Results for “Interdependency” — Page 16

NASA NTRS2017

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Gentry, Diana↗

NASA NTRS2018

Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT's hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness.

multi-scale modeling↗

NASA NTRS2018

Demonstration of Probabilistic Sensitivity Analyses Tools on the Structural Response of a Representative Inflatable Space Structure

This work provides an initial step toward demonstrating a probabilistic numerical simulation capability to support trade studies and the development of a certification plan for inflatable space habitats. This study concentrates on interpreting the results from probabilistic analysis and numerical simulation tools to identify parameter sensitivities for a novel inflatable airlock concept, specifically the Non‐Axisymmetric Inflatable Pressure Structure (NAIPS) that was designed and tested under NASA's Minimalistic Advanced Softgoods Hatch (MASH) Program. A brief overview of the finite element model is provided along with the probabilistic sensitivity analysis approach. The sensitivity studies required a model that was numerically stable and efficient enough that hundreds of simulations could be completed in the allotted time. Therefore, the existing full model was simplified by: extracting a quarter symmetry section of the dome; focusing on a single inflation pressure; and replacing the non‐linear material stress‐strain curves with linear, isotropic materials defined by elastic moduli. Responses of interest include the sensitivity of various structural component loads to material properties, cord lengths, inflation pressure and friction. Multiple sensitivity studies were completed and three are reported here. The first study focused on utilizing wide input parameter ranges to provide an opportunity to assess numerical robustness. The next two studies narrowed the parameter ranges to enable focus on understanding uncertainty at a fixed operating condition. The completion of the sensitivity studies improved understanding of the interdependence of multiple inputs on the responses. In addition, numerical stability of the simulations over wide parameter ranges, shows the feasibility of incorporating uncertainty‐based methods in the design and certification of inflatable space habitats. With the experience and trust gained, it is anticipated that these same methods will be applied to nonlinear, orthotropic models in the future.

Lyle, Karen H.↗

NASA NTRS2018

2040 Vision: A Roadmap for Integrated, Multiscale Materials and System Modeling and Simulation

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will describe the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); associated critical gaps and actions to close those gaps; and major recommendations). This roadmap is a community consensus document and is a result of over 450 professionals input obtain via: i) four society workshops (AIAA, NAFEMS, and two TMS), ii) community-wide survey, and iii) the establishment of 9 expert panels (one per key element) consisting on average 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. It is NASA's hope and desire that this roadmap provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness.

Multiscale Modeling↗

NASA NTRS2018

Temperature Mapping Above and Below Air Film-Cooled Thermal Barrier Coatings Using Phosphor Thermometry

Thermal barrier coatings (TBCs) are typically used in conjunction with air film cooling to maximize overall cooling effectiveness and reliability while minimizing sacrifices in engine performance. The effects of thermal barrier coating (TBC) thermal protection and air film cooling effectiveness have usually been studied separately; however, their contributions to combined cooling effectiveness are interdependent and are not simply additive. The combined cooling effectiveness is always less than the sum of the cooling effectiveness of stand-alone TBC protection and stand-alone air film cooling. These diminishing returns arise because adding the thermally insulating TBC between the cooling air and the surface to be cooled reduces the air film cooling effectiveness and because the air film cooling reduces the heat flux through the TBC and therefore reduces the temperature difference sustained across the TBC thickness. Due to these considerations, combined cooling effectiveness must be measured to achieve an optimum balance between TBC thermal protection and air film cooling. In this investigation, temperature mapping above and below air film-cooled TBCs was performed using luminescence lifetime imaging-based phosphor thermometry. Measurements were performed in the NASA GRC Mach 0.3 burner rig on a TBC-coated plate using a scaled-up cooling hole geometry where both the hot mainstream gas temperature and the blowing ratio were varied. Surface temperature maps were obtained from a Cr-doped GdAlO3 thermographic phosphor deposited on the surface of the electron-beam vapor-deposited yttria-stabilized zirconia (YSZ) TBC. From separate plates, temperature maps from the bottom of the TBC were obtained from a thin Er-doped YSZ layer integrated into the TBC below the overlying undoped YSZ. Procedures for temperature and cooling effectiveness mapping above and below the air film-cooled TBC surface are described. Most importantly, these measurements enable mapping the combined cooling effectiveness below the TBC, which is more important than surface cooling effectiveness when there is a barrier coating between the hot mainstream gas and the surface that needs thermal protection. Advantages of the luminescence lifetime imaging method over infrared thermography, as well as its limitations to steady-state conditions are discussed.

