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At least 1,279 records · Page 71

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NASA NTRS2015

R2U2: Monitoring and Diagnosis of Security Threats for Unmanned Aerial Systems

We present R2U2, a novel framework for runtime monitoring of security properties and diagnosing of security threats on-board Unmanned Aerial Systems (UAS). R2U2, implemented in FPGA hardware, is a real-time, REALIZABLE, RESPONSIVE, UNOBTRUSIVE Unit for security threat detection. R2U2 is designed to continuously monitor inputs from the GPS and the ground control station, sensor readings, actuator outputs, and flight software status. By simultaneously monitoring and performing statistical reasoning, attack patterns and post-attack discrepancies in the UAS behavior can be detected. R2U2 uses runtime observer pairs for linear and metric temporal logics for property monitoring and Bayesian networks for diagnosis of security threats. We discuss the design and implementation that now enables R2U2 to handle security threats and present simulation results of several attack scenarios on the NASA DragonEye UAS.

Formal Methods↗

NASA NTRS1991

Design of thrust vectoring exhaust nozzles for real-time applications using neural networks

Thrust vectoring continues to be an important issue in military aircraft system designs. A recently developed concept of vectoring aircraft thrust makes use of flexible exhaust nozzles. Subtle modifications in the nozzle wall contours produce a non-uniform flow field containing a complex pattern of shock and expansion waves. The end result, due to the asymmetric velocity and pressure distributions, is vectored thrust. Specification of the nozzle contours required for a desired thrust vector angle (an inverse design problem) has been achieved with genetic algorithms. This approach is computationally intensive and prevents the nozzles from being designed in real-time, which is necessary for an operational aircraft system. An investigation was conducted into using genetic algorithms to train a neural network in an attempt to obtain, in real-time, two-dimensional nozzle contours. Results show that genetic algorithm trained neural networks provide a viable, real-time alternative for designing thrust vectoring nozzles contours. Thrust vector angles up to 20 deg were obtained within an average error of 0.0914 deg. The error surfaces encountered were highly degenerate and thus the robustness of genetic algorithms was well suited for minimizing global errors.

Prasanth, Ravi K.↗

NASA NTRS2011

Infrared-Bolometer Arrays with Reflective Backshorts

Integrated circuits that incorporate square arrays of superconducting-transition- edge bolometers with optically reflective backshorts are being developed for use in image sensors in the spectral range from far infrared to millimeter wavelengths. To maximize the optical efficiency (and, thus, sensitivity) of such a sensor at a specific wavelength, resonant optical structures are created by placing the backshorts at a quarter wavelength behind the bolometer plane. The bolometer and backshort arrays are fabricated separately, then integrated to form a single unit denoted a backshort-under-grid (BUG) bolometer array. In a subsequent fabrication step, the BUG bolometer array is connected, by use of single-sided indium bump bonding, to a readout device that comprises mostly a superconducting quantum interference device (SQUID) multiplexer circuit. The resulting sensor unit comprising the BUG bolometer array and the readout device is operated at a temperature below 1 K. The concept of increasing optical efficiency by use of backshorts at a quarter wavelength behind the bolometers is not new. Instead, the novelty of the present development lies mainly in several features of the design of the BUG bolometer array and the fabrication sequence used to implement the design. Prior to joining with the backshort array, the bolometer array comprises, more specifically, a square grid of free-standing molybdenum/gold superconducting-transition-edge bolometer elements on a 1.4- m-thick top layer of silicon that is part of a silicon support frame made from a silicon-on-insulator wafer. The backshort array is fabricated separately as a frame structure that includes support beams and contains a correspond - ing grid of optically reflective patches on a single-crystal silicon substrate. The process used to fabricate the bolometer array includes standard patterning and etching steps that result in the formation of deep notches in the silicon support frame. These notches are designed to interlock with the support beams on the backshort-array structure to provide structural support and precise relative positioning. The backshort-array structure is inserted in the silicon support frame behind the bolometer array, and the notches in the frame serve to receive the support beams of the backshort-array structure and thus determine the distance between the backshort and bolometer planes. The depth of the notches and, thus, the distance between the backshort and bolometer planes, can be tailored to a value between 25 to 300 m adjusting only a few process steps. The backshort array is designed so as not to interfere with the placement of indium bumps for subsequent indium bump-bonding to the multiplexing readout circuitry

