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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 505 records · Page 28

Active Flow Control Stator With Coanda Surface

Active Flow Control increases the permissible aerodynamic loading. Curved surface near the trailing edge ("Coanda surface"): a) increases turning -> higher pressure ratio. b) controls boundary layer separation -> increased surge margin. Objective: Reduce the number of vanes or compressor stages. Constraints: 1. In a real compressor, the vane must still function entirely without blowing. 2. Maintain the flow exit angle of the reference stator despite the resulting increase in stator loading.

Guendogdu↗

A Formally-Verified Decision Procedure for Univariate Polynomial Computation Based on Sturm's Theorem

Sturm's Theorem is a well-known result in real algebraic geometry that provides a function that computes the number of roots of a univariate polynomial in a semiopen interval. This paper presents a formalization of this theorem in the PVS theorem prover, as well as a decision procedure that checks whether a polynomial is always positive, nonnegative, nonzero, negative, or nonpositive on any input interval. The soundness and completeness of the decision procedure is proven in PVS. The procedure and its correctness properties enable the implementation of a PVS strategy for automatically proving existential and universal univariate polynomial inequalities. Since the decision procedure is formally verified in PVS, the soundness of the strategy depends solely on the internal logic of PVS rather than on an external oracle. The procedure itself uses a combination of Sturm's Theorem, an interval bisection procedure, and the fact that a polynomial with exactly one root in a bounded interval is always nonnegative on that interval if and only if it is nonnegative at both endpoints.

Narkawicz, Anthony J.↗

P-ACTIVE Project Report

The Phase change material-based actively-tunable filter (P-ACTIVE, Dr. Hyun Jung Kim, the Principal Investigator / PI) project is a NASA Langley Research Center (LaRC)-led research endeavor that began as a NASA CIF (Center Innovation Fund) project in 2019. The goal of P-ACTIVE is to develop all-solid-state tunable optical filters that can serve as low-Size, Weight, and Power (SWaP) replacements to the ubiquitous filter wheel technology current in use, and serve as a starting point for completely new optical component technologies. By using materials commonly used in electronic memory devices, namely chalcogenide phase-change materials (PCMs), in conjunction with nanostructured surfaces with exotic, tailored optical responses (“metasurfaces”), the P-ACTIVE filters are able to tune their optical transmission/reflection behavior in real-time. Because of this new functionality, P-ACTIVE filters are highlighted for NASA science and space programs such as next generation Lidar, landing system (SLS) thermal monitoring, thermal imaging, imaging spectroscopy, and disaster monitoring (e.g., volcanic eruption observations from SmallSats). This document intends to serve as a compendium of the P-ACTIVE project. We begin by describing the project from background science and assume no prior knowledge of the subject. We then address experimental and theoretical results of P-ACTIVE device performance, as well as recent results obtained from the MISSE-14 mission related to space qualification of P-ACTIVE devices and constituent materials. We conclude with a prospective view of the P-ACTIVE technology, and discuss the potential for these filters and other similar metasurface devices to serve NASA’s mission.

metamaterial↗

Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning.

This paper describes an efficient reverse-mode differentiation algorithm for contraction operations of tensor networks that may have arbitrary and unconventional network topologies. The approach leverages the tensor contraction tree of Evenbly and Pfeifer (2014), which provides an instruction set for the contraction sequence of a network. We show that this tree can be efficiently leveraged for differentiation of a full tensor network contraction using a recursive scheme that exploits (1) the bilinear property of contraction and (2) the property that trees have single path from root to leaves. While differentiation of tensor-tensor contraction is already possible in most automatic differentiation packages, we show that exploiting these two additional properties in the specific context of contraction sequences can improve efficiency. Following a description of the algorithm and computational complexity analysis, we investigate its utility for gradient-based supervised learning for low-rank function recovery and for fitting real-world unstructured datasets. We demonstrate improved performance over alternating least-squares optimization approaches and the capability to handle heterogeneous and arbitrary tensor network formats. When compared to alternating minimization algorithms, we find that the gradient-based approach requires a smaller oversampling ratio (number of samples compared to number model parameters) for recovery. This increased efficiency extends to fitting unstructured data of varying dimensionality and when employing a variety of tensor network formats. Here, we show improved learning using the hierarchical Tucker method over the tensor-train in high-dimensional settings on a number of benchmark problems.

