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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 OSTI2022

Analytical Sensitivity Analysis of a Spent Nuclear Fuel Cask

Here, we report nuclear science and engineering is a field increasingly dominated by computational studies resulting from increasingly powerful computational tools. As a result, analytical studies, which previously pioneered nuclear engineering, are increasingly viewed as secondary or unnecessary. However, analytical solutions to reduced-fidelity models can provide important information concerning the underlying physics of a problem and aid in guiding computational studies. Similarly, there is increased interest in sensitivity analysis studies. These studies commonly use computational tools. However, providing a complementary sensitivity study of relevant analytical models can lead to a deeper analysis of a problem. This work provides the analytical sensitivity analysis of the one-dimensional (1D) cylindrical mono-energetic neutron diffusion equation using the forward sensitivity analysis procedure (FSAP) developed by Cacuci. Further, these results are applied to a reduced-fidelity model of a spent nuclear fuel cask, demonstrating how computational analysis might be improved with a complementary analytic sensitivity analysis.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Semi-analytical sensitivity analysis for nonlinear transient problems

Efficient analytical sensitivity computations are essential elements of gradient-based optimization schemes; however, they can be difficult to implement. This implementation issue is often resolved by adopting the semi-analytical method which exhibits the efficiency of the analytical methods and the ease of implementation of the finite difference method. However, care must be taken as semi-analytical sensitivities may exhibit errors due to truncation and round-off. Additional errors are introduced if the convergence tolerance of the primal analysis is not sufficiently small. This paper gives a general overview and some new developments of the analytical and semi-analytical sensitivity analyses for nonlinear steady-state, transient, and dynamic problems. We discuss the restrictive assumptions, accuracy, and consistency of these methods. Both adjoint and direct differentiation methods are studied. Numerical examples are provided.

42 ENGINEERING↗
DOE OSTI2020

Analytical Voltage Sensitivity Analysis for Unbalanced Power Distribution System

Large scale integration of distributed energy resources and electric vehicles in a transactive energy environment present new challenges in terms of voltage stability and fluctuations in a power distribution system. The impact of different level of DER/EV penetration on the voltages across the network is typically quantified through voltage sensitivity analyses. Existing methods of voltage sensitivity analysis are computationally expensive and prior efforts to develop analytical approximation lacks generality and have not been effectively validated. The objective of this work is to provide a new analytical method of voltage sensitivity analysis that has low computational cost and also allows for stochastic analysis of voltage change. This paper first derives an analytical approximation of change in voltage at a particular bus due to change in power consumption at other bus in a radial three phase unbalanced power distribution system. Then, the proposed method is shown to be valid for different load configurations, which demonstrates its generality. The results from our analytical approach is validated via classical load flow simulation of the test system based on IEEE 37 bus network. The proposed method is shown to have good accuracy, and computation complexity is of order O(1), compared to O(n3) in classical sensitivity analysis approaches.

Munikoti, Sai↗
DOE OSTI2017

Analysis of transient fission gas behaviour in oxide fuel using BISON and TRANSURANUS

The modelling of fission gas behaviour is a crucial aspect of nuclear fuel analysis in view of the related effects on the thermo-mechanical performance of the fuel rod, which can be particularly significant during transients. Experimental observations indicate that substantial fission gas release (FGR) can occur on a small time scale during transients (burst release). To accurately reproduce the rapid kinetics of burst release in fuel performance calculations, a model that accounts for non-diffusional mechanisms such as fuel micro-cracking is needed. In this work, we present and assess a model for transient fission gas behaviour in oxide fuel, which is applied as an extension of diffusion-based models to allow for the burst release effect. The concept and governing equations of the model are presented, and the effect of the newly introduced parameters is evaluated through an analytic sensitivity analysis. Then, the model is assessed for application to integral fuel rod analysis. The approach that we take for model assessment involves implementation in two structurally different fuel performance codes, namely, BISON (multi-dimensional finite element code) and TRANSURANUS (1.5D semi-analytic code). The model is validated against 19 Light Water Reactor fuel rod irradiation experiments from the OECD/NEA IFPE (International Fuel Performance Experiments) database, all of which are simulated with both codes. The results point out an improvement in both the qualitative representation of the FGR kinetics and the quantitative predictions of integral fuel rod FGR, relative to the canonical, purely diffusion-based models, with both codes. The overall quantitative improvement of the FGR predictions in the two codes is comparable. Furthermore, calculated radial profiles of xenon concentration are investigated and compared to experimental data, demonstrating the representation of the underlying mechanisms of burst release by the new model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Shape optimization using a NURBS-based interface-enriched generalized FEM

