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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 OSTI2017

Scalable Dry Printing Manufacturing to Enable Long-Life and High Energy Lithium-Ion Batteries

Slurry casting method dominates the electrode manufacture of lithium-ion batteries. The entire procedure is similar to the newspaper printing that includes premixing of cast materials into solvents homogeneously, and continuously transferring and drying the slurry mixture onto the current collector. As a market approaching US $80 billion by 2024, the optimization of manufacture process is crucial and attractive. However, the organic solvent remains irreplaceable in the wet method for making slurries, even though it is capital-intensive and toxic. In this paper, an advanced powder printing technique is demonstrated that is completely solvent-free and dry. Through removing the solvent and related procedures, this method is anticipated to statistically save 20% of the cost at a remarkably shortened production cycle (from hours to minutes). The dry printed electrodes outperform commercial slurry cast ones in 650 cycles (80% capacity retention in 500 cycles), and thick electrodes are successfully fabricated to increase the energy density. Furthermore, microscopy techniques are utilized to characterize the difference of electrode microstructure between dry and wet methods, and distinguish dry printing's advantages on controlling the microstructure. Finally, this study proves a practical fabrication method for lithium-ion electrodes with lowered cost and favorable performance, and allows more advanced electrode designs potentially.

25 ENERGY STORAGE↗
DOE OSTI2021

Polishing the Gold Standard: The Role of Orbital Choice in CCSD(T) Vibrational Frequency Prediction

While CCSD(T) with spin-restricted Hartree-Fock (RHF) orbitals has long been lauded for its ability to accurately describe closed-shell interactions, the performance of CCSD(T) on open-shell species is much more erratic, especially when using a spin-unrestricted HF (UHF) reference. Previous studies have shown improved treatment of open-shell systems when a non-HF set of molecular orbitals, like Brueckner or Kohn-Sham density functional theory (DFT) orbitals, is used as a reference. Inspired by the success of regularized orbital-optimized second-order Møller-Plesset perturbation theory (κ-OOMP2) orbitals as reference orbitals for MP3, we investigate the use of κ-OOMP2 orbitals and various DFT orbitals as reference orbitals for CCSD(T) calculations of the corrected ground-state harmonic vibrational frequencies of a set of 36 closed-shell (29 neutrals, 6 cations, 1 anion) and 59 open-shell diatomic species (38 neutrals, 15 cations, 6 anions). The aug-cc-pwCVTZ basis set is used for all calculations. The use of κ-OOMP2 orbitals in this context alleviates difficult cases observed for both UHF orbitals and OOMP2 orbitals. Removing two multireference systems and 12 systems with ambiguous experimental data leaves a pruned data set. Overall performance on the pruned data set highlights CCSD(T) with a B97 orbital reference (CCSD(T):B97), CCSD(T) with a κ-OOMP2 orbital reference (CCSD(T):κ-OOMP2), and CCSD(T) with a B97M-rV orbital reference (CCSD(T):B97M-rV) with RMSDs of 8.48 cm -1 , and 8.50 cm -1 , and 8.75 cm -1 respectively, outperforming CCSD(T):UHF by nearly a factor of 5. Moreover, the performance on the closed- and open-shell subsets shows these methods are able to treat open-shell and closed-shell systems with comparable accuracy and robustness. CCSD(T) with RHF orbitals is seen to improve upon UHF for the closed-shell species, while spatial symmetry breaking in a number of restricted open-shell HF (ROHF) references leads CCSD(T) with ROHF reference orbitals to exhibit the poorest statistical performance of all methods surveyed for open-shell species. The use of κ-OOMP2 orbitals has also proven useful in diagnosing multireference character that can hinder the reliability of CCSD(T).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Validation Strategies for Microbial Forensic Analysis

