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At least 1,783 records · Page 99

From Atom to Engine: Understanding Fundamental Effects of Structure on Combustion Using Tandem Experiment and Computation

The ability to tie structural features to a fuel candidate’s ignition properties provides a path for rational design of advantaged fuels that facilitate higher-efficiency, lower-emitting combustion in engines. The time evolution of a fuel’s radical population directly correlates with global combustion parameters, and because the generated radicals depend on the initial structure and reaction pathways of the fuel molecule, it follows that the molecular structure of a fuel has a direct impact on this cascade, and therefore salient ignition-tied fuel properties. This work aims to understand the impact of structural features in the context of global combustion properties for direct application to emerging engine technologies. Specifically, we highlight the ability to identify potential fuel blendstocks for specific engine strategies by examining and elucidating the radical cascade tied to ignition. A representative subset of alcohols possessing a variety of structural features (e.g. branching, chain length) was selected for study using a robust combination of experimental and computational methods. The approach begins with identifying short-lived radicals and likely abstraction sites upon pyrolysis in a microreactor coupled with photoionization mass spectrometry for direct detection of product species. In tandem, electronic structure calculations were performed to calculate the relevant potential energy surfaces for fuel pyrolysis as well as the subsequent O2 addition-isomerization reactions, which govern ignition behavior. Furthermore, the theoretical energetic and ro-vibrational data are used to calculate rate constants for direct ignition modeling to explore how structural effects impact NTC behavior. The microreactor data combined with electronic structure theory calculations provide a well-informed picture of the reactions relevant to ignition for each fuel in this study, as well as the most likely radicals generated under engine conditions. This thorough fundamental picture of fuel decomposition and ignition chemistry is used to correlate the observed ignition behavior to molecular structural effects.

advanced biofuels↗

Effects of PLA/PHB Blend Ratio and Wood Flour Loading on the Melt Rheology and Thermomechanical Properties of Biobased Polymer Composites

The development of sustainable, biobased polymer composites is crucial for reducing supply chain dependence on fossil fuels. A major challenge lies in understanding and predicting the processability of these sustainable material alternatives, which directly impacts large-scale manufacturing. Here, this study systematically investigates the effect of poly(lactic acid) (PLA)/polyhydroxybutyrate (PHB) blend ratios and wood flour (WF) loadings on the thermal, rheological, and mechanical properties of the composites. Composites were prepared via melt compounding and characterized by using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), oscillatory shear melt rheology, tensile testing, and scanning electron microscopy. Results showed that increasing the PHB content lowered the glass transition temperature, while higher PHB and WF loadings decreased thermal stability. Complex viscosity decreased with increasing PHB in 0 and 10% WF, whereas it increased in 20% and 30% WF for PHB-rich blends (80/20 and 70/30 PLA/PHB) due to stronger filler interactions with flexible PHB chains. At 30% WF, PHB-containing composites also showed elastic dominance with G′ higher than G″. This behavior was confirmed by van Gurp–Palmen plots, where the phase angle decreased with increasing PHB and WF loadings. WF addition also shifted Cole–Cole plots away from semicircular terminal relaxation, while time–temperature superposition validity was maintained, confirming that polymer chain dynamics continue to dominate melt behavior. Young’s modulus increased with WF loading, while tensile strength and toughness decreased due to weaker interfacial adhesion between the matrix and the filler. Interestingly, 10% WF systems containing PHB exhibited the highest toughness among all of the filled systems, indicating synergistic reinforcement from WF fillers and PHB-induced ductility. Overall, melt rheology effectively captured the internal structure and stiffness of the composites as the formulation changed, reinforcing the concept that the PLA/PHB ratio and WF content can be tuned to adjust melt elasticity and balance mechanical property trade-offs for targeted applications.

