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DOE OSTI2024

An Evaluation of The Dynamic Physical Security Risk Assessment Methodology for Fleet-Wide Applications

The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2014

A simple algorithm for beam profile diagnostics using a thermographic camera

A new algorithm for digital image processing apparatuses is developed to evaluate profiles of high-intensity DC beams from temperature images of irradiated thin foils. Numerical analyses are performed to examine the reliability of the algorithm. To simulate the temperature images acquired by a thermographic camera, temperature distributions are numerically calculated for 20 MeV proton beams with different parameters. Noise in the temperature images which is added by the camera sensor is also simulated to account for its effect. Using the algorithm, beam profiles are evaluated from the simulated temperature images and compared with exact solutions. We find that niobium is an appropriate material for the thin foil used in the diagnostic system. We also confirm that the algorithm is adaptable over a wide beam current range of 0.11–214 μA, even when employing a general-purpose thermographic camera with rather high noise (ΔT{sub NETD} ≃ 0.3 K; NETD: noise equivalent temperature difference)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Numerical modeling of carrier gas flow in atomic layer deposition vacuum reactor: A comparative study of lattice Boltzmann models

This paper characterizes the carrier gas flow in the atomic layer deposition (ALD) vacuum reactor by introducing Lattice Boltzmann Method (LBM) to the ALD simulation through a comparative study of two LBM models. Numerical models of gas flow are constructed and implemented in two-dimensional geometry based on lattice Bhatnagar–Gross–Krook (LBGK)-D2Q9 model and two-relaxation-time (TRT) model. Both incompressible and compressible scenarios are simulated and the two models are compared in the aspects of flow features, stability, and efficiency. Our simulation outcome reveals that, for our specific ALD vacuum reactor, TRT model generates better steady laminar flow features all over the domain with better stability and reliability than LBGK-D2Q9 model especially when considering the compressible effects of the gas flow. The LBM-TRT is verified indirectly by comparing the numerical result with conventional continuum-based computational fluid dynamics solvers, and it shows very good agreement with these conventional methods. The velocity field of carrier gas flow through ALD vacuum reactor was characterized by LBM-TRT model finally. The flow in ALD is in a laminar steady state with velocity concentrated at the corners and around the wafer. The effects of flow fields on precursor distributions, surface absorptions, and surface reactions are discussed in detail. Steady and evenly distributed velocity field contribute to higher precursor concentration near the wafer and relatively lower particle velocities help to achieve better surface adsorption and deposition. The ALD reactor geometry needs to be considered carefully if a steady and laminar flow field around the wafer and better surface deposition are desired.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2013

RELIABILITY BASED DESIGN OF FIXED FOUNDATION WIND TURBINES

Recent analysis of offshore wind turbine foundations using both applicable API and IEC standards show that the total load demand from wind and waves is greatest in wave driven storms. Further, analysis of overturning moment loads (OTM) reveal that impact forces exerted by breaking waves are the largest contributor to OTM in big storms at wind speeds above the operating range of 25 m/s. Currently, no codes or standards for offshore wind power generators have been adopted by the Bureau of Ocean Energy Management Regulation and Enforcement (BOEMRE) for use on the Outer Continental Shelf (OCS). Current design methods based on allowable stress design (ASD) incorporate the uncertainty in the variation of loads transferred to the foundation and geotechnical capacity of the soil and rock to support the loads is incorporated into a factor of safety. Sources of uncertainty include spatial and temporal variation of engineering properties, reliability of property measurements applicability and sufficiency of sampling and testing methods, modeling errors, and variability of estimated load predictions. In ASD these sources of variability are generally given qualitative rather than quantitative consideration. The IEC 61400‐3 design standard for offshore wind turbines is based on ASD methods. Load and resistance factor design (LRFD) methods are being increasingly used in the design of structures. Uncertainties such as those listed above can be included quantitatively into the LRFD process. In LRFD load factors and resistance factors are statistically based. This type of analysis recognizes that there is always some probability of failure and enables the probability of failure to be quantified. This paper presents an integrated approach consisting of field observations and numerical simulation to establish the distribution of loads from breaking waves to support the LRFD of fixed offshore foundations.

