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Space Resources Roundtable 2

Contents include following: Developing Technologies for Space Resource Utilization - Concept for a Planetary Engineering Research Institute. Results of a Conceptual Systems Analysis of Systems for 200 m Deep Sampling of the Martian Subsurface. The Role of Near-Earth Asteroids in Long-Term Platinum Supply. Core Drilling for Extra-Terrestrial Mining. Recommendations by the "LSP and Manufacturing" Group to the NSF-NASA Workshop on Autonomous Construction and Manufacturing for Space Electrical Power Systems. Plasma Processing of Lunar and Planetary Materials. Percussive Force Magnitude in Permafrost. Summary of the Issues Regarding the Martian Subsurface Explorer. A Costing Strategy for Manufacturing in Orbit Using Extraterrestrial Resources. Mine Planning for Asteroid Orebodies. Organic-based Dissolution of Silicates: A New Approach to Element Extraction from LunarRegohth. Historic Frontier Processes Active in Future Space-based Mineral Extraction. The Near-Earth Space Surveillance (NIESS) Mission: Discovery, Tracking, and Characterization of Asteroids, Comets, and Artificial Satellites with a microsatellite. Privatized Space Resource Property Ownership. The Fabrication of Silicon Solar Cells on the Moon Using In-Situ Resources. A New Strategy for Exploration Technology Development: The Human Exploration and Development of Space (HEDS) Exploratiori/Commercialization Technology Initiative. Space Resources for Space Tourism. Recovery of Volatiles from the Moon and Associated Issues. Preliminary Analysis of a Small Robot for Martian Regolith Excavation. The Registration of Space-based Property. Continuous Processing with Mars Gases. Drilling and Logging in Space; An Oil-Well Perspective. LORPEX for Power Surges: Drilling, Rock Crushing. An End-To-End Near-Earth Asteroid Resource Exploitation Plan. An Engineering and Cost Model for Human Space Settlement Architectures: Focus on Space Hotels and Moon/Mars Exploration. The Development and Realization of a Silicon-60-based Economy in CisLunar Space. Our Lunar Destiny: Creating a Lunar Economy. Cost-Effective Approaches to Lunar Passenger Transportation. Lunar Mineral Resources: Extraction and Application. Space Resources Development - The Link Between Human Exploration and the Long-term Commercialization of Space. Toward a More Comprehensive Evaluation of Space Information. Development of Metal Casting Molds by Sol-Gel Technology Using Planetary Resources. A New Concept in Planetary Exploration: ISRU with Power Bursts. Bold Space Ventures Require Fervent Public Support. Hot-pressed Iron from Lunar Soil. The Lunar Dust Problem: A Possible Remedy. Considerations on Use of Lunar Regolith in Lunar Constructions. Experimental Study on Water Production by Hydrogen Reduction of Lunar Soil Simulant in a Fixed Bed Reactor.

Ignatiev, A.↗

Mechanically robust high magnetic-performance Sm-Co sintered magnets through microstructure engineering

Samarium-cobalt (Sm-Co) sintered magnets have high magnetic energy densities, great resistance to demagnetization and corrosion, and excellent thermal stability in a wide temperature range (–50–550 °C). However, the utilization of these magnets is restricted by their brittleness. Based on micromechanical and the Zener pinning model, Sm-Co sintered magnets with improved mechanical properties have been designed and fabricated via microstructure engineering. A small amount of fine Sm 2 O 3 particulates (0–3 wt%) has been incorporated into Sm 2 (CoFeCuZr) 17 sintered magnets to refine the grain size by up to approximately 50% (from 45 to 22 µm) and narrow the grain size distribution. Doping with 3 wt% Sm 2 O 3 increased the flexural strength by 62% while maintaining magnetic performance. Both grain-refined unimodal microstructure and heterogeneous laminated coarse/fine grain microstructure were formed by strategically designed assemblies of Sm 2 O 3 -added Sm-Co powder feedstock mixtures. The technology is compatible with existing magnet manufacturing processes. Numerical micromechanics simulation indicates that the fracture is dominated by intragranular mode. The mechanical strength is mainly enhanced by the additive-induced grain refinement, while the small amount of Sm 2 O 3 addition has a small direct positive contribution. Finally, these magnets will be more cost-effective, efficient, and robust for various functional applications.

