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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Positron Emission Tomography in Water Resources and Subsurface Energy Resources Engineering Research

Recent studies have demonstrated that positron emission tomography (PET) is a valuable tool for in-situ characterization of fluid transport in porous and fractured geologic media at the laboratory scale. While PET imaging is routinely used for clinical cancer diagnosis and preclinical medical research—and therefore imaging facilities are available at most research institutes—widespread adoption for applications in water resources and subsurface energy resources engineering have been limited by real and perceived challenges of working with this technique. In this study we discuss and address these challenges, and provide detailed analysis highlighting how positron emission tomography can complement and improve laboratory characterization of different subsurface fluid transport problems. The physics of PET are reviewed to provide a fundamental understanding of the sources of noise, resolution limits, and safety considerations. We then layout the methodology required to perform laboratory experiments imaged with PET, including a new protocol for radioactivity dosing optimization for imaging in geologic materials. Signal-to-noise and sensitivity analysis comparisons between PET and clinical X-ray computed tomography are performed to highlight how PET data can complement more traditional characterization methods, particularly for solute transport problems. Lastly, prior work is critically reviewed and discussed to provide a better understanding of the strengths and weakness of PET and how to best utilize PET-derived data for future studies.

02 PETROLEUM↗
DOE OSTI2026

Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging

Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse that volume. Applications include seismic exploration of the Earth’s subsurface, acoustic imaging and nondestructive testing (NDT) in material science, and ultrasound computed tomography (USCT) in medicine. Current approaches for solving CWI problems can be divided into two categories: those rooted in traditional physics and those based on deep learning. Physics-based methods stand out for their ability to provide high-resolution and quantitatively accurate estimates of acoustic properties within the medium. However, they can be computationally intensive and are susceptible to ill-posedness and nonconvexity typical of CWI problems. Machine learning (ML)-based computational methods have recently emerged, offering a different perspective to address these challenges. Diverse scientific communities have independently pursued the integration of deep learning in CWI. This review discusses how contemporary scientific ML techniques, and deep neural networks in particular, have been developed to enhance and integrate with traditional physics-based methods for solving CWI problems. We present a structured framework that consolidates existing research spanning multiple domains, including computational imaging, wave physics, and data science. This study concludes with important lessons learned from existing ML-based methods and identifies technical hurdles and emerging trends through a systematic analysis of the extensive literature on this topic.

42 ENGINEERING↗
DOE OSTI2021

HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization

We present a new software, HYPPO, that enables the automatic tuning of hyperparameters of various deep learning (DL) models. Unlike other hyperparameter optimization (HPO) methods, HYPPO uses adaptive surrogate models and directly accounts for uncertainty in model predictions to find accurate and reliable models that make robust predictions. Using asynchronous nested parallelism, we are able to significantly alleviate the computational burden of training complex architectures and quantifying the uncertainty. HYPPO is implemented in Python and can be used with both TensorFlow and PyTorch libraries. We demonstrate various software features on time-series prediction and image classification problems as well as a scientific application in computed tomography image reconstruction. Finally, we show that (1) we can reduce by an order of magnitude the number of evaluations necessary to find the most optimal region in the hyperparameter space and (2) we can reduce by two orders of magnitude the throughput for such HPO process to complete.

adaptation models↗
DOE OSTI2015

Forward problem solution as the operator of filtered and back projection matrix to reconstruct the various method of data collection and the object element model in electrical impedance tomography

Back projection reconstruction has been implemented to get the dynamical image in electrical impedance tomography. However the implementation is still limited in method of adjacent data collection and circular object element model. The study aims to develop the methods of back projection as reconstruction method that has the high speed, accuracy, and flexibility, which can be used for various methods of data collection and model of the object element. The proposed method uses the forward problem solution as the operator of filtered and back projection matrix. This is done through a simulation study on several methods of data collection and various models of the object element. The results indicate that the developed method is capable of producing images, fastly and accurately for reconstruction of the various methods of data collection and models of the object element.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

