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At least 181 records · Page 10

Model Calibration in Watershed Hydrology

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

Yilmaz, Koray K.↗

Calibration Results for J-ERS-1 SAR Data Produced by the Alaska SAR Facility

The Alaska SAR Facility has been receiving and processing SAR data from the J-ERS-1 satellite since Spring 1992. Corner reflectors have been set up for J-ERS-1 SAR calibration at a site near Delta Junction, in central Alaska. Image quality and calibration analysis results from the Delta Junction site and others will be presented in this paper. The impact of the 3-bit Analog-to-Digital Converter and the automatic stepping of the gain as a function of range in the J-ERS-1 radar receiver on calibration performance has been assessed. Preliminary observations on J-ERS-1 SAR data are that the average Signal-to-Noise ratio is generally fairly low, in the range 5-6dB. Azimuth ambiguity levels are higher than preflight analysis indicated. Over land, the dynamic range in the backscatter at L-band for approximately 36 degree incidence angle is often fairly high.

Freeman, A.↗

Calibration Results for J-ERS-1 SAR Data Produced by the Alaska SAR Facility

The Alaska SAR Facility has been receiving and processing SAR data from the J-ERS-1 satellite since Spring 1992. Corner reflectors have been set up for J-ERS-1 SAR calibration at a site near Delta Junction, in central Alaska. Image quality and calibration analysis results from the Delta Junction site and others will be presented in this paper. The impact of the 3-bit Analog-to-Digital Converter and the automatic stepping of the gain as a function of range in the J-ERS-1 radar receiver on calibration performance has been assessed. Preliminary observations on J-ERS-1 SAR data are that the average Signal-to-Noise ratio is generally fairly low, in the range 5-6 dB. Azimuth ambiguity levels are higher than preflight analysis indicated. Over land, the dynamic range in the backscatter at L-band for approximately 36 degree incidence angle is often fairly high...

Freeman, A.↗

Analysis of scattering behavior and radar penetration in AIRSAR data

A technique is presented to physically characterize changes in radar backscatter with frequency in multifrequency single polarization radar images that can be used as a first step in the analysis of the data and the retrieval of geophysical parameters. The technique is automatic, relatively independent of the incidence angle, and only requires a good calibration accuracy between the different frequencies. The technique reveals large areas where scattering changes significantly with frequency and whether the surface has the characteristics of a smooth, slightly rough, rough, or very rough surface.

Rignot, Eric↗

Cryogenic probe station for use in automated microwave and noise figure measurements

A cryogenic measurement system capable of performing on-wafer RF testing of semiconductor devices and circuits has been developed. This 'CryoProbe Station' can wafer-probe devices and circuits at cryogenic temperatures, thus eliminating the need for wire bonds. The system operates under vacuum created by a sorption pump. It uses an open cycle cooling system that can be cooled with either liquid nitrogen or liquid helium. Presently, it can reach temperatures, as low as 80 K and 37 K for each of the coolants, respectively. The temperature can be raised using a heater and it is stabilized to within 0.2 K by use of a temperature controller. The CryoProbe Station features a 1 by 2 inch stage that can hold large circuits and calibration standards simultaneously. The system is used with a Hewlett Packard 8510C Automatic Network Analyzer (ANA) to obtain S-parameter data over the frequency range 0.045-26.5 GHz. S-parameter data on HEMT (high electron mobility transistors) devices has been obtained with this station. With the use of DEEMBED software from NIST, detailed transmission line studies have been performed. Although the CryoProbe Station is designed for frequencies up to 26.5 GHz, useful transmission line data has been obtained for frequencies as high as 40 GHz. The CryoProbe station has also been used with the ATN noise figure measurement system to perform automatic, temperature dependent noise figure measurements.

