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At least 577 records · Page 32

Modular, thermal bus-to-radiator integral heat exchanger design for Space Station Freedom

The baseline concept is introduced for the 'integral heat exchanger' (IHX) which is the interface of the two-phase thermal bus with the heat-rejecting radiator panels. A direct bus-to-radiator heat-pipe integral connection replaces the present interface hardware to reduce the weight and complexity of the heat-exchange mechanism. The IHX is presented in detail and compared to the baseline system assuming certain values for heat rejection, mass per unit width, condenser capacity, contact conductance, and assembly mass. The spreadsheet comparison can be used to examine a variety of parameters such as radiator length and configuration. The IHX is shown to permit the reduction of panel size and system mass in response to better conductance and packaging efficiency. The IHX is found to be a suitable heat-rejection system for the Space Station Freedom because it uses present technology and eliminates the interface mechanisms.

Chambliss, Joe↗

The in-flight calibration of the Hubble Space Telescope fine guidance sensors

The Hubble Space Telescope (HST) fine guidance sensors are unique in the precision and performance levels being attempted; spacecraft control and astrometric research at the near milliarcsecond level are the ultimate goals. The inflight calibration of the sensors is presented, describing both the algorithms being used as well as the results achieved to date. The calibration items of principal interest are optical distortion, sensor magnification, and relative alignments. Calibration accuracies at the 20 milliarcsecond level have been achieved for specific data sets for optical distortion parameters. Unexpected variations occurring from Dec. 1990 - May 1991 in the magnification and alignment parameters are currently under investigation. Plans are being developed for new data acquisitions and reductions that should substantially improve HST pointing performance.

Welter, G. L.↗

Reliability prediction for a class of highly reliable digital systems

Three theorems which show that the reliability of a popular class of systems can be computed using small and simple models are presented. This class consists of systems that are assemblages of subsystems where each subsystem is a majority-voting threeplex plus spares or majority-voting fourplex plus spares. The theorems are error bounds for model reduction and simplification. The error bounds are given in terms of readily available system parameters. The three theorems have been applied to a system that has been used as an example that generates extremely large reliability models; the system considered is one version of AIPS (Advanced Information Processing System) for IAPSA (Integrated Airframe Propulsion System Architecture).

White, Allan L.↗

Maximum life spiral bevel reduction design

Optimization is applied to the design of a spiral bevel gear reduction for maximum life at a given size. A modified feasible directions search algorithm permits a wide variety of inequality constraints and exact design requirements to be met with low sensitivity to initial values. Gear tooth bending strength and minimum contact ratio under load are included in the active constraints. The optimal design of the spiral bevel gear reduction includes the selection of bearing and shaft proportions in addition to gear mesh parameters. System life is maximized subject to a fixed back-cone distance of the spiral bevel gear set for a specified speed ratio, shaft angle, input torque, and power. Significant parameters in the design are: the spiral angle, the pressure angle, the numbers of teeth on the pinion and gear, and the location and size of the four support bearings. Interpolated polynomials expand the discrete bearing properties and proportions into continuous variables for gradient optimization. After finding the continuous optimum, a designer can analyze near optimal designs for comparison and selection. Design examples show the influence of the bearing lives on the gear parameters in the optimal configurations. For a fixed back-cone distance, optimal designs with larger shaft angles have larger service lives.

Savage, M.↗

Application of Parallel Adjoint-Based Error Estimation and Anisotropic Grid Adaptation for Three-Dimensional Aerospace Configurations

