A Robust Spatial Acquisition Algorithm for Extended Source Using Subpixel Image Scanning
Extended source spatial acquisition is a critical technology for deep space optical communications.
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Extended source spatial acquisition is a critical technology for deep space optical communications.
Within almost all space-geodetic techniques, contributions of different analysis centers (ACs) are combined in order to improve the robustness of the final product. So far, the contributing series are assumed to be independent as each AC processes the observations in different ways. However, the series cannot be completely independent as each analyst uses the same set of original observations and many applied models are subject to conventions used by each AC. In this paper, it is shown that neglecting correlations between the contributing series yields too optimistic formal errors and small, but insignificant, errors in the estimated parameters derived from the adjustment of the combined solution.
We are developing a concept for a compact, low-mass, low-power, mid-infrared (MIR; 5- 12 microns) imaging heterodyne spectrometer that incorporates fiber optic coupling, Quantum Cascade Laser (QCL) local oscillator, photomixer array, and Radio Frequency Software Defined Readout (RFSDR) for spectral analysis. Planetary Decadal Surveys have highlighted the need for miniaturized, robust, low-mass, and minimal power remote sensing technologies for flight missions. The drive for miniaturization of remote sensing spectroscopy and radiometry techniques has been a continuing process. The advent of MIR fibers, and MEMS techniques for producing waveguides has proven to be an important recent advancement for miniaturization of infrared spectrometers. In conjunction with well-established photonics techniques, the miniaturization of spectrometers is transitioning from classic free space optical systems to waveguide/fiber-based structures for light transport and producing interference effects. By their very nature, these new devices are compact and lightweight. Mercury-Cadmium-Telluride (MCT) and Quantum Well Infrared Photodiodes (QWIP) arrays for heterodyne applications are also being developed. Bulky electronics is another barrier that precluded the extension of heterodyne systems into imaging applications, and our RFSDR will address this aspect.
This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional reflectance distribution function (BRDF), spectral surface albedo and bidirectional reflectance factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16 days of MODIS data gridded to 1 km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free MODIS top of atmosphere (TOA) reflectance data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the MODIS operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of reflectance in the Red and NIR bands during the accumulation period. To adjust for the reflectance variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of MODIS data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized reflectance stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing MODIS data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional MODIS products.
Pluto, its large satellite Charon, and its four known satellites represent the first trans-Neptunian Kuiper Belt objects populating the outer-most solar system beyond the gas giant planets to be studied in detail from a spacecraft (New Horizons). A complete picture of the solar nebula, and solar system formation cannot be confidently formulated until representatives of this group of bodies at the edge of solar space have been examined. The Pluto system is composed of unique lunar- and intermediate-sized objects that can tell us much about how objects with volatile icy compositions evolve. Modeling of the interior suggests that geologic activity may have been to some degree, and observations of frost on the surface could imply the need for a geologic reservoir for the replenishment of these phases. However, the putative indicators of Pluto's geologic history are inconclusive and unspecific. Detailed examination of Pluto's geologic record is the only plausible means of bridging the gap between theory and observations. In this talk I will examine the potential importance of these tentative indications of geologic activity and how specific spacecraft observations have been designed and used to constrain the Pluto system's geologic history. The cameras of New Horizons will provide robust data sets that should be immanently amenable to geological analysis of the Pluto System's landscapes. In this talk, we begin with a brief discussion of the planned observations by New Horizons' cameras that will bear most directly on geological interpretability. Then I will broadly review major geological processes that could potentially operate of the surfaces of Pluto and its moons. I will first survey exogenic processes (i.e., those for which energy for surface modification is supplied externally to the planetary surface): impact cratering, sedimentary processes (including volatile migration) and the work of wind. I will conclude with an assessment of prospects for endogenic activity in the form of tectonics and cryo-volcanism.
The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system exergy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modelling, System Robustness, and Value Modelling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.
The NASA Systems Engineering Research Consortium was formed at the end of 2010 to study the approaches to producing elegant systems on a consistent basis. This has been a transformative study looking at the engineering and organizational basis of systems engineering. The consortium has engaged in a variety of research topics to determine the path to elegant systems. In the second year of the consortium, a systems engineering framework emerged which structured the approach to systems engineering and guided our research. This led in the third year to set of systems engineering postulates that the consortium is continuing to refine. The consortium has conducted several research projects that have contributed significantly to the understanding of systems engineering. The consortium has surveyed the application of the NASA 17 systems engineering processes, explored the physics and statistics of systems integration, and considered organizational aspects of systems engineering discipline integration. The systems integration methods have included system energy analysis, Akaike Information Criteria (AIC), State Variable Analysis, Multidisciplinary Coupling Analysis (MCA), Multidisciplinary Design Optimization (MDO), System Cost Modeling, System Robustness, and Value Modeling. Organizational studies have included the variability of processes in change evaluations, margin management within the organization, information theory of board structures, social categorization of unintended consequences, and initial looks at applying cognitive science to systems engineering. Consortium members have also studied the bidirectional influence of policy and law with systems engineering.
