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At least 433 records · Page 24

Risk-informed Graded Approach for Reliability and Performance Assessment of Machine Learning and Artificial Intelligence for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

97 - MATHEMATICS AND COMPUTING↗

Risk-informed Graded Approach for Reliability and Performance Assessment for Advanced Condition Monitoring Techniques

With the shift away from time-based maintenance and toward condition-based maintenance, and to reduce overall maintenance costs, there has been an upsurge in the usage and development of advanced condition monitoring (ACM) techniques for real-time monitoring of nuclear power plant (NPP) components. ACM is particularly useful in the development of digital twins, which are designed to predict the failure or degradation of plant components. Successful implementation of ACM requires an assessment to inform the development of a risk-informed approach to evaluate the use of ACM to meet Nuclear Regulatory Committee (NRC) regulations for in-service testing (IST) programs. This includes the monitoring and diagnostics of reactor components and systems in current, new, and advanced reactors. A key component in ACM is the usage of machine learning (ML) and artificial intelligence (AI) algorithms that can employ real-time data from instrumentation and sensors to detect and predict reactor component degradations. Such predictive capabilities enable early detection of component degradation so as to help plant personnel plan and execute necessary maintenance. For successful implementation of ML/AI in ACM such that regulatory requirements are met, a risk-informed graded approach is needed to assess the reliability and performance of ML/AI for ACM. The American Society for Mechanical Engineers (ASME) developed their Operations and Maintenance (O&M) Code to provide guidance on safe, reliable O&M of NPPs. The IST section of the O&M Code specifically establishes requirements for IST and examination to gauge operational readiness of components in water-cooled NPPs. This paper presents a state-of-the-art review of how reliability and risk assessment can be integrated with ACM to assess component performance by non-nuclear industries. This is followed by different methodologies and approaches for conducting performance and reliability assessments so as to meet IST requirements for NPP components.

99 - GENERAL AND MISCELLANEOUS↗

Sensing device and method for measuring emission time delay during irradiation of targeted samples

An apparatus for measuring emission time delay during irradiation of targeted samples by utilizing digital signal processing to determine the emission phase shift caused by the sample is disclosed. The apparatus includes a source of electromagnetic radiation adapted to irradiate a target sample. A mechanism generates first and second digital input signals of known frequencies with a known phase relationship, and a device then converts the first and second digital input signals to analog sinusoidal signals. An element is provided to direct the first input signal to the electromagnetic radiation source to modulate the source by the frequency thereof to irradiate the target sample and generate a target sample emission. A device detects the target sample emission and produces a corresponding first output signal having a phase shift relative to the phase of the first input signal, the phase shift being caused by the irradiation time delay in the sample. A member produces a known phase shift in the second input signal to create a second output signal. A mechanism is then provided for converting each of the first and second analog output signals to digital signals. A mixer receives the first and second digital output signals and compares the signal phase relationship therebetween to produce a signal indicative of the change in phase relationship between the first and second output signals caused by the target sample emission. Finally, a feedback arrangement alters the phase of the second input signal based on the mixer signal to ultimately place the first and second output signals in quadrature. Mechanisms for enhancing this phase comparison and adjustment technique are also disclosed.

Danielson, J. D. Sheldon↗

Sensing device and method for measuring emission time delay during irradiation of targeted samples utilizing variable phase tracking

An apparatus for measuring emission time delay during irradiation of targeted samples by utilizing digital signal processing to determine the emission phase shift caused by the sample is disclosed. The apparatus includes a source of electromagnetic radiation adapted to irradiate a target sample. A mechanism generates first and second digital input signals of known frequencies with a known phase relationship, and a device then converts the first and second digital input signals to analog sinusoidal signals. An element is provided to direct the first input signal to the electromagnetic radiation source to modulate the source by the frequency thereof to irradiate the target sample and generate a target sample emission. A device detects the target sample emission and produces a corresponding first output signal having a phase shift relative to the phase of the first input signal, the phase shift being caused by the irradiation time delay in the sample. A member produces a known phase shift in the second input signal to create a second output signal. A mechanism is then provided for converting each of the first and second analog output signals to digital signals. A mixer receives the first and second digital output signals and compares the signal phase relationship therebetween to produce a signal indicative of the change in phase relationship between the first and second output signals caused by the target sample emission. Finally, a feedback arrangement alters the phase of the second input signal based on the mixer signal to ultimately place the first and second output signals in quadrature. Mechanisms for enhancing this phase comparison and adjustment technique are also disclosed.

