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At least 1,549 records · Page 86

Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior. To address this, self- and binary association energies were calculated for each molecule and mixture to provide information on intermolecular interaction strength and were used as input features to the ANN. An accurate, generalized ANN model was developed with an overall average absolute deviation of 4.1%. Forward input feature selection reveals the importance of critical properties and self-association energies along with other fluid properties. Additional ANNs were developed with subsets of the full input feature set to further investigate the impact of various properties on model performance. The results from two specific mixtures are discussed in additional detail: one providing an example of strong hydrogen bonding and the other an example of extreme pressure changes, with the ANN models predicting self-diffusion well in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

3D Microstructures for Materials and Damage Models

Many challenges exist with regard to understanding and representing complex physical processes involved with ductile damage and failure in polycrystalline metallic materials. Currently, the ability to accurately predict the macroscale ductile damage and failure response of metallic materials is lacking. Research at Los Alamos National Laboratory (LANL) is aimed at building a coupled experimental and computational methodology that supports the development of predictive damage capabilities by: capturing real distributions of microstructural features from real material and implementing them as digitally generated microstructures in damage model development; and, distilling structure-property information to link microstructural details to damage evolution under a multitude of loading states.

36 MATERIALS SCIENCE↗

Dual Context: Leveraging Structured Application Context for Code Generation and Runtime Feature Activation via Chat Interfaces

Integrating artificial intelligence (AI) capabilities into software applications typically involves two common paths. For developers, AI assists in generating and documenting source code and other related software engineering efforts. For users, AI assists them through question-and-answer exchanges via chatbots. Both approaches have their value, but neither effectively leverages the modularity of component-based architectures that modern web application frameworks offer. We implement a proof of concept within a centralized suite of applications used for the Atmospheric Radiation Measurement (ARM) Data Center Operational Tools, where we introduce a third integration path through the ARM Context Engine (ACE). ACE is a context driven system that uses structured contextual specifications to enable Large Language Models (LLMs) to render interactive and feature-rich user interface (UI) components directly within chat responses, alongside or in place of conventional text outputs. These specifications serve two important purposes across what we call code context and UI context. Code context provides AI-assisted development tools with structured application knowledge beyond raw code, including component relationships, architectural patterns and schematic information, enabling the generation of consistent, well-structured code. UI context defines the rules for enabling and rendering component features at runtime based on the user's natural language input, allowing end users to activate capabilities such as data export, filtering, and pagination within chat responses, without requiring code changes or redeployment. We demonstrate, through a comparative evaluation against general-purpose AI chatbots, that context-driven component rendering provides interactive capabilities that text-based responses cannot replicate, including deterministic component behavior, application-consistent design language, and on-demand feature activation. A development effort comparison further shows that features that traditionally require multi-step development cycles can be activated with a single naturallanguage request. In this ongoing work, we present ACE as an emerging approach to AI integration that positions modular, well-documented software architecture as the foundation for AI-ready applications. ACE treats context as a shared resource across both development and user-facing AI, bringing cohesion to conventionally disconnected efforts, bridging developer tooling and end-user capabilities within a single framework.

Tadimeti, Vijay [ORNL]↗

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Complex Geometry Effects on Cavity Resonance

The flow over an aircraft bay is often represented using a rectangular cavity; however, this simplification neglects many features of actual flight geometry that could affect the unsteady pressure field and resulting loading in the bay. To address this shortcoming, a complex cavity geometry was developed to incorporate more realistic aircraft-bay features including shaped inlets, internal cavity structure, and doors. A parametric study of these features was conducted based on fluctuating pressure measurements at subsonic and supersonic Mach numbers. Resonance frequencies and amplitudes increased in the complex geometry compared to a simple rectangular cavity that could produce severe loading conditions for store carriage. High-frequency content and dominant frequencies were generated by features that constricted the flow such as leading-edge overhangs, internal cavity variations, and the presence of closed doors. Broadband frequency components measured at the aft wall of the complex cavities were also significantly higher than in the rectangular geometry. Furthermore, these changes highlight the need to consider complex geometric effects when predicting the flight loading of aircraft bays.

