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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 325 records · Page 18

Zero-Valent Iron Permeable Reactive Barrier to Remediate Volatile Organic Compounds in Groundwater - 20209

The US DOE-SRS, the US EPA, and the South Carolina Department of Health and Environmental Control determined it was appropriate to perform a non-time critical removal action at the P-Area Groundwater Operable Unit at the SRS to reduce the mass and downgradient transport of trichloroethylene in the P-Area groundwater plume. Contaminated groundwater discharges to a nearby stream, Steel Creek, within the SRS boundaries, resulting in trichloroethylene concentrations above the maximum contaminant level. Impact to surface water is limited in areal extent and supported by recently collected characterization data. The P-Area Groundwater Operable Unit encompasses the groundwater beneath an industrial area within SRS, P Area, where the P-Reactor once operated. The boundaries of the P-Area Groundwater Operable Unit extend northwest to Steel Creek, northeast toward PAR Pond, and southeast to Meyers Branch. Groundwater in the Upper Three Runs Aquifer of the P-Area Groundwater Operable Unit has been impacted by reactor and facility operations between 1954 and 1991, including tritium and volatile organic compounds. The P-Area surface units contributing to groundwater contamination were remediated as part of the P-Area Operable Unit in 2011. The P-Reactor closure is one of the first of its kind in the DOE Complex and is one of only a few full-sized production reactors in the US to undergo completion of final closure activities. The nature and extent of groundwater contamination was determined using a variety of investigative approaches such as groundwater monitoring wells, direct-push technology, and surface water samples. Groundwater contamination associated with trichloroethylene is primarily exhibited in a narrow plume that extends from the source area at P-Reactor and west to Steel Creek. Maximum contaminant level exceedances in groundwater occur over an area of ∼6.9 hectares for trichloroethylene with concentrations as high as 7.7 milligrams per liter. To the west of the P-Area facility area, the trichloroethylene groundwater plume is controlled by a buried geologic feature, assumed to be an old stream bed, that further narrows the groundwater plume in what has been designated as the 'neck area.' This narrowing of the groundwater plume provides an ideal location for a treatment barrier. The non-time critical removal action alternative chosen is to install a zero-valent iron permeable reactive barrier within the neck area of the trichloroethylene groundwater plume, perpendicular to groundwater flow direction. This technology will provide a treatment barrier that will reduce trichloroethylene groundwater concentrations by 90% and has an anticipated useful life of at least 25 years. A pre-design investigation was performed in the neck area to confirm site lithology, hydrogeology, geochemistry, and extent of trichloroethylene contamination prior to a final design. A treatability study, conducted as part of the pre-design investigation, indicated that the subsurface and groundwater in the PArea Groundwater Operable Unit is compatible with the zero-valent iron and will not lead to excessive buildup from mineralization/precipitation or biofouling. Probabilistic modeling was conducted using field and laboratory data to determine the expected performance of the zero-valent iron permeable reactive barrier. The model simulations indicated that a 3.81-centimeter thick barrier would provide greater than 90% reduction of trichloroethylene groundwater concentration. The final design of the zero-valent iron permeable reactive barrier is a barrier that will extend 80.5 linear meters in a 'zigzag' orientation to best transect the trichloroethylene plume and account for varying groundwater flow. The barrier will be installed from 13.7 meters below ground surface to 41.1 meters below ground surface for 65.8 linear meters and from 13.7 meters below ground surface to 36.6 meters below ground surface for 14.6 linear meters, the base of which is 'keyed' into a low permeability zone. The barrier is designed to a thickness of 10.2 centimeters, which was determined to reduce the trichloroethylene groundwater concentrations by greater than 90% with a safety factor of 2.67. A total of approximately 689 metric tons of zero-valent iron will be injected through 22 injection wells spaced 3.66 meters apart, using guar to suspend the zero-valent iron. Zero-valent iron permeable reactive barrier construction will be monitored through 23 installed resistivity receivers offset 7.32 meters from the zerovalent iron permeable reactive barrier. The zero-valent iron will be energized with a low-voltage 100 Hertz signal during injection and will be monitored using the resistivity receivers to ensure complete coalescence of the zero-valent iron permeable reactive barrier. The zero-valent iron was sized to have a hydraulic conductivity greater than the natural subsurface, thus promoting groundwater flow through the barrier. As contaminated groundwater contacts the zero-valent iron, volatile organic compounds, including trichloroethylene, are immediately degraded to harmless compounds such as ethylene. The performance of the zero-valent iron permeable reactive barrier will be monitored using three upgradient monitoring well clusters, six downgradient monitoring well clusters, and four in-wall monitoring wells. The in-wall monitoring wells will indicate immediate reduction of trichloroethylene mass in the groundwater and allow analyses of the zero-valent iron permeable reactive barrier health. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Improvements to Modeling Capabilities of ATF Concepts in the BISON Fuel Performance Code

