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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Several Small or Single Large? Quantifying the Catchment-Wide Performance of On-Site Wastewater Treatment Plants with Inaccurate Sensors

On-site wastewater treatment plants (OSTs) often lack monitoring, resulting in unreliable treatment performance. They thus appear to be a stopgap solution despite their potential contribution to circular water management. Low-maintenance but inaccurate soft sensors are emerging that address this concern. However, how their inaccuracy impacts the catchment-wide treatment performance of a system of many OSTs has not been quantified. Here, we develop a stochastic model to estimate catchment-wide OST performances with a Monte Carlo simulation. In our study, soft sensors with a 70% accuracy improved the treatment performance from 66% of the time functional to 98%. Soft sensors optimized for specificity, indicating the true negative rate, improve the system performance, while sensors optimized for sensitivity, indicating the true positive rate, quantify the treatment performance more accurately. This new insight leads us to suggest programming two soft sensors in practical settings with the same hardware sensor data as input: one soft sensor geared to high specificity for maintenance scheduling and one geared to high sensitivity for performance quantification. Our findings suggest that a maintenance strategy combining inaccurate sensors with appropriate alarm management can vastly improve the mean catchment-wide treatment performance of a system of OSTs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Large-eddy simulations of surface roughness parameter sensitivity to canopy-structure characteristics

Surface roughness parameters, namely the roughness length and displacement height, are an integral input used to model surface fluxes. However, most models assume these parameters to be a fixed property of plant functional type and disregard the governing structural heterogeneity and dynamics. In this study, we use large-eddy simulations to explore, in silico, the effects of canopy-structure characteristics on surface roughness parameters. We performed a virtual experiment to test the sensitivity of resolved surface roughness to four axes of canopy structure: (1) leaf area index, (2) the vertical profile of leaf density, (3) canopy height, and (4) canopy gap fraction. We found roughness parameters to be highly variable, but uncovered positive relationships between displacement height and maximum canopy height, aerodynamic canopy height and maximum canopy height and leaf area index, and eddy-penetration depth and gap fraction. We also found negative relationships between aerodynamic canopy height and gap fraction, as well as between eddy-penetration depth and maximum canopy height and leaf area index. We generalized our model results into a virtual "biometric" parameterization that relates roughness length and displacement height to canopy height, leaf area index, and gap fraction. Using a decade of wind and canopy-structure observations in a site in Michigan, we tested the effectiveness of our model-driven biometric parameterization approach in predicting the friction velocity over heterogeneous and disturbed canopies. We compared the accuracy of these predictions with the friction-velocity predictions obtained from the common simple approximation related to canopy height, the values calculated with large-eddy simulations of the explicit canopy structure as measured by airborne and ground-based lidar, two other parameterization approaches that utilize varying canopy-structure inputs, and the annual and decadal means of the surface roughness parameters at the site from meteorological observations. We found that the classical representation of constant roughness parameters (in space and time) as a fraction of canopy height performed relatively well. Nonetheless, of the approaches we tested, most of the empirical approaches that incorporate seasonal and interannual variation of roughness length and displacement height as a function of the dynamics of canopy structure produced more precise and less biased estimates for friction velocity than models with temporally invariable parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

User's Guide for RESRAD-ONSITE Code

The RESRAD-ONSITE code is equipped with a user-friendly interface that has many features to facilitate its use and comprehension. The design of the interface provides various navigation options, including entering data, performing calculations, and displaying the results of the calculations. General and context-specific help are available, offering information on editing and viewing the radionuclide database, the definitions of input parameters and their use in the calculations, and the selection and output of the results of the calculations into other applications. Two types of sensitivity analysis are supported by the code, deterministic and probabilistic, which can be used to study the influence of input parameters on the calculated results.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

User's manual for a parameter identification technique

A digital computer program written in FORTRAN is presented that implements the system identification theory for deterministic systems using input-output measurements. The user supplies programs simulating the mathematical model of the physical plant whose parameters are to be identified. The user may choose any one of three options. The first option allows for a complete model simulation for fixed input forcing functions. The second option identifies up to 36 parameters of the model from wind tunnel or flight measurements. The third option performs a sensitivity analysis for up to 36 parameters. The use of each option is illustrated with an example using input-output measurements for a helicopter rotor tested in a wind tunnel.

