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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 1,243 records · Page 69

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗

Distribution Function Instead of Steady-State Assumption in Time-Series Simulation

The quasi-steady-state assumption in time-series simulation is inadequate to model phenomena of interest to energy system integration such as inverter clipping, sell-back of excess electricity to a utility and utility hosting capacity, and battery throughput. Researchers are working on stochastic modeling, higher-resolution time series data, and machine learning approaches to address this need. This poster describes a distribution function that allows a maximum value, minimum value, and shape to the curve that can vary within each time-step based only on data inputs at the resolution of that time step (eg. Hourly). The distribution function is not used to synthesize high-resolution data, rather scalar integrals are used to calculate the quantities of interest within each time step. The form of the distribution function shows significant reduction in error when compared to 1 minute data and commercial software employing the distribution function (HOMER Pro version 14.3 and higher) shows a much improved estimate of inverter clipping in an example.

battery↗

Distribution of Neutrons in a Cold Lucite Moderator

A series of experiments was performed in 2010 to study the behavior of neutrons in a cold Lucite moderator. The diffusion of neutrons in a cold moderator is described as a two-step process. In the first step, the fast neutrons produced by a neutron source collide with the nuclei of Lucite, losing energy until they reach thermal energies. In the second step, the thermal neutrons continue to diffuse without any significant loss of energy until they are absorbed or leak out of the system. However, because the Lucite moderator is at low temperature, there is less up scattering in the neutron energy compared to a Lucite moderator at room temperature. Experiments were performed to study the behavior of neutrons and their distribution in a cold Lucite moderator and their results compared to simulations. Based on these measurements, an estimation of the absorption cross section at -78.5 °C yielded a value of 0.54 barns ± 0.02 barns.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

3D printing of metal containing structures

In an aspect, a method for making a metal-containing material comprises steps of: forming a metal-containing hydrogel from an aqueous precursor mixture using a photopolymerization; wherein the aqueous precursor mixture comprises water, one or more aqueous photosensitive binders, and one or more aqueous metal salts; and thermally treating the metal-containing hydrogel to form the metal-containing material; wherein the metal-containing hydrogel is exposed to a thermal-treatment atmosphere during the step of thermally treating; wherein a composition of the metal-containing material is at least partially determined by a composition of the thermal-treatment atmosphere during the thermally treating step.

Yee, Daryl Wei Liang↗

System Analysis Modeling and Intermodal Transportation for Commercial Spent Nuclear Fuel

The United States Department of Energy (DOE) has long term goals to develop solutions for managing the nation’s spent nuclear fuel (SNF) and high-level waste (HLW) inventory. The Integrated Waste Management (IWM) program under the DOE office of Nuclear Energy (DOE-NE) is employing system-level engineering and analysis principles to inform potential future waste management system architectures. Managing the spent nuclear waste requires the use of system-level analysis software that takes various aspects of the fuel cycle into account like waste generation, on-site/centralized storage, transportation infrastructure, and long-term disposal. The Next Generation System Analysis Model (NGSAM) is an agent-based model that was developed to simulate the transportation and storage of SNF and HLW. As an agent-based model, NGSAM has the capability to detail the interaction and movement of individual components and groups, such as rail cars and casks. The SNF inventory from commercial nuclear reactors is currently in temporary storage at multiple locations spread across the United States. Shipping of SNF from these locations relies on one of three transportation modes: rail, heavy-haul truck, or barge. Out of the three modes identified, rail is generally the most preferred due to the size of the canisters and casks the SNF would be shipped in. However, under some scenarios, a direct rail route might not be readily available to a reactor site or improving the rail infrastructure at shutdown sites might be too cost-prohibitive for utilities to opt for a direct rail transfer. Under such scenarios, using a barge or heavy haul truck to de-inventory the site and transfer the SNF to a nearby intermodal transfer site with adequate rail infrastructure where the payload could be transferred to a rail car might prove to be an attractive option. This work initially presents the various intermodal transportation options that could be used to transfer SNF from reactor sites to rail cars. This is followed by exploring the operational steps in each of these modes to move the SNF from a reactor site and transfer it to a rail car. This work also presents the procedure of implementing the intermodal transfer methodology in NGSAM using various Java methods. Finally, the process times for accomplishing each of the individual steps are furnished. The implementation ideology, assumptions, and future steps are presented in this work.