This paper demonstrates the extension of error estimation and adaptation methods to parallel computations enabling larger, more realistic aerospace applications and the quantification of discretization errors for complex 3-D solutions. Results were shown for an inviscid sonic-boom prediction about a double-cone configuration and a wing/body segmented leading edge (SLE) configuration where the output function of the adjoint was pressure integrated over a part of the cylinder in the near field. After multiple cycles of error estimation and surface/field adaptation, a significant improvement in the inviscid solution for the sonic boom signature of the double cone was observed. Although the double-cone adaptation was initiated from a very coarse mesh, the near-field pressure signature from the final adapted mesh compared very well with the wind-tunnel data which illustrates that the adjoint-based error estimation and adaptation process requires no a priori refinement of the mesh. Similarly, the near-field pressure signature for the SLE wing/body sonic boom configuration showed a significant improvement from the initial coarse mesh to the final adapted mesh in comparison with the wind tunnel results. Error estimation and field adaptation results were also presented for the viscous transonic drag prediction of the DLR-F6 wing/body configuration, and results were compared to a series of globally refined meshes. Two of these globally refined meshes were used as a starting point for the error estimation and field-adaptation process where the output function for the adjoint was the total drag. The field-adapted results showed an improvement in the prediction of the drag in comparison with the finest globally refined mesh and a reduction in the estimate of the remaining drag error. The adjoint-based adaptation parameter showed a need for increased resolution in the surface of the wing/body as well as a need for wake resolution downstream of the fuselage and wing trailing edge in order to achieve the requested drag tolerance. Although further adaptation was required to meet the requested tolerance, no further cycles were computed in order to avoid large discrepancies between the surface mesh spacing and the refined field spacing.

Lee-Rausch, E. M.↗

An Integrated Approach to Damage Accommodation in Flight Control

In this paper we present an integrated approach to in-flight damage accommodation in flight control. The approach is based on Multiple Models, Switching and Tuning (MMST), and consists of three steps: In the first step the main objective is to acquire a realistic aircraft damage model. Modeling of in-flight damage is a highly complex problem since there is a large number of issues that need to be addressed. One of the most important one is that there is strong coupling between structural dynamics, aerodynamics, and flight control. These effects cannot be studied separately due to this coupling. Once a realistic damage model is available, in the second step a large number of models corresponding to different damage cases are generated. One possibility is to generate many linear models and interpolate between them to cover a large portion of the flight envelope. Once these models have been generated, we will implement a recently developed-Model Set Reduction (MSR) technique. The technique is based on parameterizing damage in terms of uncertain parameters, and uses concepts from robust control theory to arrive at a small number of "centered" models such that the controllers corresponding to these models assure desired stability and robustness properties over a subset in the parametric space. By devising a suitable model placement strategy, the entire parametric set is covered with a relatively small number of models and controllers. The third step consists of designing a Multiple Models, Switching and Tuning (MMST) strategy for estimating the current operating regime (damage case) of the aircraft, and switching to the corresponding controller to achieve effective damage accommodation and the desired performance. In the paper present a comprehensive approach to damage accommodation using Model Set Design,MMST, and Variable Structure compensation for coupling nonlinearities. The approach was evaluated on a model of F/A-18 aircraft dynamics under control effector damage, augmented by nonlinear cross-coupling terms and a structural dynamics model. The proposed approach achieved excellent performance under severe damage effects.

Boskovic, Jovan D.↗

Greedy Sampling and Incremental Surrogate Model-Based Tailoring of Aeroservoelastic Model Database for Flexible Aircraft

This paper presents a data analysis and modeling framework to tailor and develop linear parameter-varying (LPV) aeroservoelastic (ASE) model database for flexible aircrafts in broad 2D flight parameter space. The Kriging surrogate model is constructed using ASE models at a fraction of grid points within the original model database, and then the ASE model at any flight condition can be obtained simply through surrogate model interpolation. The greedy sampling algorithm is developed to select the next sample point that carries the worst relative error between the surrogate model prediction and the benchmark model in the frequency domain among all input-output channels. The process is iterated to incrementally improve surrogate model accuracy till a pre-determined tolerance or iteration budget is met. The methodology is applied to the ASE model database of a flexible aircraft currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that the proposed method can reduce the number of models in the original database by 67%. Even so the ASE models obtained through Kriging interpolation match the model in the original database constructed directly from the physics-based tool with the worst relative error far below 1%. The interpolated ASE model exhibits continuously-varying gains along a set of prescribed flight conditions. More importantly, the selected grid points are distributed non-uniformly in the parameter space, a) capturing the distinctly different dynamic behavior and its dependence on flight parameters, and b) reiterating the need and utility for adaptive space sampling techniques for ASE model database compaction. The present framework is directly extendible to high-dimensional flight parameter space, and can be used to guide the ASE model development, model order reduction, robust control synthesis and novel vehicle design of flexible aircraft.

numerical analysi↗

Modeling-Driven Damage Tolerant Design of Graphene Nanoplatelet/Carbon Fiber/Epoxy Hybrid Composite Panels for Full-Scale Aerospace Structures

