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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 1,441 records · Page 80

Influence of functional groups on low-temperature combustion chemistry of biofuels

Ongoing progress in synthetic biology, metabolic engineering, and catalysis continues to produce a diverse array of advanced biofuels with complex molecular structure and functional groups. In order to integrate biofuels into existing combustion systems, and to optimize the design of next-generation combustion systems, understanding connections between molecular structure and ignition at low-temperature conditions (< 1000 K) remains a priority that is addressed in part using chemical kinetics modeling. The development of predictive models relies on detailed information, derived from experimental and theoretical studies, on molecular structure and chemical reactivity, both of which influence the balance of chain reactions that occur during combustion – propagation, termination, and branching. In broad context, three main categories of reactions affect ignition behavior: (i) initiation reactions that generate a distribution of organic radicals, ; (ii) competing unimolecular decomposition of and bimolecular reaction of with O2; (iii) decomposition mechanisms of peroxy radical adducts (RO), including isomerization via RO ⇌ OOH. Furthermore, all three categories are influenced by functional groups in different ways, which causes a shift in the balance of chain reactions that unfold over complex temperature- and pressure-dependent mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Wing design for a civil tiltrotor transport aircraft

The goal of this research is the proper tailoring of the civil tiltrotor's composite wing-box structure leading to a minimum-weight wing design. With focus on the structural design, the wing's aerodynamic shape and the rotor-pylon system are held fixed. The initial design requirement on drag reduction set the airfoil maximum thickness-to-chord ratio to 18 percent. The airfoil section is the scaled down version of the 23 percent-thick airfoil used in V-22's wing. With the project goal in mind, the research activities began with an investigation of the structural dynamic and aeroelastic characteristics of the tiltrotor configuration, and the identification of proper procedures to analyze and account for these characteristics in the wing design. This investigation led to a collection of more than thirty technical papers on the subject, some of which have been referenced here. The review of literature on the tiltrotor revealed the complexity of the system in terms of wing-rotor-pylon interactions. The aeroelastic instability or whirl flutter stemming from wing-rotor-pylon interactions is found to be the most critical mode of instability demanding careful consideration in the preliminary wing design. The placement of wing fundamental natural frequencies in bending and torsion relative to each other and relative to the rotor 1/rev frequencies is found to have a strong influence on the whirl flutter. The frequency placement guide based on a Bell Helicopter Textron study is used in the formulation of frequency constraints. The analysis and design studies are based on two different finite-element computer codes: (1) MSC/NASATRAN and (2) WIDOWAC. These programs are used in parallel with the motivation to eventually, upon necessary modifications and validation, use the simpler WIDOWAC code in the structural tailoring of the tiltrotor wing. Several test cases were studied for the preliminary comparison of the two codes. The results obtained so far indicate a good overall agreement between the two codes.

Rais-Rohani, Masoud↗

Design and Analysis of Convolutional Neural Network for RF Signal Modulation Classification for In-Orbit Deployment

To effectively transmit data to and from satellites requires a complex and robust RF communication system. Commonly, several different types of signal modulations may be required to maximize satellite efficiency depending on a variety of unexpected channel impairments. We propose a neural network algorithm capable of learning these RF signal modulations using a supervised learning technique designed for low power, high-efficiency in-orbit deployment. The work presented demonstrates a convolutional neural network (CNN) capable of learning and recognizing a set of modulation schemes commonly used to transmit RF information. We are capable of recognizing the modulation scheme from the I and Q data channels directly, with no preprocessing or data conversion required other than breaking the incoming signal into a set of uniform normalized samples. We perform a network design and size analysis, showing that reasonably high accuracy can be obtained using networks with a relatively low number of trainable parameters. Given that a user of a system such as this may wish to receive a signal using a modulation scheme that the network has not previously learned, we demonstrate that transfer learning can learn new modulation schemes by retraining only the fully connected layers in the CNN. Thus, this type of network would excel in outer space deployment using high-efficiency transfer learning hardware. Modulation recognition can be performed through rapid feedforward computation, and the CNN training process is significantly simplified when learning new modulations is required.

