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Results for “variability analysis”

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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Spectral indices of cardiovascular adaptations to short-term simulated microgravity exposure

We investigated the effects of exposure to microgravity on the baseline autonomic balance in cardiovascular regulation using spectral analysis of cardiovascular variables measured during supine rest. Heart rate, arterial pressure, radial flow, thoracic fluid impedance and central venous pressure were recorded from nine volunteers before and after simulated microgravity, produced by 20 hours of 6 degrees head down bedrest plus furosemide. Spectral powers increased after simulated microgravity in the low frequency region (centered at about 0.03 Hz) in arterial pressure, heart rate and radial flow, and decreased in the respiratory frequency region (centered at about 0.25 Hz) in heart rate. Reduced heart rate power in the respiratory frequency region indicates reduced parasympathetic influence on the heart. A concurrent increase in the low frequency power in arterial pressure, heart rate, and radial flow indicates increased sympathetic influence. These results suggest that the baseline autonomic balance in cardiovascular regulation is shifted towards increased sympathetic and decreased parasympathetic influence after exposure to short-term simulated microgravity.

NASA Discipline Cardiopulmonary↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS2012

Miniature Variable Pressure Scanning Electron Microscope for In-Situ Imaging and Chemical Analysis

NASA Marshall Space Flight Center (MSFC) is leading an effort to develop a Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) for in-situ imaging and chemical analysis of uncoated samples. This instrument development will be geared towards operation on Mars and builds on a previous MSFC design of a mini-SEM for the moon (funded through the NASA Planetary Instrument Definition and Development Program). Because Mars has a dramatically different environment than the moon, modifications to the MSFC lunar mini-SEM are necessary. Mainly, the higher atmospheric pressure calls for the use of an electron gun that can operate at High Vacuum, rather than Ultra-High Vacuum. The presence of a CO2-rich atmosphere also allows for the incorporation of a variable pressure system that enables the in-situ analysis of nonconductive geological specimens. Preliminary testing of Mars meteorites in a commercial Environmental SEM(Tradmark) (FEI) confirms the usefulness of lowcurrent/low-accelerating voltage imaging and highlights the advantages of using the Mars atmosphere for environmental imaging. The unique capabilities of the MVP-SEM make it an ideal tool for pursuing key scientific goals of NASA's Flagship Mission Max-C; to perform in-situ science and collect and cache samples in preparation for sample return from Mars.

Gaskin, Jessica A.↗
DOE OSTI2022

Sensitivity analysis of generic deep geologic repository with focus on spatial heterogeneity induced by stochastic fracture network generation

Geologic Disposal Safety Assessment Framework is a state-of-the-art simulation software toolkit for probabilistic post-closure performance assessment of systems for deep geologic disposal of nuclear waste developed by the United States Department of Energy. This paper presents a generic reference case and shows how it is being used to develop and demonstrate performance assessment methods within the Geologic Disposal Safety Assessment Framework that mitigate some of the challenges posed by high uncertainty and limited computational resources. Variance-based global sensitivity analysis is applied to assess the effects of spatial heterogeneity using graph-based summary measures for scalar and time-varying quantities of interest. Behavior of the system with respect to spatial heterogeneity is further investigated using ratios of water fluxes. This analysis shows that spatial heterogeneity is a dominant uncertainty in predictions of repository performance which can be identified in global sensitivity analysis using proxy variables derived from graph descriptions of discrete fracture networks. New quantities of interest defined using water fluxes proved useful for better understanding overall system behavior.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2021

Photocatalytic Transfer Hydrogenation in Water: Insight into Mechanism and Catalyst Speciation

Organometallic catalysts with strong metal-to-ligand charge-transfer (MLCT) optical transitions and reactive metal-hydride bonds provide opportunities for new excited-state reactivity. Toward this end, we have investigated photoinduced transfer hydrogenation reactions for a series of Cp*IrH complexes with functionalized bipyridyl ligands. Overcoming the baseline reactivity of this class of catalyst toward hydrogen evolution in aqueous media presents a major challenge for focusing this photochemical reactivity into desired transformations of more complex organic substrates. In this work, a photochemically induced aqueous ketone reduction catalyzed by [Cp*Ir(bpy)H][Cl] is reported and benchmarked to the competing hydrogen evolution reaction (HER). A detailed mechanistic study is conducted of the reduction of cyclohexanone with sodium formate delivering the reducing equivalent. Examining the kinetic profile of the cyclohexanone reduction revealed an unexpected induction period, suggesting a more complex underlying reaction mechanism where product selectivity was not simply a function of direct competition from a common excited-state reactive intermediate. The reaction kinetics were analyzed by variable time normalization analysis (VTNA), and the catalyst resting state was interrogated through operando light-emitting diode (LED) illumination H-1 NMR spectroscopy. Overall, these and other mechanistic studies provide insight into a photochemical reaction pathway to ketone reduction that is distinct from that previously reported for HER.