36 MATERIALS SCIENCE↗

Modeling Salt-Material Interactions in Molten Salt Reactors: Opportunities and Path Forward

A revitalized interest in molten salt reactor technology has resulted in a concerted effort across US based national laboratories and universities to investigate and overcome the remaining scientific and engineering questions facing the industry. This report provides a detailed description of the atomistic modelling techniques that could be employed to investigate the atomic-level forces and behaviors governing salt chemistry and thermodynamics, and the corrosion of container materials in these systems. The molten salt environment is broken down into three unique regions in which atomic behaviors are governed by separate processes and forces. A discussion is given on how each region can be modelled using different computational methods. The objective of the models presented for each region is to understand and quantify the individual atom-to-atom forces driving corrosion processes and changes in salt chemistry. Once these fundamental mechanisms are better understood, larger models, which connect the regions, can be designed to investigate the long-term non-equilibrium behaviors exhibited by these molten salt systems. With a large enough computational effort, employing the modeling techniques discussed in this report to supplement experimental investigations, a greater understanding of the degradation of salt-facing structural materials can be gained, enabling more accurate lifetime prediction, greater safety and regulatory compliance, and faster material innovation.

36 MATERIALS SCIENCE↗

Characterization of Model-Based Reasoning Strategies for Use in IVHM Architectures

Open architectures are gaining popularity for Integrated Vehicle Health Management (IVHM) applications due to the diversity of subsystem health monitoring strategies in use and the need to integrate a variety of techniques at the system health management level. The basic concept of an open architecture suggests that whatever monitoring or reasoning strategy a subsystem wishes to deploy, the system architecture will support the needs of that subsystem and will be capable of transmitting subsystem health status across subsystem boundaries and up to the system level for system-wide fault identification and diagnosis. There is a need to understand the capabilities of various reasoning engines and how they, coupled with intelligent monitoring techniques, can support fault detection and system level fault management. Researchers in IVHM at NASA Ames Research Center are supporting the development of an IVHM system for liquefying-fuel hybrid rockets. In the initial stage of this project, a few readily available reasoning engines were studied to assess candidate technologies for application in next generation launch systems. Three tools representing the spectrum of model-based reasoning approaches, from a quantitative simulation based approach to a graph-based fault propagation technique, were applied to model the behavior of the Hybrid Combustion Facility testbed at Ames. This paper summarizes the characterization of the modeling process for each of the techniques.

Poll, Scott↗

Predicting Maximum Temperatures of a Li-ion Battery on a Simulated Flight Profile using a Model-based Prognostics

One of the challenges in using Li-ion packs in aeronautics is their safety, and thermal runaway (TR) is a major concern. The current engineering solutions to prevent a Li-ion pack from a catastrophic TR require additional mass and volume to isolate cells. The excess mass could be reduced by improving detection and, thus, preventing a TR event. One of the possible early warning indicators of a TR is crossing a threshold temperature. We have developed an approach, based on the Unscented Kalman Filter (UKF), to predict the likelihood of reaching the threshold temperature for simulated flight profiles. The current battery prognostics algorithms for aerospace predict state-of-charge (SOC) and end-of-life (EOL) [1]. We extended this two-level algorithm to predict the maximum temperature during discharge. The amount of heat generated in a cell depends on factors such as cell chemistry, cell packaging, total cycles, operating temperature, and abuse history [2]. Our semi-empirical thermal model depends on three phenomenological parameters which account for those factors. In addition, a two-parameter reduced-order model is developed to predict the temperature rise for short bursts of “random-walk” (RW) discharge current sequence, which simulates a flight's current-loading profile. The performance of these models on different datasets and types of current loading will be presented. To predict the maximal temperatures for future cycles we must estimate the evolution of thermal parameters as the batteries age. It is found that the parameters of the 3-parametric thermal model cannot be estimated only from the RW data. To address the issue, we will present two alternative approaches: i) expanding the datasets to include discharge profiles beyond RWs; ii) model reduction to a two-parametric model. The two approaches will be illustrated by an application to the cycling data from a commercial LG 18650 cell. References: 1. M. Daigle, C.S. Kulkarni, End-of-discharge and End-of-life Prediction in Lithium-ion Batteries with Electrochemistry-based Aging Models, in: AIAA Infotech @ Aerospace, American Institute of Aeronautics and Astronautics, San Diego, California, USA, 2016. 2. M. Börner, et. al, Correlation of aging and thermal stability of commercial 18650-type lithium ion batteries, Journal of Power Sources. 342 (2017) 382–392.