CNN↗

Enabling Assurance in the MBSE Environment

A number of specific benefits that fit within the hallmarks of effective development are realized with implementation of model-based approaches to systems and assurance. Model Based Systems Engineering (MBSE) enabled by standardized modeling languages (e.g., SysML®) is at the core. These benefits in the context of spaceflight system challenges can include [1]: • Improved management of complex development • Reduced risk in the development process • Improved cost management • Improved design decisions With appropriate modeling techniques the assurance community also can improve early oversight and insight into project development. NASA has shown the basic constructs of SysML in an MBSE environment offer several key advantages, within a Model Based Mission Assurance (MBMA) initiative [2, 3]. These include the following: • Model viewpoints that promote rapid and systematic assessment of requirements coverage, hazard tagging and risk management • Embedded safety assessments for launch vehicles • Deployment of model assisted development of reliability products - Failure Modes and Effects Analyses (FMEAs) and Fault Trees • Test Planning • Validation and Verification of complex functions • Support of Assurance Case development for complex systems In addition, while there are benefits to be harvested, there is a realization that these do not come without effort and cost. Enabling model-based approaches requires structure, not only in an organizational context, but in a modeling context as well. There can be a steep learning curve and costs associated to train skilled modelers. But, on the other hand, not all of the assurance community need to be modelers. Models themselves must conform to ontologies that enable assurance. This places constraints upon the models and modelers. Optimums have yet to be developed where resources and constraints on modeling must be traded off in the organization and modeling efforts for projects. A number of barriers need to be overcome, as well, which pose challenges to the developers of the software that supports MBSE/MBMA. Information and data must be made to flow seamlessly through the life cycle. Because there is a wide variety of tools used in the community, to avoid the problems of the past of silos, delays, and diverging interests, information should flow among these tools to support the “single source of truth” paradigm of MBSE. This will greatly facilitate MBMA and advancement of assurance functions.

Evans, John W.↗

Additively Manufactured Ink-based Cell Batteries for Flexible Conformational Applications

With the rise of additively manufactured electronics, the importance of thin, flexible printed batteries has increased for shape-conformal electronics. Traditionally, battery cells such as industry-standard lithium-ion batteries, have been rigid and therefore unable to conform to time-variant surfaces such as smart cards/RFID devices, disposable battery-powered skin patches, foldable electronic devices, and IoT nodes. Aligned with the effort to advance technologies on printed electronics for habitat systems and advanced manufacturing, this proof-of-concept will focus on printing a 50 mAh Zn-Ag battery implementing a DIW Technique. After prototype manufacturing, electrical and environmental testing on the flexible battery cell will be conducted to the evaluate energy and power density over 50 charge cycles under standard atmosphere conditions. The project aims to provide PCB designers, fabricators, and assemblers an integrated battery package to eliminate external batteries, external wiring and connectors, and conformational complexity. Potential end uses of the printed battery process will be within Martian and lunar habitat systems, Gateway, and surface vehicles, or aerial robots where space and geometry is a restriction.

Printed Electronics↗

Tailoring Molecular Space to Navigate Phase Complexity in Cs-Based Quasi-2D Perovskites via Gated-Gaussian-Driven High-Throughput Discovery

Cesium-based quasi-2D halide perovskites (HPs) offer promising functionalities and low-temperature manufacturability, suited to stable tandem photovoltaics. However, the chemical interplays between the molecular spacers and the inorganic building blocks during crystallization cause substantial phase complexities in the resulting matrices. To successfully optimize and implement the quasi-2D HP functionalities, a systematic understanding of spacer chemistry, along with the seamless navigation of the inherently discrete molecular space, is necessary. Herein, by utilizing high-throughput automated experimentation, the phase complexities in the molecular space of quasi-2D HPs are explored, thus identifying the chemical roles of the spacer cations on the synthesis and functionalities of the complex materials. Furthermore, a novel active machine learning algorithm leveraging a two-stage decision-making process, called gated Gaussian process Bayesian optimization is introduced, to navigate the discrete ternary chemical space defined with two distinctive spacer molecules. Through simultaneous optimization of photoluminescence intensity and stability that “tailors” the chemistry in the molecular space, a ternary-compositional quasi-2D HP film realizing excellent optoelectronic functionalities is demonstrated. Finally, this work not only provides a pathway for the rational and bespoke design of complex HP materials but also sets the stage for accelerated materials discovery in other multifunctional systems.