The validation of the probative value of microbial forensic techniques is a critical aspect of research and development that requires careful planning and a sound conceptual framework. This paper outlines a particular approach to the validation of certain types of forensic methods that naturally generates statistical measures of the relevance and weight of the scientific evidence derived from them. The suggested approach is based on the likelihood ratio interpretation of Federal Rules of Evidence 401 and 402 and allows measurement evidence to be to be presented in a format that resembles the forensic "gold standard" - human DNA typing. Examples of specific genetic and chemical and physical analysis methods are used to illustrate how this general strategy can be applied. This approach also provides a natural interpretation of the notion of "preliminary validation" that has been proposed in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2012

The application of Plant Reliability Data Information System (PRINS) to CANDU reactor

As risk-informed applications (RIAs) are actively implanted in the nuclear industry, an issue associated with technical adequacy of Probabilistic Safety Assessment (PSA) arises in its modeling and data sourcing. In Korea, PSA for all Korean NPPs has been completed and KHNP(Korea Hydro and Nuclear Power Plant Company) developed the database called the Plant Reliability Data Information System (PRinS). It has several characteristics that distinguish it from other database system such as NPRDs (INPO,1994), PRIS (IAEA), and SRDF (EdF). This database has the function of systematic data management such as automatic data-gathering, periodic data deposition and updating, statistical analysis including Bayesian method, and trend analysis of failure rate or unavailability. In recent PSA for CANDU reactor, the component failure data of EPRI ALWR URD and Component Reliability Database were preferentially used as generic data set. The error factor for most component failure data was estimated by using the information NUREG/CR-4550 and NUREG/CR-4639. Also, annual trend analysis was performed for the functional losses of components using the statistical analysis and chart module of PRinS. Furthermore, the database has been updated regularly and maintained as a living program to reflect the current status. This paper presents the failure data analysis using PRinS which provides Bayesian analysis on main components in the CANDU reactor. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

Minima of the fluctuations of the order parameter of global seismicity

It has been recently shown [N. V. Sarlis, Phys. Rev. E 84, 022101 (2011) and N. V. Sarlis and S.-R. G. Christopoulos, Chaos 22, 023123 (2012)] that earthquakes of magnitude M greater or equal to 7 are globally correlated. Such correlations were identified by studying the variance κ{sub 1} of natural time which has been proposed as an order parameter for seismicity. Here, we study the fluctuations of this order parameter using the Global Centroid Moment Tensor catalog for a magnitude threshold M{sub thres} = 5.0 and focus on its behavior before major earthquakes. Natural time analysis reveals that distinct minima of the fluctuations of the order parameter of seismicity appear within almost five and a half months on average before all major earthquakes of magnitude larger than 8.4. This phenomenon corroborates the recent finding [N. V. Sarlis et al., Proc. Natl. Acad. Sci. U.S.A. 110, 13734 (2013)] that similar minima of the seismicity order parameter fluctuations had preceded all major shallow earthquakes in Japan. Moreover, on the basis of these minima a statistically significant binary prediction method for earthquakes of magnitude larger than 8.4 with hit rate 100% and false alarm rate 6.67% is suggested.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Integrated Process Monitoring based on Systems of Sensors for Enhanced Nuclear Safeguards Sensitivity and Robustness

This paper illustrates safeguards benefits that process monitoring (PM) can have as a diversion deterrent and as a complementary safeguards measure to nuclear material accountancy (NMA). In order to infer the possible existence of proliferation-driven activities, the objective of NMA-based methods is often to statistically evaluate materials unaccounted for (MUF) computed by solving a given mass balance equation related to a material balance area (MBA) at every material balance period (MBP), a particular objective for a PM-based approach may be to statistically infer and evaluate anomalies unaccounted for (AUF) that may have occurred within a MBP. Although possibly being indicative of proliferation-driven activities, the detection and tracking of anomaly patterns is not trivial because some executed events may be unobservable or unreliably observed as others. The proposed similarity between NMA- and PM-based approaches is important as performance metrics utilized for evaluating NMA-based methods, such as detection probability (DP) and false alarm probability (FAP), can also be applied for assessing PM-based safeguards solutions. To this end, AUF count estimates can be translated into significant quantity (SQ) equivalents that may have been diverted within a given MBP. A diversion alarm is reported if this mass estimate is greater than or equal to the selected value for alarm level (AL), appropriately chosen to optimize DP and FAP based on the particular characteristics of the monitored MBA, the sensors utilized, and the data processing method employed for integrating and analyzing collected measurements. To illustrate the application of the proposed PM approach, a protracted diversion of Pu in a waste stream was selected based on incomplete fuel dissolution in a dissolver unit operation, as this diversion scenario is considered to be problematic for detection using NMA-based methods alone. Results demonstrate benefits of conducting PM under a system-centric strategy that utilizes data collected from a system of sensors and that effectively exploits known characterizations of sensors and facility operations in order to significantly improve anomaly detection, reduce false alarm, and enhance assessment robustness under unreliable partial sensor information.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Numerically exact full counting statistics of the energy current in the Kondo regime

