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

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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessing pore network heterogeneity across multiple scales to inform CO2 injection models

Geologic heterogeneity is a key feature that must be considered when translations of scaled data are performed. This paper presents the assessment of geologic heterogeneity using a multiscale workflow that includes image analysis-based methods coupled with well log analysis to provide data in which fractals and machine learning methods estimate the carbon dioxide (CO 2 ) storage resource potential of a reservoir. The heterogeneity of rock properties of the complex Bell Creek reservoir in Montana, USA, was explored at the pore scale (~nm to mm), core scale (~mm to m), and well scale (~cm to m). The data used in this study included advanced image analysis of micro-CT (computed tomography) images (pore scale), thin sections (pore scale), plugs and core images (core scale) and well logs (well scale). The micro-CT images were segmented using a U-net segmentation approach into objects of pores and grains. Further, the segmented images were reconstructed into subvolumes of different sizes. Physical properties (porosity and permeability) and fractal dimensions were calculated for the various subvolumes, and Lorenz coefficient (Lc) values, a single parameter to describe the degree of heterogeneity within a pay zone section, were calculated from thin-section images and well logs. Porosity and fractal dimension values were used to estimate the 188-µm threshold of representative elementary volume (REV) in this study. Both the Lc and fractal dimension values were found to be negatively correlated. When these two parameters are combined, it is possible to discern differences in the complex porous networks of the samples analyzed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study

Purpose: To develop an intratumor partitioning framework for identifying high-risk subregions from {sup 18}F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods and Materials: In this institutional review board–approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). Conclusion: We propose a robust intratumor partitioning method to identify clinically relevant, high-risk subregions in lung cancer. We envision that this approach will be applicable to identifying useful imaging biomarkers in many cancer types.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Spatial and temporal prediction of radiation dose rates near Fukushima Daiichi Nuclear Power Plant

In this paper, we have developed a methodology to estimate the spatiotemporal distribution of radiation air dose rates around the Fukushima Daiichi Nuclear Power Plant (FDNPP). In our exploratory data analysis, we found that (1) the temporal evolution of dose rates is composed of a log-linear decay trend and fluctuations of air dose rates that are spatially correlated among adjacent monitoring posts; and (2) the slope of the log-linear environmental decay trend can be represented as a function of the apparent initial dose rates, coordinate position, land-use type, and soil type. From these observations, we first estimated the log-linear decay trend at each location based on these predictors, using the random forest method. We then developed a modified Kalman filter coupled with a Gaussian process model to estimate the dose-rate time series at a given location and time. We applied this method to the Fukushima evacuation zone (as of March 2017), which included 17 monitoring post locations (with monitoring datasets collected between 2014 and 2018) and generated a time series of dose-rate maps. Our results show that this approach allows us to produce accurate spatial and temporal predictions of radiation dose-rate maps using limited spatiotemporal measurements.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Pasteurization of shell eggs using radio frequency heating

The USDA-FSIS estimates that pasteurization of all shell eggs in the U.S. would reduce the annual number of illnesses by more than 110,000. However, less than 3% of shell eggs are commercially pasteurized. One of the main reasons for this is that the commercial hot water process requires as much as 60 min to complete. In the present study, a radio frequency (RF) apparatus was constructed, and a two-step process was developed that uses RF energy and hot water, to pasteurize eggs in less than half the time. In order to select an appropriate RF generator, the impedance of shell eggs was measured in the frequency range of 10–70 MHz. The power density within the egg was modeled to prevent potential hotspots. Escherichia coli (ATCC 35218) was inoculated in the yolk to approximately 7.5 log CFU/ml. The combination process first heated the egg in 35.0 °C water for 3.5 min using 60 MHz RF energy. This resulted in the yolk being preferentially heated to 61 °C. Then, the egg was heated for an additional 20 min with 56.7 °C water. This two-step process reduced the population of E. coli by 6.5 log. The total time for the process was 23.5 min. By contrast, processing for 60 min was required to reduce the E. coli by 6.6 log using just hot water. The novel RF pasteurization process presented in this study was considerably faster than the existing commercial process. As a result, this should lead to an increase in the percentage of eggs being pasteurized, as well as a reduction of foodborne illnesses.

