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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Search for additional heavy neutral Higgs and gauge bosons in the ditau final state produced in 36 fb –1 of pp collisions at $ \sqrt{s}=13 $ TeV with the ATLAS detector

Here, a search for heavy neutral Higgs bosons and Z' bosons is performed using a data sample corresponding to an integrated luminosity of 36.1 fb –1 from proton-proton collisions at √s=13 TeV recorded by the ATLAS detector at the LHC during 2015 and 2016. The heavy resonance is assumed to decay to τ + τ – with at least one tau lepton decaying to final states with hadrons and a neutrino. The search is performed in the mass range of 0.2-2.25 TeV for Higgs bosons and 0.2-4.0 TeV for Z' bosons. The data are in good agreement with the background predicted by the Standard Model. The results are interpreted in benchmark scenarios. In the context of the hMSSM scenario, the data exclude tan β > 1.0 for m A = 0.25 TeV and tan β > 42 for m A = 1.5 TeV at the 95% confidence level. For the Sequential Standard Model, Z SSM ' with m Z ' < 2.42 TeV is excluded at 95% confidence level, while Z NU ' with m Z' < 2.25 TeV is excluded for the non-universal G(221) model that exhibits enhanced couplings to third-generation fermions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1973

Geodetic analysis of Skylab altimetry preliminary data - SL/2 EREP pass 9

The author has identified the following significant results. The analysis was based on a time series intrinsic relationship between the satellite ephemeris, altimeter measured ranges, and the corresponding a priori values of subsatellite geoidal heights. Using sequential least squares processing with parameter weighting, the objective was to recover (1) the absolute geoidal heights of the subsatellite points, and (2) the associated altimeter calibration constant(s). Preliminary results from Skylab altimetry are given, using various combinations of orbit ephemeris and altimeter ranges as computed differently by NASA/JSC and NASA/Wallops. The influences of orbit accuracy, weighting functions, and a priori ground truth are described, based on the various combination solutions. It is shown that to deduce geoidal height by merely subtracting the height of the satellite from the altimeter range is inadmissible. The results of such direct subtraction can be very misleading if the orbit used is computed from data that included altimeter data used as height constraints. In view of the current state of knowledge, the use of geodetic ground truth samples as control benchmarks appears indispensable for the recovery of absolute geoidal heights with correct scale.

Mourad, A. G.↗
NASA NTRS2004

Fast-Acquisition/Weak-Signal-Tracking GPS Receiver for HEO

A report discusses the technical background and design of the Navigator Global Positioning System (GPS) receiver -- . a radiation-hardened receiver intended for use aboard spacecraft. Navigator is capable of weak signal acquisition and tracking as well as much faster acquisition of strong or weak signals with no a priori knowledge or external aiding. Weak-signal acquisition and tracking enables GPS use in high Earth orbits (HEO), and fast acquisition allows for the receiver to remain without power until needed in any orbit. Signal acquisition and signal tracking are, respectively, the processes of finding and demodulating a signal. Acquisition is the more computationally difficult process. Previous GPS receivers employ the method of sequentially searching the two-dimensional signal parameter space (code phase and Doppler). Navigator exploits properties of the Fourier transform in a massively parallel search for the GPS signal. This method results in far faster acquisition times [in the lab, 12 GPS satellites have been acquired with no a priori knowledge in a Low-Earth-Orbit (LEO) scenario in less than one second]. Modeling has shown that Navigator will be capable of acquiring signals down to 25 dB-Hz, appropriate for HEO missions. Navigator is built using the radiation-hardened ColdFire microprocessor and housing the most computationally intense functions in dedicated field-programmable gate arrays. The high performance of the algorithm and of the receiver as a whole are made possible by optimizing computational efficiency and carefully weighing tradeoffs among the sampling rate, data format, and data-path bit width.

Wintemitz, Luke↗
NASA NTRS1973

Lidar Observations of Raman Scattering from S02 in a Power Plant Stack Plume

LIDAR techniques have been successfully applied to the detection of the Raman backscatter from S02 in the plume of a 200 megawatt coal-burning electrical- generating plant from a distance of 210 meters. The LIDAR system used consists of a 61-centimeter-diameter, f /4 Newtonian telescope and a 1.0-1.5-joules per pulse, 1-pulse-per-second ruby laser. Narrow band interference filters are used to select the 7546-angstrom v (sub 1) vibrational line of S02. The signal from a photomultiplier tube was sequentially applied to each 254-nanosecond-wide channel of a 15-cihannel photon counting system, resulting in a direct correlation between channel number and range increment. Photon counts were accumulated from the backscatter of a number of laser pulses (typically 50 or 100), and the accumulated counts per channel printed on paper tape. One sequence of measurements was made during a two-hour period while the plant electrical output was being reduced by approximately 50 percent. Although the Raman system had not been quantitatively calibrated, the LIDAR data correlated well with the varying plant electrical output. N2 scattering observations were also made and an approximate quantitative S02 concentration obtained by ratioing the S02 data to N2 data. This ratio compared well to the in-situ measurements made during the same period by Environmental Protection Agency sampling instruments.

