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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Brightest cluster galaxies trace weak lensing mass bias and halo triaxiality in the three hundred project

Galaxy clusters have a triaxial matter distribution. The weak-lensing signal, an important part in cosmological studies, measures the projected mass of all matter along the line of sight, and therefore changes with the orientation of the cluster. Studies suggest that the shape of the brightest cluster galaxy (BCG) in the centre of the cluster traces the underlying halo shape, enabling a method to account for projection effects. We use 324 simulated clusters at four redshifts between 0.1 and 0.6 from ‘The Three Hundred Project’ to quantify correlations between the orientation and shape of the BCG and the halo. We find that haloes and their embedded BCGs are aligned, with an average ~20 degree angle between their major axes. The bias in weak lensing cluster mass estimates correlates with the orientation of both the halo and the BCG. Mimicking observations, we compute the projected shape of the BCG, as a measure of the BCG orientation, and find that it is most strongly correlated to the weak-lensing mass for relaxed clusters. We also test a 2D cluster relaxation proxy measured from BCG mass isocontours. The concentration of stellar mass in the projected BCG core compared to the total stellar mass provides an alternative proxy for the BCG orientation. We find that the concentration does not correlate to the weak-lensing mass bias, but does correlate with the true halo mass. Here, these results indicate that the BCG shape and orientation for large samples of relaxed clusters can provide information to improve weak-lensing mass estimates.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A Verified Optimizer for Quantum Circuits

We present VOQC, the first verified optimizer for quantum circuits, written using the Coq proof assistant. Quantum circuits are expressed as programs in a simple, low-level language called SQIR, a small quantum intermediate representation, which is deeply embedded in Coq. Optimizations and other transformations are expressed as Coq functions, which are proved correct with respect to a semantics of SQIR programs. SQIR programs denote complex-valued matrices, as is standard in quantum computation, but we treat matrices symbolically to reason about programs that use an arbitrary number of quantum bits. SQIR’s careful design and our provided automation make it possible to write and verify a broad range of optimizations in VOQC, including full-circuit transformations from cutting-edge optimizers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Multiscale Modeling of Nanoparticle Precipitation in Oxide Dispersion-Strengthened Steels Produced by Laser Powder Bed Fusion

Laser Powder Bed Fusion (LPBF) enables the efficient production of near-net-shape oxide dispersion-strengthened (ODS) alloys, which possess superior mechanical properties due to oxide nanoparticles (e.g., yttrium oxide, Y-O, and yttrium-titanium oxide, Y-Ti-O) embedded in the alloy matrix. To better understand the precipitation mechanisms of the oxide nanoparticles and predict their size distribution under LPBF conditions, we developed an innovative physics-based multiscale modeling strategy that incorporates multiple computational approaches. These include a finite volume method model (Flow3D) to analyze the temperature field and cooling rate of the melt pool during the LPBF process, a density functional theory model to calculate the binding energy of Y-O particles and the temperature-dependent diffusivities of Y and O in molten 316L stainless steel (SS), and a cluster dynamics model to evaluate the kinetic evolution and size distribution of Y-O nanoparticles in as-fabricated 316L SS ODS alloys. The model-predicted particle sizes exhibit good agreement with experimental measurements across various LPBF process parameters, i.e., laser power (110–220 W) and scanning speed (150–900 mm/s), demonstrating the reliability and predictive power of the modeling approach. The multiscale approach can be used to guide the future design of experimental process parameters to control oxide nanoparticle characteristics in LPBF-manufactured ODS alloys. Additionally, our approach introduces a novel strategy for understanding and modeling the thermodynamics and kinetics of precipitation in high-temperature systems, particularly molten alloys.

Wang, Zhengming (ORCID:0000000241627112)↗

NASA NTRS1991

Adhesion at metal interfaces

A basic adhesion process is defined, the theory of the properties influencing metallic adhesion is outlined, and theoretical approaches to the interface problem are presented, with emphasis on first-principle calculations as well as jellium-model calculations. The computation of the energies of adhesion as a function of the interfacial separation is performed; fully three-dimensional calculations are presented, and universality in the shapes of the binding energy curves is considered. An embedded-atom method and equivalent-crystal theory are covered in the framework of issues involved in practical adhesion.