17 WIND ENERGY↗

DOE OSTI2025

Transforming Energy Through Computational Excellence: A View From NREL

At the National Renewable Energy Laboratory (NREL)—a U.S. Department of Energy laboratory—computational science, high-performance computing, applied mathematics, advanced computer science, visualization, and data play a pivotal role in advancing energy abundance, affordability, security, and reliability. From fundamental scientifc discovery to systems engineering and analysis, NREL researchers tackle market-relevant challenges to develop solutions for an independent energy system that is reliable, resilient and secure. Collaborative partnerships with industry, government, and academia ensure that our research remains cutting edge, impactful, applicable, and aligned with real-world energy needs. This special issue of Computing in Science & Engineering highlights exemplary NREL projects where computational tools and methodologies drive discovery and accelerate innovation in scalable and integrated energy systems. The featured articles explore the role of computational modeling, high-performance computing, generative AI, and adaptive computing in advancing independent energy solutions, optimizing sustainability research, and enhancing decision-making for energy solutions using a broad mix of energy technologies. Here, these contributions demonstrate how NREL’s computational research bridges the gap between theoretical advancements and practical implementation, emphasizing interdisciplinary collaboration and a commitment to innovation, with a focus on translating computational excellence into real-world impact, thus accelerate progress toward national energy goals. By showcasing cutting-edge research at the intersection of computational science and energy systems, this issue aims to inspire and inform researchers, practitioners, and policymakers dedicated to shaping a more reliable energy future.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Size–strain separation in diffraction line profile analysis

Separation of size and strain effects on diffraction line profiles has been studied in a round robin involving laboratory instruments and synchrotron radiation beamlines operating with different radiation, optics, detectors and experimental configurations. The studied sample, an extensively ball milled iron alloy powder, provides an ideal test case, as domain size broadening and strain broadening are of comparable size. The high energy available at some synchrotron radiation beamlines provides the best conditions for an accurate analysis of the line profiles, as the size–strain separation clearly benefits from a large number of Bragg peaks in the pattern; high counts, reliable intensity values in low-absorption conditions, smooth background and data collection at different temperatures also support the possibility to include diffuse scattering in the analysis, for the most reliable assessment of the line broadening effect. However, results of the round robin show that good quality information on domain size distribution and microstrain can also be obtained using standard laboratory equipment, even when patterns include relatively few Bragg peaks, provided that the data are of good quality in terms of high counts and low and smooth background.

Scardi, P. (ORCID:0000000310973917)↗

DOE OSTI2017

Recordings and Analysis of Atomic Ledge and Dislocation Movements in InGaAs to Nickelide Nanowire Phase Transformation

The formation of low resistance and self‐aligned contacts with thermally stable alloyed phases is a prerequisite for realizing reliable functionality in ultrascaled semiconductor transistors. Detailed structural analysis of the phase transformation accompanying contact alloying can facilitate contact engineering as transistor channels approach a few atoms across. Original in situ heating transmission electron microscopy studies are carried out to record and analyze the atomic scale dynamics of contact alloy formation between Ni and In 0.53 Ga 0.47 As nanowire channels. It is observed that the nickelide reacts on the In 0.53 Ga 0.47 As (111) || Ni 2 In 0.53 Ga 0.47 As (0001) interface with atomic ledge propagation along the Ni 2 In 0.53 Ga 0.47 As direction. Ledges nucleate as a train of strained single‐bilayers and propagate in‐plane as double‐bilayers that are associated with a misfit dislocation of . The atomic structure is reconstructed to explain this phase transformation that involves collective gliding of three Shockley partials in In 0.53 Ga 0.47 As lattice to cancel out shear stress and the formation of misfit dislocations to compensate the large lattice mismatch in the newly formed nickelide phase and the In 0.53 Ga 0.47 As layers. This work demonstrates the applicability of interfacial disconnection (ledge + dislocation) theory in a nanowire channel during thermally induced phase transformation that is typical in metal/III–V semiconductor reactions.