Taub, Susan R.↗

Adaptive Modeling of the International Space Station Electrical Power System

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thomas, Justin Ray↗

Cross-Calibration of GNC and OLA LIDAR Systems Onboard OSIRIS-REx

The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) mission carried two distinct light detection and ranging (LIDAR) systems: A scanning LIDAR called OSIRIS-REx Laser Altimeter (OLA) as part of the science payload, and a flash LIDAR system has part of the Guidance, Navigation, & Control (GNC) subsystem to serve as a navigation sensor during TAG. This presents a unique opportunity to compare the performance of the two LIDAR systems in close proximity to a small asteroid body. During the Orbital B mission phase, between June to August 2019, the OSIRIS-REx spacecraft orbited Bennu in a near-circular terminator orbit during which the altitude above the surface varied between 645 m to 740 m. Over five-week period observations were recorded with the OLA instrument that were subsequently used to construct a global digital terrain map (DTM) with a resolution of 5 cm and accuracy of ±20 cm. This model provides an excellent reference for assessing the performance of the GNC LIDAR system. Two different GNC LIDAR checkout activities were also conducted during the Orbital B phase: A limb-crossing check-out featured a series of slews to collect GNC LIDAR data across varying ranges and phase angles and operate the automatic gain control modes of the device; An OLA-GNC LIDAR cross calibration was designed to collect data from both the OLA and GNC LIDAR devices with overlapping footprints while the spacecraft was pointed nadir. This paper compares the on-orbit performance observed during the cross-calibration activity. The OLA-based global DTM and point clouds are used to evaluate the GNC LIDAR not available during previous analysis. The GNC LIDAR measurements were found to be well within accuracy and precision specified for the instrument, but much noisier than the measurements from OLA within this operating regime.

Jason M Leonard↗

Tracking Retreat of the North Seasonal Ice Cap on Mars: Results from the THEMIS Investigation

The CO2 ice caps on Mars advance and retreat with the seasons. This phenomenon was first observed by Cassini and then confirmed by numerous ground based observations in 19th and 20th centuries. With the advent of the space age observations of the seasonal ice cap were done by all orbiting spacecraft starting with Mariner 7. Viking Orbiters and more recently the Mars Global Surveyor (particularly Mars Orbiter Camera (MOC) and Thermal Emission Spectrometer (TES) instruments) have accumulated significant data on the retreat of the CO2 seasonal cap. During Mars year 2 of THEMIS operations at Mars, we planned an observational campaign in which the THEMIS instrument (onboard the Mars Odyssey spacecraft) repeatedly observed the north seasonal polar cap from midwinter to late spring. THEMIS allows simultaneous observations in both Thermal IR (12.57 m) and Visible wavelengths (0.65 m). One of the goals for this work is to initiate an interannual program for observations of the seasonal ice caps using the THEMIS instrument. The most efficient way to detect the edge between frost and bare ground is directly onboard of the spacecraft. Prior to onboard software design effort, we have developed two groundbased algorithms for automatically finding the edge of the seasonal polar cap in THEMIS IR data. The first algorithm relies on fully calibrated data and can be used for highly reliable groundbased analyses. The second method was specifically developed for processing raw, uncalibrated data in a highly efficient way. It has the potential to enable automatic, onboard detections of the seasonal cap retreat. We have experimentally confirmed that both methods produce similar results, and we have validated both methods against a model constructed from the MGS TES data from the same season.

Ivanov, A. B.↗

GC/MS Method Development for Separating Lunar Volatile Ice Simulant Headspace Gases