This study presents a gradient-based shape optimization over a fixed mesh using a non-uniform rational B-splines-based interface-enriched generalized finite element method, applicable to multi-material structures. In the proposed method, non-uniform rational B-splines are used to parameterize the design geometry precisely and compactly by a small number of design variables. An analytical shape sensitivity analysis is developed to compute derivatives of the objective and constraint functions with respect to the design variables. Subtle but important new terms involve the sensitivity of shape functions and their spatial derivatives. As a result, verification and illustrative problems are solved to demonstrate the precision and capability of the method.

42 ENGINEERING↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2020

Single-entity electrochemistry at confined sensing interfaces

Measurements at the single-entity level provide more precise diagnosis and understanding of basic biological and chemical processes. Recent advances in the chemical measurement provide a means for ultra-sensitive analysis. Confining the single analyte and electrons near the sensing interface can greatly enhance the sensitivity and selectivity. In this work, we summarize the recent progress in single-entity electrochemistry of single molecules, single particles, single cells and even brain analysis. The benefits of confining these entities to a compatible size sensing interface are exemplified. Finally, the opportunities and challenges of single entity electrochemistry are addressed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Probabilistic Voltage Sensitivity Analysis to Quantify Impact of High PV Penetration on Unbalanced Distribution System

From an operational and planning perspective, it is important to quantify the impact of increasing penetration of photovoltaics on the distribution system. Most existing impact assessment studies are scenario-based where derived results are scenario specific and not generalizable. Moreover, stochasticity in the temporal behavior of spatially distributed PVs requires a large number of scenarios that increase with the size of the network and the level of penetration. Therefore, we propose a new computationally efficient analytical framework of voltage sensitivity analysis that allows for stochastic analysis of voltage change due to random changes in PV generation. We first derive an analytical approximation for voltage change at any node of the network due to change in power at other nodes in an unbalanced distribution network. The quality of this approximation is reinforced via bounds on the approximation error. Then, we derive the probability distribution of voltage change at a certain node due to random changes in power injections/consumptions at multiple locations of the network. The accuracy of the proposed PVSA is illustrated using a modified version of the IEEE 37 bus test system. As a result, the proposed PVSA can serve as a powerful tool for proactive monitoring/control and ease the computational burden associated with perturbation based cybersecurity mechanisms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Three-Dimensional Imaging of Lipids and Metabolites in Tissues by Nanospray Desorption Electrospray Ionization Mass Spectrometry

Abstract Three-dimensional (3D) imaging of tissue sections is a new frontier in mass spectrometry imaging (MSI). Here we report on fast 3D imaging of lipids and metabolites associated with mouse uterine decidual cells and embryo at the implantation site on day 6 of pregnancy. 2D imaging of 16-20 serial tissue sections deposited on the same glass slide was performed using nanospray desorption electrospray ionization (nano-DESI) – an ambient ionization technique that enables sensitive localized analysis of analytes on surfaces without special sample pre-treatment. In this proof-of-principle study, nano-DESI was coupled to a high-resolution Q-Exactive instrument operated at high repetition rate of >5 Hz with moderate mass resolution of 35,000 (m/Δm at m/z 200), which enabled acquisition of the entire 3D image with a spatial resolution of ~150 μm in less than 4.5 hours. The results demonstrate localization of acetylcholine in the primary decidual zone (PDZ) of the implantation site throughout the depth of the tissue examined, indicating an important role of this signaling molecule in decidualization. Choline and phosphocholine – metabolites associated with cell growth – are enhanced in the PDZ and abundant in other cellular regions of the implantation site. Very different 3D distributions were obtained for fatty acids (FA), oleic acid and linoleic acid (FA 18:1 and FA 18:2), differing only by one double bond. Localization of FA 18:2 in the PDZ indicates its important role in decidualization while FA 18:1 is distributed more evenly throughout the tissue. In contrast, several lysophosphatidylcholines (LPC) observed in this study show donut-like distributions with localization around the PDZ. Complementary distributions with minimal overlap were observed for LPC 18:0 and FA 18:2 while the 3D image of the potential precursor phosphatidylcholine (PC 36:2) showed a significant overlap with both LPC 18:0 and FA 18:2.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2020

