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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 523 records · Page 29

Gradient-Based Aeroservoelastic Optimization with Static Output Feedback

Static output feedback considers an optimal low-order feedback matrix which directly connects the sensors to the control inputs. This work demonstrates the numerical techniques needed to compute the analytical gradient of the optimal feedback matrix with respect to design variables, which may then be used for gradient-based optimization. The derivatives are demonstrated for aeroservoelastic optimization under a series of closed- loop gust load alleviation constraints, considering a continuous stochastic gust load applied to a transport vehicle configuration, among other design constraints such as utter and maneuver loads. The optimal trade-o s between passive load alleviation and active load alleviation for static output feedback are compared with those from full-state feedback, which may be considered an upper-bound for effective sensor-based control.

Stanford, Bret K.↗

Optimal Multi-Agent Search and Rescue Using Potential Field Theory

This paper presents an algorithm for efficient search and rescue using a multi-agent system of vehicles. The algorithm uses an artificial potential field combined with a time-varying reward function for visiting various points within the search area. The reward function is used to weight the attractiveness of these points in the potential field, and collision avoidance terms are used to repel vehicles from each other, which has the additional effect of reducing duplication of searching efforts. The algorithm generates velocity commands in real-time based on communication with the other vehicles. This framework allows vehicles to react in a dynamic environment, which is a significant advantage to simply following a-priori defined trajectories. Simulation results are presented to demonstrate the ability of the algorithm to cover the search area effectively. The algorithm is also compared to an exhaustive lawn-mower search pattern. This comparison is done via a Monte Carlo simulation with randomized target initial conditions and trajectories. The time to find the target improved by 16 and 30% in the mean and median, respectively. Additionally, this paper presents a method for analyzing the upper bound for time to find a target under the potential field guidance algorithm assuming a radially expanding search area.

John R Cooper↗

Planning for Compilation of a Quantum Algorithm for Graph Coloring

Recently, the problem of compiling general quantum algorithms for implementation on near-term quantum processors has been introduced to the AI community. Previous work demonstrated that temporal planning is an attractive approach for part of this compilation task, specifically, the routing of circuits that implement the Quantum Alternating Operator Ansatz (QAOA) applied to theMaxCut problem on a quantum processor architecture. In this paper, we extend the earlier work to route circuits that implement QAOAfor Graph Coloring problems. QAOA for coloring requires execution of more, and more complex, operations on the chip, which makes routing a more challenging problem. We evaluate the approach on state-of-the-art hardware architectures from leading quantum computing companies. Additionally, we investigate applying the planning approach to qubit initialization as well as routing. Our empirical evaluation shows that temporal planning compares well to reasonable analytic upper bounds [20], and that solving qubit initialization with a classical planner generally helps temporal planners in finding shorter-makespan compilations for QAOA for Graph Coloring.These advances suggest that temporal planning can be an effective approach for more complex quantum computing algorithms and architectures.

Minh Do↗

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system. The industry has experienced a steady decrease in fatalities over the years. This can be contributed to both improved flight critical systems with redundant hardware and software protections as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main practice for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave with the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety creating labels for the data requires huge amount of efforts and is largely expensive. As a result, in this article, we develop a Convolutional Variational Auto-Encoder (CVAE), an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach (as an upper bound) as well as an supervised clustering based on K-Means (as a lower bound) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Milad Memarzadeh↗

Dual Anion-Cation Crosslinked Poly(ionic liquid) Composite Membranes for Enhanced CO2 Separation

Herein, we propose a strategy of developing novel dual anionic-cationic crosslinked poly(IL)-IL composite membranes via a photopolymerization method for enhanced CO2 separations. These are the first examples of dually photopolymerized anionic-cationic poly(IL)-IL composite systems, in which the backbones of poly(IL)s feature both pendant anions and cations without any mobile counterions unlike poly(IL) reported so far in the literature. A new type of dual photopolymerizable anionic-cationic IL (DIL) monomer having methacrylate functional group tethered with highly delocalized sulfonimide anion (–SO2–N(-)–SO2–C7H7) and a vinylimidazolium counterion ([C4(vim)](+)) was successfully synthesized and photopolymerized with four distinct amounts of free IL with a structurally analogous cation ([C4(mim)][Tf2N]) and 20 wt% PEGDA crosslinker, offering novel composite matrices. Further, the structure-property relationships as well as gas separation behaviors of the four newly developed dual anioniccationic poly(IL)-IL composite membranes were extensively characterized by FT-IR, DSC, and XRD. All of the newly developed dual anionic-cationic poly(IL)-IL composite membranes displayed outstanding permselectivites for CO2/CH4, CO2/N2, and CO2/H2 gas pairs together with reasonable CO2 permeabilities. As a result, all the dual anionic-cationic poly(IL)-IL composite membranes outperformed the common poly(IL)-IL systems in the upper bound limit plots with best CO2 permeability of 40 barrer and CO2/CH4 permselectivity of 85. This study may pave a new platform to explore countless potential poly(IL)-IL composites for selective separation of CO2 from flue gas, natural gas, and syngas streams.