melt rheology↗

Effects of Melt Processing on Evolution of Structure in PEEK

We report on the effects of melt processing temperature on structure formation in Poly(ether-ether-ketone), PEEK. Real time Small Angle X-ray Scattering, SAXS, and thermal analysis are used to follow the melting behavior after various stages of processing. Assignment of peaks to structural entities within the material, the relative perfection of the crystals, and the possibility of their reorganization, are all influenced by the melt processing history. With the advent of high intensity synchrotron sources of X-radiation, polymer scientists gain a research tool which, when used along with thermal analysis, provides additional structural information about the crystals during growth and subsequent melting. PEEK is an engineering thermoplastic polymer with a very high glass transition temperature (145 C) and crystal melting point (337 C). PEEK has been the subject of recent studies by X-ray scattering in which melt and cold crystallization were followed in real-time. X-ray scattering and thermal studies have been used to address the formation of dual endothermic response which has been variously ascribed to lamellar insertion, dual crystal populations, or melting followed by re-crystallization. Another important issue is whether all of the amorphous phase is located in interlamellar regions, or alternatively whether some is located in "pockets" away from the crystalline lamellar stacks. The interpretation of scattering from lamellar stacks varies depending upon whether such amorphous pockets are formed. Some groups believe all of the amorphous phase is interlamellar. This leads to selection of a smaller thickness for the crystals. Other groups suggest that most amorphous phase is not interlamellar, and this leads to the suggestion that the crystal thickness is larger than the amorphous layer within the stacks. To investigate these ideas, we used SAXS and Differential Scanning Calorimetry to compare results of single and dual stage melt crystallization of PEEK using a treatment scheme involving annealing/crystallization at T(sub a1) followed by annealing at T(sub a2) where either T(sub a1) < T(sub a2) or T(sub a1) > T(sub a2). We proposed a model to explain multiple melting endotherms in PPS, treated according to one or two-stage melt or cold crystallization. Key features of this model are that multiple endotherms: (1) are due to reorganization/recrystallization after cold crystallization; and, (2) are dominated by crystal morphology after melt crystallization at high T. In other words, multiple distinct crystal populations are formed by the latter treatment, leading to observation of multiple melting. PEEK 45OG pellets (ICI Americas) were the starting material for this study. Films were compression molded at 400 C, then quenched to ice water. Samples were heated to 375 C in a Mettler FP80 hot stage and held for three min. to erase crystal seeds before cooling them to T(sub a1) = 280 C . Samples were held at T(sub a2) for a period of time, then immediately heated to 360 C. In the second treatment samples were held at T(sub a1) = 31 C for different crystallization times t(sub c) then cooled to 295 C and held 15 min. In situ (SAXS) experiments were performed at the Brookhaven National Synchrotron Light Source with the sample located inside the Mettler hot stage. The system was equipped with a two-dimensional position sensitive detector. The sample to detector distance was 172.7 cm and the X-ray wavelength was 1.54 Angstroms. SAXS data were taken continuously during the isothermal periods and during the heating to 360 C at 5 C/min. Each SAXS scan was collected for 30 sec. Since the samples were isotropic, circular integration was used to increase the signal to noise ratio. After dual stage melt crystallization with T(sub a1) < T(sub a2) the lower melting endotherm arises from holding at T(sub a1). During cooling a broad distribution of crystals forms, and the low-melting tail is perfected during T(sub al). Heating to T(sub a2) melts these imperfect crystals and allows others with greater average long spacing to form in their place. After dual stage crystallization with T(sub a1) > T(sub a2), the amount of space remaining for additional growth at T(sub a2) depends upon the holding time at T(sub a1). The long period of crystals formed at T(sub a2) is smaller than that formed at T(sub a1) due to growth in a now-restricted geometry. Perfection of crystals is seen as an increase of the intensity of the population scattering at higher s, while the intensity of the population scattering at lower s stays constant. During heating from below to above the minor endotherm, we see rapid decrease of the intensity of the X-ray scattering corresponding to the population of crystals scattering in the shoulder. Another important observation is that after the sample is annealed at 295 C, the shoulder intensity is restored once again. The population scattering at higher s remains longer before it disappears in the sample treated to the second stage of melt crystallization, compared to the sample crystallized with a single stage. This could be interpreted as an effect of continued perfection of the less perfect population, which is also reflected in the increased melting temperature of the smaller endotherm as the holding time at 295 C increases. In the corresponding DSC scans we see a shift in the area and the peak temperature of the lower melting endotherm with an increase of the annealing time.

Georgiev, Georgi↗

Evaluation of Aerosol Properties over Ocean from Moderate Resolution Imaging Spectroradiometer (MODIS) during ACE-Asia