Perturbation-Based Diagnosis of False Data Injection Attack Using Distributed Energy Resources

Modern smart grid relies on various sensor measurements for its operational control. In a successful false data injection attack, the attacker manipulates the measurements from the grid sensors such that undetected errors are introduced into the estimates of the system parameters leading to catastrophic situations. This paper proposes a novel perturbation based false data injection attack detection mechanism that utilizes inverter based distributed energy resources (DERs) to create low magnitude perturbation signal in the distribution system voltage that is inconsequential to the normal grid operation. Two voltage sensitivity analysis based algorithms are designed to identify the optimal set of DERs that can create the voltage perturbation signal of desired magnitude. An analytical method of voltage sensitivity analysis is used to compute the magnitude of voltage perturbation signal at each node in a computationally efficient manner. Then, a detection mechanism is developed that checks for the presence of the perturbation sequence in each sensor measurement. A sensor measurement is deemed authentic if the voltage perturbation signal is present in the data. In case of sensor malfunction or cyber-attack, the perturbation signal will not be present in the measurement data. Performance of the proposed attack detection mechanism is validated via simulation of the IEEE 69 bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Deep eutectic solvents as green and sustainable diluents in headspace gas chromatography for the determination of trace level genotoxic impurities in pharmaceuticals

Genotoxic impurities (GTIs) are potential carcinogens that need to be controlled down to ppm or lower concentration levels in pharmaceuticals under strict regulations. The static headspace gas chromatography (HS-GC) coupled with electron capture detection (ECD) is an effective approach to monitor halogenated and nitroaromatic genotoxins. Deep eutectic solvents (DESs) possess tunable physico-chemical properties and low vapor pressure for HS-GC methods. In this study, zwitterionic and non-ionic DESs have been used for the first time to develop and validate a sensitive analytical method for the analysis of 24 genotoxins at sub-ppm concentrations. Compared to non-ionic diluents, zwitterionic DESs produced exceptional analytical performance and the betaine: 7 (1,4- butane diol) DES outperformed the betaine: 5 (1,4-butane diol) DES. Limits of detection (LOD) down to the 5-ppb concentration level were achieved in DESs. Wide linear ranges spanning over 5 orders of magnitude (0.005–100 µg g –1 ) were obtained for most analytes with exceptional sensitivities and high precision. The method accuracy and precision were validated using 3 commercially available drug substances and excellent recoveries were obtained. Finally, this study broadens the applicability of HS-GC in the determination of less volatile GTIs by establishing DESs as viable diluent substitutes for organic solvents in routine pharmaceutical analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Quantitative Extraction and Mass Spectrometry Analysis at a Single-Cell Level

