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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 OSTI2020

Soft x-ray spectrum unfold of K-edge filtered x-ray diode arrays using cubic splines

Cubic spline interpolation is able to recover temporally and spectrally resolved soft x-ray flux from an array of K-edge filtered x-ray diodes without the need for a priori assumptions about the spectrum or the geometry of the emitting volume. The mathematics of the cubic spline interpolation is discussed in detail. The analytic nature of the cubic spline solution allows for analytical error propagation, and the method of calculating the error for radiation temperature, spectral power, and confidence intervals of the unfolded spectrally resolved flux is explained. An unfold of a blackbody model demonstrates the accuracy of the cubic spline unfold. Tests of cubic spline performance using spectrally convolved detailed atomic model simulation results have been performed to measure the method's ability to conserve spectral power to within a factor of 2 or better in line-dominated regimes. The unfold is also demonstrated to work when information from the x-ray diode array is limited due to high signal-to-noise ratios or lack of signal due to over-attenuation or over-filtration of the x-ray diode signal. Here, the robustness of the unfold with respect to background subtraction and raw signal processing, signal alignment between diode traces, limited signal information, and initial conditions is discussed. Results from an example analysis of a halfraum drive are presented to demonstrate the capabilities of the unfold in comparison with previously established methods.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Analysis of moisture migration in concrete at high temperature through in-situ neutron tomography

Spalling, which is a phenomenon encountered when high-performance concrete is exposed to high temperature, can lead to large economical damage and can be a major safety hazard. Moisture distribution in concrete during exposure to fire is of paramount importance for understanding the complex mechanism of this phenomenon. To capture in its fullness this mechanism, it is crucial to account for the heterogeneous nature of concrete. In this paper, the first 3D analysis of moisture distribution in concrete at high temperature through in-situ neutron tomography is presented. The world-leading flux at the Institute Laue Langevin in Grenoble, France allowed capturing one 3D scan per minute, which is sufficient to follow the fast dehydration process. The paper describes the experimental setup with the heating system and discusses in detail the framework of the neutron tomography test. Quantitative analysis showing the effect of the aggregate size on the moisture distribution is presented.

36 MATERIALS SCIENCE↗
DOE OSTI2012

PROCESSING METHOD EFFECT ON SUN DIAMETER MEASUREMENT WITH CCD SOLAR ASTROLABE

Photometric Sun diameter measurement is based on the calculation of the inflection point of the solar limb. In ground measurement, this point is located at a position on the solar limb where the signal-to-noise ratio is very high, which necessitates the appropriate filtering techniques to eliminate the noise while preserving its position. In this paper, we compare the filtering method currently in use to process the CCD solar astrolabe data, the FFTD method widely used, with a different method that we propose. Using the acquired data from the CCD astrolabe at Calern, France during 1997, we can obtain a mean difference of 130 mas in the measured radii.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Data processing and analysis of the imaging Thomson scattering diagnostic system on HT-7 tokamak

A high spatial resolution imaging Thomson scattering diagnostic system was developed in ASIPP (Institute of Plasma Physics, Chinese Academy of Sciences). After about one month trial running on the superconducting HT-7 (Hefei Tokamak-7) tokamak, the system was proved to be capable of measuring plasma electron temperature. The system setup and data calibration are described in this paper and then the instrument function is studied in detail, as well as the measurement capability, an electron temperature of 50 eV to 2 keV and density beyond 1 Multiplication-Sign 10{sup 19} m{sup -3}. Finally, the data processing method and experimental results are presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Multiresolution spatiotemporal mechanical model of the heart as a prior to constrain the solution for 4D models of the heart

In several nuclear cardiac imaging applications (SPECT and PET), images are formed by reconstructing tomographic data using an iterative reconstruction algorithm with corrections for physical factors involved in the imaging detection process and with corrections for cardiac and respiratory motion. The physical factors are modeled as coefficients in the matrix of a system of linear equations and include attenuation, scatter, and spatially varying geometric response. The solution to the tomographic problem involves solving the inverse of this system matrix. This requires the design of an iterative reconstruction algorithm with a statistical model that best fits the data acquisition. The most appropriate model is based on a Poisson distribution. Using Bayes Theorem, an iterative reconstruction algorithm is designed to determine the maximum a posteriori estimate of the reconstructed image with constraints that maximizes the Bayesian likelihood function for the Poisson statistical model. The a priori distribution is formulated as the joint entropy (JE) to measure the similarity between the gated cardiac PET image and the cardiac MRI cine image modeled as a FE mechanical model. In conclusion, the developed algorithm shows the potential of using a FE mechanical model of the heart derived from a cardiac MRI cine scan to constrain solutions of gated cardiac PET images.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

