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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Leukemia, lymphoma and multiple myeloma mortality (1950–1999) and incidence (1969–1999) in the Eldorado uranium workers cohort

Uranium workers are chronically exposed to low levels of radon decay products (RDP) and gamma (γ) radiation. Risks of leukemia from acute and high doses of γ-radiation are well-characterized, but risks from lower doses and dose-rates and from RDP exposures are controversial. Few studies have evaluated risks of other hematologic cancers in uranium workers. The purpose of this study was to analyze radiation-related risks of hematologic cancers in the cohort of Eldorado uranium miners and processors first employed in 1932–1980 in relation to cumulative RDP exposures and γ-ray doses. The average cumulative RDP exposure was 100.2 working level months and the average cumulative whole-body γ-radiation dose was 52.2 millisievert. We identified 101 deaths and 160 cases of hematologic cancers in the cohort. Overall, male workers had lower mortality and cancer incidence rates for all outcomes compared with the general Canadian male population, a likely healthy worker effect. No statistically significant association between RDP exposure or γ-ray doses, or a combination of both, and mortality or incidence of any hematologic cancer was found. We observed consistent but non-statistically significant increases in risks of chronic lymphocytic leukemia (CLL) and Hodgkin lymphoma (HL) incidence and non-Hodgkin lymphoma (NHL) mortality with increasing γ-ray doses. These findings are consistent with recent studies of increased risks of CLL and NHL incidence after γ-radiation exposure. Further research is necessary to understand risks of other hematologic cancers from low-dose exposures to γ-radiation. - Highlights: • We analyzed long-term follow-up for hematologic cancers of the Eldorado uranium workers. • Workers were exposed to a unique combination of radon decay products (RDP) and gamma (γ) ray doses. • Exposures to RDP and γ-ray doses were not associated with significantly increased risks of cancers. • Radiation risks of chronic lymphocytic leukemia (CLL) and Hodgkin lymphoma were increased. • Study findings provide additional support for radiation-related risks of CLL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Insights from an international stakeholder consultation to identify informational needs related to seafood safety

Food safety assessment and communication have a strong importance in reducing human health risks related to food consumption. The research carried out within the ECsafeSEAFOOD project aims to assess seafood safety issues, mainly related to non-regulated priority environmental contaminants, and to evaluate their impact on public health. In order to make the research results accessible and exploitable, and to respond to actual stakeholders' demands, a consultation with international stakeholders was performed by means of a survey. The focus was on policy and decision makers, food producers and processors, and agencies (i.e. EU and National or Regional agencies related to Food Safety or Public Health) and consumer organisations. The survey considered questions related to: seafood safety assessment and mitigation strategies, availability of data, such as the level of information on different contaminants, and communication among different stakeholder groups. Furthermore, stakeholders were asked to give their opinion on how they believe consumers perceive risks associated with environmental contaminants. The survey was distributed to 531 key stakeholders and 91 responses were received from stakeholders from 30 EU and non-EU countries. The main results show that communication between different groups of stakeholders needs to be improved and that there is a deficit of information and data in the field of seafood safety. This pertains mainly to the transfer of contaminants between the environment and seafood, and to the diversity of environmental contaminants such as plastic additives, algal toxins and hormones. On-line tools were perceived to be the most useful communication channel. - Highlights: • We consulted stakeholders to identify their needs about seafood safety. • An on-line survey was prepared and sent to gather stakeholders' opinions. • Communication among stakeholders needs to be improved. • There is a deficit of information and data in the field of seafood safety. • On-line tools are perceived to be the most useful communication channel.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Parallel Distributed Hydrology Soil Vegetation Model (DHSVM) using global arrays

The Distributed Hydrology Soil Vegetation Model (DHSVM) code was parallelized for distributed memory computers using Global Arrays (GA). To analyze parallel performance, DHSVM was used to simulate two significantly sized river basins located in northwest continental United States and southwest Canada at 90~m resolution: (1) Clearwater (25,000~km2) and (2) Columbia (668,000~km2). Meteorological forcing applied to both basins was dynamically down-scaled from a global circulation model using the Weather Research and Forecasting (WRF) model and read into DHSVM as 2D maps each time step. We report parallel code speed up was significant. Run times for 1-year simulations were reduced by an order of magnitude for both test basins. A maximum speed up of 105 was attained with 480 processors while simulating the Columbia basin. Speed up was limited by input dominated tasks, particularly the input of meteorological forcing data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Scaling To A Million Cores And Beyond: Using Light-Weight Simulation to Understand The Challenges Ahead On The Road To Exascale

