Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Dimensionality Selection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

Surface Flow Visualization of the High-Lift Common Research Model

A 10% scale version of the High-Lift Common Research Model (CRM-HL) was tested in the NASA Langley 14- by 22-Foot Subsonic Tunnel (14x22) in support of the NASA Advanced Air Transport Technology (AATT) Project. The CRM-HL experiment included various configurations such as conventional and simple-hinged flaps, with and without engine nacelle/pylon, with and without nacelle chine, different Active Flow Control (AFC) methods (sweeping jets, alternating pulsed jets, and preconditioned boundary layer blowing), and their various parameters. This particular study is focused on the surface flow visualization of the conventional CRM-HL model at landing configuration. The conventional CRM-HL model with the single-slotted Fowler flap system serves as a baseline for the AFC-enabled simplified high-lift configuration as well as a high-lift technology development platform due to its publicly open geometry. Surface flow visualizations were performed using fluorescent minitufts, which were found to be nonintrusive to the aerodynamic performance. Tuft flow visualizations are supplemented with the relevant pressure and force measurements in order to understand the flow characteristics developed on the conventional CRM- HL model. In addition, three dimensional, unsteady, compressible Computational Fluid Dynamic (CFD) simulations were performed for selective cases. The surface streamlines and transverse velocity fluctuations obtained by the CFD simulations are qualitatively compared to the tuft direction and tuft unsteadiness, respectively. Force measurements of the CRM-HL model show performance degradation at higher angles of attack. Surface flow visualizations revealed the performance loss due to the nacelle/pylon wake that grows with angle of attack and eventually promotes flow separation over the inboard wing. This performance loss was successfully recovered by placing a chine on the engine nacelle.

Koklu, Mehti↗

TPSAS-NF1676L-15438-DND

Additive manufacturing is a family of processing methods that selectively add material in order to directly create a three-dimensional part directly from a computer model. NASA Langley Research Center is currently investigating electron beam freeform fabrication (EBF3) as a means for making large scale components (>1 m) for a variety of aerospace applications.

Craig A Brice↗

AUTOMATIC LIMIT SURFACE SEARCH FOR PWR TRANSIENTS BY RELAP5-3D/RAVEN CODES

Deterministic safety analysis of nuclear power plants can be improved by applying modern algorithms and codes exploiting machine learning and parallel computing. In this paper we show the application of some of these advanced methodologies for the determination of limit surfaces. A limit surface is an n-dimensional surface describing the plant status, e.g. identifying, as function of selected plant parameters, the boundaries between failed and safe conditions for the core fuel. Using the RELAP5-3D system thermal-hydraulic code coupled to the RAVEN statistical-analysis code, we show how to apply machine-learning algorithms (near-neighbor, support-vector machine, etc.) for determining relevant limit surfaces for PWR station-blackout and loss of offsite power. As a first step, a set of training simulations is run to sample the nuclear power plant responses. Those calculations are used to train a Reduced-Order-Model (ROM), which RAVEN then uses for determining an approximated limit surface. Verification of the guessed limit surface is then automatically performed and calculation is terminated depending by the chosen convergence criteria. The combination of High Performance Computing (HPC) and ROMs allow a remarkable reduction of the time required for the surface determination. RAVEN performs also the automatic data collection of the output of the numerous runs, thus easing the workload of the safety analyst. Finally, using RAVEN “Ensamble Forward” sampling technique, we show how to inform the limit surface calculations with some of the code and input uncertainties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Amine-functionalized porous organic polymers for carbon dioxide capture

Recent developments in CO 2 capture using porous organic polymers (POPs) have received accrescent attention due to their sorbent properties such as high CO 2 uptake capacity and selectivity, tunable chemical structure and permanent porosity. POPs are constructed using two and/or three-dimensional organic monomers (building blocks) linked to each other through covalent bonding, creating high porosity. The pore structure in POPs is exceptionally stable, which leads to their cyclable CO 2 adsorption performance. However, POPs generally suffer from low CO 2 uptake and selectivity due to their interaction with CO 2 in physisorption limits (20–40 kJ mol -1 ). Similar to that in other physisorbents, the CO 2 uptake capacity of POPs further decreases under humid conditions. Pursuant to these limitations, amine functionalization in POPs has resulted in enhanced CO 2 uptake performance with improved CO 2 selectivity over non-polar gases such as N 2 . More importantly, several types of amine-functionalized POPs showed that the CO 2 uptake could remain intact under humid conditions such as in post-combustion flue gas. This review article covers recent developments in amine-functionalized porous organic polymers. Three main categories of amine functionalization, such as direct amine synthesis, amine impregnation and amine grafting, were investigated in detail by considering the effect of amines on the sorbent properties and CO 2 capture performance of POPs. The recent findings in amine-functionalized POPs were investigated including porous polymeric networks (PPNs), covalent organic frameworks (COFs), amine linked POPs, hyper-crosslinked polymers (HCPs), conjugated microporous polymers (CMPs), benzimidazole linked polymers (BILPs), porous aromatic frameworks (PAFs) and polymers of intrinsic microporosity (PIMs).