LANL12-RS-107J PYTHON Radiography Analysis Tool (PyRAT). Mid-Year Deliverable Report for FY15

This document is a mid-year report on a deliverable for the PYTHON Radiography Analysis Tool (PyRAT) for project LANL12-RS-107J in FY15. The deliverable is deliverable number 2 in the work package and is titled “Add the ability to read in more types of image file formats in PyRAT”. Right now PyRAT can only read in uncompressed TIF files (tiff files). It is planned to expand the file formats that can be read by PyRAT, making it easier to use in more situations. A summary of the file formats added include jpeg, jpg, png and formatted ASCII files.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Report of the Task Group 186 on model-based dose calculation methods in brachytherapy beyond the TG-43 formalism: Current status and recommendations for clinical implementation

The charge of Task Group 186 (TG-186) is to provide guidance for early adopters of model-based dose calculation algorithms (MBDCAs) for brachytherapy (BT) dose calculations to ensure practice uniformity. Contrary to external beam radiotherapy, heterogeneity correction algorithms have only recently been made available to the BT community. Yet, BT dose calculation accuracy is highly dependent on scatter conditions and photoelectric effect cross-sections relative to water. In specific situations, differences between the current water-based BT dose calculation formalism (TG-43) and MBDCAs can lead to differences in calculated doses exceeding a factor of 10. MBDCAs raise three major issues that are not addressed by current guidance documents: (1) MBDCA calculated doses are sensitive to the dose specification medium, resulting in energy-dependent differences between dose calculated to water in a homogeneous water geometry (TG-43), dose calculated to the local medium in the heterogeneous medium, and the intermediate scenario of dose calculated to a small volume of water in the heterogeneous medium. (2) MBDCA doses are sensitive to voxel-by-voxel interaction cross sections. Neither conventional single-energy CT nor ICRU/ICRP tissue composition compilations provide useful guidance for the task of assigning interaction cross sections to each voxel. (3) Since each patient-source-applicator combination is unique, having reference data for each possible combination to benchmark MBDCAs is an impractical strategy. Hence, a new commissioning process is required. TG-186 addresses in detail the above issues through the literature review and provides explicit recommendations based on the current state of knowledge. TG-43-based dose prescription and dose calculation remain in effect, with MBDCA dose reporting performed in parallel when available. In using MBDCAs, it is recommended that the radiation transport should be performed in the heterogeneous medium and, at minimum, the dose to the local medium be reported along with the TG-43 calculated doses. Assignments of voxel-by-voxel cross sections represent a particular challenge. Electron density information is readily extracted from CT imaging, but cannot be used to distinguish between different materials having the same density. Therefore, a recommendation is made to use a number of standardized materials to maintain uniformity across institutions. Sensitivity analysis shows that this recommendation offers increased accuracy over TG-43. MBDCA commissioning will share commonalities with current TG-43-based systems, but in addition there will be algorithm-specific tasks. Two levels of commissioning are recommended: reproducing TG-43 dose parameters and testing the advanced capabilities of MBDCAs. For validation of heterogeneity and scatter conditions, MBDCAs should mimic the 3D dose distributions from reference virtual geometries. Potential changes in BT dose prescriptions and MBDCA limitations are discussed. When data required for full MBDCA implementation are insufficient, interim recommendations are made and potential areas of research are identified. Application of TG-186 guidance should retain practice uniformity in transitioning from the TG-43 to the MBDCA approach.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Legacy Survey of Space and Time Data Preview 1: source dataset type

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of the source dataset type. These are measurements for detected sources in processed visit images. This release contains 1,786 datasets of this type.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Legacy Survey of Space and Time Data Preview 1: Source searchable catalog