Research into accident tolerant materials for the fuel and cladding in Light Water Reactors has been at the forefront of the nuclear fuel research community since the events that occurred at the Fukushima Daiichi nuclear power plant in March 2011. Accident tolerant materials are defined as those that provide significantly increased response time in the event of an accident while providing similar or improved performance as the conventional UO{sub 2}/zirconium-based cladding fuel rods during normal operation. In particular, qualitative attributes for materials with enhanced accident tolerance include improved reaction (e.g., oxidation) kinetics with steam, resulting in lower hydrogen (or other combustible gases) generation rate, while maintaining acceptable thermo-mechanical properties, fuel-clad interactions, and fission-product behavior. Through it's Office of Nuclear Energy, the United States Department of Energy (U.S. DOE) has accelerated research in this area through the Fuel Cycle Research and Development (FCRD) Advanced Fuels Campaign (AFC). The goal of the AFC Accident Tolerant Fuel (ATF) program is to guide selection of promising concepts for insertion into a commercial reactor as part of a lead test rod or assembly in 2022. Given the aggressive development schedule, it is impossible to perform a comprehensive set of experiments to provide material characterization data. Therefore, the AFC is utilizing computational analysis tools in an effort to understand the proposed accident tolerant materials. The two materials of interest in this work are iron-chromium-aluminum (FeCrAl) cladding and U{sub 3}Si{sub 2}. From a fuel performance standpoint, the correlations available to describe the behavior of these two materials is limited. Therefore, as additional experimental data becomes available and correlations are updated, the fuel performance models must be updated as well to assure that the material models reflect the latest experimental findings. In this paper we demonstrate the importance of utilizing the latest state-of-the-art models for fuel performance simulations by comparing the change in the updated thermal conductivity model for U{sub 3}Si{sub 2} fuel and oxidation model for FeCrAl cladding alloys using the BISON fuel performance code under normal operating conditions. The results indicate that the latest thermal conductivity model for U{sub 3}Si{sub 2} results in fuel centerline temperatures that are on average approximately 3% higher than the previous model. For the oxidation behavior of FeCrAl alloys the new model predicts observable but small oxide thickness (6 μm) compared to the previous model which predicted essentially zero oxide scale formation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hydraulic fracture characterization by integrating multidisciplinary data from the Hydraulic Fracturing Test Site 2 (HFTS-2)

Various technologies have traditionally been used to monitor and describe hydraulic fractures from different perspectives. This work demonstrates the value of data integration for hydraulic fracture characterization when multiple data resources are available. The Hydraulic Fracturing Test Site 2 (HFTS 2) is a hydraulic fracturing research project in the Delaware Basin with multiple surveillance techniques including fiber optics sensing, microseismic, pressure/temperature gauges, etc. We integrated the multidisciplinary data from the HFTS-2 to characterize hydraulic fractures. The integrated data revealed interesting fracture propagation features including layering, vertical propagation affected by pore pressure gradient, and different microseismic activities due to difference in-situ conditions. Furthermore, these findings can be insightful for understanding hydraulic fracture propagation. The comparison among multiple surveillance data also helps us to evaluate the roles of various surveillance technologies and provides us experience to make informative decisions depending on different monitoring objectives.

58 GEOSCIENCES↗

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for the National Park Service: Golden Gate National Recreation Area

