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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33

Software-Defined Solutions for Managing Energy Use in Small to Medium Sized Commercial Buildings

The Project uses state-of-the-art computer science to extend the benefits of Building Automation Systems (BAS) typically found in large buildings (>100,000 square foot) to medium-sized commercial buildings (<50,000 sq ft). The BAS developed in this project, termed OpenBAS, uses an open-source and open software architecture platform, user interface, and plug-and-play control devices to facilitate adoption of energy efficiency strategies in the commercial building sector throughout the United States. At the heart of this “turn key” BAS is the platform with three types of controllers—thermostat, lighting controller, and general controller—that are easily “discovered” by the platform in a plug-and-play fashion. The user interface showcases the platform and provides the control system set-up, system status display and means of automatically mapping the control points in the system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Variability and associated uncertainty in image analysis for soiling characterization in solar energy systems

The accumulation of soiling on photovoltaic modules and on the mirrors of concentrating solar power systems causes non-negligible energy losses with economic consequences. These challenges can be mitigated, or even prevented, through appropriate actions if the magnitude of soiling is known. Particle counting analysis is a common procedure to characterize soiling, as it can be easily performed on micrographs of glass coupons or solar devices that have been exposed to the environment. Particle counting does not, however, yield invariant results across institutions. The particle size distribution analysis is affected by the operator of the image analysis software and the methodology utilized. The results of a round-robin study are presented in this work to explore and elucidate the uncertainty related to particle counting and its effect on the characterization of the soiling of glass surfaces used in solar energy conversion systems. An international group of soiling experts analyzed the same 8 micrographs using the same open-source ImageJ software package. The variation in the particle analyses results were investigated to identify specimen characteristics with the lowest coefficient of variation (CV) and the least uncertainty among the various operators. The mean particle diameter showed the lowest CV among the investigated characteristics, whereas the number of particles exhibited the largest CV. Additional parameters, such as the fractional area coverage by particles and parameters related to the distribution's shape yielded intermediate CV values. These results can provide insights on the magnitude inter-lab variability and uncertainty for optical and microscope-based soiling monitoring and characterization.

14 SOLAR ENERGY↗

Dynamics of Laterally Propagating Flames in X-Ray Bursts. II. Realistic Burning and Rotation

In this work, we continue to investigate two-dimensional laterally propagating flames in type I X-ray bursts using fully compressible hydrodynamics simulations. In the current study we relax previous approximations where we artificially boosted the flames. We now use more physically realistic reaction rates, thermal conductivities, and rotation rates, exploring the effects of neutron star rotation rate and thermal structure on the flame. We find that at lower rotation rates the flame becomes harder to ignite, whereas at higher rotation rates the nuclear burning is enhanced by increased confinement from the Coriolis force and the flame propagates steadily. At higher crustal temperatures, the flame moves more quickly and accelerates as it propagates through the atmosphere. If the temperature is too high, instead of a flame propagating across the surface the entire atmosphere burns uniformly. Our findings could have implications for the relationship between observed burst rise times and neutron star rotation and accretion rates. All of the software used for these simulations is freely available.

79 ASTRONOMY AND ASTROPHYSICS↗

Fundamental Path Optimization Strategies for Extrusion-based Additive Manufacturing

Extrusion-based additive manufacturing processes begin with a software program, called a slicer, that generates layer geometry and fits toolpaths to each layer to define where material is to be extruded or deposited. Before the toolpaths are output as g-code for the additive manufacturing system to execute, the toolpaths should be optimized. Many complex optimization approaches using graph theory, Chinese postman problem, and other complex mathematical models exist, but these approaches are rarely used in daily printing operations and are not available through common slicing programs such as Cura and PrusaSlicer. Instead, path planning and optimization typically revolves around simpler, fully automated approaches such as inside out and next closest. This paper will explore the fundamental optimization strategies for toolpath planning and document a new implementation, available via open-source slicing software, that allows for greater control of the path planning process.

