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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Analysis of Interactive Conflict Resolution Tool Usage in a Mixed Equipage Environment

A human-in-the-loop simulation was conducted that examined separation assurance concepts in varying levels of traffic density with mixtures of aircraft equipage and automation. This paper's analysis focuses on one of the experimental conditions in which traffic levels were approximately fifty percent higher than today, and approximately fifty percent of the traffic within the test area were equipped with data communications (data comm) capabilities. The other fifty percent of the aircraft required control by voice much like today. Within this environment, the air traffic controller participants were provided access to tools and automation designed to support the primary task of separation assurance that are currently unavailable. Two tools were selected for analysis in this paper: 1) a pre-probed altitude fly-out menu that provided instant feedback of conflict probe results for a range of altitudes, and 2) an interactive auto resolver that provided on-demand access to an automation-generated conflict resolution trajectory. Although encouraged, use of the support tools was not required; the participants were free to use the tools as they saw fit, and they were also free to accept, reject, or modify the resolutions offered by the automation. This mode of interaction provided a unique opportunity to examine exactly when and how these tools were used, as well as how acceptable the resolutions were. Results showed that the participants used the pre-probed altitude fly-out menu in 14% of conflict cases and preferred to use it in a strategic timeframe on data comm equipped and level flight aircraft. The interactive auto resolver was also used in a primarily strategic timeframe on 22% of conflicts and that their preference was to use it on conflicts involving data comm equipped aircraft as well. Of the 258 resolutions displayed, 46% were implemented and 54% were not. The auto resolver was rated highly by participants in terms of confidence and preference. Factors such as aircraft equipage, ownership, and location of predicted separation loss appeared to play a role in the decision of controllers to accept or reject the auto resolver's resolutions.

auto resolver↗

Time-resolved measurements of OH during auto-ignition of syngas with trimethylsilanol and hexamethyldisiloxane

The effects of trimethylsilanol (TMSO) and hexamethyldisiloxane (HMDSO) addition on OH time histories during syngas (H 2 and CO) ignition were investigated using the University of Michigan rapid compression facility. Experiments spanned temperatures of 1010–1080 K, at a pressure of approximately 5 atm. Syngas mixtures of 1.2 % H 2 /2.8 % CO/20 % O 2 by volume (balance N 2 and Ar) provided a baseline for comparison with mixtures that included 100, 200, and 1000 ppm of the TMSO and 100 ppm of HMDSO. Narrow-line ultraviolet laser-absorption was used to measure OH mole-fraction during ignition. The addition of TMSO and HMDSO significantly shifted the OH time-histories earlier in time, by up to 51 %, compared with the baseline syngas mixture. The value of the maximum OH mole fraction was consistent between the 100 and 200 ppm TMSO mixtures and the 100 ppm HMDSO mixtures, but the maximum OH increased significantly with the 1000 ppm TMSO mixtures. Here, the OH data indicate TMSO and HMDSO were not direct sources of OH radicals. Analysis further indicates the TMSO and HMDSO decompose rapidly followed by reactions that enhance the production of H atoms, and the increased reactivity observed is via the H + O 2 = OH + O reaction.

Hexamethyldisiloxane↗

Superconducting pairing mechanism in CeCoIn 5 revisited

Spectroscopic-imaging scanning-tunneling microscopy (SI-STM) measurements have previously been applied to the study of the heavy-fermion system CeCoIn 5 to examine the superconducting gap structure and band dispersions via quasiparticle intereference. Here we directly measure the dispersing electron bands with angle-resolved-photoelectron spectroscopy (ARPES) and compare with first principles electronic structure calculations. By auto-correllating the ARPES-resolved bands with themselves we can measure the potential q-vectors and discern exactly which bands the STM is measuring. We find that the STM results are dominated by scattering associated with a cloverleaf shaped band centered at the zone corners. This same band is also a viable candidate to host the superconducting gap. Overall, the electronic structure calculations indicate that this region of the Fermi surface involves significant contributions from the Co d-electrons, an indication that the superconductivity in these materials is more 3-dimensional than that found in the related unconventional superconductors, the cuprates and the pnictides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Haxall-based (Axon) fault auto-correction package for building HVAC system (Haxall-based Fault Correction) v1.0

Haxall-based Fault Correction is a set of fault auto-correction algorithms implemented using the Axon language. These algorithms can automatically fix equipment and control problems as they arise and improve the operation of building Heating, Ventilation, and Air Conditioning (HVAC) systems. The coded auto-correction algorithms include mitigation of rogue zones, ASHRAE Guideline 36 static pressure and supply air reset, resolution of control hunting due to improper settings in a proportional-integral-derivative controller, correction of biased temperature sensors, etc. FDD tools with enhanced auto-correction capability can resolve control problems as they are detected, increasing energy savings and emissions reductions while freeing up operational staff expertise for the hardest facility problems.