cooling effectiveness.↗

NASA NTRS2016

Streamlining the Design Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center is developing a pre-Phase A tool called "Trade-space Analysis Tool for Constellations" (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper focuses on the tradespace search and how it can be streamlined by combining physical rules, as well as well-designed orbit and coverage computations, thus yielding significant speed-ups. Two use cases are shown as representative examples of the utility of TAT-C generated trades, and results are preliminarily validated against AGI's Systems Tool Kit.

Science Data Processing↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2017

Non-Linear Analysis of the NASA Super Pressure Balloons: Whole Flight Simulations

Tensys have a long-established background in the shape generation and load analysis of architectural stressed membrane structures. Founded upon their inTENS finite element analysis suite, these activities have broadened to encompass 'lighter than air' structures such as aerostats, airships, hybrid air vehicles and stratospheric balloons. Tensys have acted as consultants to the NASA Super Pressure Balloon (SPB) Program since 2004. Previous papers have focussed upon the application of inTENS to the overall structural and stability analysis of pumpkin type balloons as used in the SPB Program. Particular emphasis has been placed upon the ability to study both stress and stability at all stages of a flight. As the program has developed, increasing modelling fidelity has been introduced as design refinement has moved emphasis from the overall shape to the performance of individual details. Examples include the introduction of a contact capability into inTENS to better represent the separate cap layer of film. Localised investigations have considered the consequence of local geometric anomalies introduced during fabrication and the effects of debonding of the PBO tendon within its sleeve. Analysis to date has used a material model for the polyethylene shell film developed by Dr Rand of Winzen Engineering, supported by a program of fine resolution material tests at the Balloon Research and Development Laboratory (BRDL) at the GSFC Wallops Island Facility. Based upon work first reported by Schapery, this model has been incorporated into so-called 'snapshot' analyses within inTENS. For a given elapsed time point and temperature distribution, non-linear material properties are iteratively updated for the current stress state in each individual element until changes in those material properties are insignificant. This process has to be iterative as the film stresses and material properties are interdependent. Attempts to derive a time-stepping incremental viscoelastic capability using the Schapery Rand model encountered problems when dealing with the varying temperatures associated with balloon deployment, pressurisation and diurnal behaviour. An alternative approach has been developed by Pellegrino et al at Caltech, again with support from the NASA Balloon Program Office. This is a large strain non-linear viscoelastic model that includes film out-of-plane mechanical and thermal effects. Working from a unified base, this model can be utilised for time-stepping analyses in both a modulus or compliance mode, or a combination of both. This new capability is intended to enhance the current NASA balloon design process. This paper presents the implementation of the Caltech model into a specialist finite element suite, inTENS and its application to whole flight simulations.

