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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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CFD Simulations of Landing and Takeoff CRM High-Lift Configurations

Numerical simulations have been performed for a conventional high-lift version of the Common Research Model (CRM) model corresponding to landing and take- off configurations. Computed values of lift and drag for the landing configuration are compared with the experimental data acquired in the 14- by 22-Foot Subsonic Tunnel (14×22) at the NASA Langley Research Center (LaRC). Simulations replicated the experimentally observed improvements in the lift characteristics in the presence of a nacelle chine. Flow visualization images indicate that vortices generated by the nacelle chine reduce flow separation regions on the upper surface of the wing at higher angles of attack. Based on such observations, the take-off configuration considered is also equipped with a nacelle chine, and testing of this configuration is planned in the 14×22 tunnel in near future. Preliminary solutions are also presented to explore the feasibility of using a localized flap gap blowing (LFGB) active flow control concept for improving the aerodynamic performance at take-off conditions.

aerodynamics↗
DOE OSTI2012

Analog Video Authentication and Seal Verification Equipment Development

Under contract to the US Department of Energy in support of arms control treaty verification activities, the Savannah River National Laboratory in conjunction with the Pacific Northwest National Laboratory, the Idaho National Laboratory and Milagro Consulting, LLC developed equipment for use within a chain of custody regime. This paper discussed two specific devices, the Authentication Through the Lens (ATL) analog video authentication system and a photographic multi-seal reader. Both of these devices have been demonstrated in a field trial, and the experience gained throughout will also be discussed. Typically, cryptographic methods are used to prove the authenticity of digital images and video used in arms control chain of custody applications. However, in some applications analog cameras are used. Since cryptographic authentication methods will not work on analog video streams, a simple method of authenticating analog video was developed and tested. A photographic multi-seal reader was developed to image different types of visual unique identifiers for use in chain of custody and authentication activities. This seal reader is unique in its ability to image various types of seals including the Cobra Seal, Reflective Particle Tags, and adhesive seals. Flicker comparison is used to compare before and after images collected with the seal reader in order to detect tampering and verify the integrity of the seal.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Flow Boiling Heat Transfer Characteristics of Water for Metal-foam-filled Horizontal Tubes

The goal of this paper is to enhance the in-tube flow boiling heat transfer of water while accounting for potential increase in pressure drop. Metal foams are a class of cellular structure with large surface-area-to-volume ratio and tortuous structure which has shown promising results for various energy conversion and storage applications. The higher heat transfer area and higher nucleation sites density due to the porous media can effectively enhance the heat transfer of water in both single-phase and two-phase operations. This paper presents the local heat transfer and pressure drop measurements of water in a partially metal-foam-filled horizontal copper tube. The ranges of parameters in the experiments are: mass flux from 80 to 200 kg/s-m2, heat flux from 3.5 to 105 kW/m2, and vapor quality from subcooled to 0.3. The results in the metal-foam-filled tube are compared with that of the bare copper tube. The effect of metal foam on the thermal hydraulic characteristics is discussed and analyzed. In addition, the two-phase flow behavior in a transparent tube filled with the same metal foam was visualized and investigated by high-speed imaging system. The experiments were also conducted in the tube without the metal foam for comparison.

Nawaz, Kashif↗
DOE OSTI2016

Transperineal Prostate Core Needle Biopsy: A Comparison of Coaxial Versus Noncoaxial Method in a Randomised Trial

PurposeTo compare the procedural time and complication rate of coaxial technique with those of noncoaxial technique in transperineal prostate biopsy.Materials and MethodsTransperineal prostate biopsy with coaxial (first group, n = 120) and noncoaxial (second group, n = 120) methods was performed randomly in 240 patients. The procedural time was recorded. The level of pain experienced during the procedure was assessed on a visual analogue scale (VAS), and the rate of complications was evaluated in comparison of the two methods.ResultsThe procedural time was significantly shorter in the first group (p < 0.001). In the first group, pain occurred less frequently (p = 0.002), with a significantly lower VAS score being experienced (p < 0.002). No patient had post procedural fever. Haematuria (p = 0.029) and haemorrhage from the site of biopsy (p < 0.001) were seen less frequently in the first group. There was no significant difference in the rate of urethral haemorrhage between the two groups (p = 0.059). Urinary retention occurred less commonly in the first group (p = 0.029). No significant difference was seen in the rate of dysuria between the two groups (p = 0.078).ConclusionsTransperineal prostate biopsy using a coaxial needle is a faster and less painful method with a lower rate of complications compared with conventional noncoaxial technique.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2015