A Level Set Evaporation Model for Heterogeneous Atom Probe Tip

With the development of local electrode atom probe tomography (LEAP), the materials systems feasible for atomic structure determination has expanded from predominantly metals to include heterogeneous materials with complex structure and compositions. This makes the 3D atomic structure determination possible for most energy materials in battery, fuel cell, semiconductor, and nuclear applications. Atom probe tomography (APT) has been utilized to study multiphase materials with segregation and interface problems. The unique and quantitative information retrieved from APT can provide a foundation for the study of kinetic pathways, nanoscale composition mapping, multilayer interfacial segregation, dislocations and grain boundaries. However, a new challenge surfaces when the materials systems expand into heterogeneous materials: the traditional structure reconstruction introduces false magnification and large artifacts due to the underlying assumption of uniform and isotropic evaporation.

Atom probe, heterogeneous structure, evporation mo↗
DOE OSTI2015

Determination of solute site occupancies within γ' precipitates in nickel-base superalloys via orientation-specific atom probe tomography

In this study, the analytical limitations in atom probe tomography such as resolving a desired set of atomic planes, for solving complex materials science problems, have been overcome by employing a well-developed unique and reproducible crystallographic technique, involving synergetic coupling of orientation microscopy with atom probe tomography. The crystallographic information in atom probe reconstructions has been utilized to determine the solute site occupancies in Ni-Al-Cr based superalloys accurately. The structural information in atom probe reveals that both Al and Cr occupy the same sub-lattice within the L1 2 -ordered g precipitates to form Ni 3 (Al,Cr) precipitates in a Ni-14Al-7Cr(at.%) alloy. Interestingly, the addition of Co, which is a solid solution strengthener, to a Ni-14Al-7Cr alloy results in the partial reversal of Al site occupancy within g precipitates to form (Ni,Al) 3 (Al,Cr,Co) precipitates. This unique evidence of reversal of Al site occupancy, resulting from the introduction of other solutes within the ordered structures, gives insights into the relative energetics of different sub-lattice sites when occupied by different solutes.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Significantly Improving Regional Seismic Amplitude Tomography at Higher Frequencies by Determining S -Wave Bandwidth

Characterizing regional seismic signals continues to be a difficult problem due to their variability. Calibration of these signals is very important to many aspects of monitoring underground nuclear explosions, including detecting seismic signals, discriminating explosions from earthquakes, and reliably estimating magnitude and yield. Amplitude tomography, which simultaneously inverts for source, propagation, and site effects, is a leading method of calibrating these signals. A major issue in amplitude tomography is the data quality of the input amplitude measurements. Pre-event and prephase signal-to-noise ratio (SNR) tests are typically used but can frequently include bad signals and exclude good signals. The deficiencies of SNR criteria, which are demonstrated here, lead to large calibration errors. To ameliorate these issues, we introduce a semi-automated approach to assess the bandwidth of a spectrum where it behaves physically. We determine the maximum frequency (denoted as F max ) where it deviates from this behavior due to inflections at which noise or spurious signals start to bias the spectra away from the expected decay. We compare two amplitude tomography runs using the SNR and new F max criteria and show significant improvements to the stability and accuracy of the tomography output for frequency bands higher than 2 Hz by using our assessments of valid S-wave bandwidth. We compare Q estimates, P/S residuals, and some detailed results to explain the improvements. Lastly, for frequency bands higher than 4 Hz, needed for effective P/S discrimination of explosions from earthquakes, the new bandwidth criteria sufficiently fix the instabilities and errors so that the residuals and calibration terms are useful for application.

