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NASA NTRS1973

On board satellite processing study

The use of satellite-based, world-wide data collection and location systems for scientific purposes is discussed. The configuration of satellite borne data handling equipment to prevent premature saturation and to provide maximum capacity without degradation of performance is described. An analysis of a data collection and location system based on random time and frequency access to the satellite was conducted. The subjects presented are: (1) a general description of the concept of a random access system, (2) the quantitative characteristics of random access systems, and (3) the development of a model for comparing the various types of digital communications systems.

Reed, D. L.↗

NASA NTRS1976

Classical trajectory study of internal energy distributions in unimolecular processes

Energy flow in a molecular system such as CD3Cl or CD3H representing a chemical activation experiment is studied by the method of classical trajectories. A correlation function method is used to obtain energy distributions before and after the breakup of the activated molecule. The energy distribution in the final product is found to be randomly distributed for a surface with no exit channel barrier or strong intermode couplings. Nonrandom energy distributions result when these special forces are present. Product channel barriers result in an excess of translational energy and exit channel intermode couplings result in nonrandom vibrational distributions.

Mcdonald, J. D.↗

NASA NTRS1994

Correlation of finite element free vibration predictions using random vibration test data

Finite element analysis is regularly used during the engineering cycle of mechanical systems to predict the response to static, thermal, and dynamic loads. The finite element model (FEM) used to represent the system is often correlated with physical test results to determine the validity of analytical results provided. Results from dynamic testing provide one means for performing this correlation. One of the most common methods of measuring accuracy is by classical modal testing, whereby vibratory mode shapes are compared to mode shapes provided by finite element analysis. The degree of correlation between the test and analytical mode shapes can be shown mathematically using the cross orthogonality check. A great deal of time and effort can be exhausted in generating the set of test acquired mode shapes needed for the cross orthogonality check. In most situations response data from vibration tests are digitally processed to generate the mode shapes from a combination of modal parameters, forcing functions, and recorded response data. An alternate method is proposed in which the same correlation of analytical and test acquired mode shapes can be achieved without conducting the modal survey. Instead a procedure is detailed in which a minimum of test information, specifically the acceleration response data from a random vibration test, is used to generate a set of equivalent local accelerations to be applied to the reduced analytical model at discrete points corresponding to the test measurement locations. The static solution of the analytical model then produces a set of deformations that once normalized can be used to represent the test acquired mode shapes in the cross orthogonality relation. The method proposed has been shown to provide accurate results for both a simple analytical model as well as a complex space flight structure.

Chambers, Jeffrey A.↗

DOE OSTI2019

Informative Path Planning for Mapping Radiation

This project involves making measurements of contaminated areas using portable radiation detectors and small robots. Tasks involve operating detectors and small robots, combining data acquisition for the two systems, and automating the systems. The end result is a radiation map of contamination areas. Localization of radioactive sources and mapping of contamination distribution is essential when responding to emergencies, or when dealing with cleanup efforts. Radiation maps are used for situational awareness and for establishing a safe perimeter. However, it may be hazardous or impossible for humans to safely enter the site and survey the area. Informative Path Planning (IPP) is used to design a path for a robotic sensor platform to gather the most information about the radiation distribution while operating under the set of constraints given by the dynamics of the robot and other requirements such as minimizing the overall mission time. The key challenge for IPP is the tight coupling in multiple layers of decisions: Selection of locations to visit; Allocation of sensors to those locations; Processing of information gathered. Given a robot equipped with a basic gamma detector and Lidar sensor, how can we efficiently explore an unknown environment in such a way that we can satisfy the robot's constraints while simultaneously maximizing the accuracy of the map and minimizing the total runtime? This work presents a systematic procedure for IPP and environmental mapping that: Selects the best locations at which to sample; Finds the best path for robots; Estimates the measurement value at unknown locations using a Gaussian Process regression framework. Given a set of points where radiation measurements were taken, we are utilizing a Gaussian Process Regression with a Matern kernel to reconstruct the shape of the underlying ground truth. Mapping is done via the Robot Operating System's OpenSlam Gmapping package, which creates a 2D occupancy grid map. Simulated trials were run with a radiation source placed at random locations, and allowing the robot to select and move towards 20 samples at separate locations, as well as sampling along the path while moving. The simulated sensor model assumed an efficiency of 0.3, collection time of 1 second. Various weighting schemes were tested and compared. Quantitative evaluations often favored exploitation-heavy weighting schemes where μ was emphasized, with the Root Mean Squared Error (RMSE) quickly tending towards 2, whereas qualitative comparisons would favor exploration-biased schemes with greater weight on σ. The difference comes from operators often favoring knowing the general location of a source, rather than the exact properties of a source. Weighting of the path-length π often reduced the quality of the regression as less exploration occurred, however this may be deemed a worthwhile trade-off under certain circumstances, such as with sensitive robots. Successfully developed a methodology for informative path-planning for a robot to efficiently gather information and create a map of radiation. In the future, we would like to focus on: Hardware trials with integration of the robot platform and the IPP software; More refined sensor and environmental modeling; Multiple robot platforms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Statistical analysis of spatial distribution of pores in metal additive manufacturing