Gadey, Harish Reddy↗

System Analysis Support of Consent-Based Siting Efforts - 23400

To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the Integrated Waste Management (IWM) program within the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) has been sponsoring the development and application of system analysis tools capable of analyzing various system options for the management of spent nuclear fuel (SNF) and high-level radioactive waste. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate things like the implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, and different assumed system operation start dates. Some example system analysis results have been published previously. With the passage of the consolidated appropriations acts for fiscal years 2021 and 2022, Congress provided funding and direction for the DOE to move forward with interim storage to support near-term action in managing the nation’s SNF as an important component of an IWMS. Consent-based siting is a phased, adaptive, and collaborative approach to siting facilities that focuses on the needs and concerns of people and communities. Communities participate in the siting process by working carefully through a series of phases and steps with the DOE (as the implementing organization). Each step and phase helps a community determine whether and how hosting a facility to manage SNF is aligned to the community’s goals. By its nature, a consent-based siting process must be transparent, flexible, adaptive, and responsive to community concerns. Thus, the phases and steps are intended to serve as a guide, not a prescriptive set of instructions. System analysis research analysts interface with DOE’s consent-based siting for a federal interim storage program and can perform preliminary system analyses as requested to support various aspects of the consent-based siting team’s work. This paper provides an overview of IWM program’s system analysis activities that support the ongoing consent-based siting process. The questions that decision-makers, planners, communities, and stakeholders might have during the consent-based siting process are similar to questions that have been explored by system analysts previously. Specifically, this paper discusses work that will inform consent-based siting efforts in the areas of community impacts, cost estimates, various SNF acceptance rates by potential facilities, potential consolidated interim storage facility (CISF) capacities and configurations, and the implications of a CISF on the overall waste management system. It is expected that system analysis will continue to be performed to support the consent-based siting process in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Chromate Removal by Long Life IX Resins Without Continuous pH Adjustment - 20083

Long life resins are available for chromate removal from water but have traditionally had the disadvantage of requiring pH adjustment, first to reduce pH before treatment, and then to raise pH following treatment. The requirement for double pH adjustment leads to a significant increase in TDS, added complexity, risks associated with the use of strong acids and bases, and the ongoing costs of purchasing and using these chemicals. The mechanism of removal in long life resins used for chromate removal is ion exchange, followed by reduction of hexavalent chromium to trivalent chromium, followed by immobilization of trivalent chromium within the IX resin polymer. The second step is rate limiting and pH dependent and is the reason why lowering pH before treatment has until now been necessary. However, there is a reasonably simple way to use these long life resins that does not require continuous pH adjustment. By taking a portion of the treatment vessels off line and soaking them in a low pH solution, the rate constant for the reduction step is increased sufficiently to catch up, making the ion exchange step the limiting factor. The long life resin is effectively regenerated by the low pH soaks. Rejuvenated resin beds can then be put back on line and operated at the natural pH of the feedwater. This method of operation is protected by US Patent no. US20150136706A1. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Leveraging 3D CAD and Virtual Reality in Design of the Calcine Disposition Project - 20512

Fluor Idaho's Calcine Disposition Project (CDP) is leveraging the power of three-dimensional (3D) visualization, light detection and ranging (Lidar), and virtual reality to improve designs and worker safety. With the use of computer-aided design (CAD) modeling software, the CDP has created 3D models of the facility and systems to aid in the design, development, and operation of its retrieval and transfer system. This by itself is nothing new and has been done in industry for years. The CDP project however is taking this a few steps farther with the use of Lidar and virtual reality software. The CRP is tasked with removing a radioactive granular material from stainless steel bins located in concrete vaults that were constructed in the late 1950's and early 1960's. While construction drawings are available, it is not certain that the drawings are as-built or how accurate they truly are. Part of the project requires precise placement of equipment on to bins around multiple pipe, electrical lines, and bin stiffeners. Relying solely on the existing drawings and models created from these drawings is highly risky and prone to failure. The first step to determine the precise location and orientation of all obstructions in the vault the project will use a Lidar system to scan the vault structure and precisely locate all vault and bin components. Once this information is obtained, the data will be integrated into the CAD model. The model will then be verified, and a true as-built model developed. Precise component location, size, and orientation will be used for final design and placement of retrieval components. The second step will be to take the verified 3D model and scan data and import it into virtual reality software creating a virtual world. While some work on the project requires all work to be completed remotely due to high radiation fields, some areas have low enough radiation levels that personnel can enter and perform work. With the use of a virtual reality headset, operators and technicians will be able to enter our virtual world and become familiar with the surroundings and perform work prior to ever entering the radiation environment. This training is expected to pay dividends by improving worker efficiency, reducing errors, and improving confidence that the work can be performed as expected. It will play a key aspect in as low as reasonably achievable (ALARA) principles. An additional aspect in using the Lidar scans and virtual environment, is that it will give engineers and managers an opportunity to revisit the facility, especially radiation areas, at any time to obtain design information and measurements that may be costly or impossible to obtain once the facility transitions into radiation operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The German Site Selection Process - Implementation and Challenges - 20528