Quantitative live cell mass spectrometry analysis at a subcellular level requires the precisely controlled extraction of subpicoliter volumes of material from the cell, sensitive analysis of the extracted analytes, and their accurate quantification without prior separation. In this study, we demonstrate that localized electroosmotic extraction provides a direct path to addressing this challenge. Specifically, we demonstrate quantitative mass spectrometry analysis of biomolecules in picoliter volumes extracted from live cells. Electroosmotic extraction was performed using two electrodes and a finely pulled nanopipette with tip diameter of <1 µm containing a hydrophobic electrolyte compatible with mass spectrometry analysis. The electroosmotic drag was used to drive analytes out of the cell into the nanopipette. Analyte molecules extracted both from solutions and cell samples were analyzed using nanoelectrospray ionization (nanoESI) directly from the nanopipette into a mass spectrometer. More than 50 metabolites including sugars and flavonoids were detected in positive mode in 2-5 pL volumes of the cytoplasmic material extracted from Allium cepa. Quantification of the extracted glucose was performed using sequential extraction of a known volume of the aqueous solution containing glucose-d2 standard of known concentration. We found that the ratio of the signal of glucose to glucose-d2 increased linearly with glucose concentration. This observation indicates that the approach developed in this study enables quantitative analysis of small volumes of metabolites extracted from cells. Furthermore, we observed efficient separation of hydrophilic and hydrophobic analytes through partitioning into the aqueous and hydrophobic electrolyte phase, respectively, which provides additional important information on the molecular properties of extracted metabolites.

Yin, Ruichuan↗
DOE OSTI2017

Direct Surface and Droplet Microsampling for Electrospray Ionization Mass Spectrometry Analysis with an Integrated Dual-Probe Microfluidic Chip

Ambient mass spectrometry (MS) has revolutionized the way of MS analysis and broadened its application in various fields. This paper describes the use of microfluidic techniques to simplify the setup and improve the functions of ambient MS by integrating the sampling probe, electrospray emitter probe, and online mixer on a single glass microchip. Two types of sampling probes, including a parallel-channel probe and a U-shaped channel probe, were designed for dryspot and liquid-phase droplet samples, respectively. We demonstrated that the microfabrication techniques not only enhanced the capability of ambient MS methods in analysis of dry-spot samples on various surfaces, but also enabled new applications in the analysis of nanoliter-scale chemical reactions in an array of droplets. The versatility of the microchip-based ambient MS method was demonstrated in multiple different applications including evaluation of residual pesticide on fruit surfaces, sensitive analysis of low-ionizable analytes using postsampling derivatization, and high-throughput screening of Ugi-type multicomponent reactions.

Huang, Cong-Min↗
DOE OSTI2017

The electromechanical behavior of piezoelectric thin film composite diaphragms possessing in-plane stresses

Many piezoelectric microelectromechanical systems (MEMS) measure or generate acoustic signals via the motion of radially non-uniform, thin film composite plates. The composite layers provide piezoelectric actuation, structural support, electrode metallization, passivation, etc. Often, the layers are non-uniform over the plate and contain residual stresses introduced during the fabrication process. Accurate models of non-uniform composite plate mechanics are crucial for predicting and optimizing device performance. In this paper, an analytical solution for a radially non-uniform, piezoelectric, circular composite plate incorporating residual stress is derived. The analytical solution is compared to experimental measurements of a MEMS piezoelectric diaphragm. The results show the improved accuracy of the analytical model when including film stress, the speed of the analytical solution as compared to finite element analysis, the sensitivity of device performance to residual stress and the importance of accurate film stresses as model inputs. Finally, the analytical model presented is useful as a design optimization tool given the efficiency of the computational time, shown to be 275 times less than a comparable finite element analysis.

42 ENGINEERING↗
DOE OSTI2018

Uncertainty Quantification and Global Sensitivity Analysis of Subsurface Flow Parameters to Gravimetric Variations During Pumping Tests in Unconfined Aquifers