Thermal runaway↗

Inception Based Deep Convolutional Neural Network for Remaining Useful Life Estimation of Turbofan Engines

Accurate estimation of the remaining useful life (RUL) is a key component of condition based maintenance (CBM) and prognosis and health management (PHM). Data-based models for the estimation of RUL are of particular interest because expert knowledge of systems is not always available and physical modeling is often not feasible. In this paper, a deep convolutional neural network (CNN) architecture is investigated for its ability to estimate the RUL of turbofan engines. The input to the model is a window of time series data collected from the engine under test. Inputting raw sensor data allows features to be learned instead of manually determined. To incorporate the ability to detect features of differing lengths, inception modules are used in the neural network architecture. The model is trained and tested using the new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) data set and high prognosis accuracy was achieved. The developed model was used in the 2021 PHM Society Data Challenge and received second place, further validating its ability to accurately estimate RUL.

DeVol, Nathaniel↗

Engine System Model Development for Nuclear Thermal Propulsion

In order to design, analyze, and evaluate conceptual Nuclear Thermal Propulsion (NTP) engine systems, an improved NTP design and analysis tool has been developed. The NTP tool utilizes the Rocket Engine Transient Simulation (ROCETS) system tool and many of the routines from the Enabler reactor model found in Nuclear Engine System Simulation (NESS). Improved non-nuclear component models and an external shield model were added to the tool. With the addition of a nearly complete system reliability model, the tool will provide performance, sizing, and reliability data for NERVA-Derived NTP engine systems. A new detailed reactor model is also being developed and will replace Enabler. The new model will allow more flexibility in reactor geometry and include detailed thermal hydraulics and neutronics models. A description of the reactor, component, and reliability models is provided. Another key feature of the modeling process is the use of comprehensive spreadsheets for each engine case. The spreadsheets include individual worksheets for each subsystem with data, plots, and scaled figures, making the output very useful to each engineering discipline. Sample performance and sizing results with the Enabler reactor model are provided including sensitivities. Before selecting an engine design, all figures of merit must be considered including the overall impacts on the vehicle and mission. Evaluations based on key figures of merit of these results and results with the new reactor model will be performed. The impacts of clustering and external shielding will also be addressed. Over time, the reactor model will be upgraded to design and analyze other NTP concepts with CERMET and carbide fuel cores.

Nelson, Karl W.↗

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE neams program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework. This report summarizes recent advances in developing an integrated system- and engineering-scale modeling capability for the msr concept, which has gained significant interest in recent years. A consistent framework was established by coupling Pronghorn and SAM through the Saline interface, with thermophysical properties provided by the Molten Salt Thermal Property Database (MSTDB-TP). Further improvements were made to the coupling schemes and domain-overlapping strategies, enhancing the stability and robustness of multi-code simulations. Verification and validation efforts demonstrate the accuracy of this integration across a range of benchmark problems, including one-dimensional heated pipe flows, three-dimensional natural convection loops with evolving isotopic compositions, and \gls{msre} demonstration cases. Within Pronghorn, new capabilities were introduced to model corrosion and noble-metal plating phenomena, supported by an extended thermal-hydraulics framework and refined turbulence treatments. To capture two-phase flow behavior, a multiphase Euler–Euler model was implemented in Pronghorn, including advanced closure relations, high-resolution advection techniques, and capillary force reconstruction. Preliminary verification cases confirm the fidelity of the approach, while planned validation efforts target canonical multiphase benchmarks and application to msr components such as the msre pump bowl. Finally, updates to SAM’s msr mass transfer modeling were extended to consider noble gas migration into porous structures like graphite. The point kinetics model was updated to include reactivity feedback contributions from any defined species, such as xenon. The gas transport model was expanded for applicability to gas mixtures, bubble efflux phenomena, and species transport between liquid and gas phases. A selection of multi-scale Sherwood number correlations from MOSCATO/NekRS and multi-phase correlations from literature have been added for improved accuracy in calculating mass transfer coefficients. A companion effort on developing system-level redox corrosion has also been incorporated into SAM. Collectively, these enhancements strengthen the predictive capability of SAM and Pronghorn for simulating MSR thermal-hydraulics, corrosion, multiphase behavior, and fission-product transport, providing a more complete toolset for design, safety analysis, and licensing support of next-generation \gls{msr}s.