36 MATERIALS SCIENCE↗

A simple and practical process modeling methodology for pressure swing adsorption

Although many dynamic models exist for the design and simulation of pressure swing adsorption (PSA) processes, these models involve the solution of a complex system of coupled partial differential equations. Process engineers need a simple, practical, and yet robust short-cut model that helps decide whether to implement a PSA system in a process flowsheet. This work presents a “virtual” moving bed modeling methodology that considers only mass and energy balances and adsorption isotherms to describe the cyclic steady state behavior of PSA systems. Similar to tray efficiencies in distillation calculations, adsorption efficiencies are further introduced to account for system “non-ideality.” Finally, a lab-scale air separation system is used to illustrate the application of this modeling methodology.

42 ENGINEERING↗

Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles

Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.

Ma, Jiacheng↗

How to design a zero-emissions vehicle mandate? Simulating impacts on sales, GHG emissions and cost-effectiveness using the AUtomaker-Consumer Model (AUM)

We report although numerous studies investigate the impacts of policy on zero-emissions vehicle (ZEV) sales, few address the impacts of a ZEV sales mandate and its particular design features. We use the AUtomaker-consumer Model (AUM) to simulate varying designs of a ZEV mandate in Canada's light-duty vehicle sector, requiring 30% ZEV sales by 2030. Design features include: different penalties for non-compliance, different allocations of credits per ZEV type, and the allowance of banking credits across years. For each policy design, we consider impacts on ZEV adoption, GHG emissions, consumer surplus, automaker profits, and overall policy cost-effectiveness. Results demonstrate trade-offs among the policy designs. Generally, ZEV mandate designs that are more effective at increasing ZEV adoption and decreasing GHG emissions also induce larger reductions in consumer surplus and automaker profits. To achieve the ZEV sales goal, simulations show that a higher non-compliance penalty (CDN$ 10k per credit) is needed. ZEV adoption and GHG reductions are also improved by a “One credit per ZEV” scheme, rather than a “California-style” scheme that gives multiple credits per battery-electric vehicle. Further, allowing automakers to bank credits softens the policy impact on profit and increases automaker compliance in initial years. Across these different design combinations, we find that the most cost-effective design ($CDN/tonne mitigated, including consumer surplus and automaker profits impacts) utilizes a $10k non-compliance penalty and “One credit per ZEV” system that allows banking. Our analysis demonstrates the importance of various ZEV mandate design features, and the complex trade-offs involved among various policy goals.

54 ENVIRONMENTAL SCIENCES↗

Computational optimization of electric fields for better catalysis design

Although the ubiquitous role that long-ranged electric fields play in catalysis has been recognized, it is seldom used as a primary design parameter in the discovery of new catalytic materials. Here in this paper, we illustrate how electric fields have been used to computationally optimize biocatalytic performance of a synthetic enzyme, and how they could be used as a unifying descriptor for catalytic design across a range of homogeneous and heterogeneous catalysts. Although focusing on electrostatic environmental effects may open new routes toward the rational optimization of efficient catalysts, much more predictive capacity is required of theoretical methods to have a transformative impact in their computational design — and thus experimental relevance — when using electric field alignments in the reactive centres of complex catalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

OCCULT-ORSER complete conversational user-language translator

Translator program (OCCULT) assists non-computer-oriented users in setting up and submitting jobs for complex ORSER system. ORSER is collection of image processing programs for analyzing remotely sensed data. OCCULT is designed for those who would like to use ORSER but cannot justify acquiring and maintaining necessary proficiency in Remote Job Entry Language, Job Control Language, and control-card formats. OCCULT is written in FORTRAN IV and OS Assembler for interactive execution.

Ramapriyan, H. K.↗

Designer's guide to radiation effects on materials for use on Jupiter fly-bys and orbiters

This paper summarizes the state-of-the-art of the complex field of radiation effects on spacecraft materials. It is intended as a guide for designers of systems exposed to damaging electrons and protons. The emphasis is on the relative damage levels for the more common materials that may be used. Information on the preliminary flux and fluence levels of the yet to be designed Jupiter orbiter, Galileo, is also presented.

Bouquet, F. L.↗

Digital transmitter - Simple, yet precise

A transmitter developed for operation at high digital transmission speeds is described. It is a complex system that produces a clean waveform with data rates as high as 1 Mb/s; and its design makes it possible to vary all possible modulation schemes by reprogramming a chip, to vary data-transmission rates with the clock frequency, and to shape pulses without distortion. The design, furthermore, can be adapted to very-large-scale-integration (VLSI) fabrication and mass production. A prototype QPSK residual carrier modulation transmitter was fabricated and tested. The purpose was to create a deep null in the data spectrum to transmit a tone or residual carrier along with the modulation.