Danielson, J. D. Sheldon↗

Real-Time and Rapid Respiratory Response of the Soil Microbiome to Moisture Shifts

Microbial response to changing environmental factors influences the fate of soil organic carbon, and drought has been shown to affect microbial metabolism and respiration. We hypothesized that the access of microbes to different carbon pools in response to dry–rewet events occurs sequentially at different rates. We amended desiccated soils with 13 C-labeled glucose and measured the rates of 12 CO 2 and 13 CO 2 respiration in real time after rewetting. Using these differentiated 12 CO 2 and 13 CO 2 respiration rate soils after rewetting, we were able to deduce when microbes are accessing different pools of carbon. Immediately upon rewetting, respiration of 12 CO 2 occurred first, with negligible 13 CO 2 respiration. Appreciable metabolism and respiration of the added 13 C glucose did not occur until 15 min after rewetting. We conclude that, while all carbon pools are being accessed in the first 9 h after rewetting, the rate and timing at which new and existing carbon pools are being accessed varies. Within this study, using stable isotope-labeled substrates to discern which carbon pools are metabolized first uniquely illustrates how microorganisms access different carbon pools which has implications into understanding how carbon metabolism can further affect climate, carbon sequestration, and soil health.

59 BASIC BIOLOGICAL SCIENCES↗

Time-Distance Helioseismology Data-Analysis Pipeline for Helioseismic and Magnetic Imager Onboard Solar Dynamics Observatory (SDO-HMI) and Its Initial Results

The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) provides continuous full-disk observations of solar oscillations. We develop a data-analysis pipeline based on the time-distance helioseismology method to measure acoustic travel times using HMI Doppler-shift observations, and infer solar interior properties by inverting these measurements. The pipeline is used for routine production of near-real-time full-disk maps of subsurface wave-speed perturbations and horizontal flow velocities for depths ranging from 0 to 20 Mm, every eight hours. In addition, Carrington synoptic maps for the subsurface properties are made from these full-disk maps. The pipeline can also be used for selected target areas and time periods. We explain details of the pipeline organization and procedures, including processing of the HMI Doppler observations, measurements of the travel times, inversions, and constructions of the full-disk and synoptic maps. Some initial results from the pipeline, including full-disk flow maps, sunspot subsurface flow fields, and the interior rotation and meridional flow speeds, are presented.

Sun: helioseismology↗

LiAISON (Life-cycle Assessment Integration into Scalable Open-source Numerical models) [SWR-24-01]

We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE)7. We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming. Scientific publication available here: https://pubs.acs.org/doi/full/10.1021/acs.est.2c04246

Ghosh, Tapajyoti↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

Nuclear quadrupole resonance spectroscopy with a femtotesla diamond magnetometer

Radio frequency (RF) magnetometers based on nitrogen vacancy centers in diamond are predicted to offer femtotesla sensitivity, but previous experiments were limited to the picotesla level. We demonstrate a femtotesla RF magnetometer using a diamond membrane inserted between ferrite flux concentrators. The device provides ~300-fold amplitude enhancement for RF magnetic fields from 70 kHz to 3.6 MHz, and the sensitivity reaches ~70 fT√s at 0.35 MHz. The sensor detected the 3.6-MHz nuclear quadrupole resonance (NQR) of room-temperature sodium nitrite powder. The sensor’s recovery time after an RF pulse is ~35 μs, limited by the excitation coil’s ring-down time. The sodium-nitrite NQR frequency shifts with temperature as -1.00±0.02 kHz/K, the magnetization dephasing time is T 2 *=887±51 μs, and multipulse sequences extend the signal lifetime to 332±23 ms, all consistent with coil-based studies. Our results expand the sensitivity frontier of diamond magnetometers to the femtotesla range, with potential applications in security, medical imaging, and materials science.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Scattering of p-modes by a sunspot

The acoustic scattering properties of a large sunspot are determined from a Fourier-Hankel decomposition of p-mode amplitudes as measured from a 68-hr subset of a larger set of observations made at the South Pole in 1988. It is shown that significant improvement in the measurement of p-mode scattering amplitudes results from the increased temporal frequency resolution provided by these data. Scattering phase shifts are unambiguously determined for the first time, and the dependence of the p-mode phase shift and absorption with wavenumber and frequency is presented.