36 MATERIALS SCIENCE↗

K + block is the mechanism of functional asymmetry in bacterial Na v channels

Crystal structures of several bacterial Na v channels have been recently published and molecular dynamics simulations of ion permeation through these channels are consistent with many electrophysiological properties of eukaryotic channels. Bacterial Na v channels have been characterized as functionally asymmetric, and the mechanism of this asymmetry has not been clearly understood. To address this question, we combined non-equilibrium simulation data with two-dimensional equilibrium unperturbed landscapes generated by umbrella sampling and Weighted Histogram Analysis Methods for multiple ions traversing the selectivity filter of bacterial Na v Ab channel. This approach provided new insight into the mechanism of selective ion permeation in bacterial Nav channels. The non-equilibrium simulations indicate that two or three extracellular K + ions can block the entrance to the selectivity filter of Na v Ab in the presence of applied forces in the inward direction, but not in the outward direction. The block state occurs in an unstable local minimum of the equilibrium unperturbed free-energy landscape of two K+ ions that can be ‘locked’ in place bymodest applied forces. In contrast to K + , three Na + ions move favorably through the selectivity filter together as a unit in a loose “knock-on” mechanism of permeation in both inward and outward directions, and there is no similar local minimum in the two-dimensional free-energy landscape of two Na + ions for a block state. The useful work predicted by the non-equilibrium simulations that is required to break the K + block is equivalent to large applied potentials experimentally measured for two bacterial Na v channels to induce inward currents of K + ions. Here, these results illustrate how inclusion of non-equilibrium factors in the simulations can provide detailed information about mechanisms of ion selectivity that is missing from mechanisms derived from either crystal structures or equilibrium unperturbed free-energy landscapes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations

Background Diagnostic errors can occur, in infectious diseases, when anti-microbial immune responses involve several temporal scales. When responses span from nanosecond to week and larger temporal scales, any pre-selected temporal scale is likely to miss some (faster or slower) responses. Hoping to prevent diagnostic errors, a pilot study was conducted to evaluate a four-dimensional (4D) method that captures the complexity and dynamics of infectious diseases. Methods Leukocyte-microbial-temporal data were explored in canine and human (bacterial and/or viral) infections, with: (i) a non-structured approach, which measures leukocytes or microbes in isolation; and (ii) a structured method that assesses numerous combinations of interacting variables. Four alternatives of the structured method were tested: (i) a noise reduction oriented version, which generates a single (one data point-wide) line of observations; (ii) a version that measures complex, three-dimensional (3D) data interactions; (iii) a non-numerical version that displays temporal data directionality (arrows that connect pairs of consecutive observations); and (iv) a full 4D (single line-, complexity-, directionality based) version. Results In all studies, the non-structured approach revealed non-interpretable (ambiguous) data: observations numerically similar expressed different biological conditions, such as recovery and lack of recovery from infections. Ambiguity was also found when the data were structured as single lines. In contrast, two or more data subsets were distinguished and ambiguity was avoided when the data were structured as complex, 3D, single lines and, in addition, temporal data directionality was determined. The 4D method detected, even within one day, changes in immune profiles that occurred after antibiotics were prescribed. Conclusions Infectious disease data may be ambiguous. Four-dimensional methods may prevent ambiguity, providing earlier, in vivo, dynamic, complex, and personalized information that facilitates both diagnostics and selection or evaluation of anti-microbial therapies.

