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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Surface properties and RF performance of Vapor Diffused Nb3Sn on Nb after sequential anneals below 1000 °C

Nb3Sn is a next-generation superconducting material that can be used for future superconducting radiofrequency (SRF) accelerator cavities, promising better performance, cost reduction, and higher operating temperature than Nb. The Sn vapor diffusion method is currently the most preferred and successful technique to coat niobium cavi-ties with Nb3Sn. Among post-coating treatments to opti-mize the coating quality, higher temperature annealing without Sn is known to degrade Nb3Sn because of Sn loss. We have investigated Nb3Sn/Nb samples briefly annealed at 800-1000 °C for 10 and 20 minutes to poten-tially improve the surface to enhance the performance of Nb3Sn-coated cavities. Following the sample studies, a coated single-cell cavity was sequentially annealed at 900 °C and tested its performance each time, improving the cavity's quality factor relatively. This paper summarizes the sample studies and discusses the RF test results from sequentially annealed SRF Nb3Sn/Nb cavity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Surface Properties and RF Performance of Vapor Diffused Nb3Sn on NB After Sequential Anneals Below 1000°C

Nb3Sn is a next-generation superconducting material that can be used for future superconducting radiofrequency (SRF) accelerator cavities, promising better performance, cost reduction, and higher operating temperature than Nb. The Sn vapor diffusion method is currently the most preferred and successful technique to coat niobium cavi-ties with Nb3Sn. Among post-coating treatments to opti-mize the coating quality, higher temperature annealing without Sn is known to degrade Nb3Sn because of Sn loss. We have investigated Nb3Sn/Nb samples briefly annealed at 800-1000°C for 10 and 20 minutes to poten-tially improve the surface to enhance the performance of Nb3Sn-coated cavities. Following the sample studies, a coated single-cell cavity was sequentially annealed at 900°C and tested its performance each time, improving the cavity's quality factor relatively. This paper summarizes the sample studies and discusses the RF test results from sequentially annealed SRF Nb3Sn/Nb cavity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Effect of framework Al pairing on NO storage properties of Pd-CHA passive NOx adsorbers

For this study, three Pd/H-CHA samples were prepared containing 53.0%, 10.8% and 6.5% paired Al sites at near fixed Si/Al ratio and similar Pd loading. According to H 2 temperature-programmed reduction, Pd was present almost exclusively as isolated cations in the two samples containing the higher concentrations of paired Al sites, whereas in the other sample PdO was also present. Simulated lean cold start tests on the fresh samples conducted in a microflow reactor showed that the sample containing PdO stored the lowest amount of NOx. When tested with CO/H 2 , the sample containing 53.0% paired Al sites showed significantly better storage capacity than the other samples and deactivated less rapidly upon sequential tests. Experiments using lean gasoline engine exhaust revealed similar trends. This study showed that a high concentration of paired Al sites in Pd/H-CHA is beneficial for NOx storage capacity, thermal durability, and minimizing deactivation in the presence of CO/H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Parameter estimation by implicit sampling

© 2015 Mathematical Sciences Publishers. Implicit sampling is a weighted sampling method that is used in data assimilation to sequentially update state estimates of a stochastic model based on noisy and incomplete data. Here we apply implicit sampling to sample the posterior probability density of parameter estimation problems. The posterior probability combines prior information about the parameter with information from a numerical model, e.g., a partial differential equation (PDE), and noisy data. The result of our computations are parameters that lead to simulations that are compatible with the data. We demonstrate the usefulness of our implicit sampling algorithm with an example from subsurface flow. For an efficient implementation, we make use of multiple grids, BFGS optimization coupled to adjoint equations, and Karhunen-Loève expansions for dimensional reduction. Several difficulties of Markov chain Monte Carlo methods, e.g., estimation of burn-in times or correlations among the samples, are avoided because the implicit samples are independent.

Morzfeld, Matthias↗
DOE OSTI2018

SATYA: Defending Against Adversarial Attacks Using Statistical HypothesisTesting

The paper presents a new defense against adversarial attacks for deep neural networks. We demonstrate the effectiveness of our approach against the popular adversarial image generation method DeepFool. Our approach uses Wald’s Sequential Probability Ratio Test to sufficiently sample a carefully chosen neighborhood around an input image to determine the correct label of the image. On a benchmark of 50,000 randomly chosen adversarial images generated by DeepFool we demonstrate that our method SATYA is able to recover the correct labels for 95.76% of the images for CaffeNet and 97.43% of the correct label for GoogLeNet.

