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DOE OSTI2025

Lattice structure and dynamics of sparse molecular crystals: OsO4 and RuO4

This dataset contains input and output files from DFT simulations used to reproduce the electronic and phonon calculations of bulk and molecular OsO₄ and RuO₄. The files include data from initial electronic structure and phonon calculations performed using different functionals: PBE, PBEsol, and vdW-DF-optB86b. The computed phonon frequencies are compared with Raman crystal and gas-phase frequencies from existing literature, while the calculated phonon density of states (PhDOS) is compared with experimental PhDOS data.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Origin and evolution of HIV-1 subtype A6

Background: HIV outbreaks in the Former Soviet Union (FSU) countries were characterized by repeated transmission of the HIV variant AFSU, which is now classified as a distinct subtype A sub-subtype called A6. The current study used phylogenetic/phylodynamic and signature mutation analyses to determine likely evolutionary relationship between subtype A6 and other subtype A sub-subtypes. Methods: For this study, an initial Maximum Likelihood phylogenetic analysis was performed using a total of 553 full-length, publicly available, reverse transcriptase sequences, from A1, A2, A3, A4, A5, and A6 sub-subtypes of subtype A. For phylogenetic clustering and signature mutation analysis, a total of 5961 and 3959 pol and env sequences, respectively, were used. Results: Phylogenetic and signature mutation analysis showed that HIV-1 sub-subtype A6 likely originated from sub-subtype A1 of African origin. A6 and A1 pol and env genes shared several signature mutations that indicate genetic similarity between the two subtypes. For A6, tMRCA dated to 1975, 15 years later than that of A1. Conclusion: The current study provides insights into the evolution and diversification of A6 in the backdrop of FSU countries and indicates that A6 in FSU countries evolved from A1 of African origin and is getting bridged outside the FSU region.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Improved measurements of nonlinear integrable optics at IOTA

Nonlinear integrable optics (NIO) are a promising novel approach at improving the stability of high intensity beams. Implementations of NIO based on specialized magnetic elements are being tested at the Integrable Optics Test Accelerator (IOTA) at Fermilab. One method of verifying proper implementation of these solutions is by measuring the analytic invariants predicted by theory. The initial measurements of nonlinear invariants were performed during IOTA run in 2019/20, however the covid-19 pandemic prevented the full-scale experimental program from being completed. Several important improvements were implemented in IOTA for the 2022/23 run, including the operation at higher beam energy of 150 MeV, improved optics control, and chromaticity correction. This report presents on the improved calibrations of the NIO for nonlinear invariant measurements.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Low-Temperature Plasma Treatment for Enhanced Recovery of Highly Valued Critical REEs from Coal (Final Report)

