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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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NASA NTRS1996

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

The three-dimensional, spectral transport model used in the current project was first successfully integrated over climatological time scales by Dr. Guang Ping Lou for the simulation of atmospheric N2O using the United Kingdom Meteorological Office (UKMO) 4-dimensional, assimilated wind and temperature data set. A non-parallel, FORTRAN version of this integration using a fairly simple N2O chemistry package containing only photo-chemical reactions was used to verify our initial parallel model results. The integrations reproduced the gross features of the observed stratospheric climatological N2O distributions but also simulated the structure of the stratospheric Antarctic vortex and its evolution. Subsequently, Dr. Thomas Kindler, who produced much of the parallel version of our model, enlarged the N2O model chemistry package to include N2O reactions involving O(D-1) and also introduced assimilated wind data from NASA as well as UKMO. Initially, transport calculations without chemistry were run using Carbon-14 as a non-reactive tracer gas with the result that large differences in the transport properties of the two assimilated wind data sets were apparent from the resultant Carbon-14 distributions. Subsequent calculations for N2O, including its chemistry, with the two input winds data sets with verification from UARS satellite observations have refined the transport differences between the two such that the model's steering capabilities could be used to infer the correct climatological vertical velocity fields required to support the N2O observations. During this process, it was also discovered that both the NASA and the UKMO data contained spurious values in some of the higher frequency wave components, leading to incorrect local transport calculations and ultimately affecting the large scale properties of the model's N2O distributions, particularly at tropical latitudes. Subsequent model runs with wind data that had been filtered to remove some of the high frequency components produced much more realistic N2O distributions. During the past few months, the UKMO wind data base for a complete two-year period was processed into spectral form for model use. This new version of the input transport data base now includes complete temperature fields as well as the necessary wind data. This was done to facilitate advanced chemical calculations in the parallel model which often depend upon temperature. Additional UKMO data is being added as it becomes available.

Schwan, Karsten↗

NASA NTRS1994

Automated Performance Prediction of Message Passing Parallel Programs

As the trend toward massively parallel processing continues, the need for tools that can predict scalability trends becomes greater. While high level languages Eke HPF have come into greater use, explicit message-passing programs proliferate, and will probably do so for some time, thanks to the onslaught of standards such as MPI. Much work has been done to create simple models that represent important characteristics of parallel programs, such as latency, network contention, and communication volume. But many of these methods still require a substantial manual effort to represent an application in the model's format. The YAPP ("Yet Another Performance Predictor") tool is an attempt to automate the formation of first-order expressions for completion time, with a minimum of programmer assistance. The content of this paper is as follows: First, we explore the implementation details of YAPP, and illustrate with examples some of the reasons that automatic prediction is difficult. In the following sections, we present the results of four applications, using execution traces on the Intel i860, analyze the error in YAPP's predictions, explain the limitations of our implementation, and mention possible future additions. In particular, we illustrate techniques used to identify pipeline communication patterns, and demonstrate how compiler analysis and regression are combined to automate the prediction process.

Block, Robert J.↗

NASA NTRS2012

Development of a Robust and Efficient Parallel Solver for Unsteady Turbomachinery Flows

The traditional design and analysis practice for advanced propulsion systems relies heavily on expensive full-scale prototype development and testing. Over the past decade, use of high-fidelity analysis and design tools such as CFD early in the product development cycle has been identified as one way to alleviate testing costs and to develop these devices better, faster and cheaper. In the design of advanced propulsion systems, CFD plays a major role in defining the required performance over the entire flight regime, as well as in testing the sensitivity of the design to the different modes of operation. Increased emphasis is being placed on developing and applying CFD models to simulate the flow field environments and performance of advanced propulsion systems. This necessitates the development of next generation computational tools which can be used effectively and reliably in a design environment. The turbomachinery simulation capability presented here is being developed in a computational tool called Loci-STREAM [1]. It integrates proven numerical methods for generalized grids and state-of-the-art physical models in a novel rule-based programming framework called Loci [2] which allows: (a) seamless integration of multidisciplinary physics in a unified manner, and (b) automatic handling of massively parallel computing. The objective is to be able to routinely simulate problems involving complex geometries requiring large unstructured grids and complex multidisciplinary physics. An immediate application of interest is simulation of unsteady flows in rocket turbopumps, particularly in cryogenic liquid rocket engines. The key components of the overall methodology presented in this paper are the following: (a) high fidelity unsteady simulation capability based on Detached Eddy Simulation (DES) in conjunction with second-order temporal discretization, (b) compliance with Geometric Conservation Law (GCL) in order to maintain conservative property on moving meshes for second-order time-stepping scheme, (c) a novel cloud-of-points interpolation method (based on a fast parallel kd-tree search algorithm) for interfaces between turbomachinery components in relative motion which is demonstrated to be highly scalable, and (d) demonstrated accuracy and parallel scalability on large grids (approx 250 million cells) in full turbomachinery geometries.