97 MATHEMATICS AND COMPUTING↗

Efficient generalized boundary detection

Fast, efficient, and robust compression-based methods for detecting boundaries in arbitrary datasets, including sequences (1D datasets), are desired. The methods, each employing three simple algorithms, approximate the information distance between two adjacent sliding windows within a dataset. One of the algorithms calculates an initial ordered list of subsequences; while a second algorithm updates the ordered list of subsequences by dropping a first entry and appending a last entry rather than calculating completely new ordered lists with each iteration. Large values in the distance metric are indicative of boundary locations. A smoothed z-score or a wavelet-based algorithm may then be used to locate peaks in the distance metric, thereby identifying boundary locations. An adaptive version of the method employs a collection of window sizes and corresponding weighting functions, making it more amenable to real datasets with unknown, complex, and changing structures.

Ting, Christina↗

The Association Between Baseline Hepatic or Renal Function and Clinical Outcomes for Patients With Non–Small Cell Lung Cancer Treated With a PD –1/PD– L1 Blocking Antibody Using Real–World and Trial Data

Clinical trials have demonstrated the benefit of PD-1/PD-L1 blocking antibodies for the treatment of patients with advanced non-small cell lung cancer (NSCLC) in defined patient populations that often exclude patients with moderate or severe hepatic or renal impairment. We assessed the association between overall survival (OS) and baseline organ function in patients with advanced NSCLC treated with PD-1/PD-L1 blocking antibodies in real-world data (RWD; patient-level data from electronic health records) and pooled clinical trial data submitted to the US Food and Drug Administration (FDA). The Kaplan–Meier estimator was used to estimate OS in different subgroups based on organ function. Unadjusted and adjusted Cox proportional hazards models were used to estimate the association between OS and organ function. In this hypothesis-generating study, baseline renal impairment did not appear to be associated with OS, while patients with baseline liver impairment had shorter OS. RWD provided information on a broader range of renal and hepatic function than was evaluated in clinical trials and hold promise to complement trial data in better understanding populations not represented in clinical trials.

60 APPLIED LIFE SCIENCES↗

GPU acceleration of local and semilocal density functional calculations in the SPARC electronic structure code

We present a Graphics Processing Unit (GPU)-accelerated version of the real-space SPARC electronic structure code for performing Kohn–Sham density functional theory calculations within the local density and generalized gradient approximations. In particular, we develop a modular math-kernel based implementation for NVIDIA architectures wherein the computationally expensive operations are carried out on the GPUs, with the remainder of the workload retained on the central processing units (CPUs). Here, using representative bulk and slab examples, we show that relative to CPU-only execution, GPUs enable speedups of up to 6× and 60× in node and core hours, respectively, bringing time to solution down to less than 30 s for a metallic system with over 14 000 electrons and enabling significant reductions in computational resources required for a given wall time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The use of UNIX in a real-time environment

This paper describes a project to evaluate the feasibility of using commercial off-the-shelf hardware and the UNIX operating system, to implement a real-time control and monitor system. A functional subset of the Checkout, Control and Monitor System was chosen as the test bed for the project. The project consists of three separate architecture implementations: a local area bus network, a star network, and a central host. The motivation for this project stemmed from the need to find a way to implement real-time systems, without the cost burden of developing and maintaining custom hardware and unique software. This has always been accepted as the only option because of the need to optimize the implementation for performance. However, with the cost/performance of today's hardware, the inefficiencies of high-level languages and portable operating systems can be effectively overcome.

Luken, R. D.↗

Local performance optimization for a class of redundant eight-degree-of-freedom manipulators

Local performance optimization for joint limit avoidance and manipulability maximization (singularity avoidance) is obtained by using the Jacobian matrix pseudoinverse and by projecting the gradient of an objective function into the Jacobian null space. Real-time redundancy optimization control is achieved for an eight-joint redundant manipulator having a three-axis spherical shoulder, a single elbow joint, and a four-axis spherical wrist. Symbolic solutions are used for both full-Jacobian and wrist-partitioned pseudoinverses, partitioned null-space projection matrices, and all objective function gradients. A kinematic limitation of this class of manipulators and the limitation's effect on redundancy resolution are discussed. Results obtained with graphical simulation are presented to demonstrate the effectiveness of local redundant manipulator performance optimization. Actual hardware experiments performed to verify the simulated results are also discussed. A major result is that the partitioned solution is desirable because of low computation requirements. The partitioned solution is suboptimal compared with the full solution because translational and rotational terms are optimized separately; however, the results show that the difference is not significant. Singularity analysis reveals that no algorithmic singularities exist for the partitioned solution. The partitioned and full solutions share the same physical manipulator singular conditions. When compared with the full solution, the partitioned solution is shown to be ill-conditioned in smaller neighborhoods of the shared singularities.