The principle objective of this project was to develop a novel process flowsheet using low-temperature plasma treatment (LTP) integrated with conventional hydrometallurgical processes to recover rare earth elements (REEs), especially highly valued REEs (i.e. scandium and critical REEs), from coal and coal byproducts. LTP treatment was used to pretreat the solid feed material prior to leaching in an effort to improve the leaching characteristics of the REEs and potentially reduce acid consumption. Initially, a detailed experimental program was performed on a laboratory LTP furnace to identify a set of process parameter values to be used for assessing the enhanced leaching performance achieved on four specific gravity fractions of West Kentucky No. 13 and Fire Clay coarse coal refuse materials. High-temperature oxidation (HTO)) was also evaluated as a means for improving REE leachability on the same fractions of both coal sources. The lixiviants used to assess leachability improvements included: i) untreated water, ii) 0.1 M ammonium sulfate solution and iii) 1.2 M sulfuric acid solution at a temperature of 75°C. The laboratory data was used to develop multiple process flow sheets using HTO only to produce a rare earth oxide mix concentrate or utilizing both LTP and HTO treatment processes to generate a high purity heavy REO mix concentrate and a light REO mix concentrate. A techno-economic analysis was performed on each circuit. Low-temperature plasma oxidation was found to enhance REE leaching characteristics for all specific gravity (SG) fractions of the West Kentucky No. 13 coarse refuse material. The leaching recovery improvement was preferentially achieved for the heavy REEs with higher values obtained when treating the lower density fraction material. For example, the leaching recovery for the heavy REEs in the untreated 1.6 SG Float fraction material was 8% in a 0.1 M ammonium sulfate solution. After LTP treatment for 32 hours, heavy REE recovery increased to 33%. The corresponding recovery value for the light REEs was 10%. These findings indicate a strong affinity of the heavy REEs with the organic material, which is the component being reduced in content during the LTP treatment. Scanning electron micrographs showed the development of a honeycomb structure with increased LTP treatment with higher surface area as confirmed from BET measurements. Higher surface area promotes improved leaching efficiency due to enhance chemical interactions. When using 1.2 M sulfuric acid, the LTP treatment was found to provide a heavy REE recovery increase from 23% to 53% for the 1.6 SG Float fraction which corresponded to an ash content increase from around 20% to 35%. However, LTP treatment provided no improvement in leaching characteristic for the 2.2 SG sink material in the acid solution, which was likely due to the low organic content. The LTP treatment of the Fire Clay SG fractions provided no improvement in REE leaching characteristic, which may be due to the association with REE minerals such as monazite and REE-associated mineral matter such as clays. High temperature oxidation using temperatures in the range of 600-750OC was found to significantly enhance the leaching characteristics of both the light and heavy REEs for all density fractions in both coarse coal refuse materials. Generally, the increase in light REE recovery for the West Kentucky material was from 15% for the untreated material to 90% for the HTO treated material at 600°C. Recovery values dropped significantly when using temperatures below 600°C and above 750°C. The impact of the excessive temperatures was most likely a result of sintering. For the heavy REEs, HTO significantly improved recovery in the lighter SG fractions, which may be due to an affinity with the organic content. Only limited heavy REE recovery improvement was obtained for the denser SG fractions. Another benefit of HTO is the conversion of calcium-based minerals to a very soluble calcium oxide, which is removable using a mild acid solution, and the conversion of Fe minerals to relatively insoluble minerals such as hematite and magnetite. The pregnant leaching solution produced from the leaching of all SG fractions obtained from both coal sources was treated using two stages of solvent extraction procedurally modeling a rougher-cleaner circuit followed by oxalic acid precipitation. Rare earth oxide products having a purity greater than 97% was produced from nearly all of the SG fractions. A novel process flowsheet was developed based on the selective leaching of heavy REEs that was made possible through LTP treatment of West Kentucky No. 13 coarse refuse followed by salt leaching. In the flowsheet, coal refuse material is ground to a top size of 1mm and then treated by LTP. The treated material is mixed into a 0.1 M ammonium sulfate solution and then filtered to produce a heavy REE enriched pregnant leach solution. The heavy REEs are concentrated by two stages of selective precipitation to produce a heavy REE mix oxalate and then roasted to obtain a heavy REO mix concentrate. The solid residues remaining after salt leaching is dried and then subjected to HTO treatment followed by concentration using selective precipitation and roasting to produce a light REO mix concentrate. An alternative circuit was developed using HTO treatment only to treat 100% of the coarse refuse material followed by selective precipitation and roasting to generate a high purity REO mix product. A techno-economic analysis performed for the treatment of West Kentucky No. 13 and Fire Clay coarse refuse based on a hypothetical 500-tph plant revealed that the net present value for all scenarios was significantly negative. Primary reasons include: i) a substantial decrease in the basket value of the final product relative to the feed and ii) high chemical costs relative to the amount of product generated. The basket value reduction was primarily due to little to no scandium recovery due to poor leaching characteristics when using low acid concentrations as necessitated by the low feed grades. Operating costs were primarily influenced by the chemical costs relative to the kilograms of concentrate produced and feed grade. For the Fire Clay coarse refuse material, the total operating cost was estimated to be $354 per kg of REO produced which was higher than the basket value of the REO product ($276/kg). Approximately 37% of the total cost was the sulfuric acid used during the leaching process. A comparative analysis performed to assess the economic viability of using low-temperature plasma furnaces found that market value enhancement for the generation of both heavy REO and light REO concentrates will be needed in addition to significant technology advancements to reduce the cost of plasma furnaces.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Adaptive Recovery Model: Designing Systems for Testing Tracing and Vaccination to Support COVID-19 Recovery Planning.

This report documents a new approach to designing disease control policies that allocate scarce testing, contact tracing, and vaccination resources to better control community transmission of COVID19 or similar diseases. The Adaptive Recovery Model (ARM) combines a deterministic compartmental disease model with a stochastic network disease propagation model to enable us to simulate COVID-19 community spread through the lens of two complementary modeling motifs. ARM contact networks are derived from cell-phone location data that have been anonymized and interpreted as individual arrivals to specic public locations. Modeling disease spread over these networks allows us to identify locations within communities conducive to rapid disease spread. ARM applies this model- and data-derived abstractions of community transmission to evaluate the effectiveness of disease control measures including targeted social distancing, contact tracing, testing and vaccination. The architecture of ARM provides a unique capacity to help decision makers understand how best to deploy scarce testing, tracing and vaccination resources to minimize disease-spread potential in a community. This document details the novel mathematical formulations underlying ARM, presents a dynamical stability analysis of the deterministic model components, a sensitivity analysis of control parameters and network structure, and summarizes a process for deriving contact networks from cell-phone location data. An example use case steps through applying ARM to evaluate three targeted social distancing policies using Bernalillo County, New Mexico as an exemplar test locale. This step-by-step analysis demonstrates how ARM can be used to measure the relative performance of competing public health policies. Initial scenario tests of ARM shows that ARMs design focus on resource utilization rather than simple incidence prediction can provide decision makers with additional quantitative guidance for managing ongoing public health emergencies and planning future responses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Low-Temperature Plasma Treatment for Enhanced Recovery of Highly Valued Critical REEs from Coal (Final Technical Report)