The Aerosol Characterization Experiment-Asia (ACE-Asia) was conducted in March-May 2001 in the western North Pacific in order to characterize the complex mix of dust, smoke, urban/industrial pollution, and background marine aerosol that is observed in that region in springtime. The Moderate Resolution Imaging Spectroradiometer (MODIS) provides a large-scale regional view of the aerosol during the ACE-Asia time period. Focusing only on aerosol retrievals over ocean, MODIS data show latitudinal and longitudinal variation in the aerosol characteristics. Typically, aerosol optical depth (tau(sub a)) values at 0.55 micrometers are highest in the 30 deg. - 50 deg. latitude band associated with dust outbreaks. Monthly mean tau(sub a) in this band ranges approx. 0.40-70, although large differences between monthly mean and median values indicate the periodic nature of these dust outbreaks. The size parameters, fine mode fraction (eta), and effective radius (r(sub eff)) vary between monthly mean values of eta = 0.47 and r(sub eff)= 0.75 micrometers in the cleanest regions far offshore to approximately eta = 0.85 and r(sub eff) =.30 micrometers in near-shore regions dominated by biomass burning smoke. The collocated MODIS retrievals with airborne, ship-based, and ground-based radiometers measurements suggest that MODIS retrievals of spectral optical depth fall well within expected error (DELTA tau(sub a) = plus or minus 0.03 plus or minus 0.05 tau(sub a)) except in situations dominated by dust, in which cases MODIS overestimate both the aerosol loading and the aerosol spectral dependence. Such behavior is consistent with issues related to particle nonsphericity. Comparisons of MODIS-derived r(sub eff) with AERONET retrievals at the few occurrences of collocations show MODIS systematically underestimates particle size by 0.2 micrometers. Multiple-year analysis of MODIS aerosol size parameters suggests systematic differences between the year 2001 and the years 2000 and 2002, which are traced to instrumental electronic cross talk. Sensitivity studies show that such calibration errors are negligible in tau(sub a) retrievals but are more pronounced in size parameter retrievals, especially for dust and sea salt.

Chu, D. A.↗

Improvement of Raman lidar algorithm for quantifying aerosol extinction

Aerosols are particles of different composition and origin and influence the formation of clouds which are important in atmospheric radiative balance. At the present there is high uncertainty on the effect of aerosols on climate and this is mainly due to the fact that aerosol presence in the atmosphere can be highly variable in space and time. Monitoring of the aerosols in the atmosphere is necessary to better understanding many of these uncertainties. A lidar (an instrument that uses light to detect the extent of atmospheric aerosol loading) can be particularly useful to monitor aerosols in the atmosphere since it is capable to record the scattered intensity as a function of altitude from molecules and aerosols. One lidar method (the Raman lidar) makes use of the different wavelength changes that occur when light interacts with the varying chemistry and structure of atmospheric aerosols. One quantity that is indicative of aerosol presence is the aerosol extinction which quantifies the amount of attenuation (removal of photons), due to scattering, that light undergoes when propagating in the atmosphere. It can be directly measured with a Raman lidar using the wavelength dependence of the received signal. In order to calculate aerosol extinction from Raman scattering data it is necessary to evaluate the rate of change (derivative) of a Raman signal with respect to altitude. Since derivatives are defined for continuous functions, they cannot be performed directly on the experimental data which are not continuous. The most popular technique to find the functional behavior of experimental data is the least-square fit. This procedure allows finding a polynomial function which better approximate the experimental data. The typical approach in the lidar community is to make an a priori assumption about the functional behavior of the data in order to calculate the derivative. It has been shown in previous work that the use of the chi-square technique to determine the most likely functional behavior of the data prior to actually calculating the derivative eliminates the need for making a priori assumptions. We note that the a priori choice of a model itself can lead to larger uncertainties as compared to the method that is validated here. In this manuscript, the chi-square technique that determines the most likely functional behavior is validated through numerical simulation and by application to a large body of Raman lidar measurements. In general, we show that the chi-square approach to evaluate aerosol extinction yields lower extinction uncertainty than the traditional technique. We also use the technique to study the feasibility of developing a general characterization of the extinction uncertainty that could permit the uncertainty in Raman lidar aerosol extinction measurements to be estimated accurately without the use of the chi-square technique.

Russo, Felicita↗

The role of surface forces in environment-enhanced cracking of brittle solids

Fracture initiation and propagation in brittle materials is promoted in surface-reactive (sorptive) environments, a phenomenon known as subcritical crack growth (SCG). Laboratory measured crack-propagation velocity vs. stress intensity factor relationships typically exhibit highly nonlinear, multi-stage characteristics that are sensitive to environmental factors such as adsorbate concentration and temperature. For practical purposes, empirical relationships (e.g., a power law) have been used to describe this complex phenomenon. However, how the overall SCG behavior emerges from the underlying fundamental processes near the crack tip, such as the interaction of the crack surfaces separated by only a few nanometers and mass transport within the nano-confined space, is still not well understood. This paper develops a mechanistic, surface-force-based fracture theory (SFFT) which integrates surface force models, fluid transport models, and linear elastic fracture mechanics to quantitatively explain the multi-stage characteristics of SCG in brittle solids. A numerical model is developed based on SFFT and solved through an implicit partitioned scheme for efficiency and modularity. The results are validated by Wiederhorn's data on crack propagation in soda-lime glasses at a wide range of relative humidity levels. We show that, for the first time, the entire range of an SCG curve can be captured by a single physics-based model. The predicted SCG curves reveal that the development of repulsive disjoining pressure behind the crack tip can be responsible for the reduced apparent fracture toughness in a sorptive environment. In conclusion, the shape of the SCG curve, and its changes with respect to the environment, is found to critically depend on the assumed transport models.