Vitti, Raphael↗

Rapid Prediction of Installed Jet Noise from RANS

A new method of computing jet noise, called mSrc, was developed on the general principles of acoustic analogies. In the method, the problem of translating turbulent flow energy into acoustic energy at a far-field observer is broken into two parts, a calculation of acoustic source strengths and then their propagation. The acoustic sources are related to turbulent quantities in the jet plume in a robust manner. The propagation, which is more properly computed using a Green's function accounting for nonuniform speed of sound and solid surfaces, is instead modeled using commonly observed features of jet acoustic far field directivity, and by diffraction barrier theory for surfaces. The mSrc method does not require gradients of the predicted flow field, allowing it to make use of robust unstructured RANS CFD methods, including embedded boundary codes. Such codes do not require specification of surface meshes, and auto-refine their grid to resolve flow gradients, putting resolution where it is required without a priori user input. The ability of mSrc to use such radically unstructured flow input results in an efficient method of estimating noise from jet flows from complex nozzles installed on aircraft. Many validation cases are presented to demonstrate the accuracy and range of applicability of the mSrc method for representative jet noise applications.

Bridges, James↗

Rapid Prediction of Installed Jet Noise From RANS

A new method of computing jet noise, called mSrc, was developed on the general principles of acoustic analogies. In the method, the problem of translating turbulent flow energy into acoustic energy at a far-field observer is broken into two parts, a calculation of acoustic source strengths and then their propagation. The acoustic sources are related to turbulent quantities in the jet plume in a robust manner. The propagation, which is more properly computed using a Green's function accounting for nonuniform speed of sound and solid surfaces, is instead modeled using commonly observed features of jet acoustic far field directivity, and by diffraction barrier theory for surfaces. The mSrc method does not require gradients of the predicted flow field, allowing it to make use of robust unstructured RANS CFD methods, including embedded boundary codes. Such codes do not require specification of surface meshes, and auto-refine their grid to resolve flow gradients, putting resolution where it is required without a priori user input. The ability of mSrc to use such radically unstructured flow input results in an efficient method of estimating noise from jet flows from complex nozzles installed on aircraft. Many validation cases are presented to demonstrate the accuracy and range of applicability of the mSrc method for representative jet noise applications.

Bridges, James↗

Analysis of Automated Aircraft Conflict Resolution and Weather Avoidance

This paper describes an analysis of using trajectory-based automation to resolve both aircraft and weather constraints for near-term air traffic management decision making. The auto resolution algorithm developed and tested at NASA-Ames to resolve aircraft to aircraft conflicts has been modified to mitigate convective weather constraints. Modifications include adding information about the size of a gap between weather constraints to the routing solution. Routes that traverse gaps that are smaller than a specific size are not used. An evaluation of the performance of the modified autoresolver to resolve both conflicts with aircraft and weather was performed. Integration with the Center-TRACON Traffic Management System was completed to evaluate the effect of weather routing on schedule delays.

Love, John F.↗

Detection of Isotopes in Urban Source Search Low-Count Gamma Spectra Using Hopfield Neural Networks