Irshad Kammakakam↗

Improvements in Ionic Liquid Technology for Carbon Dioxide Removal Applications

Carbon dioxide removal from cabin air continues to be of vital importance for future space missions. Current and proposed approaches have employed solid sorbents, hollow fiber membrane separators, and direct liquid sorbent contactors. Recent developments in ionic liquids have potential to improve performance in all three of these technologies. Efficient encapsulation of ionic liquids by polymeric shell can enable their use in a solid sorbent-like configuration without significant integration intervention to the current space technology. Poly(ionic liquid)-ionic liquid membranes have the potential to cross over the Robeson selectivity-permeability upper bound, and thereby outperform traditional membranes used in hollow fibers. Advances in ionic liquid chemistry enables performance improvements in liquid sorbent contactors owing to the tunable gravimetric CO2 capacity, reaction enthalpy and liquid viscosity. This paper will describe recent work in each of these areas.

Ionic Liquid,Carbon Dioxide,Air Revitalization↗

Returning Samples from Enceladus for Life Detection

Evidence suggests that Saturn’s icy moon Enceladus has a subsurface ocean that sources plumes of water vapor and ice vented to space from its south pole. In situ analyses of this material by the Cassini spacecraft have shown that the ocean contains key ingredients for life (elements H, C, N, O and possibly S; simple and complex organic compounds; chemical disequilibria at water-rock interfaces; clement temperature, pressure, and pH). The Cassini discoveries make Enceladus’ interior a prime locale for life detection beyond Earth. Scant material exchange with the inner Solar System makes it likely that such life would have emerged independently of life on Earth. Thus, its discovery would illuminate life’s universal characteristics. The alternative result of an upper bound on a detectable biosphere in an otherwise habitable environment would likewise considerably advance our understanding of the prevalence of life beyond Earth. Here we outline the rationale for returning vented ocean samples, accessible from Enceladus’ surface or low altitudes, to Earth for life detection. Returning samples allows analyses using laboratory instruments that cannot be flown, with decades or more to adapt and repeat analyses. We describe an example set of measurements to estimate the amount of sample to be returned and discuss possible mission architectures and collection approaches. We then turn to the challenges of preserving sample integrity and implementing planetary protection policy. We conclude by placing such a mission in the broader context of Solar System exploration.

Enceladus↗

Climate and air quality impacts due to mitigation of non-methane near-term climate forcers

It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015–2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry–climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with “weak” (SSP3-7.0) versus “strong” (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2.5) and ozone (O3) decrease by −2.2±0.32 µg m−3 and −4.6±0.88 ppb, respectively (changes quoted here are for the entire 2015–2055 time period; uncertainty represents the 95 % confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0.25±0.12 K and 0.03±0.012 mm d−1, respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0.66±0.20 K and 0.03±0.02 mm d−1), south Asia (0.47±0.16 K and 0.17±0.09 mm d−1), and east Asia (0.46±0.20 K and 0.15±0.06 mm d−1). Relatively large warming and wetting of the Arctic also occur at 0.59±0.36 K and 0.04±0.02 mm d−1, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals.