Davarian, F.↗

Aeropropulsion structures

The structural engineer is faced with unique problems when dealing with aeropropulsion systems. He is faced with extremes in operating temperatures, rotational effects, and behaviors of advanced material systems which combine into complexities that require advances in many scientific disciplines involved in structural analysis and design procedures. This presentation provides an overview of the complexities of aeropropulsion structures and the theoretical, computational, and experimental research conducted to achieve the needed advances.

Nichols, Lester D.↗

Mobile telephony through LEO satellites: To OBP or not

GLOBALSTAR is a satellite-based mobile communications system that is interoperable with the current and future Public Land Mobile Network (PLMN) and Public Switched Telephone Network (PSTN). The selection of the transponder type, bent-pipe, or onboard processing (OBP), for GLOBALSTAR is based on many criteria, each of which is essential to the commercial and technological feasibility of GLOBALSTAR. The trade study that was done to determine the pros and cons of a bent-pipe transponder or an onboard processing transponder is described. The design of GLOBALSTAR's telecommunications system is a multi-variable cost optimization between the cost and complexity of individual satellites, the number of satellites required to provide coverage to the service areas, the cost of launching the satellites into their selected orbits, the ground segment cost, user equipment cost, satellite voice channel capacity, and other issues. Emphasis is on the cost and complexity of the individual satellites, specifically the transponder type and the impact of the transponder type on satellite and ground segment cost, satellite power and weight, and satellite voice channel capacity.

Monte, Paul A.↗

Distributed digital signal processors for multi-body flexible structures

Multi-body flexible structures, such as those currently under investigation in spacecraft design, are large scale (high-order) dimensional systems. Controlling and filtering such structures is a computationally complex problem. This is particularly important when many sensors and actuators are located along the structure and need to be processed in real time. This report summarizes research activity focused on solving the signal processing (that is, information processing) issues of multi-body structures. A distributed architecture is developed in which single loop processors are employed for local filtering and control. By implementing such a philosophy with an embedded controller configuration, a supervising controller may be used to process global data and make global decisions as the local devices are processing local information. A hardware testbed, a position controller system for a servo motor, is employed to illustrate the capabilities of the embedded controller structure. Several filtering and control structures which can be modeled as rational functions can be implemented on the system developed in this research effort. Thus the results of the study provide a support tool for many Control/Structure Interaction (CSI) NASA testbeds such as the Evolutionary model and the nine-bay truss structure.

Lee, Gordon K. F.↗

Development of new flux splitting schemes

Maximizing both accuracy and efficiency has been the primary objective in designing a numerical algorithm for CFD. This is especially important for solution of complex three-dimensional systems of Navier-Stokes equations which often include turbulence modeling and chemistry effects. Recently, upwind schemes have been well received for both their capability of resolving discontinuities and their sound theoretical basis in characteristic theory for hyperbolic systems. With this in mind, two new flux splitting techniques are presented for upwind differencing.

Liou, MENG-S.↗

High speed research system study. Advanced flight deck configuration effects

In mid-1991 NASA contracted with industry to study the high-speed civil transport (HSCT) flight deck challenges and assess the benefits, prior to initiating their High Speed Research Program (HSRP) Phase 2 efforts, then scheduled for FY-93. The results of this nine-month effort are presented, and a number of the most significant findings for the specified advanced concepts are highlighted: (1) a no nose-droop configuration; (2) a far forward cockpit location; and (3) advanced crew monitoring and control of complex systems. The results indicate that the no nose-droop configuration is critically dependent upon the design and development of a safe, reliable, and certifiable Synthetic Vision System (SVS). The droop-nose configuration would cause significant weight, performance, and cost penalties. The far forward cockpit location, with the conventional side-by-side seating provides little economic advantage; however, a configuration with a tandem seating arrangement provides a substantial increase in either additional payload (i.e., passengers) or potential downsizing of the vehicle with resulting increases in performance efficiencies and associated reductions in emissions. Without a droop nose, forward external visibility is negated and takeoff/landing guidance and control must rely on the use of the SVS. The technologies enabling such capabilities, which de facto provides for Category 3 all-weather operations on every flight independent of weather, represent a dramatic benefits multiplier in a 2005 global ATM network: both in terms of enhanced economic viability and environmental acceptability.

Swink, Jay R.↗