Federal Company for Radioactive Waste Disposal (Bundesgesellschaft fuer Endlagerung mbH; hereinafter referred to as BGE) is a state-owned company established in September 2016 following the 'Act on the Organisational Restructuring in the Field of Radioactive Waste Storage'. 'Repository Site Selection Act' (hereinafter referred to as StandAG) defines the site selection procedure, aiming to ensure the best possible safety for storing high-level radioactive waste in Germany for the duration of one million years. The selection procedure is a participatory, transparent, learning and self-questioning process based on scientific expertise. Possible repository sites are sought all over Germany, without excluding or predetermining any potential site at the beginning. The procedure consists of three phases. After each phase, the legislative decides on the regions for further consideration in the next phase of the site selection procedure. The current first phase (Phase I) is divided into two steps. Objective of Step 1 is to determine subareas of favorable geological conditions based on available data. Step 2 of Phase I will lead to identification of specific regions that are considered for further surface-based geoscientific and geophysical exploration. Potential host rocks are rock salt, clay rock and crystalline rock. As part of the site selection procedure, an overview of the status of the planning and implementation of R and D activities is given. Topics of particular interest are, for example, the adaptation of the maximum temperature of 100 deg. C at the container surface, the impact of long-term climate variations as well as minimally invasive exploration methods. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Investigations about iso-geometric analysis for self-shielding calculations with the subgroup method

The implementation of a self-shielding method for a neutron transport calculation code based on the iso-geometric analysis (IGA) method that can resolve the multi-group neutron transport equation for arbitrary spatial domain, is presented. The self-shielding model based on the subgroup theory is adopted because the subgroup method can be used to perform calculations for any arbitrary geometrical domain which is the main purpose of our IGA code. Some basic theory of the subgroup method is given. A self-shielding calculation based on the PWR fuel pin composed of MOX fuel is presented and compared with a Monte Carlo calculation. The result is that the combination of SN transport theory, IGA and the subgroup method gives correctly shielded cross sections. Validation of the combination of the IGA method and SN neutron transport for subgroup calculations in two steps are presented: the first step is to ascertain the correctness of the IGA solutions compared to a known analytical solution in diffusion theory; the second step is a validation of the IGA solutions compared to a reference calculation in SN transport theory. The relation between the settings for the IGA solver and the accuracy of the results are elucidated. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

An APEC-covered 2-D NEM macroscopic depletion analysis of partial MOX SMRs

A proper leakage correction is mandatory for a depletion analysis based on the conventional two-step method to take into account neighborhood effect. This study aims to apply the albedo-corrected parameterized equivalence constant (APEC) method to a macroscopic depletion in 2-D NEM analysis and assess the performance of introduced 1x1 and 2x2 APEC leakage corrections. The main idea of the APEC leakage correction is to correct homogenized group constants (HGCs) by predetermined APEC functions as a function of a normalized leakage parameter, current-to-flux ratio (CFR). Predetermined APEC functions consist of APEC cross-section (XS) and discontinuity factor (DF), and various color-set burnup calculations are conducted to generate burnup-dependent APEC functions. In this work, partial MOX SMR and variant cores are introduced to evaluate the applicability of the APEC leakage correction even in partially MOX-loaded SMRs, which are difficult to be analyzed by the conventional two-step method. Results show that the burnup-dependent 2x2 APEC leakage correction can improve the nodal equivalence in partial MOX SMRs. The burnup-dependent 2x2 APEC leakage correction is recommended to overcome the inherent limitation of the macroscopic depletion analysis with the conventional two-step method. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