Long-term Results of the UCSF-LBNL Randomized Trial: Charged Particle With Helium Ion Versus Iodine-125 Plaque Therapy for Choroidal and Ciliary Body Melanoma

Purpose: Relevant clinical data are needed given the increasing national interest in charged particle radiation therapy (CPT) programs. Here we report long-term outcomes from the only randomized, stratified trial comparing CPT with iodine-125 plaque therapy for choroidal and ciliary body melanoma. Methods and Materials: From 1985 to 1991, 184 patients met eligibility criteria and were randomized to receive particle (86 patients) or plaque therapy (98 patients). Patients were stratified by tumor diameter, thickness, distance to disc/fovea, anterior extension, and visual acuity. Tumors close to the optic disc were included. Local tumor control, as well as eye preservation, metastases due to melanoma, and survival were evaluated. Results: Median follow-up times for particle and plaque arm patients were 14.6 years and 12.3 years, respectively (P=.22), and for those alive at last follow-up, 18.5 and 16.5 years, respectively (P=.81). Local control (LC) for particle versus plaque treatment was 100% versus 84% at 5 years, and 98% versus 79% at 12 years, respectively (log rank: P=.0006). If patients with tumors close to the disc (<2 mm) were excluded, CPT still resulted in significantly improved LC: 100% versus 90% at 5 years and 98% versus 86% at 12 years, respectively (log rank: P=.048). Enucleation rate was lower after CPT: 11% versus 22% at 5 years and 17% versus 37% at 12 years, respectively (log rank: P=.01). Using Cox regression model, likelihood ratio test, treatment was the most important predictor of LC (P=.0002) and eye preservation (P=.01). CPT was a significant predictor of prolonged disease-free survival (log rank: P=.001). Conclusions: Particle therapy resulted in significantly improved local control, eye preservation, and disease-free survival as confirmed by long-term outcomes from the only randomized study available to date comparing radiation modalities in choroidal and ciliary body melanoma.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

POGO-DB—a database of pairwise-comparisons of genomes and conserved orthologous genes

POGO-DB (http://pogo.ece.drexel.edu/) provides an easy platform for comparative microbial genomics. POGO-DB allows users to compare genomes using pre-computed metrics that were derived from extensive computationally intensive BLAST comparisons of >2000 microbes. These metrics include (i) average protein sequence identity across all orthologs shared by two genomes, (ii) genomic fluidity (a measure of gene content dissimilarity), (iii) number of ‘orthologs’ shared between two genomes, (iv) pairwise identity of the 16S ribosomal RNA genes and (v) pairwise identity of an additional 73 marker genes present in >90% prokaryotes. Users can visualize these metrics against each other in a 2D plot for exploratory analysis of genome similarity and of how different aspects of genome similarity relate to each other. The results of these comparisons are fully downloadable. In addition, users can download raw BLAST results for all or user-selected comparisons. Therefore, we provide users with full flexibility to carry out their own downstream analyses, by creating easy access to data that would normally require heavy computational resources to generate. POGO-DB should prove highly useful for researchers interested in comparative microbiology and benefit the microbiome/metagenomic communities by providing the information needed to select suitable phylogenetic marker genes within particular lineages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Integration of conductivity probe with optical and x-ray imaging systems for local air–water two-phase flow measurement