In this study, we use the inchworm quantum Monte Carlo method to investigate the full counting statistics of particle and energy currents in a strongly correlated quantum dot. Our method is used to extract the heat fluctuations and entropy production of a quantum thermoelectric device, as well as cumulants of the particle and energy currents. The energy-particle current cross correlations reveal information on the preparation of the system and the interplay of thermal and electric currents. Finally, we demonstrate the signature of a crossover from Coulomb blockade to Kondo physics in the energy current fluctuations, and show how the conventional master equation approach to full counting statistics systematically fails to capture this crossover.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Deep-field analytical calibration

The next generation of imaging surveys, including the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Euclid, and the Nancy Grace Roman Space Telescope, will provide unprecedented constraints on cosmology using weak gravitational lensing. To fully exploit this statistical power, shear measurement methods must achieve sub- per cent accuracy while mitigating systematic biases from noise, the point-spread function (PSF), blending, and shear-dependent detection. The analytical calibration framework (AnaCal) has demonstrated such accuracy but requires adding noise to images, reducing effective depth. We introduce Deep-Field Analytical Calibration (DEEP-FIELD AnaCal), an extension of AnaCal that uses deep-field images to compute shear responses while preserving the statistical power of wide-field data. We validate DEEP-FIELD AnaCal on isolated and blended galaxy image simulations with LSST-like conditions, finding it meets the stringent requirement of multiplicative bias $|m| < 3\times 10^{-3}$ at 99.7 per cent confidence. Compared to standard AnaCal applied to wide-field images, DEEP-FIELD AnaCal increases the effective galaxy number density from 17 to 30 arcmin$^{-2}$ for simulated 10-yr LSST data. With deep fields $10\times$ longer than the wide field, we find pixel noise variance in shear estimation is reduced by 30 per cent and overall uncertainty by $\sim 25~{{\ \rm per\ cent}}$. Finally, using the LSST Deep Drilling Fields strategy, we assess sample variance and find an equivalent calibration uncertainty of $\lesssim 0.3~{{\ \rm per\ cent}}$. These results demonstrate that DEEP-FIELD AnaCal offers a promising path to achieve the required shear calibration for upcoming weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Underestimation of multi-decadal global O 2 loss due to an optimal interpolation method

Abstract. The global ocean's oxygen content has declined significantly over the past several decades and is expected to continue decreasing under global warming, with far-reaching impacts on marine ecosystems and biogeochemical cycling. Determining the oxygen trend, its spatial pattern, and uncertainties from observations is fundamental to our understanding of the changing ocean environment. This study uses a suite of CMIP6 Earth system models to evaluate the biases and uncertainties in oxygen distribution and trends due to sampling sparseness. Model outputs are sub-sampled according to the spatial and temporal distribution of the historical shipboard measurements, and the data gaps are filled by a simple optimal interpolation method using Gaussian covariance with a constant e-folding length scale. Sub-sampled results are compared to full model output, revealing the biases in global and basin-wise oxygen content trends. The simple optimal interpolation underestimates the modeled global deoxygenation trends, capturing approximately two-thirds of the full model trends. The North Atlantic and subpolar North Pacific are relatively well sampled, and the simple optimal interpolation is capable of reconstructing more than 80 % of the oxygen trend in the non-eddying CMIP models. In contrast, pronounced biases are found in the equatorial oceans and the Southern Ocean, where the sampling density is relatively low. The application of the simple optimal interpolation method to the historical dataset estimated the global oxygen loss to be 1.5 % over the past 50 years. However, the ratio of the global oxygen trend between the sub-sampled and full model output has increased the estimated loss rate in the range of 1.7 % to 3.1 % over the past 50 years, which partially overlaps with previous studies. The approach taken in this study can provide a framework for the intercomparison of different statistical gap-filling methods to estimate oxygen content trends and their uncertainties due to sampling sparseness.

