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An Approach to Building a Traceability Tool for Software Development

It is difficult in a large, complex computer program to ensure that it meets the specified requirements. As the program evolves over time, a11 program constraints originally elicited during the requirements phase must be maintained. In addition, during the life cycle of the program, requirements typically change and the program must consistently reflect those changes. Imagine the following scenario. Company X wants to develop a system to automate its assembly line. With such a large system, there are many different stakeholders, e.g., managers, experts such as industrial and mechanical engineers, and end-users. Requirements would be elicited from all of the stake holders involved in the system with each stakeholder contributing their point of view to the requirements. For example, some of the requirements provided by an industrial engineer may concern the movement of parts through the assembly line. A point of view provided by the electrical engineer may be reflected in constraints concerning maximum power usage. End-users may be concerned with comfort and safety issues, whereas managers are concerned with the efficiency of the operation. With so many points of view affecting the requirements, it is difficult to manage them, communicate information to relevant stakeholders. and it is likely that conflicts in the requirements will arise. In the coding process, the implementors will make additional assumptions and interpretations on the design and the requirements of the system. During any stage of development, stakeholders may request that a requirement be added or changed. In such a dynamic environment, it is difficult to guarantee that the system will preserve the current set of requirements. Tracing, the mapping between objects in the artifacts of the system being developed, addresses this issue. Artifacts encompass documents such as the system definition, interview transcripts, memoranda, the software requirements specification, user's manuals, the functional specifications, design reports, and system code. Tracing helps 1) validate system features against, the requirement specification, 2) identify error sources and, most importantly, 3) manage change. With so many people involved in the development of the system, it becomes necessary to identify the reasons behind the design requirements or the implementation decisions. This paper is concerned with an approach that maps documents to constraints that capture properties of and relationships between the objects being modeled by the program. Section 2 provides the reader with a background on traceability tools. Section 3 gives a brief description of the context monitoring system on which the approach suggested in this paper is based. Section 4 presents an overview of our approach to providing traceability. The last section presents our future direction of research.

Delgado, Nelly↗

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

GeoAI Advances in Specific Landform Mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation.

machine learning↗

New Approach to Characterize CO2 and CH4 Emissions over Sacramento, California Using an Airborne Aircraft Measurement

Emission fluxes of carbon dioxide (CO2) and methane (CH4) over Sacramento, California, USA, are estimated using an aircraft equipped with a cavity ring-down greenhouse gas sensor through the Alpha Jet Atmospheric eXperiment (AJAX). To better quantify the emission fluxes over the entire city and two small point sources within the area, we designed flights in a cylindrical pattern and computed the emission fluxes from 9 flights over all seasons using the Kriging method based on Gausss divergence theorem. The concentrations at the downwind side of Sacramento show somewhat persistent patterns among the 9 flights, but the magnitudes and locations of the fluxes vary depending on the individual weather conditions and seasonality on a given flight day. The net emission fluxes tend to be smaller in summer (July) than winter (November). Both trace gas mixing ratios as well as the wind speed and direction show high spatial variability both horizontally and vertically. The local maximum emission fluxes over a landfill and a rice field measured on July 29, 2015, were 2-3 times lower than the maximum measured over the entire city. These low emission fluxes suggest that not only the local source but also the transport of greenhouse gases due to diurnal and seasonal variation in winds have a strong effect on the CO2 and CH4 flux estimation of the both local emissions and city-size emissions. Our results highlight that the aircraft-based approach is effective and useful for capturing city-size emission fluxes and estimating the greenhouse gas emissions and its sources.

airborne↗

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

Usage of ChatGPT for Engineering Design and Analysis Tool Development

ChatGPT, a generative AI large language model, has recently captured significant attention in both the computer science community and the broader public domain. It has demonstrated a wide range of capabilities, from answering simple questions to writing fully functional computer code. This study spotlights both the capabilities and limitations of ChatGPT when addressing engineering problems. The model's capacity to generate practical engineering tools is highlighted through an example of a prompt that leads to an interactive plotting tool, enabling the examination of the fluid boundary layer around a fan blade. Subsequently, the paper also uncovers potential pitfalls in ChatGPT’s application, shown through an unsuccessful attempt to use ChatGPT to automate a process in Ansys Workbench through scripting. The research further investigates ChatGPT's proficiency in addressing inquiries and providing explanations about the functionalities of OpenMDAO, an open-source, multidisciplinary design, analysis, and optimization tool developed at NASA Glenn Research Center. Finally, an optimization methodology, developed with ChatGPT’s help, is applied to the structural optimization of a fan blade. The developed optimization method utilizes T-Blade3 for geometry generation, Ansys Mechanical for meshing and finite element analysis, and sci-kit learn’s MLPRegressor method to generate a trained neural network model of the design space. OpenMDAO is then used to find the optimal point within the design space. The outcome is a significant reduction in stress in the optimized model—less than one-fifth of the stress value in the baseline model.

