Dynamic modeling of active regeneration in catalyzed and non-catalyzed diesel particulate filters

Particulate matter (PM) emissions standards set by the US Environmental Protection Agency (EPA) have become increasingly stringent over the years. The EPA regulation for PM in heavy duty diesel engines has been reduced to 0.01 g/bhp-hr for the year 2010. Heavy duty diesel engines make use of an aftertreatment filtration device, the Diesel Particulate Filter (DPF). DPFs are highly efficient in filtering PM (known as soot) and are an integral part of 2010 heavy duty diesel aftertreatment system. PM is accumulated in the DPF as the exhaust gas flows through it. This PM needs to be removed by oxidation periodically for the efficient functioning of the filter. This oxidation process is also known as regeneration. There are 2 types of regeneration processes, namely active regeneration (oxidation of PM by external means) and passive oxidation (oxidation of PM by internal means). Active regeneration occurs typically in high temperature regions, about 500 - 600 °C, which is much higher than normal diesel exhaust temperatures. Thus, the exhaust temperature has to be raised with the help of external devices like a Diesel Oxidation Catalyst (DOC) or a fuel burner. The O2 oxidizes PM producing CO2 as oxidation product. In passive oxidation, one way of regeneration is by the use of NO2. NO2 oxidizes the PM producing NO and CO2 as oxidation products. The passive oxidation process occurs at lower temperatures (200 - 400 °C) in comparison to the active regeneration temperatures. Generally, DPF substrate walls are washcoated with catalyst material to speed up the rate of PM oxidation. The catalyst washcoat is observed to increase the rate of PM oxidation. The goal of this research is to develop a simple mathematical model to simulate the PM depletion during the active regeneration process in a DPF (catalyzed and non-catalyzed). A simple, zero-dimensional kinetic model was developed in MATLAB. Experimental data required for calibration was obtained by active regeneration experiments performed on PM loaded mini DPFs in an automated flow reactor. The DPFs were loaded with PM from the exhaust of a commercial heavy duty diesel engine. The model was calibrated to the data obtained from active regeneration experiments. Numerical gradient based optimization techniques were used to estimate the kinetic parameters of the model.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

Transformer modeling ATP : internal faults & high-frequency discretization

Power transformers are key components of the power grid and are also one of the most subjected to a variety of power system transients. The failure of a large transformer can cause severe monetary losses to a utility, thus adequate protection schemes are of great importance to avoid transformer damage and maximize the continuity of service. Computer modeling can be used as an efficient tool to improve the reliability of a transformer protective relay application. Unfortunately, transformer models presently available in commercial software lack completeness in the representation of several aspects such as internal winding faults, which is a common cause of transformer failure. It is also important to adequately represent the transformer at frequencies higher than the power frequency for a more accurate simulation of switching transients since these are a well known cause for the unwanted tripping of protective relays. This work develops new capabilities for the Hybrid Transformer Model (XFMR) implemented in ATPDraw to allow the representation of internal winding faults and slow-front transients up to 10 kHz. The new model can be developed using any of two sources of information: 1) test report data and 2) design data. When only test-report data is available, a higher-order leakage inductance matrix is created from standard measurements. If design information is available, a Finite Element Model is created to calculate the leakage parameters for the higher-order model. An analytical model is also implemented as an alternative to FEM modeling. Measurements on 15-kVA 240?/208Y V and 500-kVA 11430Y/235Y V distribution transformers were performed to validate the model. A transformer model that is valid for simulations for frequencies above the power frequency was developed after continuing the division of windings into multiple sections and including a higher-order capacitance matrix. Frequency-scan laboratory measurements were used to benchmark the simulations. Finally, a stability analysis of the higher-order model was made by analyzing the trapezoidal rule for numerical integration as used in ATP. Numerical damping was also added to suppress oscillations locally when discontinuities occurred in the solution. A maximum error magnitude of 7.84% was encountered in the simulated currents for different turn-to-ground and turn-to-turn faults. The FEM approach provided the most accurate means to determine the leakage parameters for the ATP model. The higher-order model was found to reproduce the short-circuit impedance acceptably up to about 10 kHz and the behavior at the first anti-resonant frequency was better matched with the measurements.