58 GEOSCIENCES↗
DOE OSTI2019

Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing

Highly-directional image artifacts such as ion mill curtaining, mechanical scratches, or image striping from beam instability degrade the interpretability of micrographs. These unwanted, aperiodic features extend the image along a primary direction and occupy a small wedge of information in Fourier space. Deleting this wedge of data replaces stripes, scratches, or curtaining, with more complex streaking and blurring artifacts—known within the tomography community as “missing wedge” artifacts. Here, we overcome this problem by recovering the missing region using total variation minimization, which leverages image sparsity-based reconstruction techniques—colloquially referred to as compressed sensing (CS)—to reliably restore images corrupted by stripe-like features. Our approach removes beam instability, ion mill curtaining, mechanical scratches, or any stripe features and remains robust at low signal-to-noise. In conclusion, the success of this approach is achieved by exploiting CS's inability to recover directional structures that are highly localized and missing in Fourier Space.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Swept source optical coherence tomography for in vivo imaging and vibrometry in the apex of the mouse cochlea

Cochlear amplification has been most commonly investigated by measuring the vibrations of the basilar membrane in animal models. Several different techniques have been used for measuring these vibrations such as laser Doppler vibrometry, miniature pressure sensors, low coherence interferometry, and spectral-domain optical coherence tomography (SD-OCT). We have built a swept-source OCT (SS-OCT) system, which is similar to SD-OCT in that it is capable of performing both imaging and vibration measurements within the mouse cochlea in vivo without having to open the bone. In vivo 3D images of a mouse cochlea were obtained, and the basilar membrane, tectorial membrane, Reissner’s membrane, tunnel of Corti, and reticular lamina could all be resolved. We measured vibrations of multiple structures within the mouse cochlea to sound stimuli. As well, we measured the radial deflections of the reticular lamina and tectorial membrane to estimate the displacement of the outer hair cell stereocilia. These measurements have the potential to more clearly define the mechanisms underlying the linear and non-linear processes within the mammalian cochlea.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Optimization-Based Approach for Joint X-Ray Fluorescence and Transmission Tomographic Inversion

Fluorescence tomographic reconstruction, based on the detection of photons coming from fluorescent emission, can be used for revealing the internal elemental composition of a sample. On the other hand, conventional X-ray transmission tomography can be used for reconstructing the spatial distribution of the absorption coefficient inside a sample. In this work, we integrate both X-ray fluorescence and X-ray transmission data modalities and formulate a nonlinear optimization-based approach for reconstruction of the elemental composition of a given object. This model provides a simultaneous reconstruction of both the quantitative spatial distribution of all elements and the absorption effect in the sample. Mathematically speaking, we show that compared with the single-modality inversion (i.e., the X-ray transmission or fluorescence alone), the joint inversion provides a better-posed problem, which implies a better recovery. Therefore, the challenges in X-ray fluorescence tomography arising mainly from the effects of self-absorption in the sample are partially mitigated. The use of this technique is demonstrated on the reconstruction of several synthetic samples.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Boosting Noise2Inverse via enhanced model selection for denoising computed tomography data

Synchrotron-based x-ray tomographic imaging enables the examination of the internal structure of materials at high spatial and temporal resolution. Experimental constraints can impose dose and time limits on the measurements, introducing a higher level of noise and artifacts in the reconstructed images. Deep learning has emerged as a powerful tool to remove noise from reconstructed images. Recently, the Noise2Inverse method was designed specifically for denoising reconstructed images without requiring paired noisy and clean images. This method creates multiple statistically independent reconstructions used to pair the data in which training involves transforming one reconstruction into the other, and vice versa. Originally designed to be used after a fixed number of epochs, we see in practice that this approach may not produce the optimal model and may unnecessarily waste computational resources. Therefore, we propose an alternative method of identifying the best model during training that aligns with the Noise2Inverse method. During validation, we compare the model output of the multiple reconstructions among each other. We hypothesize that the best model is the one that produces images with the highest similarity, implying a convergence in the predicted material properties and absorption values. To compare model outputs, we consider the absolute error, square error, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and cosine similarity. We evaluate our method on two simulated tomography datasets and two, real-world, low-contrast, high-energy x-ray tomography datasets. We show our approach is more effective at determining the best model, up to an increase of 12.50% and 12.53% in SSIM and PSNR, respectively, while only requiring a fifth of the training time compared to the original approach.