42 ENGINEERING↗

Orbital and spin character of doped carriers in infinite-layer nickelates

The recent discovery of superconductivity in Nd1-xSrxNiO2 has drawn significant attention in the field. A key open question regards the evolution of the electronic structure with respect to hole doping. Here we exploit x-ray absorption spectroscopy (XAS) and resonant inelastic x-ray scattering (RIXS) to probe the doping-dependent electronic structure of Nd1-xSrxNiO2. Upon doping, a high-energy feature in Ni L3-edge XAS develops in addition to the main absorption peak, while XAS at the O K-, Nd M3- and Nd M5-edge exhibits a much weaker response. This implies that doped holes are mainly introduced into Ni 3d states. By comparing our data to atomic multiplet calculations including D4h crystal field, the doping-induced feature in Ni L3-edge XAS is consistent with a d8 spin-singlet state in which doped holes reside in the 3dx2-y2 orbitals. This is further supported by the softening of RIXS orbital excitations due to doping, corroborating with the Fermi level shift associated with increasing holes in the Ni 3dx2-y2 orbital.

2-dimensional systems↗

A neutralizing antibody target in early HIV-1 infection was recapitulated in rhesus macaques immunized with the transmitted/founder envelope sequence

Transmitted/founder (T/F) HIV-1 envelope proteins (Envs) from infected individuals that developed neutralization breadth are likely to possess inherent features desirable for vaccine immunogen design. To explore this premise, we conducted an immunization study in rhesus macaques (RM) using T/F Env sequences from two human subjects, one of whom developed potent and broad neutralizing antibodies (Z1800M) while the other developed little to no neutralizing antibody responses (R66M) during HIV-1 infection. Using a DNA/MVA/protein immunization protocol, 10 RM were immunized with each T/F Env. Within each T/F Env group, the protein boosts were administered as either monomeric gp120 or stabilized trimeric gp140 protein. All vaccination regimens elicited high titers of antigen-specific IgG, and two animals that received monomeric Z1800M Env gp120 developed autologous neutralizing activity. Using early Env escape variants isolated from subject Z1800M as guides, the serum neutralizing activity of the two immunized RM was found to be dependent on the gp120 V5 region. Interestingly, the exact same residues of V5 were also targeted by a neutralizing monoclonal antibody (nmAb) isolated from the subject Z1800M early in infection. Glycan profiling and computational modeling of the Z1800M Env gp120 immunogen provided further evidence that the V5 loop is exposed in this T/F Env and was a dominant feature that drove neutralizing antibody targeting during infection and immunization. An expanded B cell clonotype was isolated from one of the neutralization-positive RM and nmAbs corresponding to this group demonstrated V5-dependent neutralization similar to both the RM serum and the human Z1800M nmAb. The results demonstrate that neutralizing antibody responses elicited by the Z1800M T/F Env in RM converged with those in the HIV-1 infected human subject, illustrating the potential of using immunogens based on this or other T/F Envs with well-defined immunogenicity as a starting point to drive breadth.

59 BASIC BIOLOGICAL SCIENCES↗

A Cultural Resources Inventory and Historical Evaluation of the Smoky Atmospheric Nuclear Test, Areas 8, 9, and 10, Nevada National Security Site, Nye County, Nevada