Roschli, Alex [ORNL] (ORCID:0000000213084632)↗

Running an open experiment: transparency and reproducibility in soil and ecosystem science

Researchers in soil and ecosystem science, and almost every other field, are being pushed--by funders, journals, governments, and their peers--to increase transparency and reproducibility of their work. A key part of this effort is a move towards open data as a way to fight post-publication data loss, improve data and code quality, enable powerful meta- and cross-disciplinary analyses, and increase trust in, and the efficiency of, publicly-funded research. Many scientists however lack experience in, and may be unsure of the benefits of, making their data and fully-reproducible analyses publicly available. Here we describe a recent "open experiment", in which we documented every aspect of a soil incubation online, making all raw data, scripts, diagnostics, final analyses, and manuscripts available in real time. We found that using tools such as version control, issue tracking, and open-source statistical software improved data integrity, accelerated our team's communication and productivity, and ensured transparency. There are many avenues to improve scientific reproducibility and data availability, of which is this only one example, and it is not an approach suited for every experiment or situation. Nonetheless, we encourage the communities in our respective fields to consider its advantages, and to lead rather than follow with respect to scientific reproducibility, transparency, and data availability.

global change↗

Shadow of the Future: Developing Trust and Software within the Exascale Computing Project

Collaboration and team science are emerging areas of interest in software production. Historically, multi-institutional research collaborations are difficult to initiate and maintain, negatively impacting communication, negotiation, and dialogue between industry, government, and academic researchers. The Exascale Computing Project (ECP), a massive, multi-team, high-stakes initiative, facilitated broader research collaboration under a shared funding structure and extended timeline to support scientific discovery. Here, we conducted interviews with ECP teams, representing a variety of domain specialties, research institutions, and programming backgrounds. Using thematic analysis, we assessed how ECP’s structure created an environment of increased trust among projects and how software shared between teams facilitated sustained collaboration. We found that the expectation of future collaboration, i.e., the shadow of the future, greatly enhanced trust among teams and the quality of scientific software produced. Based on our findings within ECP projects, we connect to the existing literature on trust in software engineering and share recommendations for sustainable multi-institutional collaboration and shared best software practices.

Exascale computing project↗

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗

Fourth Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE4)

This article summarizes motivations, organization, and activities of the Fourth Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE4). The WSSSPE series promotes sustainable research software by positively impacting principles and best practices, careers, learning, and credit. This article discusses the code of conduct; the mission and vision statements that were drafted at the workshop and finalized shortly after it; the keynote and idea papers, position papers, experience papers, demos, and lightning talks presented during the workshop; and a panel discussion on best practices. The main part of the article discusses the set of working groups that formed during the meeting, along with contact information for readers who may want to join a group. Lastly, it discusses a survey of the workshop attendees.

99 GENERAL AND MISCELLANEOUS↗

Guideline 36 Conformance Test v2.0

ASHRAE Guideline 36 provides guidance for how typical commercial building HVAC systems should be controlled to reduce energy costs and improve the indoor environmental quality for occupants. An industry-led effort is developing test scripts for how control manufacturers can test that the control logic in their control products follows Guideline 36. This software intends to support that effort in two ways. First, by providing a testbed for control manufacturers to run the test scripts against their own control products and compare their generated results to the expected results provided by the test scripts. Second, by providing a testbed that can be used during the development of test scripts to rapidly and repeatably verify they exercise Guideline 36 logic as desired and generate accurate expected results that control products can be compared to. An initial version of the software has already been developed and released open-source by a previous CEC-funded project that implemented the first use case (https://github.com/LBNL-ETA/guideline36_conformance_test/blob/master/LICENSE.txt), while this software disclosure will add the functionality of the second use case, as well as update the software where needed, all open-source. We intend to extend and contribute to the existing open-source software repository.

Blum, David [Lawrence Berkeley National Laboratory↗

DL_POLY Quantum 2.0: A modular general-purpose software for advanced path integral simulations

DL_POLY Quantum 2.0, a vastly expanded software based on DL_POLY Classic 1.10, is a highly parallelized computational suite written in FORTRAN77 with a modular structure for incorporating nuclear quantum effects into large-scale/long-time molecular dynamics simulations. This is achieved by presenting users with a wide selection of state-of-the-art dynamics methods that utilize the isomorphism between a classical ring polymer and Feynman’s path integral formalism of quantum mechanics. Here, the flexible and user-friendly input/output handling system allows the control of methodology, integration schemes, and thermostatting. DL_POLY Quantum is equipped with a module specifically assigned for calculating correlation functions and printing out the values for sought-after quantities, such as dipole moments and center-of-mass velocities, with packaged tools for calculating infrared absorption spectra and diffusion coefficients.