Design↗

Application of Digital Image Correlation in Wind Tunnel

Digital image correlation (DIC) is a non-contact measurement technique that has been used in various applications in multiple industries, from microscopic specimens all the way to large scale structures. This project involved using DIC to capture wing deflection under simulated wind loading at various angles of attack (AoA). A subscale model of a fixed-wing aircraft, shown in Figure 1, was used in the 14-footby 22-footsubsonicwind tunnel at the NASA Langley Research Center. The setup used two pairs of cameras mounted on the ceiling of the tunnel to view the starboard and port side wings. Aluminum framing was used to rigidly mount the cameras to beams in the ceiling. Camera setup challenges due to the confined space included obtaining even lighting and working around infrared (IR) cameras that were used to capture the flow over the wing. Remote connection was used to access data acquisition computers from computers in the control room. Eight measurement locations on each wing were made of 1-inch-diametercircular silver dry transfer decals that did not alter the air flow across the wing. These circles were speckled with a black ink pen and were used for the IR camera as well as for DIC systems. A mock setup outside the wind tunnel was used to optimize the camera setup and verify that the speckled tape provided sufficient correlation. DIC was used to track the position of seven locations as the AoA of the subscale model changed from −10 degrees to +10 degrees in 1-degree increments. The model was rotated at a fixed height about the center of the fuselage from −7 degrees to +10 degrees. The height of the model had to be lowered to achieve AoA slower than −7degrees due to geometric constraints of the cart supporting the model and the wind tunnel. The source of light was stationary relative to the model, so the exposure time had to be adjusted for different wing regions and AoA values. The three-dimensional (3D) visualization of the markings and the two-dimensional (2D) projection of these points onto the port wing at 0-degree AoA is shown in Figure 2.

Matlock Mennu↗

Techno-Economic Analysis of Green Hydrogen Energy Storage in A Cryogenic Flux Capacitor

The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH 2 ) storage and liquid hydrogen (LH 2 ) region near the normal boiling point. Hydrogen storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (~1,000 m 2 /g) allows its storage performance to easily exceed capacities of high-pressure GH 2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 36% over a simple tank filled with GH 2 at the same operating temperature and pressure. For LH 2 conditions, the CFC is shown to operate at improved densities, but testing is ongoing. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce green GH 2 . The TEA compares pure hydrogen produced at a small scale for a 25 MW power system and at a large scale in a 500 MW power system. The system allowed for hydrogen imports and exports at a set price with a tank sized for 10 hours of power production. The two power producing technologies are a combined cycle gas turbine (CCGT) and hydrogen fuel cells. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH), and levelized cost of storage (LCOS) are developed based on the capital cost and operating cost of the systems. The results are shown for current costs using a 2021 benchmark and DOE projections for cost improvements by 2030. The TEA showed that onsite hydrogen generation from SMR has an LCOH of about 1.4 to 2 USD per kg over the life of the plant and the PV hydrogen production LCOH is about 5.2 to 5.5 USD per kg. The LCOS of conventional GH 2 systems is estimated to be $210/MWh and cost of storage for LH 2 systems is $205/MWh for fuel cell systems and $249/MWh for CCGT systems. CFC improved the LCOS of all these systems to $198/MWh, $191/MWh and $233/MWh respectively. The LCOE also improved with conventional systems between $171/MWh and $228/MWh improved by CFC to between $167/MWh and $212/MWh. Using projections for improvement in costs following DOE’s goals by 2030, green hydrogen improved to as low as $78/MWh LCOS and LCOE for conventional cases. CFC improved over conventional storage with the lowest LCOS being $62/MWh and the lowest LCOE being $73/MWh. These results correspond to an LCOH of $2/kg. Finally, the TEA shows how LCOE is improved for hydrogen conditioning and storage over conventional systems and caverns in the 10 to 50 hour range.

