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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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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Opportunities in full-stack design of low-overhead fault-tolerant quantum computation

Quantum error correction provides a route to realizing large-scale quantum computation but incurs substantial resource overheads. Here, in this work, we highlight recent advances that reduce these overheads by co-designing different levels of the computational stack, including algorithms, quantum-error-correction strategies and hardware architecture. We then discuss opportunities for further optimization such as leveraging flexible qubit connectivity and quantum low-density parity check codes. These strategies can bring useful quantum computation closer to reality as experiments advance in the coming years.

quantum information↗

DOE OSTI2017

Quantum Control of Spins in Diamond for Nanoscale Magnetic Sensing and Imaging

Our research activities during the grant period focused on the challenges of highly accurate and precise magnetometry and magnetic imaging using quantum spins inside diamond. Our work has resulted in 6 papers published in peer-reviewed journals, with two more currently under consideration by referees. We showed that through the use of novel phase estimation algorithms inspired by quantum information science we can carry out accurate and high dynamic range DC magnetometry as well as lock-in detection of oscillating (AC) magnetic fields. We investigated the geometric phase as a route to higher precision quantum information and magnetic sensing applications, and probed the experimental limits to the fidelity of such geometric phase gates. We also demonstrated that there is a spin dependent signal in the charge state flipping of the NV defect center in diamond, which could potentialy be useful for higher fidelity spin readout at room temperature. Some of these projects have now led to further investigation in our lab on multi-photon spectroscopy (manuscript in preparation), and plasmonic guiding of light in metal nanowires (manuscript available on arxiv). In addition, several invited talks were given by the PI, and conference presentations were given by the graduate students and postdocs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1989

Piloted simulation of a ground-based time-control concept for air traffic control

A joint simulation was carried out using a piloted simulator and an advanced-concept air traffic control simulation to study the acceptability and accuracy of the ground-based four-dimensional descent advisor (DA), an automation aid based on accurate models of aircraft performance and weather conditions. In the piloted simulation, airline crews executed controller-issued descent advisories along standard curved-path arrival routes and were able to achieve an arrival-time precision of plus or minus 20 s at the metering fix. An analysis of errors generated in turns resulted in a further enhancement of the DA algorithm.

Davis, Thomas J.↗

DOE OSTI2014

Efficient modeling of photonic crystals with local Hermite polynomials

Developing compact algorithms for accurate electrodynamic calculations with minimal computational cost is an active area of research given the increasing complexity in the design of electromagnetic composite structures such as photonic crystals, metamaterials, optical interconnects, and on-chip routing. We show that electric and magnetic (EM) fields can be calculated using scalar Hermite interpolation polynomials as the numerical basis functions without having to invoke edge-based vector finite elements to suppress spurious solutions or to satisfy boundary conditions. This approach offers several fundamental advantages as evidenced through band structure solutions for periodic systems and through waveguide analysis. Compared with reciprocal space (plane wave expansion) methods for periodic systems, advantages are shown in computational costs, the ability to capture spatial complexity in the dielectric distributions, the demonstration of numerical convergence with scaling, and variational eigenfunctions free of numerical artifacts that arise from mixed-order real space basis sets or the inherent aberrations from transforming reciprocal space solutions of finite expansions. The photonic band structure of a simple crystal is used as a benchmark comparison and the ability to capture the effects of spatially complex dielectric distributions is treated using a complex pattern with highly irregular features that would stress spatial transform limits. This general method is applicable to a broad class of physical systems, e.g., to semiconducting lasers which require simultaneous modeling of transitions in quantum wells or dots together with EM cavity calculations, to modeling plasmonic structures in the presence of EM field emissions, and to on-chip propagation within monolithic integrated circuits.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Design of a final approach spacing tool for TRACON air traffic control

This paper describes an automation tool that assists air traffic controllers in the Terminal Radar Approach Control (TRACON) Facilities in providing safe and efficient sequencing and spacing of arrival traffic. The automation tool, referred to as the Final Approach Spacing Tool (FAST), allows the controller to interactively choose various levels of automation and advisory information ranging from predicted time errors to speed and heading advisories for controlling time error. FAST also uses a timeline to display current scheduling and sequencing information for all aircraft in the TRACON airspace. FAST combines accurate predictive algorithms and state-of-the-art mouse and graphical interface technology to present advisory information to the controller. Furthermore, FAST exchanges various types of traffic information and communicates with automation tools being developed for the Air Route Traffic Control Center. Thus it is part of an integrated traffic management system for arrival traffic at major terminal areas.