West, Jeff↗

DOE OSTI2017

Algorithms and analyses for stochastic optimization for turbofan noise reduction using parallel reduced-order modeling

Simulation-based optimization of acoustic liner design in a turbofan engine nacelle for noise reduction purposes can dramatically reduce the cost and time needed for experimental designs. Because uncertainties are inevitable in the design process, a stochastic optimization algorithm is posed based on the conditional value-at-risk measure so that an ideal acoustic liner impedance is determined that is robust in the presence of uncertainties. A parallel reduced-order modeling framework is developed that dramatically improves the computational efficiency of the stochastic optimization solver for a realistic nacelle geometry. The reduced stochastic optimization solver takes less than 500 s to execute. Additionally, well-posedness and finite element error analyses of the state system and optimization problem are provided.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Thermonuclear Burn in a Multiphysics Code on GPUs

Multiphysics codes links to a library called SINGE for the calculation of thermonuclear (TN) burn rates, but some current multiphysics codes do not attempt to leverage the support for parallel operation that SINGE provides. Our goal is to investigate implementations of the SINGE workflow and analyze how the use of a performance portability layer could reduce run time on CPU archi tectures while also supporting GPU architectures without requiring code modifications. We looked to the Kokkos C++ Performance Portability Ecosystem to implement hardware agnostic parallel patterns.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2003

High Performance Parallel Methods for Space Weather Simulations

This is the final report of our NASA AISRP grant entitled 'High Performance Parallel Methods for Space Weather Simulations'. The main thrust of the proposal was to achieve significant progress towards new high-performance methods which would greatly accelerate global MHD simulations and eventually make it possible to develop first-principles based space weather simulations which run much faster than real time. We are pleased to report that with the help of this award we made major progress in this direction and developed the first parallel implicit global MHD code with adaptive mesh refinement. The main limitation of all earlier global space physics MHD codes was the explicit time stepping algorithm. Explicit time steps are limited by the Courant-Friedrichs-Lewy (CFL) condition, which essentially ensures that no information travels more than a cell size during a time step. This condition represents a non-linear penalty for highly resolved calculations, since finer grid resolution (and consequently smaller computational cells) not only results in more computational cells, but also in smaller time steps.

Hunter, Paul↗

NASA NTRS1994

Missileborne Artificial Vision System (MAVIS)

Several years ago when INTEL and China Lake designed the ETANN chip, analog VLSI appeared to be the only way to do high density neural computing. In the last five years, however, digital parallel processing chips capable of performing neural computation functions have evolved to the point of rough equality with analog chips in system level computational density. The Naval Air Warfare Center, China Lake, has developed a real time, hardware and software system designed to implement and evaluate biologically inspired retinal and cortical models. The hardware is based on the Adaptive Solutions Inc. massively parallel CNAPS system COHO boards. Each COHO board is a standard size 6U VME card featuring 256 fixed point, RISC processors running at 20 MHz in a SIMD configuration. Each COHO board has a companion board built to support a real time VSB interface to an imaging seeker, a NTSC camera, and to other COHO boards. The system is designed to have multiple SIMD machines each performing different corticomorphic functions. The system level software has been developed which allows a high level description of corticomorphic structures to be translated into the native microcode of the CNAPS chips. Corticomorphic structures are those neural structures with a form similar to that of the retina, the lateral geniculate nucleus, or the visual cortex. This real time hardware system is designed to be shrunk into a volume compatible with air launched tactical missiles. Initial versions of the software and hardware have been completed and are in the early stages of integration with a missile seeker.

