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At least 91 records · Page 5

Application of a semianalytical technique for sensitivity analysis of unsteady aerodynamic computations

A semianalytical approach is developed for the sensitivity analysis of linear unsteady aerodynamic loads. The semianalytical approach is easier to implement than the analytical approach. It is also computationally less expensive than the finite difference approach when used with panel methods which require a large number of panels. The semianalytical approach is applied to an isolated airfoil in a two-dimensional flow and rotating propfan blades in three-dimensional flow. Sensitivity coefficients with respect to nonshape-dependent variables are shown for some cases.

Murthy, Durbha V.↗

Minimum Detectable Intakes and Doses for Uranium Bioassays—Comparison between Alpha Spectrometry and ICP-MS

Naturally occurring uranium complicates monitoring for occupational exposures. There are several retroactive methods that can be used to monitor for occupational exposures, with benefits and drawbacks to each. Analysis of uranium in urine by mass spectrometry and alpha spectrometry is compared, and methods of determining an occupational exposure are presented. Furthermore, the minimum detectable concentrations from each analysis and a method for intake determination based on the analytical results are compared for various solubility types and mixtures. Mass spectrometry with radiochemical separation was found to be the most sensitive analysis for detecting occupational exposures to anthropogenic mixtures based on minimum detectable doses calculated from the proposed method for intake determination.

bioassay↗

Design, analysis and test verification of advanced encapsulation systems

An analytical methodology for advanced encapsulation designs was developed. From these methods design sensitivities are established for the development of photovoltaic module criteria and the definition of needed research tasks. Analytical models were developed to perform optical, thermal, electrical and analyses on candidate encapsulation systems. From these analyses several candidate systems were selected for qualification testing. Additionally, test specimens of various types are constructed and tested to determine the validity of the analysis methodology developed. Identified deficiencies and/or discrepancies between analytical models and relevant test data are corrected. Prediction capability of analytical models is improved. Encapsulation engineering generalities, principles, and design aids for photovoltaic module designers is generated.

Garcia, A., III↗

Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making

The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

60 APPLIED LIFE SCIENCES↗

Spatial Resolution and Detectability Limits in Thin-Film X-Ray Microanalysis

The major advantages of performing x-ray microanalysis in the analytical electron microscope (AEM) are the high compositional spatial resolution and the elemental analysis sensitivity. Unfortunately, there is usually a trade-off between these two advantages. This paper discusses the factors involved in the optimization of both spatial resolution and sensitivity during x-ray microanalysis and shows the results of such optimization experiments for several AEM instruments.

Goldstein, J. I.↗

Three-Dimensional Viscous Alternating Direction Implicit Algorithm and Strategies for Shape Optimization

A gradient-based shape optimization based on quasi-analytical sensitivities has been extended for practical three-dimensional aerodynamic applications. The flow analysis has been rendered by a fully implicit, finite-volume formulation of the Euler and Thin-Layer Navier-Stokes (TLNS) equations. Initially, the viscous laminar flow analysis for a wing has been compared with an independent computational fluid dynamics (CFD) code which has been extensively validated. The new procedure has been demonstrated in the design of a cranked arrow wing at Mach 2.4 with coarse- and fine-grid based computations performed with Euler and TLNS equations. The influence of the initial constraints on the geometry and aerodynamics of the optimized shape has been explored. Various final shapes generated for an identical initial problem formulation but with different optimization path options (coarse or fine grid, Euler or TLNS), have been aerodynamically evaluated via a common fine-grid TLNS-based analysis. The initial constraint conditions show significant bearing on the optimization results. Also, the results demonstrate that to produce an aerodynamically efficient design, it is imperative to include the viscous physics in the optimization procedure with the proper resolution. Based upon the present results, to better utilize the scarce computational resources, it is recommended that, a number of viscous coarse grid cases using either a preconditioned bi-conjugate gradient (PbCG) or an alternating-direction-implicit (ADI) method, should initially be employed to improve the optimization problem definition, the design space and initial shape. Optimized shapes should subsequently be analyzed using a high fidelity (viscous with fine-grid resolution) flow analysis to evaluate their true performance potential. Finally, a viscous fine-grid-based shape optimization should be conducted, using an ADI method, to accurately obtain the final optimized shape.

Pandya, Mohagna J.↗

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Analytical Instrument for Determining the Composition of Surface Materials and Ices in the Solar System: Mini-CIDEX to TIDE

Exobiology experiments onboard spacecraft or space probes often require the detection and identification of a wide range of chemical species over vast concentration ranges. These experiments must be carried out under severely limited conditions utilizing minimal resources. The mini-Cometary Ice and Dust Experiment (mini-CIDEX) instrument was developed for the chemical analysis of a cometary environment. It combined a Gas Chromatograph (GC) with a helium-based Ion Mobility Spectrometer (IMS) to fulfill the analytical requirements of a cometary exobiology mission: universal response; ppb sensitivity; low mass, volume, and consumables. Mini-CIDEX has evolved into the Titan Ice and Dust Experiment (TIDE) for the chemical analysis of the surface (liquid and solid) and lower atmosphere of Titan. The complexity of the analyses will be similar to the comet application with a heavier emphasis on organic molecules. TIDE is a component of the Titan Orbiter Aero-Rover Mission (TOAM) proposed to NASA's New Visions Program. Advances to the Mini-CIDEX technology for the Titan application and the analytical capabilities of TIDE will be presented.