We report mechanical properties of additively manufactured parts are sensitive to the presence of pores form during the manufacturing process. The impact of pores on the mechanical performance has been investigated extensively with respect to different parameters, such as pore volume fraction, shape, and size. However, statistical investigations focusing on the relationships between the spatial distribution of pores and process parameters; and consequently, the performance of the manufactured parts are scattered and limited. Also, these sparse investigations usually suffer from an ambiguous definition of terminologies. For instance, the required criteria to consider a point pattern as complete spatial randomness (CSR) are generally not clarified. Moreover, no numerical formalism is yet developed to show how much the observed spatial results are statistically significant. To address these shortcomings, the statistical definition of CSR in a point pattern and the procedure to quantitatively determine the deviation of a pattern from CSR were discussed. The explained statistical approach was used to investigate the effect of scanning speed parameter on the spatial distribution of gas pores in laser powder bed fusion manufactured stainless steel parts. Furthermore, and to highlight the impact of the spatial distribution of pores on mechanical properties, fatigue performances of parts with clustered and randomly distributed pores were simulated by finite element analysis. It is shown that by reducing the scanning speed, the spatial distribution of gas pores deviated more from CSR, and correspondingly fatigue performance deteriorated.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Analysis of an optical imaging system prototype for autonomously monitoring zooplankton in an aquaculture facility

Traditional approaches to biomonitoring in aquatic systems, such as sample collection, sorting, and identification, require significant time and effort, thereby limiting the spatiotemporal resolution of sample collection. Additionally, collection and preservation of samples for subsequent taxonomic identification and enumeration leads to mortality of organisms. Recent advances in technologies that utilize optical imaging and machine learning have provided new opportunities to expedite biomonitoring and lead to significant cost savings. These technologies can be advantageous to scientists or managers that conduct routine biomonitoring to inform operations, as in the case of aquaculture facilities. The Small Aquatic Organism optical imaging system (SAO) is a high-throughput optical imaging and classification prototype system that relies on computer vision and machine learning (Support Vector Machines, or SVMs) to autonomously identify and enumerate aquatic organisms. The SAO provides a more sustainable method of collecting large volumes of data and has the benefit of being used in situ. In this study, we tested the performance of the SAO in providing comparable results to manual zooplankton community monitoring in ten ponds at an aquaculture facility. We performed a side-by-side study comparing the sampling methods of plankton tow nets, where major zooplankton taxonomic classes were manually identified and enumerated, to sampling with the SAO. Vouchered samples were used to develop a training library for the SAO, where classes consisted of water boatman and zooplankton groups: cladocerans, copepod adults, copepod nauplii, and rotifers. SAO imagery was manually classified and compared with predicted results for validation. Accuracy for the SVM classifier of the SAO was 37.4 %. Convolutional Neural Networks (CNN) and Random Forest classifiers were also applied to SAO imagery and image features for comparison. The best CNN model and our Random Forest model had accuracies of 80.4 % and 46.6 % respectively. Challenges faced included the small size of copepod nauplii and rotifers and the limited resolution of the imaging camera, although there are tradeoffs between imaging resolution and the sample processing rate. Furthermore, our comparison shows that advancement in both optical imaging and ML are needed in order for the SAO prototype to yield comparable results to manual community monitoring in an aquaculture facility.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Cost Analysis of Complex Radiation Therapy for Patients With Head and Neck Cancer