Joshua Schmitt↗

Negative-ion formation in the explosives RDX, PETN, and TNT using the Reversal Electron Attachment Detection (READ) technique

In the search for high sensitivity and direct atmospheric sampling of trace species, techniques have been developed such as atmospheric-sampling, glow-discharge ionization (ASGDI), corona discharge, atmospheric pressure ionization (API), electron-capture detection (ECD), and negative-ion chemical ionization (NICI) that are capable of detecting parts-per-billion to parts-per-trillion concentrations of trace species. These techniques are based on positive- or negative-ion formation via charge-transfer to the target, or electron capture under multiple-collision conditions in a Maxwellian distribution of electron energies at the source temperature. One drawback of the high-pressure, corona- or glow-discharge devices is that they are susceptible to interferences either through indistinguishable product masses, or through undesired ion-molecule reactions. The ASGDI technique is relatively immune from such interferences, since at target concentrations of less than 1 ppm the majority of negative ions arises via electron capture rather than through ion-molecule chemistry. A drawback of the conventional ECD, and possibly of the ASGDI, is that they exhibit vanishingly small densities of electrons with energies in the range 0-10 millielectron volts (meV), as can be seen from a typical Maxwellian electron energy distribution function at T = 300 K. Slowing the electrons to these subthermal (less than 10 meV) energies is crucial, since the cross section for attachment of several large classes of molecules is known to increase to values larger than 10(exp -12) sq cm at near-zero electron energies. In the limit of zero energy these cross sections are predicted to diverge as epsilon(exp -1/2), where epsilon is the electron energy. In order to provide a better 'match' between the electron energy distribution function and attachment cross section, a new concept of attachment in an electrostatic mirror was developed. In this scheme, electrons are brought to a momentary halt by reversing their direction with electrostatic fields. At this turning point the electrons have zero or near-zero energy. A beam of target molecules is introduced, and the resultant negative ions extracted. This basic idea has been recently improved to allow for better reversal geometry, higher electron currents, lower backgrounds, and increased negative-ion extraction efficiency. We present herein application of the so-called reversal electron attachment detector (READ) to the study of negative-ion formation in the explosives molecules RDX, PETN, and TNT under single-collision conditions.

Chutijian, Ara↗

Fluid Creep Effects on Near-Wall Solute Transport for Non-Isothermal Ampoules

There is a growing practical and theoretical interest in developing accurate macroscopic modelling for flows arising in chemical or physical vapor transport (VT) crystal growth experiments, including those conducted in reduced gravity environments. Rosner was the first person to point out that previously neglected rarefield gas dynamics phenomena (Stefan and bouyancy-driven flows) become rather important sources of convection. In particular, the combination of rarefaction and strong gradients of temperature (and/or concentration) tangential to the side-walls of the ampoule induces convective flows known as thermal (and concentration) 'creep' respectively. His order-of-magnitude estimates revealed that thermal creep effects can be non-negligible even at normal gravitational levels. On the macroscopic level, the bulk fluid mechanics can be adequately described by the familiar macroscopic equations as long as the boundary conditions are modified to account for the integrated effect of kinetic boundary layers adjacent to solid boundaries. Motivated by the growing importance of these phenomena, we have embarked on a series of computational studies to elucidate these fundamental creep-induced effects for a rarefied gas in simple, two-dimensional confined geometries. However, unlike previous related studies, we resort to a microscopic description of the gas, mathematically expressed by the Boltzmann integro-differential equation. We employ the direct simulation Monte Carlo (DSMC) method of Bird, the theoretical foundations and several practical applications. In the case of thermally induced flows, the no-time counter method of Bird is used, as implemented for a hard-sphere gas. The scheme has been also extended to account for realistic molecular interaction models, an extension necessary if the diffusion physics underlying concentration creep are to be captured.