Banerjea, Amitava↗

NASA NTRS2004

Verifying Diagnostic Software

Livingstone PathFinder (LPF) is a simulation-based computer program for verifying autonomous diagnostic software. LPF is designed especially to be applied to NASA s Livingstone computer program, which implements a qualitative-model-based algorithm that diagnoses faults in a complex automated system (e.g., an exploratory robot, spacecraft, or aircraft). LPF forms a software test bed containing a Livingstone diagnosis engine, embedded in a simulated operating environment consisting of a simulator of the system to be diagnosed by Livingstone and a driver program that issues commands and faults according to a nondeterministic scenario provided by the user. LPF runs the test bed through all executions allowed by the scenario, checking for various selectable error conditions after each step. All components of the test bed are instrumented, so that execution can be single-stepped both backward and forward. The architecture of LPF is modular and includes generic interfaces to facilitate substitution of alternative versions of its different parts. Altogether, LPF provides a flexible, extensible framework for simulation-based analysis of diagnostic software; these characteristics also render it amenable to application to diagnostic programs other than Livingstone.

Lindsey, Tony↗

NASA NTRS2013

Photosynthesis-dependent Isoprene Emission from Leaf to Planet in a Global Carbon-chemistry-climate Model

We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the FarquharBallBerry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50 of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 6496) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr1 that increases by 30 in the artificial absence of plant water stress and by 55 for potential natural vegetation.

photosynthesis↗

DOE OSTI2024

Development & Experimental Validation of a Generalized Resistance-Capacitance Model for Numerical Simulation of Phase-Change Material Embedded Heat Exchangers

Latent heat thermal energy storage (LHTES) using phase change material (PCM) has attracted increased attention as a viable solution for overcoming the mismatch between energy supply and demand for renewable energy-based systems. PCM-embedded heat exchangers (PCM-HX) have the potential to significantly improve thermal performance due to high storage capacity and low temperature variation during the phase change process. Most models for simulating LHTES heat transfer use Computational Fluid Dynamics (CFD) simulations, which have high computational costs resulting from considering the complex and time-dependent physics relevant to PCM-HXs. In this paper, a Generalized Resistance Capacitance-based Model (GRCM) was developed to predict the thermal performance of arbitrary PCM-HXs in a computationally efficient manner without compromising modeling accuracy. The GRCM is exercised for three case studies: (i) verification for a single-slabbed finned PCM-HX, (ii) verification and validation for a copper foam/paraffin composite PCM-HX, and (iii) validation for a straight tube annular finned PCM-HX. The copper foam PCM-HX uses an electric heater at the top of HX, while the other two configurations utilize water as heat transfer fluid. For the single-slabbed finned PCM-HX melting case, the mean deviation in average PCM temperature predicted by the GRCM compared to the CFD model was between 0.56 – 0.73 K, with maximum temperature deviation of 2.68 K. For the HTF outlet temperature, the validation results showed that GRCM prediction matches very well with experimental data, with mean temperature deviation of 0.24 K during melting case, while for solidification case was 0.34 K. These results showcase the GRCM’s capability for accurately reproducing the thermal characteristics of PCM-HXs with considerably lower computational effort.

42 ENGINEERING↗

DOE OSTI2021

EpitopeVec: linear epitope prediction using deep protein sequence embeddings

Motivation: B-cell epitopes (BCEs) play a pivotal role in the development of peptide vaccines, immuno-diagnostic reagents and antibody production, and thus in infectious disease prevention and diagnostics in general. Experimental methods used to determine BCEs are costly and time-consuming. Therefore, it is essential to develop computational methods for the rapid identification of BCEs. Although several computational methods have been developed for this task, generalizability is still a major concern, where cross-testing of the classifiers trained and tested on different datasets has revealed accuracies of 51–53%. Results: We describe a new method called EpitopeVec, which uses a combination of residue properties, modified antigenicity scales, and protein language model-based representations (protein vectors) as features of peptides for linear BCE predictions. Extensive benchmarking of EpitopeVec and other state-of-the-art methods for linear BCE prediction on several large and small datasets, as well as cross-testing, demonstrated an improvement in the performance of EpitopeVec over other methods in terms of accuracy and area under the curve. As the predictive performance depended on the species origin of the respective antigens (viral, bacterial and eukaryotic), we also trained our method on a large viral dataset to create a dedicated linear viral BCE predictor with improved cross-testing performance.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1998

A Domain-Decomposed Multi-Level Method for Adaptively Refined Cartesian Grids with Embedded Boundaries