Kanning, G.↗
NASA NTRS1999

A Quantitative Study of Oxygen as a Metabolic Regulator

An acute reduction in oxygen (O2) delivery to a tissue is generally associated with a decrease in phosphocreatine, increases in ADP, NADH/NAD, and inorganic phosphate, increased rates of glycolysis and lactate production, and reduced rates of pyruvate and fatty acid oxidation. However, given the complexity of the human bioenergetic system and its components, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in tissue O2 availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study, we extend a previously developed mathematical model of human bioenergetics to provide a physicochemical framework that permits quantitative understanding of O2 as a metabolic regulator. Specifically, the enhancement permits studying the effects of variations in tissue oxygenation and in parameters controlling the rate of cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The whole body is described as a bioenergetic system consisting of metabolically distinct tissue/organ subsystems that exchange materials with the blood. In order to study the dynamic response of each subsystem to stimuli, we solve the ordinary differential equations describing the temporal evolution of metabolite levels, given the initial concentrations. The solver used in the present study is the packaged code LSODE, as implemented in the NASA Lewis kinetics and sensitivity analysis code, LSENS. A major advantage of LSENS is the efficient procedures supporting systematic sensitivity analysis, which provides the basic methods for studying parameter sensitivities (i.e., changes in model behavior due to parameter variation). Sensitivity analysis establishes relationships between model predictions and problem parameters (i.e., initial concentrations, rate coefficients, etc). It helps determine the effects of uncertainties or changes in these input parameters on the predictions, which ultimately are compared with experimental observations in order to validate the model. Sensitivity analysis can identify parameters that must be determined accurately because of their large effect on the model predictions and parameters that need not be known with great precision because they have little or no effect on the solution. This capability may prove to be important in optimizing the design of experiments, thereby reducing the use of animals. This approach can be applied to study the metabolic effects of reduced oxygen delivery to cardiac muscle due to local myocardial ischemia and the effects of acute hypoxia on brain metabolism. Other important applications of sensitivity analysis include identification of quantitatively relevant pathways and biochemical species within an overall mechanism, when examining the effects of a genetic anomaly or pathological state on energetic system components and whole system behavior.

Radhakrishnan, Krishnan↗
NASA NTRS1977

A computationally fast one-dimensional diffusion-photochemistry model of SST wakes

A computational technique applicable to analysis of supersonic transport (SST) wake photochemistry and diffusion is presented. Sensitivity studies of SST effluent effects upon ozone depletion are facilitated by the computational rapidity of the method. The article compares results from other studies and predictions of some variables related to global NOx input. Results indicate that the NO/NO2 ratio in an SST wake at photochemical equilibrium is a sensitive function of photolysis rates.

Matloff, G. L.↗
NASA NTRS2010

Failure Bounding And Sensitivity Analysis Applied To Monte Carlo Entry, Descent, And Landing Simulations

In the study of entry, descent, and landing, Monte Carlo sampling methods are often employed to study the uncertainty in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Three methods that provide statistical insights are applied to an entry, descent, and landing simulation. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. The first method investigated was failure domain bounding which aims to reduce the computational cost of assessing the failure probability. Next a variance-based sensitivity analysis was studied for the ability to identify which input variable uncertainty has the greatest impact on the uncertainty of an output. Finally, probabilistic sensitivity analysis is used to calculate certain sensitivities at a reduced computational cost. These methods produce valuable information that identifies critical mission parameters and needs for new technology, but generally at a significant computational cost.