Braun, D. C.↗

Magnetic Compensation for Second-Order Doppler Shift in LITS

The uncertainty in the frequency of a linear-ion-trap frequency standard (LITS) can be reduced substantially by use of a very small magnetic inhomogeneity tailored to compensate for the residual second-order Doppler shift. An effect associated with the relativistic time dilatation, one cause of the second-order Doppler shift, is ion motion that is attributable to the trapping radio-frequency (RF)electromagnetic field used to trap ions. The second-order Doppler shift is reduced by using a multi-pole trap; however it is still the largest source of systematic frequency shift in the latest generation of LITSs, which are among the most stable clocks in the world. The present compensation scheme reduces the frequency instability of the affected LITS to about a tenth of its previous value. The basic principles of prior generation LITSs were discussed in several prior NASA Tech Briefs articles. Below are recapitulated only those items of basic information necessary to place the present development in context. A LITS includes a microwave local oscillator, the frequency of which is stabilized by comparison with the frequency of the ground state hyperfine transition of 199Hg+ ions. The comparison involves a combination of optical and microwave excitation and interrogation of the ions in a linear ion trap in the presence of a nominally uniform magnetic field. In the current version of the LITS, there are two connected traps (see figure): (1) a quadrupole trap wherein the optical excitation and measurement take place and (2) a 12-pole trap (denoted the resonance trap), wherein the microwave interrogation takes place. The ions are initially loaded into the quadrupole trap and are thereafter shuttled between the two traps. Shuttling ions into the resonance trap allows sensitive microwave interrogation to take place well away from loading interference. The axial magnetic field for the resonance trap is generated by an electric current in a finely wound wire coil surrounded by magnetic shields. In the quadrupole and 12-pole traps, the potentials are produced by RF voltages applied to even numbers (4 and 12, respectively) of parallel rods equally spaced around a circle. The polarity of the voltage on each rod is opposite that of the voltage on the adjacent rod. As a result, the amplitude of the RF trapping field is zero along the centerline and increases, with radius, to a maximum value near the rods.

Burt, Eric↗

Utilization of FSK communications for time

The method of time control at a radio station for time signal transmission using frequency shift keying, is discussed. Methods for extracting a recovered clock at the receiver are described. Results of a test involving the methods of processing time signals are presented. The requirements for adapting Precise Time and Time Interval control to a communications system are analyzed. A method for reducing the time required for synchronization or identification of messages and the fallout from the communication system to passive timekeeping users are reported.

Stone, R. R., Jr.↗

On the location of the oscillations in AE Aquarii

There is much recent interest on the nature of the oscillations in the cataclysmic variable AE Aquarii. Detected in the optical, UV, X-ray, and possibly gamma-ray bands, the origin of these 33-sec oscillations remains poorly understood; the oscillation time-delay curve is phase shifted by about 60 deg with respect to the emission-line radial velocity curve, although both should track the orbital motion of the white dwarf. We present simultaneous absorption and emission-line radial velocities, and from the absorption lines we derive an improved ephemeris. Our emission-line velocities are phase shifted by about 75 deg, and hence are unreliable tracers of the orbital motion of the white dwarf. However, the oscillation orbit is shifted by only 5 deg +/- 3 deg percent confirming that the oscillations arise from a region concentric with the white dwarf. Thus the arrival times of the oscillations yield a measure of the white dwarfs apparent orbital velocity, independent of emission-line radial velocity measurements.

Welsh, William F.↗

Streamflow in the United States: Characteristics, trends, regime shifts, and extremes

Long-term streamflow observations contain essential information for understanding hydrological changes and managing water resources. A continental-scale dataset or analysis of temporal streamflow change is still lacking across hydrologic gauges in the Conterminous United States (CONUS). Here, we compiled 70 years of streamflow records from 1951 to 2021 at ~ 8000 hydrologic stations across the CONUS and characterized temporal trends, regime shifts, and extreme events using a Bayesian time series analysis algorithm. We found that the occurrences of sudden streamflow changes (e.g., regime shifts and extreme events) have been increasing with time across the CONUS. In addition, we derived 181 streamflow indicators that are valuable for hydrological and biological applications, such as the duration and frequency of high or low streamflow events. The Mississippi River Basin, especially the middle and lower parts, was a hot spot of high-frequency high-flow events. Overall, we anticipate the dataset generated here offers valuable information for understanding and quantifying changes in water resources across the CONUS.