Miller, Timothy M.↗

NASA NTRS2013

Characterization of Swirl-Venturi Lean Direct Injection Designs for Aviation Gas-Turbine Combustion

Injector geometry, physical mixing, chemical processes, and engine cycle conditions together govern performance, operability and emission characteristics of aviation gas-turbine combustion systems. The present investigation explores swirl-venturi lean direct injection combustor fundamentals, characterizing the influence of key geometric injector parameters on reacting flow physics and emission production trends. In this computational study, a design space exploration was performed using a parameterized swirl-venturi lean direct injector model. From the parametric geometry, 20 three-element lean direct injection combustor sectors were produced and simulated using steady-state, Reynolds-averaged Navier-Stokes reacting computations. Species concentrations were solved directly using a reduced 18-step reaction mechanism for Jet-A. Turbulence closure was obtained using a nonlinear κ-ε model. Results demonstrate sensitivities of the geometric perturbations on axially averaged flow field responses. Output variables include axial velocity, turbulent kinetic energy, static temperature, fuel patternation and minor species mass fractions. Significant trends have been reduced to surrogate model approximations, intended to guide future injector design trade studies and advance aviation gas-turbine combustion research.

Combustion Chamber↗

DOE OSTI2022

Harnessing structural stochasticity in the computational discovery and design of microstructures

This paper presents a deep generative model-based design methodology for tailoring the structural stochasticity of microstructures. Although numerous methods have been established for designing deterministic (periodic) or stochastic microstructures, a systematic design approach that allows the unified treatment of both deterministic and stochastic microstructure design domains has yet to be created. The proposed methodology resolves this issue by learning a unified feature space that embodies diverse structural patterns with continuously varying stochasticity levels. A highly diverse microstructure database is established to incorporate various types of deterministic and stochastic microstructure patterns. A property-aware deep generative model is proposed to learn a unified feature space of the structural characteristics, as well as the relationship between structure features and properties of interest. Autoencoder (AE), Variational Autoencoder (VAE), and Adversarial Autoencoder (AAE) are compared to understand their relative merits in the property-aware learning of the unified feature space. Microstructural designs with tailorable stochasticity and properties are obtained by searching the unified feature space. Multiple design cases are presented to demonstrate the capability of designing microstructures for structural stochasticity and properties. Furthermore, the proposed method is employed to create stochastically graded structures, which manipulate the mechanical behaviors by varying the local stochasticity of the structure.

36 MATERIALS SCIENCE↗

DOE OSTI2021

ADDS-EVS: An agent-based deployment decision-support system for electric vehicle services

Rapid and sustainable development of the electric vehicle (EV) industry places the requirement for the plan of EV deployment. For public EV, existing models mainly focus on the charging facility design and fail to capture the multi-modal scenarios. In this work, we develop an agent-based decision-support system for multi-modal electric transits to locate the optimal combinations of key parameters, including the fleet size, the transit schedule, the charging facility design, and the routing strategy. We demonstrate the utilities of our system by simulating public EV services deployed to serve travel needs related to a transportation hub in New York City. To support the decision of the fleet size, we summarize system-level performances including the total satisfied demand, passengers' waiting time, vehicle idling time. The spatial and temporal patterns are extracted to serve a deeper understanding of system dynamics and service quality. Finally, we investigate the interaction between the fleet size design and the routing strategy. The results suggest a necessity of integrating the operation strategies into the planning phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2002

The Stellar Imager (SI) Mission Concept

The Stellar Imager (SI) is envisioned as a space-based, UV-optical interferometer composed of 10 or more one-meter class elements distributed with a maximum baseline of 0.5 km. It is designed to image stars and binaries with sufficient resolution to enable long-term studies of stellar magnetic activity patterns, for comparison with those on the sun. It will also support asteroseismology (acoustic imaging) to probe stellar internal structure, differential rotation, and large-scale circulations. SI will enable us to understand the various effects of the magnetic fields of stars, the dynamos that generate these fields, and the internal structure and dynamics of the stars. The ultimate goal of the mission is to achieve the best-possible forecasting of solar activity as a driver of climate and space weather on time scales ranging from months up to decades, and an understanding of the impact of stellar magnetic activity on life in the Universe. In this paper we describe the scientific goals of the mission, the performance requirements needed to address these goals, the "enabling technology" development efforts being pursued, and the design concepts now under study for the full mission and a possible pathfinder mission.