Various techniques have been developed in the past to measure different parameters in two-phase flow. Among them, the multi-sensor conductivity probe is one of the most commonly used techniques because of its good overall performance. Recently, more advanced techniques such as high speed optical imaging and fast X-ray densitometry become mature and easily accessible. The main objective of this work is to compare and integrate these different techniques, to achieve a more accurate and complete measurement of two-phase flow. In this study, a double-sensor conductivity probe is used to measure the local time-averaged parameters along the radial direction of a 2.54 cm ID round pipe. An X-ray densitometry system is used to measure the chordal averaged void fraction and gas velocity. A high speed camera system is employed to provide the visualization of the two-phase flow structure and obtain the line-averaged gas velocity. The unique advantages and main uncertainties of these three techniques are analyzed by considering their measuring principles and possible issues in practical measurements. From this, a method is developed to integrate the data obtained by the optical and X-ray systems into the probe signal processing. Finally, a better accuracy could be achieved using this method for various local two-phase flow parameters including void fraction, bubble velocity and superficial gas velocity, compared to the original probe measurements.

42 ENGINEERING↗
DOE OSTI2026

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗
DOE OSTI2014

Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization software Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Comparative Effects of Radiation Sterilization Modality on Medical PVC Tubing

As the production volume of single-use, polymer-based medical devices increases each year, so does the need for throughput capacity to sterilize the devices. Around 80% of radiation-sterilized devices are processed using gamma-ray radiation from industrial cobalt-60 sources. Supply chain, security, and disposal concerns are prompting manufacturers and contract sterilizers to explore alternatives to irradiation using cobalt-60 gamma-rays, such as electron beam (E-beam) and X-ray radiation. Advantages of these ‘machine’ sources over radioisotope-based sources are that they do not decay, a characteristic that requires cobalt-60 to be replaced over time, they can be turned off when not in use, and they do not represent the same level of concern regarding misuse. One of the barriers to direct transition from gamma-ray sterilization to E-beam or X-ray sterilization is concern over the relatively unknown effects of sterilization dose of these alternative modalities on the performance of medical device polymers. Commercially available medical devices sterilized with gamma-ray irradiation exhibit acceptable device function, acceptable mechanical performance, and acceptable discoloration. To be viable, alternate sterilization methods must not only achieve acceptable sterilization, but the process must also result in a product with functional, mechanical, and visual effects acceptable to customers and the regulator. Flexible polyvinyl chloride (PVC) is a plastic material that is commonly found in single-use medical devices and is known for its sensitivity to radiation processing. For instance, transparent PVC is known to yellow upon irradiation. To encouraging sterilization alternatives to cobalt-60 gamma-ray, we directly compared the effects of gamma-ray, E-beam, and X-ray radiation exposure at similar sterilization-relevant doses on key properties of medical grade PVC tubing.

cobalt-60↗
DOE OSTI2014

TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion

Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, segment, register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung segmentation algorithm was designed and 4D lung segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is <±2% and the time saving is by 1–2 orders of magnitude. Conclusion: A framework of 4D toolkit has been developed to analyze thoracic 4DCT automatically or interactively, facilitating both investigational and clinical use. More software tools are under development for automatic analysis of other 4D imaging modalities. This research is in part supported by NIH (U54CA137788/132378) and City Seed FY13(Grant No. 93348-14 01). AY would like to thank MSKCC summer medical student research program supported by National Cancer Institute and hosted by Department of Medical Physics at MSKCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Dentalmaps: Automatic Dental Delineation for Radiotherapy Planning in Head-and-Neck Cancer

Purpose: To propose an automatic atlas-based segmentation framework of the dental structures, called Dentalmaps, and to assess its accuracy and relevance to guide dental care in the context of intensity-modulated radiotherapy. Methods and Materials: A multi-atlas-based segmentation, less sensitive to artifacts than previously published head-and-neck segmentation methods, was used. The manual segmentations of a 21-patient database were first deformed onto the query using nonlinear registrations with the training images and then fused to estimate the consensus segmentation of the query. Results: The framework was evaluated with a leave-one-out protocol. The maximum doses estimated using manual contours were considered as ground truth and compared with the maximum doses estimated using automatic contours. The dose estimation error was within 2-Gy accuracy in 75% of cases (with a median of 0.9 Gy), whereas it was within 2-Gy accuracy in 30% of cases only with the visual estimation method without any contour, which is the routine practice procedure. Conclusions: Dose estimates using this framework were more accurate than visual estimates without dental contour. Dentalmaps represents a useful documentation and communication tool between radiation oncologists and dentists in routine practice. Prospective multicenter assessment is underway on patients extrinsic to the database.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Label-Free In Situ Chemical Characterization of Amyloid Plaques in Human Brain Tissues

