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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Simultaneous material, shape and topology optimization

Using three design fields we develop an optimization environment that can simultaneously optimize material, shape and topology. We use the implicit representation of the boundaries with level-set functions that define the shape and topology. Differentiable R-functions allow us to combine these shapes and topology descriptions with Boolean operations. Additionally, we incorporate design dependent-stiffness materials with another design field. Notably, this framework accommodates design dependent loads, has the ability to introduce holes, and ensures the satisfaction of optimality criteria. It builds upon the fictitious domain, ersatz material, material interpolation and level-set methods. Additionally, it also borrows from parameterized density-based topology optimization methods. Since analytical sensitivities can be computed, we use efficient nonlinear programming algorithms to update the design instead of the Hamilton–Jacobi’s scheme of level-set methods. We illustrate the features of our framework by designing a cantilever beam with octet truss microlattice, a dam with design-dependent loads, and a composite clevis plate.

42 ENGINEERING↗
DOE OSTI2025

Kinetic Deep Learning v0.1

Here, we present a method that uses protein levels to predict times series of metabolite concentrations. Understanding this type of pathway dynamics is important in order to predict the behavior of the pathway and, more pragmatically, to be able to design biological systems (such as strains bioengineered to produce chemical products) reliably. Typically, for this purpose, kinetic models consisting of differential equations based on the Michaelis-Menten dynamics have been used in the past. However, these methods can rarely produce good fits to measured data time series. Possibly, this happens because the kinetic constants are unknown or are different from the ones measured in vivo, or perhaps because Michaelis-Menten dynamics is not a satisfactory description. In order to improve the predictive nature of these kinetic models we have eliminated the Michaelis-Menten description of pathway dynamics and we have substituted it by algorithms that automatically learn these dynamics from previously obtained metabolomics and proteomics data using machine learning approaches. Specifically, kinetic deep learning uses deep learning to map proteomics time series to metabolite concentration time series, instead of learning the first metabolite derivative and integrating in (as in the first version of kinetic learning). This approach is shown to provide good to excellent results with a data set specifically collected for this purpose.

Garcia Martin, Hector [Joint BioEnergy Institute (↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling

Abstract Capacity factors (CFs) derived from daily expected power at 22 operating wind farms in different regions of North America are used as predictands to train statistical downscaling algorithms using output from ERA5. The statistical downscaling models are then used to make CF projections for a suite of CMIP6 Earth System Models (ESMs). Downscaling is performed using a hybrid statistical approach that employs synoptic types derived using k -means clustering applied to sea level pressure fields with variance corrections applied as a function of the pressure gradient intensity. ESMs exhibit marked variability in terms of the skill with which the frequency of synoptic types and pressure gradients are reproduced relative to ERA5, and that differential skill is used to infer differential credibility in the associated CF projections. Projections of median annual mean CF [P50(CF)] in each 20-yr period from 1980 to 2099 show evidence of declines at most wind farms except in parts of the southern Great Plains, although the magnitude of the changes is strongly dependent on the ESM. For example, P50(CF) in 2080–99 deviate from those in 1980–99 by from −3.1 to +0.2 percentage points in the Northeast. The largest-magnitude declines in P50(CF) ranging from −3.9 to −2 percentage points are projected for the southern West Coast. CF trends exhibit marked seasonality and are strongly linked to changes in the relative intensity of future synoptic patterns, with much less impact from shifts in the occurrence of synoptic types over time. Internal climate modes continue to play a significant role in inducing interannual variability in wind power production, even under high radiative forcing scenarios. Significance Statement We describe how future climate changes may affect wind resources and wind power generation. Near-term changes in projected wind power electricity generation potential at operating wind farms over North America are small, but by the end of the current century electricity production is projected to decrease in many areas but may increase in parts of the southern Great Plains. The amount of change in projected wind power production is a strong function of the Earth system model that is downscaled and also depends on the continued presence of internally forced climate variability. An additional dependence on the amount of greenhouse gas–induced global warming indicates the transition of the energy sector to low-carbon sources may assist in maintaining the abundant U.S. wind resource.