The cameras of New Horizons will provide robust data sets that should be imminently amenable to geological analysis of the Pluto systems landscapes. In this paper, we begin with a brief discussion of the planned observations by the New Horizons cameras that will bear most directly on geological interpretability. Then we broadly review the major geological processes that could potentially operate on the surfaces of Pluto and its major moon Charon. We first survey exogenic processes (i.e. those for which energy for surface modification is supplied externally to the planetary surface): impact cratering, sedimentary processes (including volatile migration), and the work of wind. We conclude with an assessment of the prospects for endogenic activity in the form of tectonics and cryovolcanism.
Satellite, reanalysis, and ocean in situ data are analyzed to evaluate regional, hemispheric and global mean trends in Earth’s energy fluxes during the first twenty years of the 21st century. Regional trends in net top-of-atmosphere (TOA) radiation from the Clouds and the Earth’s Radiant Energy System (CERES), ECMWF Reanalysis 5 (ERA5), and a model similar to ERA5 with prescribed sea surface temperature (SST) and sea ice differ markedly, particularly over the Eastern Pacific Ocean, where CERES observes large positive trends. Hemispheric and global mean net TOA flux trends for the two reanalyses are smaller than CERES, and their climatological means are half those of CERES in the southern hemisphere (SH) and more than nine times larger in the northern hemisphere (NH). The regional trend pattern of the divergence of total atmospheric energy transport (TEDIV) over ocean determined using ERA5 analyzed fields is similar to that inferred from the difference between TOA and surface fluxes from ERA5 short-term forecasts. There is also agreement in the trend pattern over ocean for surface fluxes inferred as a residual between CERES net TOA flux and ERA5 analysis TEDIV and surface fluxes obtained directly from ERA5 forecasts. Robust trends are observed over the Gulf Stream associated with enhanced surface-to-atmosphere transfer of heat. Within the ocean, larger trends in ocean heating rate are found in the NH than the SH after 2005, but the magnitude of the trend varies greatly among datasets.
We assessed the integrated safety, health, and performance risk to crews on long-duration missions, specifically to Mars. Using a systems approach rather than one focused on individual countermeasures, we examined the trade space around several such risks to identify high-potential risk mitigation strategies and characterize aspects of Mars mission architectures that could lower aggregated risk. Current Mars Design Reference missions would require durations well over two years and would increase crew exposure to radiation and microgravity well beyond ISS levels, likely resulting in significantly reduced performance beyond our current capability to mitigate that could jeopardize mission success. A “fast Mars transit” round-trip mission concept was studied using an innovative flight dynamics approach to quantify the minimum total mission energy required for a Mars transit with total mission duration less than 400 days. This approach holds promise for sending humans to Mars and returning them safely with acceptable, potentially mitigatable, exposure to microgravity and radiation using current or near-term technologies. The fast transit concept would also result in fewer time-driven vehicle failures and enable sustainable deployment of humans and infrastructure to Mars on a regular cadence, allowing steady exploration and colonization of Mars. Finally, we conclude that reliance on the Low Earth Orbit (LEO) mission operations paradigm – i.e., one of near-complete real-time dependence on experts at Mission Control to manage the combined state of the mission, vehicle, and crew – is high risk given the communication delays and limited resupply of any Mars mission, and this risk is not eliminated by the shorter missions durations of fast transit scenarios. Based on historical trends, it is highly likely that the crew will face a high-consequence problem of uncertain origin during Mars transit when ground support will be greatly reduced. While it may be possible to reduce anomaly rates through improved reliability analysis and testing, and to reduce anomaly impacts through added robustness, such mitigations address only known failure modes and known uncertainties. Therefore, a radical shift in the Human-Systems Integration Architecture (HSIA) that defines the operational paradigm, systems design, and human-systems interactions is required to improve the risk posture to an acceptable level regardless of mission duration.
