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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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DOE OSTI2026

Adaptive Computing (AC) (Open Source) [SWR-24-106]

The Adaptive Computing (AC) software stack supports goal-based computing, for which a simulation workload is created on the fly, adapting to the results of calculations. Application-specific code defines an objective, which may be to solve an optimization problem or to train a surrogate model with minimal uncertainty. Then, the AC driver decides where in the design parameter space to run simulations to best achieve that objective. This process is iterative and online; as new data is returned from simulations, the AC driver chooses new simulations to run. The AC driver can strategically run simulations on distributed hardware resources (including high performance computing machines, cloud resources, and edge devices) to maximize throughput and obey resource constraints.

Griffin, Kevin [National Laboratory of the Rockies↗

DOE OSTI2024

Human Liver Epithelium Response to HCoV-229E Infection Epigenomics (ACS-DP4)

The purpose of this experiment was to evaluate how wild-type Human coronavirus strain 229E (HCoV-229E) infection alters chromatin accessibility in infected cells only. Sample data was obtained for mock and infected (standard and UV-inactivated) immortalized human liver cells (HuH-7) and collected 24 hrs. post infection. Samples were processed using assay for transposase-accessible chromatin using high-throughput sequencing (ATAC-Seq) and generated bar coded library samples were evaluated for RNA sequencing (RNA-Seq) expression analysis. Processed ATAC-Seq datasets are openly accessible from the download button and contain secondary processed RNA-Seq results files and supporting metadata materials. Data download includes a sample naming key, infection titer metadata, normalized counts, and relevant computational source code information supporting data transparency and reuse.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

MarpoDB: An open registry for Marchantia polymorpha genetic parts

Marchantia polymorpha is an extant relative of the earliest terrestrial plants and has attracted a substantial interest as a model organism for evolutionary and developmental studies. Given its relatively simple genome, compact gene families, simple morphology, ease of propagation and transformation, M. polymorpha is becoming a promising platform for plant synthetic biology. Modular genetic parts have been essential for development of synthetic biology approaches, so we sought to design an engineering oriented database for M. polymorpha genetic parts where each gene is a standalone functional unit. MarpoDB is a database of M. polymorpha genes and genetic parts, which is tailored to become an integral tool for a synthetic biology workflow. Among its features are precompiled cross-database querying to InterPro, Pfam signatures and non-redundant Viridiplantae BLAST annotations; BLAST querying to M. polymorpha genes; sequence export in GenBank format; recoding of sequences to the common syntax for type IIS assembly and exchange of DNA parts; and a minimalistic, intuitive and interactive user interface for gene models and sequence exploration. Furthermore, we have implemented user input to encourage feedback, collaboration and exchange between the MarpoDB community. MarpoDB source-code is released on GitHub to promote development of computational tools for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Computing the Properties of Matter with Leadership Computing Resources (Closeout Report for DE-SC0018121)