COMBUSTION INITIATION BY ELECTRICAL-DISCHARGE-INDUCED PLASMA IN LEAN AND DILUTE METHANE-AIR MIXTURE: EXPERIMENTAL AND MODELING INVESTIGATION

This dissertation represents experimental and numerical investigations of combustion initiation trigged by electrical-discharge-induced plasma within lean and dilute methane air mixture. This research topic is of interest due to its potential to further promote the understanding and prediction of spark ignition quality in high efficiency gasoline engines, which operate with lean and dilute fuel-air mixture. It is specified in this dissertation that the plasma to flame transition is the key process during the spark ignition event, yet it is also the most complicated and least understood procedure. Therefore the investigation is focused on the overlapped periods when plasma and flame both exists in the system. Experimental study is divided into two parts. Experiments in Part I focuses on the flame kernel resulting from the electrical discharge. A number of external factors are found to affect the growth of the flame kernel, resulting in complex correlations between discharge and flame kernel. Heat loss from the flame kernel to code ambient is found to be a dominant factor that quenches the flame kernel. Another experimental focus is on the plasma channel. Electrical discharges into gases induce intense and highly transient plasma. Detailed observation of the size and contents of the discharge-induced plasma channel is performed. Given the complex correlation and the multi-discipline physical/chemical processes involved in the plasma-flame transition, the modeling principle is taken to reproduce detailed transitions numerically with minimum analytical assumptions. Detailed measurement obtained from experimental work facilitates the more accurate description of initial reaction conditions. The novel and unique spark source considering both energy and species deposition is defined in a justified manner, which is the key feature of this Ignition by Plasma (IBP) model. The results of numerical simulation are intuitive and the potential of numerical simulation to better resolve the complex spark ignition mechanism is presented. Meanwhile, imperfections of the IBP model and numerical simulation have been specified and will address future attentions.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Age modeling of young non-varved lake sediments: methods and limits. Examples from two lakes in Central Chile

High-resolution and highly precise age models for recent lake sediments (last 100–150 years) are essential for quantitative paleoclimate research. These are particularly important for sedimentological and geochemical proxies, where transfer functions cannot be established and calibration must be based upon the relation of sedimentary records to instrumental data. High-precision dating for the calibration period is most critical as it determines directly the quality of the calibration statistics. Here, as an example, we compare radionuclide age models obtained on two high-elevation glacial lakes in the Central Chilean Andes (Laguna Negra: 33°38′S/70°08′W, 2,680 m a.s.l. and Laguna El Ocho: 34°02′S/70°19′W, 3,250 m a.s.l.). We show the different numerical models that produce accurate age-depth chronologies based on 210Pb profiles, and we explain how to obtain reduced age-error bars at the bottom part of the profiles, i.e., typically around the end of the 19th century. In order to constrain the age models, we propose a method with five steps: (i) sampling at irregularly-spaced intervals for 226Ra, 210Pb and 137Cs depending on the stratigraphy and microfacies, (ii) a systematic comparison of numerical models for the calculation of 210Pb-based age models: constant flux constant sedimentation (CFCS), constant initial concentration (CIC), constant rate of supply (CRS) and sediment isotope tomography (SIT), (iii) numerical constraining of the CRS and SIT models with the 137Cs chronomarker of AD 1964 and, (iv) step-wise cross-validation with independent diagnostic environmental stratigraphic markers of known age (e.g., volcanic ash layer, historical flood and earthquakes). In both examples, we also use airborne pollutants such as spheroidal carbonaceous particles (reflecting the history of fossil fuel emissions), excess atmospheric Cu deposition (reflecting the production history of a large local Cu mine), and turbidites related to historical earthquakes. Our results show that the SIT model constrained with the 137Cs AD 1964 peak performs best over the entire chronological profile (last 100–150 years) and yields the smallest standard deviations for the sediment ages. Such precision is critical for the calibration statistics, and ultimately, for the quality of the quantitative paleoclimate reconstruction. The systematic comparison of CRS and SIT models also helps to validate the robustness of the chronologies in different sections of the profile. Although surprisingly poorly known and under-explored in paleolimnological research, the SIT model has a great potential in paleoclimatological reconstructions based on lake sediments

