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At least 775 records · Page 43

Theoretical assessments of CO 2 activation and hydrogenation pathways on transition-metal surfaces

Carbon dioxide (CO 2 ) hydrogenation on transition-metal active sites offers a promising carbon utilization route toward mitigating greenhouse gas emissions. C 1 products are often formed in parallel during CO 2 hydrogenation, prompting investigations into the intrinsic properties of transition metals that drive activity and product selectivity. Here, in this work, close-packed surfaces of a selection of transition-metal catalysts (Ni, Co, Rh, Ru, Pd, and Pt) were studied with density functional theory (DFT) calculations to understand their fundamental reactivities for CO 2 transformation reactions. Results indicate that CO 2 conversion proceeds through CO* formation and hydrogenation to form C 1 products (* denotes an adsorbed species). Ni, Co, Rh, and Ru favor CO/CH 4 formation, while Pd and Pt favor CO/CH 3 OH formation. The ability of a metal to dissociate C-O bonds drives selectivity between CH 4 and CH 3 OH, while competition between CO* desorption and surface hydrogenation describes CO selectivities. The C-O bond dissociation steps often impose the highest barrier along CH 4 formation reaction profiles, suggesting their kinetic relevance for CH 4 formation rates. The provided DFT-derived data sets detail a comprehensive reaction network of elementary steps relevant to C 1 chemistries, ultimately offering a benchmark for insights into design strategies for materials that exploit transition-metal active sites in carbon capture or utilization processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Practical Framework for Simulating Time-Resolved Spectroscopy Based on a Real-Time Dyson Expansion

Time-resolved spectroscopy is a powerful tool for probing electron dynamics in molecules and solids, revealing transient phenomena on subfemtosecond time scales. The interpretation of experimental results is often enhanced by parallel numerical studies, which can provide insight and validation for experimental hypotheses. However, developing a theoretical framework for simulating time-resolved spectra remains a significant challenge. The most suitable approach involves the many-body nonequilibrium Green's function formalism, which accounts for crucial dynamical many-body correlations during time evolution. While these dynamical correlations are essential for observing emergent behavior in time-resolved spectra, they also render the formalism prohibitively expensive for large-scale simulations. Substantial effort has been devoted to reducing this computational cost─through approximations and numerical techniques─while preserving the key dynamical correlations. The ultimate goal is to enable first-principles simulations of time-dependent systems ranging from small molecules to large, periodic, multidimensional solids. Here, in this perspective, we outline key challenges in developing practical simulations for time-resolved spectroscopy, with a particular focus on Green's function methodologies. We highlight a recent advancement toward a scalable framework: the real-time Dyson expansion (RT-DE) [Phys. Rev. Lett. 2024, 133, 226902]. We introduce the theoretical foundation of RT-DE and discuss strategies for improving scalability, which have already enabled simulations of system sizes beyond the reach of previous fully dynamical approaches. We conclude with an outlook on future directions for extending RT-DE to first-principles studies of dynamically correlated, nonequilibrium systems.

Reeves, Cian C. [Univ. of California, Santa Barbar↗

Radiative Heat Transfer Calculation on 16384 GPUs Using a Reverse Monte Carlo Ray Tracing Approach with Adaptive Mesh Refinement

Modeling thermal radiation is computationally challenging in parallel due to its all-to-all physical and resulting computational connectivity, and is also the dominant mode of heat transfer in practical applications such as next-generation clean coal boilers, being modeled by the Uintah framework. However, a direct all-to-all treatment of radiation is prohibitively expensive on large computers systems whether homogeneous or heterogeneous. DOE Titan and the planned DOE Summit and Sierra machines are examples of current and emerging GPU-based heterogeneous systems where the increased processing capability of GPUs over CPUs exacerbates this problem. These systems require that computational frameworks like Uintah leverage an arbitrary number of on-node GPUs, while simultaneously utilizing thousands of GPUs within a single simulation. We show that radiative heat transfer problems can be made to scale within Uintah on heterogeneous systems through a combination of reverse Monte Carlo ray tracing (RMCRT) techniques combined with AMR, to reduce the amount of global communication. In particular, significant Uintah infrastructure changes, including a novel lock and contention-free, thread-scalable data structure for managing MPI communication requests and improved memory allocation strategies were necessary to achieve excellent strong scaling results to 16384 GPUs on Titan.