Chen, Renjie↗

DOE OSTI2024

Analysis and Mitigation of Cascading Outages Using an Interaction Graph Addressing Transient Stability

Cascading outages of power systems pose great threats to system security and reliability, potentially leading to large-scale blackouts. For analysis and mitigation of cascading outages, this paper proposes a transient stability-incorporated interaction graph. This graph statistically quantifies the interactions among line outages and instabilities of generators, which can model propagation paths and patterns of cascading outages. Compared with an interaction graph that only models line outages, this new interaction graph provides important insights on how transient instability occurs along with cascading outages. It also offers more effective strategies for mitigating outage propagation. The proposed interaction graph can be constructed from datasets of historical or simulated cascading events. It is demonstrated on an NPCC 140-bus system with mitigation strategies.

Guo, Zhenping↗

DOE OSTI2021

BETO 2021 Peer Review - Strategic Analysis Support WBS 4.1.1.30

Strategic Analysis Support. The objective of the NREL strategic support project is to provide sound, unbiased, and consistent analyses to inform the strategic direction of the DOE BETO office. This project addresses key technological questions, provides critical data needed to inform strategy, and highlights barriers, gaps and data needs in support of the DOE BETO's mission to improve the affordability of bio-based fuels and products. This task employs various quantitative (techno-economic analysis, TEA) and qualitative (gap analysis) approaches to allow for direct comparisons of biomass conversion technologies across a wide slate of processing platforms and products. Furthermore, this project develops and utilizes novel analyses beyond traditional biorefinery focused TEA/LCAs to identify both technical (e.g., in sustainable design) and non-technical (e.g., in value proposition) barriers, as well as to outline mitigation strategies and R&D needs for emerging technologies. Additionally, the project is tasked with evaluating drivers that support the growing bio-economy, which is achieved by the development and public release of tools to advance the understanding and facilitate comparisons of socio-economic impacts along the supply chain. Critical to the success of this project is the development of defensible methodologies, analyses, and tools that are publicly available to support stakeholders and bioeconomy growth. To develop such high-quality analyses, the biggest challenge to this project, as with most analysis focused projects, is the availability and reliability of the underlying data. Therefore, the project team works extensively with key stakeholders (e.g., policy makers, bioenergy technology developers, and investors) in developing and reviewing the results of these analyses to overcome this challenge. Any remaining uncertainties associated with the analysis efforts are clearly defined and quantified.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Severe weather, utility spending, and the long-term reliability of the U.S. power system

There has been a limited amount of peer-reviewed literature on long-term trends in electricity reliability including the underlying factors that impact reliability across the United States. In this analysis, we considered up to 16 years of data from 203 U S. utilities—representing about 70% of electricity sales. Annual frequency of interruptions for an average customer—at the regional and U.S. national-level—has generally decreased over this timeframe. But we do not find that there is a statistically significant trend in the annual duration of interruptions for an average customer. We find that more explicit measures of severe weather are correlated with reliability. We are able to explain 7% and 16% of past variation in the reliability metrics system average interruption duration and frequency indices, respectively, is due to severe weather—a significant improvement over earlier studies. We find that current year spending by utilities is correlated with worse reliability and that cumulative spending over the preceding three years is correlated with better reliability. Finally, we demonstrate that using a statistical instrument to represent the annual frequency of interruptions for an average customer can greatly improve analysis of trends in the annual duration of interruptions for an average customer.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Application of IR Thermography with Thermal Diffusivity Analysis for Detection of Plies Displacement in CFRP Composites

This paper presents an efficient nondestructive testing (NDT) method for detection of plies displacement in carbon fiber reinforced plastic (CFRP) composites using the active thermography technique. To assess the capability of the proposed technique for detection of plies displacement, the CFRP composite specimens with simulated fault were designed and manufactured. The IR thermography measurements were conducted using two-sided experimental arrangement. From recorded sequences of thermal images, the temperature variations versus time plots were extracted to obtain the maximum thermal contrasts. For quantitative interpretation of the results, the thermal diffusivity values for each composite material were determined and related to the fiber volume fraction. The experimental results showed that the thermal diffusivity increases with an increase of fiber volume fraction; further, the values of thermal diffusivity are specimen thickness dependent. The obtained values of thermal diffusivity varied from 1.5 × 10{sup −7} m{sup 2}/s (for 3.2 mm composite with 8.5 vol.% carbon fiber) to 2.6 × 10{sup −7} m{sup 2}/s (for 7.7 mm composite with 34.1 vol.% carbon fiber). On the basis of these results, it was concluded that the active thermography combined with thermal diffusivity analysis can be considered as a reliable NDT technique for detection of plies displacement in CFRP composites.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. Furthermore, this supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.