Davis, Thomas J.↗

NASA NTRS2009

Analysis of Automated Aircraft Conflict Resolution and Weather Avoidance

This paper describes an analysis of using trajectory-based automation to resolve both aircraft and weather constraints for near-term air traffic management decision making. The auto resolution algorithm developed and tested at NASA-Ames to resolve aircraft to aircraft conflicts has been modified to mitigate convective weather constraints. Modifications include adding information about the size of a gap between weather constraints to the routing solution. Routes that traverse gaps that are smaller than a specific size are not used. An evaluation of the performance of the modified autoresolver to resolve both conflicts with aircraft and weather was performed. Integration with the Center-TRACON Traffic Management System was completed to evaluate the effect of weather routing on schedule delays.

Love, John F.↗

DOE OSTI2017

Ion Mobility Spectrometry - High Resolution LTQ-Orbitrap Mass Spectrometry for Analysis of Homemade Explosives

The detailed chemical characterization of homemade explosives (HMEs) and other chemicals that can mimic or mask the presence of explosives is important for understanding and improving the performance of commercial instrumentation used for explosive detection. To that end, an atmospheric-pressure drift tube ion mobility spectrometry (IMS) instrument has been successfully coupled to a commercial tandem mass spectrometry (MS) system. The tandem MS system is comprised of a linear ion trap and a high resolution Orbitrap analyzer. This IMS-MS combination allows extensive characterization of threat chemical compounds, including HMEs, and complex real-world background chemicals that can interfere with detection. Here, the composition of ion species originating from a specific HME, erythritol tetranitrate, has been elucidated using accurate mass measurements, isotopic ratios, and tandem MS. Gated IMS-MS and high-resolution MS have been used to identify minor impurities that can be indicative of the HME source and/or synthesis route. Comparison between data obtained on the IMS/MS system and on commercial stand-alone IMS instruments used as explosive trace detectors (ETDs) has also been performed. Such analysis allows better signature assignments of threat compounds, modified detection algorithms, and improved overall ETD performance. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Simulation of Heavy-Duty Vehicles in Platooning Scenarios

Connectivity and automation provide the potential to use information about the environment and future driving to minimize energy consumption. In order to achieve this goal, the designers of control strategies need to simulate a wide range of driving situations that can interact with other vehicles and the infrastructure to account for the specific powertrain characteristics of each automated vehicle. We present here a simulation framework called RoadRunner, which aims to facilitate the design of powertrain-aware eco-driving algorithms and a better understanding of the interactions between automation and powertrain technology. RoadRunner allows users to simulate both powertrain and longitudinal dynamics within a simulated environment. The user defines the scenario to be simulated by providing a route profile, intersection control types, number of vehicles, vehicle class, powertrain technology, connectivity, and automation level. RoadRunner then builds a Simulink diagram of the scenario, including the information flows between vehicles, and between vehicles and the road. After the simulation, the user can analyze the driving, component operations, and detailed energy consumption rates for each simulated vehicle. We present a case study on heavy-duty vehicles platooning. Using RoadRunner and detailed road data from digital maps, we quantify the impact of gap setting on fuel consumption, for a real-world route.

Kim, Namdoo↗

NASA NTRS2013

A Cockpit-Based Application for Traffic Aware Trajectory Optimization

The Traffic Aware Planner (TAP) is a cockpit-based advisory tool designed to be hosted on a Class 2 Electronic Flight Bag and developed to enable the concept of Traffic Aware Strategic Aircrew Requests (TASAR). This near-term concept provides pilots with optimized route changes that reduce fuel burn or flight time, avoids interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a trajectory change from air traffic control. TAP's internal architecture and algorithms are derived from the Autonomous Operations Planner, a flight-deck automation system developed by NASA to support research into aircraft self-separation. This paper reviews the architecture, functionality and operation of TAP.

TASAR↗

DOE OSTI2024

Agent-based modeling for multimodal transportation of CO 2 for carbon capture, utilization, and storage: CCUS-agent