36 MATERIALS SCIENCE↗

A Comprehensive Calibration Framework for the Northwest River Forecast Center

We present a comprehensive framework developed by the Northwest River Forecast Center for calibrating hydrologically diverse basins. The framework includes models for snow, soil moisture, routing, channel loss, and consumptive use. Data inputs include a wide range of open-access datasets for meteorology, land use, topography, and land cover. The framework uses conceptual hydrologic models to handle basins with various hydrologic regimes including rain-driven and snowmelt-dominated basins. We also develop a flexible automatic calibration system that can handle numerous unobservable model parameters in a computationally efficient manner. A single-basin automatic calibration run can typically be completed on a modern laptop in under 10 min. We found that model performance metrics for this new approach match the quality of the NWRFC's previous labor-intensive manual calibrations. The model performance also rivals that of a state-of-the-art deep learning model at a fraction of the computational cost. This framework presents a new standard for the quality of calibrations possible with lumped conceptual hydrologic models, combining careful data curation, an objective calibration framework, and expert local knowledge. In addition, we have made software packages available for the entire suite of National Weather Service River Forecast System models, including SAC-SMA, SNOW-17, and Lag-K. These modern interfaces are intended to increase accessibility and facilitate future research.

Forecasting↗

CASM — A software package for first-principles based study of multicomponent crystalline solids

CASM is a software package that enables first-principles based studies of crystalline materials. It has been designed to treat coupled chemical, mechanical, vibrational, and magnetic degrees of freedom to determine ground state and finite temperature properties of crystals. The symmetry of the underlying parent crystal structure is used to enumerate perturbations of the parent crystal structure and generate derivative structures which can be input to first-principles calculations in order to explore the ground state energy landscape. CASM algorithmically constructs cluster expansions that fully couple discrete and continuous degrees of freedom, and generates highly efficient code to evaluate the cluster expansion basis functions. Widely used machine learning methods are integrated for fitting expansion coefficients to first-principle calculations. The fully parameterized cluster expansions can be combined with (kinetic) Monte Carlo methods to calculate finite temperature thermodynamic and kinetic properties. CASM Alloy Manager identifies distinct parent crystal structures in an alloy system, creating individual projects for each, and integrating the results. The integrated infrastructure facilitates the linkage between first-principles statistical mechanics predictions with higher length scale computational methods, such as phase field simulations. In conclusion, CASM projects are designed to be easy to share in repositories, to re-use, and to extend to include additional chemical species or types of degrees of freedom.

36 MATERIALS SCIENCE↗

Shifting institutional culture to develop climate solutions with Open Science

To address our climate emergency, “we must rapidly, radically reshape society”—Johnson & Wilkinson, All We Can Save. In science, reshaping requires formidable technical (cloud, coding, reproducibility) and cultural shifts (mindsets, hybrid collaboration, inclusion). We are a group of cross-government and academic scientists that are exploring better ways of working and not being too entrenched in our bureaucracies to do better science, support colleagues, and change the culture at our organizations. We share much-needed success stories and action for what we can all do to reshape science as part of the Open Science movement and 2023 Year of Open Science.

54 ENVIRONMENTAL SCIENCES↗

13 C-Fingerprinting and Metabolic Flux Analysis of Bacterial Metabolisms

13 C-assisted metabolism analysis provides rigorous calculations of the intracellular reaction rates (i.e., fluxes) within the central metabolism of microbial hosts. This mapping of the intracellular network within microbes has proven to be essential for understanding the cell physiology. The approach is also a key to identifying central metabolic nodes, probing the rigidity of a metabolic network, revealing cofactor balances, and delineating hidden pathways. Here we present the methodology of using stable isotopic carbon substrates for both qualitative ( 13 C-fingerprinting of functional pathways) and quantitative (Metabolic Flux Analysis) metabolism studies on bacterial species. In this methodology, we include step-by-step instructions to use the open source WUflux software for the steady-state flux calculations based on labeling information of amino acids or free metabolites.