Numerical solution of optimal control problems with constant control delays

We investigate a class of optimal control problems that exhibit constant exogenously given delays in the control in the equation of motion of the differential states. Therefore, we formulate an exemplary optimal control problem with one stock and one control variable and review some analytic properties of an optimal solution. However, analytical considerations are quite limited in case of delayed optimal control problems. In order to overcome these limits, we reformulate the problem and apply direct numerical methods to calculate approximate solutions that give a better understanding of this class of optimization problems. In particular, we present two possibilities to reformulate the delayed optimal control problem into an instantaneous optimal control problem and show how these can be solved numerically with a stateof- the-art direct method by applying Bock’s direct multiple shooting algorithm. We further demonstrate the strength of our approach by two economic examples.

Modeling Responses of Diatom Productivity and Biogenic Silica Export to Iron Enrichment in the Equatorial Pacific Ocean

Using a three-dimensional physical-biogeochemical model, we have investigated the modeled responses of diatom productivity and biogenic silica export to iron enrichment in the equatorial Pacific, and compared the model simulation with in situ (IronEx II) iron fertilization results. In the eastern equatorial Pacific, an area of 540,000 km(2) was enhanced with iron by changing the photosynthetic efficiency and silicate and nitrogen uptake kinetics of phytoplankton in the model for a period of 20 days. The vertically integrated Chl a and primary production increased by about threefold 5 days after the start of the experiment, similar to that observed in the IronEx II experiment. Diatoms contribute to the initial increase of the total phytoplankton biomass, but decrease sharply after 10 days because of mesozooplankton grazing. The modeled surface nutrients (silicate and nitrate) and TCO(2) anomaly fields, obtained from the difference between the "iron addition'' and "ambient'' (without iron) concentrations, also agreed well with the IronEx II observations. The enriched patch is tracked with an inert tracer similar to the SF6 used in the IronEx II. The modeled depth-time distribution of sinking biogenic silica (BSi) indicates that it would take more than 30 days after iron injection to detect any significant BSi export out of the euphotic zone. Sensitivity studies were performed to establish the importance of fertilized patch size, duration of fertilization, and the role of mesozooplankton grazing. A larger size of the iron patch tends to produce a broader extent and longer-lasting phytoplankton blooms. Longer duration prolongs phytoplankton growth, but higher zooplankton grazing pressure prevents significant phytoplankton biomass accumulation. With the same treatment of iron fertilization in the model, lowering mesozooplankton grazing rate generates much stronger diatom bloom, but it is terminated by Si(OH)(4) limitation after the initial rapid increase. Increasing mesozooplankton grazing rate, the diatom increase due to iron addition stays at minimum level, but small phytoplankton tend to increase. The numerical model experiments demonstrate the value of ecosystem modeling for evaluating the detailed interaction between biogeochemical cycle and iron fertilization in the equatorial Pacific.

Modeling of ore-forming and geoenvironmental systems: Roles of fluid flow and chemical reaction processes

Ore-forming and geoenviromental systems commonly involve coupled fluid flowand chemical reaction processes. The advanced numerical methods and computational modeling have become indispensable tools for simulating such processes in recent years. This enables many hitherto unsolvable geoscience problems to be addressed using numerical methods and computational modeling approaches. For example, computational modeling has been successfully used to solve ore-forming and mine site contamination/remediation problems, in which fluid flow and geochemical processes play important roles in the controlling dynamic mechanisms. The main purpose of this paper is to present a generalized overview of: (1) the various classes and models associated with fluid flow/chemically reacting systems in order to highlight possible opportunities and developments for the future; (2) some more general issues that need attention in the development of computational models and codes for simulating ore-forming and geoenviromental systems; (3) the related progresses achieved on the geochemical modeling over the past 50 years or so; (4) the general methodology for modeling of oreforming and geoenvironmental systems; and (5) the future development directions associated with modeling of ore-forming and geoenviromental systems.

