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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 487 records · Page 27

OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets: Preprint

Increasing levels of renewable generation motivate a growing interest in data-driven approaches for AC optimal power flow (AC OPF) to manage uncertainty. However, a lack of disciplined dataset creation and benchmarking prohibits useful comparison between approaches in the literature. To instigate confidence, models must be able to reliably predict solutions across a wide range of operating conditions. This paper develops the OPF-Learn package for Julia and Python which uses a computationally efficient approach to create representative datasets that span a wide spectrum of the AC OPF feasible region. Load profiles are uniformly sampled from a convex set that contains the AC OPF feasible set. For each infeasible point found, the convex set is reduced using infeasibility certificates, found by utilizing properties of a relaxed formulation. The framework is shown to generate datasets which are more representative of the entire feasible space versus traditional techniques seen in the literature, improving machine learning model performance.

dataset↗

Adaptive Conformer Sampling for Property Prediction Using the Conductor-like Screening Model for Real Solvents

The valorization of lignocellulose-derived bioproducts requires effective separation from excessive water. Liquid–liquid extraction is a promising low-energy separation technology, but effective extraction requires solvent selection based on the thermodynamic properties of the bioproduct and solvent components. We propose a computational framework for predicting such properties by developing an adaptive conformer selection approach for use with COSMO-RS (conductor-like screening model for real solvents) calculations. In this framework, molecular dynamics simulations are used to generate many molecular structures (conformers) at representative temperatures in varying solvent environments. Conformers are then clustered based on structural metrics in a low-dimensional space and selected using a mixed-integer quadratic programming problem to iteratively insert a sampled conformer. At each iteration, we determine bioproduct properties using COSMO-RS. Here, we demonstrate the capability of the proposed framework on representative bioproducts to show convergence of the adaptive sampling toward experimentally measured properties with fewer calculations than required by random conformer sampling, enabling the improved screening of solvent systems for liquid-phase separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimizing Sub-Sampled STEM Imaging for Beam Sensitive Materials and Dynamic Processes

The goal of this research is to quantify how sub-sampling and inpainting (broadly classified as methods in Artificial Intelligence) can be used to obtain the highest resolution images under any experimental conditions, and to use this to reproducibly control dynamic in-situ processes in gases and liquids on the nanoscale. As atomic diffusion under non-extreme conditions is typically in the sub-ms time domain, the ability to use this sub-sampling approach to reduce the effect of the electron beam and to speed-up the imaging process represents the optimum combination of spatial and temporal resolution achievable in a conventional microscope. This LDRD funding demonstrated the feasibility of imaging dynamics in complex energy systems using this methodology by establishing the optimum experimental sampling conditions (optimizing the number of pixels, speed, contrast and resolution) for each experiment. For in-situ liquid cell experiments this analysis shows that simply by distributing the same dose and dose rate maximally in space and time, the kinetics for radiolysis products can be modified significantly. The final stage of this work, i.e. the experimental demonstration of its use for nucleation and growth, was severely curtailed by issues with COVID19. However, all the experiments are designed and currently underway, with the goal to complete the final demonstration and publication as soon as safety concerns for laboratory access are met.

36 MATERIALS SCIENCE↗

A copula-based rank histogram ensemble filter

Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems. The univariate inference problems are solved by sampling posterior probability densities obtained by combining constructed prior densities with observational likelihoods according to Bayes' rule. Many serial filters in the literature focus on representing the marginal posterior densities of each state. However, rigorously capturing the conditional dependencies between the different univariate inferences is crucial to correctly sampling multidimensional posteriors. This work proposes a new serial ensemble filter, called the copula rank histogram filter (CoRHF), that seeks to capture the conditional dependency structure between variables via empirical copula estimates; these estimates are used to rigorously implement the triangular (state-by-state univariate) Bayesian inference. The success of the CoRHF is demonstrated on two-dimensional examples and the Lorenz'63 problem. A practical extension to the high-dimensional setting is developed by localizing the empirical copula estimation, and is demonstrated on the Lorenz'96 problem.