6. Closed-Loop Toolpath Generation

Closed-loop paths, also known as closed-loop contours, are paths that start and stop at the same point and are typically used to define the perimeter or outermost boundary of the polygon that represents a given layer of an object, referred to as the “layer polygon.” Finding the location of a closed-loop path involves applying two offsetting steps to the edge of the layer polygon. The offsetting steps respectively serve to (1) find the area that contains the toolpath and (2) find the centerline of that area, to define the path itself. After finding the perimeter path, the remaining geometry from the layer polygon can be used for additional path-planning steps. This chapter will discuss how the location for a closed-loop path is found, including various problem scenarios, and the different types of closed-loop paths used in additive manufacturing.

Roschli, Alex↗

AI-based Detection and Defense Against Cyberattacks in Distributed Energy Resources

This study will provide comprehensive artificial intelligence (AI)-based solution tools for network security, malware prevention, and sensor data anomaly detection for distributed energy resource (DER) research, development, and demonstration. DER technologies are energy systems (e.g., solar panels, wind turbines, and energy storage systems) that are often connected to the internet and thus vulnerable to cyberattacks. Cybersecurity should be of primary concern for DERs, which is why we propose an integrated multi-layer cyber-defense system for DERs. This system encompasses risk assessments, network security, malware prevention, and detection of anomalies in the sensor data. Implementation of a comprehensive risk assessment with an overview of the model architecture should be the primary step, and should include the potential impact of experiencing, at a given time, one or more cyberattacks on the system. The second step is to ensure that the network security includes firewalls, intrusion detection, and malware prevention. The third step is to provide solution tools that enable sensor data anomaly detection for DERs. By incorporating these considerations into DER research, development, and demonstration, organizations can help ensure the safety and security of their systems and protect against potential cyberattacks.

20 FOSSIL-FUELED POWER PLANTS↗

Combustion Synthesis of Transuranic-doped Ceramics for Nuclear Waste Immobilization

Utilizing the devised SCS technique, crystalline transuranic-doped zirconate pyrochlores were formed for the first time without the need for a subsequent heating step. Typically, materials rapidly synthesized in a single-step self-sustaining exothermic reaction require further heating to induce crystallization and purify the product. The need for this secondary processing step can be attributed to factors such as an improper oxidizer to fuel ratio and the utilization of strong complexing compounds as fuels (i.e., reducing agents), all of which hinder complete combustion. The efficacy of the developed process was demonstrated by fabricating crystalline plutonium-doped Gd2Zr2O7 from solutions containing metal nitrates and urea in a properly tuned ratio

Burton-Allen, Janiya D.↗

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗

Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems

Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE-GENIORS Dynamic Irradiation Testing

As part of the homogeneous actinides recycling strategy, the EURO-GANEX process is one of the most promising options to achieve the goal of minor actinides recovery. Improvements made to EURO-GANEX system have resulted in the emergence of the so-called New EURO-GANEX process, where the composition of the solvent has been modified by replacing TODGA and DMDOHEMA with cis-mTDDGA in the organic phase and SO3-Ph-BTP with PyTri-Diol in the aqueous phase in order to resolve important issues. The objective of this work is twofold: evaluate the gamma radiolytic resistance of the new EURO-GANEX process by dynamic irradiation conditions simulating the three main steps of the process, and validate the design of CIEMAT Náyade, CEA Marcel and INL irradiation loop devices since each of them mimics different aspects of the real process. Náyade and the INL loops could irradiate the organic and aqueous phases together, whereas in the CEA loop, the irradiated solvent is recycled continuously inside a platform with several stages of mixer-settlers containing aqueous flows simulating the three main steps of the process. The extraction performances and changes in the composition of the solvent have been analyzed during the irradiation experiment by different techniques: gamma spectrometry and ICP-MS/OES for cations or radioactive tracer extraction, and HPLC-MS to identify and quantify the degradation compounds. Despite some differences between the three-irradiation facilities, this inter-institutional study shows that these three comparative tools provide similar trends in the radiolytic stability of a liquid-liquid extraction system. Favourable extraction results for the different steps are obtained according to the static irradiation studies found in literature. However, the degradation of cis-mTDDGA is appreciable leading to degradation compounds, some of which form precipitates and produce important changes in viscosity, important aspects that must be addressed prior to the successful industrial application of the new EURO-GANEX process.

38 - RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCL↗