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At least 631 records · Page 35

Simultaneous energy and mass calibration of large-radius jets with the ATLAS detector using a deep neural network

The energy and mass measurements of jets are crucial tasks for the Large Hadron Collider experiments. This paper presents a new calibration method to simultaneously calibrate these quantities for large-radius jets measured with the ATLAS detector using a deep neural network (DNN). To address the specificities of the calibration problem, special loss functions and training procedures are employed, and a complex network architecture, which includes feature annotation and residual connection layers, is used. The DNN-based calibration is compared to the standard numerical approach in an extensive series of tests. The DNN approach is found to perform significantly better in almost all of the tests and over most of the relevant kinematic phase space. In particular, it consistently improves the energy and mass resolutions, with a 30% better energy resolution obtained for transverse momenta $p$ T > $500$ GeV.

47 OTHER INSTRUMENTATION↗

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗

Influence of Solutocapillary Convection on Macrovoid Defect Formation in Polymeric Membranes

The focus of this research project involved the dry-cast process for polymeric membrane formation, whereby evaporation of solvent from an initially homogeneous polymer/solvent/ nonsolvent solution results in phase separation and the formation of polymer-rich and polymer-lean phases. Under certain conditions the polymer-lean phase gives rise to very large and usually undesirable, tear-drop-shaped pores (size approx. 10 - 50 microns) termed macrovoids (MVs). Although in many cases the presence of MV pores has deleterious effects on membrane performance, there are a number of innovative applications where the presence of such pores is highly desirable. Although researchers have proposed a variety of mechanisms for MV formation over the past three decades, two main hypotheses are currently favored: one asserts that MV growth can be attributed solely to diffusion (the diffusive growth hypothesis), whereas the other states that solutocapillary convection (the SC hypothesis) at the MV interface contributes to growth. The overall goal of this research was to obtain a more comprehensive understanding of the fundamental mechanism of MV growth. This research incorporates a coupled modeling and experimental approach to test a solutocapillary convection hypothesis for the growth of macrovoid pores in polymeric membranes. Specifically, we utilized a modification of the first principles model developed by two of the PIs (ARG and WBK) for dry-cast CA membranes. For the experimental component, two separate and mutually complementary approaches were used to study MV growth. In the first, membranes cast in a zero-g environment aboard the NASA KC-135 aircraft were compared with those cast on the ground to assess the effect of the buoyancy force on membrane morphology and MV size and shape. In the second approach, videomicroscopy flow visualization (VMFV) was utilized to observe MV formation and growth in real time and to assess the effect of surface tension on the MV growth dynamics. As a result of these fundamental studies, our research group advanced a new hypothesis for MV pore development in polymeric membranes.

Greenberg, Alan R.↗

Numerical simulation of compressible fluid-dynamics in the chamber of inertial fusion energy systems

Here, this paper aims to establish new and innovative modeling capabilities for analyzing chambers in Inertial Fusion Energy (IFE) systems. IFE is emerging as a promising method to achieve fusion power production, but several challenges must be overcome to develop an IFE pilot plant or deploy commercial IFE systems. These challenges are both theoretical and technical, encompassing a deeper understanding of the underlying physical phenomena and the development of new technologies and materials. One of the needs is to develop mathematical models to describe IFE systems and numerical tools to simulate them. This paper contributes to this endeavor by presenting a new OpenFOAM solver for IFE systems, focusing on gas dynamics in their chambers. The analysis and development of chamber designs will play a significant role in the transition from single-shot experiments to high-repetition rates, as there is a need to protect the chamber walls from the intense radiation fields produced by fusion reactions. A promising design option, normally referred to as thick wall chamber design, consists in using lithium or molten salt jet arrays within the chamber. A critical phenomenon is the venting of high-pressure gases from the center to the external part of the chamber, passing through the blanket array. This process involves the propagation and attenuation of strong pressure waves, requiring suitable modeling approaches for compressible fluid-dynamics. The solver proposed in this work implements a multi-material hydrodynamics model tailored to accurately describe the non-linear propagation of pressure waves while avoiding numerical oscillation issues typical of high-velocity compressible simulation. This solver is verified against numerical test cases, validated against experimental data, and applied to the analysis of the High-Yield Lithium-Injection Fusion-Energy (HYLIFE-I) concept. The relevance of this paper is threefold. Firstly, it contributes to developing and testing modeling approaches for compressible fluid-dynamics phenomena, with specific focus on the new and unexplored topic of IFE thick-liquid-wall blanket modeling. Secondly, it marks one of the first applications of the OpenFOAM library in the research field of IFE systems. Finally, the investigated problem is of practical interest for IFE developers, as it provides useful indications about relevant phenomena in pressure wave propagation in the chamber of these systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Comparative Ergonomic Evaluation of Spacesuit and Space Vehicle Design