42 - ENGINEERING↗

Designing a Distributed Space Systems Simulation in Accordance with the Simulation Interoperability Standards Organization (SISO)

Simulations are essential for engineering design. These virtual realities provide characteristic data to scientists and engineers in order to understand the details and complications of the desired mission. A standard development simulation package known as Trick is used in developing a source code to model a component (federate in HLA terms). The runtime executive is integrated into an HLA based distributed simulation. TrickHLA is used to extend a Trick simulation for a federation execution, develop a source code for communication between federates, as well as foster data input and output. The project incorporates international cooperation along with team collaboration. Interactions among federates occur throughout the simulation, thereby relying on simulation interoperability. Communication through the semester went on between participants to figure out how to create this data exchange. The NASA intern team is designing a Lunar Rover federate and a Lunar Shuttle federate. The Lunar Rover federate supports transportation across the lunar surface and is essential for fostering interactions with other federates on the lunar surface (Lunar Shuttle, Lunar Base Supply Depot and Mobile ISRU Plant) as well as transporting materials to the desired locations. The Lunar Shuttle federate transports materials to and from lunar orbit. Materials that it takes to the supply depot include fuel and cargo necessary to continue moon-base operations. This project analyzes modeling and simulation technologies as well as simulation interoperability. Each team from participating universities will work on and engineer their own federate(s) to participate in the SISO Spring 2011 Workshop SIW Smackdown in Boston, Massachusetts. This paper will focus on the Lunar Rover federate.

Cowen, Benjamin↗

Calculating Nozzle Side Loads using Acceleration Measurements of Test-Based Models

As part of a NASA/MSFC research program to evaluate the effect of different nozzle contours on the well-known but poorly characterized "side load" phenomena, we attempt to back out the net force on a sub-scale nozzle during cold-flow testing using acceleration measurements. Because modeling the test facility dynamics is problematic, new techniques for creating a "pseudo-model" of the facility and nozzle directly from modal test results are applied. Extensive verification procedures were undertaken, resulting in a loading scale factor necessary for agreement between test and model based frequency response functions. Side loads are then obtained by applying a wide-band random load onto the system model, obtaining nozzle response PSD's, and iterating both the amplitude and frequency of the input until a good comparison of the response with the measured response PSD for a specific time point is obtained. The final calculated loading can be used to compare different nozzle profiles for assessment during rocket engine nozzle development and as a basis for accurate design of the nozzle and engine structure to withstand these loads. The techniques applied within this procedure have extensive applicability to timely and accurate characterization of all test fixtures used for modal test.A viewgraph presentation on a model-test based pseudo-model used to calculate side loads on rocket engine nozzles is included. The topics include: 1) Side Loads in Rocket Nozzles; 2) Present Side Loads Research at NASA/MSFC; 3) Structural Dynamic Model Generation; 4) Pseudo-Model Generation; 5) Implementation; 6) Calibration of Pseudo-Model Response; 7) Pseudo-Model Response Verification; 8) Inverse Force Determination; 9) Results; and 10) Recent Work.

Brown, Andrew M.↗

Land radiative management as contributor to regional-scale climate adaptation and mitigation

The urgency to reduce greenhouse gas emissions has been recognized, but the goal of limiting global temperature rise “well below 2 degrees” and possibly down to 1.5°C remains highly challenging, despite the large regional consequences. Slow progress in the reduction of CO2 emissions have led to the discussion of climate engineering schemes,, which remain controversial within the climate research communityIn particular, the reduction of global mean temperature via solar radiation management (SRMglob) could lead to strong regional disparities. Here we show, based on a literature review and climate model simulations, that regional land radiative management (LRMreg), a generally little-considered option in assessments of climate engineering could help reduce warming (and in particular hot extremes) in densely populated and major agricultural land regions. Several ethical issues would remain with the application of LRMreg, and its efficacy would also be limited in time and space related to crop growing periods and constraints on agricultural management. However, through its regional focus and reliance on tested techniques, LRMreg avoids main shortcomings associated with SRMglob. We argue therefore that albedo-related climate benefits of land management should be considered when assessing ecosystem services and integrated in scenarios of regional-scale climate adaptation and mitigation.