97 MATHEMATICS AND COMPUTING↗

BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a powerful label-free biological imaging technique, but the raw signal requires careful processing. The vibrationally resonant (Raman) fingerprint signal is usually small compared with instrumental noise sources and the nonresonant background (NRB) inherent in the BCARS signal. Fortunately, the NRB exhibits a systematic phase relationship with the coherent Raman response, acting as a heterodyne amplifier for the weak fingerprint signal. Due to this heterodyne effect, the Raman response can be recovered quantitatively and invariantly across different instruments, provided the NRB shape is known. Even with heterodyne amplification, the amplitudes of fingerprint signal components are often comparable to system noise. Singular value decomposition (SVD), which utilizes spatial information, is often employed for additional noise filtering. Consequently, finding optimal processing parameters to properly distinguish the NRB and Raman responses and suppress noise in the complex BCARS signal requires a reference system that realistically represents the spectral and spatial properties of BCARS signals obtained from biological samples. We present a digital tissue phantom that meets these criteria as a tool for testing candidate signal processing pipelines. The digital phantom is generated with simulated hyperspectral Raman images having system-specific noise and background characteristics. Here, we analyze phantom datasets with differing background and signal-to-noise conditions to evaluate their impact on the performance of multiple signal processing pipelines. Specifically, we investigate the application of a Butterworth filter-based routine to directly estimate the NRB from the BCARS signal. Additionally, we evaluate a Lorentzian wavelet transform as an alternative to the Hilbert transform for extracting the Raman spectrum from the BCARS signal. While we demonstrate this phantom for BCARS, it can be used for any spectroscopic Raman imaging approach.

Dixon, Jessica Z. [Georgia Institute of Technology↗

High resolution variability in wet deposition in the southeastern United States

Rainwater chemistry is determined by atmospheric pollutants and particles which vary spatially and temporally. Industrial and agricultural activities and meteorological events (e.g. sea breezes, severe weather, blowing dust) alter atmospheric particle and trace gas compositions. These gases and particles are scavenged by cloud and rain droplets that drive wet deposition. During an Intensive Operation Period (IOP) from April to October 2021, rainwater was collected at higher frequency intervals, usually daily, after precipitation events at three locations on the Savannah River Site (SRS). The farthest locations were separated by approximately 20 km. The mean concentration (μeq/L) of seven ions followed the Cl⁻ > SO 4 2− > Na⁺ > NO 3 ⁻ > K⁺ > Mg 2+ > Ca 2+ downward trend. Ion concentrations were compared to background ion concentrations from the National Atmospheric Deposition Program (NADP). The high frequency monthly averaged SRS data compared well with the monthly averaged NADP background but demonstrated extensive variability. In some months in 2021, the high frequency data compared better to the NADP site near the coast while in other months inland sites compared better. Strong spatial variability for ion concentrations was observed across SRS which was attributed to localized impacts in rainfall spatial variability. High frequency measurements allowed for comparison to regional weather patterns indicating influences from the Atlantic Ocean, Gulf of Mexico, and cities. This can account for spatial variability in the wet deposition flux. Sea breezes, Saharan dust, and anthropogenic sources were shown to impact wet deposition flux variability. Higher frequency precipitation chemistry sampling at numerous locations better captures ion concentration variability and improves measurement representativeness.

54 ENVIRONMENTAL SCIENCES↗

Probabilistic modeling approach for tracking each collision and breakup of computational parcels

A modeling approach for binary collision and particle breakup is presented for a stochastic particle model in which a computational parcel represents a number of similar physical particles. Presented in this report includes sampling from a distribution of discrete data, parcel number reduction, probabilistic calculation of collision rates, and various particle-particle interactions. Modeling of elastic scattering, coalescence and agglomeration, and breakup are discussed for solid-solid, solid-liquid, and liquid-liquid particle collisions. Numerical procedures are also summarized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Census of the Taurus Star-forming Region and Neighboring Associations with Gaia*

I have used high-precision photometry and astrometry from the third data release of Gaia to perform a survey for members of the Taurus star-forming region and young associations in its vicinity. This work has produced a new catalog of 532 adopted members of Taurus, which has only minor changes relative to the previous catalog from Esplin & Luhman. I have used the Gaia astrometry to divide the Taurus members into 13 groups that have distinct kinematics. Meanwhile, I have identified 1378 candidate members of seven associations near Taurus. All of these associations have histograms of spectral types that peak near M5 (~0.15 M ⊙ ), resembling other young populations in the solar neighborhood. For the Taurus groups and neighboring associations, I have estimated ages from their sequences of low-mass stars in Hertzsprung–Russell diagrams. Most of the Taurus groups have median ages of ~1–3 Myr, while the associations have ages ranging from 13 to 56 Myr. I have used mid-infrared photometry from the Wide-field Infrared Survey Explorer to search for excess emission from circumstellar disks among the candidate members of the associations. Disks are detected for 51 stars, 20 of which are reported for the first time in this work. Some recent studies have proposed that samples of older stars (≳10 Myr) found in the vicinity of Taurus represent a distributed population that is associated with the Taurus cloud complex. However, I find that most of those stars have kinematics that are inconsistent with any relationship with Taurus.