Meteorology & Atmospheric Sciences↗
NASA NTRS1995

Multithreaded Model for Dynamic Load Balancing Parallel Adaptive PDE Computations

We present a multithreaded model for the dynamic load-balancing of numerical, adaptive computations required for the solution of Partial Differential Equations (PDE's) on multiprocessors. Multithreading is used as a means of exploring concurrency in the processor level in order to tolerate synchronization costs inherent to traditional (non-threaded) parallel adaptive PDE solvers. Our preliminary analysis for parallel, adaptive PDE solvers indicates that multithreading can be used an a mechanism to mask overheads required for the dynamic balancing of processor workloads with computations required for the actual numerical solution of the PDE's. Also, multithreading can simplify the implementation of dynamic load-balancing algorithms, a task that is very difficult for traditional data parallel adaptive PDE computations. Unfortunately, multithreading does not always simplify program complexity, often makes code re-usability not an easy task, and increases software complexity.

Chrisochoides, Nikos↗
NASA NTRS2003

Reliable Transport over SpaceWire for James Webb Space Telescope (JWST) Focal Plane Electronics (FPE) Network

NASA's James Webb Space Telescope (JWST) faces difficult technical and budgetary challenges to overcome before it is scheduled launch in 2010. The Integrated Science Instrument Module (ISIM), shares these challenges. The major challenge addressed in this paper is the data network used to collect, process, compresses and store Infrared data. A total of 114 Mbps of raw information must be collected from 19 sources and delivered to the two redundant data processing units across a twenty meter deployed thermally restricted interface. Further data must be transferred to the solid-state recorder and the spacecraft. The JWST detectors are kept at cryogenic temperatures to obtain the sensitivity necessary to measure faint energy sources. The Focal Plane Electronics (FPE) that sample the detector, generate packets from the samples, and transmit these packets to the processing electronics must dissipate little power in order to help keep the detectors at these cold temperatures. Separating the low powered front-end electronics from the higher-powered processing electronics, and using a simple high-speed protocol to transmit the detector data minimize the power dissipation near the detectors. Low Voltage Differential Signaling (LVDS) drivers were considered an obvious choice for physical layer because of their high speed and low power. The mechanical restriction on the number cables across the thermal interface force the Image packets to be concentrated upon two high-speed links. These links connect the many image packet sources, Focal Plane Electronics (FPE), located near the cryogenic detectors to the processing electronics on the spacecraft structure. From 12 to 10,000 seconds of raw data are processed to make up an image, various algorithms integrate the pixel data Loss of commands to configure the detectors as well as the loss of science data itself may cause inefficiency in the use of the telescope that are unacceptable given the high cost of the observatory. This combination of requirements necessitates a redundant, fault tolerant, high- speed, low mass, low power network with a low Bit error Rate(1E-9- 1E-12). The ISIM systems team performed many studies of the various network architectures that meeting these requirements. The architecture selected uses the Spacewire protocol, with the addition of a new transport and network layer added to implement end-to-end reliable transport. The network and reliable transport mechanism must be implemented in hardware because of the high average information rate and the restriction on the ability of the detectors to buffer data due to power and size restrictions. This network and transport mechanism was designed to be compatible with existing Spacewire links and routers so that existing equipment and designs may be leveraged upon. The transport layer specification is being coordinated with European Space Agency (ESA), Spacewire Working Group and the Consultative Committee for Space Data System (CCSDS) PlK Standard Onboard Interface (SOIF) panel, with the intent of developing a standard for reliable transport for Spacewire. Changes to the protocol presented are likely since negotiations are ongoing with these groups. A block of RTL VHDL that implements a multi-port Spacewire router with an external user interface will be developed and integrated with an existing Spacewire Link design. The external user interface will be the local interface that sources and sinks packets onto and off of the network (Figure 3). The external user interface implements the network and transport layer and handles acknowledgements and re-tries of packets for reliable transport over the network. Because the design is written in RTL, it may be ported to any technology but will initially be targeted to the new Actel Accelerator series (AX) part. Each link will run at 160 Mbps and the power will be about 0.165 Watt per link worst case in the Actel AX.

Rakow, Glenn↗
NASA NTRS2004

On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications

Differential Evolution (DE) is a simple and robust evolutionary strategy that has been provEn effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. Several approaches that have proven effective for other evolutionary algorithms are modified and implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for standard test optimization problems and for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.