Brumfield, M. L.↗
DOE OSTI2014

PdCuAu ternary alloy membranes. Hydrogen permeation properties in the presence of H 2 S

PdCuAu ternary alloy membranes with different component compositions were synthesized by sequential electroless deposition of components onto porous stainless steel substrates. The ternary with the highest Au content, Pd 69 Cu 14 Au 17 , exhibited the highest hydrogen permeation flux, comparable to that of a Pd 91 Au 9 membrane. Upon exposure to 100 ppm H 2 S/H 2 at 673 K for 24 h, all PdCuAu membranes experienced flux reductions of ~55%, followed by recovery to ~80% of the initial hydrogen flux upon reintroduction of pure hydrogen at 400 °C. Complete flux recovery after H 2 S exposure required hydrogen treatment at 500 °C. X-ray diffraction (XRD) analysis of the H 2 S-exposed PdCuAu membranes revealed fcc alloy structure with no evidence of bulk sulfide formation. In agreement with the XRD results, sulfur was not detected in the bulk of H 2 S-exposed samples by energy dispersive spectroscopy (EDS). However, analysis of H 2 S-exposed PdCuAu alloys by X-ray photoelectron spectroscopy (XPS) depth profiling revealed low, but measureable, amounts of sulfur in the near-surface region, about 10 nm in depth. The depth profiles of samples after hydrogen recovery treatment showed significantly reduced sulfur content. Furthermore, these results indicate that H 2 S exposure causes flux loss in PdCuAu alloys through a surface-poisoning mechanism, and that the surface sulfide can be removed—and flux recovered—by high temperature treatment in hydrogen.

hydrogen separation↗
DOE OSTI2015

Radionuclide gas transport through nuclear explosion-generated fracture networks

Underground nuclear weapon testing produces radionuclide gases which may seep to the surface. Barometric pumping of gas through explosion-fractured rock is investigated using a new sequentially-coupled hydrodynamic rock damage/gas transport model. Fracture networks are produced for two rock types (granite and tuff) and three depths of burial. The fracture networks are integrated into a flow and transport numerical model driven by surface pressure signals of differing amplitude and variability. There are major differences between predictions using a realistic fracture network and prior results that used a simplified geometry. Matrix porosity and maximum fracture aperture have the greatest impact on gas breakthrough time and window of opportunity for detection, with different effects between granite and tuff simulations highlighting the importance of accurately simulating the fracture network. In particular, maximum fracture aperture has an opposite effect on tuff and granite, due to different damage patterns and their effect on the barometric pumping process. From stochastic simulations using randomly generated hydrogeologic parameters, normalized detection curves are presented to show differences in optimal sampling time for granite and tuff simulations. In conclusion, seasonal and location-based effects on breakthrough, which occur due to differences in barometric forcing, are stronger where the barometric signal is highly variable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

SU-E-J-15: Automatically Detect Patient Treatment Position and Orientation in KV Portal Images

Purpose: In the course of radiation therapy, the complex information processing workflow will Result in potential errors, such as incorrect or inaccurate patient setups. With automatic image check and patient identification, such errors could be effectively reduced. For this purpose, we developed a simple and rapid image processing method, to automatically detect the patient position and orientation in 2D portal images, so to allow automatic check of positions and orientations for patient daily RT treatments. Methods: Based on the principle of portal image formation, a set of whole body DRR images were reconstructed from multiple whole body CT volume datasets, and fused together to be used as the matching template. To identify the patient setup position and orientation shown in a 2D portal image, the 2D portal image was preprocessed (contrast enhancement, down-sampling and couch table detection), then matched to the template image so to identify the laterality (left or right), position, orientation and treatment site. Results: Five day’s clinical qualified portal images were gathered randomly, then were processed by the automatic detection and matching method without any additional information. The detection results were visually checked by physicists. 182 images were correct detection in a total of 200kV portal images. The correct rate was 91%. Conclusion: The proposed method can detect patient setup and orientation quickly and automatically. It only requires the image intensity information in KV portal images. This method can be useful in the framework of Electronic Chart Check (ECCK) to reduce the potential errors in workflow of radiation therapy and so to improve patient safety. In addition, the auto-detection results, as the patient treatment site position and patient orientation, could be useful to guide the sequential image processing procedures, e.g. verification of patient daily setup accuracy. This work was partially supported by research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Cadmium retention and distribution in contaminated soil: effects and interactions of soil properties, contamination level, aging time and in situ immobilization agents