Ito, Takamitsu (ORCID:000000019873099X)↗
DOE OSTI2013

Solving large scale structure in ten easy steps with COLA

We present the COmoving Lagrangian Acceleration (COLA) method: an N-body method for solving for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). Unlike standard N-body methods, the COLA method can straightforwardly trade accuracy at small-scales in order to gain computational speed without sacrificing accuracy at large scales. This is especially useful for cheaply generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing, as those catalogs are essential for performing detailed error analysis for ongoing and future surveys of LSS. As an illustration, we ran a COLA-based N-body code on a box of size 100 Mpc/h with particles of mass ≈ 5 × 10{sup 9}M{sub s}un/h. Running the code with only 10 timesteps was sufficient to obtain an accurate description of halo statistics down to halo masses of at least 10{sup 11}M{sub s}un/h. This is only at a modest speed penalty when compared to mocks obtained with LPT. A standard detailed N-body run is orders of magnitude slower than our COLA-based code. The speed-up we obtain with COLA is due to the fact that we calculate the large-scale dynamics exactly using LPT, while letting the N-body code solve for the small scales, without requiring it to capture exactly the internal dynamics of halos. Achieving a similar level of accuracy in halo statistics without the COLA method requires at least 3 times more timesteps than when COLA is employed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Resolved Stellar Streams around NGC 4631 from a Subaru/Hyper Suprime-Cam Survey

We present the first results of the Subaru/Hyper Suprime-Cam survey of the interacting galaxy system, NGC 4631 and NGC 4656. From the maps of resolved stellar populations, we identify 11 dwarf galaxies (including already-known dwarfs) in the outer region of NGC 4631 and the two tidal stellar streams around NGC 4631, named Stream SE and Stream NW, respectively. This paper describes the fundamental properties of these tidal streams. Based on the tip of the red giant branch method and the Bayesian statistics, we find that Stream SE (7.10 Mpc in expected a posteriori, EAP, with 90% credible intervals of [6.22, 7.29] Mpc) and Stream NW (7.91 Mpc in EAP with 90% credible intervals of [6.44, 7.97] Mpc) are located in front of and behind NGC 4631, respectively. We also calculate the metallicity distribution of stellar streams by comparing the member stars with theoretical isochrones on the color–magnitude diagram. We find that both streams have the same stellar population based on the Bayesian model selection method, suggesting that they originated from a tidal interaction between NGC 4631 and a single dwarf satellite. The expected progenitor has a positively skewed metallicity distribution function with [M/H]{sub EAP}=−0.92, with 90% credible intervals of [−1.46, −0.51]. The stellar mass of the progenitor is estimated as 3.7×10{sup 8} M{sub ⊙}, with 90% credible intervals of [5.8×10{sup 6},8.6×10{sup 9}] M{sub ⊙} based on the mass–metallicity relation for Local group dwarf galaxies. This is in good agreement with the initial stellar mass of the progenitor that was presumed in the previous N-body simulation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Value of Information From Horizontal Distributed Acoustic Sensing Compared to Multicomponent Geophones Via Machine Learning