As supercomputers scale to 1,000 PFlop/s over the next decade, investigating the performance of parallel applications at scale on future architectures and the performance impact of different architecture choices for high-performance computing (HPC) hardware/software co-design is crucial. This paper summarizes recent efforts in designing and implementing a novel HPC hardware/software co-design toolkit. The presented Extreme-scale Simulator (xSim) permits running an HPC application in a controlled environment with millions of concurrent execution threads while observing its performance in a simulated extreme-scale HPC system using architectural models and virtual timing. This paper demonstrates the capabilities and usefulness of the xSim performance investigation toolkit, such as its scalability to 2^27 simulated Message Passing Interface (MPI) ranks on 960 real processor cores, the capability to evaluate the performance of different MPI collective communication algorithms, and the ability to evaluate the performance of a basic Monte Carlo application with different architectural parameters.

Engelmann, Christian↗
DOE OSTI2024

Assessing and advancing the potential of quantum computing: A NASA case study

Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. In this paper, we describe NASA’s work in assessing and advancing the potential of quantum computing. We discuss advances in algorithms, both near- and longer-term, and the results of our explorations on current hardware as well as with simulations, including illustrating the benefits of algorithm-hardware co-design in the NISQ era. This work also includes physics-inspired classical algorithms that can be used at application scale today. We discuss innovative tools supporting the assessment and advancement of quantum computing and describe improved methods for simulating quantum systems of various types on high-performance computing systems that incorporate realistic error models. We provide an overview of recent methods for benchmarking, evaluating, and characterizing quantum hardware for error mitigation, as well as insights into fundamental quantum physics that can be harnessed for computational purposes.

Rieffel, Eleanor G.↗
DOE OSTI2019

Accelerating a fluvial incision and landscape evolution model with parallelism

Solving inverse problems, performing sensitivity analyses, and achieving statistical rigour in landscape evolution models require running many model realizations. Parallel computation is necessary to achieve this in a reasonable time. However, no previous landscape evolution algorithm is able to leverage modern parallelism. In this report, I describe an algorithm that can utilize the parallel potential of GPUs and many-core processors, in addition to working well in serial. The new algorithm runs 43× faster (70 s vs. 3000 s on a 10,000×10,000 input) than the previous state-of-the-art and exhibits sublinear scaling with input size. I also identify key techniques for multiple flow direction routing and quickly eliminating landscape depressions and local minima. Complete, well-commented, easily adaptable source code for all versions of the algorithm is available on Github and Zenodo.

58 GEOSCIENCES↗
DOE OSTI2015

Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments

Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Message Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.

dynamic simulation↗
DOE OSTI2023

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Lithium promotion of Pt/m-ZrO 2 catalysts for low temperature water-gas shift

Low temperature water-gas shift (LTS) is an important reaction occurring in a fuel processor for producing and purifying hydrogen. Platinum supported on m-ZrO 2 belongs to a family of catalysts consisting of metal nanoparticles and an active partially reducible oxide, with the catalysis proposed to occur at the boundary between metal particles and the support. In this investigation, increasing the loading of lithium dopant increased the LTS rate up to 0.54 wt % lithium, where conversion was 2.4 times that of the unpromoted catalyst at 260°C. Further increases in lithium loading up to 1.5 wt % decreased the rate, although it remained higher than that of the unpromoted catalyst. Infrared spectroscopy and CO 2 temperature programmed desorption experiments showed three effects with increasing lithium loading: (1) lithium promoter weakened the C–H bond of formate, the proposed rate limiting step of the interfacial surface formate mechanism; (2) high levels of lithium suppressed the platinum site capacity required for hydrogen transfer; and (3) high levels of lithium increased catalyst basicity. Aspects (2) and (3) tended to inhibit desorption of product CO 2 , an acidic molecule the removal of which is metal-catalyzed. XANES and XPS experiments revealed that electron transfer to enrich Pt nanoparticles is unlikely the root cause of C–H bond weakening in formate. However, other electronic effects (e.g., electrostatic effects or molecular rearrangement due to enhanced basicity) were not ruled out.