Computer Science↗

Quantitative spatiotemporal mapping of thermal runaway propagation rates in lithium-ion cells using cross-correlated Gabor filtering

Abuse testing of lithium-ion batteries is widely performed in order to develop new safety standards and strategies. However, testing methodologies are not standardised across the research community, especially with failure mechanisms being inherently difficult to reproduce. High-speed X-ray radiography is proven to be a valuable tool to capture events occurring during cell failure, but the observations made remain largely qualitative. We have therefore developed a robust image processing toolbox that can quantify, for the first time, the rate of propagation of battery failure mechanisms revealed by high-speed X-ray radiography. Using Gabor filter, the toolbox selectively tracks the electrode structure at the onset of failure. This facilitated the estimation of the displacement of electrodes undergoing abuse via nail penetration, and also the tracking of objects, such as the nail, as it propagates through a cell. Further, by cross-correlating the Gabor signals, we have produced practical, illustrative spatiotemporal maps of the failure events. From these, we can quantify the propagation rates of electrode displacement prior to the onset of thermal runaway. The highest recorded acceleration (≈514 mm s -2 ) was when a nail penetrated a cell radially (perpendicular to the electrodes) as opposed to axially (parallel to the electrodes). The initiation of thermal runaway was also resolved in combination with electrode displacement, which occurred at a lower acceleration (≈108 mm s -2 ). Our assistive toolbox can also be used to study other types of failure mechanisms, extracting otherwise unattainable kinetic data. Ultimately, this tool can be used to not only validate existing theoretical mechanical models, but also standardise battery failure testing procedures.

25 ENERGY STORAGE↗

LiNbO{sub 3}: A photovoltaic substrate for massive parallel manipulation and patterning of nano-objects

The application of evanescent photovoltaic (PV) fields, generated by visible illumination of Fe:LiNbO{sub 3} substrates, for parallel massive trapping and manipulation of micro- and nano-objects is critically reviewed. The technique has been often referred to as photovoltaic or photorefractive tweezers. The main advantage of the new method is that the involved electrophoretic and/or dielectrophoretic forces do not require any electrodes and large scale manipulation of nano-objects can be easily achieved using the patterning capabilities of light. The paper describes the experimental techniques for particle trapping and the main reported experimental results obtained with a variety of micro- and nano-particles (dielectric and conductive) and different illumination configurations (single beam, holographic geometry, and spatial light modulator projection). The report also pays attention to the physical basis of the method, namely, the coupling of the evanescent photorefractive fields to the dielectric response of the nano-particles. The role of a number of physical parameters such as the contrast and spatial periodicities of the illumination pattern or the particle deposition method is discussed. Moreover, the main properties of the obtained particle patterns in relation to potential applications are summarized, and first demonstrations reviewed. Finally, the PV method is discussed in comparison to other patterning strategies, such as those based on the pyroelectric response and the electric fields associated to domain poling of ferroelectric materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An mRNA vaccine encoding the Ebola virus glycoprotein induces high neutralizing antibody titers and provides strong protection against lethal infections in mouse models