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

Mechanistic Insights into C–H Borylation of Arenes with Organoiridium Catalysts Embedded in a Microporous Metal–Organic Framework

Organometallic iridium catalysts can be used in conjunction with bispinacolatodiboron (B 2 Pin 2 ) to effect the borylation of a variety of substrates such as arenes, alkanes, heteroarenes, and oxygenates. Recently, efforts have also focused on integrating these catalysts into porous supports, such as metal–organic frameworks (MOFs). While the mechanism of homogeneous borylation systems has been thoroughly investigated experimentally and computationally, analogous studies in MOF-supported iridium catalysts have not been conducted. In this paper, we report the mechanistic investigation of a phenanthroline-iridium catalyst immobilized in the organic linker of Universitetet i Oslo (UiO)-67 (Zr 6 O 4 (OH) 4 (BPDC) 4 (PhenDC) 2 , BPDC = biphenyl-4,4'-dicarboxylate, PhenDC = 1,10-phenanthroline-4,4'-dicarboxylate). By using benzene as a model substrate, variable time normalization analysis (VTNA) of the kinetic data suggested a rate law consistent with zero-order in B 2 Pin 2 , and first-order in arene. A primary kinetic isotope effect (KIE) in the time course of benzene-d 6 borylation also provided complementary information about the role of the arene in the rate-determining step of the reaction. Characterization by techniques such as X-ray absorption spectroscopy (XAS) confirmed the presence of Ir(III), while pair distribution function (PDF) analysis suggested structures containing an Ir–Cl bond, further substantiated by X-ray photoelectron spectroscopy (XPS). Analysis of postcatalysis materials by inductively coupled plasma–optical emission spectroscopy (ICP-OES) revealed low boron accumulation, which may indicate an absence of boron in the resting state of the catalyst. Finally, in comparing borylation of benzene and toluene, a slight selectivity for benzene is observed, which is similar to the analogous homogeneous reaction, indicating the influence of substrate sterics on reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Leveraging Intramolecular π-Stacking to Access an Exceptionally Long-Lived 3 MC Excited State in an Fe(II) Carbene Complex

The ability to manipulate excited-state decay cascades using molecular structure is essential to the application of abundant-metal photosensitizers and chromophores. Ligand design has yielded some spectacular results elongating charge-transfer excited state lifetimes of Fe(II) coordination complexes, but triplet metal-centered ( 3 MC) excited states - recently demonstrated to be critical to the photoactivity of isoelectronic Co(III) polypyridyls - have to date remained elusive, with temporally isolable examples limited to the picosecond regime. Here, with this report, we show how strong-field donors and intramolecular π-stacking can conspire to stabilize a long-lived 3 MC excited state for a remarkable 4.1 ± 0.3 ns in fluid solution at ambient temperature. Analysis of variable-temperature time-resolved absorption data using theoretical models ranging from Arrhenius to semiclassical Marcus theory, combined with computational modeling and X-ray crystallography, reveal a Jahn−Teller stabilized excited state with a high activation barrier for ground-state recovery. The net result is a chromophore with a 3 MC excited-state lifetime that is orders of magnitude longer than anything yet observed for an Fe(II) complex.