With the advent of the latest human spaceflight objectives, a series of prototype architectures for a new launch and reentry spacesuit that would be suited to the new mission goals. Four prototype suits were evaluated to compare their performance and enable the selection of the preferred suit components and designs. A consolidated approach to testing was taken: concurrently collecting suit mobility data, seat-suit-vehicle interface clearances, and qualitative assessments of suit performance within the volume of a Multi-Purpose Crew Vehicle mockup. It was necessary to maintain high fidelity in a mockup and use advanced motion-capture technologies in order to achieve the objectives of the study. These seemingly mutually exclusive goals were accommodated with the construction of an optically transparent and fully adjustable frame mockup. The construction of the mockup was such that it could be dimensionally validated rapidly with the motioncapture system. This paper describes the method used to create a space vehicle mockup compatible with use of an optical motion-capture system, the consolidated approach for evaluating spacesuits in action, and a way to use the complex data set resulting from a limited number of test subjects to generate hardware requirements for an entire population. Kinematics, hardware clearance, anthropometry (suited and unsuited), and subjective feedback data were recorded on 15 unsuited and 5 suited subjects. Unsuited subjects were selected chiefly based on their anthropometry in an attempt to find subjects who fell within predefined criteria for medium male, large male, and small female subjects. The suited subjects were selected as a subset of the unsuited medium male subjects and were tested in both unpressurized and pressurized conditions. The prototype spacesuits were each fabricated in a single size to accommodate an approximately average-sized male, so select findings from the suit testing were systematically extrapolated to the extremes of the population to anticipate likely problem areas. This extrapolation was achieved by first comparing suited subjects performance with their unsuited performance, and then applying the results to the entire range of the population. The use of a transparent space vehicle mockup enabled the collection of large amounts of data during human-in-the-loop testing. Mobility data revealed that most of the tested spacesuits had sufficient ranges of motion for the selected tasks to be performed successfully. A suited subject's inability to perform a task most often stemmed from a combination of poor field of view in a seated position, poor dexterity of the pressurized gloves, or from suit/vehicle interface issues. Seat ingress and egress testing showed that problems with anthropometric accommodation did not exclusively occur with the largest or smallest subjects, but also with specific combinations of measurements that led to narrower seat ingress/egress clearance.

England, Scott↗

COUPLING SMOOTHED PARTICLE HYDRODYNAMICS WITH FINITE ELEMENT METHOD TO SIMULATE RESIDUAL STRESSES FROM FRICTION STIR PROCESSING

Friction stir processing (FSP) is a solid-state material processing technique that locally modifies the microstructure but also induces undesirable residual stresses. A robust numerical model for the FSP can help in mitigating these residual stresses. Heat source models within a finite element method (FEM) framework suffer from inaccuracies. In contrast, smoothed particle hydrodynamics (SPH) model that explicitly captures the material flow near the tool and the associated heat generation are accurate. However, the computational expense of SPH simulations can be prohibitive. In this work, we propose a coupled SPH-FEM framework. SPH is used to model the heat generation accurately near the tool and which is then inserted into to the FEM model as a heat source. To verify this proposed coupling approach, a test case is set up with typical FSP conditions and it is modeled in both SPH and SPH-FEM. The temperatures profiles were compared after the simulations have reached steady-state temperatures. The similarity of the temperature profiles from SPH-FEA and SPH validated the proposed coupling approach. This proposed approach achieves the accuracy of the SPH method while potentially retaining the low computational expense of FEM.