As soil cadmium (Cd) contamination becomes a serious concern and one of the significant environmental pollution issues all over the world, knowledge of the basic chemistry, origin, inputs, sources, quantity, chemical forms, reactions, as well as the fate and transport of Cd in different types of soil is crucial for better understanding Cd bioavailability, health risks and remedial options. This study aimed to increase the current knowledge on the complex interdependence between the factors affecting behavior, transport and fate of Cd in the soil and to test and compare the performance of the stabilization agents in different soil types. Soils demonstrated various sorption affinity and capacity for Cd accumulation, which proved to be positively correlated with soil pH and the cation exchange capacity (CEC). With increasing levels of contamination, sequential extraction analysis showed the highest increase of relative Cd amounts in the exchangeable fraction regardless of the soil properties, suggesting that added Cd is principally associated with the easily accessible and mobile fraction. For different initial Cd concentrations and soil types, Cd sorption reached the quasi-equilibrium within 24 h of contact. Prolonged aging (two months) influenced the natural stabilization of Cd in all types of soil, but only at low contamination level. The application of both, conventional (slaked lime Ca(OH) 2) and alternative phosphate-rich (annealed bovine bones B 400) amendments, resulted in Cd relocation and reduction of exchangeable Cd content. Although the effect was smaller when apatite amendment was utilized, observed re-distribution of Cd to more stable soil fractions is preferable for achieving long-term stabilization. Cd concentrations extracted in exchangeable and acid soluble fractions after the treatments of contaminated soil samples suggest that the practical applicability of in situ immobilization depends on the soil properties and the level of contamination, as well as that effect, should be monitored for the possible re-mobilization of Cd. © 2019 Elsevier Inc.

02 PETROLEUM↗
DOE OSTI2021

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components. Third Annual Progress Report

Additive manufacturing (AM) of high-strength corrosion resistance alloys for nuclear energy applications, such as stainless steel and Inconel, is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Probability of crack initiation at the pore depends on size, shape, and orientation of the defect. Pulsed Infrared Thermography Imaging (PIT) provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PIT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PIT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PIT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PIT capabilities in detecting microscopic subsurface defects in metals, and classifying shapes and orientation of pores in thermal images. For detection of microscopic defects in PIT imaging data, we have developed Spatial Temporal Denoised Thermal Source Separation (STDTSS) unsupervised machine learning (ML) image processing algorithm. We show that flat bottom hole (FBH) defects as small as 200µm in SS316 and IN718 specimens, can be detected with STDTSS algorithm. To the best of our knowledge, these are the smallest detected defects which are reported in literature. For classification of defects shapes, we have previously developed thermal tomography (TT) algorithm to obtain depth reconstructions of material defects from data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2003

Towards Automating Spacecraft Attitude Sensor Calibration

With a view towards reducing cost and complexity for spacecraft early mission support at the NASA Goddard Space Flight Center (GSFC), efforts are being made to automate the attitude sensor calibration process. This paper addresses one of the major components needed by such a system. The beneficiaries of an improved calibration process are missions that demand moderate to high precision attitude knowledge or that need to perform accurate attitude slews. Improved slew accuracy reduces the time needed for re-acquisition of fine-pointing after each attitude maneuver, Rapid target acquisition can be very important for astronomical targeting or for off-nadir surface feature targeting by Earth-oriented spacecraft. The normal sequence of on-orbit calibration starts with alignment calibration of the star trackers and possibly the Sun sensor. Their relative alignment needs to be determined using a sufficiently large data set so their fields of view are adequately sampled. Next, the inertial reference unit (IRU) is calibrated for corrections to its alignment and scale factors. The IRU biases are estimated continuously by the onboard attitude control system, but the IRU alignment and scale factors are usually determined on the ground using a batch-processing method on a data set that includes several slews sufficient to give full observability of all the IRU calibration parameters. Finally, magnetometer biases, alignment, and its coupling to the magnetic torquers are determined in order io improve momentum management and occasionally for use in the attitude determination system. The detailed approach used for automating calibrations will depend on whether the automated system resides on the ground or on the spacecraft with an ultimate goal of autonomous calibration. Current efforts focus on a ground-based system driving subsystems that could run either on the ground or onboard. The distinction is that onboard calibration should process the data sequentially rather than in a single large batch since onboard computer data storage is limited. Very good batch- processing calibration utilities have been developed and used extensively at NASA/GSFC for mission support but no sequential calibration utilities are available. To meet this need, this paper presents the mathematical description of a sequential IRU calibration system. The system has been tested using flight data from the Rossi X-ray Timing Explorer (RXTE) during a series of attitude slews. The paper also discusses the current state of the overall automated system and describes plans for adding sequential alignment calibration and other additions that will reduce the amount of analyst time and input.