The objective of this study is to design a new nano graphenecarbon fiberpolymer hybrid composite that can be used for the NASA SLS Composite Exploration Upper Stage (CEUS) forward skirt structure. The new material will improve the resistance to open-hole compression failure of the structure relative to traditional polymer fiber composites. The material is designed rapidly and with little cost using the Integrated Computational Materials Engineering (ICME) approach. Multiscale modeling and experiments are used to synergistically optimize the material design to yield improved properties and performance by controlling key processing parameters for manufacturing nano-enhanced materials. Specifically, the nanocomposite panel showed a 22 reduction in mass relative to the traditional composite panel, while both designs are equal in terms of ease of manufacture. This potential mass savings corresponds to an estimated 45 savings in materials and manufacturing costs. The multiscale ICME workflow developed for this project can be readily applied to the development of nano-enhanced composite materials and large aerospace structures. In addition, all key aspects of ICME were employed to complete this project including multiscale modeling, experimental characterization and visualization, data management, visualization, error and uncertainty quantification, and education. The results presented herein indicate a dramatic level of success, as well as the power and potential of ICME approach and multiscale modeling for composite materials.

computational mechanics↗

Hybrid Electric Turboprop Commercial Freighter Opportunity

As the era of electric and hybrid electric aviation is dawning, we have the opportunity to reduce cost, energy use, and emissions of air transportation. In this paper, the case is made for the potential efficiency benefits that can be gained with hybrid electric propulsion. Initial economic, mission profile, and propulsion system concepts for a large turboprop aircraft we designate as the Hybrid Electric Turboprop Commercial Freighter (HETCOF) are presented. Market analysis shows HETCOF has the potential to serve a large market share, but the cost requirements for a new purpose built are challenging relative to the repurposed narrow body aircraft currently operating in the market. Comparing HETCOF to a genericized large turboprop freighter the payload capacity is reduced by 40% for the TRL 5+ configuration but is equivalent to the baseline for the TRL 1-2 configuration. All HETCOF configurations result in increased efficiency and subsequent block fuel, block energy, and block emissions reductions. An integrated power/thermal/and energy storage system is presented and analyzed using key performance parameters to estimate weights and losses at three technology readiness levels. Analysis shows that for a concept like this to have economic and energy benefits, many TRL 1-2 level technologies would be needed. Relevant ARPA-E programs and NASA technologies being developed to enable the benefit are also described. The most significant result of this paper is that the HETCOF concept can close with reduced fuel burn, energy use, and emissions while retaining some or all of the cargo capability of the baseline aircraft across TRL level assumptions, which enables this platform to be used for near term introduction with increasing benefits as technology matures.

Ralph H Jansen↗

Perturbing Parameters to Understand Cloud Contributions to Climate Change

Abstract The sensitivity of cloud feedbacks to atmospheric model parameters is evaluated using a CAM6 perturbed parameter ensemble (PPE). The CAM6 PPE perturbs 45 parameters across 262 simulations, 206 of which are used here. The spread in the total cloud feedback and its six components across the CAM6 PPE are comparable to the spread across the CMIP6 and AMIP ensembles, indicating that parametric uncertainty mirrors structural uncertainty. However, the high-cloud altitude feedback is generally larger in the CAM6 PPE than WCRP assessment, CMIP6, and AMIP values. We evaluate the influence of each of the 45 parameters on the total cloud feedback and each of the six cloud feedback components. We also explore whether the CAM6 PPE can be used to constrain the total cloud feedback, with inconclusive results. Further, we find that despite the large parametric sensitivity of cloud feedbacks in CAM6, a substantial increase in cloud feedbacks from CAM5 to CAM6 is not a result of changes in parameter values. Notably, the CAM6 PPE is run with a more recent version of CAM6 (CAM6.3) than was used for AMIP (CAM6.0) and has a smaller total cloud feedback (0.56 W m −2 K −1 ) as compared to CAM6.0 (0.81 W m −2 K −1 ) owing primarily to reductions in low clouds over the tropics and midlatitudes. The work highlights the large sensitivity of cloud feedbacks to both parameter values and structural details in CAM6.