Gaebler, John A.↗
NASA NTRS1992

Interchangeable end effector tools utilized on the PFMA

An instrumented task board, used for measuring forces applied by the Protoflight Manipulator Arm (PFMA) to the task board, was fabricated and delivered to Marshall Space Flight Center. SRS Technologies phased out the existing IBM compatible data acquisition system, used with a instrumented task board, and integrated the force measuring electronic hardware in with the Macintosh II data acquisition system. The purpose of this change was to acquire all data with the same time tag, allowing easier and more accurate data reduction in addition to real-time graphics. A three-dimensional optical position sensing system for determining the location of the PFMA's end effect or in reference to the center of the instrumented task board was also designed and delivered under. An improved task board was fabricated which included an improved instrumented beam design. The modified design of the task board improved the force/torque measurement system by increasing the sensitivity, reliability, load range and ease of maintenance. A calibration panel for the optical position system was also designed and fabricated. The calibration method developed for the position sensors enhanced the performance of the sensors as well as simplified the installation and calibration procedures required. The modifications made under this effort expanded the capabilities of the task board system. The system developed determines the arm's position relative to the task board and measures the signals to the joints resulting from the operator's control signals in addition to the task board forces. The software and hardware required to calculate and record the position of the PFMA during the performance of tasks with the instrumented task board were defined, designed and delivered to MSFC. PFMA joint input signals can be measured from a breakout box to evaluate the sensitivity or response of the arm operation to control commands. The data processing system provides the capability for post processing of time-history graphics and plots of the PFMA positions, the operator's actions, and the PFMA servo reactions in addition to realtime force and position sensor data presentation.

Cody, Joe↗
DOE OSTI2020

Enhancing nuclear data validation analysis by using machine learning

In this work, we demonstrate how machine learning (ML) techniques can be used as an auxiliary tool for nuclear data validation analysis. The output of the ML analysis can inform evaluators and validators on the quality, or lack thereof, of specific nuclear data and benchmark experiments with respect to simulating these experimental benchmark values. To this end, measured and simulated effective neutron multiplication factors, k eff , of 875 selected ICSBEP critical assemblies and the latter's sensitivities with respect to nuclear data as well as benchmarks' features (e.g., material nuclide, core geometry) are used as input for a random forest (RF) regression model. The RF is used to encode the complex inter-dependencies between thousands of nuclear data features (i.e., sensitivity profiles and aspects describing the measurements) and 875 simulated and experimental k eff values in order to understand what nuclear data features are most informative for predicting bias. The complexity of relationships and high-dimensional space is difficult-to-impossible to search fully using simply expert judgment. As a first proof-of-concept—step, it is demonstrated that this technique is able to correctly trace large discrepancies between simulated and experimental k eff back to fabricated shortcomings in nuclear data that were perturbed to simulated k eff values. In a second, real-case scenario, step, the RF algorithm is used to validate the ENDF/B-VIII.0 library in comparison to ENDF/B-VII.1 nuclear data. One case is showcased where the chosen ML algorithms highlighted nuclear data (the 19 F(n,inl) cross section from 0.4–0.9 MeV) that are shown to be problematic by comparing them to associated differential experimental data and nuclear data from other libraries. In addition to that, it is shown that the RF results point towards poor benchmark experiments and associated underestimated uncertainties (e.g., the PU-SOL-THERM-028 series). However, using the RF algorithm for validating nuclear data with respect to k eff is currently limited to pinpointing groups of questionable nuclear data due to the inherent correlations between features introduced by the nuclear data themselves and how k eff is simulated. Due to this, we recommend that the ML methods presented be used to augment—rather than replace—the expert knowledge of evaluators and validators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