Ebola virus (EBOV) is the causative agent of Ebola disease (EBOD), a viral hemorrhagic fever with a notably high case fatality rate. Current treatments for EBOD are limited to monoclonal antibodies or two licensed viral vector vaccines, a recombinant vesicular stomatitis virus (rVSV)-vectored vaccine or an adenovirus and modified vaccinia Ankara regimen. However, comparisons of protection, efficacy, and durability with alternative nucleotide platforms remain understudied. Here, we evaluated the immunogenicity of an mRNA vaccine expressing the EBOV glycoprotein (GP) in parallel with rVSV- and DNA-based vaccine platforms. The mRNA EBOV-GP vaccine, formulated in lipid nanoparticles, elicited significantly higher levels of total IgG and neutralizing antibody titers compared to the rVSV-EBOV-GP vaccine. Linear antibody epitope analysis indicated a preference for targeting the mucin-like domain in EBOV-GP1 following rVSV-based vaccination, while the mRNA platform distinctly targeted the internal fusion loop of EBOV-GP2. After characterizing the immunogenicity of the mRNA vaccine, two models of EBOD were used to demonstrate its protective efficacy: a surrogate rVSV-based challenge model of EBOD using type-I interferon deficient C57BL/6 mice and infection of BALB/c mice with authentic mouse-adapted EBOV. In both studies, the EBOV mRNA vaccine fully protected the mouse cohorts against morbidity and mortality. Additionally, the EBOV mRNA vaccine produced greater neutralizing antibody titers compared to the DNA EBOV-GP vaccine. These results suggest that an mRNA vaccine expressing EBOV-GP can induce robust, functional humoral responses that are protective against EBOD, warranting further development as an alternative to, or as part of a vaccine strategy including, viral vectored vaccines.

DNA vaccines↗

Site-specific regulation of oral mucosa-recruiting CD8{sup +} T cells in a mouse contact allergy model

Contact allergy is a T cell-mediated, delayed-type hypersensitivity generated by contact exposure of an allergen to the skin and mucosal surface. The clinical manifestations of allergic responses between the skin and oral mucosa vary and the differences in immunopathology have not been clarified. We generated hapten-induced contact hypersensitivity (CH) of the buccal mucosa (BM) in parallel studies with ear skin (ES) CH, and observed several characteristic findings of BM CH. The BM challenge induced more rapid and more severe inflammation than the ES challenge, with abundant granulocyte and CD8{sup +} T cell infiltration. However, these inflammatory responses diminished quickly. Recruiting CD8{sup +} T cells in the BM had higher ratios of CD62L{sup −}CD44{sup low-hi} memory-type cells, and showed impaired IFN-γ, greater PD-1, and comparable Ki-67 expression, suggesting that the recruiting-proliferating CD8{sup +} T cells were unable to differentiate into effector T cells and converted into exhausted T cells at the local site. This finding may explain the rapid recovery of the BM from severe inflammation. Preferentially greater expression of PD-1 ligand (B7-H1), was observed in the BM epithelium under the peak inflammation, and the absence of B7-H1 further accelerated CH responses, suggesting the occurrence of PD-1:B7-H1-mediated immune regulation at the local site. Our results may facilitate the understanding of the unique features of contact allergies in the oral mucosa, and guide the development of new strategies for control of contact allergy. - Highlights: • Contact allergy in the oral mucosa shows severe responses, but quick recovery. • Oral mucosa-infiltrating CD8{sup +} T cells have unique activatory and regulatory status. • PD-1:B7-H1-mediated pathway is involved in the site-specific regulation.

60 APPLIED LIFE SCIENCES↗

Planning for Pre-Exascale Platform Environment (Fiscal Year 2015 Level 2 Milestone 5216)

This Plan for ASC Pre-Exascale Platform Environments document constitutes the deliverable for the fiscal year 2015 (FY15) Advanced Simulation and Computing (ASC) Program Level 2 milestone Planning for Pre-Exascale Platform Environment. It acknowledges and quantifies challenges and recognized gaps for moving the ASC Program towards effective use of exascale platforms and recommends strategies to address these gaps. This document also presents an update to the concerns, strategies, and plans presented in the FY08 predecessor document that dealt with the upcoming (at the time) petascale high performance computing (HPC) platforms. With the looming push towards exascale systems, a review of the earlier document was appropriate in light of the myriad architectural choices currently under consideration. The ASC Program believes the platforms to be fielded in the 2020s will be fundamentally different systems that stress ASC’s ability to modify codes to take full advantage of new or unique features. In addition, the scale of components will increase the difficulty of maintaining an errorfree system, thus driving new approaches to resilience and error detection/correction. The code revamps of the past, from serial- to vector-centric code to distributed memory to threaded implementations, will be revisited as codes adapt to a new message passing interface (MPI) plus “x” or more advanced and dynamic programming models based on architectural specifics. Development efforts are already underway in some cases, and more difficult or uncertain aspects of the new architectures will require research and analysis that may inform future directions for program choices. In addition, the potential diversity of system architectures may require parallel if not duplicative efforts to analyze and modify environments, codes, subsystems, libraries, debugging tools, and performance analysis techniques as well as exploring new monitoring methodologies. It is difficult if not impossible to selectively eliminate some of these activities until more information is available through simulations of potential architectures, analysis of systems designs, and informed study of commodity technologies that will be the constituent parts of future platforms.