Sedlak, Joseph↗
DOE OSTI2016

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared imaging thermal feature porosity probability maps

We report that local thermal history can significantly vary in parts during metal Additive Manufacturing (AM), leading to local defects. However, the sequential layer-by-layer nature of AM facilitates in-situ part voxelmetric observations that can be used to detect and correct these defects for part qualification and quality control. The challenge is to relate this local radiometric data with local defect information to estimate process error likelihood in future builds. This paper uses a Short-Wave Infrared (SWIR) camera to record the temperature history for parts manufactured with Laser Powder Bed Fusion (LPBF) processes. The porosity from a cylindrical specimen is measured by ex-situ micro-computed tomography (μCT). Specimen data from the SWIR camera, combined with the μCT data, are used to generate thermal feature-based porosity probability maps. The porosity predictions made by various SWIR thermal feature-porosity probability maps of a specimen with a complex geometry are scored against the true porosity obtained via μCT. The receiver operating characteristic curves constructed from the predictions for the complex sample demonstrate the porosity probability mapping methodology’s potential for in-situ based porosity detection.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning epistatic polygenic phenotypes with Boolean interactions

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models. The epiTree pipeline first selects a set of variants derived from tissue-specific estimates of gene expression. Next, it uses iterative random forests (iRF) to search training data for candidate Boolean interactions (pairwise and higher-order). We derive significance tests for interactions, based on a stabilized likelihood ratio test, by simulating Boolean tree-structured null (no epistasis) and alternative (epistasis) distributions on hold-out test data. Finally, our pipeline computes PCS epistasis p-values that probabilisticly quantify improvement in prediction accuracy via bootstrap sampling on the test set. We validate the epiTree pipeline in two case studies using data from the UK Biobank: predicting red hair and multiple sclerosis (MS). In the case of predicting red hair, epiTree recovers known epistatic interactions surrounding MC1R and novel interactions, representing non-linearities not captured by logistic regression models. In the case of predicting MS, a more complex phenotype than red hair, epiTree rankings prioritize novel interactions surrounding HLA-DRB1 , a variant previously associated with MS in several populations. Taken together, these results highlight the potential for epiTree rankings to help reduce the design space for follow up experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Facile Separation of Sr-90, Fe-55, Nb-94, Ni-59,63 with Large Amount of Ca by Controlled pH Precipitation - 17190

it is important to manage low-and intermediate-level radioactive wastes from nuclear power plants due to a permanent disposal. According to the Nuclear Safety and Security Commission (NSSC), among all the regulatory radionuclides, a few radionuclides from the fission products and corrosion products such as Sr-90, Fe-55, Nb-94, Ni-59,63 which emit low-energy x-ray and beta radiation. Thus, it is necessary to separate beta-emitting nuclides individually. For that reason, KAERI has established analytical procedures which can separate Sr-90, Fe-55, Nb-94, Ni-59,63 from radioactive waste samples. However, when radioactive wastes contain large amount of Ca (above 300 mg), it is not easy to recover the target radionuclides because high concentration of Ca has a strong influence on the effective analyses. In order to combat this problem, there was an attempt to make the precipitate as CaF{sub 2} by using hydrofluoric acid. However, this way had a limitation; Fe-55, Nb-94 were precipitated as fluoride compounds as well as Ca. In this study, we have focused on developing a separation procedure stage by stage in the radioactive wastes with Sr-90, Fe-55, Nb-94, Ni-59,63 and large amount of Ca (1500 mg). The detailed steps are described below; (1) Separation of Fe-55, Nb-94, Ni-59,63 as metal hydroxide precipitates: low solubility product constant (Ksp) between pH 6 and pH 10. (2) Selective elimination of Ca-oxalate complex under strong acidic conditions. Consequently, all the metal sources were sequentially separated and quantitatively recovered by inductively coupled plasma atomic emission spectrometric (ICP-AES) analysis, the recovery is as follows; Sr-90 (3 mg): 89.47±5.48%, Fe-55 (20 mg): 99.80±3.19%, Nb-94 (20 mg): 97.45±2.42%, Ni-59,63 (2 mg): 83.59±15.31%, Ca (1500 mg): 85.32±6.38%, respectively. This methodology will help us separation of radioactive wastes efficiently if apply properly. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2015