42 ENGINEERING↗
DOE OSTI2022

Multiscale petrophysical characterization and flow unit classification of the Minnelusa eolian sandstones

Integration of petrophysical and geological information is critical to simulation of subsurface carbon storage (GCS). In this sense, two depositional facies were identified from the core description and well-log interpretation, namely massive (MS) and cross-bedded (CB) facies groups. Additionally, pore-scale characteristics were studied by a combination of techniques, e.g. Nuclear Magnetic Resonance (NMR) and mercury intrusion capillary pressure (MICP). Scanning electron microscope (SEM) and petrographic analyses show that the pore structure is dominantly controlled by the depositional environment and dolomite cementation. NMR-T 2 distributions of MS and CB facies show triple and quadruple modes, respectively. In addition, MICP of high- and low-permeability MS facies samples, and their CB facies group mixtures were collected. The MS sample pore-throat size distribution is uni-modal, while the triple-modal characteristic of the mixtures indicates heterogeneous pore structures at the sub-core scale for CB facies. The reliably estimates of porosity and permeability for both facies groups via NMR techniques and the MLR (Multiple Linear Regression) approach demonstrate the applicability of these techniques to eolian sandstone. Moreover, irreducible water saturation via the T 2 -cutoff method correlates strongly with T 2LM instead of porosity. Finally, the rock quality index and flow zone indicator were calculated based on Combinable Magnetic Resonance (CMR) log interpretations. This provides direct connection to properties measured in the well. Four flow units were classified for both facies groups. Finally, results show that better reservoir quality with significant heterogeneities is observed in the CB facies. This study highlights the importance integrating multiscale petrophysical properties including facies, pore architecture and diagenesis analysis with core- to log-scale property characterization. The results herein validate our reservoir characterization and flow unit classification in eolian reservoirs.

58 GEOSCIENCES↗
DOE OSTI2016

A method to improve the sensitivity of neutron porosity measurement based on D-T source

Compensated porosity logging tool utilizing deuterium-tritium (D-T) source shows a lower sensitivity to the variation of formation porosity compared with that adopting Am-Be source. In order to improve the sensitivity, the factors of an infinite homogeneous formation influencing slowing-down length and the near to far counts ratio are analyzed in this paper. Then Monte Carlo simulation method is used to build well logging models to study the responses of a neutron porosity logging tool to hydrogen index and formation density. It shows that in addition to hydrogen index, the variation of the density also has a great impact on slowing-down length and the ratio which reduces the response sensitivity to porosity. A new model depicts the relationship between the count ratio and porosity is proposed. Finally, when the model is used to process the measured ratio, the ratio shows improved dynamic range and sensitivity to porosity compared with the values without processing.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

The crystal structure and electrical properties of K{sub 2}NiF{sub 4}-type (Ca{sub 2−x}Sm{sub x})MnO{sub 4}