Purpose: This cost analysis aimed to prospectively assess differences in costs between TomoTherapy and volumetric modulated arc therapy (VMAT) in patients with head and neck cancer. Methods and Materials: Economic data were gathered from a multicenter study. However, randomization was not possible due to the availability of equipment. Costs were calculated using the microcosting technique from the hospital's perspective (in 2013 euros), and the time horizon was radiation therapy. Only resources that entered the hospital production process and which were likely to vary between the strategies being compared were considered. Acute adverse events observed within the time horizon were also assessed. Results: The cost analysis was based on a total of 173 patient treatments given between 2010 and 2012 in 14 French cancer centers: 73 patients were treated with TomoTherapy, 92 with VMAT RapidArc, and 8 with VMAT SmartArc. Estimated costs of SmartArc were removed from the comparison due to the small sample size. The mean ± SD cost per patient of the treatment planning phase was €314 (±€214) for TomoTherapy and €511 (±€590) for RapidArc. Mean costs ± SD per patient of irradiation reached €3144 (±€565) for TomoTherapy and €1350 (±€299) for RapidArc. The most sensitive parameter of irradiation was the annual operating time of accelerators. Ninety-five percent confidence intervals for the mean costs of irradiation were €3016 to €3272 for TomoTherapy and €1281 to €1408 for RapidArc. The number of acute adverse events during radiation therapy was not significantly different between strategies. Conclusions: TomoTherapy appeared to be more expensive than RapidArc mainly due to the higher price of the accelerator, the higher costs of maintenance, and the longer duration of treatment sessions. Because strategies were not significantly different in clinical effect, RapidArc appeared to be the strategy to be recommended at this stage of knowledge.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2023

Meta-analysis of biogas upgrading to renewable natural gas through biological CO 2 conversion

Biogas upgrading through CO 2 conversion by hydrogenotrophic methanogenesis is receiving an increasing attention worldwide because of the demand for renewable natural gas. Herein, a holistic and statistical study of the operation conditions, driving forces, performances, and potential implementation of biogas upgrading via biological CO 2 conversion was conducted. Based on a systematic review and meta-analysis of 46 existing publications that were selected from 1475 papers, we have compiled a global dataset of CO 2 bioconversion biogas upgrading, encompassing 308 study cases. Subsequently, we employed a rigorous analytical framework incorporating data processing and mixed effects linear regression analysis to examine the dataset. This analysis revealed a significant positive relationship between the H 2 :CO 2 ratio and the methane percentage in the upgraded biogas when using the study as a random effect. Furthermore, we performed meta-analysis on observations taken when the ratio was close to 4:1 and found that ex situ reactors (91.93% [88.11%, 95.75%]) can perform better than in situ reactors (84.74% [80.69%, 88.80%]). No evidence of differential performance was found based on the present dataset between different temperature regimes or operation modes. Furthermore, those findings establish a database that will contribute to a deeper understanding of the biogas upgrading via biological CO 2 conversion.

Biogas upgrading↗

DOE OSTI2022

Hard-to-soft transition-enhanced piezoelectricity in poly(vinylidene fluoride) via relaxor-like secondary crystals activated by high-power ultrasonication

We report although high piezoelectric coefficients have recently been observed in poly(vinylidene fluoride-co-trifluoroethylene) [P(VDF-TrFE)] random copolymers, they have low Curie temperatures, which makes their piezoelectricity thermally unstable. It has been challenging to achieve high piezoelectric performance from the more thermally stable PVDF homopolymer. In this report, we describe how high-power ultrasonic processing was used to induce a hard-to-soft piezoelectric transition and improve the piezoelectric coefficient d 31 in neat PVDF. After high-power ultrasonication for 20 min, a uniaxially stretched and poled PVDF film exhibited a high d 31 of 50.2 ± 1.7 pm V -1 at room temperature. Upon heating to 65 °C, the d 31 increased to a maximum value of 76.2 ± 1.2 pm V -1 , and the high piezoelectric performance persisted up to 110 °C. The enhanced piezoelectricity was attributed to the relaxor-like secondary crystals in the oriented amorphous fraction, broken off from the primary crystals by ultrasonication, as suggested by differential scanning calorimetry and broadband dielectric spectroscopy studies.

relaxor-like secondary crystals↗

DOE OSTI2021

Removal of spurious data in Bragg coherent diffraction imaging: an algorithm for automated data preprocessing