In order to add more capabilities to Halide, we have designed a new framework called Tiramisu and integrated this framework into Halide. Since Tiramisu enables Halide to target heterogeneous architectures, our development efforts have been refocused on Tiramisu. Most high-performance computer systems today are complex and increasingly heterogeneous; they may have CPUs, GPUs and FPGAs. Achieving best performance requires taking full advantage of all these different architectures. To address this issue, we have designed Tiramisu, an optimization framework that enables Halide (and other DSLs) to target heterogeneous architectures. Tiramisu is an optimization framework that takes as input a high level, architecture-independent representation of code and a set of scheduling and data mapping commands that guide code transformation. The input can either be generated by a domain-specific language (DSL) compiler such as Halide or directly written by a programmer. Tiramisu then applies the user-specified code and data-layout transformations and generates an architecture-specific, low-level intermediate representation (IR) that takes advantage of modern architectural features such as multicore parallelism, non-uniform memory (NUMA) hierarchies, clusters, and accelerators like GPUs and FPGAs. We integrated Tiramisu within Halide and implemented a representative set of benchmarks to evaluate this integration. Tiramisu is now open source and is available for public use (http://tiramisu-compiler.org/). A paper about Tiramisu was published, it shows that Tiramisu extends Halide with many new capabilities and that Tiramisu can generate efficient code for multicores, GPUs, FPGAs and distributed heterogeneous systems. The performance of code generated by the Tiramisu backends matches or exceeds hand optimized reference implementations. For example, the multicore backend matches the highly optimized Intel MKL library on many kernels and shows speedups reaching 4x over the original Halide. In addition to making Tiramisu more robust, we have used Tiramisu to implement a set of representative tensor operation for constructing baryon building blocks required for multi baryon contractions in LQCD. In order to implement this code, we needed to generalize Tiramisu in two ways: first we needed to support indirect array accesses, and second, we needed to add support for complex numbers to Tiramisu. The code generated by Tiramisu is 6x faster than the reference code. Our efforts towards an MPI based multi-node version of tiramisu have matured and the resulting code scales well on multiple nodes (tests up to 512 KNL nodes have been undertaken).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Ocean power technology design optimization

For this study, the National Renewable Energy Laboratory and Ocean Power Technologies (OPT) conducted a collaborative code validation and design optimization study for OPT's PowerBuoy wave energy converter (WEC). NREL utilized WEC-Sim, an open-source WEC simulator, to compare four design variations of OPT's PowerBuoy. As an input to the WEC-Sim models, viscous drag coefficients for the PowerBuoy floats were first evaluated using computational fluid dynamics. The resulting WEC-Sim PowerBuoy models were then validated with experimental power output and fatigue load data provided by OPT. The validated WEC-Sim models were then used to simulate the power performance and loads for operational conditions, extreme conditions, and directional waves, for each of the four PowerBuoy design variations, assuming the wave environment of Humboldt Bay, California. And finally, ratios of power-to-weight, power-to-fatigue-load, power-to-maximum-extreme-load, power-to-water-plane-area, and power-to-wetted-surface-area were used to make a final comparison of the potential PowerBuoy WEC designs. Lastly, the design comparison methodologies developed and presented in this study are applicable to other WEC devices and may be useful as a framework for future WEC design development projects.

16 TIDAL AND WAVE POWER↗

DOE OSTI2022

Turbulent broadening of electron heat-flux width in electromagnetic gyrokinetic simulations of a helical scrape-off layer model

Here, we demonstrate that cross field transport in the scrape-off layer (SOL) can be moderately increased by electromagnetic effects in high-beta regimes, resulting in broadening of the electron heat-flux width on the endplates. This conclusion is taken from full- f electromagnetic gyrokinetic simulations of a helical SOL model that roughly approximates the SOL of the National Spherical Torus Experiment. The simulations have been performed with the Gkeyll code, which recently became the first code to demonstrate the capability to simulate electromagnetic gyrokinetic turbulence on open magnetic field lines with sheath boundary conditions. We scan the source rate and thus β, so that the normalized pressure gradient (the MHD ballooning parameter $α ∝ ∂β/∂r ∝ β/Lρ$) is scanned over an experimentally relevant range, α = 0.3 - 1.5. While there is little change in the pressure gradient scale length L p near the midplane as beta is increased, a 10% increase in cross field transport near the midplane results in an increase in the electron heat-flux width λ q and a 25% reduction of the peak electron heat flux to the endplates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Parallel k-means Clustering of Geospatial Data Sets Using Manycore CPU Architectures

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery and mining of weather, climate, ecological, and other geoscientific data sets fused from disparate sources. Many of the standard tools used on individual workstations are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of parallelism available in state-of-the-art high-performance computing platforms can enable such analysis. Here, we describe pKluster, an open-source tool we have developed for accelerated k-means clustering of geospatial and geospatiotemporal data, and discuss algorithmic modifications and code optimizations we have made to enable it to effectively use parallel machines based on novel CPU architectures—such as the Intel “Knights Landing” Xeon Phi and Skylake Xeon processors—with many cores and hardware threads, and employing significant single instruction, multiple data (SIMD) parallelism. We outline some applications of the code in ecology and climate science contexts and present a detailed discussion of the performance of the code for one such application, LiDAR-derived vertical vegetation structure classification.