Source search campaigns involve measurements of background gamma-ray spectra with a mobile detector-spectrometer traveling along arbitrarily chosen trajectories over a wide screening area. Radiation counts are typically measured with a tellurium-doped sodium iodide [NaI(Tl)] scintillator detector-spectrometer in short acquisition intervals, usually 1 s. The objective is to detect orphan isotopes with half-lives shorter than those of the isotopes in the natural background. In principle, radioisotopes can be identified by their unique gamma emission spectrum. However, detecting orphan isotopes in search data is challenging because low counts measured in short acquisition intervals result in incomplete spectral lines. In this study, we investigate the performance of a Hopfield neural network (HNN) that implements an auto-associative memory for the detection of isotopes of interest in an urban search campaign. The HNN is trained on one example of gamma spectra with well-resolved spectral lines of each isotope of interest. During testing, the auto-associative memory implementation of the HNN processes low-count gamma spectra with partially complete isotopic lines by matching incoming measurements to the closest one of its memory-stored patterns. The testing database consisted of almost 10 000 1-s gamma spectra, including measurements of orphan isotopes 137 Cs, 241 Am, and 131 I, obtained during two urban search surveys with a NaI(Tl) detector. The performance of the HNN detection algorithm was evaluated using precision, recall, and F1 scores, and benchmarked with a multiple linear regression (MLR) identification algorithm. In conclusion, the test results demonstrate that HNN outperforms MLR in the detection of all the isotopes of interest.

Auto associative memory↗

Spatially-resolved soot evolution and statistics in high-pressure diesel spray flames using two-color pyrometry

Previous studies of diesel spray flames have focused on details of the sooting behavior mainly during the quasi-steady period, but few have considered the spatially-resolved transient evolution in combination with injection-to-injection variations. In this study, a 500-injection data set is utilized to investigate the temporal evolution of a spray flame during auto-ignition, the premixed burn phase, and the quasi-steady period. Spatially-resolved OH* chemiluminescence data provide ignition delay times and reaction zone locations. Two-color pyrom-etry with a vastly improved optical system is used to quantify spatially-resolved soot evolution and its statistical variations. The ambient thermodynamic con-ditions are slightly below those in modern diesel engines, resulting in longer lift-off lengths and lower overall soot production. Spatially, soot formation in the lift-off region is small, but appreciable soot forms in the jet core and jet head regions, while it oxidizes gradually on the jet periphery. Total soot mass profiles indicate that regions with larger local soot mass take longer to form, but are the first to oxidize. Probability distributions of soot mass in localized regions indicate that a few injections with high soot mass bias the average soot mass data towards higher values. Altogether, results show good agreement with previous studies employing different diagnostic techniques while providing statistical details of transient and localized soot behavior in high pressure diesel spray flames in support of the related modeling efforts.

09 BIOMASS FUELS↗

Application of Frequency Division Multiplexing and Neural Networks in the Operation and Diagnosis of the Stator Current and Shaft Position Sensors Used in Electric/Hybrid Vehicles

Fast, precise and robust sensing of currents and motor shaft angle is essential for the excellent performance of electric and hybrid vehicles (EV/HEV). Multiplexing techniques are commonly applied in data acquisition systems (DAQs) to digitize the signals sensed in EV/HEV drives. Frequency-division multiplexing (FDM) applied to get the signals from current sensors and resolver angular position sensor has advantages over conventional multiplexing approaches. However, problems such as aging and mechanical imperfections distort the outputs of those sensors, producing measurement errors of the angular position and currents. Conventional techniques designed to compensate for those errors cannot be applied in signals multiplexed in frequency. This paper proposes online techniques to detect and compensate for the distortions in the resolver sensor and current sensors. The demultiplexing process was adjusted to allow distortion detection and compensation. An auto-associative neural network (ANN) compensates for the current measurement error, while an energy-based technique is applied to compensate for the distortions in the resolver outputs. The obtained results show that the distortions were compensated, allowing a more accurate estimation of stator currents and angular position when FDM is applied in EV/HEV DAQs.

Pereira Pinto, Joao↗

Investigation of the ignition processes of a multi-injection flame in a Diesel engine environment using the flamelet model

In this paper, the first flamelet analysis is conducted of a highly resolved DNS of a multi-injection flame with both auto-ignition and ignition induced by flame-flame interaction. A novel method is proposed to identify the different combustion modes of ignition processes using generalized flamelet equations. The state-of-the-art DNS database generated by Rieth et al. (US National Combustion Meeting, 2019) for a multi-injection flame in a Diesel engine environment is investigated. Three-dimensional flamelets are extracted from the DNS at different time instants with a focus on auto-ignition and interaction-ignition processes. The influences of mixture field interactions and the scalar dissipation rate on the ignition process are investigated by varying the species composition boundary conditions of the transient flamelet equations. Budget analyses of the generalized flamelet equations show that the transport along the mixture fraction iso-surface is insignificant during the auto-ignition process, but becomes important when interaction-ignition occurs, which is further confirmed through a flamelet regime classification method.