carbene compounds↗
DOE OSTI2026

A High-Fidelity Molecular Model of the Cu(111) Repeating Unit

Dynamic processes at surfaces are central to heterogeneous catalysis, but their atomistic mechanism(s) can prove difficult to elucidate due to variations in material structure and the corresponding impact on reactivity. Moreover, disparities between reaction conditions and those employed for spectroscopic characterization at surfaces can inhibit detailed understanding of catalysis-relevant chemistries. Herein, we substantiate the so-called “cluster-surface” analogy by leveraging a low-valent tricopper architecture ( 1 ) as a model system for small molecule activation at Cu(111). Two reaction classes are explored: the adsorption of carbon monoxide (CO) and the dissociative adsorption of dihydrogen (H 2 ). These processes serve as an ideal testbed to compare the reactivity of a molecular cluster ( 1 ) to that of a heterogeneous surface, as both reactions have empirical data from measurements performed on crystalline Cu(111). Cluster 1 reversibly binds CO. Variable temperature NMR analysis with 13 CO reveals a favorable enthalpy but large negative entropy (−5.1 kcal × mol –1 and −22.9 cal × mol –1 × K –1 , respectively) for CO binding, affording a process that is marginally endergonic at room temperature (ΔG ads (298.15 K) = 1.7 ± 0.5 kcal × mol –1 ). Similarly, analogous to a Cu(111) surface, 1 is shown to oxidatively add (chemisorb) H 2 . Kinetic parameters were determined for this process and the activation enthalpy (8.4 ± 0.5 kcal × mol –1 ) closely mirrors that established for H 2 binding at the Cu(111) facet (6.0 to 12.4 kcal × mol –1 ). Together, these results showcase that a trinuclear cluster can reproduce the small molecule binding and activation energetics of a bulk crystalline surface, setting the stage for studying less-defined surface processes in an atomically precise molecular setting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Decadal increases in carbon uptake offset by respiratory losses across northern permafrost ecosystems

Tundra and boreal ecosystems encompass the northern circumpolar permafrost region and are experiencing rapid environmental change with important implications for the global carbon (C) budget. We analysed multi-decadal time series containing 302 annual estimates of carbon dioxide (CO 2 ) flux across 70 permafrost and non-permafrost ecosystems, and 672 estimates of summer CO 2 flux across 181 ecosystems. We find an increase in the annual CO 2 sink across non-permafrost ecosystems but not permafrost ecosystems, despite similar increases in summer uptake. Thus, recent non-growing-season CO 2 losses have substantially impacted the CO 2 balance of permafrost ecosystems. Furthermore, analysis of interannual variability reveals warmer summers amplify the C cycle (increase productivity and respiration) at putatively nitrogen-limited sites and at sites less reliant on summer precipitation for water use. Our findings suggest that water and nutrient availability will be important predictors of the C-cycle response of these ecosystems to future warming.

58 GEOSCIENCES↗
DOE OSTI2022

Thermo-Mechanical Distortion of Tungsten-Coated Steel During High Heat Flux Testing Using Plasma Arc Lamps

An experimental setup and a test section were designed and fabricated for high heat flux testing (HHFT) of neutron-irradiated specimens using water-wall plasma arc lamps. Because of the radiological considerations and limitations of reactor irradiation, the size of the test articles was limited to disks less than 10 mm in diameter. The specimen was clamped onto an actively cooled block, and clamping allowed the insertion of several thermocouples on the back surface of the specimen through a copper (Cu) block. Five vacuum plasma sprayed tungsten (W)–coated F82H steel specimens were subjected to HHFT. Surface profilometry measurements, which were conducted after HHFT, revealed central bowing of the top W surface. This type of residual distortion occurred for all of the specimens, and the larger the specimens were, the larger was the distortion.In an attempt to understand specimen distortion and address the science questions related to the testing of subsize specimens during HHFT, a simplified thermo-mechanical model was developed. By using a measured temperature in the Cu as an isothermal boundary condition, the model eliminated the need for coupling cooling fluid flow models with stress models, greatly simplifying the analysis. The main variable in the proposed model is hC, i.e., the thermal contact conductance between the F82H and the Cu washer. Inelastic properties, including hardening properties, were considered for F82H steel and Cu. Numerical simulation results demonstrated a buildup of residual deformation during HHFT and a very complex state of stress and deformation during typical heat flux (HF) cycling. Additionally, hoop stress evolution during a high heat flux cycle reveals that F82H at an interface with W would be mainly in compression during HF application and experienced a transition to a tension state during cooldown. Also, specimen distortion evolves during each HF cycle, as the specimen bows downward during HF application and upward during the cooldown period between HF cycles. The final specimen distortion, i.e., upward bowing of the specimen center, was qualitatively predicted for hC values of 4000 to 5000 W/(m 2 ·K). This hC range of values, for which bulging is obtained, is at the lower spectrum of the range of values for hC, consistent with the low thermal contact conductance expected from the unpolished F82H surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine-assisted discovery of integrable symplectic mappings