Papadopoulos, Dimitrios↗

Superboom Caustic Analysis and Measurement Program (SCAMP) Final Report

The objectives of the Superboom Caustic Analysis and Measurement (SCAMP) Program were to develop and validate, via flight-test measurements, analytical models for sonic boom signatures in and around focal zones as they are expected to occur during commercial aircraft transition from subsonic to supersonic flight, and to apply these models to focus boom prediction of low-boom aircraft designs. The SCAMP program has successfully investigated sonic boom focusing both analytically and experimentally, while gathering a comprehensive empirical flight test and acoustic dataset, and developing a suite of focused sonic boom prediction tools. An experimental flight and acoustic measurement test was designed during the initial year of the SCAMP program, with execution of the SCAMP flight test occurring in May 2011. The current SCAMP team, led by Wyle, includes partners from the Boeing Company, Pennsylvania State University, Gulfstream Aerospace, Eagle Aeronautics, and Central Washington University. Numerous collaborators have also participated by supporting the experiment with human and equipment resources at their own expense. The experiment involved precision flight of a McDonnell Douglas (now Boeing) F-18B executing different maneuvers that created focused sonic booms. The maneuvers were designed to center on the flight regime expected for commercial supersonic aircraft transonic transition, and also span a range of caustic curvatures in order to provide a variety of conditions for code validations. The SCAMP experiment was designed to capture concurrent F-18B on-board flight instrumentation data, high-fidelity ground-based and airborne acoustic data, and surface and upper air meteorological data. Close coordination with NASA Dryden resulted in the development of new experimental instrumentation and techniques to facilitate the SCAMP flight-test execution, including the development of an F-18B Mach rate cockpit display, TG-14 powered glider in-flight sonic boom measurement instrumentation and "Where's the Focus?" (WTF) software for near-real time way-point computation accounting for local atmospherics. In May 2011, 13 F-18B flights were conducted during 5 flying days over a 2 week period. A densely populated 10,000 ft-long ground acoustic array with 125-ft microphone spacing was designed to capture pre-, focus, and post-focus regions. The ground-based acoustic array was placed in a nominally east-west orientation in the remote Cuddeback lakebed region, north of Edwards AFB. This area was carefully selected to avoid placing focused booms on populated areas or solar power facilities. For the SCAMP measurement campaign, approvals were obtained to temporarily extend the Black Mountain supersonic corridor northward by three miles. The SCAMP flight tests successfully captured 70 boom events, with 61 focus passes, and 9 calibration passes. Seventeen of the focus passes and three of the calibration passes were laterally offset; with the others being centerline flights. Airborne incoming sonic boom wave measurements were measured by the TG-14 for 10 of the F-18B flight passes including one maximum focus signature, several N-u combinations, several overlapped N-u signatures, and several evanescent waves. During the 27-month program, the SCAMP team developed a suite of integrated computer codes with sonic boom focusing predictive capabilities: PCBoom, Lossy Nonlinear Tricomi Equation Method (LNTE) and the Nonlinear Progressive wave Equation (NPE) method. PCBoom propagates the rays through the atmosphere and, in addition to legacy focus signature prediction based on the Gill-Seebass method, provides input source characteristics and propagation parameters to LNTE and NPE. LNTE, a Tricomi solver that incorporates atmospheric losses, computes the focus signature at the focus, and computes the focus signature in the vicinity of the focal zone, including the evanescent and post-focus zones. LNTE signature auralization from low-boom vehicle designs has been demonstrated in the NASA Langley Interior Effects Room (IER). The NPE has also been validated for use in prediction of focused ground boom signatures in sonic boom focal zones. The NPE formulation has the capability to incorporate atmospheric turbulence in the predictions. This has been applied to sonic boom propagation in the past. Prediction of turbulence effects on focal zone signatures was not, however, explored during the SCAMP program.

Page, Juliet↗

Temperature-Staged Thermal Energy Storage Enabling Low Thermal Exergy Loss Reflux Boiling in Full Spectrum Solar Systems

Hybrid full spectrum solar systems (FSSS) designed to capture and convert the full solar wavelength spectrum use hybrid solar photovoltaic/thermodynamic cycles that require low thermal exergy loss systems capable of transferring high thermal energy rates and fluxes with very low temperature differentials and losses. One approach to achieving this capability are high-heat-flux reflux boiling systems that take advantage of high heat transfer boiling and condensation mechanisms. Advanced solar systems are also intermittent by their nature and their electrical generation is often out-of-phase with electric utility power demand, and their required power system cycling reduces efficiency, performance (dispatch ability), lifetime, and reliability. High temperature thermal energy storage (TES) at 300-600°C enables these reflux boiling systems to simultaneously store thermal energy internally to increase the energy dispatch ability of the associated solar system, as this can increase the power generation profile by several hours (up to 6-10 hours) per day. Many TES phase change materials (PCM’s) exist including KNO3, NaNO3, LiBr/KBr, MgCl2/NaCl/KCl, Zn/Mg, and CuCl/NaCl, which have various operating melting points and different latent heats of fusion. Common, cost effective TES PCM's are FeCl2/NaCl/KCl mixtures, whose phase change temperature can be varied and controlled by simple composition adjustments. This paper presents and discusses unique "temperature-staged" thermal energy storage configurations using these TES materials and analysis of such systems integrated into high-heat-flux reflux boiling systems. In this specific application, the TES materials are designed to operate at staged temperatures surrounding an operating design point near 350°C, while providing 18 kW of source heat transfer to operate a thermoacoustic power system during off-sun conditions (e.g., temporary cloud conditions, after sun-down). This work discusses relevant configurations, and critical thermal and entropy models of the TES configurations, which show the inherent minimization of thermal exergy during critical heat transfers within the configurations and systems envisioned.