97 MATHEMATICS AND COMPUTING↗

Efficient data IO for a Parallel Global Cloud Resolving Model

Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2-4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk without creating a serious bottleneck in the execution of the GCRM code while also supporting efficient post-execution data analysis is a significant challenge. This paper discusses an Input/Output (IO) application programmer interface (API) for the GCRM that efficiently moves data from the model to disk while maintaining support for community standard formats, avoiding the creation of very large numbers of files, and supporting efficient analysis. Several aspects of the API will be discussed in detail. First, we discuss the output data layout which linearizes the data in a consistent way that is independent of the number of processors used to run the simulation and provides a convenient format for subsequent analyses of the data. Second, we discuss the flexible API interface that enables modelers to easily add variables to the output stream by specifying where in the GCRM code these variables are located and to flexibly configure the choice of outputs and distribution of data across files. The flexibility of the API is designed to allow model developers to add new data fields to the output as the model develops and new physics is added and also provides a mechanism for allowing users of the GCRM code itself to adjust the output frequency and the number of fields written depending on the needs of individual calculations. Third, we describe the mapping to the NetCDF data model with an emphasis on the grid description. Fourth, we describe our messaging algorithms and IO aggregation strategies that are used to achieve high bandwidth while simultaneously writing concurrently from many processors to shared files. We conclude with initial performance results.

99 GENERAL AND MISCELLANEOUS↗

Influence of polarization and a source model for dose calculation in MRT

Purpose: Microbeam Radiation Therapy (MRT), an alternative preclinical treatment strategy using spatially modulated synchrotron radiation on a micrometer scale, has the great potential to cure malignant tumors (e.g., brain tumors) while having low side effects on normal tissue. Dose measurement and calculation in MRT is challenging because of the spatial accuracy required and the arising high dose differences. Dose calculation with Monte Carlo simulations is time consuming and their accuracy is still a matter of debate. In particular, the influence of photon polarization has been discussed in the literature. Moreover, it is controversial whether a complete knowledge of phase space trajectories, i.e., the simulation of the machine from the wiggler to the collimator, is necessary in order to accurately calculate the dose. Methods: With Monte Carlo simulations in the Geant4 toolkit, the authors investigate the influence of polarization on the dose distribution and the therapeutically important peak to valley dose ratios (PVDRs). Furthermore, the authors analyze in detail phase space information provided byMartínez-Rovira et al. [“Development and commissioning of a Monte Carlo photon model for the forthcoming clinical trials in microbeam radiation therapy,” Med. Phys. 39(1), 119–131 (2012)] and examine its influence on peak and valley doses. A simple source model is developed using parallel beams and its applicability is shown in a semiadjoint Monte Carlo simulation. Results are compared to measurements and previously published data. Results: Polarization has a significant influence on the scattered dose outside the microbeam field. In the radiation field, however, dose and PVDRs deduced from calculations without polarization and with polarization differ by less than 3%. The authors show that the key consequences from the phase space information for dose calculations are inhomogeneous primary photon flux, partial absorption due to inclined beam incidence outside the field center, increased beam width and center to center distance due to the beam propagation from the collimator to the phantom surface and imperfect absorption in the absorber material of the Multislit Collimator. These corrections have an effect of approximately 10% on the valley dose and suffice to describe doses in MRT within the measurement uncertainties of currently available dosimetry techniques. Conclusions: The source for the first clinical pet trials in MRT is characterized with respect to its phase space and the photon polarization. The results suggest the use of a presented simplified phase space model in dose calculations and hence pave the way for alternative and fast dose calculation algorithms. They also show that the polarization is of minor importance for the clinical important peak and valley doses inside the microbeam field.