We study the contribution of typically uncertain subsurface flow parameters to gravity changes that can be recorded during pumping tests in unconfined aquifers. We do so in the framework of a Global Sensitivity Analysis and quantify the effects of uncertainty of such parameters on the first four statistical moments of the probability distribution of gravimetric variations induced by the operation of the well. System parameters are grouped into two main categories, respectively, governing groundwater flow in the unsaturated and saturated portions of the domain. We ground our work on the three-dimensional analytical model proposed by Mishra and Neuman (2011), which fully takes into account the richness of the physical process taking place across the unsaturated and saturated zones and storage effects in a finite radius pumping well. The relative influence of model parameter uncertainties on drawdown, moisture content, and gravity changes are quantified through (a) the Sobol' indices, derived from a classical decomposition of variance and (b) recently developed indices quantifying the relative contribution of each uncertain model parameter to the (ensemble) mean, skewness, and kurtosis of the model output. Our results document (i) the importance of the effects of the parameters governing the unsaturated flow dynamics on the mean and variance of local drawdown and gravity changes; (ii) the marked sensitivity (as expressed in terms of the statistical moments analyzed) of gravity changes to the employed water retention curve model parameter, specific yield, and storage, and (iii) the influential role of hydraulic conductivity of the unsaturated and saturated zones to the skewness and kurtosis of gravimetric variation distributions. The observed temporal dynamics of the strength of the relative contribution of system parameters to gravimetric variations suggest that gravity data have a clear potential to provide useful information for estimating the key hydraulic parameters of the system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Breaking through the false coincidence barrier in electron–ion coincidence experiments

Photoelectron Photoion Coincidence (PEPICO) spectroscopy holds the promise of a universal, isomer-selective, and sensitive analytical technique for time-resolved quantitative analysis of bimolecular chemical reactions. Unfortunately, its low dynamic range of ~10 3 has largely precluded its use for this purpose, where a dynamic range of at least 10 5 is generally required. This limitation is due to the false coincidence background common to all coincidence experiments, especially at high count rates. Electron/ion pairs emanating from separate ionization events but arriving within the ion time of flight (TOF) range of interest constitute the false coincidence background. Although this background has uniform intensity at every m/z value, the Poisson scatter in the false coincidence background obscures small signals. In this paper, temporal ion deflection coupled with a position-sensitive ion detector enables suppression of the false coincidence background, increasing the dynamic range in the PEPICO TOF mass spectrum by 2–3 orders of magnitude. The ions experience a time-dependent electric deflection field at a well-defined fraction of their time of flight. This deflection defines an m/z- and ionization-time dependent ion impact position for true coincidences, whereas false coincidences appear randomly outside this region and can be efficiently suppressed. When cold argon clusters are ionized, false coincidence suppression allows us to observe species up to Ar 9 + , whereas Ar 4 + is the largest observable cluster under traditional operation. As a result, this advance provides mass-selected photoelectron spectra for fast, high sensitivity quantitative analysis of reacting systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Dissecting galaxy formation models with sensitivity analysis—a new approach to constrain the Milky Way formation history

We present an application of a statistical tool known as sensitivity analysis to characterize the relationship between input parameters and observational predictions of semi-analytic models of galaxy formation coupled to cosmological N-body simulations. We show how a sensitivity analysis can be performed on our chemo-dynamical model, ChemTreeN, to characterize and quantify its relationship between model input parameters and predicted observable properties. The result of this analysis provides the user with information about which parameters are most important and most likely to affect the prediction of a given observable. It can also be used to simplify models by identifying input parameters that have no effect on the outputs (i.e., observational predictions) of interest. Conversely, sensitivity analysis allows us to identify what model parameters can be most efficiently constrained by the given observational data set. We have applied this technique to real observational data sets associated with the Milky Way, such as the luminosity function of the dwarf satellites. The results from the sensitivity analysis are used to train specific model emulators of ChemTreeN, only involving the most relevant input parameters. This allowed us to efficiently explore the input parameter space. A statistical comparison of model outputs and real observables is used to obtain a 'best-fitting' parameter set. We consider different Milky-Way-like dark matter halos to account for the dependence of the best-fitting parameter selection process on the underlying merger history of the models. For all formation histories considered, running ChemTreeN with best-fitting parameters produced luminosity functions that tightly fit their observed counterpart. However, only one of the resulting stellar halo models was able to reproduce the observed stellar halo mass within 40 kpc of the Galactic center. On the basis of this analysis, it is possible to disregard certain models, and their corresponding merger histories, as good representations of the underlying merger history of the Milky Way.

79 ASTRONOMY AND ASTROPHYSICS↗