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy's Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (ITSNA) to collect data on federal fleet operations as part of the Advanced Vehicle Testing Activity's Federal Fleet Vehicle Data Logging and Characterization study. The Advanced Vehicle Testing Activity study seeks to collect data to validate the utilization of advanced electric drive vehicle transportation. This report focuses on the Golden Gate National Recreation Area (GGNRA) fleet to identify daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support the successful introduction of plug-in electric vehicles (PEVs) into the agencies' fleets. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle or plug-in hybrid electric vehicle (PHEV) (collectively PEVs) can fulfill the mission requirements. GGNRA identified 182 vehicles in its fleet, which are under the management of the U.S. General Services Administration. Fleet vehicle mission categories are defined in Section 4, and while the GGNRA vehicles conduct many different missions, only two (i.e., support and law enforcement missions) were selected by agency management to be part of this fleet evaluation. The selected vehicles included sedans, trucks, and sport-utility vehicles. This report will show that battery electric vehicles and/or PHEVs are capable of performing the required missions and providing an alternative vehicle for support vehicles and PHEVs provide the same for law enforcement, because each has a sufficient range for individual trips and time is available each day for charging to accommodate multiple trips per day. These charging events could occur at the vehicle home base, high-use work areas, or intermediately along routes that the vehicles frequently travel. Replacement of vehicles in the current fleet would result in significant reductions in the emission of greenhouse gases and petroleum use, while also reducing fuel costs. The San Francisco Bay Area is a leader in the adoption of PEVs in the United States. PEV charging stations, or more appropriately identified as electric vehicle supply equipment, located on the GGNRA facility would be a benefit for both GGNRA fleets and general public use. Fleet drivers and park visitors operating privately owned PEVs benefit by using the charging infrastructure. ITSNA recommends location analysis of the GGNRA site to identify the optimal placement of the electric vehicle supply equipment station. ITSNA recognizes the support of Idaho National Laboratory and ICF International for their efforts to initiate communication with the National Parks Service and GGNRA for participation in the study. ITSNA is pleased to provide this report and is encouraged by the high interest and support from the National Park Service and GGNRA personnel.

99 GENERAL AND MISCELLANEOUS↗

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for the National Park Service: Fort Vancouver National Historic Site

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for the U.S. Department of Energy’s Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (ITSNA) to collect data on federal fleet operations as part of the Advanced Vehicle Testing Activity’s Federal Fleet Vehicle Data Logging and Characterization study. The Advanced Vehicle Testing Activity study seeks to collect data to validate the use of advanced electric drive vehicle transportation.

33 ADVANCED PROPULSION SYSTEMS↗

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for the United States Forest Service: Caribou-Targhee National Forest

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC contracted with Intertek Testing Services, North America (ITSNA) to collect and evaluate data on federal fleet operations as part of the Advanced Vehicle Testing Activity’s Federal Fleet Vehicle Data Logging and Characterization study. The Advanced Vehicle Testing Activity study seeks to collect and evaluate data to validate the utilization of advanced electric drive vehicle transportation. This report focuses on the Caribou-Targhee National Forest (CTNF) fleet to identify daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support the successful introduction of plug-in electric vehicles (PEVs) into the agencies’ fleets. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle (BEV) or plug-in hybrid electric vehicle (PHEV) (collectively plug-in electric vehicles, or PEVs) can fulfill the mission requirements. ITSNA acknowledges the support of Idaho National Laboratory and CTNF for participation in the study. ITSNA is pleased to provide this report and is encouraged by enthusiasm and support from the Forest Service and CTNF personnel.

33 ADVANCED PROPULSION SYSTEMS↗

Tensor Analysis Methods for Activity Characterization in Spatiotemporal Data

Tensor (multiway array) factorization and decomposition offers unique advantages for activity characterization in spatio-temporal datasets because these methods are compatible with sparse matrices and maintain multiway structure that is otherwise lost in collapsing for regular matrix factorization. This report describes our research as part of the PANTHER LDRD Grand Challenge to develop a foundational basis of mathematical techniques and visualizations that enable unsophisticated users (e.g. users who are not steeped in the mathematical details of matrix algebra and mulitway computations) to discover hidden patterns in large spatiotemporal data sets.

97 MATHEMATICS AND COMPUTING↗

Public Data Set: Initial Characterization of Electron Temperature and Density Profiles in PEGASUS Spherical Tokamak Discharges Driven Solely by Local Helicity Injection

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in G.M. Bodner et al., ‘Initial Characterization of Electron Temperature and Density Profiles in PEGASUS Spherical Tokamak Discharges Driven Solely by Local Helicity Injection,’ Physics of Plasmas 28, 102504 (2021) and its erratum in Physics of Plasmas 31, 129904 (2024).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electricity consumption patterns within cities: application of a data-driven settlement characterization method

