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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 145 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Stress-Drop and Source Scaling of the 2019 Ridgecrest, California, Earthquake Sequence

Stress drop, while difficult to measure reliably and at scale, is a key source parameter for understanding the earthquake rupture process and its relationship to strong ground motion. Here, we use a P-wave spectral decomposition approach, designed for large and densely sampled datasets, to measure earthquake stress drop in the region surrounding the 2019 Ridgecrest, California, earthquake sequence. With more than 11,000 measurements of earthquake stress drop in the 20-yr time period from 2000 through 2019, this dataset provides an opportunity to understand how coseismic stress changes and how other geophysical factors relate to the distribution of stress drop and its evolution in space and time. We observe a mild but persistent deviation from self-similar scaling, with larger events having systematically higher stress drops, though this trend depends on the assumption of an omega-square source spectral model. Earthquake stress drop increases with hypocentral depth in this study region, and the Ridgecrest aftershocks tend to have higher stress drops than the pre-event seismicity. This is in part due to their deeper hypocenters. Coherent spatial patterns of stress drop in the aftershock sequence correlate with the slip distribution of the M 7.1 mainshock, whose northwest rupture tip terminated in a long-lived zone of enervated stress drop. Although physical interpretation of these results is complicated by the trade-offs between the timing, depth, and location of these earthquakes, the observations provide new insight into the physics of the earthquake source in an area of renewed seismic activity in southern California.

58 GEOSCIENCES↗

DOE OSTI2022

Probing the Kinetic Origin of Varying Oxidative Stability of Ethyl- vs. Propyl-spaced Amines for Direct Air Capture

Amine-based adsorbents are promising for direct air capture of CO 2 , yet oxidative degradation remains a key unmitigated risk hindering wide-scale deployment. Borrowing wisdom from the basic auto-oxidation scheme, insights are gained into the underlying degradation mechanisms of polyamines by quantum chemical, advanced sampling simulations, adsorbent synthesis, and accelerated degradation experiments. The reaction kinetics of polyamines are contrasted with that of typical aliphatic polymers and they elucidate for the first time the critical role of aminoalkyl hydroperoxide decomposition in the oxidative degradation of amino-oligomers. The experimentally observed variation in oxidative stability of polyamines with different backbone structures is explained by the relationship between the local chemical structure and the free energy barrier of aminoalkyl hydroperoxide decomposition, suggesting that its energetics can be used as a descriptor to screen and design new polyamines with improved stability. In conclusion, the developed computational capability sheds light on radical-induced degradation chemistry of other organic functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1981

An optimization model for energy generation and distribution in a dynamic facility

An analytical model is described using linear programming for the optimum generation and distribution of energy demands among competing energy resources and different economic criteria. The model, which will be used as a general engineering tool in the analysis of the Deep Space Network ground facility, considers several essential decisions for better design and operation. The decisions sought for the particular energy application include: the optimum time to build an assembly of elements, inclusion of a storage medium of some type, and the size or capacity of the elements that will minimize the total life-cycle cost over a given number of years. The model, which is structured in multiple time divisions, employ the decomposition principle for large-size matrices, the branch-and-bound method in mixed-integer programming, and the revised simplex technique for efficient and economic computer use.

Lansing, F. L.↗

NASA NTRS1993

(abstract) 3D Electromagnetic Plasma Particle Simulations

A 3D electromagnetic plasma particle-in-cell code has been developed using the General Concurrent PIC algorithm. The GCPIC algorithm uses a domain decomposition to divide the computation among the processors. Particles must be exchanged between processors as they move. The efficiencies for 1-, 2-, and 3-dimensional partitions of the three dimensional domain are compared, and the algorithm is found to be very efficient even when a large fraction (e.g., 30%) of the particles must be exchanged at every time step. This PIC code has been used to perform simulations of a variety of space plasma physics problems. Results of three applications will be discussed: 1) plasma disturbances induced by moving conducting bodies in a magnetized plasma; 2) plasma plume interactions; and 3) solar wind termination shock.

