6 and 7 were constant in tonal quality among all the lakes while channels 4 and 5 varied from lake to lake and in various parts of Orchard Lake. These findings are significant because it means that small inland lake color differences are recorded by the MSS even on a cloudy or hazy day. It also confirms that ERTS-1 is performing well enough to be used for correlation to ground truth and aircraft underflights.

Chase, P. E.↗

Theory of optimal weighting of data to detect climatic change

A search for climatic change predicted by climate models can easily yield unconvincing results because of 'climatic noise,' the inherent, unpredictable variability of time-average atmospheric data. A weighted average of data that maximizes the probability of detecting predicted climatic change is presented. To obtain the optimal weights, an estimate of the covariance matrix of the data from a prior data set is needed. This introduces additional sampling error into the method. This is presently taken into account. A form of the weighted average is found whose probability distribution is independent of the true (but unknown) covariance statistics of the data and of the climate model prediction.

Bell, T. L.↗