59 BASIC BIOLOGICAL SCIENCES↗

Hierarchically MoS2 nanospheres assembled from nanosheets for superior CO gas-sensing properties

Highlights: • Preparation of 3D Hierarchical large surface area MoS{sub 2} nanospheres from nansheets. • The efficient enhanced gas-sensing response of 92.6 at 500 ppm for CO at 230 °C. • Higher selectivity towards CO than other gases at different temperature ranges. - Abstract: Hierarchical three dimensional MoS{sub 2}nanostructures composed of small sheet-like nanostructures are successfully prepared using a simple two-step hydrothermal process with sodium dodecyl sulfate (SDS), as a surface modifier. The as-preparedMoS{sub 2}nanospheres are characterized by XRD, BET, XPS, EDS, SEM and HRTEM. The gas–sensing properties of as–prepared MoS{sub 2}nanostructures are tested at 175–230 °C temperatures for 50–500 ppm concentration range, using an efficient ceramic-tube sensor system via an intelligent gas testing system. A high response and selectivity towards carbon monoxide than other gases is observed. Comparative studies of MoS{sub 2}nanostructures for different concentration of carbon monoxide gas and definite sensor-stability for different gases are studied, as well. The sensor fabrication and sensing mechanism is discussed as well.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of -4.14 +/- 0.76 MgC/hay. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.

Pinage, Ekena Rangel↗

Theory-Guided Machine Learning in Materials Science

Materials scientists are increasingly adopting the use of machine learning tools to discover hidden trends in data and make predictions. Applying concepts from data science without foreknowledge of their limitations and the unique qualities of materials data, however, could lead to errant conclusions. The differences that exist between various kinds of experimental and calculated data require careful choices of data processing and machine learning methods. Here, we outline potential pitfalls involved in using machine learning without robust protocols. We address some problems of overfitting to training data using decision trees as an example, rational descriptor selection in the field of perovskites, and preserving physical interpretability in the application of dimensionality reducing techniques such as principal component analysis. We show how proceeding without the guidance of domain knowledge can lead to both quantitatively and qualitatively incorrect predictive models.

36 MATERIALS SCIENCE↗

Conformationally Adaptable Extractant Flexes Strong Lanthanide Reverse-Size Selectivity

Chemical selectivity is traditionally understood in the context of rigid molecular scaffolds with precisely defined local coordination and chemical environments that ultimately facilitate a given transformation of interest. By contrast, nature leverages dynamic structures and strong coupling to enable specific interactions with target species in otherwise complex media. Taking inspiration from nature, we demonstrate unconventional selectivity in the solvent extraction of light over heavy lanthanides using a conformationally flexible ligand called octadecyl acyclopa (ODA). This novel ligand forms pseudocyclic molecular complexes with lanthanide ions at organic/aqueous interfaces, revealed by vibrational sum frequency generation spectroscopy. These complexes are extracted into the organic phase, where femtosecond structural dynamics are probed by two-dimensional infrared spectroscopy and ab initio molecular dynamics simulations to mechanistically frame the macroscopic selectivity trends. We find larger-than-expected structural fluctuations and bond lengths for heavy Ln–ODA complexes that arise from an inability of ODA to contort around the smaller ions to satisfy all would-be bonding interactions, despite forming some individually strong bonds. This finding contrasts with the binding of ODA with lighter lanthanides where, despite individually weaker bonds, collective interactions manifest that minimize structural fluctuations and give rise to enhanced thermodynamic stability. Furthermore, these results point to a new paradigm where conformational dynamics and cumulative bonding interactions can be used to facilitate unconventional chemical transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Feature Selection and Inferential Procedures for Video Data [Slides]

With the rise of electronic and high-dimensional data, new and innovative feature detection and statistical methods are required to perform accurate and meaningful statistical analysis of these datasets that provide unique statistical challenges. In the area of feature detection, much of the recent feature detection research in the computer vision community has focused on deep learning methods, which require large amounts of labeled training data. However, in many application areas, training data is very limited and often difficult to obtain. We develop methods for fast, unsupervised, precise feature detection for video data based on optical flows, edge detection, and clustering methods. We also use pretrained neural networks and interpretable linear models to extract features using very limited training data. In the area of statistics, while high-dimensional data analysis has been a main focus of recent statistical methodological research, much focus has been on populations of high-dimensional vectors, rather than populations of high-dimensional tensors, which are three-dimensional arrays that can be used to model dependent images, such as images taken of the same person or ripped video frames. Our feature detection method is a non-model-based method that fusses information from dense optical flow, raw image pixels, and frame differences to generate detections. Our hypothesis testing methods are based on the assumption that dependent images are concatenated into a tensor that follows a tensor normal distribution, and from this assumption, we derive likelihood-ratio, score, and regression-based tests for one- and multiple-sample testing problems. Our methods will be illustrated on simulated and real datasets. We conclude this report with comments on the relationship between feature detection and hypothesis testing methods.