This report presents the results of a National Historic Preservation Act Section 106 cultural resources inventory and historical evaluation of the 1957 Smoky atmospheric test location on the Nevada National Security Site (NNSS). The Desert Research Institute (DRI) was tasked to conduct a cultural resources study of the Smoky test area as a result of a proposed undertaking by the Department of Energy Environmental Management. This undertaking involves investigating Corrective Action Unit (CAU) 550 for potential contaminants of concern as delineated in a Corrective Action Investigation Plan. CAU 550 is an area that spatially overlaps portions of the Smoky test location. Smoky, T-2c, was a 44 kt atmospheric nuclear test detonated at 5:30 am on August 31, 1957, on top of a 213.4 m (700 ft) 200 ton tower (T-2c) in Area 8 of the NNSS. Smoky was a weapons related test of the Plumbbob series (number 19) and part of the Department of Defense Exercise Desert Rock VII and VIII. The cultural resources effort involved the development of a historic context based on archival documents and engineering records, the inventory of the cultural resources in the Smoky test area and an associated military trench location in Areas 9 and 10, and an evaluation of the National Register eligibility of the cultural resources. The inventory of the Smoky test area resulted in the identification of structures, features, and artifacts related to the physical development of the test location and the post-test remains. The Smoky test area was designated historic district D104 and coincides with a historic archaeological site recorded as 26NY14794 and the military trenches designed for troop observation, site 26NY14795. Sites 26NY14794 and 26NY14795 are spatially discrete with the trenches located 4.3 km (2.7 mi) southeast of the Smoky ground zero. As a result, historic district D104 is discontiguous and in total it covers 151.4 hectares (374 acres). The Smoky test location, recorded as historic district D104 and historic sites 26NY14794 and 26NY14795, is the best preserved post-shot atmospheric nuclear tower test at the NNSS and possibly in the world. It is of local, national, and international importance due to nuclear testing’s pivotal role in the Cold War between the United States and the former Soviet Union. The district and sites are linked to the historic theme of atmospheric nuclear testing. D104 retains aspects of the engineering plan and design for the Smoky tower, instrument stations used to measure test effects, German and French personnel shelters, and military trenches. A total of 33 structures contribute to the significance of D104. Artifacts and features provide significant post-test information. Historic district D104 (discontiguous) and historic site 26NY14794 (the Smoky test area) are eligible for listing on the NRHP under Criteria A, B, C, and D. The historic site 26NY14795 (the Smoky military trenches) is eligible for listing under Criteria A, C, and D. Several items have been identified for removal by the CAU 550 investigation. However, none of them is associated with the Smoky atmospheric test, but with later activities in the area. The military trenches are not part of CAU 550 and no actions are planned there. A proposed closure of the Smoky test area with restrictions will limit access and contribute to the preservation of the cultural resources. It is recommended that the Smoky historic district and sites be included in the NNSS cultural resources monitoring program.

54 ENVIRONMENTAL SCIENCES↗

SIS-AOP Cueing/Segmenting Algorithm (FOA_SIS-AOP) Using the Sandia FOA 4.0 Framework

For machine vision, one of the most important operations is fast and effective object cueing or segmentation. Sandia National Labs has a long history of development and implementation of very fast and effective cueing/segmentation algorithms. This report covers the history, motivation and implementation of evolving frameworks (Sandia FOA Frameworks) upon which this long legacy of successful algorithms are built. The report describes the innovative microprocessor implementation, enabling extremely fast morphological processing, combined with a novel adaptive quantization front - end and a feature - based backend that resulted in Sandia developing fast and effective cueing in a wide variety of applications, from defect detection to SAR ATR. The report covers evolution from Sandia FOA 1.0 Framework (1995) to current Sandia FOA 4.0 Framework (2021). Requirements for the cueing algorithm for SIS - AOP (FOA_SIS - AOP) that drove the Sandia FOA 4.0 Framework development are discussed, along with information on how to use the Sandia FOA Frameworks.

97 MATHEMATICS AND COMPUTING↗

Feature discrimination and detection probability in synthetic aperture radar imaging system

Images obtained using synthetic aperture radar (SAR) systems can only represent the intensities of resolution cells in the scene of interest probabilistically since radar receiver noise and Rayleigh scattering of the transmitted radiation are always present. Consequently, when features to be identified differ only by their contribution to the mean power of the radar return, discrimination can be treated by detection theory. In this paper, we develop a 'sufficient statistic' for discriminating between competing features and compare it with some suboptimal methods frequently used. Discrimination is measured by probability of detection error and depends on number of samples or 'looks', signal-to-noise ratio (SNR), and ratio of mean power returns from the competing features. Our results show discrimination and image quality rapidly saturate with SNR (very small improvement for SNR not less than 10 dB) but continue to improve with increasing number of looks.