Urban areas presently consume around 75% of global primary energy supply, which is expected to significantly increase in the future due to urban growth. Having sustainable, universal energy access is a pressing challenge for most parts of the globe. Understanding urban energy consumption patterns may help to address the challenges to urban sustainability and energy security. However, urban energy analyses are severely limited by the lack of urban energy data. Such datasets are virtually non-existent for the developing countries. As per current projections, most of the new urban growth is bound to occur in these data-starved regions. Hence, there is an urgent need of research methods for monitoring and quantifying urban energy utilization patterns. Here, we apply a data-driven approach to characterize urban settlements based on their formality, which is then used to assess intra-urban urban energy consumption in Johannesburg, South Africa; Sana’a, Yemen; and Ndola, Zambia. Electricity is the fastest growing energy fuel. By analyzing the relationship between the settlement types and the corresponding nighttime light emission, a proxy of electricity consumption, we assess the differential electricity consumption patterns. Our study presents a simple and scalable solution to fill the present data void to understand intra-city electricity consumption patterns.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Bayesian Inversion of Seismic and Electromagnetic Data for Marine Gas Reservoir Characterization Using Multi-chain Markov Chain Monte Carlo Sampling

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

Ren, Huiying↗

AVTA Federal Fleet PEV Readiness Data Logging and Characterization Study for NASA Glenn Research Center

The Advanced Vehicle Testing Activity’s study seeks to collect and evaluate data to validate the utilization of advanced plug-in electric vehicle (PEV) transportation. This report focuses on the NASA Glenn Research Center (GRC) fleet to identify daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support the successful introduction of PEVs into the agencies’ fleets. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle or plug-in hybrid electric vehicle (collectively referred to as PEVs) can fulfill the mission requirements.

33 ADVANCED PROPULSION SYSTEMS↗

OpenCRUMS USA: An Open Machine Learning Framework for Characterizing Variability in Aerosol Reanalysis Data

Advances in artificial intelligence (AI) have called for exploring how these techniques can be used for exploring patterns in large climate datasets. To that regard, the U.S. Department of Energy AI for Earth System Predictability (AI4ESP) supported a pilot initiative called the Open Classification of Regimes in the Southeast USA (OpenCRUMS USA) project to explore how AI can be used to characterize modes of spatial variability in large climate datasets. For this study, we focus on comparing two methods for characterizing the modes of spatial variability of surface aerosol concentration over the Houston region: empirical orthogonal functions (EOFs) and layerwise relevance propagation (LRP) applied to a convolutional neural network (CNN) classifier. We show that EOF analysis typically attributes spatial variability modes that span all of southeast Texas, prohibiting the attribution of spatial variability to localized regions. However, using LRP on the CNN classifier resolves the explanatory parameters at a finer spatial resolution than EOFs. This allows for the attribution of the spatial variability of surface aerosols to local regions of organic carbon which was not possible using EOFs. In addition, the LRP analysis also suggests that synoptic-scale transport of dust is most prevalent during anticyclonic and pretrough synoptic conditions as categorized by self-organizing maps.

54 ENVIRONMENTAL SCIENCES↗

Data-driven Resilience Characterization of Control Dynamical Systems

In this paper, we define and quantify resiliency of a power network and propose data-driven algorithms for computing the same for the power grid. To do this, we use the Koopman operator framework to lift the controlled dynamical system to an abstract (possibly higher) dimensional space, where the evolution is linear. The linear system representation allows us to relate small time local controllability and observability of a general nonlinear control system to the controllability and observability of the lifted linear system. Finally, we define the resiliency of the underlying power grid in terms of the controllability and observability gramians of the lifted linear system. We illustrate the proposed approach to compute the resiliency metrics on time-series data obtained from a microgrid.

koopman operator, resilience, control↗

Data for Discovery, Characterization, and Application of Chromosomal Integration Sites for Stable Heterologous Gene Expression in Rhodotorula toruloides

Rhodotorula toruloides is a non-model, oleaginous yeast uniquely suited to produce acetyl-CoA-derived chemicals. However, the lack of well-characterized genomic integration sites has impeded the metabolic engineering of this organism. Here we report a set of computationally predicted and experimentally validated chromosomal integration sites in R. toruloides . We first implemented an in silico platform by integrating essential gene information and transcriptomic data to identify candidate sites that meet stringent criteria. We then conducted a full experimental characterization of these sites, assessing integration efficiency, gene expression levels, impact on cell growth, and long-term expression stability. Among the identified sites, 12 exhibited integration efficiencies of 50% or higher, making them sufficient for most metabolic engineering applications. Using selected high-efficiency sites, we achieved simultaneous double and triple integrations and efficiently integrated long functional pathways (up to 14.7 kb). Additionally, we developed a new inducible marker recycling system that allows multiple rounds of integration at our characterized sites. We validated this system by performing five sequential rounds of GFP integration and three sequential rounds of MaFAR integration for fatty alcohol production, demonstrating, for the first time, precise gene copy number tuning in R. toruloides . These characterized integration sites should significantly advance metabolic engineering efforts and future genetic tool development in R. toruloides .