Carpenter, Kenneth G.↗

DOE OSTI2020

Optical Design and Characterization of 40-GHz Detector and Module for the BICEP Array

Families of cosmic inflation models predict a primordial gravitational-wave background that imprints B-mode polarization pattern in the cosmic microwave background (CMB). High-sensitivity instruments with wide frequency coverage and well-controlled systematic errors are needed to constrain the faint B-mode amplitude. We have developed antenna-coupled transition edge sensor arrays for high-sensitivity polarized CMB observations over a wide range of millimeter-wave bands. BICEP array, the latest phase of the BICEP/Keck experiment series, is a multi-receiver experiment designed to search for inflationary B-mode polarization to a precision σ(r) between 0.002 and 0.004 after 3 full years of observations, depending on foreground complexity and the degree of lensing removal. We describe the electromagnetic design and measured performance of BICEP array’s low-frequency 40-GHz detector, their packaging in focal plane modules, and optical characterization including efficiency and beam matching between polarization pairs. We summarize the design and simulated optical performance, including an approach to improve the optical efficiency due to mismatch losses. Here, we report the measured beam maps for a new broadband corrugation design to minimize beam differential ellipticity between polarization pairs caused by interactions with the module housing frame, which helps minimize polarized beam mismatch that converts CMB temperature to polarization (T→P) anisotropy in CMB maps.

47 OTHER INSTRUMENTATION↗

NASA NTRS1999

Investigation of Near Shannon Limit Coding Schemes

Turbo codes can deliver performance that is very close to the Shannon limit. This report investigates algorithms for convolutional turbo codes and block turbo codes. Both coding schemes can achieve performance near Shannon limit. The performance of the schemes is obtained using computer simulations. There are three sections in this report. First section is the introduction. The fundamental knowledge about coding, block coding and convolutional coding is discussed. In the second section, the basic concepts of convolutional turbo codes are introduced and the performance of turbo codes, especially high rate turbo codes, is provided from the simulation results. After introducing all the parameters that help turbo codes achieve such a good performance, it is concluded that output weight distribution should be the main consideration in designing turbo codes. Based on the output weight distribution, the performance bounds for turbo codes are given. Then, the relationships between the output weight distribution and the factors like generator polynomial, interleaver and puncturing pattern are examined. The criterion for the best selection of system components is provided. The puncturing pattern algorithm is discussed in detail. Different puncturing patterns are compared for each high rate. For most of the high rate codes, the puncturing pattern does not show any significant effect on the code performance if pseudo - random interleaver is used in the system. For some special rate codes with poor performance, an alternative puncturing algorithm is designed which restores their performance close to the Shannon limit. Finally, in section three, for iterative decoding of block codes, the method of building trellis for block codes, the structure of the iterative decoding system and the calculation of extrinsic values are discussed.

Kwatra, S. C.↗

NASA NTRS2021

Solar-power for Deep Space Science Missions

Solar power systems have enabled dazzling planetary science missions to much of the Solar System. This chapter outlines the types of solar array structures that have been used on U.S.-led robotic planetary science missions since the beginning of the space age, including several in development for future launch. The first solar-powered spacecraft employed body-mounted solar cells but designs quickly moved to extended panels to generate more electrical power. Early “paddle” designs were replaced by deployable twin rectangular “wings” which are still common in science missions and nearly ubiquitous in commercial telecommunications satellites. The increasing complexity of science missions investigating the nature of the space environment drove the development of the solar-powered satellites from the very beginning, and unique mission requirements to explore ever more distant and harsher regions of our solar system continue to drive innovations in spacecraft design, including solar arrays. This general progression to ever larger solar arrays to power ever more sophisticated spacecraft in ever harsher environments, punctuated by missions that emphasize lower cost and complexity, is a pattern that began in the 1960s and continues to this day. This chapter describes the solar array configurations used on deep space missions, with an emphasis on NASA’s planetary science missions, including specific design requirements that led to individual design selections. Future trends are also described.