97 MATHEMATICS AND COMPUTING↗

Investigation of adaptive-wall wind tunnels with two measured interfaces

An adaptive wall wind tunnel with two measured interfaces has been studied using two interface static pressure measurements near the tunnel walls. An iterative procedure with static pressure measurements on two interfaces is described. The functional relationships of static pressure on two measured interfaces for the exterior region are presented. The convergence of the selected iterative procedure is proved analytically. The one-step convergence formulae are obtained and validated by the simulation of a numerical wind tunnel. Experimental investigation has been conducted with a two-dimensional airfoil model of NASA 0012 at a supercritical Mach number. The results have indicated that the selected procedure is feasible to speed up the flow convergence to the unconfined condition in applying the one-step convergence formulae.

Lo, C. F.↗

Effect of scanline orientation on ventricular flow propagation: assessment using high frame-rate color Doppler echocardiography

Color M-mode echocardiography has recently been utilized to describe diastolic flow propagation velocity (Vp) in the left ventricle. While increasing temporal resolution from 15 to 200 Hz, this M-mode technique requires the user to select a single scanline, potentially limiting quantification of Vp due to the complex three-dimensional inflow pattern. We previously performed computational fluid dynamics simulations to demonstrate the insignificance of the scanline orientation, however geometric complexity was limited. The purpose of this study was to utilize high frame-rate 2D color Doppler images to investigate the importance of scanline selection in patients for the quantification of Vp. 2D color Doppler images were digitally acquired at 50 frames/s in 6 subjects from the apical 4-chamber window (System 5, GE/Vingmed, Milwaukee, WI). Vp was determined for a set of scanlines positioned through 5 locations across the mitral annulus (from the anterior to posterior mitral annulus). An analysis of variance was performed to examine the differences in Vp as a function of scanline position. Vp was not effected by scanline position in sampled locations from the center of the mitral valve towards the posterior annulus. Although not statistically significant, there was a trend to slower propagation velocities on the anterior side of the valve (60.8 +/- 16.7 vs. 54.4 +/- 13.6 cm/s). This study clinically validates our previous numerical experiment showing that Vp is insensitive to small perturbations of the scanline through the mitral valve. However, further investigation is necessary to examine the impact of ventricular geometry in pathologies including dilated cardiomyopathy.

Non-NASA Center↗

Design, fabrication, and test of a Graphite/Epoxy Metering Shell (GEMS)

A program to design, fabricate and test a dimensionally stable metering structure in support of the large space telescope (LST) program is discussed. Graphite/epoxy was the material selected as the only viable candidate material which can meet the stringent thermal expansion criteria of the LST. A metering shell was designed and fabricated, with emphasis on dimensional stability in conjunction with low cost. Thermal expansion test coupons extracted from the layups of the skin panels indicated the attainment of a coefficient of thermal expansion of 0.0666 micrometers/m K. Subsequent thermal vacuum chamber tests on the complete metering shell demonstrated an expansion of the 2.95-meter overall length of 0.27 micrometers/K. Static and dynamics tests, which demonstrated adequacy with respect to limit loads and stiffness, were also accomplished.

Source record↗

Electronic and catalytic engineering in two-dimensional vdW metal–organic frameworks through alloying

Bimetallic metal-organic framework (MOF s ) alloys, in which heterogeneous metal clusters are incorporated into their backbone, are capable of highly selective separations and catalysis. Due to limitations in our fundamental understanding of their alloying, however, established methods result in phase-separated or amorphous two-dimensional (2D) MOF s or lack precise control over alloy ratios. Here, our results demonstrate 2D MOF alloys where metal cation ratios (M 1 and M 2 ) in M 1 xM 2 1-x BDC (M 1 or M 2 = Zn, Cu, Ni, Co, Fe, Mn) can be engineered on demand by controlling the metal salt dissociation constants. Resulting MOF alloys exhibit a highly 2D nature with excellent crystallinity and minute control over metal cation ratios. Overall, our experimental and theoretical results show that their electronic bandgaps and photoexcited carrier lifetimes can be engineered by metal cation alloying. Interestingly, 2D alloyed MOF s enable high-efficiency photo-catalytic water reduction performance in Co/Ni MOF alloys owing to the spatially separated metal clusters in 2D MOF alloys.

