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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Assured Vehicle Automation 1 Sim - Results Outbrief

In early 2022, the Human Autonomy Teaming Lab (NASA Ames Research Center) conducted a manned, human-in-the-loop (HITL) simulation. This part-task HITL began the lab’s Hazard Perception and Avoidance (HPA) technical work under NASA’s Advanced Air Mobility (AAM), Automated Flight and Contingency Management (AFCM) Sub-Project. The results of that sim guided the objectives of the current study, which were to examine pilots’ use of the Airborne Collision Avoidance System (ACAS) rotorcraft variant (Xr) v2 in multiple phases of flight with two separate Xr Modes, fully leverage Xr v2 features (e.g., use radar altimeter data to inform low altitude Resolution Advisory [RA] behavior, utilize the ability to designate “terminal-area intruders,” and display airspeed-based Detect and Avoid [DAA] guidance), emulate a “Traffic Advisory” (TA), and present Xr in a higher-fidelity environment. Therefore, this study was conducted in the Vertical Motion Simulator, and the variables included Phase of Flight (En-route, Hover, and Approach) as well as ACAS Xr Mode (TA/RA and DAA). The data collected included response times, losses of well clear, and maneuver sizes and durations as well as subjective ratings like acceptability and usability. Additional details and future anticipations are also discussed.

air taxis↗
DOE OSTI2024

Emulator of PR‐DNS: Accelerating Dynamical Fields With Neural Operators in Particle‐Resolved Direct Numerical Simulation

Abstract Particle‐resolved direct numerical simulations (PR‐DNS) play an increasing role in investigating aerosol‐cloud‐turbulence interactions at the most fundamental level of processes. However, the high computational cost associated with high resolution simulations poses considerable challenges for large domain or long duration simulation using PR‐DNS. To address these issues, here we present an emulator of the complex physics‐based PR‐DNS developed by use of the data‐driven Fourier Neural Operator (FNO) method. The effectiveness of the method is showcased by presenting turbulence and temperature fields in a two‐dimensional space. The results demonstrate high accuracy at various resolutions and the emulator is two orders of magnitude cheaper in terms of computational demand compared to the physics‐based PR‐DNS model. Furthermore, the FNO emulator exhibits strong generalization capabilities for different initial conditions and ultra‐high‐resolution without the need to retrain models. These findings highlight the potential of the FNO method as a promising tool to simulate complex fluid dynamics problems with high accuracy, computational efficiency, and generalization capabilities, enhancing our understanding of the aerosol‐cloud‐precipitation system.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Optimal Control for the Quantum Simulation of Nuclear Dynamics

We propose a method for enacting the unitary time propagation of two interacting neutrons at leading order of chiral effective-field theory by efficiently encoding the nuclear dynamics into a single multilevel quantum device. The emulated output of the quantum simulation shows that, by applying a single gate that draws on the underlying characteristics of the device, it is possible to observe multiple cycles of the nuclear dynamics before the onset of decoherence. Owing to the signal's longevity, we can then extract spectroscopic properties of the simulated nuclear system. This allows us to validate the encoding of the nuclear Hamiltonian and the robustness of the simulation in the presence of quantum-hardware noise by comparing the extracted spectroscopic information to exact calculations. This work paves the way for transformative calculations of the dynamical properties of nuclei on near-term quantum devices.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1989

Centralized database for interconnection system design

A database application called DFACS (Database, Forms and Applications for Cabling and Systems) is described. The objective of DFACS is to improve the speed and accuracy of interconnection system information flow during the design and fabrication stages of a project, while simultaneously supporting both the horizontal (end-to-end wiring) and the vertical (wiring by connector) design stratagems used by the Jet Propulsion Laboratory (JPL) project engineering community. The DFACS architecture is centered around a centralized database and program methodology which emulates the manual design process hitherto used at JPL. DFACS has been tested and successfully applied to existing JPL hardware tasks with a resulting reduction in schedule time and costs.

Billitti, Joseph W.↗
NASA NTRS2020

Detector Channel Combining Results from a High Photon Efficiency Optical Communications Link Test Bed

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is developing a low cost, scalable, photon-counting receiver prototype for space-to-ground optical communications links. The receiver is being tested in a test bed that emulates photon-starved space-to-ground optical communication links. The receiver uses an array of single-pixel fiber-coupled superconducting nanowire single-photon detectors. The receiver is designed to receive the high photon efficiency serially concatenated pulse position modulation (SCPPM) waveform specified in the Consultative Committee for Space Data Systems (CCSDS) Optical Communications Coding and Synchronization Blue Book Standard. The optical receiver consists of an array of single-pixel superconducting nanowire detectors, analog phase shifters for channel alignment, digitizers for each detector channel, and digital processing of the received signal. An overview of the test bed and arrayed receiver system is given. Simulation and system characterization results are presented. The data rate increase of using a four-channel arrayed detector system over using one single pixel nanowire detector is characterized. Results indicate that a single-pixel detector is capable of receiving data at a rate of 40 Mbps and a four-channel arrayed detector system is capable of receiving data at a rate of 130 Mbps.