The accumulation of amyloid plaques and increased brain redox burdens are neuropathological hallmarks of Alzheimer’s disease. Altered metabolism of essential biometals is another feature of Alzheimer’s, with amyloid plaques representing sites of disturbed metal homeostasis. Despite these observations, metal-targeting disease treatments have not been therapeutically effective to date. A better understanding of amyloid plaque composition and the role of the metals associated with them is critical. To establish this knowledge, the ability to resolve chemical variations at nanometer length scales relevant to biology is essential. Here, we present a methodology for the label-free, nanoscale chemical characterization of amyloid plaques within human Alzheimer’s disease tissue using synchrotron X-ray spectromicroscopy. Our approach exploits a C–H carbon absorption feature, consistent with the presence of lipids, to visualize amyloid plaques selectively against the tissue background, allowing chemical analysis to be performed without the addition of amyloid dyes that alter the native sample chemistry. Using this approach, we show that amyloid plaques contain elevated levels of calcium, carbonates, and iron compared to the surrounding brain tissue. Chemical analysis of iron within plaques revealed the presence of chemically reduced, low-oxidation-state phases, including ferromagnetic metallic iron. The zero-oxidation state of ferromagnetic iron determines its high chemical reactivity and so may contribute to the redox burden in the Alzheimer’s brain and thus drive neurodegeneration. Ferromagnetic metallic iron has no established physiological function in the brain and may represent a target for therapies designed to lower redox burdens in Alzheimer’s disease. Additionally, ferromagnetic metallic iron has magnetic properties that are distinct from the iron oxide forms predominant in tissue, which might be exploitable for the in vivo detection of amyloid pathologies using magnetically sensitive imaging. We anticipate that this label-free X-ray imaging approach will provide further insights into the chemical composition of amyloid plaques, facilitating better understanding of how plaques influence the course of Alzheimer’s disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Photophysics and Electronic Structure of Lateral Graphene/MoS 2 and Metal/MoS 2 Junctions

Integration of semiconducting transition metal dichalcogenides (TMDs) into functional optoelectronic circuitries requires an understanding of the charge transfer across the interface between the TMD and the contacting material. In this work, we use spatially resolved photocurrent microscopy to demonstrate electronic uniformity at the epitaxial graphene/molybdenum disulfide (EG/MoS 2 ) interface. A 10× larger photocurrent is extracted at the EG/MoS 2 interface when compared to the metal (Ti/Au)/MoS 2 interface. This is supported by semi-local density functional theory (DFT), which predicts the Schottky barrier at the EG/MoS 2 interface to be ~2× lower than that at Ti/MoS 2 . We provide a direct visualization of a 2D material Schottky barrier through combination of angle-resolved photoemission spectroscopy with spatial resolution selected to be ~300 nm (nano-ARPES) and DFT calculations. A bending of ~500 meV over a length scale of ~2-3 μm in the valence band maximum of MoS 2 is observed via nano-ARPES. We explicate a correlation between experimental demonstration and theoretical predictions of barriers at graphene/TMD interfaces. Spatially resolved photocurrent mapping allows for directly visualizing the uniformity of built-in electric fields at heterostructure interfaces, providing a guide for microscopic engineering of charge transport across heterointerfaces. This simple probe-based technique also speaks directly to the 2D synthesis community to elucidate electronic uniformity at domain boundaries alongside morphological uniformity over large areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A comparison of light-coupling into high and low index nanostructured photovoltaic thin films