Experimental, theoretical and numerical investigation of the nonlinear micromechanical properties of bone

Aging societies suffer from an increasing incidence of bone fractures. Bone strength depends on the amount of mineral measured by clinical densitometry, but also on the micromechanical properties of the bone hierarchical organization. A good understanding has been reached for elastic properties on several length scales, but up to now there is a lack of reliable postyield data on the lower length scales. In order to be able to describe the behavior of bone at the microscale, an anisotropic elastic-viscoplastic damage model was developed using an eccentric generalized Hill criterion and nonlinear isotropic hardening. The model was implemented as a user subroutine in Abaqus and verified using single element tests. A FE simulation of microindentation in lamellar bone was finally performed show-ing that the new constitutive model can capture the main characteristics of the indentation response of bone. As the generalized Hill criterion is limited to elliptical and cylindrical yield surfaces and the correct shape for bone is not known, a new yield surface was developed that takes any convex quadratic shape. The main advantage is that in the case of material identification the shape of the yield surface does not have to be anticipated but a minimization results in the optimal shape among all convex quadrics. The generality of the formulation was demonstrated by showing its degeneration to classical yield surfaces. Also, existing yield criteria for bone at multiple length scales were converted to the quadric formulation. Then, a computational study to determine the influence of yield surface shape and damage on the in-dentation response of bone using spherical and conical tips was performed. The constitutive model was adapted to the quadric criterion and yield surface shape and critical damage were varied. They were shown to have a major impact on the indentation curves. Their influence on indentation modulus, hardness, their ratio as well as the elastic to total work ratio were found to be very well described by multilinear regressions for both tip shapes. For conical tips, indentation depth was not a significant fac-tor, while for spherical tips damage was insignificant. All inverse methods based on microindentation suffer from a lack of uniqueness of the found material properties in the case of nonlinear material behavior. Therefore, monotonic and cyclic micropillar com-pression tests in a scanning electron microscope allowing a straightforward interpretation comple-mented by microindentation and macroscopic uniaxial compression tests were performed on dry ovine bone to identify modulus, yield stress, plastic deformation, damage accumulation and failure mecha-nisms. While the elastic properties were highly consistent, the postyield deformation and failure mech-anisms differed between the two length scales. A majority of the micropillars showed a ductile behavior with strain hardening until failure by localization in a slip plane, while the macroscopic samples failed in a quasi-brittle fashion with microcracks coalescing into macroscopic failure surfaces. In agreement with a proposed rheological model, these experiments illustrate a transition from a ductile mechanical behavior of bone at the microscale to a quasi-brittle response driven by the growth of preexisting cracks along interfaces or in the vicinity of pores at the macroscale. Subsequently, a study was undertaken to quantify the topological variability of indentations in bone and examine its relationship with mechanical properties. Indentations were performed in dry human and ovine bone in axial and transverse directions and their topography measured by AFM. Statistical shape modeling of the residual imprint allowed to define a mean shape and describe the variability with 21 principal components related to imprint depth, surface curvature and roughness. The indentation profile of bone was highly consistent and free of any pile up. A few of the topological parameters, in particular depth, showed significant correlations to variations in mechanical properties, but the cor-relations were not very strong or consistent. We could thus verify that bone is rather homogeneous in its micromechanical properties and that indentation results are not strongly influenced by small de-viations from the ideal case. As the uniaxial properties measured by micropillar compression are in conflict with the current literature on bone indentation, another dissipative mechanism has to be present. The elastic-viscoplastic damage model was therefore extended to viscoelasticity. The viscoelastic properties were identified from macroscopic experiments, while the quasistatic postelastic properties were extracted from micropillar data. It was found that viscoelasticity governed by macroscale properties has very little influence on the indentation curve and results in a clear underestimation of the creep deformation. Adding viscoplasticity leads to increased creep, but hardness is still highly overestimated. It was possible to obtain a reasonable fit with experimental indentation curves for both Berkovich and spherical indenta-tion when abandoning the assumption of shear strength being governed by an isotropy condition. These results remain to be verified by independent tests probing the micromechanical strength prop-erties in tension and shear. In conclusion, in this thesis several tools were developed to describe the complex behavior of bone on the microscale and experiments were performed to identify its material properties. Micropillar com-pression highlighted a size effect in bone due to the presence of preexisting cracks and pores or inter-faces like cement lines. It was possible to get a reasonable fit between experimental indentation curves using different tips and simulations using the constitutive model and uniaxial properties measured by micropillar compression. Additional experimental work is necessary to identify the exact nature of the size effect and the mechanical role of interfaces in bone. Deciphering the micromechanical behavior of lamellar bone and its evolution with age, disease and treatment and its failure mechanisms on several length scales will help preventing fractures in the elderly in the future.