2D materials↗

Technical properties of biomass and solid recovered fuel (SRF) co-fired with coal: Impact on multi-dimensional resource recovery value

The power plant sector is adopting the co-firing of biomass and solid recovered fuel (SRF) with coal in an effort to reduce its environmental impact and costs. Whereas this intervention contributes to reducing carbon emissions and those of other pollutants related with the burning of fossil fuel, it may also result in hidden impacts that are often overlooked. When co-firing, the physical and chemical properties of the mixed fuels and the subsequent technical implications on the process performance and by-products are significant. Interconnections between multiple values nested within four domains of value, i.e. environmental, economic, technical and social, mean that changes in the one domain (in the co-firing case, the technical one) can have considerable implications in the other domains as well. In this study, using a systematic and flexible approach to conceptualising multi-dimensional aspects associated with the co-firing of biomass and SRF with coal, we unveil examples of such interconnections and implications on overall value delivered through the use and recovery of waste resources. Such an analysis could underpin the selection of useful metrics (quantitative or semi-quantitative descriptors) for enabling a systemic multi-dimensional value assessment, and value’s distribution amongst interconnected parts of resource recovery systems; key in enabling sound analysis and decision-making.

09 BIOMASS FUELS↗

Development of a Numerical Modeling Approach for Buckling Analysis of Sandwich Composite Cylindrical Shells with Selected Results

The buckling response of geometrically perfect and imperfect cylindrical sandwich shells can be investigated using nonlinear finite element analyses with two-dimensional general-purpose shell elements. Such analyses are used in the NASA Engineering and Safety Center Shell Buckling Knockdown Factor Project, which has the goal of developing new analysis-based buckling design recommendations for select classes of sandwich composite cylindrical structures under uniaxial compressive load. As such, finite element models of sandwich composite cylinders were developed and analyses were performed to predict the buckling responses of geometrically perfect and imperfect sandwich composite cylinders. The development of the selected finite-element modeling approach for a sandwich composite cylinder is discussed. Buckling-response sensitivity of geometrically imperfect sandwich cylinders for various shell element types were investigated as part of this study. Preliminary results of geometric imperfections influence on buckling response of sandwich cylinders are also presented.

Structural Modeling↗

Evaluation of the robustness of the preprocessing technique improving reversible compressibility of CT images: Tested on various CT examinations

Purpose: To modify the preprocessing technique, which was previously proposed, improving compressibility of computed tomography (CT) images to cover the diversity of three dimensional configurations of different body parts and to evaluate the robustness of the technique in terms of segmentation correctness and increase in reversible compression ratio (CR) for various CT examinations.Methods: This study had institutional review board approval with waiver of informed patient consent. A preprocessing technique was previously proposed to improve the compressibility of CT images by replacing pixel values outside the body region with a constant value resulting in maximizing data redundancy. Since the technique was developed aiming at only chest CT images, the authors modified the segmentation method to cover the diversity of three dimensional configurations of different body parts. The modified version was evaluated as follows. In randomly selected 368 CT examinations (352 787 images), each image was preprocessed by using the modified preprocessing technique. Radiologists visually confirmed whether the segmented region covers the body region or not. The images with and without the preprocessing were reversibly compressed using Joint Photographic Experts Group (JPEG), JPEG2000 two-dimensional (2D), and JPEG2000 three-dimensional (3D) compressions. The percentage increase in CR per examination (CR{sub I}) was measured.Results: The rate of correct segmentation was 100.0% (95% CI: 99.9%, 100.0%) for all the examinations. The median of CR{sub I} were 26.1% (95% CI: 24.9%, 27.1%), 40.2% (38.5%, 41.1%), and 34.5% (32.7%, 36.2%) in JPEG, JPEG2000 2D, and JPEG2000 3D, respectively.Conclusions: In various CT examinations, the modified preprocessing technique can increase in the CR by 25% or more without concerning about degradation of diagnostic information.

62 RADIOLOGY AND NUCLEAR MEDICINE↗