Raj, Sunny↗
DOE OSTI2024

Laminography as a tool for imaging large-size samples with high resolution

Despite the increased brilliance of the new generation synchrotron sources, there is still a challenge with high-resolution scanning of very thick and absorbing samples, such as a whole mouse brain stained with heavy elements, and, extending further, brains of primates. Samples are typically cut into smaller parts, to ensure a sufficient X-ray transmission, and scanned separately. Compared with the standard tomography setup where the sample would be cut into many pillars, the laminographic geometry operates with slab-shaped sections significantly reducing the number of sample parts to be prepared, the cutting damage and data stitching problems. In this work, a laminography pipeline for imaging large samples (>1 cm) at micrometre resolution is presented. The implementation includes a low-cost instrument setup installed at the 2-BM micro-CT beamline of the Advanced Photon Source. Additionally, sample mounting, scanning techniques, data stitching procedures, a fast reconstruction algorithm with low computational complexity, and accelerated reconstruction on multi-GPU systems for processing large-scale datasets are presented. The applicability of the whole laminography pipeline was demonstrated by imaging four sequential slabs throughout an entire mouse brain sample stained with osmium, in total generating approximately 12 TB of raw data for reconstruction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Chemical Speciation and Stability of Uranium in Unconventional Shales: Impact of Hydraulic Fracture Fluid

Uranium and other radionuclides are prominent in many unconventional oil/gas shales and is a potential contaminant in flowback/produced waters due to the large volumes/types of chemicals injected into the subsurface during stimulation. In this work, to understand the stability of U before and after stimulation, a geochemical study of U speciation was carried out on three shales (Marcellus, Green River, and Barnett). To do so, two types of samples for each shale were subjected to sequential chemical extractions: unreacted and shale-reacted with a synthetic hydraulic fracture fluid. Furthermore, a significant proportion of the total U (20–57%) was released from these three shales after reaction with fracture fluid, indicating that U is readily leachable. The total U released exceeds labile water-soluble and exchangeable fractions in unreacted samples, indicating that fluids leach more recalcitrant phases in the shale. Radiographic analysis of unreacted Marcellus shale thin sections shows U associated with detrital quartz and the clay matrix in the shale. Detrital zircon and TiO2 identified by an electron microprobe could account for the hot spots. This study shows that significant proportions of U in three shales are mobile upon stimulation. In addition, the extent of mobilization of U depends on the U species in these rocks.

58 GEOSCIENCES↗
DOE OSTI2016

Evolution of deep-bed filtration of engine exhaust particulates with trapped mass

Micro-scale filtration experiments were performed on cordierite filter samples using particulate matter (PM) generated by a spark-ignition direct-injection (SIDI) engine fueled with tier II EEE certification gasoline. Size-resolved mass and number concentrations were obtained from several engine operating conditions. The resultant mass-mobility relationships showed weak dependence on the operating condition. An integrated particle size distribution (IPSD) method was used estimate the PM mass concentration in the exhaust stream from the SIDI engine and a heavy duty diesel (HDD) engine. The average estimated mass concentration between all conditions was ~77****** % of the gravimetric measurements performed on Teflon filters. Despite the relatively low elemental carbon fraction (~0.4 to 0.7), the IPSD mass for stoichiometric SIDI exhaust was ~83±38 % of the gravimetric measurement. Identical cordierite filter samples with properties representative of diesel particulate filters were sequentially loaded with PM from the different SIDI engine operating conditions, in order of increasing PM mass concentration. Simultaneous particle size distribution measurements upstream and downstream of the filter sample were used to evaluate filter performance evolution and the instantaneous trapped mass within the filter for two different filter face velocities. The evolution of filtration performance for the different samples was sensitive only to trapped mass, despite using PM from a wide range of operating conditions. Higher filtration velocity resulted in a more rapid shift in the most penetrating particle size towards smaller mobility diameters.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Reversible oxygen intercalation in hexagonal Y 0.7 Tb 0.3 MnO 3+δ : toward oxygen production by temperature-swing absorption in air