Wakefield, David↗

NASA NTRS2016

Real-Time Early Warning Techniques

Contemporary approaches to aerospace vehicle system monitoring rely heavily on thresholds that represent a compromise between providing warning early enough to avert a mishap while simultaneously minimizing false alarms. While this reliance on thresholds has been in place for decades and has permeated both cockpits and control rooms, we often find it insufficient when retrospectively analyzing data from an accident. To modernize and enhance flight test safety, we introduce new methods of monitoring for anomalous patterns of interaction rather than for thresholds exceedance. For systems with a well characterized baseline we show how the Inductive Monitoring System (IMS), utilized by NASA in the aftermath of the Columbia accident, might be implemented in real-time to provide earlier warning than currently employed techniques. For systems without such a baseline, we introduce new developments in statistical methods relating to critical slowing down, first applied in medicine and physics, which show promise for adaptation to flight test. Finally, the familiar resource constrained environment leads to a reliance on increased instrumentation that is challenging the limits of the current one-sensor, one-indicator threshold paradigm. Existing methods thus fail to accurately reflect the true complexity of a vehicle rich with interdependent interacting systems. We highlight these concepts in a brief summary of the 2001 Air Transat Flight 236 deadstick landing in the Azores. We then suggest control room and cockpit modifications to better display the information gleaned using these novel monitoring methods.

Javorsek, Dan↗

NASA NTRS2016

Enhancing Flight Test Safety with Real-Time Early Warning Techniques

Contemporary approaches to aerospace vehicle system monitoring rely heavily on thresholds that represent a compromise between providing warning early enough to avert a mishap while simultaneously minimizing false alarms. While this reliance on thresholds has been in place for decades and has permeated both cockpits and control rooms, we often find it insufficient when retrospectively analyzing data from an accident. To modernize and enhance flight test safety, we introduce new methods of monitoring for anomalous patterns of interaction rather than for thresholds exceedance. For systems with a well characterized baseline we show how the Inductive Monitoring System (IMS), utilized by NASA in the aftermath of the Columbia accident, might be implemented in real-time to provide earlier warning than currently employed techniques. For systems without such a baseline, we introduce new developments in statistical methods relating to critical slowing down, first applied in medicine and physics, which show promise for adaptation to flight test. Finally, the familiar resource constrained environment leads to a reliance on increased instrumentation that is challenging the limits of the current "one-sensor, one-indicator" threshold paradigm. Existing methods thus fail to accurately reflect the true complexity of a vehicle rich with interdependent interacting systems. We highlight these concepts in a brief summary of the 2001 Air Transat Flight 236 deadstick landing in the Azores. We then suggest control room and cockpit modifications to better display the information gleaned using these novel monitoring methods.

Javorsek, Daniel, II↗

NASA NTRS2017

Navigating the Deployment and Downlink Tradespace for Earth Imaging Constellations

Distributed Spacecraft Missions (DSMs) are gaining momentum in their application to Earth Observation (EO) missions owing to their unique ability to increase observation sampling in spatial, spectral, angular and temporal dimensions simultaneously. DSM design includes a much larger number of variables than its monolithic counterpart, therefore, Model-Based Systems Engineering (MBSE) has been often used for preliminary mission concept designs, to understand the trade-offs and interdependencies among the variables. MBSE models are complex because the various objectives a DSM is expected to achieve are almost always conflicting, non-linear and rarely analytical. NASA Goddard Space Flight Center (GSFC) is developing a pre-Phase A tool called Tradespace Analysis Tool for Constellations (TAT-C) to initiate constellation mission design. The tool will allow users to explore the tradespace between various performance, cost and risk metrics (as a function of their science mission) and select Pareto optimal architectures that meet their requirements. This paper will describe the different types of constellations that TAT-C’s Tradespace Search Iterator is capable of enumerating (homogeneous Walker, heterogeneous Walker, precessing type, ad-hoc) and their impact on key performance metrics such as revisit statistics, time to global access and coverage. We will also discuss the ability to simulate phased deployment of the given constellations, as a function of launch availabilities and/or vehicle capability, and show the impact on performance. All performance metrics are calculated by the Data Reduction and Metric Computation module within TAT-C, which issues specific requests and processes results from the Orbit and Coverage module. Our TSI is also capable of generating tradespaces for downlinking imaging data from the constellation, based on permutations of available ground station networks - known (default) or customized (by the user). We will show the impact of changing ground station options for any given constellation, on data latency and required communication bandwidth, which in turn determines the responsiveness of the space system.