54 ENVIRONMENTAL SCIENCES↗

ML-based Dimension Reduction Strategies

Deep learning (DL)--based surrogate models have achieved success in various applications in carbon capture and storage (CCS). However, the model training on high-dimensional spaces is computationally expensive and impractical for large-scale and complex geological models, because the models usually contain hundreds of thousands to millions of grid cells, each with a set of parameters. Furthermore, the high cost of generating training data with sufficient variation is another limitation of model training on high-dimensional spaces, which may result in overfitting and reduce the model efficiency and prediction performance. We proposed the workflow incorporating dimension reduction methods and deep learning models, which aim to extract the latent variables of input parameters and output state variables, and then build the mapping function at the latent spaces. The proposed workflow can significantly reduce the computational complexity in solving both forward and inverse problems compared to models trained on high-dimensional spaces. Dimensionality reduction models showed great potential in workflows for fast reservoir simulation, history matching, prior model generation, visualization, and more, ultimately enhancing DL model performance in related SMART Work Packages.

Hosseini, Seyyed↗

Acoustic and aerodynamic performance investigation of inverted velocity profile coannular plug nozzles

The results of model scale parametric static and wind tunnel aerodynamic performance tests on unsuppressed coannular plug nozzle configurations with inverted velocity profile are discussed. The nozzle configurations are high-radius-ratio coannular plug nozzles applicable to dual-stream exhaust systems typical of a variable cycle engine for Advanced Supersonic Transport application. In all, seven acoustic models and eight aerodynamic performance models were tested. The nozzle geometric variables included outer stream radius ratio, inner stream to outer stream ratio, and inner stream plug shape. When compared to a conical nozzle at the same specific thrust, the results of the static acoustic tests with the coannular nozzles showed noise reductions of up to 7 PNdB. Extensive data analysis showed that the overall acoustic results can be well correlated using the mixed stream velocity and the mixed stream density. Results also showed that suppression levels are geometry and flow regulation dependent with the outer stream radius ratio, inner stream-to-outer stream velocity ratio and inner stream velocity ratio and inner stream plug shape, as the primary suppression parameters. In addition, high-radius ratio coannular plug nozzles were found to yield shock associated noise level reductions relative to a conical nozzle. The wind tunnel aerodynamic tests showed that static and simulated flight thrust coefficient at typical takeoff conditions are quite good - up to 0.98 at static conditions and 0.974 at a takeoff Mach number of 0.36. At low inner stream flow conditions significant thrust loss was observed. Using an inner stream conical plug resulted in 1% to 2% higher performance levels than nozzle geometries using a bent inner plug.

Knott, P. R.↗

Advanced Technology Subsonic Transport Study: N+3 Technologies and Design Concepts

Conceptual Research Corporation, the Science of the Possible, has completed a two-year study of concepts and technologies for future airliners in the 180-passenger class. This NASA-funded contract was primarily focused on the ambitious goal of a 70 percent reduction in fuel consumption versus the market-dominating Boeing 737-800. The study is related to the N+3 contracts awarded in 2008 by NASA s Aeronautics Research Mission Directorate to teams led by Boeing, GE Aviation, MIT, and Northrop Grumman, but with more modest goals and funding. CRC s contract featured a predominant emphasis on propulsion and fuel consumption, but since fuel consumption depends upon air vehicle design as much as on propulsion technology, the study included notional vehicle design, analysis, and parametric studies. Other NASA goals including NOx and noise reduction are of long-standing interest but were not highlighted in this study, other than their inclusion in the propulsion system provided to CRC by NASA. The B-737-800 was used as a benchmark, parametric tool, and design point of departure. It was modeled in the RDS-Professional aircraft design software then subjected to extensive parametric variations of parasitic drag, drag-due-to-lift, specific fuel consumption, and unsized empty weight. These studies indicated that the goal of a 70 percent reduction in fuel consumption could be attained with roughly a 30 percent improvement in all four parameters. The results were then fit to a Response Surface and coded for ease of use in subsequent trade studies. Potential technologies to obtain such savings were identified and discussed. More than 16 advanced concept designs were then prepared, attempting to investigate almost every possible emerging concept for application to this class airliner. A preliminary assessment of these concepts was done based on their total wetted area after design normalization of trimmed maximum lift. This assessment points towards a Tailless Airliner concept which was designed and analyzed in some detail. To make it work, a retracting canard and an all-moving chin rudder were employed, along with the use of the Active Aeroelastic Wing technology. Results indicate that a 60 percent savings in fuel burn may be credibly attained, but this depends upon a lot of technology maturation, concept development, and risk reduction. This should be expected-such a dramatic reduction in fuel consumption is a "game changer" in the world of commercial aviation. It won t be easy.