smoothed particle hydrodynamics, Finite Element Me↗

Noise Reduction for Solar-Induced Fluorescence Retrievals Using Machine Learning and Principal Component Analysis: Simulations and Applications to GOME-2 Satellite Retrievals

We use a spectral-based approach that employs principal component analysis along with a relatively shallow artificial neural network (NN) to substantially reduce noise and other artifacts in terrestrial chlorophyll solar-induced fluorescence (SIF) retrievals. SIF is a very small emission at red and far-red wavelengths that is difficult to measure and is highly sensitive to random errors and systematic artifacts. Our approach relies upon an assumption that a trained NN can effectively reconstruct the total SIF signal from a relatively small number of leading principal components of the satellite-observed far-red radiance spectra without using information from the trailing modes that contain most of the random errors. We test the approach with simulated reflectance spectra produced with a full atmospheric and surface radiative transfer model using different observing and geophysical parameters and various noise levels. Resulting noisy and noise-reduced retrieved SIF values are compared with true values to assess performance. We then apply our noise reduction approach to SIF derived from two different satellite spectrometers. For evaluation, since the truth in this case is unknown, we compare SIF retrievals from two independent sensors with each other. We also compare the noise-reduced SIF temporal variations with those from an independent gross primary product (GPP) product that should display similar variations. Results show that our noise reduction approach improves capture of SIF seasonal and inter-annual variability. Our approach should be applicable to many noisy data products derived from spectral measurements. Our methodology does not replace the original retrieval algorithms; rather the original noisy retrievals are needed as the target for the NN training process.

noise reduction, solar-induced fluorescence, SIF, ↗

New data-driven approach to bridging power system protection gaps with deep learning

Protection is a critical function in power systems to avoid equipment damage, maintain personnel safety, and support system reliability. However, current protective relay technology cannot adequately protect equipment and personnel from effects of some events; these deficiencies are termed protection gaps. In this paper, a data-driven approach is proposed to complement traditional protection technology and distinguish fault conditions from transients caused by normal operations. A combined convolutional neural network and long short-term memory (CNN-LSTM) network is implemented to achieve data translation invariance and capture the temporal correlation of the time-series input data. As a result, the data-driven method can accurately detect system faults despite variation and noise in the input data. In addition, using the CNN-LSTM--based method avoids the complicated, manual feature extraction procedure required by many traditional data-driven methods. The effectiveness of the proposed approach is tested on two kinds of protection gaps: high-impedance faults and transformer inter-turn faults. Lastly, a transfer learning method is also proposed to address the common issue of data-driven methods for which real-world training data are scarce. Extensive study results demonstrate that the proposed approach can accurately bridge power system protection gaps.

42 ENGINEERING↗

A Systems Engineering Approach to Quality Assurance for Aerospace Testing

On the surface, it appears that AS9100 has little to say about how to apply a Quality Management System (QMS) to major aerospace test programs (or even smaller ones). It also appears that there is little in the quality engineering Body of Knowledge (BOK) that applies to testing, unless it is nondestructive examination (NDE), or some type of lab or bench testing associated with the manufacturing process. However, if one examines: a) how the systems engineering (SE) processes are implemented throughout a test program; and b) how these SE processes can be mapped to the requirements of AS9100, a number of areas for involvement of the quality professional are revealed. What often happens is that quality assurance during a test program is limited to inspections of the test article; what could be considered a manufacturing al fresco approach. This limits the quality professional and is a disservice to the programs and projects, since there are a number of ways that quality can enhance critical processes, and support efforts to improve risk reduction, efficiency and effectiveness. The Systems Engineering (SE) discipline is widely used in aerospace to ensure the progress from Stakeholder Expectations (the President, Congress, the taxpayers) to a successful, delivered product or service. Although this is well known, what is not well known is that these same SE processes are implemented in varying complexity, to prepare for and implement test projects that support research, development, verification and validation, qualification, and acceptance test projects. Although the test organization's terminology may vary from the SE terminology, and from one test service provider to another, the basic process is followed by successful, reliable testing organizations. For this analysis, NASA Procedural Requirements (NPR) 7123.1, NASA Systems Engineering Processes and Requirements is used to illustrate the SE processes that are used for major aerospace testing. Many of these processes are also implemented for smaller test projects, and this set of processes will also look familiar to those who have participated in launch site activation and flight demonstrations.