Seneviratne, Sonia I. (ORCID:0000000195282917)↗

Constitutive modeling for isotropic materials

The third and fourth years of a 4-year research program, part of the NASA HOST Program, are described. The program goals were: (1) to develop and validate unified constitutive models for isotropic materials, and (2) to demonstrate their usefulness for structural analysis of hot section components of gas turbine engines. The unified models selected for development and evaluation were those of Bodner-Partom and of Walker. The unified approach for elastic-viscoplastic constitutive equations is a viable method for representing and predicting material response characteristics in the range where strain rate and temperature dependent inelastic deformations are experienced. This conclusion is reached by extensive comparison of model calculations against the experimental results of a test program of two high temperature Ni-base alloys, B1900+Hf and Mar-M247, over a wide temperature range for a variety of deformation and thermal histories including uniaxial, multiaxial, and thermomechanical loading paths. The applicability of the Bodner-Partom and the Walker models for structural applications has been demonstrated by implementing these models into the MARC finite element code and by performing a number of analyses including thermomechanical histories on components of hot sections of gas turbine engines and benchmark notch tensile specimens. The results of the 4-year program have been published in four annual reports. The results of the base program are summarized in this report. The tasks covered include: (1) development of material test procedures, (2) thermal history effects, and (3) verification of the constitutive model for an alternative material.

Chan, K. S.↗

CRCNS22 Learning Rules in the Hippocampus and their Mapping to Neuromorphic Systems (Final Technical Report)

Large scale biologically-realistic computational models are key to investigating the interplay between structure and function in nervous systems, thus paving the way to new clinical methods and neuro-inspired computing solutions. This project focuses on the hippocampus, in particular the CA3-CA1 regions, due to their role in associative learning and memory, pattern separation and completion, and spatial navigation. Investigations into the neuronal organization and learning rule(s) of this circuit can shed light into how declarative memories are formed, stored, recalled and forgotten and inform computational, experimental and clinical neuroscience work. Our project aims at developing a novel data-driven methodology supported by a broad heterogeneous base of neuroscience experimental knowledge and inspired from advances in computer science and engineering. Specifically, this work will benchmark existing and new learning rules within a full-scale spiking neural network simulation of the CA3-CA1 region. The model will be based on an open-source repository, called the Hippocampome, which contains neuronal morphologies, firing patterns, synapse probabilities, and most other required parameters for all known neuron types in the rodent hippocampal formation. The model will be first trained in a supervised fashion for associative memory tasks using backpropagation through time traditionally used in computer science, enhanced with a new technique called the surrogate gradient method. This optimization method will be used to obtain a global loss minimization, but it is not biologically inspired as it assumes the use of data not locally available to the synapses. However, we propose its use as a benchmarking tool, to compare the training performance of local biologically plausible and hardware-mappable learning rules at scale. New rules or combinations will be proposed and tested as needed, based on the obtained results. Progress in this area will also drive the development of novel hardware-mappable algorithms for continual lifelong learning and categorization of new events from few presented examples. This project goes beyond the existing state-of-the-art by looking at large scale realistic neuronal circuits as networks trainable via global optimization methods such as surrogate gradient descent. The objective function of the brain that supports learning is largely unknown, but it is likely that it operates through local learning rules. Studying network trajectories around local minima as proposed in this work represents a useful strategy for understanding whether a network is training by using a specific (set of) learning rule(s). Starting from a completely untrained network is a challenging test since it is difficult to determine how the learning rule affects the trajectory of the network. This interdisciplinary project will help understand what rule governs learning in these regions or if multiple learning rules are involved. The work will develop a robust methodology to measure if the network is converging to the target solution, oscillating around it, or diverging away.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive uncertainty quantification (UQ) for full engineering models by solving probability density function (PDF) equation

This report details a new method for propagating parameter uncertainty (forward uncertainty quantification) in partial differential equations (PDE) based computational mechanics applications. The method provides full-field quantities of interest by solving for the joint probability density function (PDF) equations which are implied by the PDEs with uncertain parameters. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known apriori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the driving (dynamics) term of the PDEs based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the dynamics term of the governing PDEs. The efficacy of the method is demonstrated by applying it to two target problems: solid mechanics explicit dynamics with uncertain material model parameters, and reacting hypersonic fluid mechanics with uncertain chemical kinetic rate parameters. A minimally invasive implementation of the method for representative codes SPARC (reacting hypersonics) and NimbleSM (finite- element solid mechanics) and associated software details are described. For solid mechanics demonstration problems the method shows order of magnitudes improvement in accuracy over traditional stochastic collocation. For the reacting hypersonics problem, the method is implemented as a streamline integration and results show very good accuracy for the approximate sample solutions of re-entry flow past the Apollo capsule geometry at Mach 30.