Andes, David K.↗

DOE OSTI2016

Parallel methodology to capture cyclic variability in motored engines

Numerical prediction of of cycle-to-cycle variability (CCV) in SI engines is extremely challenging for two key reasons: (i) high-fidelity methods such as large eddy simulation (LES) are require to accurately capture the in-cylinder turbulent flowfield, and (ii) CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. In this study, a new methodology is proposed to dissociate this long time-scale problem into several shorter time-scale problems, which can considerably reduce the computational time without sacrificing the fidelity of the simulations. The strategy is to perform multiple single-cycle simulations in parallel by effectively perturbing the simulation parameters such as the initial and boundary conditions. It is shown that by perturbing the initial velocity field effectively based on the intensity of the in-cylinder turbulence, the mean and variance of the in-cylinder flowfield is captured reasonably well. Adding perturbations in the initial pressure field and the boundary pressure improves the predictions. It is shown that this new approach is able to give accurate predictions of the flowfield statistics in less than one-tenth of time required for the conventional approach of simulating consecutive engine cycles.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Scale-dependent spatial variabilities of hydrological exchange flows and transit time in a large regulated river

Hydrological exchange flows (HEF) across the river-aquifer interface and the associated residence time of river water in the aquifer have important implications for contaminant plume migration and biogeochemical processes in the river corridor. HEFs and residence time are influenced by both subsurface physical features and hydrologic forcing related to the transport process, which can exhibit complex spatial and temporal variations. In this study, we used a massively parallel subsurface flow model and a particle-tracking model to study the influences of different control factors on spatial variability of HEFs and residence time distributions (RTD) in the Hanford Reach of the Columbia River in Washington State. A total number of 100M particles were randomly injected in time and space and then tracked in a model domain that covers a 51-km 2 area (15.1M model cells). We used hourly river stages and groundwater levels to drive the model to provide dynamic velocity fields for the particle tracking in the simulation period that was longer than 2 years. The groundwater flow simulation and particle-tracking results provide the first comprehensive assessment of the spatial distribution of HEFs and residence time in large complex river corridors. Overall, our results show that the aquifer hydrogeological structure has the strongest correlation with the extent and magnitude of exchange flux. The residence time exhibits complex patterns that are impacted by all the river geomorphologic, hydrodynamic, and hydrogeologic factors and are strongly correlated with the downwelling ratio of exchange flux. The new insights gained through this study can be used to support the development of reduced-order models of HEFs and RTDs for large complex river systems.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1989

Passive microwave remote sensing of precipitation from space - Impact of cloud microphysics

Numerical experiments to investigate the impact of time-dependent cloud microphysical structure on the transfer to space of passive microwave radiation are carried out, using a vertically and angularly detailed, plane-parallel radiative transfer model for unpolarized microwave radiation. The object is to explore the feasibility of multichannel passive-microwave retrieval techniques to estimate precipitation from space. Results on the time-dependent influence of large graupel-size ice particles on top-of-atmosphere brightness temperature - rainfall rate relationships at 6.6, 10.7, 18, 19.35, 22.235, 37, 89.5, 130, and 231 GHz are given. Frequency-dependent vertical profiles of a generalized brightness-temperature weighting function, introduced to vertically resolve the contributions by individual cloud and precipitation layers to the brightness temperatures, are also shown.

Mugnai, Alberto↗

NASA NTRS1979

Autonomous attitude estimation via star sensing and pattern recognition

Results are reported on the development of an autonomous, onboard, near real time spacecraft attitude estimation technique. The approach uses CCD based star sensors to digitize relative star positions. Three microcomputers are envisioned, configured in parallel, to: (1) determine star image centroids and delete spurious images; (2) identify measured stars with stars in an onboard catalog and determine discrete attitude estimates; (3) integrate gyro rate measurements and determine optimal real time attitude estimates for use in the control system and for feedback to the star identification algorithm. Algorithms for the star identification are presented. The discrete attitude estimation algorithm recovers thermally varying interlock angles between two star sensors. The optimal state estimation process recovers rate gyro biases in addition to real time attitude estimates.

Junkins, J. L.↗

DOE OSTI2020

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗

DOE OSTI2023

Online Monitoring of Medium Voltage Cable Systems with Spread Spectrum Time Domain and Frequency Domain Reflectometry