Hendricks, Terry J.↗

A New Method for Accurate Treatment of Flow Equations in Cylindrical Coordinates Using Series Expansions

The motivation of this work is the ongoing effort at the Center for Turbulence Research (CTR) to use large eddy simulation (LES) techniques to calculate the noise radiated by jet engines. The focus on engine exhaust noise reduction is motivated by the fact that a significant reduction has been achieved over the last decade on the other main sources of acoustic emissions of jet engines, such as the fan and turbomachinery noise, which gives increased priority to jet noise. To be able to propose methods to reduce the jet noise based on results of numerical simulations, one first has to be able to accurately predict the spatio-temporal distribution of the noise sources in the jet. Though a great deal of understanding of the fundamental turbulence mechanisms in high-speed jets was obtained from direct numerical simulations (DNS) at low Reynolds numbers, LES seems to be the only realistic available tool to obtain the necessary near-field information that is required to estimate the acoustic radiation of the turbulent compressible engine exhaust jets. The quality of jet-noise predictions is determined by the accuracy of the numerical method that has to capture the wide range of pressure fluctuations associated with the turbulence in the jet and with the resulting radiated noise, and by the boundary condition treatment and the quality of the mesh. Higher Reynolds numbers and coarser grids put in turn a higher burden on the robustness and accuracy of the numerical method used in this kind of jet LES simulations. As these calculations are often done in cylindrical coordinates, one of the most important requirements for the numerical method is to provide a flow solution that is not contaminated by numerical artifacts. The coordinate singularity is known to be a source of such artifacts. In the present work we use 6th order Pade schemes in the non-periodic directions to discretize the full compressible flow equations. It turns out that the quality of jet-noise predictions using these schemes is especially sensitive to the type of equation treatment at the singularity axis. The objective of this work is to develop a generally applicable numerical method for treating the singularities present at the polar axis, which is particularly suitable for highly accurate finite-differences schemes (e.g., Pade schemes) on non-staggered grids. The main idea is to reinterpret the regularity conditions developed in the context of pseudo-spectral methods. A set of exact equations at the singularity axis is derived using the appropriate series expansions for the variables in the original set of equations. The present treatment of the equations preserves the same level of accuracy as for the interior scheme. We also want to point out the wider utility of the method, proposed here in the context of compressible flow equations, as its extension for incompressible flows or for any other set of equations that are solved on a non-staggered mesh in cylindrical coordinates with finite-differences schemes of various level of accuracy is straightforward. The robustness and accuracy of the proposed technique is assessed by comparing results from simulations of laminar forced-jets and turbulent compressible jets using LES with similar calculations in which the equations are solved in Cartesian coordinates at the polar axis, or in which the singularity is removed by employing a staggered mesh in the radial direction without a mesh point at r = 0.