Mills, Richard T↗

DOE OSTI2015

Digital Image Correlation Engine v.3.0

DICe is an open source digital image correlation (DIC) tool intended for use as a module in an external application or as a standalone analysis code. It's primary capability is computing full-field displacements and strains from sequences of digital These images are typically of a material sample undergoing a materials characterization experiment, but DICe is also useful for other applications (for example, trajectory tracking). DICe is machine portable (Windows, Linux and Mac) and can be effectively deployed on a high performance computing platform. Capabilities from DICe can be invoked through a library interface, via source code integration of DICe classes or through a graphical user interface.

Turner, Dan↗

DOE OSTI2018

Concepts and Meta-Programming Library

CAMP provides a portable optimized implementation of template meta-programming primitives. All capabilities found within are available in other open source projects, including metal and mpl among others, but no other library we know of supports all compilers required by LLNL codes. CAMP serves as an efficient facility for writing portable compile-time operations in C++ codes. It was developed as part of the RAJA project to facilitate more complex compile-time introspection and better error message delivery to users, but has since proven useful in Umpire, CHAI and other pre-release LLNL software projects and is thus being re-factored to stand alone. The CAMP library uses portable C++ template mechanisms almost exclusively, with the exception of intrinsics provided for performance by some compilers such as clang and gee. There are no private or protected interfaces and no proprietary information included in the source. Any and all future versions will limit themselves to implementing commonly available and well known primitives for compile-time manipulation of types. A new public github repository will be created to host the code independent of its current location in the raja repository, likely at github.com/llnl/camp.

Kunen, AdamJ.↗

DOE OSTI2017

The Yale–Potsdam Stellar Isochrones

We introduce the Yale–Potsdam Stellar Isochrones (YaPSI), a new grid of stellar evolution tracks and isochrones of solar-scaled composition. In an effort to improve the Yonsei–Yale database, special emphasis is placed on the construction of accurate low-mass models (M{sub ∗}<0.6 M{sub ⊙}), and in particular on their mass–luminosity and mass–radius relations, both crucial for characterizing exoplanet-host stars, and, in turn, their planetary systems. The YaPSI models cover the mass range 0.15–5.0 M{sub ⊙} densely enough to permit detailed interpolation in mass, and the metallicity and helium abundance ranges [Fe/H] = −1.5 to +0.3 and Y {sub 0} = 0.25–0.37 are specified independently of each other (i.e., no fixed ΔY/ΔZ relation is assumed). The evolutionary tracks are calculated from the pre-main sequence up to the tip of the red giant branch. The isochrones, with ages between 1 Myr and 20 Gyr, provide UBVRI colors in the Johnson–Cousins system, and JHK colors in the homogenized Bessell and Brett system, derived from two different semi-empirical T{sub eff}–color calibrations from the literature. We also provide utility codes, such as an isochrone interpolator, in age, metallicity, and helium content, and an interface of the tracks with an open-source Monte Carlo Markov-Chain tool for the analysis of individual stars. Finally, we present comparisons of the YaPSI models with the best empirical mass–luminosity and mass–radius relations available to date, as well as isochrone fitting of well-studied stellar clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

The FluxCompensator: Making Radiative Transfer Models of Hydrodynamical Simulations Directly Comparable to Real Observations