The Legacy Survey of Space and Time Data Preview 1 (DP1) is the first release of data from the NSF-DOE Vera C. Rubin Observatory. It consists of raw and calibrated single-epoch images, co-adds, difference images, detection catalogs, and other derived data products. DP1 is based on 1792 science-grade optical/near-infrared exposures acquired over 48 distinct nights by the Rubin Commissioning Camera, LSSTComCam, on the Simonyi Survey Telescope at the Summit Facility on Cerro Pachón, Chile during the first on-sky commissioning campaign in late 2024. DP1 covers a total of approximately 15 sq. deg. over seven roughly equally-sized non-contiguous fields, each independently observed in six broad photometric bands, ugrizy, spanning a range of stellar densities and latitudes and overlapping with external reference datasets. This dataset is a subset of the full data release consisting of a searchable catalog named Source. This catalog contains measurements for detected sources in processed visit images. This catalog contains 45,565,632 rows with 156 columns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SU-F-I-51: CT/MR Image Deformation: The Clinical Assessment QA in Target Delineation

Purpose: To study the deformation effects in CT/MR image registration of head and neck (HN) cancers. We present a clinical indication in guiding and simplifying registration procedures of this process while CT images possessed artifacts. Methods: CT/MR image fusion provides better soft tissue contrast in intracranial GTV definition with artifacts. However, whether the fusion process should include the deformation process is questionable and not recommended. We performed CT/MR image registration of a HN patient with tonsil GTV and nodes delineation on Varian Velocity™ system. Both rigid transformation and deformable registration of the same CT/MR imaging data were processed separately. Physician’s selection of target delineation was implemented to identify the variations. Transformation matrix was shown with visual identification, as well as the deformation QA numbers and figures were assessed. Results: The deformable CT/MR images were traced with the calculated matrix, both translation and rotational parameters were summarized. In deformable quality QA, the calculated Jacobian matrix was analyzed, which the min/mean/max of 0.73/0/99/1.37, respectively. Jacobian matrix of right neck node was 0.84/1.13/1.41, which present dis-similarity of the nodal area. If Jacobian = 1, the deformation is at the optimum situation. In this case, the deformation results have shown better target delineation for CT/MR deformation than rigid transformation. Though the root-mean-square vector difference is 1.48 mm, with similar rotational components, the cord and vertebrae position were aligned much better in the deformable MR images than the rigid transformation. Conclusion: CT/MR with/without image deformation presents similar image registration matrix; there were significant differentiate the anatomical structures in the region of interest by deformable process. Though vendor suggested only rigid transformation between CT/MR assuming the geometry remain similar, our findings indicated with patient positional variations, deformation registration is needed to generate proper GTV coverage, which will be irradiated more accurately in the following boost phase.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Out-of-distribution detection with non-parametric density estimation for models predicting processing history of uranium ore concentrates

The rapid advancement in machine learning (ML) and computer vision (CV) coincides with the growth of interest in deploying these ML/CV models in numerous fields from medicine to social science. Similar to those areas, we have witnessed a great number of works in materials science employing ML/CV models – neural networks in particular – in their studies in recent years. These models have proven to obtain accurate performance in various tasks. However, these models struggle to attain a similar performance when encountering test samples coming from a distribution that is different from the training set. More importantly, they fail without providing any warning to the users. Therefore, we propose a framework for detecting out-of-distribution (OOD) samples to alert users when a human intervention might be necessary in this work. Specifically, we explore the use of a non-parametric density estimation method to detect OOD samples. Here, we assess OOD detection capability of the proposed framework on ML models developed for categorizing precipitation routes of U 3 O 8 when encountering OOD datasets that contain samples (1) undergone different imaging acquisition process, (2) undergone different material synthesis process, and (3) different materials than ID set. Through those experiments, we achieve an average area under the receiver operating characteristic (AUROC) of at least 91% on average in detecting OOD samples. With minimal overhead cost and superior performance, the proposed framework enables a reliable and safe system when deploying in real-world scenarios.

Convolutional neural networks↗
DOE OSTI2016

Cementitious Grouts for ILW Encapsulation - Hydration and Continuity of Supply within the UK - 16184