Raymer, Daniel P.↗

Extracting galactic structure parameters from multivariated density estimation

Multivariate statistical analysis, including includes cluster analysis (unsupervised classification), discriminant analysis (supervised classification) and principle component analysis (dimensionlity reduction method), and nonparameter density estimation have been successfully used to search for meaningful associations in the 5-dimensional space of observables between observed points and the sets of simulated points generated from a synthetic approach of galaxy modelling. These methodologies can be applied as the new tools to obtain information about hidden structure otherwise unrecognizable, and place important constraints on the space distribution of various stellar populations in the Milky Way. In this paper, we concentrate on illustrating how to use nonparameter density estimation to substitute for the true densities in both of the simulating sample and real sample in the five-dimensional space. In order to fit model predicted densities to reality, we derive a set of equations which include n lines (where n is the total number of observed points) and m (where m: the numbers of predefined groups) unknown parameters. A least-square estimation will allow us to determine the density law of different groups and components in the Galaxy. The output from our software, which can be used in many research fields, will also give out the systematic error between the model and the observation by a Bayes rule.

Chen, B.↗

Quantifying transport and electrocatalytic reaction processes in a gastight rotating cylinder electrode reactor via integration of Computational Fluid Dynamics modeling and experiments

Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.

42 ENGINEERING↗

Dynamic and Regression Modeling of Ocean Variability in the Tide-Gauge Record at Seasonal and Longer Periods

Comparison of monthly mean tide-gauge time series to corresponding model time series based on a static inverted barometer (IB) for pressure-driven fluctuations and a ocean general circulation model (OM) reveals that the combined model successfully reproduces seasonal and interannual changes in relative sea level at many stations. Removal of the OM and IB from the tide-gauge record produces residual time series with a mean global variance reduction of 53%. The OM is mis-scaled for certain regions, and 68% of the residual time series contain a significant seasonal variability after removal of the OM and IB from the tide-gauge data. Including OM admittance parameters and seasonal coefficients in a regression model for each station, with IB also removed, produces residual time series with mean global variance reduction of 71%. Examination of the regional improvement in variance caused by scaling the OM, including seasonal terms, or both, indicates weakness in the model at predicting sea-level variation for constricted ocean regions. The model is particularly effective at reproducing sea-level variation for stations in North America, Europe, and Japan. The RMS residual for many stations in these areas is 25-35 mm. The production of "cleaner" tide-gauge time series, with oceanographic variability removed, is important for future analysis of nonsecular and regionally differing sea-level variations. Understanding the ocean model's strengths and weaknesses will allow for future improvements of the model.

Hill, Emma M.↗

A survey study on arsenic speciation in coal fly ash and insights into the role of coal combustion conditions

Coal fly ashes (CFAs) are the low-density byproducts of the coal combustion process. Improper or uncontrolled CFA disposal poses significant environmental and health concerns due to the potential leaching of toxic heavy metals such as arsenic (As). Previous studies have investigated the content and speciation of As in different CFA samples, yet systematic information on As speciation in CFA with representative coal source and combustion conditions is still missing. Based on a recent survey study on the typical coal sources and combustion conditions across the U.S., this study selected 19 representative CFA samples to systematically investigate As speciation and potential correlations with these parameters. The composition, morphology, mineralogy, and As speciation of these CFA samples were characterized by complementary analytical, microscopic, and spectroscopic techniques. Synchrotron X-ray spectroscopy and microscopy analyses revealed the dominant As oxidation state to be As(V) and with strong associations to Ca, with the exception of 3 samples that had 19–51% As(III), likely due to the use of selective catalytic reduction (SCR) process. Principal component analysis was conducted to identify potential correlations of As concentration and oxidation state with parameters such as major element content, loss on ignition (LOI), average particle size, coal source, and combustion condition. Al 2 O 3 and FeO content were found to capture a majority of the variability. Further, results from this study provide fundamental basis for understanding the correlations between coal source, combustion conditions, CFA characteristics, and As speciation, and providing insights for downstream beneficial utilization or disposal management.

01 COAL, LIGNITE, AND PEAT↗

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning↗