Screening sensitivity analysis of a PWR fuel assembly FEM structural model

Within the present project, computational methods to describe the static mechanical response of PWR fuel assemblies (FA) in the reactor core are developed. For this purpose a structural model of a PWR fuel assembly has been implemented with the Finite Element Method (FEM) using the ANSYS APDL Mechanical code. The purpose of the model is to investigate the long-term creep deformation of the fuel assemblies in the reactor core, commonly known as fuel assembly bow. FA bow is considered to be a complex process with a large number of influencing mechanisms and many only roughly known boundary conditions. Uncertainty and sensitivity analyses are a common way to investigate the predictive power and reliability of such complex models. Hence, as a first approach to understand the importance of the many model parameters, a qualitative sensitivity analysis of the model was conducted using the screening method proposed by Morris. In the first part of the paper, the FA structural model and its principal parameters are presented. The second part presents first the different simulation experiments used for the screening analyses. Based on the model description, relevant input parameters are then identified and a typical range of values is determined. The sensitivity analysis is performed in two subsequent steps. First, the model is screened for influential stiffness parameters with the objective of stiffening the FA structure. Second, the influence of the uncertain boundary conditions and material models on the FA creep deformation is tested. For the considered FA design it is concluded that the influence of the involved uncertainties is comparable to the influence of the parameters which can increase the stiffness. An integral approach accounting for these uncertainties is hence necessary to predict FA bow reliably in order to take additional measures for a further reduction of FA bow amplitudes. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Measurement of the CKM angle γ from a combination of LHCb results

A combination of measurements sensitive to the CKM angle γ from LHCb is performed. The inputs are from analyses of time-integrated B+ → DK+, B0 → DK*0, B0 → DK+π- and B+ → DK+π+π- tree-level decays. In addition, results from a time-dependent analysis of Bs0 → Ds∓K± decays are included. The combination yields γ = (72. 2- 7.3+ 6.8)°, where the uncertainty includes systematic effects. The 95.5% confidence level interval is determined to be γ ϵ [55.9, 85.2]°. A second combination is investigated, also including measurements from B+ → Dπ+ and B+ → Dπ+π-π+ decays, which yields compatible results.

Aaij, R↗
DOE OSTI2022

Co-Based superalloy morphology evolution: A phase field study based on experimental thermodynamic and kinetic data

Cobalt-based superalloys with two phase $\gamma$/$\gamma '$ microstructures offer great promise as candidates for next-generation high-temperature alloys for applications, such as turbine blades. It is essential to understand the thermodynamic and kinetic factors that influence the microstructural evolution of these alloys in order to optimize the alloy compositions and processing steps with a goal to improve their coarsening, creep and rafting behavior. We are using a continuum phase field approach to study the diffusion process and to predict the equilibrium shapes of Co-Al-W $\gamma '$ precipitates. In order to obtain quantitatively predictive capabilities, we extract chemical free energies for the $\gamma$/$\gamma '$ phases based on CALculation of PHAse Diagrams (CALPHAD) thermodynamic data and diffusion mobilities for Co alloys based on CALPHAD kinetic data. We also use experimental or first-principles data for other quantities, such as misfit strain and interface information, for the parameterization of our model. A particular focus of our study is to understand how different energy balances, misfit strain and kinetics affect the coarsening and rafting behavior of $\gamma '$ precipitates, and the sensitivity of the final precipitate shape to materials parameters. Here, we find that the equilibrium shape of the precipitate results from a delicate competition between chemical, interfacial, and elastic energies, and it is very sensitive to changes in model parameters. Here, we examine how modeling input parameters affect the equilibrium shape of precipitates and relate these parameters to experimentally available values.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Soil carbon fractions and biological activity based indices can be used to study the impact of land management and ecological successions