In the UK the preferred route to disposal for the majority of intermediate level nuclear waste (ILW) streams is encapsulation within a cementitious matrix, accounting for 83% of waste conditioned to date (NDA, 2013). The method is well-defined and produces a waste package that is both chemically and physically stable, providing a multi-layered barrier to the release of the waste species contained within. Due to the process of treatment, facilitated via remote operation, it is necessary for the grouting matrices to meet strict performance limits in terms of their flow, setting time and avoidance of the formation of bleed water or segregation. To this end, the limits on composition of the anhydrous materials (a mixture of ordinary Portland cement [OPC] and blast furnace slag [BFS]) are tight to ensure conformity. Whilst these limits on composition are well understood, their impact upon grout hydration, and hence performance, is poorly defined. This study investigates the effects of modifying the physical and chemical composition of both the OPC and the BFS components of the matrix in order to identify the sensitivity or otherwise of the system to ensure that a continuity of supply is maintained. A number of techniques, scanning electron microscopy - image analysis (SEM-IA), chemical shrinkage (measured via dilatometry), isothermal conduction calorimetry (ICC), thermogravimetric analysis (TGA) and X-ray diffraction (XRD), have been applied to assess the rate and degree of hydration (DoH) of a range of grouts prepared with OPC and BFS with a range of chemical and physical compositions. This has been coupled with subsequent engineering performance testing, with additional analysis to understand the impact of a fire scenario within a storage or disposal facility, to provide an indication towards the resilience of the waste packages to a potential catastrophic event. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

A quantification strategy for missing bone mass in case of osteolytic bone lesions

Purpose: Most of the patients who died of breast cancer have developed bone metastases. To understand the pathogenesis of bone metastases and to analyze treatment response of different bone remodeling therapies, preclinical animal models are examined. In breast cancer, bone metastases are often bone destructive. To assess treatment response of bone remodeling therapies, the volumes of these lesions have to be determined during the therapy process. The manual delineation of missing structures, especially if large parts are missing, is very time-consuming and not reproducible. Reproducibility is highly important to have comparable results during the therapy process. Therefore, a computerized approach is needed. Also for the preclinical research, a reproducible measurement of the lesions is essential. Here, the authors present an automated segmentation method for the measurement of missing bone mass in a preclinical rat model with bone metastases in the hind leg bones based on 3D CT scans. Methods: The affected bone structure is compared to a healthy model. Since in this preclinical rat trial the metastasis only occurs on the right hind legs, which is assured by using vessel clips, the authors use the left body side as a healthy model. The left femur is segmented with a statistical shape model which is initialised using the automatically segmented medullary cavity. The left tibia and fibula are segmented using volume growing starting at the tibia medullary cavity and stopping at the femur boundary. Masked images of both segmentations are mirrored along the median plane and transferred manually to the position of the affected bone by rigid registration. Affected bone and healthy model are compared based on their gray values. If the gray value of a voxel indicates bone mass in the healthy model and no bone in the affected bone, this voxel is considered to be osteolytic. Results: The lesion segmentations complete the missing bone structures in a reasonable way. The mean ratiov{sub r}/v{sub m} of the reconstructed bone volume v{sub r} and the healthy model bone volume v{sub m} is 1.07, which indicates a good reconstruction of the modified bone. Conclusions: The qualitative and quantitative comparison of manual and semi-automated segmentation results have shown that comparing a modified bone structure with a healthy model can be used to identify and measure missing bone mass in a reproducible way.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Comparison of the results of refractometric measurements in the process of diffusion, obtained by means of the backgroundoriented schlieren method and the holographic interferometry method

The results of the study of interdiffusion of two liquids, obtained using the holographic recording scheme with a nonstationary reference wave with the frequency linearly varying in space and time are compared with the results of correlation processing of digital photographs, made with a random background screen. The spatio-temporal behaviour of the signal in four basic representations ('space – temporal frequency', 'space – time', 'spatial frequency – temporal frequency' and 'spatial frequency – time') is found in the holographic experiment and calculated (in the appropriate coordinates) based on the background-oriented schlieren method. Practical coincidence of the results of the correlation analysis and the holographic double-exposure interferometry is demonstrated. (interferometry)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

A selection of giant radio sources from NVSS

Results of the application of pattern-recognition techniques to the problem of identifying giant radio sources (GRSs) from the data in the NVSS catalog are presented, and issues affecting the process are explored. Decision-tree pattern-recognition software was applied to training-set source pairs developed from known NVSS large-angular-size radio galaxies. The full training set consisted of 51,195 source pairs, 48 of which were known GRSs for which each lobe was primarily represented by a single catalog component. The source pairs had a maximum separation of $20^{\prime} $ and a minimum component area of 1.87 square arcmin at the 1.4 mJy level. The importance of comparing the resulting probability distributions of the training and application sets for cases of unknown class ratio is demonstrated. The probability of correctly ranking a randomly selected (GRS, non-GRS) pair from the best of the tested classifiers was determined to be 97.8 ± 1.5%. The best classifiers were applied to the over 870,000 candidate pairs from the entire catalog. Images of higher-ranked sources were visually screened, and a table of over 1600 candidates, including morphological annotation, is presented. These systems include doubles and triples, wide-angle tail and narrow-angle tail, S- or Z-shaped systems, and core-jets and resolved cores. In conclusion, while some resolved-lobe systems are recovered with this technique, generally it is expected that such systems would require a different approach.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Two-photon polymerization printed lattices as support structures in multi-shell ICF targets: Platform development and initial assessment