Here, to understand the system-level interactions between the entities in Carbon Capture, Utilization, and Storage (CCUS), an agent-based foundational modeling tool, CCUS-Agent, is developed for a large-scale study of transportation flows and infrastructure in the United States. Key features of the tool include (i) modular design, (ii) multiple transportation modes, (iii) capabilities for extension, and (iv) testing against various system components and networks of small and large sizes. Five matching algorithms for CO 2 supply agents (e.g., powerplants and industrial facilities) and demand agents (e.g., storage and utilization sites) are explored: Most Profitable First Year (MPFY), Most Profitable All Years (MPAY), Shortest Total Distance First Year (SDFY), Shortest Total Distance All Years (SDAY), and Shortest distance to long-haul transport All Years (ACAY). Before matching, the supply agent, demand agent, and route must be available, and the connection must be profitable. A profitable connection means the supply agent portion of revenue from the 45Q tax credit must cover the supply agent costs and all transportation costs, while the demand agent revenue portion must cover all demand agent costs. A case study employing over 5500 supply and demand agents and multimodal CCUS transportation infrastructure in the contiguous United States is conducted. The results suggest that it is possible to capture over 9 billion tonnes (GT) of CO 2 from 2025 to 2043, which will increase significantly to 22 GT if the capture costs are reduced by 40 %. The MPFY and SDFY algorithms capture more CO 2 earlier in the time horizon, while the MPAY and SDAY algorithms capture more later in the time horizon.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Snapshot multispectral imaging using a diffractive optical network

Abstract Multispectral imaging has been used for numerous applications in e.g., environmental monitoring, aerospace, defense, and biomedicine. Here, we present a diffractive optical network-based multispectral imaging system trained using deep learning to create a virtual spectral filter array at the output image field-of-view. This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum, and at the same time, routes a pre-determined set of spectral channels onto an array of pixels at the output plane, converting a monochrome focal-plane array or image sensor into a multispectral imaging device without any spectral filters or image recovery algorithms. Furthermore, the spectral responsivity of this diffractive multispectral imager is not sensitive to input polarization states. Through numerical simulations, we present different diffractive network designs that achieve snapshot multispectral imaging with 4, 9 and 16 unique spectral bands within the visible spectrum, based on passive spatially-structured diffractive surfaces, with a compact design that axially spans ~72 λ m , where λ m is the mean wavelength of the spectral band of interest. Moreover, we experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network that creates at its output image plane a spatially repeating virtual spectral filter array with 2 × 2 = 4 unique bands at terahertz spectrum. Due to their compact form factor and computation-free, power-efficient and polarization-insensitive forward operation, diffractive multispectral imagers can be transformative for various imaging and sensing applications and be used at different parts of the electromagnetic spectrum where high-density and wide-area multispectral pixel arrays are not widely available.

36 MATERIALS SCIENCE↗

NASA NTRS1988

Design of automation tools for management of descent traffic

The design of an automated air traffic control system based on a hierarchy of advisory tools for controllers is described. Compatibility of the tools with the human controller, a key objective of the design, is achieved by a judicious selection of tasks to be automated and careful attention to the design of the controller system interface. The design comprises three interconnected subsystems referred to as the Traffic Management Advisor, the Descent Advisor, and the Final Approach Spacing Tool. Each of these subsystems provides a collection of tools for specific controller positions and tasks. This paper focuses primarily on the Descent Advisor which provides automation tools for managing descent traffic. The algorithms, automation modes, and graphical interfaces incorporated in the design are described. Information generated by the Descent Advisor tools is integrated into a plan view traffic display consisting of a high-resolution color monitor. Estimated arrival times of aircraft are presented graphically on a time line, which is also used interactively in combination with a mouse input device to select and schedule arrival times. Other graphical markers indicate the location of the fuel-optimum top-of-descent point and the predicted separation distances of aircraft at a designated time-control point. Computer generated advisories provide speed and descent clearances which the controller can issue to aircraft to help them arrive at the feeder gate at the scheduled times or with specified separation distances. Two types of horizontal guidance modes, selectable by the controller, provide markers for managing the horizontal flightpaths of aircraft under various conditions. The entire system consisting of descent advisor algorithm, a library of aircraft performance models, national airspace system data bases, and interactive display software has been implemented on a workstation made by Sun Microsystems, Inc. It is planned to use this configuration in operational evaluations at an en route center.

Erzberger, Heinz↗

NASA NTRSDate not supplied

Applying the Cognitive Space Gateway to Swarm Topologies

NASA’s future vision for interplanetary networking includes a lunar network, Cube Satellite (CubeSat) constellations, and deep space robotic missions, comprising what could be viewed as a network of networks. Delay-tolerant networking (DTN) architecture and protocols provide a standard network layer among these varying scenarios and mitigate many challenges of the space environment, such as long delays, unplanned service interruptions, and asymmetric links. The Cognitive Space Gateway (CSG) is a routing method in a DTN architecture that uses spiking neural networks as the learning element to optimize outing decisions in a complex environment. This work aims to further develop cognitive networking technologies in several critical areas, including DTN, the CSG algorithm, SmallSat swarm topologies, and cloud services. The CSG algorithm is tested in a realistic scenario in which the emulated network topology is based on a SmallSat swarm. The emulation environment will be built upon a commercial cloud service, such as Amazon Web Services (AWS) Elastic Compute Cloud. This work investigates the ability of such a platform to enable a flexible, lower maintenance approach to creating a multihop network outside of a physical laboratory. The cloud platform will provide a secure environment allowing for collaboration among government and academic entities.