Bragg coherent diffraction imaging (BCDI) provides a powerful tool for obtaining high-resolution structural information from nanocrystalline materials. Here a BCDI sample consisting of a large number of randomly oriented nanoscale crystals is considered. Ideally, only one crystal is oriented to produce a Bragg peak on the detector. However, diffraction from other crystals often produces additional signals on the detector. Before the measured diffraction patterns can be processed into structural images, scientists routinely need to manually identify and remove the `alien' intensities from sources other than the intended crystal. With the development of modern high-coherence storage rings, such as the upgraded Advanced Photon Source (APS), the already slow process of manual preprocessing will be untenable for the large volumes of data that will be produced. An automated method of identifying and deleting alien intensities is proposed. This method exploits the fact that BCDI of a perfect crystal produces diffraction data with inversion symmetry around the Bragg peak. This approach uses the machine learning clustering method DBSCAN to distinguish between diffraction from multiple sources, and then calculates cluster size and inversion symmetry to assess whether clusters of intensity belong to desired data or alien signals. This approach can dramatically reduce the amount of time spent manually processing data, allowing BCDI data processing capabilities to keep pace with the technological advances of fourth-generation synchrotron light sources.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Optimizing transmit field inhomogeneity of parallel RF transmit design in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) provides a higher signal-to-noise ratio and, thereby, higher spatial resolution. However, UHF MRI introduces challenges such as transmit radiofrequency (RF) field (B+1) inhomogeneities, leading to uneven flip angles and image intensity anomalies. These issues can significantly degrade imaging quality and its medical applications. This study addresses B+1 field homogeneity through a novel deep learning-based strategy. Traditional methods like Magnitude Least Squares (MLS) optimization have been effective but are time-consuming and dependent on the patient’s presence. Recent machine learning approaches, such as RF Shim Prediction by Iteratively Projected Ridge Regression and deep learning frameworks, have shown promise but face limitations like extensive training times and oversimplified architectures. We propose a two-step deep learning strategy. First, we obtain the desired reference RF shimming weights from multi-channel B+1 fields using random-initialized Adaptive Moment Estimation. Then, we employ Residual Networks (ResNets) to train a model that maps B+1 fields to target RF shimming outputs. Our approach does not rely on pre-calculated reference optimizations for the testing process and efficiently learns residual functions. Comparative studies with traditional MLS optimization demonstrate our method’s advantages in terms of speed and accuracy. The proposed strategy achieves a faster and more efficient RF shimming design, significantly improving imaging quality at UHF. This advancement holds potential for broader applications in medical imaging and diagnostics.

Lu, Zhengyi [Vanderbilt University]↗

DOE OSTI2023

Adaptive estimation of quantum observables

The accurate estimation of quantum observables is a critical task in science. With progress on the hardware, measuring a quantum system will become increasingly demanding, particularly for variational protocols that require extensive sampling. Here, we introduce a measurement scheme that adaptively modifies the estimator based on previously obtained data. Our algorithm, which we call AEQuO, continuously monitors both the estimated average and the associated error of the considered observable, and determines the next measurement step based on this information. We allow both for overlap and non-bitwise commutation relations in the subsets of Pauli operators that are simultaneously probed, thereby maximizing the amount of gathered information. AEQuO comes in two variants: a greedy bucket-filling algorithm with good performance for small problem instances, and a machine learning-based algorithm with more favorable scaling for larger instances. The measurement configuration determined by these subroutines is further post-processed in order to lower the error on the estimator. We test our protocol on chemistry Hamiltonians, for which AEQuO provides error estimates that improve on all state-of-the-art methods based on various grouping techniques or randomized measurements, thus greatly lowering the toll of measurements in current and future quantum applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

A Study of the Properties and Dynamics of the Disk of Satellites in a Milky-Way-like Galaxy System

The dynamics of the satellite systems of Milky-Way-like galaxies offer a useful means by which to study the galaxy formation process in the cosmological context. It has been suggested that the currently observed anisotropic distribution of the satellites in such galaxy systems is inconsistent with the concordance ΛCDM cosmology model on the galactic scale if the observed satellites are random samples of the dark matter (DM) sub-halos that are nearly isotropically distributed around the central galaxy. In this study, we present original high-resolution zoom-in studies of central galaxies and satellite systems based upon initial conditions for the DM distribution from the Aquarius simulations but with substantial high-resolution baryon physics added. We find that the galaxy most like the Milky Way in this study does indeed contain a disk of satellites (DOS). Although one galaxy DOS system does not answer the question of how common such disks are, it does allow the opportunity to explore the properties and dynamics of the DOS system. Our investigation centers on the spatial arrangement (distances, angles, etc.) of satellites in this Milky-Way-like galaxy system with a specific emphasis on identifying and analyzing the disk-like structure along with its dynamical and morphological properties. Among the conclusions from this study, we find that the satellites and DM sub-halos in the galaxy simulations are anisotropically distributed. The dynamical properties of the satellites, however, indicate that the direction of the angular momentum vector of the whole satellite system is different from the normal direction of the fitted DOS and from the normal direction of the velocity dispersion of the system. Hence, the fitted DOS appears to be comprised of infalling sub-halos and is not a rotationally supported system.