79 ASTRONOMY AND ASTROPHYSICS↗

Baltimore Ecosystem Study: Soil atmosphere fluxes of carbon dioxide, nitrous oxide and methane, 1998 - ongoing

The Baltimore Ecosystem Study (BES) established a network of long-term permanent biogeochemical study plots in 1998. These plots provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The network of study plots includes forest plots (upland and riparian), chosen to represent the range of forest conditions in the area and grass plots (to represent home lawns). Plots are instrumented with lysimeters (drainage and tension) to sample soil solution chemistry, time domain reflectometry probes to measure soil moisture, dataloggers to measure and record soil temperature, and trace gas flux chambers to measure the flux of carbon dioxide, nitrous oxide and methane from soil to the atmosphere. Measurements of in situ nitrogen mineralization, nitrification and denitrification were made at approximately monthly intervals from Fall 1998 - Fall 2000. Detailed vegetation characterization (all layers) was done in summer 1998 and 2015. Data from these plots has been published in Groffman et al. (2006, 2009), Groffman and Pouyat (2009), Savva et al. (2010), Costa and Groffman (2013), Duncan et al. (2013), Waters et al. (2014), Ni and Groffman (2018), Templeton et al. (2019). Literature Cited Costa, K.H. and P.M. Groffman. 2013. Factors regulating net methane flux in urban forests and grasslands. Soil Science Society of America Journal 77:850 - 855. Duncan, J. M., L. E. Band, and P. M. Groffman. 2013. Towards closing the watershed nitrogen budget: Spatial and temporal scaling of denitrification. Journal of Geophysical Research Biogeosciences 118:1-5; DOI: 10.1002/jgrg.20090 Groffman PM, Pouyat RV, Cadenasso ML, Zipperer WC, Szlavecz K, Yesilonis IC,. Band LE and Brush GS. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Groffman, P.M., C.O. Williams, R.V. Pouyat, L.E. Band and I.C. Yesilonis. 2009. Nitrate leaching and nitrous oxide flux in urban forests and grasslands. Journal of Environmental Quality 38:1848-1860. Groffman, P.M. and R.V. Pouyat. 2009. Methane uptake in urban forests and lawns. Environmental Science and Technology 43:5229-5235. DOI: 10.1021/es803720h. Ni, X. and P.M. Groffman. 2018. Declines in methane uptake in forest soils. Proceedings of the National Academies of Science of the United States of America 115:8587-8590. Savva, Y., K. Szlavecz, R. V. Pouyat, P. M. Groffman, and G. Heisler. 2010. Effects of land use and vegetation cover on soil temperature in an urban ecosystem. Soil Science Society of America Journal 74:469-480. Templeton, L., M.L. Cadenasso, J. Sullivan, M. Neel and P.M. Groffman. 2019. Changes in vegetation structure and composition of urban and rural forest patches in Baltimore from 1998 to 2015. Forest Ecology and Management. In press. Waters, E.R., J.L. Morse, N.D. Bettez and P.M. Groffman. 2014. Differential carbon and nitrogen controls of denitrification in riparian zones and streams along an urban to exurban gradient. Journal of Environmental Quality 43:955–963.