36 MATERIALS SCIENCE↗

Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission

Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft’s health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system’s health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD’s ability to run successfully in a spacecraft’s resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.

Nikora, Allen↗

Enabling Mission Flexibility to Battery Driven Deep Space Endeavors With Generalized Battery-Health-Monitoring Using Physics-Based and Data-Driven Reduced-Order Models

The needs and requirements for an electrochemical energy storage for deep space exploration is well explored. It is often understood that different mission sites and environmental conditions require different battery chemistries or technologies. Additionally, various engineering solutions are deployed to overcome specific chemical challenges. One often overlooked need is the “health” monitoring of an electrochemical storage system. The term generalized health monitoring, as envisioned in this work, refers to the monitoring of various aspects such as electrode health, electrolyte health, reaction pathway health, cooling system health, sensor health, and BMS health [1]. Generalized health monitoring allows mission leads, engineers, and scientists to incorporate flexibility in mission designs, make on-the-fly mission changes, and extend the duration of science missions. Moreover, it enables automation and data-driven decision-making without compromising safety and performance. Recently, our group developed a hierarchy of thermal reduced-order models (TROM) by combining a physics-based modeling approach and data-driven model reduction techniques applied to flight data [2]. The resulting TROMs were found to be not only accurate but also identifiable from the flight data. Consequently, the coefficient of variance of the model parameters is small over the course of hundreds of flights, allowing for monitoring the parameter evolution trajectories as the battery ages and degrades. These parameters constitute the metrics of the generalized health of a battery. Monitoring their evolution allows such models to be used for anomaly detection and prognostics, improving early detection of abnormal behavior and thus enabling timely maintenance, longer battery life, and enhanced battery safety. For this presentation, the practicality of the thermal model will be validated on a pack of 14cells under various topology configurations such as 1S14P, 2P7S, 7S2P, and 1P14S. It is well known that manufacturing and non-uniform aging lead to variability in the performance of a cell, which is exacerbated by cell balancing during active load. Additionally, in extreme scenarios, the paramount objective is to complete the mission, regardless of the stresses on the battery. Topology-induced balancing issues further stress the battery. The goal of this study is to determine if the noise (identifiability) in the reduced-order thermal model parameters is sensitive to topology, cell spacing, cooling strategy, and manufacturing or age variability. The variability in cells is considered by assuming a multimodal distribution for microscopic parameters of a cell (such as porosity, tortuosity, reaction kinetics, volumetric thermal conductivity, and volumetric heat capacity). The compounded effect of manufacturing variability, topological selection, cooling strategies, and cell balancing ages each cell in a battery differently. The study aims to clarify whether the challenge in extracting maximum information depends on the minimum number of sensors or models used for data extraction.

Automation↗

Estimating the Single-Trial Characteristics of Event-Related Responses: Evaluation of the MCERP Algorithm

Single-trial event-related responses collected during the course of an experiment are typically averaged before analysis resulting in a rather crude picture of event-related brain dynamics. It has been quite clear for some time that these responses exhibit trial-to-trial variability: however, the computational techniques necessary to deal with such responses in noisy conditions have not been available. To this end we have developed the multiple-component, event-related potential model (mcERP), which assumes that the each event-related response consists of a sum of multiple evoked components each described by a stereotypical waveshape. These waveshapes are allowed to vary in amplitude and onset latency from trial to trial, which allows us to capture, to first-order, the trial-dependent variations in event-related brain dynamics. We have constructed many sets of synthetic data designed to simulate intracortical recordings from a 15 channel, linear-array multielectrode implanted acutely in V1 of an awake-behaving macaque undergoing visual stimulation with a red light flash. This synthetic data was used to characterize the performance of the mcERP algorithm. First we quantified the degree to which such trial-to-trial variability aids in the identification of multiple components, and we demonstrate that amplitude variability is a more important factor in component separation than latency variability. Second, we quantified the behavior of the algorithm under two distinct signal-to-noise ratio (SNR) conditions: Gaussian noise independently present in each channel, and highly correlated (1/f distributed), far-field noise presented identically in each channel of the array. The mcERP algorithm was found to be robust to noise accurately identifying all component waveshapes and their associated single-trial characteristics down to SNR levels of -20dB for Gaussian noise and -7dB for 1/f far-field noise. Comparisons of the performance of this algorithm with factor analysis (FA) and independent component analysis (ICA) will be described by Knuth et al. (SFN abstracts, 2002). In addition, the advantages of application of mcERP to real data will be described by Shah et al, (these abstracts, 2002: SFN abstracts, 2002).