Constantinescu, G.S.↗

The Nature and Evolutionary History of GRO J1744-28

GRO J1744-28 is the first known X-ray source to display bursts, periodic pulsations, and quasi-periodic oscillations. This source may thus provide crucial clues that will lead to an understanding of the differences in the nature of the X-ray variability from various accreting neutron stars. The orbital period is 11.8 days, and the measured mass function of 1.31 x 10(exp -4) solar mass is one of the smallest among all known binaries. If we assume that the donor star is a low-mass giant transferring matter through the inner Lagrange point, then we can show that its mass is lower than approximately 0.7 solar mass and probably closer to 0.25 solar mass. Higher mass, but unevolved, donor stars are shown to be implausible. We also demonstrate that the current He core mass of the donor star lies in the range of 0.20-0.25 solar mass. Thus, this system is most likely in the final stages of losing its hydrogen-rich envelope, with only a small amount of mass remaining in the envelope. If this picture is correct, then GRO J1744-28 may well represent the closest observational link that we have between the low-mass X-ray binaries and recycled binary pulsars in wide orbits. We have carried out a series of binary evolution calculations and explored, both systematically and via a novel Monte Carlo approach, the range of initial system parameters and input physics that can lead to the binary parameters of the present-day GRO J1744-28 system. The input parameters include both the initial total mass and the core mass of the donor star, the neutron-star mass, the strength of the magnetic braking, the mass-capture fraction, and the specifics of the core mass/radius relation for giants. Through these evolution calculations, we compute probability distributions for the current binary system parameters (i.e., the total mass, core mass, radius, luminosity, and K-band magnitude of the donor star, the neutron star mass, the orbital inclination angle, and the semimajor axis of the binary). Our calculations yield the following values for the GRO J1744-28 system parameters (with 95% confidence limits in parentheses): donor star mass: 0.24 solar mass (0.2-0.7 solar mass); He core mass of the donor star: 0.22 solar mass (0.20-0.25 solar mass); neutron-star mass: 1.7 solar mass (1.39-1.96 solar mass); orbital inclination angle: 18deg (7deg-22deg); semi- major axis: 64 lt-s (60-67 lt-s); radius of the donor star: 6.2 solar radius(6-9 solar radius); luminosity of donor star: 23 solar luminosity (15-49 solar luminosity), and long-term mass transfer rate at the current epoch: 5 x 10(exp -10)solar mass/yr (2 x 10(exp -10) to 5 x 10(exp -9)solar mass/yr). We deduce that the magnetic field of the underlying neutron star lies in the range of approximately 1.8 x 10(exp 11)G to approximately 7 x 10(exp 11)G, with a most probable value of 2.7 x 10(exp 11)G. This is evidently sufficiently strong to funnel the accretion flow onto the magnetic polar caps and suppress the thermonuclear flashes that would otherwise give rise to the type 1 X-ray bursts observed in most X-ray bursters. We present a simple paradigm for magnetic accreting neutron stars where X-ray pulsars, GRO J1744-28, the Rapid Burster, and the type 1 X-ray bursters may form a continuum of possible behaviors among accreting neutron stars, with the strength of the neutron-star magnetic field serving as a crucial parameter that determines the mode of X-ray variability from a given object.

Rappaport, S.↗

Survival of Organic Materials in Ancient Cryovolcanically-Produced Halite Crystals

Spectroscopic evidence supports the presence of Mg-Na-K salts derived from cryovolcanism on the surface of Europa. Halite (NaCl) is effective at very long-term preservation of organic phases and structures. Collection of salt crystals from Europan plumes would provide solid inclusions of organics, potentially also biomaterials, all suitable for analysis. Two thermally-metamorphosed ordinary chondrite regolith breccias (Monahans 1998 (H5) and Zag (H3-6)) contain fluid and solid inclusion-bearing halite crystals, dated to approximately 4.5 billion years, and thus the trapped aqueous fluids and solids are at least as old. Heating/freezing studies of the aqueous fluid inclusions in these halites demonstrated that they were trapped near 25 degrees Centigrade, and their continued presence in the halite grains requires that their incorporation into the H chondrite asteroid occurred after that body's metamorphism ended, since heating would have dessicated the halite. O and H isotopes of the trapped fluids are consistent with mixing of asteroidal and cometary water. Cryovolcanic Origin of the Halite: We hypothesize that these meteoritic halites derive from ancient cryovolcanism based on the following points. (1) Salts crystals are observed as products of current cryovolcanism on Enceladus. (2) In-situ spacecraft analysis of some of the icy grains associated with the Enceladus salt found minor organic or siliceous components, including methane, also found in the Monahans halite. (3) Cryovolcanic fluids are observed to be in chemical disequilibrium, reflecting incomplete reactions between interior volatiles and rocky materials. The coexistence of N2 and HCN in Enceladus' cryovolcanic fluids requires that the plume consists of a mixture of materials whose sources experienced different degrees of aqueous processing, including primordial material trapped in ice that has not been in contact with liquid water. The observed mineral assemblage within the Monahans and Zag halites is also far from equilibrium. Cryovolcanoes on Ceres are a potential source of our halite, however the processes that form halite should also be operating within Europa. Dissolution of Monahans halite grains has revealed a remarkable variety of organics, which dominate the population of solid inclusions. Thermal alteration of this macromolecular carbon (measured by Raman spectroscopy) shows remarkable diversity. We have identified highly-condensed aromatics, diamond, carbonates and chloromethane. Light organic compounds like methane tend to be water soluble and require cold formation temperatures at high hydrogen fugacity - i.e. require water ice. Another indication that these halites have not been heated is that light organics readily volatilize or aromaticize into PAHs. We are currently analyzing the organics by Raman and C-XANES, and measuring the content and exploring the potential chirality of amino acids in the halite. Implications for Europa Plumes: Organic materials and structures erupted by a Europa cryovolcano should be similarly preserved within halite, and other salts, which will be a convenient form for capture and analysis, since halite will serve to encapsulate and protect the organics from spacecraft contamination. Also, being transparent at many wavelengths halite will permit analysis by spacecraft-mounted spectroscopic techniques. In addition, halite is readily dissolved, permitting further analysis of entrained organics.