Groffman, Peter M↗

Predeployment progress of the Canister Deposition Field Demonstration

This report updates the high-level test plan for evaluating surface deposition on three commercial 32PTH2 spent nuclear fuel (SNF) canisters inside NUTECH Horizontal Modular Storage (NUHOMS) Advanced Horizontal Storage Modules (AHSMs) from Orano (formerly Transnuclear Inc.) and provides a summary of the surface sampling activities that have been conducted to date. The details contained in this report represent the best designs and approaches explored for testing as of this publication. Given the rapidly developing nature of this test program, some of these plans may change to accommodate new objectives or requirements. One goal of this testing is to collect defensible and detailed dust deposition measurements from the surface of dry storage canisters in a marine coastal environment to guide chloride-induced stress corrosion cracking (CISCC) research. Another goal is to provide data for the validation of computational fluid dynamics (CFD) based deposition modeling. To facilitate surface sampling, the otherwise highly prototypic dry storage systems will not contain SNF but rather will be electrically heated to mimic the decay heat and thermal hydraulic environment. Test and heater design is supported by detailed CFD modeling. Instrumentation throughout the canister, storage module, and environment will provide extensive information about the thermal-hydraulic behavior of horizontal dry cask storage systems. Manual sampling over a comprehensive portion of the canister surface at regular time intervals will offer detailed quantification and composition of the deposited particulates from a realistic storage environment. Discussions of a potential host site for the Canister Deposition Field Demonstration (CDFD) are ongoing. Until a host site is chosen, testing of key CDFD hardware components including the heater assemblies, power skid, and remote data acquisition system will continue. Functional testing of the finalized heater assemblies and test apparatus started this fiscal year. These initial heater tests have shown the assemblies are performing within design specifications. Staged surface sampling of a mockup of a canister outside the AHSM on a transfer skid was also performed. Refinements to the sampling procedures and techniques were captured from observation of these activities and lessons-learned debriefs. These updated sampling procedures and techniques are planned to be tested again in the field using the mockup in order to assure personnel are using the most accurate and repeatable methods possible prior to deployment for actual CDFD testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Colloidal Three-Dimensional Covalent Organic Frameworks and Their Application as Porous Liquids

Developing solid porous materials into free-flowing liquids with permanent porosity is a promising strategy for overcoming certain limitations of conventional sorbent materials employed in gas storage and separation applications. The ability to control the pore size and chemical functionalities of organic frameworks gives these particular nanoporous materials distinct advantages over other small cage-like molecules or hollow particles that have been developed into porous liquids. Here, we describe the synthesis of a 3D imine-linked colloidal covalent organic framework (COF)-based porous liquid, designed for efficient size-exclusion of solvent, as well as for long-term stability. By tethering ionic liquids to the colloid surface, the colloids can be dried, purified, and resuspended in a variety of solvents without irreversible aggregation typically observed of COF colloids. Colloid size could be controlled between 50 and 400 nm, with surface areas as high as 800 m2/g. The 3D intertwining morphology of the colloids had pore sizes ranging from 5 to 14 Å, allowing them to efficiently sizeexclude bulky ionic liquids. The COF colloids were stable towards flocculation in an ionic liquid for > 1 year. Permanent porosity was confirmed with a combination of 19F NMR measurements and gas sorption techniques. CO2 and CH4 uptake in these porous liquids increased more than 10 and 20-fold, respectively, over non-porous, neat ionic liquid control samples. The work not only advances the state of COF-based colloid science but also represents a practical advance towards developing more robust, tunable framework-based porous liquid materials for a host of gas storage and separation applications.

Mow, Rachel E.↗

Towards validation of combined-accelerated stress testing through failure analysis of polyamide-based photovoltaic backsheets

Abstract Novel methods for advancing reliability testing of photovoltaic (PV) modules and materials have recently been developed. Combined-accelerated stress testing (C-AST) is one such method which has demonstrated reliable reproduction of some field-failures which were not reproducible by standard certification tests. To increase confidence and assist in the development of C-AST, and other new testing protocols, it is important to validate that the failure modes observed and mechanisms induced are representative of those observed in the field, and not the product of unrealistic stress conditions. Here we outline a method using appropriate materials characterization and modelling to validate the failure mechanisms induced in C-AST such that we can increase confidence in the test protocol. The method is demonstrated by applying it to a known cracking failure of a specific polyamide (PA)-based backsheet material. We found that the failure of the PA-based backsheet was a result of a combination of stress factors. Photo-oxidation from ultra-violet (UV) radiation exposure caused a reduction in fracture toughness, which ultimately lead to the cracking failure. We show that the chemical and structural changes observed in the backsheet following C-AST aging were also observed in field-aged samples. These results increase confidence that the conditions applied in C-AST are representative of the field and demonstrates our approach to validating the failure mechanisms induced.