42 ENGINEERING↗

DOE OSTI2014

Interrater Reliability of the Categorization of Late Radiographic Changes After Lung Stereotactic Body Radiation Therapy

Purpose: Radiographic changes after lung stereotactic body radiation therapy (SBRT) have been categorized into 4 groups: modified conventional pattern (A), mass-like fibrosis; (B), scar-like fibrosis (C), and no evidence of increased density (D). The purpose of this study was to assess the interrater reliability of this categorization system in patients with early-stage non-small cell lung cancer (NSCLC). Methods and Materials: Seventy-seven patients were included in this study, all treated with SBRT for early-stage (T1/2) NSCLC at a single institution, with a minimum follow-up of 6 months. Six experienced clinicians familiar with post-SBRT radiographic changes scored the serial posttreatment CT images independently in a blinded fashion. The proportion of patients categorized as A, B, C, or D at each interval was determined. Krippendorff's alpha (KA), Multirater kappa (M-kappa), and Gwet's AC1 (AC1) scores were used to establish interrater reliability. A leave-one-out analysis was performed to demonstrate the variability among raters. Interrater agreement of the first and last 20 patients scored was calculated to explore whether a training effect existed. Results: The number of ratings ranged from 450 at 6 months to 84 at 48 months of follow-up. The proportion of patients in each category was as follows: A, 45%; B, 16%; C, 13%; and D, 26%. KA and M-kappa ranged from 0.17 to 0.34. AC1 measure range was 0.22 to 0.48. KA increased from 0.24 to 0.36 at 12 months with training. The percent agreement for pattern A peaked at 12 month with a 54% chance of having >50% raters in agreement and decreased over time, whereas that for patterns B and C increased over time to a maximum of 20% and 22%, respectively. Conclusion: This post-SBRT radiographic change categorization system has modest interrater agreement, and there is a suggestion of a training effect. Patterns of fibrosis evolve after SBRT and alternative categorization systems should be evaluated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Machine learning-based optimization of air-cooled heat sinks

Machine learning-based models using Artificial Neural Network (ANN) and greedy search algorithm are used to optimize air-cooled parallel plate-finned heat sinks (PPFHSs) subjected to laminar flow over an extensive range of design parameters. Here, the thermal and hydraulic performances of PPFHSs are represented by heat transfer coefficient (h) and pressure drop (ΔP), respectively. Optimization objectives for PPFHS designs can vary from industry to industry depending on their design priorities. The present study proposes a novel and generalized optimization method that defines practical optimization objectives and provides an accurate optimization process to design effective PPFHSs for a wide range of industrial applications with different design requirements. Three optimization objectives are presented in this study: (i) the largest h PΔ, (ii) the largest h within a specified maximum allowed flow rate, and (iii) the lowest weight that maximizes h for operation within the maximum allowed flow rate. While the shortcoming of the first objective is demonstrated, the other two objectives are found to be suitable for designing effective heat sinks (HSs) across different applications. Results suggest a promising trend from the third objective to develop HSs with ~ 37-68% lower weight, 80-85% reduced ΔP, and negligible penalty in h compared with optimized HSs obtained from the second objective. However, since the third objective leads to HSs with thinner fins, structural analysis should be performed to ensure reliable operation of the HSs.

42 ENGINEERING↗

DOE OSTI2026

Accurate determination of chemical abundances near a supermassive black hole

The metal abundances in galactic nuclei carry key information on the history of star formation and mass transfer in central regions of galaxies. X-ray fluorescence analysis is a unique tool to reliably measure the abundances of various elements via simple physics. Here we present a new observation of the active nucleus in the Circinus galaxy with the XRISM satellite at unprecedented X-ray energy resolution. The fluorescent iron Kα line profile modified by Compton scattering indicates that the material responsible for its emission is cold and metal rich and is located ≳0.024 pc from the supermassive black hole, consistent with the dusty torus region. The abundance pattern derived from comparing fluorescent line intensities of different metals shows subsolar ratios of argon- and calcium-to-iron and a supersolar ratio of nickel-to-iron. This abundance pattern is best produced by a combination in number fraction of 92$^{+2}_{–4}$% core-collapse supernovae from progenitor stars less massive than 20$^{+3}_{–2}$ M ⊙ and 8$^{+4}_{–2}$% type Ia supernovae. This suggests that gas feeding the supermassive black hole was enriched by recent core-collapse supernovae. Our findings imply that in metal-rich environments stars more massive than about 20 M ⊙ directly collapse into black holes or make faint supernovae without ejecting heavy metals into the space.