Downey, Jennifer N.↗
NASA NTRS2020

Detector Channel Combining Results from a High Photon Efficiency Optical Communications Link Test Bed

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is developing a low cost, scalable, photon counting receiver prototype for space-to-ground optical communications links. The receiver is being tested in a test bed that emulates photon-starved space-to-ground optical communication links. The receiver uses an array of single-pixel fiber-coupled superconducting nanowire single-photon detectors. The receiver is designed to receive the high photon efficiency serially concatenated pulse position modulation (SCPPM) waveform specified in the Consultative Committee for Space Data Systems (CCSDS) Optical Communications Coding and Synchronization Blue Book Standard. The optical receiver consists of an array of single-pixel superconducting nanowire detectors, analog phase shifters for channel alignment, digitizers for each detector channel, and digital processing of the received signal. An overview of the test bed and arrayed receiver system is given. Simulation and system characterization results are presented. The data rate increase of using a four-channel arrayed detector system over using one single pixel nanowire detector is characterized. Results indicate that a single-pixel detector is capable of receiving data at a rate of 40 Mbps and a four-channel arrayed detector system is capable of receiving data at a rate of 130 Mbps.

Downey, Jennifer N.↗
NASA NTRSDate not supplied

Insertion Loss of a Multi-Plane Light Conversion Device with Few Mode Fiber Outputs Under Atmospheric Conditions

A key challenge of photon counting optical communication is delivering light with atmospherically distorted wavefronts from the telescope to detectors efficiently. When using fiber coupled single photon detectors, the efficiency of the transmittance is constrained by the modes supported by the fiber. The number of modes supported by a fiber depends on the size of the core. The larger the core, the more modes supported. However, commercial off the shelf superconducting nanowire single photon detectors (SNSPDs) are currently limited in area, which limits the core size of the fibers that can efficiently couple to the detectors. To increase the amount of light that can be delivered to the detectors, NASA Glenn Research Center is considering many different fiber/detector architectures. This paper compares insertion loss of the fiber device for two different architectures: • a multi-plane light conversion device to split the light from a 30 µm core diameter fiber into 7 separate, 15 µm core diameter few-mode fibers butt-coupled to 7 single-element SNSPDs, and • a 30 µm core diameter multimode fiber butt-coupled to a 16 multi-element, SNSPD array. The measured insertion loss for each fiber device under emulated atmospheric conditions with D/r0 between 2 and 30 is presented. The multi-plane light conversion device shows a consistent ~1 dB loss more than the multimode fiber. Also presented is the measured uneven power splitting of the multiplane light conversion device, especially at lower D/r0. How this uneven power splitting contributes to system loss called blocking loss is discussed.

Fiber↗
NASA NTRSDate not supplied

Insertion Loss of a Multi-Plane Light Conversion Device with Few Mode Fiber Outputs Under Atmospheric Conditions

A key challenge of photon counting optical communication is delivering light with atmospherically distorted wavefronts from the telescope to detectors efficiently. When using fiber coupled single photon detectors, the efficiency of the transmittance is constrained by the modes supported by the fiber. The number of modes supported by a fiber depends on the size of the core. The larger the core, the more modes supported. However, commercial off the shelf superconducting nanowire single photon detectors (SNSPDs) are currently limited in area, which limits the core size of the fibers that can efficiently couple to the detectors. To increase the amount of light that can be delivered to the detectors, NASA Glenn Research Center is considering many different fiber/detector architectures. This paper compares insertion loss of the fiber device for two different architectures: • a multi-plane light conversion device to split the light from a 30 µm core diameter fiber into 7 separate, 15 µm core diameter few-mode fibers butt-coupled to 7 single-element SNSPDs, • and a 30 µm core diameter multimode fiber butt-coupled to a 16 multi-element, SNSPD array. The measured insertion loss for each fiber device under emulated atmospheric conditions with D/r0 between 2 and 30 is presented. The multi-plane light conversion device shows a consistent ~1 dB loss more than the multimode fiber. Also presented is the measured uneven power splitting of the multiplane light conversion device, especially at lower D/r0. How this uneven power splitting contributes to system loss called blocking loss is discussed.