08 HYDROGEN↗
DOE OSTI2022

Residual elastic strain evolution due to thermal cycling of a ceramic-metal composite (WC-Cu) via high energy X-ray diffraction and analytical modeling

Residual stress, when superimposed with in-service loading, can significantly reduce the lifetime and performance of a component. Ceramic-metal composites are susceptible to residual stresses due to the thermal expansion mismatch of the ceramic and metallic phases. The WC-Cu composite explored in the present study provides a promising combination of thermal conductivity and strength properties, while exhibiting counterintuitive improvements in strength and ductility after thermal cycling. Further, this work quantifies the evolution of the residual elastic strains as a result of processing and cyclic thermal loading in a co-continuous WC-Cu composite through experimental high energy X-ray diffraction and kinetics-based modeling. Both analyses indicate that processing-induced residual tensile stress in the copper phase is relieved upon subsequent thermal cycling, with kinetics modeling revealing the cyclic-dependent nature of the active power-law creep mechanisms. The results indicate that, through stress relaxation, this material system maintains structural stability during thermal cycling. The illustrated kinetics of relaxation can inform general material processors and designers of ceramic-metal composites to minimize detrimental residual stress and improve performance of these material systems.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Clinically Applicable Monte Carlo–based Biological Dose Optimization for the Treatment of Head and Neck Cancers With Spot-Scanning Proton Therapy

Purpose: Our aim is to demonstrate the feasibility of fast Monte Carlo (MC)–based inverse biological planning for the treatment of head and neck tumors in spot-scanning proton therapy. Methods and Materials: Recently, a fast and accurate graphics processor unit (GPU)–based MC simulation of proton transport was developed and used as the dose-calculation engine in a GPU-accelerated intensity modulated proton therapy (IMPT) optimizer. Besides dose, the MC can simultaneously score the dose-averaged linear energy transfer (LET{sub d}), which makes biological dose (BD) optimization possible. To convert from LET{sub d} to BD, a simple linear relation was assumed. By use of this novel optimizer, inverse biological planning was applied to 4 patients, including 2 small and 1 large thyroid tumor targets, as well as 1 glioma case. To create these plans, constraints were placed to maintain the physical dose (PD) within 1.25 times the prescription while maximizing target BD. For comparison, conventional intensity modulated radiation therapy (IMRT) and IMPT plans were also created using Eclipse (Varian Medical Systems) in each case. The same critical-structure PD constraints were used for the IMRT, IMPT, and biologically optimized plans. The BD distributions for the IMPT plans were obtained through MC recalculations. Results: Compared with standard IMPT, the biologically optimal plans for patients with small tumor targets displayed a BD escalation that was around twice the PD increase. Dose sparing to critical structures was improved compared with both IMRT and IMPT. No significant BD increase could be achieved for the large thyroid tumor case and when the presence of critical structures mitigated the contribution of additional fields. The calculation of the biologically optimized plans can be completed in a clinically viable time (<30 minutes) on a small 24-GPU system. Conclusions: By exploiting GPU acceleration, MC-based, biologically optimized plans were created for small–tumor target patients. This optimizer will be used in an upcoming feasibility trial on LET{sub d} painting for radioresistant tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Computing the ankle-brachial index with parallel computational fluid dynamics

The ankle-brachial index (ABI), a ratio of arterial blood pressure in the ankles and upper arms, is used to diagnose and monitor circulatory conditions such as coarctation of the aorta and peripheral artery disease. Computational simulations of the ABI can potentially determine the parameters that produce an ABI indicative of ischemia or other abnormalities in blood flow. However, 0- and 1-D computational methods are limited in describing a 3-D patient-derived geometry. Thus, we present a massively parallel framework for computational fluid dynamics (CFD) simulations in the full arterial system. Additionally, using the lattice Boltzmann method to solve the Navier–Stokes equations, we employ highly parallelized and scalable methods to generate the simulation domain and efficiently distribute the computational load among processors. For the first time, we compute an ABI with 3-D CFD. In this proof-of-concept study, we investigate the dependence of ABI on the presence of stenoses, or narrowed regions of the arteries, by directly modifying the arterial geometry. As a result, our framework enables the computation a hemodynamic factor characterizing flow at the scale of the full arterial system, in a manner that is extensible to patient-specific imaging data and holds potential for treatment planning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Variably Saturated Flow and Multicomponent Biogeochemical Reactive Transport Modeling of a Uranium Bioremediation Field Experiment