Williams, Robert L., II↗

Are grid cells used for navigation? On local metrics, subjective spaces, and black holes

The symmetric, lattice-like spatial pattern of grid-cell activity is thought to provide a neuronal global metric for space. This view is compatible with grid cells recorded in empty boxes but inconsistent with data from more naturalistic settings. Here, we review evidence arguing against the global-metric notion, including the distortion and disintegration of the grid pattern in complex and three-dimensional environments. We argue that deviations from lattice symmetry are key for understanding grid-cell function. We propose three possible functions for grid cells, which treat real-world grid distortions as a feature rather than a bug. First, grid cells may constitute a local metric for proximal space rather than a global metric for all space. Second, grid cells could form a metric for subjective action-relevant space rather than physical space. Third, distortions may represent salient locations. Finally, we discuss mechanisms that can underlie these functions. These ideas may transform our thinking about grid cells.

59 BASIC BIOLOGICAL SCIENCES↗

All-electron, density-functional-based method for angle-resolved tunneling ionization in the adiabatic regime

Here we develop and test a method that integrates many-electron weak-field asymptotic theory (ME-WFAT) [O. I. Tolstikhin, L. B. Madsen, and T. Morishita, Phys. Rev. A 89, 013421 (2014)] in the integral representation (IR) into the density-functional-theory (DFT) framework. In particular, we present modifications of the integral formula in the IR ME-WFAT to incorporate the potential terms unique to DFT. By solving an adiabatic rate equation for the angle-resolved ionization yield in our DFT-based ME-WFAT method, we show that the results are in excellent agreement with those of real-time time-dependent density-functional-theory (TDDFT) simulations for NO, OCS, C⁢H 3 ⁢Br, and C⁢H 3 ⁢Cl interacting with one- and two-color laser fields with a fundamental wavelength of 800 nm. This agreement is significant because the WFAT calculations take only a small fraction of the time of full TDDFT calculations. These results suggest that in the wavelength region commonly used in strong-field experiments (800 nm and longer), our DFT-based WFAT treatment can be used to rapidly screen for the ionization properties of a large number of molecules as a function of alignment or orientation between the molecule and the strong field.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

OpenSatKit Enables Quick Startup for CubeSat Missions

The software required to develop, integrate, and operate a spacecraft is substantial regardless of whether its a large or small satellite. Even getting started can be a monumental task. To solve this problem, NASAs Core Flight System (cFS), NASA's 42 spacecraft dynamics simulator, and Ball Aerospaces COSMOS ground system have been integrated together into a kit called OpenSatKit that provides a complete and open source software solution for starting a new satellite mission. Users can have a working system with flight software, dynamics simulation, and a ground command and control system up and running within hours.Every satellite mission requires three primary categories of software to function. The first is Flight Software (FSW) which provides the onboard control of the satellites and its payload(s). NASA's cFS provides a great platform for developing this software. Second, while developing a satellite on earth, it is necessary to simulate the satellites orbit, attitude, and actuators, to ensure that the systems that control these aspects will work correctly in the real environment. NASAs 42 simulator provides these functionalities. Finally, the ground has to be able to communicate with the satellite, monitor its performance and health, and display its data. Additionally, test scripts have to be written to verify the system on the ground. Ball Aerospace's COSMOS command and control system provides this functionality. Once the OpenSatKit is up and running, the next step is to customize the platform and get it running on the end target. Starting from a fully working system makes porting the cFS from Linux to a users platform much easier. An example Raspberry Pi target is included in the kit so users can gain experience working with a low cost hardware target. All users can benefit from OpenSatKit but the greatest impact and benefits will be to SmallSat missions with constrained budgets and small software teams. This paper describes OpenSatKits system design, the steps necessary to run the system to target the Raspberry Pi, and future plans. OpenSatKit is a free fully functional spacecraft software system that we hope will greatly benefit the SmallSat community.

