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Results for “Sequential 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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

CMM Sequential Analysis Program

This report documents a design agency (DA) method to evaluate coordinate measuring machine (CMM) data by constructing an algorithm that is equivalent to the production agency (PA) algorithm for processing the raw CMM data. Several refinements of the CMM analyses were implemented at both the PA and the DA to process inherent limitations of the raw data, such as the absence of measurements at the exact ends of the connector-adapter assembly (CAA) and the recovery from these limitations through (worst-case) adjustments to the the positional errors. Also, inherent errors of the CMM measurements were accommodated by introducing a guard band, which effectively lowered the tolerance so that the CMM code could not pass bad parts. The DA and the PA showed remarkable agreement in all areas of analysis. The ultimate comparison is shown in Figures 13a and 13b, where the effect of using a guard band and end adjustments to the CMM measurements were clearly shown.

42 ENGINEERING↗
DOE OSTI2021

Systematic investigations on iron cycling in phosphorus/siderophore systems: Synergism or antagonism?

Synergisms between microbial exudates on Fe (hydr)oxide dissolution as an effective Fe acquisition pathway have been recently addressed and vigorously debated. However, Fe liberation mechanisms and where siderophores and phosphorus (P) coexist received little attentions. Current study systematically investigated ferrihydrite dissolution in the presence of desferrioxamine B (DFOB) (a kind of fungally-derived siderophores) and inorganic/organic phosphorus (orthophosphate, Pi; myo-inositol hexaphosphate, IHP), as a function of solute pH, reaction time and reagent content. Reacted solids were characterized by N 2 -BET adsorption, zeta (ζ) potential analysis, sequential extraction analysis (SEDEX), field emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HRTEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), micro Raman spectroscopy and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR). Our results indicate that upon reaction with P-only or (DFOB + P) systems, interfacial complexation partially switched from monolayer bidentate-binuclear surface complexes to ternary complexes, or laterally transformed into amorphous Fe–P precipitates. The Fe-Pi complex precipitated more readily under acidic conditions, and Fe-IHP complex preferentially nucleated in neutral-alkaline environments. Phosphorus slightly promoted Fe release from minerals and fixation to the leached layer or interfacial liquid zone initially, but subsequently prevented further attacks from protons and DFOB. The co-effects of P and DFOB likely correspond to two successive scenarios: 1) DFOB is preferentially attracted toward ferrihydrite surfaces by negative electrical fields induced by adsorbed phosphorus and can act synergistically with labile P–Fe complexes, resulting in intensive temporal dissolution of Fh; 2) subsequent Fe shuttling to DFOB can be prohibited by stabilized, passive P/Fe–P layers. Finally, our results emphasize the antagonism between P compounds and siderophores (i.e., DFOB here) on ferrihydrite dissolution to improve understanding of the biologically-mediated Fe cycling in natural systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Design, fabrication and test of a pneumatically controlled, renewable, microfluidic bead trapping device for sequential injection analysis applications

This paper describes the design, fabrication, and testing of a pneumatically controlled,renewable, microfluidic device for conducting bead-based assays in an automated sequential injection analysis system. The device used a “brick wall”-like pillar array (pillar size: 20 μm length X 50 μm width X 45 μm height) with 5 μm gaps between the pillars serving as the micro filter. The flow channel where bead trapping occurred is 500 μm wide X 75 μm deep. An elastomeric membrane and an air chamber were located underneath the flow channel. By applying pressure to the air chamber, the membrane is deformed and pushed upward against the filter structure. This effectively traps beads larger than 5 μm and creates a “bed” or micro column of beads that can be perfused and washed with liquid samples and reagents. Upon completion of the assay process, the pressure is released and the beads are flushed out from underneath the filter structure to renew the device. Mouse IgG was used as a model analyte to test the feasibility of using the proposed device for immunoassay applications. Resulting microbeads from an on-chip fluorescent immunoassay were individually examined using flow cytometry. The results show that the fluorescence signal intensity distribution is fairly narrow indicating high chemical reaction uniformity among the beads population. Electrochemical onchip assay was also conducted. A detection limit of 0.1 ng/mL1 ppb was achieved and good device reliability and repeatability were demonstrated. The novel microfluidic-based beadstrapping device thus opens up a new pathway to design micro-bead based biosensor immunoassays for clinical and othervarious applications.

beads trapping↗
NASA NTRS1970

Tracking and navigational accuracy analysis

Sequential estimation with process noise for processing DSN tracking data during planetary orbiter missions and Doppler determinations of polar motion using satellites

Source record↗
NASA NTRS2016

Uncertainty Reduction using Bayesian Inference and Sensitivity Analysis: A Sequential Approach to the NASA Langley Uncertainty Quantification Challenge

This paper presents a computational framework for uncertainty characterization and propagation, and sensitivity analysis under the presence of aleatory and epistemic un- certainty, and develops a rigorous methodology for efficient refinement of epistemic un- certainty by identifying important epistemic variables that significantly affect the overall performance of an engineering system. The proposed methodology is illustrated using the NASA Langley Uncertainty Quantification Challenge (NASA-LUQC) problem that deals with uncertainty analysis of a generic transport model (GTM). First, Bayesian inference is used to infer subsystem-level epistemic quantities using the subsystem-level model and corresponding data. Second, tools of variance-based global sensitivity analysis are used to identify four important epistemic variables (this limitation specified in the NASA-LUQC is reflective of practical engineering situations where not all epistemic variables can be refined due to time/budget constraints) that significantly affect system-level performance. The most significant contribution of this paper is the development of the sequential refine- ment methodology, where epistemic variables for refinement are not identified all-at-once. Instead, only one variable is first identified, and then, Bayesian inference and global sensi- tivity calculations are repeated to identify the next important variable. This procedure is continued until all 4 variables are identified and the refinement in the system-level perfor- mance is computed. The advantages of the proposed sequential refinement methodology over the all-at-once uncertainty refinement approach are explained, and then applied to the NASA Langley Uncertainty Quantification Challenge problem.