electromagnetic plasma particles simulations 3D al↗

NASA NTRSDate not supplied

Invited: uPSP Launch Vehicle Demonstration Test at NASA Ames Research Center

The Unsteady Pressure-Sensitive Paint (uPSP) Development Team outof NASA Ames Research Center (ARC) has spent the past five yearsimproving the systems and processes to advance the uPSP technology for production-level wind tunnel testing. Already considered turnkey for small-scale and research applications, development in acquisition, calibration, data transfer, and data processing were needed to be useful to customers testing at NASA wind tunnels. This development focused at ARC at the Unitary Plan Wind Tunnel (UPWT) 11-by 11-ft Transonic Wind Tunnel due to the large optical access of the test section and the NASA Advanced Supercomputer(NAS), also located at ARC. A Launch Vehicle Demonstration Test (LVDT) at the UPWT represents a milestone of this initial phase of development where several new improvements were demonstrated in a production wind tunnel environment for the first time. LVDT was conducted in April 2024 and used a 4% forebody Space Launch System (SLS) Block 1B model as the test article. Both a crew and cargo configuration were tested, with varying Mach numbers, pressures, model positions, and camera magnifications. This paper summarizes the details of the test and is part of a collection with four additional papers that provide greater detail on: high-speed lifetime methodology, spectral proper orthogonal decomposition analysis, quality of high-resolution data compared to Corcos model, and data quality, calibration, and uncertainty.

SLS↗

NASA NTRS2002

Multi-Zone Liquid Thrust Chamber Performance Code with Domain Decomposition for Parallel Processing

Computational Fluid Dynamics (CFD) has considerably evolved in the last decade. There are many computer programs that can perform computations on viscous internal or external flows with chemical reactions. CFD has become a commonly used tool in the design and analysis of gas turbines, ramjet combustors, turbo-machinery, inlet ducts, rocket engines, jet interaction, missile, and ramjet nozzles. One of the problems of interest to NASA has always been the performance prediction for rocket and air-breathing engines. Due to the complexity of flow in these engines it is necessary to resolve the flowfield into a fine mesh to capture quantities like turbulence and heat transfer. However, calculation on a high-resolution grid is associated with a prohibitively increasing computational time that can downgrade the value of the CFD for practical engineering calculations. The Liquid Thrust Chamber Performance (LTCP) code was developed for NASA/MSFC (Marshall Space Flight Center) to perform liquid rocket engine performance calculations. This code is a 2D/axisymmetric full Navier-Stokes (NS) solver with fully coupled finite rate chemistry and Eulerian treatment of liquid fuel and/or oxidizer droplets. One of the advantages of this code has been the resemblance of its input file to the JANNAF (Joint Army Navy NASA Air Force Interagency Propulsion Committee) standard TDK code, and its automatic grid generation for JANNAF defined combustion chamber wall geometry. These options minimize the learning effort for TDK users, and make the code a good candidate for performing engineering calculations. Although the LTCP code was developed for liquid rocket engines, it is a general-purpose code and has been used for solving many engineering problems. However, the single zone formulation of the LTCP has limited the code to be applicable to problems with complex geometry. Furthermore, the computational time becomes prohibitively large for high-resolution problems with chemistry, two-equation turbulence model, and two-phase flow. To overcome these limitations, the LTCP code is rewritten to include the multi-zone capability with domain decomposition that makes it suitable for parallel processing, i.e., enabling the code to run every zone or sub-domain on a separate processor. This can reduce the run time by a factor of 6 to 8, depending on the problem.

Homayun K. Navaz↗

DOE OSTI2024

Data-driven models of nonautonomous systems

Nonautonomous dynamical systems are characterized by time-dependent inputs, which complicates the discovery of predictive models describing the spatiotemporal evolution of the state variables of quantities of interest from their temporal snapshots. When dynamic mode decomposition (DMD) is used to infer a linear model, this difficulty manifests itself in the need to approximate the time-dependent Koopman operators. Our approach is to approximate the original nonautonomous system with a modified system derived via a local parameterization of the time-dependent inputs. The modified system comprises a sequence of local parametric systems, which are subsequently approximated by a parametric surrogate model using the DRIPS (dimension reduction and interpolation in parameter space) framework. The offline step of DRIPS relies on DMD to build a linear surrogate model, endowed with reduced-order bases for the observables mapped from training data. The online step interpolates on suitable manifolds to construct a sequence of iterative parametric surrogate models; the target/test parameter points on these manifolds are specified by a local parameterization of the test time-dependent inputs. Here, we use numerical experimentation to demonstrate the robustness of our method and compare its performance with that of deep neural networks.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1983

Monitoring tropical vegetation succession with LANDSAT data

The shadowing problem, which is endemic to the use of LANDSAT in tropical areas, and the ability to model changes over space and through time are problems to be addressed when monitoring tropical vegetation succession. Application of a trend surface analysis model to major land cover classes in a mountainous region of the Phillipines shows that the spatial modeling of radiance values can provide a useful approach to tropical rain forest succession monitoring. Results indicate shadowing effects may be due primarily to local variations in the spectral responses. These variations can be compensated for through the decomposition of the spatial variation in both elevation and MSS data. Using the model to estimate both elevation and spectral terrain surface as a posteriori inputs in the classification process leads to improved classification accuracy for vegetation of cover of this type. Spatial patterns depicted by the MSS data reflect the measurement of responses to spatial processes acting at several scales.