Madavan, Nateri K.↗
DOE OSTI2025

Generative AI models for learning flow maps of stochastic dynamical systems in bounded domains

Simulating stochastic differential equations (SDEs) in bounded domains, presents significant computational challenges due to particle exit phenomena, which requires accurate modeling of interior stochastic dynamics and boundary interactions. Despite the success of machine learning-based methods in learning SDEs, existing learning methods are not applicable to SDEs in bounded domains because they cannot accurately capture the particle exit dynamics. We present a unified hybrid data-driven approach that combines a conditional diffusion model with an exit prediction neural network to capture both interior stochastic dynamics and boundary exit phenomena. Our ML model consists of two major components: a neural network that learns exit probabilities using binary cross-entropy loss with rigorous convergence guarantees, and a training-free diffusion model that generates state transitions for non-exiting particles using closed-form score functions. The two components are integrated through a probabilistic sampling algorithm that determines particle exit at each time step and generates appropriate state transitions. Here, the performance of the proposed approach is demonstrated via three test cases: a one-dimensional simplified problem for theoretical verification, a two-dimensional advection-diffusion problem in a bounded domain, and a three-dimensional problem of interest to magnetically confined fusion plasmas.

Bounded domains↗
DOE OSTI2025

Computing Nonequilibrium Responses with Score-Shifted Stochastic Differential Equations

Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used to interpret experiments and shed light on microscopic dynamics. For nonequilibrium systems, perturbations cannot be interpreted simply by monitoring fluctuations in a conjugate observable and general response results rely on path ensemble averaging. Furthermore, these techniques do not apply to perturbations that affect the diffusion tensor in a stochastic system. Here, we introduce an “effective” physical process that represents the diffusion perturbed dynamics and enables accurate calculations of responses to a change in the diffusion. Interestingly, the effective dynamics contain an additional drift involving the instantaneous “score” of the system, and we leverage score matching algorithms to carry out nonequilibrium response calculations on systems for which the exact stationary distribution is unknown.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Three-Dimensional Reconstruction Algorithm for Scanning Transmission Electron Microscopy Data from a Single Sample Orientation

Abstract Increasing interest in three-dimensional nanostructures adds impetus to electron microscopy techniques capable of imaging at or below the nanoscale in three dimensions. We present a reconstruction algorithm that takes as input a focal series of four-dimensional scanning transmission electron microscopy (4D-STEM) data. We apply the approach to a lead iridate, PbIrO, and yttrium-stabilized zirconia, YZrO, heterostructure from data acquired with the specimen in a single plan-view orientation, with the epitaxial layers stacked along the beam direction. We demonstrate that Pb–Ir atomic columns are visible in the uppermost layers of the reconstructed volume. We compare this approach to the alternative techniques of depth sectioning using differential phase contrast scanning transmission electron microscopy (DPC-STEM) and multislice ptychographic reconstruction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Jet-hadron correlations with respect to the event plane in $\sqrt{s_{NN}}$ = 200 GeV Au + Au collisions in STAR

Angular distributions of charged particles relative to jet axes are studied in $\sqrt{s_{NN}}$ = 200 GeV Au+Au collisions as a function of the jet orientation with respect to the event plane. This differential study tests the expected path-length dependence of energy loss experienced by a hard-scattered parton as it traverses the hot and dense medium formed in heavy-ion collisions. A second-order event plane is used in the analysis as an experimental estimate of the reaction plane formed by the collision impact parameter and the beam direction. Charged-particle jets with 15 < 𝑝 T,jet < 20 and 20 < 𝑝 T,jet < 40 ⁢GeV/𝑐 were reconstructed with the anti-𝑘 T algorithm with radius parameter setting of 𝑅 = 0.4 in the 20–50% centrality bin to maximize the initial-state eccentricity of the interaction region. The reaction plane fit method is implemented to remove the flow-modulated background with better precision than prior methods. Yields and widths of jet-associated charged-hadron distributions are extracted in three angular bins between the jet axis and the event plane. The event-plane (EP) dependence is further quantified by ratios of the associated yields in different EP bins. No dependence on orientation of the jet axis with respect to the event plane is seen within the uncertainties in the kinematic regime studied. This finding is consistent with a similar experimental observation by ALICE in $\sqrt{s_{NN}}$ = 2.76 TeV Pb-Pb collision data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1993

Accurate computation and continuation of homoclinic and heteroclinic orbits for singular perturbation problems

In earlier papers, Doedel and the authors have developed a numerical method and derived error estimates for the computation of branches of heteroclinic orbits for a system of autonomous ordinary differential equations in R(exp n). The idea of the method is to reduce a boundary value problem on the real line to a boundary value problem on a finite interval by using a local (linear or higher order) approximation of the stable and unstable manifolds. A practical limitation for the computation of homoclinic and heteroclinic orbits has been the difficulty in obtaining starting orbits. Typically these were obtained from a closed form solution or via a homotopy from a known solution. Here we consider extensions of our algorithm which allow us to obtain starting orbits on the continuation branch in a more systematic way as well as make the continuation algorithm more flexible. In applications, we use the continuation software package AUTO in combination with some initial value software. The examples considered include computation of homoclinic orbits in a singular perturbation problem and in a turbulent fluid boundary layer in the wall region problem.