Knuth, K. H.↗

Soil Water Content Effects on Net Ecosystem CO2 Exchange and Actual Evapotranspiration in a Mediterranean Semiarid Savanna of Central Chile

Biosphere-atmosphere water and carbon fluxes depend on ecosystem structure, and their magnitudes and seasonal behavior are driven by environmental and biological factors. We studied the seasonal behavior of net ecosystem CO2 exchange (NEE), Gross Primary Productivity (GPP), Ecosystem Respiration (RE), and actual evapotranspiration (ETa) obtained by eddy covariance measurements during two years in a Mediterranean Acacia savanna ecosystem (Acacia caven) in Central Chile. The annual carbon balance was −53 g C/sq. m in 2011 and −111 g C/sq. m in 2012, showing that the ecosystem acts as a net sink of CO2, notwithstanding water limitations on photosynthesis observed in this particularly dry period. Total annual ETa was of 128 mm in 2011 and 139 mm in 2012. Both NEE and ETa exhibited strong seasonality with peak values recorded in the winter season (July to September), as a result of ecosystem phenology, soil water content and rainfall occurrence. Consequently, the maximum carbon assimilation rate occurred in wintertime. Results show that soil water content is a major driver of GPP and RE, defining their seasonal patterns and the annual carbon assimilation capacity of the ecosystem, and also modulating the effect that solar radiation and air temperature have on NEE components at shorter time scales.

Meza, Francisco J.↗

What’s That Supposed to Mean? Capturing Micro-Behaviors in Teams

Future long-duration space exploration (LDSE) crews will require extensive coordination, cooperation, and team functioning as they face a myriad of challenges rooted in both taskwork and teamwork (Bell et al., 2015; Landon et al., 2018). While exposed to extreme conditions, crew members must navigate living and working together in prolonged confinement. Moreover, astronaut teams are becoming increasingly diverse, introducing significant variability in team composition. This increasing diversity, alongside traditional constraints of LDSE, introduces additional challenges into effective team functioning. To date, most methods for capturing team functioning rely on self-report measures. Such measures are prone to several limitations, including but not limited to social desirability bias, halo effect, and leniency effects (Trull & Ebner-Priemer, 2013), which skew data and limit nuanced understandings of phenomena at play. Self-report measures broadly capture team functioning, lending the nature of such methods to identifying underlying “macro”-behaviors (i.e., behaviors that are long-standing and last over time). However, team functioning is far more complex than a series of macro-behaviors, rendering reliance on self-report data deficient for accurate measurement. Recent research demonstrates the potential of alternative methods for capturing team functioning, such as speech and physiological data (Chaffin et al., 2017; Murray & Oertel, 2018). Consequently, these methods are more suitable for capturing micro-behaviors: brief, often unconscious expressions that affect the extent to which an individual feels included by others around them (Paletz et al., 2013). Micro-behaviors can be further classified into microaggressions (i.e., subtle, negative exchanges; Keller & Galgay, 2010) or micro-affirmations (i.e., subtle, positive exchanges; Kyte et al. 2020), both of which influence team functioning. Due to the subtle nature of micro-behaviors, contextual factors have a significant impact when determining if it is aggressive or affirmative. Additionally, several iterations of microbehaviors can have lingering effects on team interactions. For example, the use of “mm-hmm” by a crew member can function as both a micro-affirmation and micro-aggression. Specifically, it can be indication of active listening (i.e., micro-affirmation) or as an expression of annoyance (i.e., aggression) depending on the context in which it occurs. Auditory features (e.g., tone, frequency) can help delineate between the two forms; however, the contextual factors (e.g., previous interactions between team members, crew demographics) add a layer of complexity that render auditory features alone as insufficient to capture micro-behaviors. Consequently, this paper seeks to provide a novel approach in which multi-modal data (i.e., auditory features and contextual features) are used in a random-forest model to better identify distinguishing characteristics between micro-affirmations and micro-aggressions. In turn, detected micro-behaviors are used to predict team performance, thereby demonstrating the value of capturing micro-behaviors as supplemental data to macro-behaviors.