Integrable systems possess a hidden symmetry associated with the existence of conserved quantities known as integrals of motion. These systems play an important role in understanding general dynamics in accelerators and have potential for future designs. This work will cover two automated methods for finding integrable symplectic maps of the plane. The first algorithm is based on the observation that the evolution of an integrable system in phase space is confined to a lower-dimensional submanifold of a specific type. The second algorithm relies on an analysis of dynamical variables. Both methods rediscover some of the famous McMillan-Suris integrable mappings and ultra-discrete Painlev\'e equations. Over 100 new integrable families are presented and analyzed, some of which are isolated in the space of parameters, while others are families with one parameter (or the ratio of parameters) being either continuous or discrete. In addition, the newly discovered maps are related to a general 2D symplectic map through the use of discrete perturbation theory. A method is proposed for constructing smooth near-integrable dynamical systems based on mappings with polygon invariants.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Formality of Operations and Nuclear Criticality Safety Standards [Slides]

This presentation is on the formality of operations and nuclear criticality safety standards. This lecture starts with an Introduction then leads into a conversation on the dependencies of formality of operations. Secondly the presentation includes a review of past issues. Included is a Discussion about “credible” and “unlikely” – variables for process analysis in ANS-8.1, Section 4.1.2, and the double contingency principle, Section 4.2.2, respectively. The presentation finishes with some conclusions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Machine-Assisted Discovery of Integrable Symplectic Mappings

Integrable systems possess a hidden symmetry associated with the existence of conserved quantities known as integrals of motion. These systems play an important role in understanding general dynamics in accelerators and have potential for future designs. This work will cover two automated methods for finding integrable symplectic maps of the plane. The first algorithm is based on the observation that the evolution of an integrable system in phase space is confined to a lower-dimensional submanifold of a specific type. The second algorithm relies on an analysis of dynamical variables. Both methods rediscover some of the famous McMillan-Suris integrable mappings and ultra-discrete Painlev\'e equations. Over 100 new integrable families are presented and analyzed, some of which are isolated in the space of parameters, while others are families with one parameter (or the ratio of parameters) being either continuous or discrete. In addition, the newly discovered maps are related to a general 2D symplectic map through the use of discrete perturbation theory. A method is proposed for constructing smooth near-integrable dynamical systems based on mappings with polygon invariants.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

flat10MIP: an emissions-driven experiment to diagnose the climate response to positive, zero and negative CO2 emissions

Abstract. The proportionality between global mean temperature and cumulative emissions of CO2 predicted in Earth system models (ESMs) is the foundation of carbon budgeting frameworks. Deviations from this behavior could impact estimates of required net-zero timings and negative emissions requirements to meet the Paris Agreement climate targets. However, existing ESM diagnostic experiments do not allow for direct estimation of these deviations as a function of defined emissions pathways. Here, we perform a set of climate model diagnostic experiments for the assessment of transient climate response to cumulative CO2 emissions (TCRE), the Zero Emissions Commitment (ZEC), and climate reversibility metrics in an emissions-driven framework. The emissions-driven experiments provide consistent independent variables simplifying simulation, analysis and interpretation, with emissions rates more comparable to recent levels than existing protocols using model-specific compatible emissions from the CMIP DECK 1pctCO2 experiment, where emissions rates tend to increase during the experiment, such that at the time of CO2 doubling in year 70, emissions are much greater than present-day values. A base experiment, “esm-flat10”, has constant emissions of CO2 of 10 GtC per year (near-present-day values), and initial results show that the TCRE estimated in this experiment is about 0.1 K less than that obtained using 1pctCO2. A subset of ESMs exhibit land carbon sinks that saturate during this experiment. A branch experiment, esm-flat10-zec, illustrates that both positive and negative ZEC effects are less pronounced under esm-flat10 than under 1pctCO2 – the magnitude of ZEC50 in ESMs is, on average, reduced by 30 % compared with 1pctCO2 branch experiments. A final experiment, esm-flat10-cdr, assesses climate reversibility under negative emissions, where we find that peak warming may occur before or after net zero and that the asymmetry in temperature at a given level of cumulative emissions between the positive and negative emissions phases is well described by ZEC in most models. Further, we find that existing probabilistic simple climate model (SCM) ensembles tend to overestimate temperature reversibility compared with ESMs, highlighting the need for additional constraints. We propose a set of climate diagnostic indicators to quantify various aspects of climate reversibility. These experiments were suggested as potential candidates in CMIP7 and have since been adopted as “fast track” simulations.

Sanderson, Benjamin M↗
DOE OSTI2026

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