Astronomy and AstroPhysics↗

DOE OSTI2023

Short-lead seasonal precipitation forecast in northeastern Brazil using an ensemble of artificial neural networks

This study assesses the deterministic and probabilistic forecasting skill of a 1-month-lead ensemble of Artificial Neural Networks (EANN) based on low-frequency climate oscillation indices. The predictand is the February-April (FMA) rainfall in the Brazilian state of Ceará, which is a prominent subject in climate forecasting studies due to its high seasonal predictability. Additionally, the study proposes combining the EANN with dynamical models into a hybrid multi-model ensemble (MME). The forecast verification is carried out through a leave-one-out cross-validation based on 40 years of data. The EANN forecasting skill is compared with traditional statistical models and the dynamical models that compose Ceará’s operational seasonal forecasting system. A spatial comparison showed that the EANN was among the models with the smallest Root Mean Squared Error (RMSE) and Ranked Probability Score (RPS) in most regions. Moreover, the analysis of the area-aggregated reliability showed that the EANN is better calibrated than the individual dynamical models and has better resolution than Multinomial Logistic Regression for above-normal (AN) and below-normal (BN) categories. It is also shown that combining the EANN and dynamical models into a hybrid MME reduces the overconfidence of the extreme categories observed in a dynamically-based MME, improving the reliability of the forecasting system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

A symmetric organic-based nonaqueous redox flow battery and its state of charge diagnostics by FTIR

Redox flow batteries have shown outstanding promise for grid-scale energy storage to promote utilization of renewable energy and improve grid stability. Nonaqueous battery systems can potentially achieve high energy density because of their broad voltage window. In this paper, we report a new organic redox-active material for use in a nonaqueous redox flow battery, 2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (PTIO) that has high solubility (>2.6 M) in organic solvents. PTIO exhibits electrochemically reversible disproportionation reactions and thus can serve as both anolyte and catholyte redox materials in a symmetric flow cell. The PTIO flow battery has a moderate cell voltage of ~1.7 V and shows good cyclability under both cyclic voltammetry and flow cell conditions. Moreover, we demonstrate that FTIR can offer accurate estimation of the PTIO concentration in electrolytes and determine the state of charge of the PTIO flow cell, which suggests FTIR potentially as a powerful online battery status sensor. In conclusion, this study is expected to inspire more insights in this under-addressed area of state of charge analysis aiming at operational safety and reliability of flow batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Evaluation of Analytical and Numerical Techniques for Defining the Radius of Influence for an Open-Loop Ground Source Heat Pump System

In an open-loop groundwater heat pump (GHP) system, groundwater is extracted, run through a heat exchanger, and injected back into the ground, resulting in no mass balance changes to the flow system. Although the groundwater use is non-consumptive, the withdrawal and injection of groundwater may cause negative hydraulic and thermal impacts to the flow system. Because GHP is a relatively new technology and regulatory guidelines for determining environmental impacts for GHPs may not exist, consumptive use metrics may need to be used for permit applications. For consumptive use permits, a radius of influence is often used, which is defined as the radius beyond which hydraulic impacts to the system are considered negligible. In this paper, the hydraulic radius of influence concept was examined using analytical and numerical methods for a non-consumptive GHP system in southeastern Washington State. At this location, the primary hydraulic concerns were impacts to nearby contaminant plumes and a water supply well field. The results of this study showed that the analytical techniques with idealized radial flow were generally unsuited because they over predicted the influence of the well system. The numerical techniques yielded more reasonable results because they could account for aquifer heterogeneities and flow boundaries. In particular, the use of a capture zone analysis was identified as the best method for determining potential changes in current contaminant plume trajectories. The capture zone analysis is a more quantitative and reliable tool for determining the radius of influence with a greater accuracy and better insight for a non-consumptive GHP assessment.

GHPs↗