Software↗

Logarithmic enhancements in conformal perturbation theory and their real time interpretation

We study various corrections of correlation functions to leading order in conformal perturbation theory, both on the cylinder and on the plane. Many problems on the cylinder are mathematically equivalent to those in the plane if we give the perturbations a position dependent scaling profile. The integrals to be done are then similar to those in the study of correlation functions with one additional insertion at the center of the profile. We will be primarily interested in the divergence structure of these corrections when computed in dimensional regularization. In particular, we show that the logarithmic divergences (enhancements) that show up in the plane under these circumstances can be understood in terms of resonant behavior in time dependent perturbation theory, for a transition between states that is induced by an oscillatory perturbation on the cylinder.

Physics↗

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Litt, Jonathan↗

Real-time computer data system for the 40- by 80-foot wind tunnel facility at Ames Research Center

The background material and operational concepts of a computer-based system for an operating wind tunnel are described. An on-line real-time computer system was installed in a wind tunnel facility to gather static and dynamic data. The computer system monitored aerodynamic forces and moments of periodic and quasi-periodic functions, and displayed and plotted computed results in real time. The total system is comprised of several off-the-shelf, interconnected subsystems that are linked to a large data processing center. The system includes a central processor unit with 32,000 24-bit words of core memory, a number of standard peripherals, and several special processors; namely, a dynamic analysis subsystem, a 256-channel PCM-data subsystem and ground station, a 60-channel high-speed data acquisition subsystem, a communication link, and static force and pressure subsystems. The role of the test engineer as a vital link in the system is also described.

Cambra, J. M.↗

Out-of-time-ordered-correlators for the pure inverted quartic oscillator: classical chaos meets quantum stability

Out-of-time-ordered-correlators (OTOCs) have been suggested as a means to diagnose chaotic behavior in quantum mechanical systems. Recently, it was found that OTOCs display exponential growth for the inverted quantum harmonic oscillator, mirroring the fact that this system is classically and quantum mechanically unstable. In this work, I study OTOCs for the inverted anharmonic (pure quartic) oscillator in quantum mechanics, finding only oscillatory behavior despite the classically unstable nature of the system. For higher temperature, OTOCs seem to exhibit saturation consistent with a value of –2< x 2 > T < p 2 > T at late times. I provide analytic evidence from the spectral zeta-function and the WKB method as well as direct numerical solutions of the Schrödinger equation that the inverted quartic oscillator possesses a real and positive energy eigenspectrum, and normalizable wave-functions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Gauges, loops, and polynomials for partition functions of graphical models

Graphical models represent multivariate and generally not normalized probability distributions. Computing the normalization factor, called the partition function, is the main inference challenge relevant to multiple statistical and optimization applications. The problem is #P-hard that is of an exponential complexity with respect to the number of variables. Here, aimed at approximating the partition function, we consider multi-graph models where binary variables and multivariable factors are associated with edges and nodes, respectively, of an undirected multi-graph. We suggest a new methodology for analysis and computations that combines the Gauge function technique from Chertkov and Chernyak with the technique developed in Anari and Oveis Gharan 2017 arXiv:1702.02937; Gurvits 2011 arXiv:1106.2844; Straszak and Vishnoi 2017 55th Annual Allerton Conf. on Communication, Control, and Computing, based on the recent progress in the field of real stable polynomials. We show that the Gauge function, representing a single-out term in a finite sum expression for the partition function which achieves extremum at the so-called belief-propagation gauge, has a natural polynomial representation in terms of gauges/variables associated with edges of the multi-graph. Moreover, Gauge function can be used to recover the partition function through a sequence of transformations allowing appealing algebraic and graphical interpretations. Algebraically, one step in the sequence consists of the application of a differential operator over gauges associated with an edge. Graphically, the sequence is interpreted as a repetitive elimination/contraction of edges resulting in multi-graph models on decreasing in size (number of edges) graphs with the same partition function as in the original multi-graph model. Even though the complexity of computing factors in the sequence of the derived multi-graph models and respective Gauge functions grow exponentially with the number of eliminated edges, polynomials associated with the new factors remain bi-stable if the original factors have this property. Moreover, we show that BP estimations in the sequence do not decrease, each low-bounding the partition function.

97 MATHEMATICS AND COMPUTING↗