Uncertainty↗
NASA NTRS1974

Sequential decision analysis for nonstationary stochastic processes

A formulation of the problem of making decisions concerning the state of nonstationary stochastic processes is given. An optimal decision rule, for the case in which the stochastic process is independent of the decisions made, is derived. It is shown that this rule is a generalization of the Bayesian likelihood ratio test; and an analog to Wald's sequential likelihood ratio test is given, in which the optimal thresholds may vary with time.

Schaefer, B.↗
NASA NTRS1999

Data Assimilation in the Presence of Forecast Bias: The GEOS Moisture Analysis

We describe the application of the unbiased sequential analysis algorithm developed by Dee and da Silva (1998) to the GEOS DAS moisture analysis. The algorithm estimates the persistent component of model error using rawinsonde observations and adjusts the first-guess moisture field accordingly. Results of two seasonal data assimilation cycles show that moisture analysis bias is almost completely eliminated in all observed regions. The improved analyses cause a sizable reduction in the 6h-forecast bias and a marginal improvement in the error standard deviations.

Dee, Dick P.↗
NASA NTRS1991

A sequential approach to multivariable stability robustness analysis

In sequential loop closure, the importance of evaluating the stability and stability robustness at the intermediate loop closures is well known, yet how the stability and stability robustness evaluated at the intermediate steps contribute to the stability and stability robustness of the overall feedback system must be developed. An analysis of the complete feedback system reveals the multivariable Nyquist contributions from the intermediate loop closures. It is also shown that the results greatly simplify if frequency separation exists between the intermediate loops. The analysis is presented with a two-step loop closure procedure using 'inner' and 'outer' loops which can be generalized to multi-step situations. The control of the longitudinal dynamics of an aircraft is addressed to further clarify and demonstrate the results.

Newman, Brett↗
NASA NTRS1971

Analysis of lunar samples for carbon compounds.

Description of one approach to the analysis for carbon compounds in lunar materials from the Apollo 11 mission. The sequential scheme followed generally accepted organic geochemical practices, but was unusual in its application to a single sample. The procedures of the scheme were designed to minimize handling of the solids and extracts or hydrolysates. The solid lunar sample was retained in all steps of the sequential analysis in the vessel in which it was originally placed. Centrifugation was used to separate solid and liquid phases after extraction or refluxing. Liquids were recovered from solids by decantation.

Kvenvolden, K. A.↗
NASA NTRS1981

Comparison between variable and fixed dwell-time PN acquisition algorithms

Pseudo noise (PN) spread spectrum systems require a very accurate alignment between the PN code epochs at the transmitter and receiver. This synchronism is typically established through a two-step algorithm, including a coarse synchronization procedure and a fine synchronization procedure. A standard approach for the coarse synchronization is a sequential search over all code phases. The measurement of the power in the filtered signal is used to either accept or reject the code phase under test as the phase of the received PN code. This acquisition strategy, called a single dwell-time system, has been analyzed by Holmes and Chen (1977). A synopsis of the field of sequential analysis as it applies to the PN acquisition problem is provided. From this, the implementation of the variable dwell time algorithm as a sequential probability ratio test is developed. The performance of this algorithm is compared to the optimum detection algorithm and to the fixed dwell-time system.

Braun, W. R.↗
DOE OSTI2017

Fully vs. Sequentially Coupled Loads Analysis of Offshore Wind Turbines

The design and analysis methods for offshore wind turbines must consider the aerodynamic and hydrodynamic loads and response of the entire system (turbine, tower, substructure, and foundation) coupled to the turbine control system dynamics. Whereas a fully coupled (turbine and support structure) modeling approach is more rigorous, intellectual property concerns can preclude this approach. In fact, turbine control system algorithms and turbine properties are strictly guarded and often not shared. In many cases, a partially coupled analysis using separate tools and an exchange of reduced sets of data via sequential coupling may be necessary. In the sequentially coupled approach, the turbine and substructure designers will independently determine and exchange an abridged model of their respective subsystems to be used in their partners' dynamic simulations. Although the ability to achieve design optimization is sacrificed to some degree with a sequentially coupled analysis method, the central question here is whether this approach can deliver the required safety and how the differences in the results from the fully coupled method could affect the design. This work summarizes the scope and preliminary results of a study conducted for the Bureau of Safety and Environmental Enforcement aimed at quantifying differences between these approaches through aero-hydro-servo-elastic simulations of two offshore wind turbines on a monopile and jacket substructure.

17 WIND ENERGY↗
DOE OSTI2020

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. Here, we have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ~77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