Nag, Sreeja↗

NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗

NASA NTRS2016

Creating Systems Engineering Products with Executable Models in a Model-Based Engineering Environment

Applying systems engineering across the life-cycle results in a number of products built from interdependent sources of information using different kinds of system level analysis. This paper focuses on leveraging the Executable System Engineering Method (ESEM) which automates requirements verification (e.g. power and mass budget margins and duration analysis of operational modes) using executable SysML models. The particular value proposition is to integrate requirements, and executable behavior and performance models for certain types of system level analysis. The models are created with modeling patterns that involve structural, behavioral and parametric diagrams, and are managed by an open source Model Based Engineering Environment (named OpenMBEE). This paper demonstrates how the ESEM is applied in conjunction with OpenMBEE to create key engineering products (e.g. operational concept document) for the Alignment and Phasing System (APS) within the Thirty Meter Telescope (TMT) project, which is under development by the TMT International Observatory (TIO).

MBSE↗

NASA NTRS2018

Understanding Mercury's Exosphere: Models Derived from MESSENGER Observations: Chapter - 15

The observations of Mercury's exosphere described in Chapter 14 have led to many modeling efforts. Early models were based upon a few simple assumptions and primarily explored the dynamics of sodium atoms pushed anti-sunward by radiation pressure [Ip, 1986; Smyth and Marconi, 1995]. More recently, these early models have been superseded by simulations with an increasing number of interdependent source processes [Leblanc and Johnson, 2003; Mura et al., 2009; Leblanc and Johnson, 2010; Burger et al., 2010, 2012, 2014]. We briefly summarize the source and loss processes before describing the published exosphere models, first for the three species observed almost continuously during the MESSENGER mission by the Ultraviolet and Visible Spectrometer (UVVS) channel of the Mercury Atmospheric and Surface Composition2Spectrometer (MASCS), (Na, Mg and Ca), and then more briefly for other species that have been observed or for which new upper limits have been derived.15.1 Overview of Source and Loss Processes15.1.1 Source Processes15.1.1.1 Thermal DesorptionThermal desorption (or thermal evaporation) is the release of adsorbed atoms from a surface via heating. Thermal desorption is related to the binding energy of the atom on the surface and the vibrational frequency of the bound atom, such that the rate of thermal desorption is given by, (15.1)where TD,

Thermal↗

NASA NTRS2017

Measuring the Effectiveness of Human Autonomy Teaming

Human-Automation Teaming (HAT), is now recognized as a promising solution to the problems of humans managing increasingly complex work systems. A human-automation team can be defined as the interdependent coupling between one or more human operators and one or more autonomous systems requiring collaboration and coordination to accomplish system and task goals (e.g., Langan-Fox et al., 2009). In this conception, automated agents are considered team members that can operate at various levels of automation, be focused on one or more human-information-processing stages, and the interactions with human operators may be adaptable, adjustable or mixed initiative. We investigated some metrics for assessing HAT effectiveness in a demonstration of a HAT tool used by ground station operators in a Reduced Crew Operations project that was conducted at NASA Ames Human Automation Teaming Laboratory. In this paper, we focus on operator metrics of HAT effectiveness, specifically workload and operator behaviors.

measurements↗

NASA NTRS2019

2040 Vision Study: an Enlargement of Model Based Engineering

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This talk will briefly review the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); associated critical gaps and actions to close those gaps; and major recommendations). The study, NASA CR 2018- 219771, envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that marries two non-mutually exclusive paradigms _ "design of the materials" (material scientist viewpoint) and "design with the materials" (structural analyst viewpoint) _ into a concurrent transformational paradigm that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT's hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness.

