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NASA NTRS2018

Hybrid Reduced Order Model for N2-N2 Interactions for Application to Dissociation and Energy Transfer Processes

Recent work in the aerothermodynamics community has focused on the development of reduced-order models for thermo-chemical non-equilibrium which avoid the restrictive assumptions of multi-temperature models and the prohibitive cost associated with State-to-State (StS) models. In the present work, this is accomplished by lumping energy states together and assuming groups of states are roughly in equilibrium. As a result, the non-equilibrium behavior of a gas can be captured at a reduced computational cost from a full StS simulation. In this work, we present a hybrid grouping model for studying energy transfer and dissociation in a mixture of nitrogen molecules due to N2-N2 reactions. This is accomplished by making use of a grouping strategy informed by data from the N2-N StS kinetic data. However, due to the massive computational cost associated with constructing StS data for the N2-N2 system, the kinetic data for the hybrid grouping model are calculated using the quasi-classical trajectory (QCT) method by sampling states for trajectory within the groups. This general framework is called the Maximum-Entropy Quasi-Classical Trajectory (ME-QCT) method. The primary challenge associated with this method is that rates for reverse grouped reactions cannot be obtained through detailed balance at a group level, due to the variation of group internal temperatures. To construct the full model for N2-N2 grouped kinetics using the ME-QCT method, detailed balance is invoked at the microscopic level, allowing for the calculation of the full kinetic data from QCT. Results will be presented using the full ME-QCT model for the N2-N2 system in an isothermal and isochoric reactor simulation. In addition, simple CFD test cases for a one-dimensional standing shock and for a quasi-one-dimensional nozzle will be used for demonstration of the ME-QCT method. This method allows for the calculation of non-equilibrium behavior for the N2-N2 system without the prohibitive cost of a full StS simulation. Moreover, it enables the construction of a unified model for the dissociating and recombining non-equilibrium flows.

nonequilibrium modeling↗

NASA NTRS2006

Cascaded Perforates as One-Dimensional, Bulk Absorbers

Porous cell honeycomb liners for aircraft engine nacelles offer the possibility of exploiting extended reaction effects to improve liner attenuation bandwidth as generally attributed to the performance of bulk absorbers. This paper describes an analytical procedure, starting with an impedance prediction model for a single perforated plate, to estimate the bulk-absorber parameters for a cascade of such perforates - a first step to modeling a porous wall honeycomb structure. The objective is to build confidence in a lumped element impedance model, when applied to a uniformly-spaced set of porous plates to predict its .bulk. absorber properties. The model is based upon a modified version of the two-parameter flow resistance model of the form A + BV(sub inc), where A and B are physics-based, semi-empirical parameters that are adjusted to provide an optimum fit to a composite dataset from three plate porosities of 2.5, 5 and 10%. The composite dataset is achieved by reformulating the two-parameter flow resistance model into a .reduced pressure drop coefficient. dependency on perforate hole Reynolds number. The resulting impedance model is employed to calculate surface impedance spectra for N and 2N-layer perforate cascades. The well-known two-thickness method for experimental determination of bulk-absorber parameters is then applied to these .synthesized. data sets to predict the characteristic impedance and propagation constant for the perforate cascades. These results are then compared with experimental results reported in a companion paper.

Parrott, T. L.↗

NASA NTRS1972

Vibration computer programs E13101, E13102, E13104, and E13112 and application to the NERVA program. Project 187: Methodology documentation

Programs for the analyses of the free or forced, undamped vibrations of one or two elastically-coupled lumped parameter teams are presented. Bearing nonlinearities, casing and rotor distributed mass and elasticity, rotor imbalance, forcing functions, gyroscopic moments, rotary inertia, and shear and flexural deformations are all included in the system dynamics analysis. All bearings have nonlinear load displacement characteristics, the solution is achieved by iteration. Rotor imbalances allowed by such considerations as pilot tolerances and runouts as well as bearing clearances (allowing concail or cylindrical whirl) determine the forcing function magnitudes. The computer programs first obtain a solution wherein the bearings are treated as linear springs of given spring rates. Then, based upon the computed bearing reactions, new spring rates are predicted and another solution of the modified system is made. The iteration is continued until the changes to bearing spring rates and bearing reactions become negligibly small.

Mironenko, G.↗

NASA NTRS1989

On the driving force of PAH production

The kinetic factors affecting the production of polycyclic aromatic hydrocarbons (PAH) in high-temperature pyrolysis and combustion environments are analyzed. A lumped kinetic model representing polymerization-type growth by one irreversible step and two reversible steps is considered. It is shown that at high temperatures, PAH growth is controlled by the superequilibrium of hydrogen atoms; at low temperatures and low H2 concentrations, the PAH growth rate is proportional to the rate of the H-abstraction of a hydrogen atom from aromatic molecules; while at low temperatures and high H2 concentrations, it is controlled by the thermodynamics of the H-abstraction and the kinetics of acetylene addition to aromatic radicals. The presence of oxygen mainly affects the small-molecule reactions during the induction period.