Graphical abstract: The relationship between log ρ of K{sub 2}NiF{sub 4}-type (Ca{sub 2−x}Sm{sub x})MnO{sub 4} and 1000/T. - Highlights: • K{sub 2}NiF{sub 4}-type (Ca{sub 2−x}Sm{sub x})MnO{sub 4} was synthesized using a polymerized complex route. • The semiconductive samples had minimum values of ρ and E{sub a} at x = 0.1. • The log ρ–1/T curve of x = 0.3 consisted of two different lines at 315 K. • The 1/χ − T curve of x = 0.3 had a peak at 325 K. • These results indicated the presence of a charge-ordering transition at x = 0.3. - Abstract: K{sub 2}NiF{sub 4}-type (Ca{sub 2−x}Sm{sub x})MnO{sub 4} (0.02 ≤ x ≤ 0.3) was synthesized using a polymerized complex route. The crystal structure changed from tetragonal to orthorhombic at x = 0.3. A variation in the lattice parameters was explained by the Mn–O(2) distance, the Mn−O(2)−Mn angle, and the (Ca,Sm)–(Ca,Sm) distance. The samples were n-type semiconductors, and the minimum values of electrical resistivity (ρ) and an energy gap (E{sub g}) at x = 0.1 were accounted by electron transfer through an Mn−O(2)−Mn path and overlap between the Mnt{sub 2g} and Op{sub π} orbitals. In the sample (x = 0.3), the log ρ–1000/T curve consisted of two different lines that intersected at ca. 325 K, and a peak was observed at ca. 315 K in the magnetic susceptibility–temperature curve. These results indicated the presence of a charge-ordering (CO) transition at 315–325 K.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Secondary porosity prediction in complex carbonate reefs using 3D CT scan image analysis and machine learning

Development and preservation of carbonate porosity and permeability are critical to characterizing reservoirs. However, secondary porosity, such as vugs and fractures, are difficult to identify and require collection of expensive wireline tools or core sampling. Wireline logs and cores have traditionally been used to identify the presence of secondary porosity but fail to quantify the contribution to total reservoir porosity. Additionally, advanced wireline logs and core are not readily available for most wells. Dual energy CT scans were collected on whole core from the A-1 Carbonate and Brown Niagaran formations drawn from six wells in northern Michigan. 3D analysis techniques were applied to identify and isolate secondary porosity features. A series of machine learning and data analytics techniques were applied to the dataset to predict secondary porosity features on basic wireline logs. The predictive model successfully predicted secondary porosity with high confidence.

02 PETROLEUM↗
DOE OSTI2015

Oral prenylation inhibition with lonafarnib in chronic hepatitis D infection: a proof-of-concept randomised, double-blind, placebo-controlled phase 2A trial

Background: Therapies for chronic hepatitis delta virus (HDV) infection are unsatisfactory. Prenylation is essential for HDV and inhibition abrogates HDV production in experimental models. Here, in a proof-of-concept study, we aimed to assess the effect on HDV RNA levels, safety, and tolerability of the prenylation inhibitor lonafarnib in patients with chronic delta hepatitis. Methods: In this phase 2A double-blind, randomised, placebo-controlled study, patients aged 18 years or older with chronic HDV infection were randomly assigned (3:1 in group 1 and 2:1 in group 2) to receive lonafarnib 100 mg (group 1) or lonafarnib 200 mg (group 2) twice daily for 28 days with 6 months' follow-up. Participants were randomised by random-number tables blocked in groups of four without stratification. Both groups enrolled six treatment participants and two placebo participants. Group 1 placebo patients received open-label lonafarnib as group 2 participants. The primary therapeutic endpoint was a decrease in HDV RNA viral titre in serum and the primary safety endpoint was the ability to tolerate the drug at the prescribed dose for the full 4-week duration, defined as drug discontinuation due to intolerance or grade 3/4 adverse events. This trial is registered with ClinicalTrials.gov, number NCT01495585. Findings: Between Jan 19, 2012, and April 28, 2014, 14 patients were enrolled, of whom eight were assigned to group 1 and six were assigned to group 2. At day 28, compared with placebo, mean log HDV RNA declines from baseline were -0·73 log IU/mL in group 1 (95% CI 0·17–1·31; p=0·03) and -1·54 log IU/mL in group 2 (1·21–1·93; p<0·0001). Lonafarnib serum concentrations correlated with HDV RNA change (r 2 =0·78, p<0·0001). Model fits show that hepatitis B surface antigen (HBsAg) remained stable after a short pharmacological delay (0·75 days [SE 0·24]), lonafarnib effectiveness in blocking HDV production was greater in group 2 than in group 1 (0·952 [SE 0·06] vs 0·739 [0·05], p<0·001), and the HDV half-life was 1·62 days (0·07). There was no evidence of virological resistance. Adverse events were mainly mild to moderate with group 1 patients experiencing diarrhoea in three patients (50%) and nausea in two patients (33%) and in group 2 with all patients (100%) experiencing nausea, diarrhoea, abdominal bloating, and weight loss greater than 2 kg (mean of 4 kg). No treatment discontinuations occurred in any treatment groups. Interpretation: Treatment of chronic HDV with lonafarnib significantly reduces virus levels. The decline in virus levels significantly correlated with serum drug levels, providing further evidence for the efficacy of prenylation inhibition in chronic HDV.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗
DOE OSTI2019