Sydney R. Begerowski↗

Numerical simulation of shock/turbulent boundary layer interaction

Most flows of aerodynamic interest are compressible and turbulent. However, our present knowledge on the structures and mechanisms of turbulence is mostly based on incompressible flows. In the present work, compressibility effects in turbulent, high-speed, boundary layer flows are systematically investigated using the Direct Numerical Simulation (DNS) approach. Three-dimensional, time-dependent, fully nonlinear, compressible Navier-Stokes equations were numerically integrated by high-order finite-difference methods; no modeling for turbulence is used during the solution because the available resolution is sufficient to capture the relevant scales. The boundary layer problem deals with fully-turbulent compressible flows over flat geometries. Apart from its practical relevance to technological flows, turbulent compressible boundary layer flow is the simplest experimentally realizable turbulent compressible flow. Still, measuring difficulties prohibit a detailed experimental description of the flow, especially in the near-wall region. DNS studies provide a viable means to probe the physics of compressible turbulence in this region. The focus of this work is to explore the paths of energy transfer through which compressible turbulence is sustained. The structural similarities and differences between the incompressible and compressible turbulence are also investigated. The energy flow patterns or energy cascades are found to be directly related to the evolution of vortical structures which are generated in the near-wall region. Near-wall structures, and mechanisms which are not readily accessible through physical experiments are analyzed and their critical role on the evolution and the behavior of the flow is documented extensively.

Biringen, Sedat↗

The OpenSE Cookbook: A Practical, Recipe Based Collection of Patterns, Procedures, and Best Practices for Executable Systems Engineering for the Thirty Meter Telescope

The OpenSE Cookbook is an open-sourced collection of patterns, procedures, and best practices targeted for systems engineers who seek guidance on applying model-based and executable systems engineering (MBSE) using SysML. Its content has emerged from the system level modeling effort on the European Framework Program 6 (FP6) and the Thirty Meter Telescope (TMT). The TMT MBSE approach applied the Executable Systems Engineering Method (ESEM) and the open-source Engineering Environment (OpenMBEE) to specify, analyze, and verify requirements of TMT’s Alignment and Phasing System (APS) and the Narrow Field Infrared Adaptive Optics System (NFIRAOS). In these applications, implicit dependencies are made explicit in a formal model through the use of ESEM, OpenMBEE, and SysML modeling constructs. The value proposition for applying this MBSE approach was to establish precise requirements and fine-grained traceability to system designs, and to verify key requirements beginning early in development. The integration of ESEM and the OpenMBEE tooling infrastructure (providing linked-data and web-operability) is a significant added value for the MBSE approach. The APS is responsible for the overall pre-adaptive optics wavefront quality, using starlight to measure wavefront errors and align the TMT optics. In the formally integrated and executable SysML model, simulations are performed to analyze the impact of changed requirements and verify specified constraints for various operational scenarios. The APS team used several modeling patterns to capture information such as the requirements, the operational scenarios, involved subsystems and their interaction points, the estimated or required time durations, and the mass and power consumption. Adaptive optics systems are designed to sense real-time atmospheric turbulence and correct the telescope’s optical beam to remove its effect. The system model for the adaptive optics operational modes was developed to capture sequence behaviors and operational scenarios to run Monte-Carlo simulations for verifying acquisition time, observing efficiency, and operational behavior requirements. The model is particularly useful for investigating the effect of parallelization, identifying interface issues, and re-ordering sequence acquisition tasks. A former version of the Cookbook (which is now updated to MBSE challenges, goals, and lessons learned) included modeling guidelines and conventions for all system aspects, hierarchy levels, and views, which were developed during for the Active Phasing Experiment (APE), an opto-mechatronical system technology demonstrator for the Extremely Large Telescope (ELT). The Cookbook utilizes the above mentioned system models as real-world case-studies to demonstrate and document the applications of the recipes, providing also instructional examples and addressing the available tooling support. The Cookbook is accompanied by a number of SysML models and aodel libraries which facilitate model authoring and maintenance. The Cookbook covers the different aspects of Systems Engineering such as management of Requirements, Design (behavior and structure), Interfaces, Interdisciplinary Integration, Analysis, Trade Studies, and Technical Resources. This paper presents the background, motivation, architecture, and highlights some key content of the Cookbook. For example, interface management, error budget management, requirements verification, Monte Carlo driven analysis, and timing analysis of operational scenarios. The paper discusses how the capabilities of OpenMBEE contributed significantly to the adoption of executable systems engineering.