The work presents a new method for on-the-fly domain decomposition technique for mapping grids and solution algorithms to parallel machines, and is applicable to both shared-memory and message-passing architectures. It will be demonstrated on the Cray T3E, HP Exemplar, and SGI Origin 2000. Computing time has been secured on all these platforms. The decomposition technique is an outgrowth of techniques used in computational physics for simulations of N-body problems and the event horizons of black holes, and has not been previously used by the CFD community. Since the technique offers on-the-fly partitioning, it offers a substantial increase in flexibility for computing in heterogeneous environments, where the number of available processors may not be known at the time of job submission. In addition, since it is dynamic it permits the job to be repartitioned without global communication in cases where additional processors become available after the simulation has begun, or in cases where dynamic mesh adaptation changes the mesh size during the course of a simulation. The platform for this partitioning strategy is a completely new Cartesian Euler solver tarcreted at parallel machines which may be used in conjunction with Ames' "Cart3D" arbitrary geometry simulation package.

Aftosmis, M. J.↗

DOE OSTI2026

Interpretable and flexible non-intrusive reduced-order models using reproducing kernel Hilbert spaces

This paper develops an interpretable, non-intrusive reduced-order modeling technique using regularized kernel interpolation. Existing non-intrusive approaches approximate the dynamics of a reduced-order model (ROM) by solving a data-driven least-squares regression problem for low-dimensional matrix operators. Our approach instead leverages regularized kernel interpolation, which yields an optimal approximation of the ROM dynamics from a user-defined reproducing kernel Hilbert space. We show that our kernel-based approach can produce interpretable ROMs whose structure mirrors full-order model structure by embedding judiciously chosen feature maps into the kernel. The approach is flexible and allows a combination of informed structure through feature maps and closure terms via more general nonlinear terms in the kernel. We also derive a computable a posteriori error bound that combines standard error estimates for intrusive projection-based ROMs and kernel interpolants. In conclusion, the approach is demonstrated in several numerical experiments that include comparisons to operator inference using both proper orthogonal decomposition and quadratic manifold dimension reduction.

Data-driven model reduction↗

DOE OSTI2026

The Extended Embedded Self-Shielding Method in SCALE 6.3/Polaris

The SCALE transport lattice code, Polaris, has been previously developed to generate few-group homogenized cross sections for whole-core nodal diffusion simulators in which the embedded self-shielding method (ESSM) is used for resonance self-shielding calculations to process cross sections. Although the ESSM capability has been very successful in light-water reactor analysis, it may require enhancements in computational efficiency; treatment of spatially dependent resonance self-shielding effects; and handling of interrelated resonance effects among fuel, cladding, and control rod materials. Therefore, this study focuses on improving computational efficiency by using a Dancoff-based Wigner–Seitz approximation combined with a material-based resonance categorization, through which a spatially dependent ESSM capability is developed to accurately estimate self-shielded cross sections inside the fuel. Benchmark results show that the new capability significantly enhances computational efficiency and accuracy for spatially dependent local zones within the fuel and through depletion.

ESSM↗

NASA NTRS1973

On the numerical simulation of three-dimensional transonic flow with application to the C-141 wing

Results computed by a finite-difference, relaxation algorithm are presented for the supercritical flow (M = 0.825) about the C-141 airplane wing, which has sweep, taper, and twist. Comparisons with both wind-tunnel and flight data indicate that computed solutions of the classical transonic small disturbance equation can accurately simulate high Reynolds number flows when the shock sweep angle is small. It is also shown that this equation poorly approximates the complete potential equation when embedded shock waves are swept at angles greater than about 15 deg. Hence, a more consistent small disturbance equation is derived for use in more general cases.

Lomax, H.↗

NASA NTRS1992

A numerical model for coupling between atomization and spray dynamics in liquid rocket thrust chambers

This paper describes a novel method of coupling the atomization and spray combustion processes encountered in coaxial injection elements of liquid rocket engine thrust chambers. This method is based on the Jet-Embedding technique in which the liquid jet core equations and the gas phase equations are solved separately. The liquid and gas phase solutions, however, are coupled through the boundary conditions at the interface between the phases. The computational grid for the gas phase calculations are adapted to the shape of the liquid jet core. The axial variation of droplet sizes are calculated using a stability analysis appropriate for the atomization regime of liquid jet breakup. The predictions of this method have been validated with experimental data on low speed water jets. Using this method, calculations are performed for the SSME fuel preburner single injector flow field. The results obtained are in good agreement with the predictions of the volume-of-fluid method.