CT↗
DOE OSTI2024

Three-dimensional structure of buried heterointerfaces revealed by multislice ptychography

Here, we report on the three-dimensional (3D) structure determination of a twisted hexagonal boron nitride (h-BN) heterointerface from a single-view dataset using multislice ptychography. We identify the buried heterointerface between two twisted h-BN flakes with a lateral resolution of 0.57 Å and a depth resolution of 2.5 nm. The latter represents a significant improvement (∼2.7 times) over the aperture-limited depth resolution of incoherent imaging modes, such as annular-dark-field scanning transmission electron microscopy. This improvement is attributed to the diffraction signal extending beyond the aperture edge, with the depth resolution set by the curvature of the Ewald sphere. Future advancements in this approach could enhance the depth resolution to the subnanometer level and enable the identification of individual dopants, defects, and color centers in twisted heterointerfaces and other materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

TH-AB-207A-06: The Use of Realistic Phantoms to Predict CT Dose to Pediatric Patients

Purpose: To predict pediatric patient dose from diagnostic CT scans using Monte Carlo simulation of realistic reference phantoms of various ages, weights, and heights. Methods: A series of deformable pediatric reference phantoms using Non-Uniform Rational B-Splines (NURBS) was developed for a large range of ages, percentiles, and reference anatomy. Individual bones were modeled using age-dependent factors, and red marrow was modeled as functions of age and spatial distribution based on Cristy1. Organ and effective doses for the phantom series were calculated using Monte Carlo simulation of chest, abdominopelvic, and chest-abdomen-pelvis CT exams. Non-linear regression was performed to determine the relationship between dose-length-product (DLP)-normalized organ and effective doses and phantom diameter. Patient-specific voxel computational phantoms were also created by manual segmentation of previously acquired CT images for 40 pediatric patients (0.7 to 17 years). Organ and effective doses were determined by Monte Carlo simulation of these patient-specific phantoms. Each patient was matched to the closest pediatric reference phantom based primarily on age and diameter for all major organs within the torso. Results: A total of 80 NURBS phantoms were created ranging from newborn to 15 years with height/weight percentiles from 10 to 90%. Organ and effective dose normalized by DLP correlated strongly with exponentially decreasing average phantom diameter (R{sup 2} > 0.95 for most organs). A similar relationship was determined for the patient-specific voxel phantoms. Differences between patient-phantom matched organ-dose values ranged from 0.37 to 2.39 mGy (2.87% to 22.1%). Conclusion: Dose estimation using NURBS-based pediatric reference phantoms offers the ability to predict patient dose before and after CT examinations, and physicians and scientists can use this information in their analysis of dose prescriptions for particular subjects and study types. This may lead to practices that minimize radiation dose while still achieving high quality images and, ultimately, improved patient care. NIH/NCI 1 R01 CA155400-01A1.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Estimating scatter in cone beam CT with striped ratio grids: A preliminary investigation

Purpose: To propose a new method for estimating scatter in x-ray imaging. Conventional antiscatter grids reject scatter at an efficiency that is constant or slowly varying over the surface of the grid. A striped ratio antiscatter grid, composed of stripes that alternate between high and low grid ratio, could be used instead. Such a striped ratio grid would reduce scatter-to-primary ratio as a conventional grid would, but more importantly, the signal discontinuities at the boundaries of stripes can be used to estimate local scatter content. Methods: Signal discontinuities provide information on scatter, but are contaminated by variation in primary radiation. A nonlinear image processing algorithm is used to estimate the scatter content in the presence of primary variation. We emulated a striped ratio grid by imaging phantoms with two sequential CT scans, one with and one without a conventional grid. These two scans are processed together to mimic a striped ratio grid. This represents a best case limit of the striped ratio grid, in that the extent of grid ratio modulation is very high and the scatter contrast is maximized. Results: In a uniform cylinder, the striped ratio grid virtually eliminates cupping. Artifacts from scatter are improved in an anthropomorphic phantom. Some banding artifacts are induced by the striped ratio grid. Conclusions: Striped ratio grids could be a simple and effective evolution of conventional antiscatter grids. Construction and validation of a physical prototype remains an important future step.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