Brower, Eric↗

VpROM: a novel variational autoencoder-boosted reduced order model for the treatment of parametric dependencies in nonlinear systems

Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction, such as Proper Orthogonal Decomposition. The limitation of the linear nature of such operators is typically tackled via a library of local reduction subspaces, which requires the assembly of numerous local ROMs to address parametric dependencies. Our work attempts to define a more generalisable mapping between parametric inputs and reduced bases for the purpose of generative modeling. We propose the use of Variational Autoencoders (VAEs) in place of the typically utilised clustering or interpolation operations, for inferring the fundamental vectors, termed as modes, which approximate the manifold of the model response for any and each parametric input state. The derived ROM still relies on projection bases, built on the basis of full-order model simulations, thus retaining the imprinted physical connotation. However, it additionally exploits a matrix of coefficients that relates each local sample response and dynamics to the global phenomena across the parametric input domain. The VAE scheme is utilised for approximating these coefficients for any input state. This coupling leads to a high-precision low-order representation, which is particularly suited for problems where model dependencies or excitation traits cause the dynamic behavior to span multiple response regimes. Moreover, the probabilistic treatment of the VAE representation allows for uncertainty quantification on the reduction bases, which may then be propagated to the ROM response. The performance of the proposed approach is validated on an open-source simulation benchmark featuring hysteresis and multi-parametric dependencies, and on a large-scale wind turbine tower characterised by nonlinear material behavior and model uncertainty.

Conditional VAEs↗

What Controls the Entrainment Rate of Dry Buoyant Thermals with Varying Initial Aspect Ratio?

Here, this study uses theory and numerical simulations to analyze the nondimensional spreading rate a (change in radius with height) of buoyant thermals as they rise and entrain surrounding environmental fluid. A focus is on how a varies with initial thermal aspect ratio A r , defined as height divided by width of the initial buoyancy perturbation. An analytic equation for thermal ascent rate w t that depends on a is derived from the thermal-volume-averaged momentum bud get equation. The thermal top height when w t is maximum, defining a critical height z c , is inversely proportional to a. The height z c also corresponds to the thermal top height when buoyant fluid along the thermal’s vertical axis is fully replaced by entrained nonbuoyant environmental fluid rising from below the thermal. The time scale for this process is controlled by the vertical velocity of parcels rising upward through the thermal’s core. This parcel vertical velocity is approximated from Hill’s analytic spherical vortex, yielding an analytic inverse relation between a and A r . Physically, this a–A r relation is connected to changes in circulation as A r is modified. Numerical simulations of thermals with A r varied from 0.5 to 2 give a values close to the analytic theoretical relation, with a factor of ~3 decrease in a as A r is increased from 0.5 to 2. The theory also explains why a of initially spherical thermals from past laboratory and modeling studies is about 0.15. Overall, this study provides a theoretical underpinning for understanding the entrainment behavior of thermals, relevant to buoyantly driven atmospheric flows.

54 ENVIRONMENTAL SCIENCES↗

Time-dependent Computational Studies of Premixed Flames in Microgravity

This report describes the research performed at the Center for Reactive Flow and Dynamical Systems in the Laboratory for Computational Physics and Fluid Dynamics, at the Naval Research Laboratory, in support of NASA Microgravity Science and Applications Program. The primary focus of this research is on investigating fundamental questions concerning the propagation and extinction of premixed flames in earth gravity and in microgravity environments. Our approach is to use detailed time-dependent, multispecies, numerical models as tools to simulate flames in different gravity environments. The models include a detailed chemical kinetics mechanism consisting of elementary reactions among the eight reactive species involved in hydrogen combustion, coupled to algorithms for convection, thermal conduction, viscosity, molecular and thermal diffusion, and external forces. The external force, gravity, can be put in any direction relative to flame propagation and can have a range of values. Recently more advanced wall boundary conditions such as isothermal and no-slip have been added to the model. This enables the simulation of flames propagating in more practical systems than before. We have used the numerical simulations to investigate the effects of heat losses and buoyancy forces on the structure and stability of flames, to help resolve fundamental questions on the existence of flammability limits when there are no external losses or buoyancy forces in the system, to understand the interaction between the various processes leading to flame instabilities and extinguishment, and to study the dynamics of cell formation and splitting. Our studies have been able to bring out the differences between upward- and downward-propagating flames and predict the zero-gravity behavior of these flames. The simulations have also highlighted the dominant role of wall heat losses in the case of downward-propagating flames. The simulations have been able to qualitatively predict the formation of multiple cells and the cessation of cell-splitting. Our studies have also shown that some flames in a microgravity environment can be extinguished due to a chemical instability and without any external losses. However, further simulations are needed to more completely understand upward-propagating and zero-gravity flames as well as to understand the potential effect of radiative heat losses.