Volatility and Viscosity Are Correlated in Terpene Secondary Organic Aerosol Formed in a Flow Reactor

Secondary organic aerosol (SOA) is a complex mixture of largely unspeciated compounds. Volatility and viscosity of the bulk organic aerosol influence new particle formation, processing, and lifetime in the atmosphere. Relationships between these properties are well-defined for pure compounds, but currently unavailable for bulk organic aerosol. In this survey study, we characterized SOA formed from a range of biogenic precursors and conditions in an oxidation flow reactor for volatility (thermodenuder), viscosity (dimer coagulation, isolation, and coalescence), and oxidation state (aerosol chemical speciation monitor). We find linear trends in log-linear and log-log plots of single-parameter representations of volatility and viscosity, with higher condensed phase fractions of extremely low and low volatility material associated with increased viscosity (R=0.69). Per this relationship, a 10% increase in the contribution of these fractions (i.e., lower volatility) results in an increase in viscosity of approximately 200%. The viscosity (at 30°C) of SOA fell between $6.2 × 10^5$ to $8.0 × 10^8$ Pa s, and thus in the semi-solid range. SOA oxidation state ranged from -1.0 and 0.1, and was weakly anti-correlated with volatility (but not viscosity). We found larger SOA mass loadings generally associated with increased volatility and decreased viscosity. Overall, the results of this preliminary study are consistent with “molecular corridor”-style frameworks employing molecular mass and volatility to estimate viscosity to bulk real-world SOA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Extension of structure-reactivity correlations for the hydrogen abstraction reaction by bromine atom and comparison to chlorine atom and hydroxyl radical

Recently we presented structure-reactivity correlations for the gas-phase ambient-temperature rate constants for hydrogen abstraction from sp 3 -hybridized carbon by chlorine atom and hydroxyl radical (Cl•/HO• + HCR 3 → HCl/HOH + •CR 3 ); the reaction enthalpy effect was represented by the independent variable Δ r H and the polar effect by the independent variables F and R, the Hammett constants for field/inductive and resonance effects. Both these reactions are predominantly exothermic and have early transition states. Here we present a parallel treatment for Br• whose reaction is significantly endothermic with a correspondingly late transition state. In spite of lower expectations because the available data base is less extensive and much more scattered and because long temperature extrapolations are often required, the resulting least-squares fit (log k 298,Br = –0.147 Δ r H –4.32 ΣF –4.28 ΣR –12.38 with r 2 = 0.92) was modestly successful and useful for initial predictions. The coefficient of Δ r H was ~4-fold greater, indicative of the change from an early to a late transition state; meanwhile the sizable coefficients of ΣF and ΣR indicate the persistence of the polar effect. Although the mean unsigned deviation of 0.79 log k 298 units is rather large, it must be considered in the context of a total span of over 15 log units in the data set. Lastly, the major outliers are briefly discussed.