Robinson, V. B.↗

NASA NTRS1999

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Caines, P. E.↗

NASA NTRS2003

On the Hilbert-Huang Transform Data Processing System Development

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). The Fourier view of nonlinear mechanics that had existed for a long time, and the associated FFT (fairly recent development), carry strong a-priori assumptions about the source data, such as linearity and of being stationary. Natural phenomena measurements are essentially nonlinear and nonstationary. A very recent development at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), known as the Hilbert-Huang Transform (HHT) proposes a novel approach to the solution for the nonlinear class of spectrum analysis problems. Using the Empirical Mode Decomposition (EMD) followed by the Hilbert Transform of the empirical decomposition data (HT), the HHT allows spectrum analysis of nonlinear and nonstationary data by using an engineering a-posteriori data processing, based on the EMD algorithm. This results in a non-constrained decomposition of a source real value data vector into a finite set of Intrinsic Mode Functions (IMF) that can be further analyzed for spectrum interpretation by the classical Hilbert Transform. This paper describes phase one of the development of a new engineering tool, the HHT Data Processing System (HHTDPS). The HHTDPS allows applying the "T to a data vector in a fashion similar to the heritage FFT. It is a generic, low cost, high performance personal computer (PC) based system that implements the HHT computational algorithms in a user friendly, file driven environment. This paper also presents a quantitative analysis for a complex waveform data sample, a summary of technology commercialization efforts and the lessons learned from this new technology development.

Kizhner, Semion↗

DOE OSTI2020

Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction

In this paper, we propose a variational approach to estimate eddy viscosity using forward sensitivity method (FSM) for closure modeling in nonlinear reduced order models. FSM is a data assimilation technique that blends model's predictions with noisy observations to correct initial state and/or model parameters. We apply this approach on a projection based reduced order model (ROM) of the one-dimensional viscous Burgers equation with a square wave defining a moving shock, and the two-dimensional vorticity transport equation formulating a decay of Kraichnan turbulence. We investigate the capability of the approach to approximate an optimal value for eddy viscosity with different measurement configurations. Specifically, we show that our approach can sufficiently assimilate information either through full field or sparse noisy measurements to estimate eddy viscosity closure to cure standard Galerkin reduced order model (GROM) predictions. Therefore, our approach provides a modular framework to correct forecasting error from a sparse observational network on a latent space. We highlight that the proposed GROM-FSM framework is promising for emerging digital twin applications, where real-time sensor measurements can be used to update and optimize surrogate model's parameters.

42 ENGINEERING↗

NASA NTRS1994

Root growth and development in response to CO2 enrichment

A non-destructive technique (minirhizotron observation tubes) was used to assess the effects of CO2 enrichment on root growth and development in experimental plots in a scrub oak-palmetto community at the Kennedy Space Center. Potential effects of CO2 enrichment on plants have a global significance in light of concerns over increasing CO2 concentrations in the Earth's atmosphere. The study at Kennedy Space Center focused on aboveground physiological responses (photosynthetic efficiency and water use efficiency), effects on process rates (litter decomposition and nutrient turnover), and belowground responses of the plants. Belowground dynamics are an exceptionally important component of total plant response but are frequently ignored due to methodological difficulties. Most methods used to examine root growth and development are destructive and, therefore, severely compromise results. Minirhizotrons allow nondestructive observation and quantification of the same soil volume and roots through time. Root length density and root phenology were evaluated for CO2 effects with this nondestructive technique.

Day, Frank P., Jr.↗

NASA NTRS1988

Parallel algorithms for mapping pipelined and parallel computations

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

Nicol, David M.↗

DOE OSTI2024

Leveraging Temperature-Dependent (Electro)Chemical Kinetics for High-Throughput Flow Battery Characterization

The library of redox-active organics that are potential candidates for electrochemical energy storage in flow batteries is exceedingly vast, necessitating high-throughput characterization of molecular lifetimes. Demonstrated extremely stable chemistries require accurate yet rapid cell cycling tests, a demand often frustrated by time-denominated capacity fade mechanisms. We have developed a high-throughput setup for elevated temperature cycling of redox flow batteries, providing a new dimension in characterization parameter space to explore. We utilize it to evaluate capacity fade rates of aqueous redox-active organic molecules, as functions of temperature. We demonstrate Arrhenius-like behavior in the temporal capacity fade rates of multiple flow battery electrolytes, permitting extrapolation to lower operating temperatures. Collectively, these results highlight the importance of accelerated decomposition protocols to expedite the screening process of candidate molecules for long lifetime flow batteries.