14 SOLAR ENERGY↗

Quasi-In-Situ Analysis of Electrode Top Atomic Layers via High-Sensitivity Low-Energy Ion Scattering and Potential-Controlled Sample Transfer

Electrocatalytic reactions involve interfacial interactions between the surfaces of electrodes and reactive species at an electrolyte interface. There are presently no universal or unambiguous methods to directly assay the active top atomic layer composition that influences the reactivity of these electrodes under relevant operating conditions. Low-energy ion scattering (LEIS) spectroscopy is a surface characterization technique that yields compositional analysis of the outermost atomic layer of a material, but it must be performed in ultrahigh vacuum (UHV). Application of LEIS measurements to electrochemical materials that are removed from ambient liquid-phase environments thus leaves an open question as to whether the surface that is transferred to UHV is truly the surface that manifested during the electrochemical reaction. Toward the goal of preserving the active surface state, we developed a sample transfer workflow for LEIS enabling air-free removal and drying of an electrode from an electrochemical cell while maintaining control of the potential using an auxiliary electrode. The potential-controlled emersion method was demonstrated to give distinct potential-dependent surface compositions for a Cu−Pd alloy relative to removal after uncontrolled return to open-circuit potential. A Cu-enriched surface was found at anodic potential and a Pd-enriched surface at cathodic potential, suggesting that the approach can be used to retain representative atomic configurations during transfer. Since adsorbates will often persist from the reaction environment, conventional sample pretreatment methods for removal, including atomic O and atomic H exposure, were also contrasted. Both methods were found to differ with results from incidental low-dose depth profiling by the LEIS primary ion source, which removes adventitious species and surface atoms during the course of repeated measurements. These depth profiles were found to be sensitive to sample history and thus qualitatively informative, despite the possible changes induced by ion damage. The results exhibit (i) the need for complete control over the polarization state of the sample at all times (no excursions to open circuit during transfer) and (ii) the utility of low-dose depth profiling to capture changes in the near-surface composition.

Alloys↗

The Atacama Cosmology Telescope: Weighing Distant Clusters with the Most Ancient Light

We use gravitational lensing of the cosmic microwave background (CMB) to measure the mass of the most distant blindly selected sample of galaxy clusters on which a lensing measurement has been performed to date. In CMB data from the the Atacama Cosmology Telescope and the Planck satellite, we detect the stacked lensing effect from 677 near-infrared-selected galaxy clusters from the Massive and Distant Clusters of WISE Survey (MaDCoWS), which have a mean redshift of $\langle z\rangle =1.08$. There are currently no representative optical weak lensing measurements of clusters that match the distance and average mass of this sample. We detect the lensing signal with a significance of $4.2\sigma $. We model the signal with a halo model framework to find the mean mass of the population from which these clusters are drawn. Assuming that the clusters follow Navarro–Frenk–White (NFW) density profiles, we infer a mean mass of $\langle {M}_{500c}\rangle =\left(1.7\pm 0.4\right)\times {10}^{14}\,{M}_{\odot }$. We consider systematic uncertainties from cluster redshift errors, centering errors, and the shape of the NFW profile. These are all smaller than 30% of our reported uncertainty. This work highlights the potential of CMB lensing to enable cosmological constraints from the abundance of distant clusters populating ever larger volumes of the observable universe, beyond the capabilities of optical weak lensing measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Mosquito Distribution and West Nile Virus Surveillance Results on the Nevada National Security Site in South Central Nevada

A 10-year study (2004-2013) was conducted to determine mosquito distribution and the prevalence of West Nile Virus (WNV) on the Nevada National Security Site (NNSS) in south central Nevada. Mosquito traps baited with dry ice were set overnight at sites where standing water provided potential breeding sites for mosquitoes. Captured mosquitoes were identified to species and tested for WNV. A total of 556 mosquitoes representing 6 species were captured and identified at 20 sites around the NNSS during 124 surveys. A vast majority (89%) of mosquitoes were Culex tarsalis. None of the mosquitoes tested were positive for WNV although 2 samples, both Culiseta inornata, were suspect for WNV in 2005 and 2006, both from Well 3 Pond. Additionally, 24 birds representing 5 species were opportunistically collected and tested for WNV with no positive results. Results from this study reveal patterns of mosquito distribution across the NNSS and suggest that NNSS workers have a very low risk of being exposed to WNV.