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Coupling of CTF and TRACE for Modeling of Transients

This report documents the improvements that have been made to the capabilities for coupling CTF to systems codes-specifically, the US Nuclear Regulatory Commission (NRC) TRACE code. An initial systems coupling capability had been set up previously using a nonoverlapping domain approach with the codes exchanging data at the core boundaries. The present work adds a new approach using overlapping domains, in which the system code models the core as well. A new input format has been added to allow the user to specify the physical quantities to be exchanged and their location in the system model, which gives the flexibility of applying one-way or two-way coupling between the codes using the desired data exchanges. In addition to applying thermal-hydraulics (T/H) boundary condition (BC) values obtained from TRACE, a capability was added to allow CTF to apply flow resistance feedback to TRACE to match the CTF core pressure drop. Support was added for executing parallel CTF models within the CTF-systems coupling. The system coupling capability was successfully applied to a parallel MSLB transient, demonstrating that both the one-way and two-way coupling behaved as expected and provided substantial improvements to numerical stability and routine compared to the previous nonoverlapping domain coupling. An initial capability was also developed for performing restart calculations in CTF which will be used in the future for restarting CTF-TRACE simulations at specific points in the transient simulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

A Combined Water and CO2 Direct Air Capture System (CRADA 521)

The primary objective of this project is to demonstrate the outstanding technical and economic performance of a transformational Hybrid DAC (HDAC) technology that simultaneously captures CO2 and water from the air. Air is passed over a CO2 selective sorbent to remove ≥85% of the CO2 from the air stream. The atmospheric water extraction (AWE) section of the unit utilizes a novel isothermal pressure swing regeneration cycle with desiccant beds thermally coupled by heat pipes that provide a passive heat transfer mechanism to “cancel” the heat of water vapor adsorption. By proving system performance through this demonstration project, our initial technoeconomic analysis (TEA) will be validated, showing that HDAC technology: 1) is deployable in many more locations with limited water resources, 2) improves the financial returns, and 3) reduces risks from volatility in the price of CO2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Questionable Benchmarks [Slides]

An investigation and initial review of ‘questionable benchmarks’ was performed at LANL. Multiple methods were used, including machine learning techniques, to identify 'questionable benchmarks' and/or benchmarks with low uncertainties. Those benchmarks were then reviewed for obvious errors. This is not a recommendation to ICSBEP, but can be used as a starting point for a more comprehensive review. A journal paper is being written on this work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Final Cooling with Thick Wedges for a Muon Collider

A muon collider is a particle accelerator that collides muons rather than protons or electrons. An important component of such a collider is cooling, in which the emittance of the muon beam is reduced to make it suitable for use in a collider. In the last stage of this process, called final 4D cooling, emittance in the transverse axes is reduced while emittance in the longitudinal axis is allowed to grow. In previous studies, Final 4-D cooling used absorbers within very high field solenoids to cool low-momentum muons. Simulations of the systems did not reach the desired cooling design goals. In this study, we develop and optimize a different conceptual design for the final 4D cooling channel, which is based on single thick wedges. We used G4Beamline to simulate the channel and Python to generate and analyze particle distributions. We characterized the effects of various parameters on the performance of this system, including the initial emittances and Twiss parameters, the length and angle of the wedges, the length of the drift channel, and the length, frequency, gradient, and phase of the RF cavities. We optimized the design parameters of the cooling channel and produced two conceptual designs (corresponding to two possible starting points for the input beam) which achieve transverse cooling in both x and y by a factor of ≈ 3.5. These channels achieve a lower transverse and longitudinal emittance than the best design previously published.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Manufacturing of Fabric Electrodes using a High-Throughput Screening Platform for Redox Flow Batteries