Climate↗

Monocular Ranging for Small Unmanned Aerial Systems in the Far-Field

Recent proliferation of small Unmanned Aerial Systems (sUAS) applications requires onboard collision avoidance systems to mitigate the risk of collision with non-cooperative aircraft and manned aircraft, which may not see sUAS in time to perform an avoidance maneuver. An attractive avenue for onboard collision avoidance is the utilization of machine vision cameras due to their low size, weight and power (SWaP) requirements. In this paper, we characterize the range performance of a machine vision system developed in-house and mounted onto an sUAS. The technique was designed to estimate the performance of a sense-and-avoid system to ensure that the sensing components meet the well-clear requirements for the chosen platform and avoidance strategy. Experimental flight-test data was acquired from test-flights flown along multiple collision geometries for two intruders: a general Aviation (GA) aircraft and a fixed-wing sUAS. The ownship and both intruders were instrumented with inertial navigation systems (INS) recording position and attitude information. The range at first detection, 𝑹𝟎, was extracted from in-flight imagery of head-on collision course geometry synchronized with INS data from both aircraft and ground-truth values extracted from the raw imagery. This initial detection distance, 𝑹𝟎, scales with atmospheric attenuation. Therefore, under clear sky conditions, the derived 𝑹𝟎 value represents the upper bound on the detection range achievable by the test configuration of the detector. Results indicate that the maximum initial detection distance for a 4k resolution action camera fitted with a 41º Field of View (FOV) lens is 2.763 ± 0.037 km for a GA aircraft and 0.881 ± 0.061 km for a fixed-wing sUAS, respectively. The in results this study suggest that a vision-based detect and track system may be analyzed using the sensor characterization and contextualized within aircraft well-clear volumes.

Chester V. Dolph↗

Linear Algorithms for Worst Case Identification in H infinity with Applications to Flexible Structures

This paper is concerned with linear algorithms for identification in which have been studied in [9]. It is shown that the two different linear algorithms in [9] can be unified into a single one which can be further extended to nonuniformly spaced frequency response samples with exponential convergence for the noise free case. Improved upper bounds for the corresponding identification errors are derived. Applications to the identification of lightly damped systems such as flexible structures are also considered.

linear↗

Irradiation with molecular hydrogen as an accelerated total dose hardness assurance test method for bipolar linear circuits

High dose rate irradiation with hydrogen stress is proposed as an accelerated total dose test method for bipolar linear circuits. The method is validated across process and circuit technologies with five parts that are commonly used in space: a comparator (LM193 from National Semi-conductor), a voltage regulator (HSYE-117 RH from Intersil), a voltage reference (LT1019 from Linear Technology), a JFET input op amp (OP42 from Analog Devices) and a temperature transducer (AD590 from Analog Devices). The testing technique could rapidly establish an upper bound to the low dose rate response of parts in space and help with the part selection process in the design phase of a mission. The technology dependence and the viability of this technique are qualitatively explored using a physical model describing the dose rate response and the effect of hydrogen in bipolar technologies. The model uses four core processes: 1) space charge effects, 2) free electron/hole pair recombination, hole-hydrogen defect reactions in the oxides and 4) proton depassivation of dangling bonds at the Si/SiO2 interface. Radiation hardness assurance implications are discussed.

Pease, Ron↗

Interval Predictor Models for Robust System Identification

This paper proposes a framework for the identification and uncertainty quantification of plant models according to multivariable data. The only restriction imposed upon such models is for their outputs to depend continuously on their parameters. An Interval Predictor Model (IPM) prescribes the parameters of a computational model as a path-connected set thereby making each predicted output an interval-valued function of its inputs. The formulation proposed seeks the parameter set for which the predicted outputs tightly enclose the data. This set, which is modeled as a semi-algebraic set of low-degree polynomials, enables the characterization of possibly strong parameter dependencies commonly found in practice. This uncertainty characterization makes the resulting plant model amenable to robust control approaches using polynomial optimization. Furthermore, we use non-convex scenario theory to assess the reliability of the resulting IPM. This assessment yields a distribution-free upper bound on the probability that future data will fall outside the predicted intervals.

interval↗

The SUrvey for Pulsars and Extragalactic Radio Bursts - IV. Discovery and polarimetry of a 12.1-s radio pulsar

We report the discovery of PSR J2251−3711, a radio pulsar with a spin period of 12.1 s, the second longest currently known. Its timing parameters imply a characteristic age of 15 Myr, a surface magnetic field of 1.3 × 10^(13) G, and a spin-down luminosity of 2.9 × 10^(29) erg/s. Its dispersion measure of 12.12(1) pc/cu. cm leads to distance estimates of 0.5 and 1.3 kpc according to the NE2001 and YMW16 Galactic free electron density models, respectively. Some of its single pulses show an uninterrupted 180-deg sweep of the phase-resolved polarization position angle, with an S-shape reminiscent of the rotating vector model prediction. However, the fact that this sweep occurs at different phases from one pulse to another is remarkable and without straightforward explanation. Although PSR J2251−3711 lies in the region of the P − P˙ parameter space occupied by the X-ray isolated neutron stars (XINS), there is no evidence for an X-ray counterpart in our Swift XRT observation; this places a 99 per cent-confidence upper bound on its unabsorbed bolometric thermal luminosity of 1.1 × 10^(31) (d/1 kpc)^2 erg/s for an assumed temperature of 85 eV, where d is the distance to the pulsar. Further observations are needed to determine whether it is a rotation-powered pulsar with a true age of at least several Myr, or a much younger object such as an XINS or a recently cooled magnetar. Extreme specimens like PSR J2251−3711 help bridge populations in the so-called neutron star zoo in an attempt to understand their origins and evolution.