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

Toward Quantitatively Accurate Calculation of the Redox-Associated Acid–Base and Ligand Binding Equilibria of Aquacobalamin

In redox processes in complex transition metal-containing species are often intimately associated with changes in ligand protonation states and metal coordination number. Moreover, a major challenge is therefore to develop consistent computational approaches for computing pH-dependent redox and ligand dissociation properties of organometallic species. Reduction of the Co center in the vitamin B12 derivative aquacobalamin can be accompanied by ligand dissociation, protonation, or both, making these properties difficult to compute accurately. We examine this challenge here by using density functional theory and continuum solvation to compute Co ligand binding equilibrium constants (Kon/off), pKas and reduction potentials for models of aquacobalamin in aqueous solution. We consider two models for cobalamin ligand coordination: the first follows the hexa, penta, tetra coordination scheme for Co III , Co II , and Co I species, respectively, and the second model features saturation of each vacant axial coordination site on Co II and Co I species with a single, explicit water molecule to maintain six directly interacting ligands or water molecules in each oxidation state. Comparing these two coordination schemes in combination with five dispersion-corrected density functionals, we find that the accuracy of the computed properties is largely independent of the scheme used, but including only a continuum representation of the solvent yields marginally better results than saturating the first solvation shell around Co throughout. PBE performs best, displaying balanced accuracy and superior performance overall, with RMS errors of 80 mV for seven reduction potentials, 2.0 log units for five pK a s and 2.3 log units for two log K on/off values for the aquacobalamin system. Furthermore, we find that the BP86 functional commonly used in corrinoid studies suffers from erratic behavior and inaccurate descriptions of Co axial ligand binding, leading to substantial errors in predicted pK a s and K on/off values. Finally, these findings demonstrate the effectiveness of the present approach for computing electrochemical and thermodynamic properties of a complex transition metal-containing cofactor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Quantum Chemical Approach for Calculating Stability Constants of Mercury Complexes

Stability constants are central to the multi-scale modeling of the thermodynamic speciation, cycling, and transport of mercury (Hg) and other contaminants in aquatic environments. However, for Hg, experimental values for many relevant complexes are not available, and for others can span ranges in excess of 10 log units. The missing data and large uncertainties mean there are significant knowledge gaps in predictions of thermodynamic speciation. As an alternative to experimental measurements, thermodynamic quantities can be calculated with quantum chemical methods. Among these, density functional theory (DFT) with a polarizable continuum solvent combines accuracy with practicability. In this paper, we present an accurate and quick approach in which we use DFT with continuum solvation to calculate stability constants of Hg complexes with inorganic and low molecular-weight organic ligands in aqueous solution. Specifically, we use the M06/[SDD]6-31+G(d,p) level of theory in combination with a modified version of the SMD solvent model in which the solute radii are re-optimized with a scaled solvent-accessible surface (sSAS) approach. For the set of 37 Hg complexes used for optimization, which contain environmentally relevant functional groups and have reliable experimental stability constants, we obtain a mean unsigned error of 1.4 log units. Testing the method on an independent set of 12 Hg complexes reproduces the experimental stability constants to a mean unsigned error of 1.6 log units. Finally, this approach is a substantial step toward generally applicable rapid stability constant derivation for a wide range of Hg complexes, including those present in dissolved organic matter.

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

Pairing in a dry Fermi sea

In the traditional Bardeen–Cooper–Schrieffer theory of superconductivity, the amplitude for the propagation of a pair of electrons with momentum k and -k has a log singularity as the temperature decreases. This so-called Cooper instability arises from the presence of an electron Fermi sea. It means that an attractive interaction, no matter how weak, will eventually lead to a pairing instability. However, in the pseudogap regime of the cuprate superconductors, where parts of the Fermi surface are destroyed, this log singularity is suppressed, raising the question of how pairing occurs in the absence of a Fermi sea. In this paper, we report Hubbard model numerical results and the analysis of angular-resolved photoemission experiments on a cuprate superconductor. Finally, in contrast to the traditional theory, we find that in the pseudogap regime the pairing instability arises from an increase in the strength of the spin–fluctuation pairing interaction as the temperature decreases rather than the Cooper log instability.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Removal of Staphylococcus aureus from skin using a combination antibiofilm approach