In-service failures of wave energy convertor (WEC) cable systems can have a significant cost and power availability impact. Close parallel research 2019 data showed > 1B£ and 9 Terra-Watt-Hours associated with global off-shore wind (OSW) cable failures (Strang-Moran 2020). OSW is a closely related technology but currently is significantly cheaper than WEC technology. For wave energy to compete, the problem of reliable cable transmission must be mitigated. This project develops isolation technology to allow online high frequency reflectometry testing of medium voltage cables (1 to 10 kV and higher) without arcing or damage to the test instrument. Online spread spectrum time domain reflectometry (SSTDR) testing has been established for low voltage cable systems in the aircraft and rail industry and the ability to detect and locate cable flaws of interest is well understood. Extending reflectometry testing to medium voltage systems could enable detection of cable damage before failures occur thereby allowing repair and replacement of damaged cable segments to be scheduled and managed. The seedling project succeeded to pass and receive high frequency SSTDR signals onto a cable up to 1 kV using a parallel trace isolation circuit board that can be connected onto the test cable. The approach used a novel circuit design for which an invention disclosure has been filed. A proposed sapling project would extend the technology toward the higher operating voltages used by WEC systems, thereby enabling online SSTDR cable monitoring. The goal of the seedling project was to extend the capability of the ARENA cable/motor test bed to address medium voltages and to develop a high pass filter isolation architecture to protect the reflectometry instrument from the low frequency (DC – 60 Hz) line voltage while allowing the high frequency diagnostic signal to pass to and from the test instrument to the live line. Initial efforts focused on passive LCR filter circuits to reduce 60 Hz levels below 10 volts from a 10 kV line while allowing the MHz high frequency chirps to pass onto the cables and for mV signals to be detected. We discovered that the parasitic loss behavior of real high voltage components precluded this approach from working. An alternate approach was adapted for the electric field to couple between two parallel traces on a printed circuit board much like a radio-frequency coupler. The challenge here was and is to have the parallel traces close enough to each other to effectively pass the high frequency chirp onto the live line and receive any reflected signal from any encountered impedance change along the cable. This reflected signal will be in the mV range. The traces however must be far enough apart to not allow arcing on the board. A design with 3 mm spacing was determined to allow the high frequency signal to pass onto the live line and receive the mV signal back into the instrument while reducing the 60 Hz voltage amplitude by >80 dB (more than a factor of 10,000) without allowing arcing from across the parallel traces. This was confirmed by simulation and test.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

Integrated hydrogeophysical modelling and data assimilation for geoelectrical leak detection

Time-lapse electrical resistivity tomography (ERT) measurements provide indirect observations of hydrological processes in the Earth's shallow subsurface at high spatial and temporal resolution. ERT has been used in the past decades to detect leaks and monitor the evolution of associated contaminant plumes. Specifically, inverted resistivity images allow visualization of the dynamic changes in the structure of the plume. However, existing methods do not allow the direct estimation of leak parameters (e.g. leak rate, location, etc.) and their uncertainties. We propose an ensemble-based data assimilation framework that evaluates proposed hydrological models against observed time-lapse ERT measurements without directly inverting for the resistivities. Each proposed hydrological model is run through the parallel coupled hydro-geophysical simulation code PFLOTRAN-E4D to obtain simulated ERT measurements. The ensemble of model proposals is then updated using an iterative ensemble smoother. In this paper, we demonstrate the proposed framework on synthetic and field ERT data from controlled tracer injection experiments. Our results show that the approach allows joint identification of contaminant source location, initial release time, and solute loading from the cross-borehole time-lapse ERT data, alongside with an assessment of uncertainties in these estimates. We demonstrate a reduction in site-wide uncertainty by comparing the prior and posterior plume mass discharges at a selected image plane. This framework is particularly attractive to sites that have previously undergone extensive geological investigation (e.g., nuclear sites). It is well suited to complement ERT imaging and we discuss practical issues in its application to field problems.

58 GEOSCIENCES↗

DOE OSTI2021

Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models

We improved the quality and reduced the time to produce machine learned models for use in small molecule antiviral design. Our globally asynchronous multi-level parallel training approach strong scales to all of Sierra with up to 97.7% efficiency. We trained a novel, character-based Wasserstein autoencoder that produces a higher quality model trained on 1.613 billion compounds in 23 minutes while the previous state of the art takes a day on 1 million compounds. Reducing training time from a day to minutes shifts the model creation bottleneck from computer job turnaround time to human innovation time. Our implementation achieves 318 PFLOPs for 17.1% of half-precision peak. We will incorporate this model into our molecular design loop enabling the generation of more diverse compounds; searching for novel, candidate antiviral drugs improves and reduces the time to synthesize compounds to be tested in the lab.