Field experiments at a former uranium mill tailings site have identified the potential for stimulating indigenous bacteria to catalyze the conversion of aqueous uranium in the +6 oxidation state to immobile solid-associated uranium in the +4 oxidation state. This effectively removes uranium from solution resulting in groundwater concentrations below actionable standards. Three-dimensional, coupled variably-saturated flow and biogeochemical reactive transport modeling of a 2008 in situ uranium bioremediation field experiment is used to better understand the interplay of transport rates and biogeochemical reaction rates that determine the location and magnitude of key reaction products. A comprehensive reaction network, developed largely through previous 1-D modeling studies, was used to simulate the impacts on uranium behavior of pulsed acetate amendment, seasonal water table variation, spatially-variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. A principal challenge is the mechanistic representation of biologically-mediated terminal electron acceptor process (TEAP) reactions whose products significantly alter geochemical controls on uranium mobility through increases in pH, alkalinity, exchangeable cations, and highly reactive reduction products. In general, these simulations of the 2008 Big Rusty acetate biostimulation field experiment in Rifle, Colorado confirmed previously identified behaviors including (1) initial dominance by iron reducing bacteria that concomitantly reduce aqueous U(VI), (2) sulfate reducing bacteria that become dominant after {approx}30 days and outcompete iron reducers for the acetate electron donor, (3) continuing iron-reducer activity and U(VI) bioreduction during dominantly sulfate reducing conditions, and (4) lower apparent U(VI) removal from groundwater during dominantly sulfate reducing conditions. New knowledge on simultaneously active metal and sulfate reducers has been incorporated into the modeling. In this case, an initially small population of slow growing sulfate reducers is active from the initiation of biostimulation. Three-dimensional, variably saturated flow modeling was used to address impacts of a falling water table during acetate injection. These impacts included a significant reduction in aquifer saturated thickness and isolation of residual reactants and products, as well as unmitigated uranium, in the newly unsaturated vadose zone. High permeability sandy gravel structures resulted in locally high flow rates in the vicinity of injection wells that increased acetate dilution. In downgradient locations, these structures created preferential flow paths for acetate delivery that enhanced local zones of TEAP reactivity and subsidiary reactions. Conversely, smaller transport rates associated with the lower permeability lithofacies (e.g., fine) and vadose zone were shown to limit acetate access and reaction. Once accessed by acetate, however, these same zones limited subsequent acetate dilution and provided longer residence times that resulted in higher concentrations of TEAP products when terminal electron donors and acceptors were not limiting. Finally, facies-based porosity and reactive surface area variations were shown to affect aqueous uranium concentration distributions; however, the ranges were sufficiently small to preserve general trends. Large computer memory and high computational performance were required to simulate the detailed coupled process models for multiple biogeochemical components in highly resolved heterogeneous materials for the 110-day field experiment and 50 days of post-biostimulation behavior. In this case, a highly-scalable subsurface simulator operating on 128 processor cores for 12 hours was used to simulate each realization. An equivalent simulation without parallel processing would have taken 60 days, assuming sufficient memory was available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Interlocked optimization and fast gradient algorithm for a seismic inverse problem

Highlights: {yields} A 2D extension of the 1D nonlinear inversion of well-seismic data is given. {yields} Appropriate regularization yields a well-determined large scale inverse problem. {yields} An interlocked optimization loop acts as an efficient preconditioner. {yields} The adjoint state method is used to compute the misfit function gradient. {yields} Domain decomposition method yields an efficient parallel implementation. - Abstract: We give a nonlinear inverse method for seismic data recorded in a well from sources at several offsets from the borehole in a 2D acoustic framework. Given the velocity field, approximate values of the impedance are recovered. This is a 2D extension of the 1D inversion of vertical seismic profiles . The inverse problem generates a large scale undetermined ill-conditioned problem. Appropriate regularization terms render the problem well-determined. An interlocked optimization algorithm yields an efficient preconditioning. A gradient algorithm based on the adjoint state method and domain decomposition gives a fast parallel numerical method. For a realistic test case, convergence is attained in an acceptable time with 128 processors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Solution to PDEs using radial basis function finite-differences (RBF-FD) on multiple GPUs