25 ENERGY STORAGE↗

NASA NTRS1993

Single block three-dimensional volume grids about complex aerodynamic vehicles

This paper presents an alternate approach for the generation of volumetric grids for supersonic and hypersonic flows about complex configurations. The method uses parametric two dimensional block face grid definition within the framework of GRIDGEN2D. The incorporation of face decomposition reduces complex surfaces to simple shapes. These simple shapes are combined to obtain the final face definition. The advantages of this method include the reduction of overall grid generation time through the use of vectorized computer code, the elimination of the need to generate matching block faces, and the implementation of simplified boundary conditions. A simple axisymmetric grid is used to illustrate this method. In addition, volume grids for two complex configurations, the Langley Lifting Body (HL-20) and the Space Shuttle Orbiter, are shown.

Alter, Stephen J.↗

NASA NTRS1999

Chemical Vapor Deposition at High Pressure in a Microgravity Environment

In this paper we present an evaluation of critical requirements of organometallic chemical vapor deposition (OMCVD) at elevated pressure for a channel flow reactor in a microgravity environment. The objective of using high pressure is to maintain single-phase surface composition for materials that have high thermal decomposition pressure at their optimum growth temperature. Access to microgravity is needed to maintain conditions of laminar flow, which is essential for process analysis. Based on ground based observations we present an optimized reactor design for OMCVD at high pressure and reduced gravity. Also, we discuss non-intrusive real-time optical monitoring of flow dynamics coupled to homogeneous gas phase reactions, transport and surface processes. While suborbital flights may suffice for studies of initial stages of heteroepitaxy experiments in space are essential for a complete evaluation of steady-state growth.

McCall, Sonya↗

DOE OSTI2020

Faster Johnson–Lindenstrauss transforms via Kronecker products

The Kronecker product is an important matrix operation with a wide range of applications in signal processing, graph theory, quantum computing and deep learning. In this work, we introduce a generalization of the fast Johnson–Lindenstrauss projection for embedding vectors with Kronecker product structure, the Kronecker fast Johnson–Lindenstrauss transform (KFJLT). The KFJLT reduces the embedding cost by an exponential factor of the standard fast Johnson–Lindenstrauss transform’s cost when applied to vectors with Kronecker structure, by avoiding explicitly forming the full Kronecker products. Here, we prove that this computational gain comes with only a small price in embedding power: consider a finite set of $p$ points in a tensor product of $d$ constituent Euclidean spaces $\bigotimes _{k=d}^{1}{\mathbb{R}}^{n_k}$, and let $N = \prod _{k=1}^{d}n_k$. With high probability, a random KFJLT matrix of dimension $m \times N$ embeds the set of points up to multiplicative distortion $(1\pm \varepsilon )$ provided $m \gtrsim \varepsilon ^{-2} \, \log ^{2d - 1} (p) \, \log N$. We conclude by describing a direct application of the KFJLT to the efficient solution of large-scale Kronecker-structured least squares problems for fitting the CP tensor decomposition.

Kronecker structure↗

DOE OSTI2022

Optimal, centralized dynamic curbside parking space zoning

In this paper we formulate a dynamic mixed integer program for optimally zoning curbside parking spaces subject to transportation policy-inspired constraints and regularization terms. First, we illustrate how given some objective of curb zoning valuation as a function of zone type (paid parking, bus stop, etc.), dynamically rezoning involves unrolling this optimization program over a fixed time horizon. Second, we implement two different solution methods given an example curb zoning valuation. In the first method, we solve long horizon dynamic zoning problems via approximate dynamic programming. In the second method, we employ Dantzig-Wolfe decomposition to break-up the mixed-integer program into a master problem and several sub-problems that can be solved in parallel. This speeds up the computational solve-time of the MIP considerably. We present simulation results and comparisons of the different employed techniques on vehicle arrival-rate data obtained for a neighborhood in downtown Seattle, Washington, USA.

Nazir, Mohammad Nawaf↗