Vaughan, William W.↗
NASA NTRSDate not supplied

IMUFDIR Tuning In Response To Structural Deformation Of The Orion Capsule

During system level Thermal Vacuum (TVAC) testing it was discovered that the pressure differential of the crew cabin in a vacuum would deflect the capsule slightly, causing significant misalignment of Orion’s three Inertial Measurement Units (IMUs). This phenomenon has been likened to a balloon expanding. When this misalignment was modeled in simulation as a function of atmospheric pressure, it was determined that the rate of deflection on reentry was significant enough to cause a mis-compare of the angular rates measured by the IMUs. This mis-comparison of the rates caused Orion’s Fault Detection Isolation and Recovery (FDIR) algorithm to falsely fail one of the IMUs. This manuscript will discuss how the IMUFDIR algorithm was detuned to be insensitive to these ballooning effects, while still meeting FDIR requirements to capture real faults in an IMU. All testing to validate this detuning was performed in a Six Degree of Freedom (6 DOF) Monte Carlo Simulation Environment.

Nicholas Rahaim↗
DOE OSTI2021

A general approach to seismic inversion with automatic differentiation

Imaging Earth structure or seismic sources from seismic data involves minimizing a target misfit function, and is commonly solved through gradient-based optimization. The adjoint-state method has been developed to compute the gradient efficiently; however, its implementation can be time-consuming and difficult. We develop a general seismic inversion framework to calculate gradients using reverse-mode automatic differentiation. The central idea is that adjoint-state methods and reverse-mode automatic differentiation are mathematically equivalent. Here, the mapping between numerical PDE simulation and deep learning allows us to build a seismic inverse modeling library, ADSeismic, based on deep learning frameworks, which supports high performance reverse-mode automatic differentiation on CPUs and GPUs. We demonstrate the performance of ADSeismic on inverse problems related to velocity model estimation, rupture imaging, earthquake location, and source time function retrieval. ADSeismic has the potential to solve a wide variety of inverse modeling applications within a unified framework.

58 GEOSCIENCES↗
NASA NTRS2023

The Earth in Living Color - NASA’s Surface Biology and Geology Designated Observable

The Surface Biology and Geology (SBG) Designated Observable will transform our understanding of the global land surface, inland and coastal aquatic ecosystems through visible-to-shortwave infra-red imaging (VSWIR) spectroscopy and thermal infra-red (TIR) imaging. SBG is one of four high-priority observables recommended in the 2017 NASA Earth Science Decadal Survey t o address science questions on vegetation and aquatic ecosystem health, snow-cover dynamics, volcanic activity, and minerology. With a planned launch readiness date of 2028, SBG is currently in Pre-Phase A, with Level 1 requirements being developed for a two-spacecraft architecture, including an additional constellation pathfinder. The recommended architecture emerged from an extensive study (2018-2021) that engaged the research and applications community to consider the science questions and measurement objectives of the Decadal Survey. A Science and Applications Traceability Matrix was used as a basis for scoring candidate architectures, with inputs from four working groups that covered algorithms, applications, calibration and validation, and modeling. Two pathfinder studies, Modeling End-to-End Traceability in support of SBG (MEET-SBG) and Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) are providing pre-launch modeling tools and data for algorithm development to support science value trades. The architecture consists of one spacecraft hosting a wide-swath VSWIR imaging spectrometer providing 30-m ground-sample distance (GSD), a spectral range of 380-2500 nm (at 10 nm resolution), 16-day revisit with 400 signal-to-noise for VNIR and 250 for SWIR (at 25% reflectance). A separate spacecraft will host a wide swath thermal imager, with five to seven bands placed between 4-12 μm), with 60-m (GSD), 3- day revisit, and 0.2K noise-equivalent differential temperature (NeDT). A VNIR compact camera will be hosted on the TIR spacecraft to enable coincident TIR and VNIR observations. A constellation pathfinder will evaluate options for enabling VSWIR mission continuity using Small Sats or data buys. Partnerships with international space agencies contribute technology as well as improvements to temporal revisit. SBG, when launched, will be the first dedicated mission collecting the full spectra of the Earth’s ‘living color’ and will play a critical role in NASA’s Earth System Observatory.