NOvA is a long-baseline neutrino oscillation experiment with two functionally identical detectors: a Near Detector (ND) at Fermilab, placed 1 km from the neutrino source, and a Far Detector (FD) located 810 km away from the ND in Minnesota. NOvA s primary physics goals are to measure the neutrino oscillation parameters $\theta_{23}$ and $\Delta m^2_{32}$ with high precision, determine the neutrino mass hierarchy, and constrain the value of $\delta_{CP}$, primarily via the study of muon neutrino to electron neutrino oscillation. Extracting values for oscillation parameters from fits to data usually relies on treating systematic uncertainties as nuisance parameters, a strategy that suffers from poor scalability as the number of uncertainties becomes larger. This work introduces PISCES (Parameter Inference with Systematic Covariance and Exact Statistics), a novel method that circumvents this scalability problem by encoding systematic uncertainties into a covariance matrix. PISCES utilizes a nested minimization in which optimal systematic pulls are first computed using the covariance matrix in an inner minimization step, then the oscillation parameters are profiled over in the outer minimization. PISCES also uses a Poisson Likelihood term, making it ideal for the inclusion of low-statistic samples in the fits. PISCES is a flexible framework that also supports complex fits, such as a joint Near and Far detector fit. In the standard NOvA analysis, oscillation parameters are extracted using an extrapolation technique in which the ND data indirectly constrain the FD prediction via a ratio method. PISCES, on the other hand, enables a simultaneous ND+FD fit, allowing the high-statistics ND data to directly constrain systematic uncertainties across all samples. This thesis presents the full PISCES joint ND+FD fit for the NOvA three-flavor analysis, details its implementation, and evaluates its performance through extensive robustness tests and fake data studies. It also provides a comparison between the PISCES joint ND+FD results and the standard NOvA extrapolation method using the full NOvA 10-year data set. The results demonstrate that PISCES can successfully fit NOvA data while incorporating the constraints from the ND detectors consistently, using physically motivated systematic uncertainties to account for data/MC discrepancies.
We present cosmological constraints from the Dark Energy Survey Year 3 (DES Y3) weak lensing data using hierarchical hybrid statistics within a Bayesian simulation-based inference framework that is based on the Gower Street simulations. To maximize the precision of the inference, we have developed a new, information-theory based, data compression of the weak lensing maps to just seven highly informative summary statistics. The hybrid scheme exploits the high information content of the power spectrum, compressing both the power spectrum and neural-based summaries that are designed to extract further information. Our simulation-based approach enables principled forward modelling of all major sources of systematic uncertainty and survey properties into realistic mock observations, including the survey mask, photometric redshift uncertainties, intrinsic galaxy alignments, multiplicative shear calibration bias, source galaxy clustering, non-Gaussian shape noise, and non-linear structure formation. The summary statistics are then used in a Bayesian simulation-based inference pipeline. The inference is validated through coverage tests and checks for robustness against baryonic feedback. Assuming a $w$CDM cosmology, our analysis yields $S_8 = 0.808 \pm 0.017$, $Ω_{\rm m} = 0.325 \pm 0.024$, and $w < -0.766$ (marginalized posterior 68 per cent credible intervals). This rigorous combination of information theory, physics- and neural network-based extreme data compression, and principled Bayesian analysis improves the figure of merit for $(Ω_{\rm m}, S_8, w)$ by 60 per cent over the previous state-of-the-art, and by almost a factor of 3 over two-point analyses of the same data. They are the most precise joint constraints on $(Ω_{\rm m}, S_8, w)$ from weak gravitational lensing data alone of any survey to date. We intend to apply this analysis to the more recent DES Y6 data.
T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has a variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.
Multi-scale coupling has increasingly drawn attention as a promising approach for modeling thermal systems. Traditional system codes provide fast and robust predictions at the plant scale, while high-fidelity computational fluid dynamics (CFD)-based tools resolve localized flow and heat transfer phenomena with greater accuracy. By combining these complementary strengths, co-simulations enable multi-scale analysis that would otherwise be computationally prohibitive for a standalone CFD code. Here, this work introduces a robust and problem-agnostic domain overlapping (DO) coupling between the system thermal-hydraulic (STH) code System Analysis Module (SAM) and the coarse-mesh CFD code Pronghorn. Both applications belong to the Comprehensive Reactor Analysis Bundle (BlueCRAB) code suite, a code suite in active development at the Idaho National Laboratory (INL), tailored for multi-physics analysis of advanced reactors. Unlike previous approaches, BlueCRAB supports an agnostic interface between codes based on different fidelity, while its coupling formulation can address arbitrary flow geometries with multiple inlets and outlets in coupled components. The implemented method leads to consistent pressure drops, enthalpies, and scalar concentrations between coupled SAM and Pronghorn simulations. The methodology is demonstrated through two verification tests, which ensure the numerical consistency and conservation across the codes, and through one validation test against experimental data. The proposed problems explore different physical aspects inherent to thermal systems, with particular attention given to nuclear reactor analysis. These include buoyancy-driven flows, complex flow patterns, and setups with multiple inlets and outlets, representing challenges in advanced reactor applications.