Monte Carlo modeling of polarized light propagation: Stokes vs Jones - Part I

This bipartite comparative study aims at inspecting the similarities and differences between the Jones and Stokes–Mueller formalisms when modeling polarized light propagation with numerical simulations of the Monte Carlo type. In this first part, we review the theoretical concepts that concern light propagation and detection with both pure and partially/totally unpolarized states. The latter case involving fluctuations, or “depolarizing effects,” is of special interest here: Jones and Stokes–Mueller are equally apt to model such effects and are expected to yield identical results. In a second, ensuing paper, empirical evidence is provided by means of numerical experiments, using both formalisms.

Resolving diffusion in clay minerals at different time scales: Combination of experimental and modeling approaches

Since no single experimental or modeling technique provides data that allow a description of transport processes in clays and clay minerals at all relevant scales, several complementary approaches have to be combined to understand and explain the interplay between transport relevant phenomena. In this paper molecular dynamics simulations (MD) were used to investigate the mobility of water in the interlayer of montmorillonite (Mt), and to estimate the influence of mineral surfaces and interlayer ions on the water diffusion. Random Walk (RW) simulations based on a simplified representation of pore space in Mt were used to estimate and understand the effect of the arrangement of Mt particles on the meso- to macroscopic diffusivity of water. These theoretical calculations were complemented with quasielastic neutron scattering (QENS) measurements of aqueous diffusion in Mt with two pseudo-layers of water performed at four significantly different energy resolutions (i.e. observation times). The size of the interlayer and the size of Mt particles are two characteristic dimensions which determine the time dependent behavior of water diffusion in Mt. MD simulations show that at very short time scales water dynamics has the characteristic features of an oscillatory motion in the cage formed by neighbors in the first coordination shell. At longer time scales, the interaction of water with the surface determines the water dynamics, and the effect of confinement on the overall water mobility within the interlayer becomes evident. At time scales corresponding to an average water displacement equivalent to the average size of Mt particles, the effects of tortuosity are observed in the meso- to macroscopic pore scale simulations. Consistent with the picture obtained in the simulations, the QENS data can be described using a (local) 3D diffusion at short observation times, whereas at sufficiently long observation times a 2D diffusive motion is clearly observed. The effects of tortuosity measured in macroscopic tracer diffusion experiments are in qualitative agreement with RW simulations. By using experimental data to calibrate molecular and mesoscopic theoretical models, a consistent description of water mobility in clay minerals from the molecular to the macroscopic scale can be achieved. In turn, simulations help in choosing optimal conditions for the experimental measurements and the data interpretation. (C) 2014 Elsevier B.V. All rights reserved.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

Comparison of 3D kinetic and hydrodynamic models to ROSINA-COPS measurements of the neutral coma of 67P/Churyumov-Gerasimenko

67P/Churyumov-Gerasimenko (67P) is a Jupiter-family comet and the object of investigation of the European Space Agency mission Rosetta. This report presents the first full 3D simulation results of 67P’s neutral gas coma. In this study we include results from a direct simulation Monte Carlo method, a hydrodynamic code, and a purely geometric calculation which computes the total illuminated surface area on the nucleus. All models include the triangulated 3D shape model of 67P as well as realistic illumination and shadowing conditions. The basic concept is the assumption that these illumination conditions on the nucleus are the main driver for the gas activity of the comet. As a consequence, the total production rate of 67P varies as a function of solar insolation. The best agreement between the model and the data is achieved when gas fluxes on the night side are in the range of 7% to 10% of the maximum flux, accounting for contributions from the most volatile components. To validate the output of our numerical simulations we compare the results of all three models to in situ gas number density measurements from the ROSINA COPS instrument. We are able to reproduce the overall features of these local neutral number density measurements of ROSINA COPS for the time period between early August 2014 and January 1 2015 with all three models. Some details in the measurements are not reproduced and warrant further investigation and refinement of the models. However, the overall assumption that illumination conditions on the nucleus are at least an important driver of the gas activity is validated by the models. According to our simulation results we find the total production rate of 67P to be constant between August and November 2014 with a value of about 1 × 10²⁶ molecules s⁻¹.