The objective of this project is to establish a new manufacturing methodology with machine learning- based high-throughput screening for the design and development of hierarchical structured, high-performance fabric electrodes for redox flow batteries (RFBs). The end goal of the project is to design and manufacture fabric electrodes for RFB applications that can provide 250 mA/cm2 current density operation for 100-cycles with 80% average energy efficiency. This was accomplished by first examining the structure-performance-property linkages of the electrodes provided by our partner, AvCarb. The electrodes’ microstructure was characterized by determining their pore size distribution, tortuosity, specific surface area, and porosity. The ohmic, charge transfer and mass transfer resistances were then calculated using electrochemical impedance spectroscopy. Carbon cloth electrodes showed the greatest resistance, which was dominated by charge transfer resistance, which we believe is related to the surface functionalization. Full cell cycling was used in order to determine the area specific resistance and energy efficiency of the cells. All of this experimental data and the results of the mathematical model (to increase the amount of inputs with parametric sweeping) were used to develop a machine learning-based model for the design of high-performance fabric electrodes. Using the results from the machine learning tool, optimized electrodes were fabricated by AvCarb. The ohmic, charge transfer and mass transfer resistances for these new electrodes were measured, and both performed better than any of the initial samples which had been provided by AvCarb.

25 ENERGY STORAGE↗

DOE OSTI2025

Advanced Processing of Coal and Coal Waste to Produce Graphite for Fast-Charging Lithium-Ion Battery Anode

The University of North Dakota (UND) Energy & Environmental Research Center (EERC), in collaboration with the UND Center for Process Engineering Research (CPER), conducted a project to validate two technologies capable of converting North Dakota lignite and lignite coal waste to high-quality graphite for fast-charging lithium-ion battery (LIB) anode. The project was conducted over about 3 years from April 7, 2022, to July 6, 2025. The two technological paths pursued in this project include path A – direct conversion of coal or coal waste to graphite by the upgraded carbon ores to products (UCOP) process being developed at the EERC and path B – lignite-derived coal tar pitch (CTP) conversion to graphite (CTP2G) process being developed at CPER. The results from this project validate the two technological approaches and are expected to be an integral part of a portfolio of emerging technologies for making high-quality graphite not only from North Dakota lignite, but from all ranks of U.S. domestic coal and coal waste resources. The quality of the graphite produced by these technologies is high enough for various applications, including batteries for the fast-growing electric vehicle industry, energy storage applications, electric arc furnace electrodes for steel production, and graphene production, among others. Although the two technologies can produce high-quality graphite, they are fundamentally different in that the UCOP technology provides a direct path to transform coal to graphite, while the CTP2G technology needs to go through a CTP intermediate and a coking process for the intermediate, which requires a special facility to accomplish. For application in the industry, the UCOP process is designed to be more flexible, with feedstock to include potentially any carbonaceous material such as all coal ranks and biochar, while the CTP2G process is designed to utilize CTP as the starting precursor. The key project accomplishments include the following: • Successful preparation of high-quality synthetic graphite from North Dakota lignite coal/coal wastes and lignite-derived CTP. • Patent application has been filed for the UCOP process and an internal invention disclosure has been filed for the CTP2G process. • The produced graphite performs better than a commercial battery-grade sample in LIB coin cells, especially fast-charging capability, stability, and long-duration cycling. • Coin-type Li-ion half-cells with CTP2G graphite showed excellent performance, with >370 mAh/g capacity, >90% initial coulombic efficiency, and 93%/67% retention at 1C/2C rate, which outperforms commercial graphite in charging speed, stability, and cycling. • Results of fabricated 18650 cells were consistent with the observations in coin cells. • Preliminary techno-economic analysis (TEA) estimates for the UCOP technology indicate a manufacturing cost of about $\$$39/kg based on 50-metric ton/year capacity. • Preliminary TEA estimates for the CTP2G technology indicate a market price of about $\$$7107/ton ($\$$7/kg) based on 22,000-ton/year production capacity.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Initial Refinement and Optimization of the Image Reconstruction (U-MBIR) Algorithm to Optimize its Performance in Detecting Damage and Flaws

Concrete is a critical component of nuclear power plants; thus, its safety and reliability must be thoroughly examined throughout the life cycle of the structural system. During the life cycle of this infrastructure, monitoring of the concrete for signs of degradation should be performed through nondestructive evaluation (NDE). Ultrasonic measurements have been an industry standard for both surface and subsurface inspections. As such, Oak Ridge National Laboratory (ORNL) is developing advanced image reconstruction algorithms to overcome the limitations of traditional ultrasonic NDE methodologies. The results and discussion presented herein summarize the current state of the ultrasonic model–based iterative reconstruction (U-MBIR) algorithm developed at ORNL.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection

The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of data, making it challenging and expensive to deploy data analytics platforms in new environments. Transfer learning (TL) mechanisms promise to mitigate data sparsity and model complexity by utilizing pre-trained models for a new task. Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. In this study, we present the potential of TL within the context of high-dimensional ST AD with a hybrid autoencoder architecture, incorporating convolutional, graph, and recurrent neural networks. Motivated by the need for improved model accuracy and robustness, particularly in scenarios with limited training data on systems with thousands of sensors, this research investigates the transferability of models trained on different sections of the Hadron Calorimeter of the Compact Muon Solenoid experiment at CERN. The key contributions of the study include exploring TL’s potential and limitations within the context of encoder and decoder networks, revealing insights into model initialization and training configurations that enhance performance while substantially reducing trainable parameters and mitigating data contamination effects.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Spatial heterogeneity effects on land surface modeling of water and energy partitioning

Abstract. Understanding the influence of land surface heterogeneity on surface water and energy fluxes is crucial for modeling earth system variability and change. This study investigates the effects of four dominant heterogeneity sources on land surface modeling, including atmospheric forcing (ATM), soil properties (SOIL), land use and land cover (LULC), and topography (TOPO). Our analysis focused on their impacts on the partitioning of precipitation (P) into evapotranspiration (ET) and runoff (R), partitioning of net radiation into sensible heat and latent heat, and corresponding water and energy fluxes. An initial set of 16 experiments were performed over the continental US (CONUS) using the E3SM land model (ELMv1) with different combinations of heterogeneous and homogeneous datasets. The Sobol' total and first-order sensitivity indices were utilized to quantify the relative importance of the four heterogeneity sources. Sobol' total sensitivity index measures the total heterogeneity effects induced by a given heterogeneity source, consisting of the contribution from its own heterogeneity (i.e., the first-order index) and its interactions with other heterogeneity sources. ATM and LULC are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning, mainly contributed by their own heterogeneity and slightly contributed by their interactions with other heterogeneity sources. Their heterogeneity effects are complementary, both spatially and temporally. The overall impacts of SOIL and TOPO are negligible, except TOPO dominates the spatial variability of R/P across the transitional climate zone between the arid western and humid eastern CONUS. Accounting for more heterogeneity sources improves the simulated spatial variability of water and energy fluxes when compared with ERA5-Land reanalysis dataset. An additional set of 13 experiments identified the most critical components within each heterogeneity source, which are precipitation, temperature, and longwave radiation for ATM, soil texture, and soil color for SOIL and maximum fractional saturated area parameter for TOPO.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

The AWAKEN wind farm benchmark, Part 2: Modeling results

Accurately modeling wind farm performance in complex atmospheric flows remains a challenge. This paper presents the modeling results of the American WAKE experimeNt (AWAKEN) wind farm benchmark, a collaborative effort involving 16 research groups from academia and industry within the International Energy Agency Wind Technology Collaboration Programme Task 57. The study evaluates a diverse suite of simulation tools, ranging from fast-running engineering wake models to high-fidelity large-eddy simulations, against a diurnal case study observed during the AWAKEN campaign. The benchmark utilized a three-phase structure to progressively assess model performance as observational data availability increased. Initial blind predictions showed that higher-fidelity models did not uniformly outperform simpler simulation tools. A distinct spatial bias was observed where models struggled to resolve the interplay between a low-level jet, wakes, and terrain-induced flow acceleration. In subsequent phases, leveraging additional measurements for model improvement led to a reduction in mean absolute error across the model ensemble; however, this effect was most pronounced in engineering wake models, where targeted calibration reduced error by up to 40~\%. Overall, the study demonstrates that inflow characterization remains a primary prerequisite for accuracy, particularly for models relying on coarse forcing datasets. While the limited ability to resolve local terrain-flow interactions under single-day conditions represent a recognized constraint, the overall findings on wake modeling and real-world validation still provide valuable guidance for model application and for mitigating this limitation.

Bodini, Nicola↗

DOE OSTI2020

The Locus Algorithm III: A Grid Computing system to generate catalogues of optimised pointings for Differential Photometry

This paper discusses the hardware and software components of the Grid Computing system used to implement the Locus Algorithm to identify optimum pointings for differential photometry of 61,662,376 stars and 23,799 quasars. The scale of the data, together with initial operational assessments demanded a High Performance Computing (HPC) system to complete the data analysis. Grid computing was chosen as the HPC solution as the optimum choice available within this project. The physical and logical structure of the National Grid computing Infrastructure informed the approach that was taken. That approach was one of layered separation of the different project components to enable maximum flexibility and extensibility.

Creaner, Oisń↗