Jacobs, Sam Ade↗

DOE OSTI2023

Microstructurally driven self-sharpening mechanism in beaver incisor enamel facilitates their capacity to fell trees

Beavers ( Castor ) stand out among mammals for their unique capacity to fell trees using their large, ever-growing incisors. This routine consumption of resistant fodder induces prodigious wear in the lower incisors, despite this blunting effect the incisors maintain a remarkably sharp cutting edge. Notably, the enamel edges of their incisors show a highly complex two-part microstructure of which the biomechanical import is unknown. Here, using fracture analysis, nanoindentation, and wear testing on North American beaver ( C. canadensis ) incisors we test the microstructure's possible contribution to maintaining incisal sharpness. Although comparable in hardness, the inner enamel preferentially fails and readily wears at 2.5 times the rate of the outer enamel. The outer microstructure redirects all fractures in parallel, decreasing fracture coalescence. Conversely, the inner microstructure facilitates crack coalescence increasing the wear rate by isolating layers of enamel prisms that readily fragment. Together these two architectures form a microstructurally driven self-sharpening mechanism contained entirely within the thin enamel shell. Here, our results demonstrate that enamel microstructures exposed at the occlusal surface can markedly influence both enamel crest shape and surface texture in wearing dentitions. The methods introduced here open the door to exploring the biomechanical functionality and evolution of enamel microstructures throughout Mammalia.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

An optical-input Maximum Likelihood Estimation feedback system demonstrated on tokamak horizontal equilibrium control

A readily parallelized Maximum Likelihood Estimation (MLE) algorithm with linear computational complexity is demonstrated in real time using only measurements from an extreme ultraviolet (EUV) diagnostic to control the horizontal position of a tokamak plasma. A set of trial emissivity profiles are parameterized by the control quantity of interest (R m ), and the MLE is identified from the profile which minimizes the signal reconstruction residual. The algorithm depends on an empirically determined likelihood function with exponential form. EUV emission (λ ≈ 15eV-1keV) is captured in a poloidal plane by four 16-channel AXUV diodes mounted at different poloidal angles with radial and angular resolution sufficient to discern plasma equilibrium evolution in HBT-EP. Calculations of the plasma major radius by the system are consistent within diagnostic uncertainty for the majority of the discharge with those of: a weighted average of vertical soft X-ray or EUV chords, magnetic sensors, and an equilibrium reconstruction. The feedback system corrects for a horizontal displacement of the major radius equal to 20% of the plasma minor radius by adjusting the vertical field produced from 40 in-vessel control coils in real time. The MLE calculation is performed on a GPU in a 15 μs cycle, with similar performance in this application to a simple weighted average of vertical chords. Finally, results demonstrate horizontal position control using magnetic actuators and an optical observer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Carburization and decarburization behavior of Grade 91 ferritic-martensitic steel in liquid sodium environments

Here, this paper presents a study of carbon transfer and its effect on microstructure and tensile properties of Grade 91 (G91) ferritic-martensitic steel exposed to sodium at 550–650 °C. Sodium exposure tests were conducted in Argonne's forced convection sodium loops up to exposure times of ~40,000 h. Thermal aging study of G91 steel was conducted in parallel to isolate the thermal aging effect from the sodium effect. It was found that sodium exposures at 650 °C dissolved M 23 C 6 carbides, eliminated the martensite subgrain structure resulting in excessive grain growth and reduced the tensile strength by >50%, while sodium exposures at 550 and 600 °C had an insignificant effect on its microstructure and tensile properties. These effects were attributed to the carburization/decarburization process of G91 steel in sodium environments. Carbon concentrations in sodium were determined by a foil equilibration method. The estimated carbon concentration was in the range of 0.8–1.2 ppm in the SMT-1 loop and 0.3–0.7 ppm in the SMT-2 loop. Thermodynamic analysis of the carburization – decarburization process was conducted for G91 steels exposed in sodium environments. The carbon activity-concentration relationship for G91 was evaluated by considering four phases in G91, i.e. bcc ferrite, M 23 C 6 , NbC and VC carbides. It was found that the carburization-decarburization process in G91 steel was dictated by M 23 C 6 carbides at high carbon activities, while NbC and VC carbides dominated the process at low carbon activities. The calculated carburization-decarburization boundary showed that G91 would undergo decarburization at 650 °C and carburization at 550 °C in the sodium loop environments, which was consistent with our experimental observations. This experimental and theoretical analysis provided a basis for predicting the effect of carbon transfer on the integrity of reactor components in sodium environments and for the design of new alloys used in sodium-cooled fast reactors.

36 MATERIALS SCIENCE↗