Lipes, R. G.↗

Greater Sage-Grouse Habitat Use and Population Demographics at the Simpson Ridge Wind Resource Area, Carbon County, Wyoming

This study was conducted to obtain baseline data on use of the proposed Simpson Ridge Wind Resource Area (SRWRA) in Carbon County, Wyoming by greater sage-grouse. The first two study years were designed to determine pre-construction seasonally selected habitats and population-level vital rates (productivity and survival). The presence of an existing wind energy facility in the project area, the PacifiCorp Seven Mile Hill (SMH) project, allowed us to obtain some information on initial sage-grouse response to wind turbines the first two years following construction. To our knowledge these are the first quantitative data on sage-grouse response to an existing wind energy development. This report presents results of the first two study years (April 1, 2009 through March 30, 2011). This study was selected for continued funding by the National Wind Coordinating Collaborative Sage-Grouse Collaborative (NWCC-SGC) and has been ongoing since March 30, 2011. Future reports summarizing results of this research will be distributed through the NWCC-SGC. To investigate population trends through time, we determined the distribution and numbers of males using leks throughout the study area, which included a 4-mile radius buffer around the SRWRA. Over the 2-year study, 116 female greater sage-grouse were captured by spotlighting and use of hoop nets on roosts surrounding leks during the breeding period. Radio marked birds were located anywhere from twice a week to once a month, depending on season. All radio-locations were classified to season. We developed predictor variables used to predict success of fitness parameters and relative probability of habitat selection within the SRWRA and SMH study areas. Anthropogenic features included paved highways, overhead transmission lines, wind turbines and turbine access roads. Environmental variables included vegetation and topography features. Home ranges were estimated using a kernel density estimator. We developed resource selection functions (RSF) to estimate probability of selection within the SRWRA and SMH. Fourteen active greater sage-grouse leks were documented during lek surveys Mean lek size decreased from 37 in 2008 to 22 in 2010. Four leks located 0.61, 1.3, 1.4 and 2.5 km from the nearest wind turbine remained active throughout the study, but the total number of males counted on these four leks decreased from 162 the first year prior to construction (2008), to 97 in 2010. Similar lek declines were noted in regional leks not associated with wind energy development throughout Carbon County. We obtained 2,659 sage-grouse locations from radio-equipped females, which were used to map use of each project area by season. The sage-grouse populations within both study areas are relatively non-migratory, as radio-marked sage-grouse used similar areas during all annual life cycles. Potential impacts to sage-grouse from wind energy infrastructure are not well understood. The data rom this study provide insight into the early interactions of wind energy infrastructure and sage-grouse. Nest success and brood-rearing success were not statistically different between areas with and without wind energy development in the short-term. Nest success also was not influenced by anthropogenic features such as turbines in the short-term. Additionally, female survival was similar among both study areas, suggesting wind energy infrastructure was not impacting female survival in the short-term; however, further analysis is needed to identify habitats with different levels of risk to better understand the impact of wind energy development on survival. Nest and brood-rearing habitat selection were not influenced by turbines in the short-term; however, summer habitat selection occurred within habitats closer to wind turbines. Major roads were avoided in both study areas and during most of the seasons. The impact of transmission lines varied among study areas, suggesting other landscape features may be influencing selection. The data provided in this report are preliminary and are not meant to provide a basis for forming any conclusions regarding potential impacts of wind energy development on sage-grouse. Although the data collected during the initial phases of this study indicate that greater sage-grouse may continue to use habitats near wind-energy facilities, research conducted on greater sage-grouse response to oil and gas development has found population declines may not occur until 2-10 years after development. Therefore, long-term data from several geographic areas within the range of the sage-grouse will likely be required to adequately assess impacts of wind-energy development on greater sage-grouse.