Periodically structured electrodes are typically introduced to thin-film photovoltaics for the purpose of light management. Highly effective light-trapping and optimal in-coupling of light is crucial to enhance the overall device performance in such thin-film systems. Here, wavelength-scale structures are transferred via direct laser interference patterning to electron-selective TiO{sub 2} electrodes. Two representative thin-film solar cell architectures are deposited on top: an organic solar cell featuring blended P3HT:PCBM as active material, and a hybrid solar cell with Sb{sub 2}S{sub 3} as inorganic active material. A direct correlation in the asymmetry in total absorption enhancement and in structure-induced light in-coupling is spectroscopically observed for the two systems. The structuring is shown to be beneficial for the total absorption enhancement if a high n active material is deposited on TiO{sub 2}, but detrimental for a low n material. The refractive indices of the employed materials are determined via spectroscopic ellipsometry. The study outlines that the macroscopic Fresnel equations can be used to investigate the spectroscopically observed asymmetry in light in-coupling at the nanostructured TiO{sub 2} active material interfaces by visualizing the difference in reflectivity caused by the asymmetry in refractive indices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sub-millisecond keyhole pore detection in laser powder bed fusion using sound and light sensors and machine learning

Laser powder bed fusion is a mainstream additive manufacturing technology widely used to manufacture complex parts in prominent sectors, including aerospace, biomedical, and automotive industries. However, during the printing process, the presence of an unstable vapor depression can lead to a type of defect called keyhole porosity, which is detrimental to the part quality. In this study, we developed an effective approach to locally detect the generation of keyhole pores during the printing process by leveraging machine learning and a suite of optical and acoustic sensors. Simultaneous synchrotron x-ray imaging allows the direct visualization of pore generation events inside the sample, offering high-fidelity ground truth. A neural network model adopting SqueezeNet architecture using single-sensor data was developed to evaluate the fidelity of each sensor for capturing keyhole pore generation events. Our comparative study shows that the near infrared images gave the highest prediction accuracy, followed by 100 kHz and 20 kHz microphones, and the photodiode sensitive to processing laser wavelength had the lowest accuracy. Using a single sensor, over 90% prediction accuracy can be achieved with a temporal resolution as short as 0.1 ms. A data fusion scheme was also developed with features extracted using SqueezeNet neural network architecture and classification using different machine learning algorithms. Our work demonstrates the correlation between the characteristic optical and acoustic emissions and the keyhole oscillation behavior, and thereby provides strong physics support for the machine learning approach.

36 MATERIALS SCIENCE↗
DOE OSTI2017

On coincident loop transient electromagnetic induction logging

Coincident loop transient induction wireline logging is examined as the borehole analog of the well-known land and airborne time-domain electromagnetic (EM) method. The concept of whole-space late-time apparent resistivity is modified from the half-space version commonly used in land and airborne geophysics and applied to the coincident loop voltages produced from various formation, borehole, and invasion models. Given typical tool diameters, off-time measurements with such an instrument must be made on the order of nanoseconds to microseconds — much more rapidly than for surface methods. Departure curves of the apparent resistivity for thin beds, calculated using an algorithm developed to model the transient response of a loop in a multilayered earth, indicate that the depth of investigation scales with the bed thickness. Modeled resistivity logs are comparable in accuracy and resolution with standard frequency-domain focused induction logs. However, if measurement times are longer than a few microseconds, the thicknesses of conductors can be overestimated, whereas resistors are underestimated. Thin-bed resolution characteristics are explained by visualizing snapshots of the EM fields in the formation, where a conductor traps the electric field while two current maxima are produced in the shoulder beds surrounding a resistor. Radial profiling is studied using a concentric cylinder earth model. Results found that true formation resistivity can be determined in the presence of either oil- or water-based mud, although in the latter case, measurements must be taken several orders of magnitude later in time. Lastly, the ability to determine true formation resistivity is governed by the degree that the EM field heals after being distorted by borehole fluid and invasion, a process visualized and particularly evident in the case of conductive water-based mud.

58 GEOSCIENCES↗