Soil organic carbon (SOC) is a strong indicator of soil health. Development of efficient soil quality indicators is crucial to better understand the impact of land management strategies on the recovery of degraded ecosystems. We hypothesized that SOC fractions and biological attributes can compose strong soil quality indicators to assess an ecosystem recovery following disturbance. Thus, the objective of this study was to evaluate the use of soil biological activity and SOC fractions to study the impact of different land use systems and ecological successions in ecosystem recovery. We selected six land use systems: tobacco (Nicotiana tabacum) cultivation; pastureland; reforested land with Eucalyptus sp.; and natural ecological successions with 10, 20 and 35 years of vegetation regeneration, respectively. We collected disturbed and undisturbed soil samples in triplicate at 0–5, 5–10, 10–20 and 20–40 cm depth intervals. Several fractionation approaches were used to determine SOC pools: hot water extractable organic carbon, permanganate oxidized organic carbon, particulate organic carbon, mineral associated organic carbon and total SOC. The activity of the enzyme arylsulfatase was used to represent soil biological attributes. We calculated three indices to represent the soil quality: carbon management index, soil resilience index and biological activity index. Our results suggest that the SOC fractions and the enzyme activity followed the increase of vegetation complexity of the ecological succession stages. The labile SOC pool, in addition to enzyme activity, was the most sensitive variable to assess land use changes. The biomass-C input was considered to be the main reason of SOC increase, and the gains of labile SOC fractions were directly related to the increase of SOC stocks. Both, biological and carbon management indices were efficient tools to characterize the impact of studied management systems. Also, we found that assessment of deeper soil layers (20–40 cm) was extremely important as incomplete inferences might be reached while evaluating only surface soil layers (0–20 cm). Here, we conclude that the carbon management and biological indices captured the stage of soil degradation and the influence of vegetation diversity in the soil resilience restoration, providing an advance in monitoring strategies that can be reproducible in any environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sub-Hertz resonance by weak measurement

Weak measurement (WM) with state pre- and post-selection can amplify otherwise undetectable small signals and thus has potential in precision measurement applications. Although frequency measurements offer the hitherto highest precision due to the stable narrow atomic transitions, it remains a long-standing interest to develop new schemes to further escalate their performance. Here, we demonstrate a WM-enhanced correlation spectroscopy technique capable of narrowing the resonance linewidth down to 0.1 Hz in a room-temperature atomic vapour cell. The potential of this technique for precision measurement is demonstrated through weak magnetic-field sensing. By judiciously pre- and post-selecting frequency-modulated input and output optical states in a nearly orthogonal manner, a sensitivity of 7 fT Hz -1/2 at a low frequency near DC is achieved using only one laser beam with 15 µW of power. Additionally, our results extend the WM framework to a non-Hermitian Hamiltonian and shed new light on metrology and bio-magnetic field sensing.

Science & Technology - Other Topics↗
DOE OSTI2017

Atmospheric evidence for a global secular increase in carbon isotopic discrimination of land photosynthesis

First, a decrease in the 13 C/ 12 C ratio of atmospheric CO 2 has been documented by direct observations since 1978 and from ice core measurements since the industrial revolution. This decrease, known as the 13 C-Suess effect, is driven primarily by the input of fossil fuel-derived CO 2 but is also sensitive to land and ocean carbon cycling and uptake. Using updated records, we show that no plausible combination of sources and sinks of CO 2 from fossil fuel, land, and oceans can explain the observed 13 C-Suess effect unless an increase has occurred in the 13 C/ 12 C isotopic discrimination of land photosynthesis. A trend toward greater discrimination under higher CO 2 levels is broadly consistent with tree ring studies over the past century, with field and chamber experiments, and with geological records of C 3 plants at times of altered atmospheric CO 2 , but increasing discrimination has not previously been included in studies of long-term atmospheric 13 C/ 12 C measurements. In our paper, we further show that the inferred discrimination increase of 0.014 ± 0.007‰ ppm -1 is largely explained by photorespiratory and mesophyll effects. This result implies that, at the global scale, land plants have regulated their stomatal conductance so as to allow the CO 2 partial pressure within stomatal cavities and their intrinsic water use efficiency to increase in nearly constant proportion to the rise in atmospheric CO 2 concentration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Bayesian inference of nuclear-matter density from proton scattering