61 RADIATION PROTECTION AND DOSIMETRY↗

Mixed Integer Nonlinear Programming Approaches to Enhance Resiliency and Response Strategies in Critical Infrastructure

Motivation. Critical infrastructures are large, complex engineered systems that must be operated robustly under abnormal conditions resulting from natural hazards or intentional acts. For example, electric power systems must be robust to line faults, water utilities must rapidly mitigate contamination incidents, and computing networks must adapt to adversarial intrusions to protect critical information. Problem. It is difficult for decision-makers within resiliency analysis in critical infrastructure to optimize designs and develop effective response strategies that can account for uncertainties. Facing incomplete information and the sheer scope that a natural hazard or attack vector may incorporate, response can be ineffective without reliable, scalable decision support tools. These problems are intrinsically nonlinear and involve discrete decisions, and unfortunately, existing off-the-shelf mathematical programming methods cannot support optimization-based decision-making of these nonlinear at scale. Method/Approach and Results. This project emphasized development of fundamental optimization strategies that supported real- time mitigation and response for critical infrastructures. In particular, the project developed multi- tree approaches based on piecewise outer-approximations for solution of mixed-integer nonlinear programming (MINLP) problems. These techniques alternate between an MILP or MISOCP relaxation to obtain a lower bound and candidate discrete solutions and an NLP subproblem to obtain upper bounds. Using tailored relaxations based on problem structure, these methods were used to solve several key applications in resilience and response of critical infrastructure. This work resulted in two open-source, copyrighted software packages: CORAMIN (https://github.com/Coramin/Coramin) -- an object-oriented mathematical programming framework that supports tailored multi-tree algorithms for solution of large- scale mixed-integer nonlinear programming; and EGRET (Electrical Grid Research and Engineering Toolkit) (https://github.com/grid- parity-exchange/Egret) -- a declarative mathematical programming framework built upon CORAMIN and Pyomo for formulation and solution of resilience and operations problems in power grid systems. Furthermore, these tools resulted in several important published results, including the following: The first known global optimization approach that could solve the unit-commitment problem with nonlinear power flow constraints on medium-sized test problems; Improved parallel optimization-based bounds tightening and strengthening of relaxations of AC power flow constraints; and, Optimization-based approaches for improved grid resilience and use of demand response to improve grid resilience with reduction in capital requirements. Result Implications. This project developed first-of-a-kind algorithms for decision-making in critical infrastructure resilience operations and planning, as well as a next-generation toolkit for MINLP researchers. These approaches leveraged high-performance computing architectures to solve some of the largest, most challenging nonlinear discrete optimization problems to global optimality, and these successes were captured in open-source software to enable optimization-based decision-making, and efficient solution of MINLP formulations for electric power transmission grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗

CO₂ Capture Membrane Process for Power Plant Flue Gas

Because the fleet of coal-fired power plants is of such importance to the nation's energy production while also being the single largest emitter of CO₂, the development of retrofit, post-combustion CO₂ capture technologies for existing and new, upcoming coal power plants will allow coal to remain a major component of the U.S. energy mix while mitigating global warming. Post-combustion carbon capture technologies are an attractive option for coal-fired power plants as they do not require modification of major power-plant infrastructures, such as fuel processing, boiler, and steam-turbine subsystems. In this project, the overall objective was to develop an advanced, hollow-fiber, polymeric membrane process that could be cost-effectively retrofitted into current pulverized coal-fired power plants to capture at least 90% of the CO₂ from plant flue gas with 95% captured CO₂ purity. The approach for this project tackled the technology development on three different fronts in parallel: membrane materials R&D, hollow-fiber membrane module development, and process development and engineering. The project team consisted of RTI (prime) and two industrial partners, Arkema, Inc. and Generon IGS, Inc. Two CO₂-selective membrane polymer platforms were targeted for development in this project. For the near term, a next-generation, high-flux polycarbonate membrane platform was spun into hollow-fiber membranes that were fabricated into both lab-scale and larger prototype (~2,200 ft²) membrane modules. For the long term, a new fluoropolymer membrane platform based on poly(vinylidene fluoride) [PVDF] chemistry was developed using a copolymer approach as improved capture membrane materials with superior chemical resistance to flue-gas contaminants (moisture, SO₂, NO x , etc.). Specific objectives were: - Development of new, highly chemically resistant, fluorinated polymers as membrane materials with minimum selectivity of 30 for CO₂ over N₂ and CO₂ permeance greater than 300 gas permeation units (GPU) targeted; - Development of next-generation polycarbonate hollow-fiber membranes and membrane modules with higher CO₂ permeance than current commercial polycarbonate membranes; - Development and fabrication of membrane hollow fibers and modules from candidate polymers; - Development of a CO₂ capture membrane process design and integration strategy suitable for end-of-pipe, retrofit installation; and - Techno-economic evaluation of the "best" integrated CO₂ capture membrane process design package In this report, the results of the project research and development efforts are discussed and include the post-combustion capture properties of the two membrane material platforms and the hollow-fiber membrane modules developed from them and the multi-stage process design and analysis developed for 90% CO₂ capture with 95% captured CO₂ purity.

20 FOSSIL-FUELED POWER PLANTS↗

ELSI: A unified software interface for Kohn–Sham electronic structure solvers

Solving the electronic structure from a generalized or standard eigenproblem is often the bottleneck in large scale calculations based on Kohn-Sham density-functional theory. This problem must be addressed by essentially all current electronic structure codes, based on similar matrix expressions, and by high-performance computation. We here present a unified software interface, ELSI, to access different strategies that address the Kohn-Sham eigenvalue problem. Currently supported algorithms include the dense generalized eigensolver library ELPA, the orbital minimization method implemented in libOMM, and the pole expansion and selected inversion (PEXSI) approach with lower computational complexity for semilocal density functionals. The ELSI interface aims to simplify the implementation and optimal use of the different strategies, by offering (a) a unified software framework designed for the electronic structure solvers in Kohn-Sham density-functional theory; (b) reasonable default parameters for a chosen solver; (c) automatic conversion between input and internal working matrix formats, and in the future (d) recommendation of the optimal solver depending on the specific problem. As a result, comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800 basis functions) on distributed memory supercomputing architectures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement

The standard LU factorization-based solution process for linear systems can be enhanced in speed or accuracy by employing mixed-precision iterative refinement. Most recent work has focused on dense systems. We investigate the potential of mixed-precision iterative refinement to enhance methods for sparse systems based on approximate sparse factorizations. In doing so, we first develop a new error analysis for LU- and GMRES-based iterative refinement under a general model of LU factorization that accounts for the approximation methods typically used by modern sparse solvers, such as low-rank approximations or relaxed pivoting strategies. We then provide a detailed performance analysis of both the execution time and memory consumption of different algorithms, based on a selected set of iterative refinement variants and approximate sparse factorizations. Our performance study uses the multifrontal solver MUMPS, which can exploit block low-rank factorization and static pivoting. We evaluate the performance of the algorithms on large, sparse problems coming from a variety of real-life and industrial applications showing that mixed-precision iterative refinement combined with approximate sparse factorization can lead to considerable reductions of both the time and memory consumption.