The oxygen storage capacity, structure and thermodynamic stability were studied for hexagonal Y 0.7 Tb 0.3 MnO 3+δ in oxygen and air to assess its applicability for oxygen separation from air by a temperature-swing adsorption process. We show that large amounts of oxygen excess can be reversibly incorporated into and extracted from small particle-size samples of Y 0.7 Tb 0.3 MnO 3+δ prepared by sol–gel synthesis for fixed oxygen partial pressures. The hyperstoichiometric material, with δ ≥ 0.45 prepared in oxygen or high-pressure oxygen atmospheres, assumes a new hexagonal structure with interstitial oxygen defects near the nominally five coordinated Mn site as determined by neutron diffraction and supported by scanning and transmission electron microscopy. Thermogravimetric measurements demonstrate reversible intercalation of oxygen in a pure O 2 atmosphere at around 300 °C, but more importantly, also in air over a remarkably narrow temperature range of ~20 °C, albeit producing smaller oxygen amounts δ ≤ 0.25. Comparison of samples' properties obtained by the sol–gel and solid-state synthesis methods confirms enhanced oxygen storage capacity and oxygen exchange kinetics for the small particle-size samples which exhibit larger specific surface areas. Sequential temperature-swing absorption and long-term annealing experiments demonstrate the high practical potential of Y 0.7 Tb 0.3 MnO 3 compounds for the industrial production of oxygen enriched gases by utilization of waste heat at 250–350 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Rapid Sequential Separation Method for Determination of Actinides and TENORM in Fracking Wastes - 20223

With recent advances in unconventional drilling technology in the US and around the world, the risks of environmental contamination and exposure due to technologically enhanced naturally occurring radioactive materials (TENORM) from fracking wastes have also surfaced. Although the Permian Basin (southeastern New Mexico, western Texas) has long been a modest producer of oil, the advent of fracking technology a decade ago turned it into hot property for producers. A 2018 assessment of undiscovered, technically recoverable continuous oil and gas resources by the U.S. Geological Survey estimates an average 46.3 billion barrels of oil and 281 trillion cubic feet of gas. This is likely to increase the use of unconventional drilling and TENORM generation. TENORM concentrations in oil and gas exploration and production waste can be several hundred to several thousand times higher than background TENORM concentrations. Both the thorium and uranium decay chains contribute to airborne radionuclides arising from the radon gas escaping the ground and subsequently decaying as airborne particulates. Additionally, radon decay products {sup 210}Pb and {sup 210}Po can build up in scale on the internal surfaces of oil and gas handling pipes and in sludge in refineries, becoming potential inhalation and ingestion hazards for workers. Furthermore, southeastern NM is also home to world's only licensed and operating transuranic nuclear waste repository, the DoE's Waste Isolation Pilot Plant (WIPP). Plutonium isotopes ({sup 239+240}Pu) and {sup 241}Am, are expected to account for more than 99% of the total radioactivity scheduled for disposal in the WIPP repository. Thus, an improved understanding of the environmental fate and transport of TENORM, liberated by unconventional drilling, is essential to assess how best to protect individuals and the environment. In this context, accurate measurement of TENORM and actinides in environmental and biological samples is essential. In this presentation, a new sequential method for the separation and pre-concentration of actinides (Pu, Am, Np) and TENORM (Po, U and Th) derived from oil and gas exploration is proposed. The TEVA method involves a rapid co-precipitation step to remove matrix interferences from the samples, followed by plutonium oxidation state adjustment to Pu (IV) and an incubation period of ∼ 1 hour at 50-60 deg. C to allow the resultant Po (II) to oxidize into Po(IV). The polonium, neptunium, thorium and plutonium are then separated on a TEVA column, while americium and uranium are separated on a TRU column. After separation, the alpha counting source was prepared by micro-precipitation with copper sulfide (CuS) for polonium and neodymium fluoride (NdF{sub 3}) for actinides. The efficiency and reliability of the procedures were tested by analyzing filter, drinking water and frack sand samples. The method is simple, robust and can be performed quickly with excellent removal of interferences, high chemical recovery and very good alpha peak resolution. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Sequential Kalman tuning of the t -preconditioned Crank-Nicolson algorithm: efficient, adaptive and gradient-free inference for Bayesian inverse problems

Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when applied to the Bayesian inverse problem EKI is only exact in the regime of Gaussian target measures and linear forward models. Here, in this work we propose embedding EKI and Flow Annealed Kalman Inversion, its normalizing flow (NF) preconditioned variant, within a Bayesian annealing scheme as part of an adaptive implementation of the t-preconditioned Crank-Nicolson (tpCN) sampler. The tpCN sampler differs from standard pCN in that its proposal is reversible with respect to the multivariate t-distribution. The more flexible tail behaviour allows for better adaptation to sampling from non-Gaussian targets. Within our Sequential Kalman Tuning (SKT) adaptation scheme, EKI is used to initialize and precondition the tpCN sampler for each annealed target. The subsequent tpCN iterations ensure particles are correctly distributed according to each annealed target, avoiding the accumulation of errors that would otherwise impact EKI. We demonstrate the performance of SKT for tpCN on three challenging numerical benchmarks, showing significant improvements in the rate of convergence compared to adaptation within standard SMC with importance weighted resampling at each temperature level, and compared to similar adaptive implementations of standard pCN. The SKT scheme applied to tpCN offers an efficient, practical solution for solving the Bayesian inverse problem when gradients of the forward model are not available. Code implementing the SKT schemes for tpCN is available at https://github.com/RichardGrumitt/KalmanMC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Sequential polymer infusion into solid substrates (SPISS): Impact of processing on sorbent CO 2 adsorption properties

Solid sorbents made of small amine molecules and polyamines infused into mesoporous substrates are promising materials for CO 2 capture technologies. To date, their preparation is mainly based on wet infusion with focus on increasing amine content by varying the structure of the amine sorbent and designing solid substrates of various pore parameters. Less explored in the field are changes in processing to afford efficient CO 2 sorbents. In this study, branched poly(ethylenimine) (bPEI, M w = 800 Da) alone and blends with linear poly(propylenimine) (LPPI, M n = 6,700 Da) are infused into solid SBA-15 substrates by a method that varies the solution processing called sequential polymer infusion into solid substrates (SPISS). The reference 40 % bPEI-SBA-15 samples are split by two methods: split batch in dry suspension (SBD) and split batch in liquid suspension (SBL). Sequentially, alcoholic 10% of bPEI (non-blends) and 10% of LPPI (blends) solutions are introduced to afford the desired products. Under dry conditions, the resulting 50% bPEI-SBA-15 SBD & SBL sorbents display high CO 2 capacities up to 3.47 mmol CO 2 /g SiO 2 for simulated flue gas (10% CO 2 ) and 2.62 mmol CO 2 /g SiO 2 for direct air capture (DAC, 400 ppm CO 2 ). Under humid DAC conditions the CO 2 performance is further enhanced with an uptake of 4.62 mmol CO 2 /gSiO 2 and amine efficiency of 0.22 mmol CO 2 /mmol N. Subjected to extended temperature swing adsorption kinetic cycling (20 cycles), the SPISS samples display stable working capacities and retain over 70% (blends) and over 90% (non-blends) of their initial 12 h adsorption performance. LPPI is demonstrated to be an effective water sorption limiting agent using dynamic vapor sorption measurements. Solid state NMR techniques reveal important insights into the dynamics of the amine polymers confined into SBA-15 pores, as impacted by processing conditions. The results suggest that the conformation of the polymers is different depending on the processing method, displaying relatively tight (SBD) and loose (SBL) packing. Finally, the simple solution processing approaches presented here show that processing variations may guide the design of solid amine sorbents with desirable properties relevant for integration into CO 2 capture technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Engineering metal–metal oxide surfaces for high-performance oxygen reduction on Ag–Mn electrocatalysts

Understanding fundamental material–property relationships in mixed-element catalyst systems is crucial to advancing the viability of renewable electrochemical energy technologies, an important part of creating a more sustainable future. Herein, we report our insight on the nature and dynamics of highly active silver–manganese oxide (Ag–MnOx) catalyst surfaces for the oxygen reduction reaction (ORR) via a combined experimental–theoretical approach. Experimentally, we synthesize well-mixed Ag–Mn co-deposited thin films that are measurably flat and smooth, despite Mn surface migration and oxidation upon air exposure and electrochemical measurements. Cyclic voltammetry in 0.1 M KOH demonstrates up to 10-fold specific activity enhancements over pure Ag at 0.8 V vs. RHE for Ag-rich films (70–95% Ag in bulk). To further understand the Ag–Mn system, separate samples were synthesized with small amounts of Mn sequentially deposited onto the surface of a pure Ag thin film (Mn@Ag), ranging from partial to full surface coverage (down to 0.3 nm Mn $cm^{-2}_{geo}$ ~ 0.2 μg Mn $cm^{-2}_{geo}$). These sequentially deposited Mn@Ag films show analogous performance to their co-deposited counterparts indicating similar enhanced active sites. With density functional theory (DFT), we calculate that this enhancement arises from the tuned d-band of these material surfaces owing to the optimal hybridization of the electronic structures in specific Ag and MnO x geometries. Together, electrochemical measurements, DFT calculations, X-ray absorption spectroscopy, and valence-band X-ray photoelectron spectroscopy suggest synergistic electronic interactions between Ag and MnOx yield enhanced oxygen adsorption, and thus ORR activity, with DFT highlighting the Ag–MnO x interface sites as the most enhanced. This work demonstrates how combined experimental–theoretical methods can help design electrocatalysts with enhanced electrocatalytic properties and understand the nature of complex mixed metal–metal oxide surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