Zolensky, M.↗

Wall-Modeled Large-Eddy Simulations of Jet Noise in Flight Conditions

A campaign of wall-modeled large-eddy simulations (WMLES) using structured curvilinear overlapping grids has been performed with the Launch Ascent and Vehicle Aerodynamics (LAVA) computational fluid dynamics (CFD) software to predict jet noise for single-stream axisymmetric round jets. The simulations address the new Prediction Uncertainty Reduction (PUR) technical challenge within the context of NASA’s Commercial Supersonic Technology (CST) project. The focus of this effort is to generate a simulation database for single-stream axisymmetric round nozzles at several operating points both for static (no ambient co-flow), and in-flight (M ͚ =0.3 co-flow) conditions. The operating conditions range in jet exit Mach number from 0.38 to 1.1 with nozzle temperature ratios (NTR) from 0.84 to 2.7. The effect of the flight-stream on far-field noise sound spectra is assessed. Comparison of LES predictions to microphone array measurements demonstrate good agreement within the resolved frequency range. A dip in the predicted low frequency noise spectra for observers between 120° and 145° is observed. This dip is smaller for lower Mach numbers and seems to be correlated to the Mach wave radiation angle. The Mach 1.1 jet shows broadband-shock associated noise. While the onset of BBSN appears to be captured correctly in WMLES, some differences in its magnitude and the prominent frequency at which it occurs persist between the experiment and the simulations. The effect of the outer nozzle boundary layer state created by the co-flow is assessed and shows to be important for accurate comparisons with experiments. A change of 2.5dB between a slip-wall condition and a artificially thickened turbulent boundary layer was observed. In addition, simulations were performed with an alternative nozzle geometry that includes a internal plug and has twice the nozzle exit diameter. These two configurations resulted in very comparable spectra which is consistent with experimental observations. A generally stronger deviation from experimental results is observed for in-flight cases compared to static conditions. The applicability and correct usage of acoustic analogies used for far-field propagation with strong turbulent co-flows needs to be investigated more systematically using canonical problems to improve comparisons between experiments and WMLES. This is especially true for coherent noise sources seen in BBSN.