Zhao, Xinghai↗

NASA NTRS1978

Beta-to-alpha transformation in polycrystalline SiC. II - Interfacial energetics

A phenomenological analysis of the energetics of the beta-to-alpha transformation in polycrystalline SiC is presented. It is found that the extreme anisotropy of the interfacial energy between alpha- and beta-SiC can account for the rapid growth of composite grains into the beta matrix during conventional sintering or hot-pressing processes. The composite grains consist of alpha-SiC plates 'sandwiched' between well-oriented and recrystallized beta-SiC 'envelopes'. The interfaces involving the 111 plane type of beta and (0001) of alpha have much lower energies than random beta/alpha interfaces.

Mitchell, T. E.↗

NASA NTRS1985

Terrestrial Analog Studies for Martian Patterned Ground

A recurring problem in understanding Martian patterned ground is explaining its large size. Terrestrial patterned ground in Swedish Lapland offers an analog that may help explain this. In cold, arid regions with strong winds, polygonal features are accentuated paralled to the dominant wind direction. Preliminary results of a comparison between Martian polygonal troughs and dominant wind directions suggests a good correlation. This evolutionary model involving aeolian modification of Martian polygonal ground helps explain the large size features without requiring multiple, deep freeze-thaw cycles. A well-established geographical technique, nearest neighbor analysis, can be modified and applied to the distribution of patterned ground on Earth and Mars. The procedure determines the R-statistic, which reflects the degree to which on observation departs from an expected random pattern. The R-statistic is independent of scale, and therefore it can be applied to any size of type of pattern. Preliminary results indicate that there may be a correlation between the R-statistic and the process that create the polygons.

Rossbacher, L. A.↗

NASA NTRS1994

Calibration of the COBE FIRAS instrument

The Far-Infrared Absolute Spectrophotometer (FIRAS) instrument on the Cosmic Background Explorer (COBE) satellite was designed to accurately measure the spectrum of the cosmic microwave background radiation (CMBR) in the frequency range 1-95/cm with an angular resolution of 7 deg. We describe the calibration of this instrument, including the method of obtaining calibration data, reduction of data, the instrument model, fitting the model to the calibration data, and application of the resulting model solution to sky observations. The instrument model fits well for calibration data that resemble sky condition. The method of propagating detector noise through the calibration process to yield a covariance matrix of the calibrated sky data is described. The final uncertainties are variable both in frequency and position, but for a typical calibrated sky 2.6 deg square pixel and 0.7/cm spectral element the random detector noise limit is of order of a few times 10(exp -7) ergs/sq cm/s/sr cm for 2-20/cm, and the difference between the sky and the best-fit cosmic blackbody can be measured with a gain uncertainty of less than 3%.

Fixsen, D. J.↗

NASA NTRS2001

Method and Apparatus for Determining Position Using Global Positioning Satellites

A global positioning satellite receiver having an antenna for receiving a L1 signal from a satellite is presented. The L1 signal is processed by a preamplifier stage including a band pass filter and a low noise amplifier and output as a radio frequency (RF) signal. A mixer receives and de-spreads the RF signal in response to a pseudo-random noise code, i,e., Gold code, generated by an internal pseudo-random noise code generator. A microprocessor enters a code tracking loop, such that during the code tracking loop, it addresses the pseudorandom code generator to cause the pseudo-random code generator to sequentially output pseudo-random codes corresponding to satellite codes used to spread the L1 signal, until correlation occurs. When an output of the mixer is indicative of the occurrence of correlation between the RF signal and the generated pseudo-random codes, the microprocessor caters an operational state which slows the receiver code sequence to stay locked with the satellite cede sequence. The output of the mixer is provided to a detector which, in turn, controls certain routines of the microprocessor. The microprocessor will output pseudo range information according to an interrupt routine in response detection of correlation. The pseudo range information is to be telemetered to a ground station which determines the position of the global positioning satellite receiver.

John L Ward↗

NASA NTRS2004

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

Hou, Arthur Y.↗