Various investigators propose the lunar surface contains widely distributed volatiles, especially water- like species, i.e. OH and H2O. Surface volatiles are theorized to exist as a hydrated regolith layer, concentrated in extremely cold polar permanently shadowed regions (PSR), and/or solar wind implantation reservoirs in lunar glasses. The proposed sources of lunar surface volatiles range from cometary impacts, solar wind, or a supply present during moon formation. Future Artemis missions aim to collect and return the samples containing volatiles collected near lunar polar craters or PSRs. We, as advanced curation scientists, are responsible for developing techniques and methodologies for preserving returned sample integrity as much as possible. Pristine volatile-bearing samples are invaluable to the scientific community seeking to unravel the history of the solar system. Realistically, a sample will experience alteration during collection, transportation back to earth, and storage. The Planetary Exploration and Astromaterials Research Lab (PEARL) seeks to understand temperature and pressure effects on high-fidelity volatile-containing regolith simulants, the foundation for the future of cold curation. This abstract outlines the separation, identification, and quantification of headspace gases over volatile ice feed stock material using gas chromatography/mass spectrometry (GC/MS). Preliminary objectives concentrated on sample handling, reproducibility, and understanding the elution characteristics for each analyte. Initial GC/MS method development experiments utilized diluted static headspace sample preparation. Diluted samples were used because sampling headspace gases directly from a vial containing liquid analyte resulted in overloading of the column and detector. Overloading is evident based on chromatogram peak shapes and instrument contamination, or carry over, between experiments. A mixture of three alcohols were used for a majority of the sample handling and reproducibility studies. Reproducibility was tested via multiple users, calibration curves, and check standards. Stock solutions of condensed lunar volatile analytes included methanol, ammonia in methanol, hydrogen sulfide in water, and an equal volume mixture of methanol, ethanol, and isopropanol. Current samples use room air as the headspace sample matrix, however future experiments will incorporate an inert purge gas, such as argon or nitrogen. Three mL of each analyte solution were capped in separate 20 mL crimp top GC vials. Dilutions were carried out by removing an aliquot of headspace gases with a calibrated 1 mL gastight syringe and immediately transferring to a 20 mL capped crimp top vial. The GC/MS is a Thermo Fisher Trace 1310/ISQ 7000 with a TriPlus RSH autosampler and split/splitless injector module. The experiments outlined in this abstract use the following hardware: a 2.5 mL gastight headspace syringe tool, 1 mm ID x 78.5 mm length ultra-inert straight injection liner, and a TG-BondQ 30 m × 0.32 mm × 10 μm column. Various parameters, such as hardware selection and the temperature, pressure, and split ratio set points, continue to evolve as the overall experiment is refined. Diluted headspace chromatograms were collected for the individual stock solutions. Retention times, peak shapes, and mass spectra were evaluated and added to the data processing method for each molecule of interest. Figure 1 shows the total ion chromatograms for the three major lunar volatile simulant stock solutions: methanol, 7 N ammonia in methanol, and 0.4% hydrogen sulfide in water. Tailing peak shapes for ammonia (2.98 min rt) and water (4.06 min rt) indicate the molecules are not properly eluting from the selected column with the current separation method. Additionally, hydrogen sulfide and ammonia have overlapping peak windows, which could impact quantification. Ongoing experiments aim to address the peak shape and overlapping via the separation method and hardware selection. Sample preparation reproducibility experiments used stock solution containing equal volumes of a non- interactive mixture of methanol, ethanol, and isopropanol. Mass spectrum ion traces were used to identify and quantify all three alcohols. Peaks were automatically detected, identified, and integrated through the mass spectra detection and processing parameters. Calibration response curves and check standards were used to evaluate the validity of the sample preparation procedure. Figure 2 shows the methanol chromatogram peak area versus total headspace dilution volume transferred from the alcohol mixture vial. The calibration response curves and check standards validate sample preparation procedure. Continuing data analysis efforts are working towards correlating the peak area and instrument response factor to the headspace analyte concentration and condensed phase composition. Static headspace gas chromatography theory relies on Dalton’s law, Raoult’s law, Henry’s Law, and the Kolb and Ettre equation to associate peak area to the analyte composition in a non-ideal solution. Equation 1 is a simplified expression derived from the aforementioned theories. Future experiments involve liquid injections of the individual stock solutions, liquid and headspace analysis of various stock solution combinations, and the addition of regolith simulants to the mixtures. Temperature is another variable expected to affect reaction rates and will be explored.

Cecilia L. Amick↗

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

59 BASIC BIOLOGICAL SCIENCES↗

Self-calibrating models for dynamic monitoring and diagnosis

The present goal in qualitative reasoning is to develop methods for automatically building qualitative and semiquantitative models of dynamic systems and to use them for monitoring and fault diagnosis. The qualitative approach to modeling provides a guarantee of coverage while our semiquantitative methods support convergence toward a numerical model as observations are accumulated. We have developed and applied methods for automatic creation of qualitative models, developed two methods for obtaining tractable results on problems that were previously intractable for qualitative simulation, and developed more powerful methods for learning semiquantitative models from observations and deriving semiquantitative predictions from them. With these advances, qualitative reasoning comes significantly closer to realizing its aims as a practical engineering method.

Kuipers, Benjamin↗

Design and analysis of an automatic method of measuring silicon-controlled-rectifier holding current

The design of an automated SCR holding-current measurement system is described. The circuits used in the measurement system were designed to meet the major requirements of automatic data acquisition, reliability, and repeatability. Performance data are presented and compared with calibration data. The data verified the accuracy of the measurement system. Data taken over a 48-hr period showed that the measurement system operated satisfactorily and met all the design requirements.

Maslowski, E. A.↗

On The Processing of Log Files for Monitoring Antenna Health

In order to improve the quality of geodetic results, we have developed an infrastructure for timely processing of telemetry from IVS observing stations. We check every hour for new log files with telemetry from both VLBI observing sessions, single dish experiments, and stow-in data collection and automatically process them. The telemetry data we use is the system temperature, phase calibration phases and amplitudes, system equivalent flux density, and the differences between formatter clock and GPS clock. For the system temperature and phase calibration, processing includes filtering out outliers and computing averages and rms of the scatter in each scan. Furthermore, for the phase calibration we also compute the group delay and detect spurious signals. Cleaned and post-processed telemetry is archived. Our process detects abnormalities, such as, anomalously high system temperature, unstable phase calibration phases, jumps in the GPS and formatter clock differences, and others. With our procedure, the latency of detection of station abnormalities is reduced to less than two hours. Early detection of abnormalities reduces the amount of affected data since station personnel get early alerts. We discuss our experience of running this system since 2022.