Background: Proton elastic scattering at intermediate energy is widely employed as a tool for determining the matter radius of atomic nuclei. Here, the sensitivity of the approach relies on high-resolution measurements at small scattering angles and low-momentum transfer. Under these conditions, the Glauber multiple scattering theory accurately describes the proton-nucleus elastic cross section. Purpose: Investigate the sensitivity of the Glauber multiple scattering theory to uncertainties associated with input parameters such as the nuclear-matter density distribution and nucleon-nucleon data. Method: A joint Bayesian inference was performed using 12 angular distributions of elastic scattering at different energies on 58 Ni, 90 Zr, and 208 Pb targets. A Metropolis-Hastings algorithm was implemented to make an uncertainty quantification analysis for the input parameters used in the Glauber multiple scattering theory. Results: The experimental cross sections were fitted simultaneously using a joint Bayesian inference approach. Posterior probability density distributions of 42 input parameters were obtained from the analysis. A moderate correlation between the nuclear density parameters and the nucleon-nucleon cross sections was found. This correlation impacts the extraction of the nuclear-matter radius. Conclusions: The present analysis provided a consistent method for extracting the nuclear-matter density distribution of 58 Ni, 90 Zr, and 208 Pb from data across different incident energies. Due to the correlation of the nucleon-nucleon cross sections with the other input parameters, a constrained Bayesian inference using free nucleon-nucleon cross section data was performed. The nuclear-matter radii obtained from the analysis are in good agreement with multiple results reported in the literature.

190 ≤ A ≤ 219↗
DOE OSTI2016

Towards a Consolidated Approach for the Assessment of Evaluation Models of Nuclear Power Reactors

The STARS project at the Paul Scherrer Institut (PSI) has adopted the TRACE thermal-hydraulic (T-H) code for best-estimate system transient simulations of the Swiss Light Water Reactors (LWRs). For analyses involving interactions between system and core, a coupling of TRACE with the SIMULATE-3K (S3K) LWR core simulator has also been developed. In this configuration, the TRACE code and associated nuclear power reactor simulation models play a central role to achieve a comprehensive safety analysis capability. Thus, efforts have now been undertaken to consolidate the validation strategy by implementing a more rigorous and structured assessment approach for TRACE applications involving either only system T-H evaluations or requiring interfaces to e.g. detailed core or fuel behavior models. The first part of this paper presents the preliminary concepts of this validation strategy. The principle is to systematically track the evolution of a given set of predicted physical Quantities of Interest (QoIs) over a multidimensional parametric space where each of the dimensions represent the evolution of specific analysis aspects, including e.g. code version, transient specific simulation methodology and model "nodalisation". If properly set up, such environment should provide code developers and code users with persistent (less affected by user effect) and quantified information (sensitivity of QoIs) on the applicability of a simulation scheme (codes, input models, methodology) for steady state and transient analysis of full LWR systems. Through this, for each given transient/accident, critical paths of the validation process can be identified that could then translate into defining reference schemes to be applied for downstream predictive simulations. In order to illustrate this approach, the second part of this paper presents a first application of this validation strategy to an inadvertent blowdown event that occurred in a Swiss BWR/6. The transient was initiated by the spurious actuation of the Automatic Depressurization System (ADS). The validation approach progresses through a number of dimensions here: First, the same BWR system simulation model is assessed for different versions of the TRACE code, up to the most recent one. The second dimension is the "nodalisation" dimension, where changes to the input model are assessed. The third dimension is the "methodology" dimension. In this case imposed power and an updated TRACE core model are investigated. For each step in each validation dimension, a common set of QoIs are investigated. For the steady-state results, these include fuel temperatures distributions. For the transient part of the present study, the evaluated QoIs include the system pressure evolution and water carry-over into the steam line.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