DEVELOPMENT OF A NUCLEAR FUEL SAFEGUARDS VERIFICATION TECHNOLOGY FOR NEW FACILITY TYPES: Use of fast neutron emission tomography for spent fuel verification

With the buildup of spent fuel inventories around the world from decommissioning activities, a tool for the efficient and effective verification of a variety of fuel types for long-term disposition is needed. Fast neutron emission tomography is a promising imaging technology that can address this problem and has been under development at Oak Ridge National Laboratory for the past two years. The goal of this capability is to detect the removal or substitution of individual fuel pins in spent nuclear fuel assemblies for international safeguards applications. The present imaging technique is based on neutron emissions originating primarily from curium-244, which is produced predominantly at the end of the exposure cycle. As a result, this technique may be sensitive not only to fuel pins that are removed or substituted subsequent to all irradiation, but also to fuel pins that are substituted and subsequently irradiated. At present, a laboratory prototype imager is under construction. The purpose of the prototype is to demonstrate an imaging capabilitysufficient to resolve individual fuel pins using commercially available boron straw detectors that can withstand the high gamma ray dose from a typical spent fuel assembly. To achieve both practical measurement durations and sufficient resolution to discern individual pins, the prototype imager employs a novel collimator design where the slits of a parallel-slit collimator are rearranged to distribute them around a ring surrounding the target fuel assembly. This paper will report on simulations and experimental results undertaken to converge on a final design, image reconstruction of sample fuel types of interest, and challenges associated.

Iyengar, Anagha↗
DOE OSTI2015

Robust primary modulation-based scatter estimation for cone-beam CT

Purpose: Scattered radiation is one of the major problems facing image quality in flat detector cone-beam computed tomography (CBCT). Previously, a new scatter estimation and correction method using primary beam modulation has been proposed. The original image processing technique used a frequency-domain-based analysis, which proved to be sensitive to the accuracy of the modulator pattern both spatially and in amplitude as well as to the frequency of the modulation pattern. In addition, it cannot account for penumbra effects that occur, for example, due to the finite focal spot size and the scatter estimate can be degraded by high-frequency components of the primary image. Methods: In this paper, the authors present a new way to estimate the scatter using primary modulation. It is less sensitive to modulator nonidealities and most importantly can handle arbitrary modulator shapes and changes in modulator attenuation. The main idea is that the scatter estimation can be expressed as an optimization problem, which yields a separation of the scatter and the primary image. The method is evaluated using simulated and experimental CBCT data. The scattering properties of the modulator itself are analyzed using a Monte Carlo simulation. Results: All reconstructions show strong improvements of image quality. To quantify the results, all images are compared to reference images (ideal simulations and collimated scans). Conclusions: The proposed modulator-based scatter reduction algorithm may open the field of flat detector-based imaging to become a quantitative modality. This may have significant impact on C-arm imaging and on image-guided radiation therapy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Hybrid radiosity-SP{sub 3} equation based bioluminescence tomography reconstruction for turbid medium with low- and non-scattering regions

To provide an ideal solution for a specific problem of gastric cancer detection in which low-scattering regions simultaneously existed with both the non- and high-scattering regions, a novel hybrid radiosity-SP{sub 3} equation based reconstruction algorithm for bioluminescence tomography was proposed in this paper. In the algorithm, the third-order simplified spherical harmonics approximation (SP{sub 3}) was combined with the radiosity equation to describe the bioluminescent light propagation in tissues, which provided acceptable accuracy for the turbid medium with both low- and non-scattering regions. The performance of the algorithm was evaluated with digital mouse based simulations and a gastric cancer-bearing mouse based in situ experiment. Primary results demonstrated the feasibility and superiority of the proposed algorithm for the turbid medium with low- and non-scattering regions.

60 APPLIED LIFE SCIENCES↗