David S Schimel↗
DOE OSTI2022

Autoregressive Neural Network for Simulating Open Quantum Systems via a Probabilistic Formulation

The theory of open quantum systems lays the foundation for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of simulating open quantum systems calls for the development of strategies to approximate their dynamics. In this Letter, we present an approach for tackling open quantum system dynamics. Using an exact probabilistic formulation of quantum physics based on positive operator-valued measure, we compactly represent quantum states with autoregressive neural networks; such networks bring significant algorithmic flexibility due to efficient exact sampling and tractable density. We further introduce the concept of string states to partially restore the symmetry of the autoregressive neural network and improve the description of local correlations. Efficient algorithms have been developed to simulate the dynamics of the Liouvillian superoperator using a forward-backward trapezoid method and find the steady state via a variational formulation. Our approach is benchmarked on prototypical one-dimensional and two-dimensional systems, finding results which closely track the exact solution and achieve higher accuracy than alternative approaches based on using Markov chain Monte Carlo method to sample restricted Boltzmann machines. Our Letter provides general methods for understanding quantum dynamics in various contexts, as well as techniques for solving high-dimensional probabilistic differential equations in classical setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1997

Enhanced Multiobjective Optimization Technique for Comprehensive Aerospace Design

A multidisciplinary design optimization procedure which couples formal multiobjectives based techniques and complex analysis procedures (such as computational fluid dynamics (CFD) codes) developed. The procedure has been demonstrated on a specific high speed flow application involving aerodynamics and acoustics (sonic boom minimization). In order to account for multiple design objectives arising from complex performance requirements, multiobjective formulation techniques are used to formulate the optimization problem. Techniques to enhance the existing Kreisselmeier-Steinhauser (K-S) function multiobjective formulation approach have been developed. The K-S function procedure used in the proposed work transforms a constrained multiple objective functions problem into an unconstrained problem which then is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Weight factors are introduced during the transformation process to each objective function. This enhanced procedure will provide the designer the capability to emphasize specific design objectives during the optimization process. The demonstration of the procedure utilizes a computational Fluid dynamics (CFD) code which solves the three-dimensional parabolized Navier-Stokes (PNS) equations for the flow field along with an appropriate sonic boom evaluation procedure thus introducing both aerodynamic performance as well as sonic boom as the design objectives to be optimized simultaneously. Sensitivity analysis is performed using a discrete differentiation approach. An approximation technique has been used within the optimizer to improve the overall computational efficiency of the procedure in order to make it suitable for design applications in an industrial setting.

Chattopadhyay, Aditi↗
NASA NTRS2001

Configural Scoring of Simulator Sickness, Cybersickness and Space Adaptation Syndrome: Similarities and Differences?

From a survey of ten U.S. Navy flight simulators a large number (N > 1,600 exposures) of self-reports of motion sickness symptomatology were obtained. Using these data, scoring algorithms were derived, which permit examination of groups of individuals that can be scored either for 1) their total sickness experience in a particular device; or, 2) according to three separable symptom clusters which emerged from a Factor Analysis. Scores from this total score are found to be proportional to other global motion sickness symptom checklist scores with which they correlate (r = 0.82). The factors that surfaced from the analysis include clusters of symptoms referable as nausea, oculomotor disturbances, and disorientation (N, 0, and D). The factor scores may have utility in differentiating the source of symptoms in different devices. The present chapter describes our experience with the use of both of these types of scores and illustrates their use with examples from flight simulators, space sickness and virtual environments.

Kennedy, Robert S.↗
NASA NTRS1983

Close-mode identification performance of the ITD algorithm

Results of Monte Carlo numerical simulations conducted to study the close-mode performance of the Ibrahim Time-Domain (ITD) modal identification algorithm are presented. The ITD technique is a matrix eigensolution method for obtaining structural modal parameters directly from free-response test data without using the FFT. Thus, the well-known resolution and leakage limitations of the FFT procedure, that are particularly significant with short records, are avoided. As an example, one of several experimental data analyses where close modes have been accurately identified using very short records is shown. Although the identification scatter is found to increase as the square of reductions in frequency separation at small separations, the ability to differentiate modes spaced at fractions of the FFT resolution is substantiated.

Pappa, R. S.↗