Design of Lead Telluride Based Thermoelectric Materials through Incorporation of Lead Sulfide Inclusions or Ligand Stripping of Nanosized Building Blocks

Design of thermoelectric materials focuses on the optimization of several unfavorably coupled factors: electrical conductivity, Seebeck coefficient, and thermal conductivity. Recent work in thermoelectrics has focused on decreasing lattice thermal conductivity by nanostructuring thermoelectric materials, while recent work in photovoltaics has demonstrated ligand stripping as a means to increased electron mobility in thin films of nanoparticles. In the present work, these two features are combined. A multigram scale synthesis of dispersible, lead telluride nanocrystals (25–50 nm) is developed using hot-injection methods in common organic solvents. These nanocrystals (NCs) are ligand stripped with sulfide (PbTe-S) or iodide (PbTe-I) sources to result in p-type or n-type materials with large Seebeck coefficients at room temperature of 520 or –540 μV·K –1 , respectively. Sequential stripping with sulfide and then iodide (PbTe-SI) resulted in a small Seebeck due to counter doping. PbTe-S and PbTe-SI are found to generate nanostructured composites by growth of lead sulfide nanocrystals (~50–60 nm) in situ upon annealing. However, the electrical conductivities are low (<1 S·cm –1 ) due to excess doping during the ligand stripping. Intentional formation of a nanocomposite (PbTe–PbS) is achieved by combining PbTe NCs with 4–6 nm diameter lead sulfide particles via mixing by incipient wetness with a target of 8 mol % lead sulfide. The resulting nanocomposite is n-type with a Seebeck coefficient of –160 μV·K –1 and an electrical conductivity of 42 S·cm –1 at room temperature. The lattice thermal conductivities of all materials at room temperature are substantially lower than those of bulk lead telluride (2.0 W m –1 ·K –1 ). However, thermoelectric figure of merit (ZT) values are low for all samples (maximum ZT = 0.03 for PbTe–PbS), attributed primarily to the low electrical conductivities. As a result, this work underscores the importance of developing new methods for augmenting electrical conductivity if nanoparticle assemblies are to be practically employed in thermoelectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Effect of long-term irrigation patterns on phosphorus forms and distribution in the brown soil zone

Continuous application of P fertilizers under different irrigation patterns can change soil phosphorus (P) chemical behavior and increase soil P levels that are of environmental concern. To assess the effect of long-term different irrigation patterns on soil P fractions and availability, this study examined sequential changes in soil organic P and inorganic P from furrow irrigation (FI), surface drip irrigation (SUR), and subsurface drip irrigation (SDI) in the brown soil zone (0–60 cm) during 1998 to 2011. Analyses of soil P behavior showed that the levels of total P are frequently high on top soil layers. The total P (TP) contents of the entire soil profiles under three irrigation treatments were 830.2–3180.1 mg/kg. The contents of available P (AP) were 72.6–319.3 mg P/kg soil through soil profiles. The greatest TP and AP contents were obtained within the upper soil layers in FI. Results of Hedley’s P fractionation indicate that HCl-P is a dominant form and the proportion to TP ranges from 29% to 43% in all three methods. The contents of various fractions of P were positively correlated with the levels of total carbon (TC), total inorganic carbon (TIC), and calcium (Ca), whereas the P fractions had negative correlation with pH in all soil samples. Regression models proved that NaHCO 3 -P o was an important factor in determining the amount of AP in FI. H 2 O-P o , NaHCO 3 -P o , and NaOH-P i were related to available P values in SUR. NaHCO 3 -P o and NaOH-P o played important roles in SDI. The tomato yield under SUR was higher than SDI and FI. The difference of P availability was also controlled by the physicochemical soil properties under different irrigation schedule. Here, SUR was a reasonable irrigation pattern to improve the utilization efficiency of water and fertilizer.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Deep Space navigation for the BioSentinel spacecraft science orbit