Kojiro, Daniel R.↗

Analytical Tools to Assess Polymer Biodegradation: A Critical Review and Recommendations

Many petroleum-derived plastic materials are highly recalcitrant and persistent in the environment, posing significant threats to human and ecological receptors due to their accumulation in ecosystems. In recent years, research efforts have focused on advancing biological methods for polymer degradation. Enzymatic depolymerization has emerged as particularly relevant for biobased plastic recycling, potentially scalable for industrial use. Biodegradation involves adsorption to the plastic solid surface, followed by an interfacial reaction, resulting in cleavage of bonds of polymer chains exposed on the surface. Here, widely varying substrate-specific kinetics are observed, with the polymer’s properties possessing a significant impact on the rate of this interfacial catalysis. Thus, there is a critical need for sensitive and accurate characterization of the material surface during and after interfacial depolymerization to fully understand the reaction mechanisms. Here, we provide a critical review of a range of techniques used in the analysis of material surfaces to characterize the chemical, topological, and morphological features relevant to the study of enzymatic biocatalysis, including microscopy techniques, spectroscopic techniques (e.g., X-ray diffraction analysis, Fourier transform infrared attenuated total reflectance spectroscopy, and mass spectrometry detection of analytes associated with degradation). Techniques for evaluation of surface energy and topology in their relevancy for sensitive detection of biological surface modifications are also discussed. In addition, this paper provides an overview of the strengths of these techniques and compares their performance in both sensitivity and throughput, including emerging techniques, which can be useful, particularly for the rapid analysis of the surface properties of polymeric materials in high-throughput screening of candidate biocatalysts. This research serves as a starting point in selecting and applying appropriate methodologies that provide direct evidence to the ongoing biotic degradation of polymeric materials.

Colachis, Matthew↗

A novel framework for hosting capacity analysis with spatio-temporal probabilistic voltage sensitivity analysis

Smart grids are envisioned to accommodate high penetration of distributed photovoltaic (PV) generation, which may cause adverse grid impacts in terms of voltage violations. Therefore, PV Hosting capacity is being used as a planning tool to determine the maximum PV installation capacity that causes the first voltage violation and above which would require infrastructure upgrades. Additionally, traditional methods of Hosting capacity analysis are scenario based and computationally complex as they rely on iterative load flow algorithms that require investigating a large number of scenarios for accurate assessment of PV impacts. Therefore, this paper presents a computationally efficient analytical approach to compute the probability distribution of voltage change due to random behavior of randomly located multiple distributed PVs. The proposed approach is based on Spatio-temporal probabilistic voltage sensitivity analysis that exploits both spatial and temporal uncertainties associated with PV injections. Thereafter, the derived distribution is used to quantify voltage violations for various PV penetration levels and subsequently determine the hosting capacity of the system without the need to examine large number of scenarios. Results of the proposed framework are validated via conventional load flow based simulation approach on the IEEE 37 and IEEE 123 node test systems.

42 ENGINEERING↗

Advancing xEMU Lunar Dust Mitigation Devices

Fine, electrically charged, glass like dust particles caused significant damage to the Apollo EMU9 during lunar EVAs, identified as one of the greatest challenges to future exploration. Passive Lunar Dust Mitigation Devices (LDMD) were developed, within a SBIR Phase II, to prohibit this dust from interrupting venting space suit component operation. A Computational Fluid-Dynamics and Discrete Element Method (CFD-DEM) Simulation Tool was developed at the University of Colorado, Boulder to predict venting gas flow ability to self-clean adhered dust particles from LDMD surfaces. Lunar dust properties (i.e., adhesion and cohesion strengths) required to complete Simulation Tool analysis are relatively unknown due to considerable differences between the Earth and the Moon (i.e., gravity, humidity) and due to an absence of dust particles in their native state. Analytically determining gas flow velocity, density and direction within the fluid Boundary Layer, microns from LDMD surfaces presented a second challenge. Dusty Plasma Chamber testing is being performed at Auburn University, Auburn to observe electrostatically charged dust behavior as it adheres to LDMD prototypes and specific geometry and is then blown away by metered gas flow. Test articles were developed to offer insight into the impact of different flow geometries, surface roughness and dust removal within the gas Boundary-Layer. Observed dust behavior is currently being developed to support the CFD-DEM analysis. Many Simulation Tool analytical cases have been processed to support the intention of completing sensitivity studies to assess how different dust adherence values and Boundary Layer fluid properties impact LDMD self-cleaning effectivity.