This paper presents parallelization strategies for the radial basis function-finite difference (RBF-FD) method. As a generalized finite differencing scheme, the RBF-FD method functions without the need for underlying meshes to structure nodes. It offers high-order accuracy approximation and scales as O(N) per time step, with N being with the total number of nodes. To our knowledge, this is the first implementation of the RBF-FD method to leverage GPU accelerators for the solution of PDEs. Additionally, this implementation is the first to span both multiple CPUs and multiple GPUs. OpenCL kernels target the GPUs and inter-processor communication and synchronization is managed by the Message Passing Interface (MPI). We verify our implementation of the RBF-FD method with two hyperbolic PDEs on the sphere, and demonstrate up to 9x speedup on a commodity GPU with unoptimized kernel implementations. On a high performance cluster, the method achieves up to 7x speedup for the maximum problem size of 27,556 nodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Parallel multiscale simulations of a brain aneurysm

Cardiovascular pathologies, such as a brain aneurysm, are affected by the global blood circulation as well as by the local microrheology. Hence, developing computational models for such cases requires the coupling of disparate spatial and temporal scales often governed by diverse mathematical descriptions, e.g., by partial differential equations (continuum) and ordinary differential equations for discrete particles (atomistic). However, interfacing atomistic-based with continuum-based domain discretizations is a challenging problem that requires both mathematical and computational advances. We present here a hybrid methodology that enabled us to perform the first multiscale simulations of platelet depositions on the wall of a brain aneurysm. The large scale flow features in the intracranial network are accurately resolved by using the high-order spectral element Navier–Stokes solver NεκTαr. The blood rheology inside the aneurysm is modeled using a coarse-grained stochastic molecular dynamics approach (the dissipative particle dynamics method) implemented in the parallel code LAMMPS. The continuum and atomistic domains overlap with interface conditions provided by effective forces computed adaptively to ensure continuity of states across the interface boundary. A two-way interaction is allowed with the time-evolving boundary of the (deposited) platelet clusters tracked by an immersed boundary method. The corresponding heterogeneous solvers (NεκTαr and LAMMPS) are linked together by a computational multilevel message passing interface that facilitates modularity and high parallel efficiency. Results of multiscale simulations of clot formation inside the aneurysm in a patient-specific arterial tree are presented. We also discuss the computational challenges involved and present scalability results of our coupled solver on up to 300 K computer processors. Validation of such coupled atomistic-continuum models is a main open issue that has to be addressed in future work.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Temporal coarse-graining method to simulate the movement of atoms

We propose a novel method to simulate the movement of atoms at finite temperature. The main idea of our method is to derive “renormalized,” or coarse-grained in time, dynamics from the Euler–Maruyama scheme, which is the standard method for solving the stochastic differential equations numerically. Based on this renormalization, we propose a new algorithm for solving overdamped Langevin equations. We test our renormalization scheme on two models and demonstrate that the results obtained by this method are consistent with those obtained by the standard method. Our algorithm performs better than the standard scheme, especially at low temperatures and with multiple processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Higher-order adaptive finite-element methods for Kohn–Sham density functional theory

We present an efficient computational approach to perform real-space electronic structure calculations using an adaptive higher-order finite-element discretization of Kohn–Sham density-functional theory (DFT). To this end, we develop an a priori mesh-adaption technique to construct a close to optimal finite-element discretization of the problem. We further propose an efficient solution strategy for solving the discrete eigenvalue problem by using spectral finite-elements in conjunction with Gauss–Lobatto quadrature, and a Chebyshev acceleration technique for computing the occupied eigenspace. The proposed approach has been observed to provide a staggering 100–200-fold computational advantage over the solution of a generalized eigenvalue problem. Using the proposed solution procedure, we investigate the computational efficiency afforded by higher-order finite-element discretizations of the Kohn–Sham DFT problem. Our studies suggest that staggering computational savings—of the order of 1000-fold—relative to linear finite-elements can be realized, for both all-electron and local pseudopotential calculations, by using higher-order finite-element discretizations. On all the benchmark systems studied, we observe diminishing returns in computational savings beyond the sixth-order for accuracies commensurate with chemical accuracy, suggesting that the hexic spectral-element may be an optimal choice for the finite-element discretization of the Kohn–Sham DFT problem. A comparative study of the computational efficiency of the proposed higher-order finite-element discretizations suggests that the performance of finite-element basis is competing with the plane-wave discretization for non-periodic local pseudopotential calculations, and compares to the Gaussian basis for all-electron calculations to within an order of magnitude. Further, we demonstrate the capability of the proposed approach to compute the electronic structure of a metallic system containing 1688 atoms using modest computational resources, and good scalability of the present implementation up to 192 processors.

97 MATHEMATICS AND COMPUTING↗