54 ENVIRONMENTAL SCIENCES↗

Upper limits on the isotropic gravitational radiation background from pulsar timing analysis

A pulsar and the earth may be thought of as end masses of a free-mass gravitational wave antenna in which the relative motion of the masses is monitored by observing the Doppler shift of the pulse arrival times. Using timing residuals from PSR 1133 + 16, 1237 + 25, 1604-00, and 2045-16, an upper limit to the spectrum of the isotropic gravitational radiation background has been derived in the frequency band 4 x 10 to the -9th to 10 to the -7th Hz. This limit is found to be S(E) = 10 to the 21st f-cubed ergs/cu cm Hz, where S(E) is the energy density spectrum and f is the frequency in Hz. This would limit the energy density at frequencies below 10 to the -8th Hz to be 0.00014 times the critical density.

Hellings, R. W.↗

Local time distribution of the SSC-associated HF-Doppler frequency shifts

The HF-Doppler frequency shift observed at the storm's sudden commencement is composed of a frequency increase (+) and decrease (-), and classified into four types, SCF(+ -), SCF(- +), SCF(+) and SCF(-). Since the latter two types are special cases of the former two types, two different kinds of electrical field exist in the F region and cause the ExB drift motion of plasma. HUANG (1976) interpreted the frequency increase of SCF(+ -) as due to the westward induction electric field proportional to delta H/ delta t and the succeeding frequency decrease due to the eastward conduction electric field which produces ionospheric currents responsible for the magnetic increase on the ground. In spite of his success in interpreting the SCF(+ -), some other interpretations are needed for the explanation of the whole set of SCF's, particularly SCF(- +). Local time distributions of the SCF's are derived from 41 SCF's which are observed on the HF standard signal (JJY) as received in Okinawa (path length =1600 km) and Kokubunji (60 km). It is shown that the SCF(+ -) appears mainly during the day, whereas the SCF(- +) is observed during the night. The results indicate that the preliminary frequency shift (+) of SCF(+ -) and (-) of SCF(- +) is caused by a westward electric field in the dayside hemisphere, while by an eastward electric field in the nightside hemisphere. The main frequency shift (-) of SCF(+ -) and (+) of SCF(- +) is caused by the reversed electric field. Consequently, the preliminary frequency shift is caused by the dusk-to-dawn electric field, while the main frequency shift by the dawn-to-dusk electric field.

Kikuchi, T.↗

PFLOTRAN-SIP: A PFLOTRAN Module for Simulating Spectral-Induced Polarization of Electrical Impedance Data

Spectral induced polarization (SIP) is a non-intrusive geophysical method that collects chargeability information (the ability of a material to retain charge) in the time domain or its phase shift in the frequency domain. Although SIP is a temporal method, it cannot measure the dynamics of flow and solute/species transport in the subsurface over long times (i.e., 10–100 s of years). Data collected with the SIP technique need to be coupled with fluid flow and reactive-transport models in order to capture long-term dynamics. To address this challenge, PFLOTRAN-SIP was built to couple SIP data to fluid flow and solute transport processes. Specifically, this framework couples the subsurface flow and transport simulator PFLOTRAN and geoelectrical simulator E4D without sacrificing computational performance. PFLOTRAN solves the coupled flow and solute-transport process models in order to estimate solute concentrations, which were used in Archie’s model to compute bulk electrical conductivities at near-zero frequency. These bulk electrical conductivities were modified while using the Cole–Cole model to account for frequency dependence. Using the estimated frequency-dependent bulk conductivities, E4D simulated the real and complex electrical potential signals for selected frequencies for SIP. These frequency-dependent bulk conductivities contain information that is relevant to geochemical changes in the system. This study demonstrated that the PFLOTRAN-SIP framework is able to detect the presence of a tracer in the subsurface. SIP offers a significant benefit over ERT in the form of greater information content. It provided multiple datasets at different frequencies that better constrained the tracer distribution in the subsurface. Consequently, this framework allows for practitioners of environmental hydrogeophysics and biogeophysics to monitor the subsurface with improved resolution.

54 ENVIRONMENTAL SCIENCES↗