Thomas J Stapleton↗

Energy-balance climate models

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

North, G. R.↗

Energy balance climate models

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

North, G. R.↗

Error budget analysis for advanced X-ray Astrophysics Facility (AXAF)

The AXAF telescope was analytically investigated during the period from September 1979 to March 1980. The results of a performance evaluation in the presence of aligment errors and surface defects, a sensitivity analysis of every individual subsystem, and a diffraction analysis of the telescope assembly are presented.

Korsch, D.↗

New insights into the drainage of inundated ice-wedge polygons using fundamental hydrologic principles

Abstract. The pathways and timing of drainage from the inundated centers of ice-wedge polygons in a warming climate have important implications for carbon flushing, advective heat transport, and transitions from methane to carbon dioxide dominated emissions. Here, we expand on previous research using a recently developed analytical model of drainage from a low-centered polygon. Specifically, we perform (1) a calibration to field data identifying necessary model refinements and (2) a rigorous model sensitivity analysis that expands on previously published indications of polygon drainage characteristics. This research provides intuition on inundated polygon drainage by presenting the first in-depth analysis of drainage within a polygon based on hydrogeological first principles. We verify a recently developed analytical solution of polygon drainage through a calibration to a season of field measurements. Due to the parsimony of the model, providing the potential that it could fail, we identify the minimum necessary refinements that allow the model to match water levels measured in a low-centered polygon. We find that (1) the measured precipitation must be increased by a factor of around 2.2, and (2) the vertical soil hydraulic conductivity must decrease with increasing thaw depth. Model refinement (1) accounts for runoff from rims into the ice-wedge polygon pond during precipitation events and possible rain gauge undercatch, while refinement (2) accounts for the decreasing permeability of deeper soil layers. The calibration to field measurements supports the validity of the model, indicating that it is able to represent ice-wedge polygon drainage dynamics. We then use the analytical solution in non-dimensional form to provide a baseline for the effects of polygon aspect ratios (radius to thaw depth) and coefficient of hydraulic conductivity anisotropy (horizontal to vertical hydraulic conductivity) on drainage pathways and temporal depletion of ponded water from inundated ice-wedge polygon centers. By varying the polygon aspect ratio, we evaluate the relative effect of polygon size (width), inter-annual increases in active-layer thickness, and seasonal increases in thaw depth on drainage. The results of our sensitivity analysis rigorously confirm a previous analysis indicating that most drainage through the active layer occurs along an annular region of the polygon center near the rims. This has important implications for transport of nutrients (such as dissolved organic carbon) and advection of heat towards ice-wedge tops. We also provide a comprehensive investigation of the effect of polygon aspect ratio and anisotropy on drainage timing and patterns, expanding on previously published research. Our results indicate that polygons with large aspect ratios and high anisotropy will have the most distributed drainage, while polygons with large aspect ratios and low anisotropy will have their drainage most focused near their periphery and will drain most slowly. Polygons with small aspect ratios and high anisotropy will drain most quickly. These results, based on parametric investigation of idealized scenarios, provide a baseline for further research considering the geometric and hydraulic complexities of ice-wedge polygons.

Harp, Dylan R. (ORCID:0000000197778000)↗

Uncertainty propagation and sensitivity analysis for constrained optimization of nuclear waste vitrification

Abstract The vitrification of high‐level waste (HLW) by heating a mixture of glass‐forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses. UP is the effort of propagating uncertain inputs through a system to understand and quantify output distributions. Uncertainty intervals are crafted from output distributions to inform the optimization algorithm. UP is often implemented with Monte Carlo (MC) sampling for large nonlinear systems, which can be difficult to implement within a constrained optimization algorithm that requires derivative information. Other UP methods often used for optimization under uncertainty (OUU) can be designed to work within an established constrained optimization framework. Methods of UP are evaluated in this study including iterative sampling approaches, first‐order approximations, and surrogate modeling with machine learning (ML). A method of dimensional reduction based on global sensitivity analysis is introduced to support the UP methods for the large dimensionality of the problem. Analytical UP methods able to achieve similar optimums 10 times faster than the baseline MC approach, and produce 93.9% similar output distributions are reported.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A research program in active control/aeroelasticity in the JIAFS at NASA Langley Research Center

A control law synthesis methodology for multifunctional active control system to satisfy root-mean-square load and response constraints as well as to meet stability robustness requirements at plant input and output was developed. Modern control theory, singular value analysis and optimization techniques were utilized. All stability and response derivative expressions were derived analytically for sensitivity study. The software is incorporated as an update to the AB/LAD general control design software package PADLOCS.

Whitesides, J. L.↗

Reconnection voltage as a function of IMF clock angle

Magnetic reconnection between the IMF and the geomagnetic field is thought to play a major role in the transfer of solar wind momentum and energy to the magnetosphere. Both analytic modeling and analysis of geophysical data have shown that this coupling process should be a sensitive function of the clock angle of the IMF. Results are presented from a three-dimensional, MHD, global numerical simulation code for the reconnection voltage between the closed geomagnetic field and the IMF as a function of the IMF clock angle. These results are consistent with a sin(theta/2) functional behavior.

Fedder, J. A.↗