Arnold, Steven M.↗

NASA NTRS2016

Heat Exchanger Performance Impacts on Optimum Cost Conditions in Thermoelectric Energy Recovery Designs

Cost is just as important as power density or efficiency for the adoption of waste heat recovery thermoelectric generators (TEG). Prior work [1] has shown that the system design that minimizes cost (e.g., the $/W value) can be close to the designs that maximize the system’s efficiency or power density, however, it is important to understand the relationship between those designs to optimize TEG performance-cost compromises. Expanding on recent work [1, 2, 3] the impact of heat exchanger conditions on the optimum TEG fill factors and cost scaling of a waste heat recovery thermoelectric generator with a detailed treatment of the hot side exhaust heat exchanger has been investigated further. The effect of the heat lost to the environment and updated relationships between the hot-side and cold-side conductances [4] that maximize power output are considered. The optimum fill factor to minimize TEG energy recovery system costs is strongly dependent on the heat leakage fraction, σ, the mass flow rate of the exhaust, the hot-side heat exchanger effectiveness, heat exchanger UAh, and heat flux. These relationships are explored and characterized for typical exhaust gas-flow conditions to show the inherent design complexities. The heat exchanger costs often dominate the TEG cost equation and it is critical to fully understand the tradeoff between heat exchanger performance, optimum TEG fill factors, and cost to establish potentially optimum design points within the cost-performance design space. This work will explore the design tradeoffs and relationships within the cost-efficiency-power density design space for a typical thermoelectric energy recovery system application. The interplay between optimum TEG fill factors and heat exchanger design can impact system footprint, volume, and mass in weight-sensitive applications. Less-effective, low-cost heat exchangers may outperform higher cost alternatives from a market adoption perspective. This shift of emphasis acknowledging the interdependence of optimum TEG fill factors and heat exchanger performance has significant implications on thermoelectric waste heat recovery systems designs and their operation. In addition, preferred TEG design regimes exist that accommodate reasonable compromises in TE performance and cost. This effort highlights how the optimum fill factor–heat exchanger performance relations couple to these optimum TEG performance-cost domains based on TEG-system-level analyses and provides a focus for future system research and development efforts.

Energy recovery↗

NASA NTRS2020

Effects of Hydrogen Bonding and Molecular Chain Flexibility of Substituted n-Alkyldimethylsilanes On Impact Ice Adhesion Shear Strength

The effects of hydrogen bonding and molecular flexibility upon ice adhesion shear strength were investigated using aluminum substrates coated with substituted n-alkyldimethylalkoxysilanes. The location of the chemical group substitution was on the opposing end of the linear n-alkyl chain with respect to silicon. Three hydrogen-bonding characteristics were evaluated: 1) non-hydrogen bonding, 2) donor/acceptor, and 3) acceptor. Varying the length of the n-alkyl chain provided an assessment of molecular chain flexibility. Coated and uncoated aluminum surfaces were characterized by receding water contact angle and surface roughness. Ice adhesion shear strength was determined in the Adverse Environment Rotor Test Stand facility from -16 to -8°C that simulated aircraft in-flight icing conditions within the FAR Part 25/29 Appendix C icing envelope. Surface roughness of the coatings was similar allowing for comparison of the test results. An adhesion reduction factor, based on the ice adhesion shear strength data with respect to uncoated aluminum obtained at the same temperature, was calculated to compare the data. The results revealed complex interactions with impacting supercooled water droplets that were interdependent upon ice accretion temperature, surface energy characteristics of water and ice, hydrogen bonding characteristic of the substituent, and length of the n-alkyl chain. To aid in explaining the results, 1) changes in the surface energy component (i.e., non-polar and polar) values that water undergoes during its’ phase change from liquid to solid that arise from the freezing of impacting supercooled water droplets on the surface depended upon the temperature during accretion were taken into account and 2) the physical properties (i.e., water solubility and melting point) of small compounds analogous to the substituted n-alkyldimethylalkoxysilanes used in this study were compared.

Smith, Joseph G.↗