Abstract Faults play an important role in recharging many geothermal reservoirs, and seismic information can image the locations of these faults. The value of information (VOI) metric is used to objectively quantify and compare the value of two types of seismic receiver data via a machine learning approach. The demonstrated VOI methodology is novel by including spatial models from seismic data and obtaining the information statistics from machine learning. Our two-dimensional numerical experiments compare images created from sparsely spaced (80 m), two-component geophone sampling to high spatial resolution (1 m), single-component DAS. We used a three-fold cross validation of a U-Net convolutional neural networks to achieve average classification statistics. The results suggest that when horizontal sources are utilized, geophones and DAS identify reflectors and non-reflectors at roughly the same rate. The average F1 score for horizontal DAS is 0.939 and 0.931 for geophones. For images created from a vertical source, DAS performed marginally better (F1 = 0.919) than geophones (F1 = 0.877). Our transferrable methodology can provide guidance on which acquisition scenarios can improve images of important structures in the subsurface and present an efficient method for obtaining reliability statistics from high-dimensional, spatial data.

Energy & Fuels↗
DOE OSTI2019

Evolving charge correlations in a hybrid model with both hydrodynamics and hadronic Boltzmann descriptions

Background: Correlations from charge correlation, known as charge balance functions, provide critical tests of the chemical evolution of matter in a heavy-ion collision. Comparisons of experimental balance functions with calculations from parametric descriptions of the final state suggest that the charge production in the earliest stages of a heavy-ion collision are consistent with having generated an amount of light up, down, and strange quarks that are largely consistent with expectations for creating a chemically equilibrate quark-gluon plasma. Purpose: This work describes a full simulation of the evolving correlations superimposed on a state-of-the-art microscopic description of the collision. Methods: The creation and diffusion of balancing charges is modeled on the background of a hybrid description of the evolution based on hydrodynamics, for when the matter’s temperature is above 155 MeV, and a microscopic hadronic simulation, for the breakup stage. The translation of the charge-charge correlation function, indexed by the flavors up, down, and strange, into correlations between specific hadron species is built on the assumption that differential charges enhance differential yields according to statistical equilibrium. Monte Carlo methods are implemented when applicable. Results: The charge balance functions are predicted for pairs indexed by charge alone or by whether the particle pairs are any combination of pions, kaons, or protons. We report comparisons with experiment are remarkably successful except for the proton-kaon balance functions. Conclusions: This demonstrates first that two-particle correlations from charge conservation can be calculated for a state-of-the-art model of the evolution with moderate amounts of computation. Aside from the magnitude of the proton-kaon correlations, the calculations well describe preliminary experimental results from the STAR Collaboration at the Relativistic Heavy Ion Collider. Ignoring the one disagreement, this suggests that the matter in a heavy-ion collision comes close to maintaining chemical equilibrium during the superhadronic stage of a heavy-ion collision.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems

The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H{sub 2}O, N{sub 2}, and F{sub 2} molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

TURBULENCE AND STAR FORMATION IN A SAMPLE OF SPIRAL GALAXIES

We investigate turbulent gas motions in spiral galaxies and their importance to star formation in far outer disks, where the column density is typically far below the critical value for spontaneous gravitational collapse. Following the methods of Burkhart et al. on the Small Magellanic Cloud, we use the third and fourth statistical moments, as indicators of structures caused by turbulence, to examine the neutral hydrogen (H i) column density of a sample of spiral galaxies selected from The H i Nearby Galaxy Survey. We apply the statistical moments in three different methods—the galaxy as a whole, divided into a function of radii and then into grids. We create individual grid maps of kurtosis for each galaxy. To investigate the relation between these moments and star formation, we compare these maps with their far-ultraviolet images taken by the Galaxy Evolution Explorer satellite.We find that the moments are largely uniform across the galaxies, in which the variation does not appear to trace any star-forming regions. This may, however, be due to the spatial resolution of our analysis, which could potentially limit the scale of turbulent motions that we are sensitive to greater than ∼700 pc. From comparison between the moments themselves, we find that the gas motions in our sampled galaxies are largely supersonic. This analysis also shows that the Burkhart et al. methods may be applied not just to dwarf galaxies but also to normal spiral galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Online evolutionary neural architecture search for multivariate non-stationary time series forecasting