Phase Calibration↗

On The Processing of Log Files for Monitoring Antenna Health

In order to improve the quality of geodetic results, we have developed an infrastructure for timely processing of telemetry from IVS observing stations. We check every hour for new log files with telemetry from both VLBI observing sessions, single dish experiments, and stow-in data collection and automatically process them. The telemetry data we use is the system temperature, phase calibration phases and amplitudes, system equivalent flux density, and the differences between formatter clock and GPS clock. For the system temperature and phase calibration, processing includes filtering out outliers and computing averages and rms of the scatter in each scan. Furthermore, for the phase calibration we also compute the group delay and detect spurious signals. Cleaned and post-processed telemetry is archived. Our process detects abnormalities, such as, anomalously high system temperature, unstable phase calibration phases, jumps in the GPS and formatter clock differences, and others. With our procedure, the latency of detection of station abnormalities is reduced to less than two hours. Early detection of abnormalities reduces the amount of affected data since station personnel get early alerts. We discuss our experience of running this system since 2022.

VLBI↗

A Pulse Generation Framework with Augmented Program-aware Basis Gates and Criticality Analysis

Near-term intermediate scale quantum (NISQ) de- vices are subject to considerable noise and short coherence time. Consequently, it is critical to minimize circuit execution latency. Traditionally, each basis gate of a transpiled circuit is decoded into a fixed episode of the device control pulses. Recently, people started to investigate merged pulse generation for customized gates through quantum optimal control (QOC). However, existing QOC approaches face the challenges of (i) restricted search space due to prohibitive compilation overhead; (ii) suboptimal end-to-end performance due to aggressive local optimization and falsely introduced dependency among the customized gates; (iii) inadequate adaptivity towards system calibration, which is critical for NISQ devices. In this work, we propose PAQOC, a novel QOC framework that can (i) automatically detect frequently encountered gate patterns in the logical circuit by modeling the problem as a subgraph mining process and reuse these patterns to enable much larger search space exploration (i.e., program aware); (ii) systemically construct customized gate-set based on the impact to the overall program latency (i.e., criticality-aware); and (iii) quickly adapt to system re-calibration thanks to the small-scale pattern-based gate generation (i.e., adaptivity-aware). PAQOC achieves a good tradeoff between circuit performance and compilation time, allowing fully automatic, single stop, ad- hoc customized pulse generation for more efficient execution of user programs on NISQ devices. Evaluations using fifteen applications show that PAQOC can achieve on average 1.95× speedup of the circuit latency and achieve on average 36.7% reduction in compilation overhead. With PAQOC, circuits can run faster with reduced noise, allowing deeper circuits to be tested within the coherence time of present NISQ platforms.

Chen, Yanhao↗

Magnitude calibration of a fixed head star tracker using Astro-1 flight data

The Astro-1 UV astronomy mission was hampered by the failures of the automatic star acquisition procedure. The acquisition procedure depended on the Instrument Pointing Subsystem's Fixed Head Star Trackers (FHST) to acquire, track and identify guidestars of known visual magnitude. During the Astro-1 mission it was suspected that the star magnitudes measured by the FHST were much lower than predicted. A postflight investigation of the Astro-1 flight data confirmed and quantified this suspicion. Star magnitude calibration curves computed from the flight data depict the variance from the preflight calibration curves. These results are helping engineers to plan improvements to the acquisition procedure for the upcoming Astro-2 mission.

Rakoczy, John M.↗

Rapid and precise measurement of flatband voltage

The paper outlines the design, principles of operation, and calibration of a five-IC network intended to give a rapid, precise, and automatic determination of the flatband voltage of MOS capacitors. The basic principle of measurement is to compare the analog output voltage of a capacitance meter - which is directly proportional to the capacitance being measured - with a preset or dialed-in voltage proportional to the calculated flatband capacitance by means of a comparator circuit. The bias to the MOS capacitor supplied through the capacitance meter is provided by a ramp voltage going from a negative toward a positive voltage level and vice versa. The network employs two monostable multivibrators for reading and recording the flatband voltage and for resetting the initial conditions and restarting the ramp. The flatband voltage can be held and read on a digital voltmeter.

Li, S. P.↗

Systems Analyze Water Quality in Real Time

A water analyzer developed under Small Business Innovation Research (SBIR) contracts with Kennedy Space Center now monitors treatment processes at water and wastewater facilities around the world. Originally designed to provide real-time detection of nutrient levels in hydroponic solutions for growing plants in space, the ChemScan analyzer, produced by ASA Analytics Inc., of Waukesha, Wisconsin, utilizes spectrometry and chemometric algorithms to automatically analyze multiple parameters in the water treatment process with little need for maintenance, calibration, or operator intervention. The company has experienced a compound annual growth rate of 40 percent over its 15-year history as a direct result of the technology's success.

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