42 ENGINEERING↗

Mixed gain detector configurations for time-resolved X-ray solution scattering

X-ray detection at X-ray free-electron lasers is challenging in part due to the XFEL's extremely short and intense X-ray pulses. Experimental measurements are further complicated by the large fluctuations inherent to the self-amplified spontaneous emission process producing the X-rays. At the Linac Coherent Light Source the ePix10ka2M detector offers multiple gain modes, and auto-ranging between these, to increase the dynamic range while retaining low noise. For diffuse scattering techniques, such as time-resolved X-ray solution scattering, where the shape of the scattering pattern largely does not change between exposures, a fixed mix of different gain modes offers many of the same advantages as auto-ranging. We find that configuring individual ASICs in separate gain modes does not impact the intensity linearity of the gain response and has a limited effect on the effective dynamic range in regions with different gain mode settings while avoiding the complexities of auto-ranging. Small (<5%) non-linear gain contributions arise when pixels on the same ASIC are configured in different gain modes. We present a configuration scheme that is designed to select the optimal mixed gain configuration to minimize effects of saturation in the high-/medium-gain region, while maximizing the number of pixels with higher gain to improve the signal-to-noise ratio.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pin Load Control Applied to Retractable Pin Tool Technology and Its Characterization

Until the development of retractable pin tool (RPT) technology, friction stir welding (FSW) was limited to constant thickness joining of aluminum materials and the choices of keyhole elimination focused on traditional fusion and plug weld repair techniques. An invention, US Patent Number 5,893,507, "Auto-Adjustable Pin Tool for Friction Stir Welding" assigned to NASA, demonstrated an approach to resolve these serious drawbacks. This approach brings forth a technique that allows the crater, or keyhole, to be closed out automatically at the end of the weld joint without adding any additional equipment or material. Also the probe length can be varied automatically in the weld joint to compensate for material thickness changes, such as, in a tapered joint. This paper reports the effects of pin extension and retraction rates in the weld joint and its correlation to weld quality. The investigation utilized a pin load-detecting device that was integrated in the Phase IIA RPT designed by Boeing for NASA/MSFC. The RPT modification provided pin load data that was accessed and used to eliminate root side indications and determine pin manipulation rates necessary to produce consistence homogeneous joints.

Olegoetz, P.↗

Pin Load Control Applied to Retractable Pin Tool Technology and its Characterization

Until the development of retractable pin tool (RPT) technology, friction stir welding (FSW) was limited to constant thickness joining of aluminum materials and the choices of keyhole elimination focused on traditional fusion and plug weld repair techniques. An invention, US Patent Number 5,893,507, "Auto-Adjustable Pin Tool for Friction Stir Welding" assigned to NASA, demonstrated an approach to resolve these serious drawbacks. This approach brings forth a technique that allows the crater, or keyhole, to be closed out automatically at the end of the weld joint without adding any additional equipment or material. Also the probe length can be varied automatically in the weld joint to compensate for material thickness changes, such as, in a tapered joint. This paper reports the effects of pin extension and retraction rates in the weld joint and its correlation to weld quality. The investigation utilized a pin load-detecting device that was integrated in the Phase 2A RPT designed by Boeing for NASA/MSFC. The RPT modification provided pin load data that was accessed and used to eliminate root side indications and determine pin manipulation rates necessary to produce consistence homogeneous joints.

Oelgoetz, Peter A.↗

Pin Load Control Applied to Retractable Pin Tool Technology and its Characterization

Until the development of retractable pin tool (RPT) technology, friction stir welding (FSW) was limited to constant thickness joining of aluminum materials and the choices of keyhole elimination focused on traditional fusion and plug weld repair techniques. An invention, US Patent Number 5,893.507, "Auto-Adjustable Pin Tool for Friction Stir Welding" assigned to NASA, demonstrated an approach to resolve these serious drawbacks. This approach brings forth a technique that allows the crater, or keyhole, to be closed out automatically at the end of the weld joint without adding any additional equipment or material. Also the probe length can be varied automatically in the weld joint to compensate for material thickness changes, such as, in a tapered joint. This paper reports the effects of pin extension and retraction rates in the weld joint and its correlation to weld quality. The investigation utilized a pin load-detecting device that was integrated in the Phase 2A RPT designed by Boeing for NASA/MSFC. The RPT modification provided pin load data that was accessed and used to eliminate root side indications and determine pin manipulation rates necessary to produce consistence homogeneous joints.