Staphylococcus aureus (S. aureus) including methicillin resistant S. aureus (MRSA) is one of the primary microorganisms responsible for surgical site infection (SSI). Since S. aureus contamination is known to originate from the skin, eradicating it on the skin surface at surgical sites is an important intervention to reduce the chance of SSIs. Here we developed and evaluated the efficacy of a combination probiotic/brush sonication strategy for skin preparation at surgical, injection and insertion sites in medicine. A 24 h biofilm on porcine skin explants was used as a worst-case scenario for the evaluation of preparation strategies. Conventional ethanol wipes achieved 0.8~2 log reduction in viable bacteria depending on how many times wiped (x4 or x6). Brush sonication or probiotic supernatant pre-treatment alone achieved a similar reduction as ethanol wipes (1.4 and 0.7~1.4 log reduction, respectively). Notably, combining sonication and probiotic pre-treatment achieved a 4 log reduction in viable bacteria. In addition, probiotic supernatant incubation times as short as 2 h achieved the full effect of this reduction in the combined strategy. These findings suggest the promising potential of combination-format skin preparation strategies that can be developed to more effectively penetrate cracks and folds in the skin to remove biofilms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Extreme high temperature redox kinetics in ceria: exploration of the transition from gas-phase to material-kinetic limitations

The redox kinetics of undoped ceria (CeO 2-δ ) are investigated by the electrical conductivity relaxation method in the oxygen partial pressure range of -4.3 ≤ log(pO 2 /atm) ≤ -2.0 at 1400 °C. It is demonstrated that extremely large gas flow rates, relative to the mass of the oxide, are required in order to overcome gas phase limitations and access the material kinetic properties. Using these high flow rate conditions, the surface reaction rate constant k chem is found to obey the correlation log(k chem /cm s -1 ) = (0.84 ± 0.02) × log(pO 2 /atm) - (0.99 ± 0.05) and increases with oxygen partial pressure. This increase contrasts the known behavior of the dominant defect species, oxygen vacancies and free electrons, which decrease in concentration with increasing oxygen partial pressure. For the sample geometries employed, diffusion was too fast to be detected. At low gas flow rates, the relaxation process becomes limited by the capacity of the sweep gas to supply/remove oxygen to/from the oxide. An analytical expression is derived for the relaxation in the gas-phase limited regime, and the result reveals an exponential decay profile, identical in form to that known for a surface reaction limited process. Thus, measurements under varied gas flow rates are required to differentiate between surface reaction limited and gas flow limited behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantifying Distribution System Resilience From Utility Data: Large Event Risk and Benefits of Investments

We focus on blackouts in electric distribution systems that have a large cost to customers. To quantify resilience to these events, we show how to calculate risk metrics from the historical outage data routinely collected by utilities' outage management systems. Risk is defined using a customer cost exceedance curve. The exceedance curve has a heavy tail that implies large fluctuations in large blackout costs, and this makes estimating the mean large cost in the usual way impractical. To avoid this problem, we use new resilience metrics describing the large event risk; these metrics are the probability of a large cost event, the annual log cost resilience index, and the average of the logarithm of the cost of large-cost events or the slope magnitude of the tail on a log–log exceedance curve. Resilience can be improved by planned investments to upgrade system components or speed up restoration. The benefits that these investments would have had if they had been made in the past can be quantified by “rerunning history” with the effects of the investment included, and then recalculating the large event risk to find the improvement in resilience. An example using utility data shows a 2% reduction in the probability of a large cost event due to 10% wind hardening and 6%–7% reduction due to 10% faster restoration in two different areas of a distribution utility. This new data-driven approach to quantify resilience and resilience investments is realistic and much easier to apply than complicated approaches based on modeling all the phases of resilience. Moreover, an appeal to improvements to past lived experience may well be persuasive to customers and regulators in making the case for resilience investments.

24 POWER TRANSMISSION AND DISTRIBUTION↗