60 APPLIED LIFE SCIENCES↗

Metagenomic Methods for Addressing NASA's Planetary Protection Policy Requirements on Future Missions: A Workshop Report

Molecular biology methods and technologies have advanced substantially over the past decade. These new molecular methods should be incorporated among the standard tools of planetary protection (PP) and could be validated for incorporation by 2026. To address the feasibility of applying modern molecular techniques to such an application, NASA conducted a technology workshop with private industry partners, academics, and government agency stakeholders, along with NASA staff and contractors. The technical discussions and presentations of the Multi-Mission Metagenomics Technology Development Workshop focused on modernizing and supplementing the current PP assays. The goals of the workshop were to assess the state of metagenomics and other advanced molecular techniques in the context of providing a validated framework to supplement the bacterial endospore-based NASA Standard Assay and to identify knowledge and technology gaps. In particular, workshop participants were tasked with discussing metagenomics as a stand-alone technology to provide rapid and comprehensive analysis of total nucleic acids and viable microorganisms on spacecraft surfaces, thereby allowing for the development of tailored and cost-effective microbial reduction plans for each hardware item on a spacecraft. Workshop participants recommended metagenomics approaches as the only data source that can adequately feed into quantitative microbial risk assessment models for evaluating the risk of forward (exploring extraterrestrial planet) and back (Earth harmful biological) contamination. Participants were unanimous that a metagenomics workflow, in tandem with rapid targeted quantitative (digital) PCR, represents a revolutionary advance over existing methods for the assessment of microbial bioburden on spacecraft surfaces. The workshop highlighted low biomass sampling, reagent contamination, and inconsistent bioinformatics data analysis as key areas for technology development. Finally, it was concluded that implementing metagenomics as an additional workflow for addressing concerns of NASA's robotic mission will represent a dramatic improvement in technology advancement for PP and will benefit future missions where mission success is affected by backward and forward contamination.

59 BASIC BIOLOGICAL SCIENCES↗

A statistical and simulation-informed model for estimating permeability from pore size distribution in saturated geomaterials

Accurate permeability estimation is essential across subsurface engineering applications but remains challenging due to the complex pore structures of natural geomaterials. Traditional empirical methods and simplified theoretical models often inadequately capture the role of pore size distribution and connectivity. Here, this study develops a statistical and simulation-informed permeability model that collapses pore-scale complexity into a compact scaling of the form k = αϕμ d 2 , where ϕ is porosity, μ d is mean pore size, and α is a weakly varying coefficient. By combining pore network simulations with statistical analysis of unimodal and bimodal pore size distributions, we identify three key findings: (i) permeability is much more sensitive to mean pore size than to porosity; (ii) across extensive datasets, the ratio σ d /μ d (standard deviation to mean) clusters around a characteristic value ∼0.4, allowing the effects of the full pore size distribution to be represented by μ d and a narrowly varying α ≈ 0.05; and (iii) for bimodal systems, there exists a critical fraction of small pores ∼0.78 above which flow becomes small-pore dominated, enabling the definition of an effective flow-controlling pore population and facilitating simplified permeability estimation for such systems. The resulting model, which requires only porosity and a representative mean pore size as inputs, is validated against comprehensive experimental datasets (>1700 samples) spanning diverse soils and rocks and achieves good predictive accuracy. Overall, this work provides a physically grounded yet practically simple permeability estimator suitable for subsurface engineering, environmental protection, and resource management applications.

Permeability↗

Oil price states and drivers: An analysis of the second-month spot-futures price differential

Oil remains a dominant component of global energy use, and its price, characterized by frequent changes and an ever-present potential for large swings, continues to be a focus of industry participants, policymakers and analysts attention. Here, this study examines the behavior of future spot oil prices using a continuous-time hidden Markov model (HMM) and daily price data spanning years 2007 to 2024. We identify six states in the second-month WTI spot-futures price differential and assess the roles of eleven futures price, quantity, financial market, and geopolitical/volatility variables in each state. The model yields several insights into the workings of the oil market and the relative roles of these drivers. We find support for several theoretical and empirical findings in the oil market literature, including the role of inventory, volatility/risk, and market responses to contango/backwardation in futures markets. A novel finding is that “normal contango” conditions represent a significant portion of next-day states in our in-sample data. Under the most volatile normal contango state, many of the oil market drivers differ markedly in coefficient signs and magnitudes from those in other states. The resulting model also performed well out-of-sample and would, in addition to understanding the impact of market drivers, be useful for short-term forecasting. Overall, the findings highlight the highly non-linear, regime-dependent interactions of the oil price and its drivers, emphasizing the importance of detailed information to market stakeholders.

Oladosu, Gbadebo A. [Oak Ridge National Laboratory↗