Conversion↗

Data sharing report characterization of the surveillance and maintenance project miscellaneous process inventory waste items Oak Ridge National Laboratory, Oak Ridge, TN

The U.S. Department of Energy (DOE) Oak Ridge Office of Environmental Management (EM-OR) requested Oak Ridge Associated Universities (ORAU), working under the Oak Ridge Institute for Science and Education (ORISE) contract, to provide technical and independent waste management planning support under the American Recovery and Reinvestment Act (ARRA). Specifically, DOE EM-OR requested ORAU to plan and implement a sampling and analysis campaign to target certain items associated with URS|CH2M Oak Ridge, LLC (UCOR) surveillance and maintenance (S&M) process inventory waste. Eight populations of historical and reoccurring S&M waste at the Oak Ridge National Laboratory (ORNL) have been identified in the Waste Handling Plan for Surveillance and Maintenance Activities at the Oak Ridge National Laboratory, DOE/OR/01-2565&D2 (WHP) (DOE 2012) for evaluation and processing for final disposal. This waste was generated during processing, surveillance, and maintenance activities associated with the facilities identified in the process knowledge (PK) provided in Appendix A. A list of items for sampling and analysis were generated from a subset of materials identified in the WHP populations (POPs) 4, 5, 6, 7, and 8, plus a small number of items not explicitly addressed by the WHP. Specifically, UCOR S&M project personnel identified 62 miscellaneous waste items that would require some level of evaluation to identify the appropriate pathway for disposal. These items are highly diverse, relative to origin; composition; physical description; contamination level; data requirements; and the presumed treatment, storage, and disposal facility (TSDF). Because of this diversity, ORAU developed a structured approach to address item-specific data requirements necessary for acceptance in a presumed TSDF that includes the Environmental Management Waste Management Facility (EMWMF)—using the approved Waste Lot (WL) 108.1 profile—the Y-12 Sanitary Landfill (SLF) if appropriate; EnergySolutions Clive; and the Nevada National Security Site (NNSS) (ORAU 2013b). Finally, the evaluation of these wastes was more suited to a judgmental sampling approach rather than a statistical design, meaning data were collected for each individual item, thereby providing information for item-byitem disposition decisions. ORAU prepared a sampling and analysis plan (SAP) that outlined data collection strategies, methodologies, and analytical guidelines and requirements necessary for characterizing targeted items (ORAU 2013b). The SAP described an approach to collect samples that allowed evaluation as to whether or not the waste would be eligible for disposal at the EMWMF. If the waste was determined not to be eligible for EMWMF disposal, then there would be adequate information collected that would allow the waste to be profiled for one of the alternate TSDFs listed above.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Contrast- vs. non-contrast enhanced MR data sets for characterization of perianal fistulas

Purpose: To evaluate the diagnostic efficacy between pre- and post-contrast MRI sequences in perianal fistulas using intra-operative findings as the gold standard. Materials and methods: Retrospective analysis of 50 patients with a history of perianal fistula and MRI performed between January 2006 and January 2018 was performed. The inclusion criteria were patients who underwent MRI prior to surgery and had a detailed surgical report available. Pre- and post-contrast MR data sets were evaluated by two radiologists at two-week-intervals, assessed fistula type, internal/external opening, presence of abscess/secondary tracts, and confidence scores. The area under the curve (AUC) was used for comparison the diagnostic ability. The sensitivity and specificity were compared using the McNemar’s test. Results: The confidence scores in detecting perianal fistulas were significantly higher in the post-contrast MR data set (p < 0.003). The post-contrast MR data set had similar ability to classify perianal fistulas as combined T2-DWI and isolated T2 data sets in 49/50 cases. For internal/external opening, the post-contrast MR, combined T2-DWI, and isolated T2 data sets had 100% concordance with intra-operative reports. For perianal abscess, there was no significant difference in sensitivity or AUC value between the isolated T2 or combined T2-DWI data sets and post-contrast MR data set (p > 0.05). All MR data sets correctly identified secondary tracts in all 50 cases. Conclusions: Although contrast-enhanced MR studies can improve a radiologist’s confidence, non-contrast MR studies had similar diagnostic efficacy in identifying perianal fistulas and their complications. Therefore, a non-contrast study may suffice in selected patients such as those with renal impairment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