Frenklach, Michael↗

NASA NTRS2001

Switching between simple cognitive tasks: the interaction of top-down and bottom-up factors

How do top-down factors (e.g., task expectancy) and bottom-up factors (e.g., task recency) interact to produce an overall level of task readiness? This question was addressed by factorially manipulating task expectancy and task repetition in a task-switching paradigm. The effects of expectancy and repetition on response time tended to interact underadditively, but only because the traditional binary task-repetition variable lumps together all switch trials, ignoring variation in task lag. When the task-recency variable was scaled continuously, all 4 experiments instead showed additivity between expectancy and recency. The results indicated that expectancy and recency influence different stages of mental processing. One specific possibility (the configuration-execution model) is that task expectancy affects the time required to configure upcoming central operations, whereas task recency affects the time required to actually execute those central operations.

Cognition↗

NASA NTRSDate not supplied

Predicting Maximum Thermal Response in a Li-ion Cell as a Thermal Runaway Predictor for a UAV Fight

As the energy storage devices continue to "pack" more energy in a small space, any damage, battery component failure, manufacturing defect, or electrically abusing the battery can lead to catastrophic thermal runaway events. A catastrophic thermal event in a cell leads to high temperature, in some instances to spewing of battery materials due to gas development from side reactions initiated due to high internal temperatures. Moreover, a thermal runaway can propagate from a single "failed" cell to a whole battery pack, resulting in a more serious event. The commercial and automotive sectors need to mitigate thermal runaway events. An electric aircraft (or air taxi) has no alternative in the event of a failure, so preventing such events is paramount. Currently, battery prognostics algorithms only predict the state-of-charge (SOC) and end-of-life (EOL) of a Li-ion battery in a UAV (unmanned air vehicle), but do not predict the maximum temperature during a flight or the likelihood of thermal runaway. Our current work focuses on adding the thermal model (based on Birkl's OCV model, in Ref. [1]) to the existing hybrid electrochemical model (single-particle model with lumped parameters as in Ref. [2]) to determine end-of-discharge, end-of-life, and maximum temperature during discharge.

Thermal runaway↗

NASA NTRS2001

Thermal Analysis for Orbiter and ISS Plume Impingement on International Space Station

The NASA Reaction Control System (RCS) Plume Model (RPM) is an exhaust plume flow field and impingement heating code that has been updated and applied to components of the International Space Station (ISS). The objective of this study was to use this code to determine if plume environments from either Orbiter PRCS jets or ISS reboost and Attitude Control System (ACS) jets cause thermal issues on ISS component surfaces. This impingement analysis becomes increasingly important as the ISS is being assembled with its first permanent crew scheduled to arrive by the end of fall 2000. By early summer 2001 , the ISS will have a number of major components installed such as the Unity (Node 1), Destiny (Lab Module), Zarya (Functional Cargo Block), and Zvezda (Service Module) along with the P6 solar arrays and radiators and the Z-1 truss. Plume heating to these components has been analyzed with the RPM code as well as additional components for missions beyond Flight 6A such as the Propulsion Module (PM), Mobile Servicing System, Space Station Remote Manipulator System, Node 2, and the Cupola. For the past several years NASA/JSC has been developing the methodology to predict plume heating on ISS components. The RPM code is a modified source flow code with capabilities for scarfed nozzles and intersecting plumes that was developed for the 44 Orbiter RCS jets. This code has been validated by comparison with Shuttle Plume Impingement Flight Experiment (SPIFEX) heat flux and pressure data and with CFD and Method of Characteristics solutions. Previous analyses of plume heating predictions to the ISS using RPM have been reported, but did not consider thermal analysis for the components nor jet-firing histories as the Orbiter approaches the ISS docking ports. The RPM code has since been modified to analyze surface temperatures with a lumped mass approach and also uses jet-firing histories to produce pulsed heating rates. In addition, RPM was modified to include plume heating from ISS jets to ISS components where the jet coordinates are specified, together with the engine cant angle. These latter studies have been focused on the PM with plumes from its reboost and ACS jets impinging on various ISS components and also focused on the Japanese H2 Transfer Vehicle (HTV) with the plumes from its reboost engines impinging on the Cupola window. This paper will present plume heating and surface temperature results on a number of ISS components with and without jet-firing histories, evaluate post-flight data, and describe any potential thermal issues

Rochelle, William C.↗