Ricardo Lent↗

DOE OSTI2022

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Multiperiod Distribution System Restoration With Routing Repair Crews, Mobile Electric Vehicles, and Soft-Open-Point Networked Microgrids

This paper proposes a distribution system restoration model which is in response to multiple outages caused by natural disasters. The proposed restoration model includes the coordination of routing repair crews (RRCs), mobile batterycarried vehicles (MBCVs), and networked microgrids (NMGs) formed by soft open points (SOPs). The travel and repair time constraints are modeled for each RRC; travel path and charging strategy are modeled for each MBCV; and the network reconfiguration is developed considering the optimal operation of SOP-based NMGs. Furthermore, the proposed model is presented as a mixedinteger linear program which is solved by an auxiliary induce function based algorithm to reduce the computational complexity. The modified IEEE 33-bus and 69-bus distribution systems are tested with multiple outages. The presented results demonstrate the effectiveness of the proposed model

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Orchestrated trios: compiling for efficient communication in Quantum programs with 3-Qubit gates

Current quantum computers are especially error prone and require high levels of optimization to reduce operation counts and maximize the probability the compiled program will succeed. These computers only support operations decomposed into one- and two-qubit gates and only two-qubit gates between physically connected pairs of qubits. Typical compilers first decompose operations, then route data to connected qubits. We propose a new compiler structure, Orchestrated Trios, that first decomposes to the three-qubit Toffoli, routes the inputs of the higher-level Toffoli operations to groups of nearby qubits, then finishes decomposition to hardware-supported gates. This significantly reduces communication overhead by giving the routing pass access to the higher-level structure of the circuit instead of discarding it. A second benefit is the ability to now select an architecture-tuned Toffoli decomposition such as the 8-CNOT Toffoli for the specific hardware qubits now known after the routing pass. Furthermore, we perform real experiments on IBM Johannesburg showing an average 35% decrease in two-qubit gate count and 23% increase in success rate of a single Toffoli over Qiskit. We additionally compile many near-term benchmark algorithms showing an average 344% increase in (or 4.44x) simulated success rate on the Johannesburg architecture and compare with other architecture types.

compiler↗

DOE OSTI2018

Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand

This paper proposes a novel method to co-optimize the distribution system operation and repair crew routing for outage restoration after extreme weather events. A two-stage stochastic mixed integer linear program is developed. The first stage is to dispatch the repair crews to the damaged components. The second stage is distribution system restoration using distributed generators, and reconfiguration. We consider demand uncertainty in terms of a truncated normal forecast error distribution, and model the uncertainty of the repair time using a lognormal distribution. A new decomposition approach, combined with the progressive hedging algorithm, is developed for solving large-scale outage management problems in an effective and timely manner. Furthermore, the proposed method is validated on modified IEEE 34- and 8500-bus distribution test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2015

A Stochastic Scheduler for Integrated Arrival, Departure and Surface Operations in Los Angeles

In terminal airspace, integrating arrivals, departures, and surface operations with competing resources provides the potential of improving operational efficiency by removing barriers between different operations. This work develops a centralized stochastic scheduler for operations in a terminal area including airborne and surface operations using Non-dominated sorting genetic algorithm and Monte Carlo simulations. The scheduler handles completing resources between different flows, such as runway allocations, runway crossing, departure fixes, and other interaction way points between arrivals and departures. Meanwhile, the scheduler also takes time-varied uncertainties into account when optimizing schedules. The scheduler is run sequentially to identify the best and robust schedule for the next planning window. Resulting schedules decide the routes, speed or delays, and runway assignments with separation constraints at mergingdiverging waypoints in the air and crossing and separations on runways. The Los Angels terminal area was used as an example. The implementation of this stochastic scheduler for integrated arrival, departure and surface operations is completed. And several preliminary runs are finished for over 1,200 flights in LAX in a typical day. Sensitivity studies on various planning window sizes are presented, which shows that trade-off exits between planning window size and achievable minimum delay. Preliminary results on runway usage are also presented in this abstract. Because arrivals on the outer runways have to be followed by crossings on the inner runways, algorithmic runway allocation prefers inner runways for arrivals and outer runways for departures. More results will be presented in the final paper. And current terminal arrival and departure procedures based on first-come-first-serve procedure will also be set up and used as a baseline for comparison.

integrated scheduler↗