Shepherd, Christena C.↗

Sub-ply level scaling approach investigated for graphite-epoxy composite beam columns

Scale model graphite-epoxy composite specimens were fabricated using the 'sub-ply level' approach and tested as beam-columns under an eccentric axial load to determine the effect of specimen size on flexural response and failure. In the current research project, although the fiber diameters are not scaled, the thickness of the pre-preg material itself has been scaled by adjusting the number of fibers through the thickness of a single ply. Three different grades of graphite-epoxy composite material (AS4/3502) were obtained from Hercules, Inc., in which the number of fibers through the thickness of a single ply was reduced (Grade 190 with 12 to 16 fibers, Grade 95 with 6 to 8 fibers, and Grade 48 with 3 to 4 fibers). Thus, using the sub-ply level approach, a baseline eight ply quasi-isotropic laminate could be fabricated using either the Grade 48 or Grade 95 material and the corresponding full-scale laminate would be constructed from Grade 95 or standard Grade 190 material, respectively. Note that in the sub-ply level approach, the number of ply interfaces is constant for the baseline and full-scale laminates. This is not true for the ply level and sublaminate level scaled specimens. The three grades of graphite-epoxy composite material were used to fabricate scale model beam-column specimens with in-plane dimensions of 0.5*n x 5.75*n, where n=1,2,4 corresponsing to 1/4, 1/2, and full-scale factors. Angle ply, cross ply, and quasi-isotropic laminate stacking sequences were chosen for the investigation and the test matrices for each laminate type are given. Specimens in each laminate family with the same in-plane dimensions but different thicknesses were tested to isolate the influence of the thickness dimension on the flexural response and failure. Also, specific lay-ups were chosen with blocked plies and dispersed plies for each laminate type. Specimens were subjected to an eccentric axial load until failure. The load offset was introduced through a set of hinges which were attached to the platens of a standard load test machine. Three sets of geometrically scaled hinges were used to ensure that scaled loading conditions were applied. This loading condition was chosen because it promotes large flexural deformations and specimens fail at the center of the beam, away from the grip supports. Five channels of data including applied vertical load, end shortening displacement, strain from gages applied back-to-back at the midspan of the beam, and rotation of the hinge from a bubble inclinometer were recorded for each specimen. The beam-column test configuration was used previously to study size effects in ply level scaled composite specimens of the same material system, sizes, and stacking sequences. Thus, a direct comparison between the two scaling approaches is possible. Ply level scaled beam-columns with angle ply, cross ply, and quasi-isotropic lay-ups exhibited no size dependencies in the flexural response, but significant size effects in strength. The reduction in strength with increasing specimen size was not predicted successfully by analysis techniques. It is anticipated that results from this investigation will lead to a better understanding of the strength scale effect in composite structures.

Jackson, Karen E.↗

Daytime Water Detection Based on Sky Reflections

Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide-open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies. One of the properties of water useful for detecting it is that its surface acts as a horizontal mirror at large incidence angles. Water bodies can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. The Jet Propulsion Laboratory (JPL) has implemented a water detector based on sky reflections that geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground and predicts if the ground pixel is water based on color similarity and local terrain features. This software detects water bodies in wide-open areas on cross-country terrain at mid- to far-range using imagery acquired from a forward-looking stereo pair of color cameras mounted on a terrestrial UGV. In three test sequences approaching a pond under a clear, overcast, and cloudy sky, the true positive detection rate was 100% when the UGV was beyond 7 meters of the water's leading edge and the largest false positive detection rate was 0.58%. The sky reflection based water detector has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA, USA.

sky reflections↗

Range wide genetic differentiation in the bull kelp Nereocystis luetkeana with a seascape genetic focus on the Salish Sea