17 WIND ENERGY↗

Final Scientific Report: A Scalable Development Environment for Peta-Scale Computing

This document is the final scientific report of the project DE-SC000120 (A scalable Development Environment for Peta-Scale Computing). The objective of this project is the extension of the Parallel Tools Platform (PTP) for applying it to peta-scale systems. PTP is an integrated development environment for parallel applications. It comprises code analysis, performance tuning, parallel debugging and system monitoring. The contribution of the Juelich Supercomputing Centre (JSC) aims to provide a scalable solution for system monitoring of supercomputers. This includes the development of a new communication protocol for exchanging status data between the target remote system and the client running PTP. The communication has to work for high latency. PTP needs to be implemented robustly and should hide the complexity of the supercomputer's architecture in order to provide a transparent access to various remote systems via a uniform user interface. This simplifies the porting of applications to different systems, because PTP functions as abstraction layer between parallel application developer and compute resources. The common requirement for all PTP components is that they have to interact with the remote supercomputer. E.g. applications are built remotely and performance tools are attached to job submissions and their output data resides on the remote system. Status data has to be collected by evaluating outputs of the remote job scheduler and the parallel debugger needs to control an application executed on the supercomputer. The challenge is to provide this functionality for peta-scale systems in real-time. The client server architecture of the established monitoring application LLview, developed by the JSC, can be applied to PTP's system monitoring. LLview provides a well-arranged overview of the supercomputer's current status. A set of statistics, a list of running and queued jobs as well as a node display mapping running jobs to their compute resources form the user display of LLview. These monitoring features have to be integrated into the development environment. Besides showing the current status PTP's monitoring also needs to allow for submitting and canceling user jobs. Monitoring peta-scale systems especially deals with presenting the large amount of status data in a useful manner. Users require to select arbitrary levels of detail. The monitoring views have to provide a quick overview of the system state, but also need to allow for zooming into specific parts of the system, into which the user is interested in. At present, the major batch systems running on supercomputers are PBS, TORQUE, ALPS and LoadLeveler, which have to be supported by both the monitoring and the job controlling component. Finally, PTP needs to be designed as generic as possible, so that it can be extended for future batch systems.

97 MATHEMATICS AND COMPUTING↗

Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data: Preprint

This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox low battery as a function of the active power output and the battery state of charge.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Normal mode analysis of macromolecular systems with the mobile block Hessian method

Until recently, normal mode analysis (NMA) was limited to small proteins, not only because the required energy minimization is a computationally exhausting task, but also because NMA requires the expensive diagonalization of a 3N{sub a}×3N{sub a} matrix with N{sub a} the number of atoms. A series of simplified models has been proposed, in particular the Rotation-Translation Blocks (RTB) method by Tama et al. for the simulation of proteins. It makes use of the concept that a peptide chain or protein can be seen as a subsequent set of rigid components, i.e. the peptide units. A peptide chain is thus divided into rigid blocks with six degrees of freedom each. Recently we developed the Mobile Block Hessian (MBH) method, which in a sense has similar features as the RTB method. The main difference is that MBH was developed to deal with partially optimized systems. The position/orientation of each block is optimized while the internal geometry is kept fixed at a plausible - but not necessarily optimized - geometry. This reduces the computational cost of the energy minimization. Applying the standard NMA on a partially optimized structure however results in spurious imaginary frequencies and unwanted coordinate dependence. The MBH avoids these unphysical effects by taking into account energy gradient corrections. Moreover the number of variables is reduced, which facilitates the diagonalization of the Hessian. In the original implementation of MBH, atoms could only be part of one rigid block. The MBH is now extended to the case where atoms can be part of two or more blocks. Two basic linkages can be realized: (1) blocks connected by one link atom, or (2) by two link atoms, where the latter is referred to as the hinge type connection. In this work we present the MBH concept and illustrate its performance with the crambin protein as an example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SNNVis: Visualizing Graph Embedding of Evolutionary Optimization for Spiking Neural Networks

While Spiking Neural Networks (SNNs) show a lot of promise, it is difficult to optimize them because applying traditional gradient-based optimization techniques is difficult. Even though evolutionary algorithms (EAs) have been shown to promise to optimize SNNs, understanding the relationship between evolving the characteristics of SNNs and their performance to improve the optimization algorithm is challenging because of the complex characteristics and huge population size. We propose visual analytics with novel graph embedding for evolutionary SNNs to address the challenges. While existing graph embedding techniques have limitations in preserving the specific features of the nodes and edges, our approach maintains them. Also, we develop visual analytics for understanding the relationship between the network performance and the features of nodes and edges and exploring and analyzing the evolving SNNs to build insights into improving the EA.