V Morello↗

Dynamic Stability And Adaptive Control of Networked Evolving Formations with Weak Nonlinearities

The dynamic stability of formation geometry is vital to the design of large scale multiagent systems. In this paper, we probe into the structure of the formation system matrix using the Laplacian of a digraph to develop several fundamental theoretical results on the stability of formation geometry. Our key-results include the integration of the graph Laplacian into linear and weak-nonlinear relative dynamics, the development of several new coordinate transformations that expose the influence of the graph Laplacian matrix on the control laws of the agents, and the use of direct adaptive control as stability restoring devices. We also develop two fundamental results that provide upper bounds for stable formation evolution under nonlinear perturbations of agent dynamics. Finally, we use an illustrative example to demonstrate our theoretical findings.

Gehlot, Vinod P.↗

Monitoring Airspace Complexity and Determining Contributing Factors

The national airspace has evolved over many years to accommodate increased traffic demand while simultaneously maintaining air travel as one of the safest forms of transportation. One of the reasons for this success is the ability of the air traffic control system and the operators to adapt and accommodate to situations that routinely disrupt normal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators’ ability to control. These factors can lead to states where automation is unable to properly handle these issues, and therefore air traffic controllers and pilots have to intervene — ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions, complexity increases. This is because, under these conditions humans are required to make tactical decisions in response to external factors. This results in a departure from the original strategic plan where operations would be more efficiently managed. Human operators manage airspace complexity under rigid regulations but in a constantly changing environment. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. Some prior studies devised airspace complexity metrics in commercial aviation and related these metrics to controller workload. The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic — including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to ours that identifies such contributing factors or precursor patterns.

Precursor↗

Galactic origin of relativistic bosons and XENON1T excess

We entertain the exotic possibility that dark matter (DM) decays or annihilations taking place in our galaxy may produce a flux of relativistic very weakly-coupled bosons, axions or dark photons. We show that there exist several upper bounds for this flux on Earth assuming generic minimal requirements for DM, such as a lifetime longer than the age of the Universe or an annihilation rate that leaves unaffected the background evolution during matter domination. These bounds do not depend on the identity or the couplings of the bosons. We then show that this new flux cannot be large enough to explain the recent XENON1T excess, while assuming that the bosons’ couplings to the Standard Model are consistent with all current experimental and observational constraints. We also discuss a possible caveat to these bounds and a route to explain the excess.

Jatan Buch↗

Using Gaia Data 2 to Constrain Local Dark Matter Density and Thin Dark Disk

We use stellar kinematics from the latest Gaia data release (DR2) to measure the local dark matter (DM) density ρDM in a heliocentric cylinder of radius R = 150 pc and half-height z = 200 pc. We also explore the prospect of using our analysis to estimate the DM density in local substructure by setting constraints on the surface density and scale height of a thin dark disk aligned with the baryonic disk and formed due to dissipative dark matter self-interactions. Performing the statistical analysis within a Bayesian framework for three types of tracers, we obtain ρDM = 0.016 ± 0.010 Mꙩ/p c 3 for A stars; early G stars give a similar result, while F stars yield a significantly higher value. For a thin dark disk, A stars set the strongest constraint: excluding surface densities (5–12) Mꙩ/pc 2 for scale heights below 100 pc with 95% confidence. The upper bound of this constraint implies . 1% of the Milky Way DM mass is present in a dissipative dark sector. Comparing our results with those derived using Tycho-Gaia Astrometric Solution (TGAS) data, we find that the uncertainty in our measurements of the local DM content is dominated by systematic errors that arise from assumptions of our dynamical analysis in the low z region. Furthermore, there will only be a marginal reduction in these uncertainties with more data in the Gaia era. We comment on the robustness of our method and discuss potential improvements for future work.

dark matter theory↗