Introduction: In temperate regions, one of the most critical determinants of present range-wide genetic diversity was the Pleistocene climate oscillations, the most recent one created by the last glacial maximum (LGM). This study aimed to describe N. luetkeana genetic structure across its entire range (Alaska to California) and test different models of population connectivity within the Salish Sea. This region was colonized after the LGM and has been under increased disturbance in recent decades. Methods: We utilized microsatellite markers to study N. luetkeana genetic diversity at 53 sites across its range. Using higher sampling density in the Salish Sea, we employed a seascape genetics approach and tested isolation by hydrodynamic transport and environment models. Results: At the species distribution scale, we found four main groups of genetic co-ancestry, Alaska; Washington with Vancouver Island’s outer coast and Juan de Fuca Strait; Washington’s inner Salish Sea; and Oregon with California. The highest allelic richness (AR) levels were found in California, near the trailing range edge, although AR was also high in Alaska. The inner Salish Sea region had the poorest diversity across the species distribution. Nevertheless, a pattern of isolation by hydrodynamic transport and environment was supported in this region. Discussion: The levels of allelic, private allele richness and genetic differentiation suggest that during the LGM, bull kelp had both northern and southern glacial refugia in the Prince of Wales Island-Haida Gwaii region and Central California, respectively. Genetic diversity in Northern California sites seems resilient to recent disturbances, whereas the low levels of genetic diversity in the inner Salish Sea are concerning.

59 BASIC BIOLOGICAL SCIENCES↗

Increasing Durability of Flame-Sprayed Strain Gauges

Thermally sprayed dielectric ceramic coatings are the primary means of attaching strain and temperature gauges to hot-section rotating parts of turbine engines. As hot-section temperatures increase, lifetimes of installed gauges decrease, and seldom exceed one hour above 2,000 F (approx.1,100 C). Advanced engine components are expected to operate at temperatures approaching 2,200 F (approx.1,200 C), and the required high-temperature lifetime is 10 hours minimum. Typically, to enable a ceramic coating to adhere to the smooth surface of an engine component, a thermally sprayed NiCrAlY or NiCoCrAlY bond coat is applied to the smooth surface, thereby providing a textured surface to which the ceramic coat can adhere. The main failure mechanism of this system is decohesion and/or delamination at the interface between the ceramic top coat and the bond coat, caused by oxidation of the bond coat and stresses from the mismatch between the coefficients of thermal expansion of the ceramic top coat and the metallic bond coat. The approach taken to increase the high-temperature lifetime of a gauge attached to an engine component by the method described above involves (1) selective oxidation of the bond coat by means of a heat treatment in reduced oxygen partial pressure followed by (2) the application of a noble-metal diffusion barrier. In experiments to test this approach, heat treatments of NiCoCrAlY bond coats were carried out in a tube furnace in which, in each case, the temperature was alternately (1) increased at a rate of 3 C per minute and (2) held steady for one hour until the desired temperature was reached. The tube furnace was continuously purged with dry nitrogen gas. A final heat-treatment temperature range of 1,600 to 1,800 F (871 to 982 C) proved most beneficial.

Gregory, Otto J.↗

Balanced k -means clustering on an adiabatic quantum computer

Adiabatic quantum computers are a promising platform for efficiently solving challenging optimization problems. Therefore, many are interested in using these computers to train computationally expensive machine learning models. We present a quantum approach to solving the balanced k-means clustering training problem on the D-Wave 2000Q adiabatic quantum computer. In order to do this, we formulate the training problem as a quadratic unconstrained binary optimization (QUBO) problem. Unlike existing classical algorithms, our QUBO formulation targets the global solution to the balanced k-means model. We test our approach on a number of small problems and observe that despite the theoretical benefits of the QUBO formulation, the clustering solution obtained by a modern quantum computer is usually inferior to the solution obtained by the best classical clustering algorithms. Nevertheless, the solutions provided by the quantum computer do exhibit some promising characteristics. We also perform a scalability study to estimate the run time of our approach on large problems using future quantum hardware. Finally, as a final proof of concept, we used the quantum approach to cluster random subsets of the Iris benchmark data set.