Chae, Junghoon [ORNL] (ORCID:0000000206016746)↗

SU-C-BRC-03: Development of a Novel Strategy for On-Demand Monte Carlo and Deterministic Dose Calculation Treatment Planning and Optimization for External Beam Photon and Particle Therapy

Purpose: Accurate and fast dose calculation is a prerequisite of precision radiation therapy in modern photon and particle therapy. While Monte Carlo (MC) dose calculation provides high dosimetric accuracy, the drastically increased computational time hinders its routine use. Deterministic dose calculation methods are fast, but problematic in the presence of tissue density inhomogeneity. We leverage the useful features of deterministic methods and MC to develop a hybrid dose calculation platform with autonomous utilization of MC and deterministic calculation depending on the local geometry, for optimal accuracy and speed. Methods: Our platform utilizes a Geant4 based “localized Monte Carlo” (LMC) method that isolates MC dose calculations only to volumes that have potential for dosimetric inaccuracy. In our approach, additional structures are created encompassing heterogeneous volumes. Deterministic methods calculate dose and energy fluence up to the volume surfaces, where the energy fluence distribution is sampled into discrete histories and transported using MC. Histories exiting the volume are converted back into energy fluence, and transported deterministically. By matching boundary conditions at both interfaces, deterministic dose calculation account for dose perturbations “downstream” of localized heterogeneities. Hybrid dose calculation was performed for water and anthropomorphic phantoms. Results: We achieved <1% agreement between deterministic and MC calculations in the water benchmark for photon and proton beams, and dose differences of 2%–15% could be observed in heterogeneous phantoms. The saving in computational time (a factor ∼4–7 compared to a full Monte Carlo dose calculation) was found to be approximately proportional to the volume of the heterogeneous region. Conclusion: Our hybrid dose calculation approach takes advantage of the computational efficiency of deterministic method and accuracy of MC, providing a practical tool for high performance dose calculation in modern RT. The approach is generalizable to all modalities where heterogeneities play a large role, notably particle therapy.

60 APPLIED LIFE SCIENCES↗

Developments in the design, analysis, and fabrication of advanced technology transmission elements

Over the last decade, the presently reported proprietary development program for the reduction of helicopter drive system weight and cost and the enhancement of reliability and survivability has produced high speed roller bearings, resin-matrix composite rotor shafts and transmission housings, gear/bearing/shaft system integrations, photoelastic investigation methods for gear tooth strength, and the automatic generation of complex FEM models for gear/shaft systems. After describing the design features and performance capabilities of the hardware developed, attention is given to the prospective benefits to be derived from application of these technologies, with emphasis on the relationship between helicopter drive system performance and cost.

Drago, R. J.↗

The national carbon capture center at the power systems development facility

The Power Systems Development Facility (PSDF) is a state-of-the-art test center sponsored by the U.S. Department of Energy and dedicated to the advancement of clean coal technology. In addition to the development of advanced coal gasification processes, the PSDF features the National Carbon Capture Center (NCCC) to study CO2 capture from coal-derived syngas and flue gas. The NCCC includes multiple, adaptable test skids that allow technology development of CO2 capture concepts using coal-derived syngas and flue gas in industrial settings. Because of the ability to operate under a wide range of flow rates and process conditions, research at the NCCC can effectively evaluate technologies at various levels of maturity. During the Budget Period Three reporting period, efforts at the NCCC/PSDF focused on testing of pre-combustion CO2 capture and related processes; commissioning and initial testing at the post-combustion CO2 capture facilities; and operating the gasification process to develop gasification related technologies and for syngas generation to test syngas conditioning technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