97 MATHEMATICS AND COMPUTING↗

Managing Low-Level Waste at Dounreay - 16269

Dounreay Site Restoration Limited (DSRL) is the site licence company responsible for the clean-up and demolition of Britain's former centre of fast reactor research and development. The Dounreay site requires facilities to dispose of up to 175,000 cubic metres of low level waste (LLW) that has been and will continue to be generated during the decommissioning and restoration of the site. In May 2014, construction of two new vaults for the disposal of LLW at Dounreay was completed, including the necessary roads, infrastructures and services, followed by an encapsulation plant in September 2014. The vaults are located immediately to the northeast of the Dounreay licensed site, on NDA-owned land. The facilities are for disposal of the solid LLW generated at Dounreay and the adjacent Vulcan site only. In 2004, following consultation with stakeholders and members of the public, Dounreay issued the 'Best Practicable Environmental Option (BPEO) Report' on the management of Dounreay LLW. This report assessed potential management options for LLW against a range of criteria, including technical, environmental, cost, health and safety issues. The study was conducted in line with best practice and involved consultation with a range of people, including the local community and organisations with an interest in radioactive waste management. The recommendations and conclusions from the study provided the basis for the 'Dounreay Solid LLW Overall Strategy', which was published in March 2005. A fundamental component of this strategy was the development of new below-ground disposal vaults for LLW at Dounreay. Siting the vaults on land at Dounreay avoids any need to transport the LLW away from Dounreay on public roads. Disposal at Dounreay therefore satisfies the proximity principle of managing the waste at source. Disposal at Dounreay is also consistent with UK Government Policy on LLW management, the Scottish Government's Radioactive Waste Management Policy and the Nuclear Decommissioning Authority's (NDA's) strategy on management of LLW from the UK nuclear industry. A planning application was initially lodged with the Highland Council in June 2006. The period for the determination of this application was extended to allow the Scottish Environment Protection Agency (SEPA) sufficient time to assess fully the supporting Environmental Safety Case (ESC). The planning application was re-activated in May 2008, and planning permission was granted by Highland Council in April 2009. The planning permission included 26 conditions on DSRL, covering a wide range of environmental issues such as construction noise/dust, traffic, visual impact and also a condition to develop a community fund aimed at socio-economic development of the area around the Dounreay site. After undertaking the necessary detailed design work, construction of the phase one vaults commenced in November 2011 by principal contractor, Graham Construction. Work was undertaken on both vaults simultaneously, excavating around 243,000 m{sup 3} of rock. When excavation was complete, steel reinforcement was placed and concrete poured to construct the floor slabs. This was followed by the construction of the reinforced walls and then the installation of the steel support structure and materials that form the roof. Mechanical and electrical installation then followed, in parallel with the construction of the vault apron, ramps and access roads. A pumping system and control building was also constructed to remove groundwater from around the vaults to allow the vaults to be kept dry while they are being filled with waste. A layer of excavated material, approximately 3 m thick, was placed across the existing ground surface between the vaults and the coast, to ensure the water table lies well below the new ground surface after closure of the vaults, and that any future trace contaminated groundwater flows out to the sea rather than to the soil zone. This layer is referred to in project documents as the 'enhanced geosphere'. After disposals are completed and the vaults are closed, this layer will be joined to the capping over the vaults so that the ensemble merges visually with the surrounding landscape. The original vegetation and soil mix will be returned as far as is practicable. An encapsulation plant has been constructed to fill the LLW containers with grout prior to disposal in the vault, similar to the process used at the national Low-Level Waste Repository facility (LLWR), near Drigg in Cumbria. The plant has the capacity to grout up to four containers per day. The grout fills voids in the container and helps provide chemical conditions in the vault that limit the release of radionuclides in the far future, after the vault has been penetrated by groundwater. On April 24 2015, active commissioning began at the Encapsulation Plant and LLW Vaults. Half-height ISO containers packed with low level waste are currently being filled with grout and disposed of in the LLW Vault. Also packaged Demolition Low Level Waste (DLLW) is being processed and disposed of in the Demolition Low Level Waste Vault. To date over 2500 packages of DLLW and 70 containers LLW have been disposed of. Completion of construction and the start of operating the Phase One vaults and encapsulation plant are fundamental to the successful and efficient decommissioning of the Dounreay site, upon which many millions of pounds of investment and hundreds of jobs rely.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