Recent interest in fielding direct drive multi-shell targets on the NIF [K. Molvig et al., Phys. Rev. Lett. 116, 255003 (2016) and S. X. Hu et al., Phys. Rev. E 100, 063204 (2019)] has highlighted the need for a low density structure to support the inner shell(s) and to avoid energy loss in the acceleration and collision process. We have developed a two-shell platform to evaluate the use of low density two-photon polymerization (2PP) printed lattices as a support structure between the shells. Here, 2PP structures are an attractive option because they can be produced at densities as low as 5 mg/cc, which is ideal for multi-shell targets, and their 3D structure can be tailored to the user's needs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

NETL Plastic Pipes Project (Final Report)

Plastic or composite pipelines have been the bane of the utility locating industry because they are neither conductive nor magnetic which are the properties traditionally used to locate buried utilities. Ground penetrating radar (GPR) is an effective geophysical tool for locating plastic/composite pipelines where resistive cover allows for adequate penetration of radar energy. However, GPR has limited applicability in areas where the soil cover is conductive due to significant clay and/or salt content. This study examines complementary near-surface geophysical methods that are potentially useful for locating buried plastic/composite pipelines, either singly or in combination. Specifically, this modeling study used computational numerical methods to forward model the response of GPR, resistivity, seismic, gravity gradiometry, and photoacoustic/thermoacoustic imaging methods to plastic/composite pipelines for various scenarios including: (1) pipe diameters ranging between 2 in. to 12 in.; (2) burial depths ranging between 3 ft. to 4 ft.; (3) various degrees in contrast in physical properties (i.e., electrical permittivity, elasticity, resistivity, density); and (4) various experimental acquisition choices (e.g., GPR radar and seismic source frequencies, electrode spacing). Numerical modeling performed herein reconfirmed that GPR is the preferred method for detecting/locating plastic pipelines. A caveat for GPR detection is that the material covering the plastic pipe (trench fill material and adjacent soil) must be sufficiently resistive to allow the two-way propagation to the required depth of investigation and back to the surface. GPR was the only method modeled in this study that can be used to directly detect plastic pipelines of 2-in.-diameter and larger when buried 3-ft-deep. GPR data processing and imaging also can determine pipe depth, pipe diameter, trench dimensions, and moisture conditions. Seismic modeling results suggest that direct detection of a 12-in.-diameter plastic pipe at 3-ft.-depth may be possible under favorable conditions; however, the associated signature would be weak (e.g., surface- to S-wave, backscattered surface-waves, and/or forward scattered surface-waves to S-wave). Direct pipe detection under field conditions with noise and strong lateral geologic heterogeneity is doubtful. Numerical modeling also suggests that plastic pipelines can be indirectly located by detecting the trench in which they are buried. GPR, direct current (DC) resistivity, and seismic methods have the potential to locate the pipeline trench if there is sufficient contrast between the trench-wall and trench-fill materials for the physical property being measured by each method (i.e., electrical permittivity for GPR; resistivity for DC resistivity; or density, compressional velocity, or shear velocity for seismic). Modeling also indicated that currently available (commercial) gravity gradiometers would be unable to directly detect/locate plastic pipelines ≤ 8-in.-diameter when buried 3-ft.-deep given the typical instrument noise floor for field surveying as well as the expected density variations due to geologic heterogeneity. The numerical modeling performed in this project did not identify a universal geophysical technology that can locate buried plastic pipelines in all parts of the United States (although GPR is suggested for all areas with resistive cover). However, the project results suggest that a towed land streamer simultaneously acquiring multiple geophysical data types including multi-offset GPR, multi-channel DC resistivity, seismic geophone- and/or distributed acoustic sensing (DAS), and potentially photoacoustic/thermoacoustic data would be an appropriate platform for locating buried plastic pipeline. Moreover, the complementary multiphysics data acquired by a towed land streamer would permit the use of joint and/or cooperative inversion frameworks for a more rigorous and consistent data interpretation.

42 ENGINEERING↗