Carolyn R Mercer↗

DOE OSTI2015

Development and Industrialization of InGaN/GaN LEDs on Patterned Sapphire Substrates for Low Cost Emitter Architecture

Patterned sapphire substrate (PSS) technology has proven to be an effective approach to improve efficacy and reduce cost of light-emitting diodes (LEDs). The volume emission from the transparent substrate leads to high package efficiency, while the simple and robust architecture of PSS-based LEDs enables low cost. PSS substrates have gained wide use in mid-power LEDs over the past years. In this project, Lumileds has developed and industrialized PSS and epitaxy technology for high- power flip-chip LEDs to bring these benefits to a broader range of applications and accelerate the adoption of energy-efficient solid-state lighting (SSL). PSS geometries were designed for highly efficient light extraction in a flip-chip architecture and high-volume manufacturability, and corresponding sapphire patterning and epitaxy manufacturing processes were integrally developed. Concurrently, device and package architectures were developed to take advantage of the PSS flip-chip die in different types of products that meet application needs. The developed PSS and epitaxy technology has been fully implemented in manufacturing at Lumileds’ San Jose, CA location, and incorporated in illumination-grade LED products that have been successfully introduced to the market, including LUXEON Q and LUXEON FlipChip White.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Improved Accuracy for Automated Communication Pattern Characterization Using Communication Graphs and Aggressive Search Space Pruning

An understanding of a parallel application’s communication behavior is useful for a range of activities including debugging and optimization, job scheduling, target system selection, and system design. Because it can be challenging to understand communication behavior, especially for those who lack expertise or who are not familiar with the application, I and two colleagues recently developed an automated, search-based approach for recognizing and parameterizing application communication behavior using a library of common communication patterns. This initial approach was effective for characterizing the behavior of many workloads, but I identified some combinations of communication patterns for which the method was inefficient or would fail. In this paper, I discuss one such troublesome pattern combination and propose modifications to the recognition method to handle it. Specifically, I propose an alternative approach that uses communication graphs instead of traditional communication matrices to improve recognition accuracy for collective communication operations, and that uses a non-greedy recognition technique to avoid search space dead-ends that trap the original greedy recognition approach. My modified approach uses aggressive search space pruning and heuristics to control the potential for state explosion caused by its non-greedy pattern recognition method. I demonstrate the improved recognition accuracy and pruning efficacy of the modified approach using several synthetic and real-world communication pattern combinations.

Roth, Philip↗

NASA NTRS1989

Engineering specification and system design for CAD/CAM of custom shoes. Phase 5: UMC involvement (January 1, 1989 - June 30, 1989)

The CAD/CAM of custom shoes is discussed. The solid object for machining is represented by a wireframe model with its nodes or vertices specified systematically in a grid pattern covering its entire length (point-to-point configuration). Two sets of data from CENCIT and CYBERWARE were used for machining purposes. It was found that the indexing technique (turning the stock by a small angle then moving the tool on a longitudinal path along the foot) yields the best result in terms of ease of programming, savings in wear and tear of the machine and cutting tools, and resolution of fine surface details. The work done using the LASTMOD last design system results in a shoe last specified by a number of congruent surface patches of different sizes. This data format was converted into a form amenable to the machine tool. It involves a series of sorting algorithms and interpolation algorithms to provide the grid pattern that the machine tool needs as was the case in the point to point configuration discussed above. This report also contains an in-depth treatment of the design and production technique of an integrated sole to complement the task of design and manufacture of the shoe last. Clinical data and essential production parameters are discussed. Examples of soles made through this process are given.