Kailasanath, K.↗

Candle Flames in Non-Buoyant Atmospheres

This paper addresses the behavior of a candle flame in a long-duration, quiescent microgravity environment both on the space Shuttle and the Mir Orbiting Station. On the Shuttle, the flames became dim blue after an initial transient where there was significant yellow (presumably soot) in the flame. The flame lifetimes were typically less than 60 seconds. The safety-mandated candlebox that contained the candle flame inhibited oxygen transport to the flame and thus limited the flame lifetime. The flames on the Mir were similar, except that the yellow luminosity persisted longer into the flame lifetime because of a higher initial oxygen concentration, The Mir flames burned for as long as 45 minutes. The difference in the flame lifetime between the Shuttle and Mir flames was primarily the redesigned candlebox that did not inhibit oxygen transport to the flame. In both environments, the flame intensity and the height-to-width ratio gradually decreased as the ambient oxygen content in the sealed chamber slowly decreased. Both sets of experiments showed spontaneous, axisymmetric flame oscillations just prior to extinction. The paper also presents a numerical model of a candle flame. The formulation is two-dimensional and time-dependent in the gas phase with constant specific heats, thermal conductivity and Lewis number (although different species can have different Lewis numbers), one-step finite-rate kinetics, and gas-phase radiative losses from CO2 and H2O. The treatment of the liquid/wick phase assumes that the, fuel evaporates from a constant diameter sphere connected to an inert cone. The model predicts a steady flame with a shape and size quantitatively similar to the Shuttle and Mir flames. The computation predicts that the flame size will increase slightly with increasing ambient oxygen mole fraction. The model also predicts pre-extinction flame oscillations if the rate of decrease in ambient oxygen is small enough, such as that which would occur for a flame burning in a sealed ambient.

Dietrich, D. L.↗

Development of Numerical Codes for Modeling Electromagnetic Behavior at High Frequencies Near Large Objects

A study into the problem of determining electromagnetic solutions at high frequencies for problems involving complex geometries, large sizes and multiple sources (e.g. antennas) has been initiated. Typical applications include the behavior of antennas (and radiators) installed on complex conducting structures (e.g. ships, aircrafts, etc..) with strong interactions between antennas, the radiation patterns, and electromagnetic signals is of great interest for electromagnetic compatibility control. This includes the overall performance evaluation and control of all on-board radiating systems, electromagnetic interference, and personnel radiation hazards. Electromagnetic computational capability exists at NASA LaRC, and many of the codes developed are based on the Moment Method (MM). However, the MM is computationally intensive, and this places a limit on the size of objects and structures that can be modeled. Here, two approaches are proposed: (i) a current-based hybrid scheme that combines the MM with Physical optics, and (ii) an Alternating Direction Implicit-Finite Difference Time Domain (ADI-FDTD) method. The essence of a hybrid technique is to split the overall scattering surface(s) into two regions: (a) a MM zone (MMZ) which can be used over any part of the given geometry, but is most essential over irregular and "non-smooth" geometries, and (b) a PO sub-region (POSR). Currents induced on the scattering and reflecting surfaces can then be computed in two ways depending on whether the region belonged to the MMZ or was part of the POSR. For the MMZ, the current calculations proceed in terms of basis functions with undetermined coefficients (as in the usual MM method), and the answer obtained by solving a system of linear equations. Over the POSR, conduction is obtained as a superposition of two contributions: (i) currents due to the incident magnetic field, and (ii) currents produced by the mutual induction from conduction within the MMZ. This effectively leads to a reduction in the size of linear equations from N to N - Npo with N being the total number of segments for the entire surface and Npo the number of segments over the POSR. The scheme would be appropriate for relatively large, flat surfaces, and at high frequencies. The ADI-FDTD scheme provides for both transient and steady state analyses. The restrictive Courant-Friedrich-Levy (CFL) condition on the time-step is removed, and so large time steps can be chosen even though the spatial grids are small. This report includes the problem definition, a detailed discussion of both the numerical techniques, and numerical implementations for simple surface geometries. Numerical solutions have been derived for a few simple situations.

Joshi, R. P.↗