First principles study of the structural, electronic, and transport properties of triarylamine-based nanowires

We investigate with state of the art density functional theory the structural, electronic, and transport properties of a class of recently synthesized nanostructures based on triarylamine derivatives. First, we consider the single molecule precursors in the gas phase and calculate their static properties, namely (i) the geometrical structure of the neutral and cationic ions, (ii) the electronic structure of the frontier molecular orbitals, and (iii) the ionization potential, hole extraction potential, and internal reorganization energy. This initial study does not evidence any direct correlation between the properties of the individual molecules and their tendency to self-assembly. Subsequently, we investigate the charge transport characteristics of the triarylamine derivatives nanowires, by using Marcus theory. For one derivative we further construct an effective Hamiltonian including intermolecular vibrations and evaluate the mobility from the Kubo formula implemented with Monte Carlo sampling. These two methods, valid respectively in the sequential hopping and polaronic band limit, give us values for the room-temperature mobility in the range 0.1–12 cm{sup 2}/Vs. Such estimate confirms the superior transport properties of triarylamine-based nanowires, and make them an attracting materials platform for organic electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Cylindrical Magnetron Development for Nb3sn Deposition via Magnetron Sputtering

Due to its better superconducting properties (critical temperature Tc~ 18.3 K, superheating field Hsh~ 400 mT), Nb₃Sn is considered as a potential alternative to niobium (Tc~ 9.25 K, Hsh~ 200 mT) for superconducting radiofrequency (SRF) cavities for particle acceleration. Magnetron sputtering is an effective method to produce superconducting Nb₃Sn films. We deposited superconducting Nb₃Sn films on samples with magnetron sputtering using co-sputtering, sequential sputtering, and sputtering from a stoichiometric target. Nb₃Sn films produced by magnetron sputtering in our previous experiments have achieved DC superconducting critical temperature up to 17.93 K and RF superconducting transition at 17.2 K. A magnetron sputtering system with two identical cylindrical cathodes that can be used to sputter Nb₃Sn films on cavities has been designed and is under development now. We report on the design and the current progress on the development of the system.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Robust Importance Sampling for Bayesian Model Calibration with Spatio-Temporal Data

This paper addresses two challenges in Bayesian calibration: 1) computational speed of existing sampling algorithms, and 2) calibration with spatio-temporal responses. The commonly used Markov Chain Monte Carlo (MCMC) approaches require many sequential model evaluations making the computational expense prohibitive. This paper proposes an efficient sampling algorithm: iterative importance sampling with genetic algorithm (IISGA). While iterative importance sampling enables computational efficiency, the genetic algorithm enables robustness by preventing sample degeneration and avoids getting stuck in multimodal search spaces. An inflated likelihood further enables robustness in high-dimensional parameter spaces by enlarging the target distribution. Spatio-temporal data complicate both surrogate modeling, which is necessary for expensive computational models, and the likelihood estimation. In this work, singular value decomposition is investigated for reducing the high-dimensional field data to a lower-dimensional space prior to Bayesian calibration. Then the likelihood is formulated and Bayesian inference is performed in the lower-dimension, latent space. An illustrative example is provided to demonstrate IISGA relative to existing sampling methods, and then IISGA is employed to calibrate a thermal battery model with 26 uncertain calibration parameters and spatio-temporal response data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Multilevel sequential Monte Carlo samplers

Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h L . In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levels ${\infty}$ >h 0 >h 1 ...>h L . In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.

77 NANOSCIENCE AND NANOTECHNOLOGY↗