This work proposes a power control strategy based on the linear quadratic regulator with optimal reference tracking (LQR-ORT) for a three-phase inverter-based generator (IBG) using an LCL filter. The use of an LQR-ORT controller increases robustness margins and reduces the quadratic value of the power error and control inputs during transient response. A model in a synchronous reference frame that integrates power sharing and voltage–current (V–I) dynamics is also proposed. This model allows for analyzing closed-loop eigenvalue location and robustness margins. The proposed controller was compared against a classical droop approach using proportional-resonant controllers for the inner loops. Mathematical analysis and hardware-in-the-loop (HIL) experiments under variations in the LCL filter components demonstrate fulfillment of robustness and performance bounds of the LQR-ORT controller. Experimental results demonstrate accuracy of the proposed model and the effectiveness of the LQR-ORT controller in improving transient response, robustness, and power decoupling.
Biomass-derived streams that contain acidic compounds from the degradation of lignin and polysaccharides (e.g. black liquor, pyrolysis oil, pyrolytic lignin, etc.) are chemically complex solutions prone to instability and degradation during analysis, making quantification of compounds within them challenging. Here we present a robust analytical method to quantify acidic compounds in complex biomass-derived mixtures using ion exchange, sample reconstitution in pyridine and derivatization with BSTFA. The procedure is based on an earlier method originally reported for kraft black liquors and, in this work, is applied to identify and quantify a large slate of acidic compounds in corn stover derived alkaline pretreatment liquor (APL) as a function of pretreatment severity. Analysis of the samples is conducted with GCxGC-TOFMS to achieve good resolution of the components within the complex mixture. The results reveal the dominant low molecular weight components and their concentrations as a function of pretreatment severity. Application of this method is also demonstrated in the context of lignin conversion technologies by applying it to track the microbial conversion of an APL substrate. Here as well excellent results are achieved, and the appearance and disappearance of compounds is observed in agreement with the known metabolic pathways of two bacteria, indicating the sample integrity was maintained throughout analysis. Finally, it is shown that this method applies more generally to lignin-rich materials by demonstrating its usefulness in analysis of pyrolysis oil and pyrolytic lignin.
Glycoproteins plays key roles in various cellular functions such as protein folding, protein targeting, receptor function, cell–cell recognition, protein stability, signaling, and other cellular functions. Currently a comprehensive and universal tool for the automated analysis of glycopeptides through their tandem mass spectrometry and data processing is a tedious process. We recently developed a method, Tool for Rapid Analysis of glycopeptide by Permethylation (TRAP), that simplifies glycoprotein analysis by integrating glycan sequencing and glycopeptide analysis in a single experiment. We employed this approach for the detailed analysis of glycosidic linkages, composition, glycan sequencing, glycosylation site mapping and sequencing of peptide moiety of glycopeptides of glycoproteins from both prokaryotes and eukaryotes. Here we are presenting an easy to use, robust, suitable for large as well as small sample sets and also cost‐effective glycoprotein analysis tool through TRAP approach. A permethylation protocol which can be automated and suitable for reliable permethylation of glycopeptides from the protease digest of glycoproteins was developed. Initial studies on glycopeptides from a model glycoprotein bovine RNAse B indicates that improved sensitivity and throughput of permethylation reactions can be achieved in conducting the reaction in microscale. This approach would enable convenient, rapid, and reliable high‐throughput screening of protein glycosylation and can be employed as a cost‐effective kit for glycosylated biomarker discoveries. In order to improvise the comprehensive glycosylation analysis and throughput, we have also developed an LC‐MS/MS platform for the analysis of glycopeptides processed through TRAP. We have conducted the analysis of standard glycoproteins such as bovine RNase B, human transferrin, and bovine fetuin and our preliminary results indicate that TRAP hyphened with LC‐MS/MS enables characterization of isomers of each glycoform at each glycosylation sites of complex glycoprotein mixtures. Support or Funding Information This research was supported by the National Institutes of Health (NIH) funded research, Grant R21GM122633; resource for biomedical glycomics, Grant P41GM103490; instrument grant, Grant S10OD018530; and U.S. Department of Energy grant, Grant DE‐SC0015662, to the Complex Carbohydrate Research Center. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
Robust design of forming processes using numerical simulations is gaining attention throughout the industry. In this work, it is demonstrated how robust optimization can assist in further stretching the limits of metal forming processes. A deterministic and a robust optimization study are performed, considering a stretch-drawing process of a hemispherical cup product. For the robust optimization study, both the effect of material and process scatter are taken into account. For quantifying the material scatter, samples of 41 coils of a drawing quality forming steel have been collected. The stochastic material behavior is obtained by a hybrid approach, combining mechanical testing and texture analysis, and efficiently implemented in a metamodel based optimization strategy. The deterministic and robust optimization results are subsequently presented and compared, demonstrating an increased process robustness and decreased number of product rejects by application of the robust optimization approach.