42 ENGINEERING↗

The circular bioeconomy: a driver for system integration

Background: Human and earth system modeling, traditionally centered on the interplay between the energy system and the atmosphere, are facing a paradigm shift. The Intergovernmental Panel on Climate Change’s mandate for comprehensive, cross-sectoral climate action emphasizes avoiding the vulnerabilities of narrow sectoral approaches. Our study explores the circular bioeconomy, highlighting the intricate interconnections among agriculture, forestry, aquaculture, technological advancements, and ecological recycling. Collectively, these sectors play a pivotal role in supplying essential resources to meet the food, material, and energy needs of a growing global population. We pose the pertinent question of what it takes to integrate these multifaceted sectors into a new era of holistic systems thinking and planning. Results: The foundation for discussion is provided by a novel graphical representation encompassing statistical data on food, materials, energy flows, and circularity. This representation aids in constructing an inventory of technological advancements and climate actions that have the potential to significantly reshape the structure and scale of the economic metabolism in the coming decades. In this context, the three dominant mega-trends—population dynamics, economic developments, and the climate crisis—compel us to address the potential consequences of the identified actions, all of which fall under the four categories of substitution, efficiency, sufficiency, and reliability measures. Substitution and efficiency measures currently dominate systems modeling. Including novel bio-based processes and circularity aspects might require only expanded system boundaries. Conversely, paradigm shifts in systems engineering are expected to center on sufficiency and reliability actions. Effectively assessing the impact of sufficiency measures will necessitate substantial progress in inter- and transdisciplinary collaboration, primarily due to their non-technological nature. In addition, placing emphasis on modeling the reliability and resilience of transformation pathways represents a distinct and emerging frontier that highlights the significance of an integrated network of networks. Conclusions: Existing and emerging circular bioeconomy practices can serve as prime examples of system integration. These practices facilitate the interconnection of complex biomass supply chain networks with other networks encompassing feedstock-independent renewable power, hydrogen, CO 2 , water, and other biotic, abiotic, and intangible resources. Elevating the prominence of these connectors will empower policymakers to steer the amplification of synergies and mitigation of tradeoffs among systems, sectors, and goals.

09 BIOMASS FUELS↗

Determination of water surface temperature based on the use of Thermal Infrared Multispectral Scanner data

A straightforward method for compensating Thermal Infrared Multispectral Scanner (TIMS) digital data for the influence of atmospheric path radiance and the attenuation of target energy by the atmosphere is presented. A band ratioing model useful for estimating water surface temperatures, which requires no ground truth measurements, is included. A study conducted to test the potential of the model and the magnitudes of the corrections for atmosphere encountered is presented. Results of the study, which was based on data collected during an engineering evaluation flight of TIMS, indicate errors in the estimate of the surface temperature of the water fall from +/- 1.0 C for uncorrected data to +/- 0.4 C when data have been corrected according to the model presented. This value approaches the noise-limited thermal resolution of the sensor at the time of the flight.

Anderson, James E.↗

Neural Network and Response Surface Methodology for Rocket Engine Component Optimization

The goal of this work is to compare the performance of response surface methodology (RSM) and two types of neural networks (NN) to aid preliminary design of two rocket engine components. A data set of 45 training points and 20 test points obtained from a semi-empirical model based on three design variables is used for a shear coaxial injector element. Data for supersonic turbine design is based on six design variables, 76 training, data and 18 test data obtained from simplified aerodynamic analysis. Several RS and NN are first constructed using the training data. The test data are then employed to select the best RS or NN. Quadratic and cubic response surfaces. radial basis neural network (RBNN) and back-propagation neural network (BPNN) are compared. Two-layered RBNN are generated using two different training algorithms, namely solverbe and solverb. A two layered BPNN is generated with Tan-Sigmoid transfer function. Various issues related to the training of the neural networks are addressed including number of neurons, error goals, spread constants and the accuracy of different models in representing the design space. A search for the optimum design is carried out using a standard gradient-based optimization algorithm over the response surfaces represented by the polynomials and trained neural networks. Usually a cubic polynominal performs better than the quadratic polynomial but exceptions have been noticed. Among the NN choices, the RBNN designed using solverb yields more consistent performance for both engine components considered. The training of RBNN is easier as it requires linear regression. This coupled with the consistency in performance promise the possibility of it being used as an optimization strategy for engineering design problems.

Vaidyanathan, Rajkumar↗