Multi-plane light conversion device↗
DOE OSTI2025

Programmable exploration of magnetic states in Lieb-kagome interpolated lattices

We investigate a hybrid modeling framework in which a quantum annealer is used to simulate magnetic interactions in molecular qubit lattices inspired by experimentally realizable systems. Using phthalocyanine assemblies as a structurally constrained prototype, we model a continuous deformation from a Lieb to a kagome lattice, revealing frustration-driven disorder and magnetic field-induced reordering in the spin structure. Here, the goal is to show how a quantum annealer can operate as a physically instantiated, programmable platform to emulate experimentally relevant lattice deformations and produce observables in a manner analogous to an experimental measurement, enabling the characterization of magnetic arrangements beyond the reach of current molecular architectures. This surrogate modeling approach offers a pathway to explore and iteratively design tunable magnetic states in synthetic materials. The synthetic design, structural characterization, and quantum simulation framework established here defines a modular and scalable paradigm for probing the limits of engineered matter across chemistry, condensed matter, and quantum information science.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Emulating the Android Boot Process

Critical vulnerabilities continue to be discovered in the boot process of Android smartphones used around the world. The entire device's security is compromised if boot security is compromised, so any weakness presents undue risk to users. Vulnerabilities persist, in part, because independent security analysts lack access and appropriate tools. In response to this gap, we implemented a procedure for emulating the early phase of the Android boot process. This work demonstrated feasibility and utility of emulation in this space. By using HALucinator, we derived execution context and data flow, as well as incorporated peripheral hardware behavior. While smartphones with shared processors have substantial code overlap regardless of vendor, generational changes can have a significant impact. By applying our approach to older and modern devices, we learned interesting characteristics about the system. Such capabilities introduce new levels of introspection and operation understanding not previously available to mobile researchers.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Implementation of the DAST ARW II control laws using an 8086 microprocessor and an 8087 floating-point coprocessor

A 5 MHZ single-board microprocessor system which incorporates an 8086 CPU and an 8087 Numeric Data Processor is used to implement the control laws for the NASA Drones for Aerodynamic and Structural Testing, Aeroelastic Research Wing II. The control laws program was executed in 7.02 msec, with initialization consuming 2.65 msec and the control law loop 4.38 msec. The software emulator execution times for these two tasks were 36.67 and 61.18, respectively, for a total of 97.68 msec. The space, weight and cost reductions achieved in the present, aircraft control application of this combination of a 16-bit microprocessor with an 80-bit floating point coprocessor may be obtainable in other real time control applications.

Kelly, G. L.↗
NASA NTRS2010

Emulating an Optical Planetary Access Link with an Aircraft

Video imagery was streamed from the ground to an aircraft using a free-space laser communication link. The link operated at 270 Mb/s over slant ranges of 5-9 km in day and night time background conditions. The experiment was designed to demonstrate autonomous link acquisition and served as a first proof-of-concept for a planetary access link between a surface asset and an orbiter at Mars. System parameters monitored during the link demonstration including acquisition and tracking and communication performance are discussed.

Ground-to-Aircraft↗
DOE OSTI2021

Chemoselective and Site-Selective Reductions Catalyzed by a Supramolecular Host and a Pyridine–Borane Cofactor

Supramolecular catalysts emulate the mechanism of enzymes to achieve large rate accelerations and precise selectivity under mild and aqueous conditions. While significant strides have been made in the supramolecular host-promoted synthesis of small molecules, applications of this reactivity to chemoselective and site-selective modification of complex biomolecules remain virtually unexplored. We report here a supramolecular system where coencapsulation of pyridine-borane with a variety of molecules including enones, ketones, aldehydes, oximes, hydrazones, and imines effects efficient reductions under basic aqueous conditions. Furthermore, upon subjecting unprotected lysine to the host-mediated reductive amination conditions, we observed excellent ε-selectivity, indicating that differential guest binding within the same molecule is possible without sacrificing reactivity. Inspired by the post-translational modification of complex biomolecules by enzymatic systems, we then applied this supramolecular reaction to the site-selective labeling of a single lysine residue in an 11-amino acid peptide chain and human insulin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning

Spiking Neural Networks (SNNs) are computational models inspired by the event-driven communication and connectivity patterns of biological neural circuits. They enable high energy efficiency and natural support for diverse architectures ranging from layered networks to small-world and graphstructured topologies. In this work, we introduce NeuroCoreX, an open-source, FPGA-based spiking neural network emulator that provides real-time, on-chip learning and flexible network organization. NeuroCoreX supports both feedforward sensory inputs streamed directly from sensors or PCs via UART and recurrent on-chip connectivity, enabling simultaneous processing and learning from external stimuli and internal network dynamics-capabilities rarely available in existing FPGA SNN platforms. The system implements a Leaky Integrate-and-Fire (LIF) neuron model with current-based synapses and supports pair-based STDP learning on both feedforward and recurrent synapses. A lightweight Python interface enables interactive configuration, live monitoring, weight read-back, and experiment control. Importantly, NeuroCoreX is tightly integrated with the SuperNeuroMAT simulator, allowing SNN models to be transferred seamlessly from software to hardware for hardware-in-the-loop development. By combining real-time plasticity, flexible connectivity, and an open-source VHDL implementation, NeuroCoreX provides an extensible and accessible platform for neuromorphic research, algorithm-hardware co-design, and energy-efficient edge intelligence.