BioSentinel is an astrobiology small spacecraft mission. The payload consists of two parts, the first has optical and microfluidics sensors, and the second is a Linear Energy Transfer spectrometer that has the objective to measure deep space radiation from events such as coronal mass ejections. The goal of the mission is to observe potential DNA damage due to the radiation in heliocentric space on the living organism Saccharomyces cerevisiae, which is a budding yeast. Two types of this living organism are included in the payload. The first is a natural type that is more radiation tolerant, while the second is a mutant strain that has a deficiency in a gene that allows DNA repair once damage occurs. The impact caused by the radiation on the DNA is compared to an identical sample aboard the International Space Station, as well as another identical sample at a laboratory on the ground. The BioSentinel mission consists of a 6U CubeSat currently ,as of January 2024, active in heliocentric orbit. The spacecraft was launched aboard the first SLS flight as part of the Artemis-I campaign in November 2022. After successful deployment from the launch vehicle, it performed a lunar flyby with an altitude of 406 km. The delta-V imparted by the flyby provided the necessary energy to achieve a heliocentric orbit, in an Earth-trailing pattern. The navigation analysis consisted of a Kalman-filter that utilized data from the Deep Space Network and the ESA Estrack network. All those antennas were needed since the Artemis-1 campaign included the deployment of several other cubesats, therefore the scheduling process required more antenna assets than usual due to simultaneous demands from various missions. The processed tracking data was later also refined with a smoother in order to obtain a more accurate solution. The type of tracking data included TCP, Sequential Range, Doppler and Range formats. The solar radiation pressure coefficient, as well as the delta-V from the deployment and the flyby were modeled to obtain suitable solutions that could decrease the position and velocity uncertainties at several steps along the mission concept of operations. The final product each time resulted in updated ephemeris files that were used by the mission and the antenna networks as the mission progressed. Once in the final science orbit, the utilized antennas are only from the DSN network and the data format is bounded to just TCP. Regular orbit determination is performed, every two weeks. The spacecraft is in a nominal well-known orbit, performing regular operations. This paper includes an analysis of the final science orbit, the techniques and procedures utilized to perform orbit determination and a description of the overall navigation campaign produced during the mission and, more specifically, during the final science operations in Deep Space.

BioSentinel↗
NASA NTRS2001

Tracking and Data Relay Satellite (TDRS-3) Range Biases and Momentum Unload Modeling for Terra (EOS-AMI)

The Flight Dynamics Facility (FDF) reports its performance in meeting Tracking and Data Relay Satellite (TDRS) predicted ephemeris accuracy requirements with TDRS-3. The Terra (Earth Observing System AM-1) satellite has 3-sigma TDRS requirements of 75 m for total position accuracy predicted over one day onboard. The study sample includes selected cases over 21 months after Guam Remote Ground Terminal (GRGT) support started in June 1998. For daily solutions with a 1.5-day prediction span, predicted results of the study were below the Terra requirement by at least 12 m. Refined range bias estimation and modeled momentum unloads are needed to meet Terra's requirements for TDRS-3. Maintained at 275 W longitude over the zone of exclusion, TDRS-3 is analyzed separately from other TDRSs because of its unique tracking data. Only the Bilateration Ranging Transponder (BRT) at Alice Springs (ALS), Australia, and the Telemetry, Tracking and Command (TT&C) system at Guam are used for routine operational tracking data for TDRS-3. Simultaneous batch orbit solutions with three TDRSs and either the Compton Gamma Ray Observatory (GRO) or Terra were done with the Goddard Trajectory Determination System (GTDS) to periodically refine the TT&C and BRT System (BRTS) range biases. As new biases were determined, significant changes were made in estimating the absolute position. FDF achieved similar results using a sequential filter with all operational TDRSs and four user satellites. Definitive accuracy (3-sigma) is expected to be below 50 m. The White Sands Complex (WSC) performs momentum unloads to maintain three-axis stabilized attitude of TDRSs. The relationship between velocity changes (delta-V) and reaction wheel speed changes was empirically determined for roll/yaw unloads. A theoretical relationship was verified and used for pitch unloads. Modeling both pitch and roll/yaw momentum unloads is necessary to meet the 75-m requirement. Moving the orbit solution epoch an hour before a momentum unload can improve delta-V optimization and prediction accuracy over 1.5 days.

Ward, Douglas T.↗