Oelgoetz, Peter↗

Evaluating Chemical Kinetics Predictions for Propane Using 3-D and 0-D Models in a Boosted Spark-Ignited Engine

Propane has been shown to be a promising alternative fuel to reduce emissions while simultaneously achieving high efficiencies in medium- and heavy-duty engines. These high-power density applications require boosted engines which, combined with high compression ratio, can lead to auto-ignition and knock. While three-dimensional (3-D) computational fluid dynamics (CFD) models are often used for resolving the complex fluid flow in engines, these models can become computationally expensive when simulating detailed chemical kinetics. Likewise, zero-dimensional (0-D) models are computationally concise enough for kinetics development, but lack any flow-field information which governs the flame propagation processes in spark ignition (SI) engines. This work presents a comprehensive comparison between 3-D and 0-D closed cycle simulations at knocking conditions in a high compression ratio high stroke-to-bore ratio propane engine. In order to initialize the flow-field for the 3-D closed cycle (intake valve closing, (IVC) to exhaust valve opening, (EVO)) simulation, a motored multi-cycle 3-D model was run using Converge to create a map at IVC, reducing the computational time. The map allowed a non-homogeneous 3-D closed cycle simulation to be satisfactorily validated against experiments, while a homogeneous case using only the turbulence field mapping was also simulated, mimicking 0-D modeling. The 3-D simulations were used to prescribe the initial conditions (e.g., IVC thermodynamics, speciation, burn-rate profile) for a 2-zone 0-D SI engine model in Chemkin Pro for both cases. It was found that 2-zone 0-D modeling underpredicted the knock onset timing, likely due to the lack of thermal stratification in the unburned gas region. Future work will carry multi-zone 0-D modeling to capture the fuel auto-ignition in the unburned region.

Douvry-Rabjeau, Julien [Oakland University, Roches↗

Unsupervised Learning Based Interaction Force Model for Nonspherical Particles in Incompressible Flows

This project provides a neural network-based interaction force model for gas-solid flows from low to intermediate Reynolds numbers and concentration, which can be linked to MFiX-DEM. We have constructed a database of the interaction force between the irregular-shaped particles using a spherical harmonic method and the fluid phase based on the particle-resolved direct numerical simulation (PR-DNS) with immersed boundary-based gas kinetic scheme. Unsupervised learning method, i.e., variational auto-encoder (VAE) has been applied to extract the primitive shape factors determining the drag force, lifting forces, and torque. The interaction force model has been trained and validated with a simple but effective multi-layer feed-forward neural network: multi-layer perceptron (MLP), which will be concatenated after the encoder of the previously trained VAE for geometry feature extraction for single, irregular particles. We have trained transpose convolutional neural networks with the PR-DNS data to predict the velocity and pressure gradient of the single particle systems and utilized them to calculate drag force of multi-particle systems. This model can provide high computational efficiency because it does not require collecting multiparticle system data from PR-DNS.

99 GENERAL AND MISCELLANEOUS↗

Data Services Upgrade: Perfecting the ISIS-I Topside Digital Ionogram Database

The ionospheric topside sounders of the International Satellites for Ionospheric Studies (ISIS) program were designed as analog systems. More than 16,000 of the original telemetry tapes from three satellites were used to produce topside digital ionograms, via an analog-to-digital (A/D) conversion process, suitable for modern analysis techniques. Unfortunately, many of the resulting digital topside ionogram files could not be auto-processed to produce topside Ne(h) profiles because of problems encountered during the A/D process. Software has been written to resolve these problems and here we report on (1) the first application of this software to a significant portion of the ISIS-1 digital topside-ionogram database, (2) software improvements motivated by this activity, (3) N(sub e)(h) profiles automatically produced from these corrected ISIS-1 digital ionogram files, and (4) the availability via the Virtual Wave Observatory (VWO) of the corrected ISIS-1 digital topside ionogram files for research. We will also demonstrate the use of these N(sub e)(h) profiles for making refinements in the International Reference Ionosphere (IRI) and in the determination of transition heights from Oxygen ion to Hydrogen ion.

topside ionosphere↗