Bao, Han P.↗

NASA NTRS1992

Artificial neural network implementation of a near-ideal error prediction controller

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Mcvey, Eugene S.↗

DOE OSTI2018

Modulating Self-Assembly of DNA Crystals with Rationally Designed Agents

This article reports a strategy for controlling the crystallization kinetics and improving the quality of engineered self-assembled 3D DNA crystals. Growing large, high-quality biomacromolecule crystals is critically important for determining the 3D structures of biomacromolecules. It often presents a great challenge to structural biologists. Herein, we introduce a rationally designed agent to modulate the crystallization process. Under such conditions, fewer, but larger, crystals that yield diffraction patterns of modestly higher resolution are produced compared with the crystals from conditions without the modulating agent. We attribute the improvement to a smaller number of nuclei and slow growth rate of crystallization. This strategy is expected to be generally applicable for crystallization of other biomacromolecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Differential degradation patterns of photovoltaic backsheets at the array level

There are relatively few field studies on the degradation of non-fluoropolymer-based backsheets, and understanding their in-field behavior is critical for further development of such products. In this paper, backsheet degradation of modules with one of these new types of backsheets (polyethylene naphthalate (PEN)-based) was documented at a four-year old utility-scale array located in Maryland (USA). Visual inspection, colorimetry, glossimetry, and Fourier-transform infrared spectroscopy (FTIR) revealed highly varied properties depending on module position within the array. Specifically, modules near the edge of the array and with higher mounting elevations underwent greater amounts of backsheet degradation, as indicated by yellowing and gloss-loss. The reason for these unique degradation patterns were differential backside exposure conditions, especially of ultraviolet light. This was strongly influenced by the array design, including array structural and environmental factors, such as module spacing and ground cover, respectively. Within the array, no clear link between backsheet degradation and module output or safety has been identified. However, such a relationship may be expected to become more pronounced with time, affecting system lifetime and ultimately the levelized cost of electricity (LCOE). Finally, the observed phenomena have implications for both backsheet product development and array design, especially for modules that utilize newer classes of non-fluoropolymer-based backsheets which are typically more susceptible to environmental degradation.

14 SOLAR ENERGY↗

DOE OSTI2022

Discovery of chalcogenides structures and compositions using mixed fluxes

Advancements in many modern technologies rely on the continuous need for materials discovery. However, the design of synthesis routes leading to new and targeted solid-state materials requires understanding of reactivity patterns. Advances in synthesis science are necessary to increase efficiency and accelerate materials discovery. We present a highly effective methodology for the rational discovery of materials using high-temperature solutions or fluxes having tunable solubility. This methodology facilitates product selection by projecting the free-energy landscape into real synthetic variables: temperature and flux ratio. We demonstrate the effectiveness of this technique by synthesizing compounds in the chalcogenide system of A(Ba)-Cu-Q(O) (Q = S or Se; A = Na, K or Rb) using mixed AOH/AX (A = Li, Na, K or Rb; X = Cl or I) fluxes. We present 30 unreported compounds or compositions, including more than ten unique structural types, by systematically varying the temperature and flux ratios without requiring changing the proportions of starting materials. Additionally, we found that the structural dimensionality of the compounds decreases with increasing reactant solubility and temperature. This methodology serves as an effective general strategy for the rational discovery of inorganic solids.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Perovskite nanowire–block copolymer composites with digitally programmable polarization anisotropy

One-dimensional (1D) nanomaterials with highly anisotropic optoelectronic properties are key components in energy harvesting, flexible electronics, and biomedical imaging devices. 3D patterning methods that precisely assemble nanowires with locally controlled composition and orientation would enable new optoelectronic device designs. As an exemplar, we have created and 3D-printed nanocomposite inks composed of brightly emitting colloidal cesium lead halide perovskite (CsPbX 3 , X = Cl, Br, and I) nanowires suspended in a polystyrene-polyisoprene-polystyrene block copolymer matrix. The nanowire alignment is defined by the programmed print path, resulting in optical nanocomposites that exhibit highly polarized absorption and emission properties. Several devices have been produced to highlight the versatility of this method, including optical storage, encryption, sensing, and full-color displays.

36 MATERIALS SCIENCE↗