13C-MFA, Metabolites, Flux ratio, Metabolism, Prot↗

SUSPECT: MINLP special structure detector for Pyomo

We present SUSPECT, an open source toolkit that symbolically analyzes mixed-integer nonlinear optimization problems formulated using the Python algebraic modeling library Pyomo. We present the data structures and algorithms used to implement SUSPECT. SUSPECT works on a directed acyclic graph representation of the optimization problem to perform: bounds tightening, bound propagation, monotonicity detection, and convexity detection. We show how the tree-walking rules in SUSPECT balance the need for lightweight computation with effective special structure detection. SUSPECT can be used as a standalone tool or as a Python library to be integrated in other tools or solvers. Here, we highlight the easy extensibility of SUSPECT with several recent convexity detection tricks from the literature. We also report experimental results on the MINLPLib 2 dataset.

97 MATHEMATICS AND COMPUTING↗

Computation of Effective Radiative Properties of Powders for Selective Laser Sintering Simulations

Selective laser sintering (SLS) is an additive manufacturing technique for rapidly creating parts directly from a computer-aided design (CAD) model by using a laser to fuse successive layers of powder. However, better understanding of the effect of particle-level variations on the overall build quality is needed. In this work, we investigated these effects computationally by considering the role of the particle size distribution and variations in the powder bed depth to mimic the part complexity found in overhangs and protrusions. In addition, the results from these studies can be distilled to obtain better effective material properties such as laser absorptivity and laser extinction coefficient that are needed for continuum models of the process. We implement a Monte Carlo ray-tracing algorithm within the discrete element model in the open-source simulation software MFiX. Random, loose-packed, particle bed structures are generated, and effective absorptivity and extinction coefficients are calculated. Results are compared against previous computational and experimental measurements for free, monodisperse, and deep powder beds, with good agreement being obtained. Correlations along with uncertainties are developed to allow the effective absorptivity and extinction coefficient as a function of various particle and operational parameters to be accurately set in SLS macroscale models.

Moser, Daniel↗

PetIGA: A framework for high-performance isogeometric analysis

We present PetIGA, a code framework to approximate the solution of partial differential equations using isogeometric analysis. PetIGA can be used to assemble matrices and vectors which come from a Galerkin weak form, discretized with Non-Uniform Rational B-spline basis functions. We base our framework on PETSc, a high-performance library for the scalable solution of partial differential equations, which simplifies the development of large-scale scientific codes, provides a rich environment for prototyping, and separates parallelism from algorithm choice. We describe the implementation of PetIGA, and exemplify its use by solving a model nonlinear problem. To illustrate the robustness and flexibility of PetIGA, we solve some challenging nonlinear partial differential equations that include problems in both solid and fluid mechanics. Lastly, we show strong scaling results on up to 4096 cores, which confirm the suitability of PetIGA for large scale simulations.

97 MATHEMATICS AND COMPUTING↗

Predicting the volumes of crystals

New crystal structures are frequently derived by performing ionic substitutions on known crystal structures. These derived structures are then used in further experimental analysis, or as the initial guess for structural optimization in electronic structure calculations, both of which usually require a reasonable guess of the lattice parameters. In this work, we propose two lattice prediction schemes to improve the initial guess of a candidate crystal structure. The first scheme relies on a one-to-one mapping of species in the candidate crystal structure to a known crystal structure, while the second scheme relies on data-mined minimum atom pair distances to predict the crystal volume of the candidate crystal structure and does not require a reference structure. We demonstrate that the two schemes can effectively predict the volumes within mean absolute errors (MAE) as low as 3.8% and 8.2%. Here we also discuss the various factors that may impact the performance of the schemes. Implementations for both schemes are available in the open-source pymatgen software.

36 MATERIALS SCIENCE↗