CST↗

TOWARD A METHOD FOR SCALING HUMAN BODY MODELS IN AN IMU-BASED WORKFLOW

BACKGROUND Scaled biomechanical models can more accurately inform crew health decisions when tailored to the wide range of astronaut sizes. One component to improve scaling of existing models to better represent each unique astronaut’s size is the individual length scaling of limbs. Traditionally, these lengths are determined by motion capture or manual measurement. A new method is herein proposed for length scaling which can be done by measuring linear and angular accelerations at a desired point during isolated motion around a point of rotation, then calculating the distance between the desired point and point of rotation. When an Inertial Measurement Unit (IMU) device is placed at the distal point of a limb, the isolated motion is about that limb’s proximal joint. For example, to measure forearm length, an IMU is placed at the wrist, the point of rotation is at the elbow, and the isolated motion is forearm flexion and extension. These calculated lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. This method of scaling limb segments can be used for any limb that has an easily defined proximal joint for the limb to rotate around including hands, arms, legs, feet. Utilizing IMUs for data collection also provides the synergistic ability to record data without a dedicated space in a room with many cameras, therefore reducing the data collection footprint, or record data where optical motion capture is not possible, such as inside a spacesuit. METHODS AND RESULTS To test this method, upper body data collection was performed with 5 Xsens DOT IMUs on a single subject. IMUs consist of an accelerometer, a gyroscope, and a magnetometer which collect linear acceleration, angular velocity, and magnetic fluctuations, respectively. Before any ground-based laboratory collection, the magnetic fluctuations are used to correct the heading of the IMU in space relative to the Earth’s magnetic field. The direct measurement of angular velocity is integrated to calculate angular acceleration. Then the linear acceleration ( a ) and angular acceleration (α) are solved using r = at/α to calculate the radius, which in this case is the distance between the IMU and the point of rotation (i.e., segment length). The IMU must be placed at the most distal point of the limb being measured (i.e., ankle if measuring lower leg length) and the test plan must consist of an isolated motion about that limb’s proximal joint (i.e., knee flexion and extension if measuring lower leg length). The distances (radii) calculated at every time interval were filtered (bandpass filter keeping 5th-90th percentile data) to eliminate outliers and spurious data that occur when the isolated motion was stopped or nearly stopped. The remaining distances were averaged, resulting in the calculated limb length. Scaling factors were then computed by dividing the calculated limb length by the unscaled model’s length. These scale factors are plugged into the Scale Tool in OpenSim [1,2] to apply the scaling to the OpenSim Full Body Rajagopal Model [3,4]. Manual measurements of limb lengths were taken before data collection started and used for comparing against the calculated lengths. The Anthropometric Survey of US Army Personnel (ANSUR II) [5] was also used as a third source of reference for limb length measurements. The following measurements were retrieved from the subject before data collection: 34.5 cm from L1 to C7 (thorax), 25.7 cm from C7 Joint Center (JC) to head vertex (neck and head), 36.3 cm from shoulder JC to elbow JC (humerus), 29.5 cm from elbow JC to wrist JC (forearm), and 16.2 cm from clavicle to acromion (clavicle). Of those five, forearm and humerus lengths were calculated using this proposed method to obtain preliminary results. The forearm length after filtering and averaging was calculated to be 37.6 cm. This is a 28% overestimation from the measured forearm length (29.5 cm). The humerus length after filtering and averaging was calculated to be 47.8 cm. This is a 31% difference from the measured subject length (36.3 cm). Sources of error include imperfect isolated motion (method currently expects that motion should be perfectly circular in a 2D plane, include no rotation of the IMU, and be relatively smooth; a more secure IMU attachment method will help), unrefined filter techniques (removed highest and lowest values with 20% high and low pass filters and no smoothing filters), arbitrary removal of stopped or near stopped data (kept data for only a short range before and after the angular velocity peaking), and a more representative method for removing gravitational acceleration is needed (current method is to zero all accelerations against a baseline taken just before the isolated motion which does not account for the gravitational acceleration changed due to IMU rotation during movement). Addressing these error sources will improve the accuracy of the limb length calculation. Next steps include creating a method for whole-body scaling estimation using individual limb scale factors. Continued pursuit of these techniques is expected to enable acquiring anthropometric information using only IMUs in real-time.

E. K. Marecki↗

Fan Noise Predictions of the NASA Source Diagnostic Test using Unsteady Simulations with LAVA Part II - Tonal and Broadband Noise Assessment

The NASA Source Diagnostic Test (SDT) campaign experimental data is used for validation of a sliding mesh technique recently implemented within the Launch, Ascent, and Vehicle Aerodynamics computational framework for time-accurate simulation of rotating fans. The far-field acoustics are analyzed in this work, building upon the aerodynamic validation studies previously published in Part I. Two modeling approaches are explored: the unsteady Reynolds-averaged Navier Stokes (uRANS) with the negative Spalart-Allmaras (SA-neg) turbulence model closure, and a hybrid Reynolds-averaged Navier Stokes/large-eddy simulation (RANS/LES) paradigm employing a zonal detached-eddy simulation (ZDES) closure with enhanced shielding protection. Two convective flux scheme approaches with different dissipation properties are also explored with ZDES. The Ffowcs-Williams and Hawkings (FW-H) permeable surface approach is used for propagation of the near-field acoustics to the far-field microphone locations. This work analyzes the low-speed (approach) condition, characterized by a fan rotation speed of 7808 rotations-per-minute (RPM). Three different grid levels ranging between 200 million and 1.1 billion grid points are considered. Results show good prediction of the broadband noise levels at sideline angles ranging between 70° and 110°. The forward arc observers show an under-prediction of the overall sound pressure levels (OASPL) even at the fine grid level. A breakdown of the inlet and exhaust contributions reveals a steep drop-off in the broadband noise levels past a blade-passing frequency (BPF) of 1.5, potentially caused by a lack of resolved small-scale turbulent fluctuations in the interstage region. Past 110° the OASPL are over-predicted by up to 10 dB due to an over-prediction of the low-frequency broadband noise levels in the aft arc. The detuning of BPF2 caused by small deviations in the blade stagger angle around the wheel is captured, and a corresponding decrease in the sound power level for this cut-on tone is observed.

AATT↗