When modeling astronomical objects throughout the universe, it is important to correctly treat the limitations of the data, for instance finite resolution and sensitivity. In order to simulate these effects, and to make radiative transfer models directly comparable to real observations, we have developed an open-source Python package called the FluxCompensator that enables the post-processing of the output of 3D Monte Carlo radiative transfer codes, such as Hyperion. With the FluxCompensator, realistic synthetic observations can be generated by modeling the effects of convolution with arbitrary point-spread functions, transmission curves, finite pixel resolution, noise, and reddening. Pipelines can be applied to compute synthetic observations that simulate observatories, such as the Spitzer Space Telescope or the Herschel Space Observatory . Additionally, this tool can read in existing observations (e.g., FITS format) and use the same settings for the synthetic observations. In this paper, we describe the package as well as present examples of such synthetic observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Dynamic modeling and simulation of pressure swing adsorption processes using toPSAil

Pressure swing adsorption (PSA) has attracted significant recent interest for chemical process intensification due to its potential for high energy efficiency and amenability to small, modular designs. However, the lack of simulation tools that are readily available, transparent, and trusted, has been identified as a serious impediment to widespread adoption of PSA, as well as to further research on PSA modeling, numerical solution, optimization, and control. This paper presents a complete framework for dynamic modeling and simulation of PSA processes and its implementation in an open-source simulator called toPSAil. Further, the presentation is tutorial and includes many modeling and implementation details often overlooked in existing literature. Novel methods are presented for handling flow reversals and implementing various pressure–flow relationships, along with controlled boundary conditions. Finally, the code contains several innovations designed to improve efficiency and reduce the extensive trial-and-error tuning often required to produce a working PSA cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

A minimally-dissipative low-Mach number solver for complex reacting flows in Open$\mathrm{FOAM}$

Large eddy simulation (LES) has become the de-facto computational tool for modeling complex reacting flows, especially in gas turbine applications. However, readily usable general-purpose LES codes for complex geometries are typically academic or proprietary/commercial in nature. In this report the objective is to develop and disseminate an open source LES tool for low-Mach number turbulent combustion using the OpenFOAM framework. In particular, a collocated-mesh approach suited for unstructured grid formulation is provided. Unlike other fluid dynamics models, LES accuracy is intricately linked to so-called primary and secondary conservation properties of the numerical discretization schemes. This implies that although the solver only evolves equations for mass, momentum, and energy, the implied discrete equation for kinetic energy (square of velocity) should be minimally-dissipative. Here, a specific spatial and temporal discretization is imposed such that this kinetic energy dissipation is minimized. The method is demonstrated using manufactured solutions approach on regular and skewed meshes for a canonical flow and a lab-scale turbulent flow problem.

42 ENGINEERING↗

DOE OSTI2023

DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models

We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

pyFEHM

PyFEHM is an open-source Python library that provides classes and methods to support a scripting environment for the subsurface heat and mass transfer, and geomechanics code FEHM. It is inspired by a similar library, PyTOUGH, available for use with the TOUGH2 family of codes.

Dempsey, David↗

DOE OSTI2017

XFEMParaviewPlugin

The XFEMClipPartialElements tool is a plugin for the open-source Paraview visualization software to correctly visualize results with discontinuities represented using the extended finite element method (XFEM) in MOOSE-based codes.

Spencer, Ben↗

DOE OSTI2017

Branson: A Mini-App for Studying Parallel IMC, Version 1.0

This code solves the gray thermal radiative transfer (TRT) equations in parallel using simple opacities and Cartesian meshes. Although Branson solves the TRT equations it is not designed to model radiation transport: Branson contains simple physics and does not have a multigroup treatment, nor can it use physical material data. The opacities have are simple polynomials in temperature there is a limited ability to specify complex geometries and sources. Branson was designed only to capture the computational demands of production IMC codes, especially in large parallel runs. It was also intended to foster collaboration with vendors, universities and other DOE partners. Branson is similar in character to the neutron transport proxy-app Quicksilver from LLNL, which was recently open-sourced.

Long, Alex↗

DOE OSTI2017

Branson: A Mini-App for Studying Parallel IMC, Version 1.0

Long, Alex↗