Giridharan, M. G.↗

NASA NTRS2007

Arbitrating Control of Control and Display Units

The ARINC 739 Switch is a computer program that arbitrates control of two multi-function control and display units (MCDUs) between (1) a commercial flight-management computer (FMC) and (2) NASA software used in research on transport aircraft. (MCDUs are the primary interfaces between pilots and FMCs on many commercial aircraft.) This program was recently redesigned into a software library that can be embedded in research application programs. As part of the redesign, this software was combined with software for creating custom pages of information to be displayed on a CDU. This software commands independent switching of the left (pilot s) and right (copilot s) MCDUs. For example, a custom CDU page can control the left CDU while the FMC controls the right CDU. The software uses menu keys to switch control of the CDU between the FMC or a custom CDU page. The software provides an interface that enables custom CDU pages to insert keystrokes into the FMC s CDU input interface. This feature allows the custom CDU pages to manipulate the FMC as if it were a pilot.

Sugden, Paul C.↗

NASA NTRS2016

Cubesat Application for Planetary Entry (CAPE) Missions: Micro-Return Capsule (MIRCA)

The Cubesat Application for Planetary Entry Missions (CAPE) concept describes a high-performing Cubesat system which includes a propulsion module and miniaturized technologies capable of surviving atmospheric entry heating, while reliably transmitting scientific and engineering data. The Micro Return Capsule (MIRCA) is CAPE's first planetary entry probe flight prototype. Within this context, this paper briefly describes CAPE's configuration and typical operational scenario, and summarizes ongoing work on the design and basic aerodynamic characteristics of the prototype MIRCA vehicle. CAPE not only opens the door to new planetary mission capabilities, it also offers relatively low-cost opportunities especially suitable to university participation. In broad terms, CAPE consists of two main functional components: the "service module" (SM), and "CAPE's entry probe" (CEP). The SM contains the subsystems necessary to support vehicle targeting (propulsion, ACS, computer, power) and the communications capability to relay data from the CEP probe to an orbiting "mother-ship". The CEP itself carries the scientific instrumentation capable of measuring atmospheric properties (such as density, temperature, composition), and embedded engineering sensors for Entry, Descent, and Landing (EDL). The first flight of MIRCA was successfully completed on 10 October 2015 as a "piggy-back" payload onboard a NASA stratospheric balloon launched from Ft. Sumner, NM.

Cubesat↗

NASA NTRS2019

Computational Micromechanics Model for the Analysis of Fiber Kinking in Unidirectional FRP

A computational micromechanics (CMM) model is developed to analyze fiber kinking, which is a failure mechanism that takes place in fiber-reinforced composites when they are loaded under longitudinal compression. The CMM model consists of a single AS4 carbon fiber with an initial misalignment embedded in an 8552 polymer matrix. The deformation of the model is governed by periodic boundary conditions (PBC). The relatively simple CMM model enables the evaluation of the role played by initial misalignment of the fiber, shear yielding of the matrix and fiber-matrix debonding. A novel microscale experimental technique devoted to the characterization of the longitudinal compressive strength of the fibers, X(sup f)(sub c) , was developed. By exercising the model and comparing it with several existing models in the literature, the nonlinear shear response of the composite lamina was shown to play a fundamental role not only in the prediction of the compressive strength X(sub c), but also during the post-peak regime in terms of residual stress σ(sub r) and fiber rotation φ. Finally, the influence of the fiber-matrix interface damage (not considered in most other fiber kinking models) on the fiber kinking phenomenon was assessed through a parametric study.

Polymer-matrix composites (PMC)↗

DOE OSTI2026

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗

DOE OSTI2025

Active-noise-induced dynamic clustering of passive colloidal particles

Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive soft materials embedded within an active fluid into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active matter and nonequilibrium self-assembly. Here, we present a simple and efficient computational approach to model soft materials advected by active fluids, by simulating particles moving in a spatiotemporally correlated noise field. To illustrate our approach, we simulate the dynamical self-organization of repulsive colloids within such an active noise field. The colloids form structures whose sizes and dynamics can be tuned by the correlation time and length of the active fluid, and range from small rotating droplets to clusters with internal flows and system-spanning sizes that vastly exceed the active correlation length. Our results explain how the interplay between active fluid time and length scales and emergent driven assembly can be used to rationally design functional assemblies. More broadly, our approach can be used to efficiently simulate diverse active fluids and other systems with spatiotemporally correlated noise.

Brownian dynamics↗