97 MATHEMATICS AND COMPUTING↗

Effect of Uncertainty on Deterministic Runway Scheduling

Active runway scheduling involves scheduling departures for takeoffs and arrivals for runway crossing subject to numerous constraints. This paper evaluates the effect of uncertainty on a deterministic runway scheduler. The evaluation is done against a first-come- first-serve scheme. In particular, the sequence from a deterministic scheduler is frozen and the times adjusted to satisfy all separation criteria; this approach is tested against FCFS. The comparison is done for both system performance (throughput and system delay) and predictability, and varying levels of congestion are considered. The modeling of uncertainty is done in two ways: as equal uncertainty in availability at the runway as for all aircraft, and as increasing uncertainty for later aircraft. Results indicate that the deterministic approach consistently performs better than first-come-first-serve in both system performance and predictability.

Gupta, Gautam↗

Operational Test Results of the Final Approach Spacing Tool

A prototype decision support tool for terminal area air traffic controllers, referred to as the Final Approach Spacing Tool (FAST), was recently evaluated in operation with live air traffic at the Dallas/Fort Worth Terminal Radar Approach Control (TRACON) facility in the United States. Controllers utilized the FAST system's runway assignment and sequence advisories to manage and control arrival traffic during more than twenty five peak rush traffic periods. The system performed well resulting in capacity increases at the airport of 10-20% depending on weather and airport conditions. As a result of these tests, the US Federal Aviation Administration (FAA) is proceeding with plans to further develop the prototype FAST system for national deployment at five to ten TRACONs within the United States during the next five years. This paper will present the results of these tests including data on the FAST system impact on airport capacity, aircraft flight times in the terminal area, delay reduction, tower operations including ground movement, and human factors data including workload assessments.

Davis, Thomas J.↗

Use of Probability Distribution Functions for Discriminating Between Cloud and Aerosol in Lidar Backscatter Data

In this paper we describe the algorithm hat will be used during the upcoming Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission for discriminating between clouds and aerosols detected in two wavelength backscatter lidar profiles. We first analyze single-test and multiple-test classification approaches based on one-dimensional and multiple-dimensional probability density functions (PDFs) in the context of a two-class feature identification scheme. From these studies we derive an operational algorithm based on a set of 3-dimensional probability distribution functions characteristic of clouds and aerosols. A dataset acquired by the Cloud Physics Lidar (CPL) is used to test the algorithm. Comparisons are conducted between the CALIPSO algorithm results and the CPL data product. The results obtained show generally good agreement between the two methods. However, of a total of 228,264 layers analyzed, approximately 5.7% are classified as different types by the CALIPSO and CPL algorithm. This disparity is shown to be due largely to the misclassification of clouds as aerosols by the CPL algorithm. The use of 3-dimensional PDFs in the CALIPSO algorithm is found to significantly reduce this type of error. Dust presents a special case. Because the intrinsic scattering properties of dust layers can be very similar to those of clouds, additional algorithm testing was performed using an optically dense layer of Saharan dust measured during the Lidar In-space Technology Experiment (LITE). In general, the method is shown to distinguish reliably between dust layers and clouds. The relatively few erroneous classifications occurred most often in the LITE data, in those regions of the Saharan dust layer where the optical thickness was the highest.

Liu, Zhaoyan↗

A Systems Engineering Approach to Quality Assurance for Aerospace Testing

On the surface, it appears that AS91001 has little to say about how to apply a Quality Management System (QMS) to major aerospace test programs (or even smaller ones). It also appears that there is little in the quality engineering Body of Knowledge (BOK)2 that applies to testing, unless it is nondestructive examination (NDE), or some type of lab or bench testing associated with the manufacturing process. However, if one examines: a) how the systems engineering (SE) processes are implemented throughout a test program; and b) how these SE processes can be mapped to the requirements of AS9100, a number of areas for involvement of the quality professional are revealed. What often happens is that quality assurance during a test program is limited to inspections of the test article; what could be considered a manufacturing al fresco approach. This limits the quality professional and is a disservice to the programs and projects, since there are a number of ways that quality can enhance critical processes, and support efforts to improve risk reduction, efficiency and effectiveness.

Shepherd, Christena C.↗