Time series forecasting (TSF) is one of the most important tasks in data science. TSF models are usually pre-trained with historical data and then applied on future unseen datapoints. However, real-world time series data is usually non-stationary and models trained offline usually face problems from data drift. Models trained and designed in an offline fashion can not quickly adapt to changes quickly or be deployed in real-time. To address these issues, this work presents the Online NeuroEvolution-based Neural Architecture Search (ONE-NAS) algorithm, which is a novel neural architecture search method capable of automatically designing and dynamically training recurrent neural networks (RNNs) for online forecasting tasks. Without any pre-training, ONE-NAS utilizes populations of RNNs that are continuously updated with new network structures and weights in response to new multivariate input data. ONE-NAS is tested on real-world, large-scale multivariate wind turbine data as well as the univariate Dow Jones Industrial Average (DJIA) dataset. These results demonstrate that ONE-NAS outperforms traditional statistical time series forecasting methods, including online linear regression, fixed long short-term memory (LSTM) and gated recurrent unit (GRU) models trained online, as well as state-of-the-art, online ARIMA strategies. Additionally, results show that utilizing multiple populations of RNNs which are periodically repopulated provide significant performance improvements, allowing this online neural network architecture design and training to be successful.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

NSE abundance data

A novel method of calculating nuclear statistical equilibrium (NSE) is presented. Basic equations are carefully solved using arbitrary precision arithmetic. A special interpolation procedure is then used to retrieve all abundances using tabulated results for neutrons and protons, together with basic nuclear data. Proton and neutron abundance tables, basic nuclear data, and partition functions for nuclides used in the calculations are provided. A simple interpolation algorithm using pre-calculated p and n abundances tabulated as functions of kT, {rho} and Y{sub e} is outlined. Unique properties of this method are: (1) ability to pick up out of NSE selected nuclei only, (2) computational time scaling linearly with number of re-calculated abundances, (3) relatively small amount of stored data: only two large tables, (4) slightly faster than solving the NSE equations using traditional Newton-Raphson methods for small networks (few tens of species); superior for huge (800-3000) networks, (5) does not require initial guess; works well on random input, (6) can be tailored to specific application, (7) ability to use third-party NSE solvers to obtain fully compatible tables, and (8) encapsulation of the NSE code for bug-free calculations. A range of applications for this approach is possible: covering tests of traditional NSE Newton-Raphson codes, generating starting values, code-to-code verification, and possible replacement of the old legacy procedures in supernova simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Primary and secondary battery consumption trends in Sweden 1996–2013: Method development and detailed accounting by battery type

Highlights: • Developed MFA method was validated by the national statistics. • Exponential increase of EEE sales leads to increase in integrated battery consumption. • Digital convergence is likely to be a cause for primary batteries consumption decline. • Factors for estimation of integrated batteries in EE are provided. • Sweden reached the collection rates defined by European Union. - Abstract: In this article, a new method based on Material Flow Accounting is proposed to study detailed material flows in battery consumption that can be replicated for other countries. The method uses regularly available statistics on import, industrial production and export of batteries and battery-containing electric and electronic equipment (EEE). To promote method use by other scholars with no access to such data, several empirically results and their trends over time, for different types of batteries occurrence among the EEE types are provided. The information provided by the method can be used to: identify drivers of battery consumption; study the dynamic behavior of battery flows – due to technology development, policies, consumers behavior and infrastructures. The method is exemplified by the study of battery flows in Sweden for years 1996–2013. The batteries were accounted, both in units and weight, as primary and secondary batteries; loose and integrated; by electrochemical composition and share of battery use between different types of EEE. Results show that, despite a fivefold increase in the consumption of rechargeable batteries, they account for only about 14% of total use of portable batteries. Recent increase in digital convergence has resulted in a sharp decline in the consumption of primary batteries, which has now stabilized at a fairly low level. Conversely, the consumption of integrated batteries has increased sharply. In 2013, 61% of the total weight of batteries sold in Sweden was collected, and for the particular case of alkaline manganese dioxide batteries, the value achieved 74%.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