Gautam, Ashish [ORNL]↗
DOE OSTI2024

High-Fidelity Dataset Generation for Sensor Anomalies in Power Grids using Hardware-in-the-Loop Testbed

Sensor anomalies in power grids can have significant impacts on the operation of the grid due to the increased reliance of the grid operation on data-driven applications. However, there is a lack of datasets that accurately capture these anomalies as many of the anomalies go undetected using the current bad data detectors. High-fidelity labeled datasets are essential for developing robust applications that can detect and mitigate the impacts of anomalies. In this paper, we propose a hardware-in-the-loop testbed model that can emulate the grid behavior with high-fidelity. This testbed is used to inject anomalies at various levels in the grid architecture and generate labeled datasets. These high-fidelity datasets can be used for development and validation of data-driven applications for detection and mitigation of anomalies in grids and other cyber-physical systems.

Hyder, Burhan↗
NASA NTRS1978

Modeling of a latent fault detector in a digital system

Methods of modeling the detection time or latency period of a hardware fault in a digital system are proposed that explain how a computer detects faults in a computational mode. The objectives were to study how software reacts to a fault, to account for as many variables as possible affecting detection and to forecast a given program's detecting ability prior to computation. A series of experiments were conducted on a small emulated microprocessor with fault injection capability. Results indicate that the detecting capability of a program largely depends on the instruction subset used during computation and the frequency of its use and has little direct dependence on such variables as fault mode, number set, degree of branching and program length. A model is discussed which employs an analog with balls in an urn to explain the rate of which subsequent repetitions of an instruction or instruction set detect a given fault.

Nagel, P. M.↗
NASA NTRS2012

Shape and Color Features for Object Recognition Search

A bio-inspired shape feature of an object of interest emulates the integration of the saccadic eye movement and horizontal layer in vertebrate retina for object recognition search where a single object can be used one at a time. The optimal computational model for shape-extraction-based principal component analysis (PCA) was also developed to reduce processing time and enable the real-time adaptive system capability. A color feature of the object is employed as color segmentation to empower the shape feature recognition to solve the object recognition in the heterogeneous environment where a single technique - shape or color - may expose its difficulties. To enable the effective system, an adaptive architecture and autonomous mechanism were developed to recognize and adapt the shape and color feature of the moving object. The bio-inspired object recognition based on bio-inspired shape and color can be effective to recognize a person of interest in the heterogeneous environment where the single technique exposed its difficulties to perform effective recognition. Moreover, this work also demonstrates the mechanism and architecture of the autonomous adaptive system to enable the realistic system for the practical use in the future.

Duong, Tuan A.↗
NASA NTRS2024

An Extensible Perturbed Parameter Ensemble for the Community Atmosphere Model Version 6

This paper documents the methodology and preliminary results from a Perturbed Parameter Ensemble (PPE) technique, where multiple parameters are varied simultaneously and the parameter values are determined with Latin hypercube sampling. This is done with the Community Atmosphere Model version 6 (CAM6), the atmospheric component of the Community Earth System Model version 2 (CESM2). We apply the PPE method to CESM2-CAM6 to understand climate sensitivity to atmospheric physics parameters. The initial simulations vary 45 parameters in the microphysics, convection, turbulence and aerosol schemes with 263 ensemble members. These atmospheric parameters are typically the most uncertain in many climate models. Control simulations are analyzed and targeted simulations to understand climate forcing due to aerosols and fast climate feedbacks. The use of various emulators is explored in the multi- dimensional space mapping input parameters to output metrics. Parameter impacts on various model outputs, such as radiation, cloud and aerosol properties are evaluated. Machine learning is also used to probe optimal parameter values against observations. Our findings show that using PPE is a valuable tool for climate uncertainty analysis. Furthermore, by varying many parameters simultaneously, we find that many different combinations of parameter values can produce results consistent with observations, and thus careful analysis of tuning is important. The CESM2-CAM6 PPE is publicly available, and extensible to other configurations to address questions of other model processes in the atmosphere and other model components (e.g. coupling to the land surface).

Machine learning↗