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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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This report discusses the importance of software testing, referencing two examples that illustrate setbacks and losses without adequate testing. The report also highlights various levels of testing and provides guiding questions to help with the process.
This report provides detailed documentation of the algorithms that were developed and implemented in the Plato software over the course of the Optimization-based Design for Manufacturing LDRD project.
NREL and its project partners built and commercialized the novel Solar Automated Permitting Processing Plus (SolarAPP+) software platform that delivers instant residential rooftop solar permits. The tool provides installers with a standard portal for entering permit information for residential solar systems across all Authorities Having Jurisdiction (AHJs) using SolarAPP+, thereby providing a streamlined plan review form, transparency into permitting timelines, and required specifications. The project has proven to reduce permitting timelines from as many as 20 business days to zero, delivering solar projects faster in the four participating AHJs using the platform. Streamlining permitting timelines, all else equal, results in consumers installing their systems and reducing their electricity bills faster. The continued expansion of SolarAPP+ features and adoption nationwide will expand the benefits of the SolarAPP+ beyond the current user base.
VERAIO is a set of utility codes used to provide a common set of inputs and outputs to the Virtual Environment for Reactor Applications (VERA). VERA is a collection of several different computer codes that all have a common input and output. This prevents the need to manage input and output from each individual code, allowing for ease of use and reducing errors associated with code operability. The VERAIO utilities include VERAIn, VERAView, and VERARun. Each of these utilities is described below. VERAIn is an input processor that reads an ASCII input file generated by users, parses the file, performs some error checking, and writes an XML file to be read by other VERA codes. The main purpose of VERAIn is to provide a common input to all of the VERA codes, so users only need to learn one input. VERAIn is written in Perl and uses YAML configuration files to provide flexibility. VERAView is a graphical user interface (GUI) that reads a VERA hierarchical data format (HDF) output file and allows users to visualize results. VERAView is written in Python. VERARun is a script that drives the VERA execution in a high performance computing (HPC) environment. Work performed at the code level supports the quality assurance program plan (QAPP) (VERA-QA-001) and the VERA Software Quality Assurance Plan (VERA-QA-002).
The U.S. Department of Energy has a broad mission to ensure the nation’s security by addressing ongoing environmental challenges, developing novel energy production technologies, and mitigating nuclear security concerns. These efforts benefit from developing more effective semiconductor materials and devices. The research discussed in this report aims to further the development of these new electronics by improving implementations of vertical device structures, which offer theoretically better performance compared to lateral structures. Specifically, it reviews the background and development of a new and easy-to-use program for data processing and analysis from experiments run on vertical gallium nitride power devices. Current vertical structures fall short in critical performance metrics, such as On-Resistance and Breakdown Voltage, due to poor management of the device’s electric field. Junction termination extensions, or JTEs, are a field management technique that increases a device’s resilience to expected failure modes by controlling its surface electric fields. Each JTE design requires significant experimental validation, consisting of hundreds of tested devices, each outputting an enormous set of data points. The new software includes multiple methods of filtering large sets of device testing data to identify and remove flawed devices, automate device analyses, and provide statistical breakdowns for four metrics used to define the effectiveness of the JTE and the current carrying capacity of the device. These results can then be related back to fabrication techniques and device design, and in the future, be combined with processing simulations to further improve our understanding of the JTE mechanisms.
The MPACT code solves a discretized form of the Boltzmann transport equation on a wide variety of geometries and is distributed with a multigroup neutron cross section library. MPACT provides an advanced geometrically resolved neutral-particle transport capability to solve the flux distribution throughout the entire problem geometry, and it can model the isotopic depletion, decay, and activation of materials. The flux solution in MPACT is provided using a 2D/1D synthesis method within the framework of the 3D coarse mesh finite difference (CMFD) method for which axial and radial correction factors are obtained from 2D method of characteristics (MOC) and 1D nodal expansion method (NEM), PN, or SN. Other key characteristics of the MPACT code include the subgroup method and the embedded self-shielding method (ESSM) for resonance treatment, depletion capability based on the ORIGEN exponential matrix method, and a simplified thermal-hydraulics method for temperature/fluid feedback. The sole purpose of the simplified feedback model is to provide a mechanism for testing during code development and to provide a limited capability for educational applications. Work performed at the code level supports the VERA-QA-001, quality assurance program plan (QAPP) and VERA-QA-002, VERA Software Quality Assurance Plan.
Milestone accomplishments staged the ExaWind team for successful completion of KPP-2 challenge problem in FY23, which requires the simulation on Frontier of at least four MW-scale turbines in an atmospheric boundary layer with at least 20B gridpoints. The ExaWind project and software stack is many faceted, with team members working on multiple areas, including linear-system solvers (Trilinos, hypre, AMReX), overset meshes, turbulence modeling, and in situ visualization, all with an aim for high fidelity predictions and performance portability. This milestone marks significant improvements on many fronts and provides the team with a pathway to exascale wind farm simulations in FY23.
As part of the verification and validation (V&V) efforts of the Argonne Reactor Code (ARC) software system to support the Versatile Test Reactor (VTR) project of the U.S. Department of Energy (DOE), work has been performed to verify and validate the gamma (or photon) library of the multigroup cross section generation code MC 2 -3 of the ARC system, which is the essential part of the coupled neutron and gamma heating calculations to determine the heat generation rate or power distribution in the core. This V&V study was carried out in three steps: 1) review of the procedures and utility programs for generating the MC 2 -3 gamma library, 2) verification tests of cross sections and KERMA factors by comparing the total heat generation rate of coupled neutron and gamma calculation with that obtained with reaction Q values under the assumption of local gamma energy deposition and by comparing the prompt heat generation rate with that calculated with the MCNP6.2 code, and 3) validation tests of cross sections and KERMA factors by analyzing the ZPPR-15D gamma dose data measured with thermoluminescent dosimeters (TLD).
Software and Computing (S&C) are essential to all High Energy Physics (HEP) experiments and many theoretical studies. The size and complexity of S&C are now commensurate with that of experimental instruments, playing a critical role in experimental design, data acquisition/instrumental control, reconstruction, and analysis. Furthermore, S&C often plays a leading role in driving the precision of theoretical calculations and simulations. Within this central role in HEP, S&C has been immensely successful over the last decade. This report looks forward to the next decade and beyond, in the context of the 2021 Particle Physics Community Planning Exercise ("Snowmass") organized by the Division of Particles and Fields (DPF) of the American Physical Society.
High-resolution multi-frequency radars when networked together, form a robust and seamless monitoring system for high-valued items. The multi-look-direction radar network investigated by LLNL and DSI, operates at 77 GHz and 5.8GHz, and is capable of detection at centimeter resolution movement of objects of interest. This dual frequency radar (unlike optical methods) can operate under various environments with conditions such a smoke, dust, and other natural or manmade obscurations. In addition, the multiband network radar is based on low-cost FCC approved EM specifications and can be scaled with the dimensions of the room and objects under consideration by user-defined inputs. Furthermore, the underlying radar signal processing based on software-defined radar engine is adaptive to its operational environment, where operators can input the size of the facility and object of interest and the distance between the object and radar. Finally, this multi-frequency radar employs a host of change detection and machine learning algorithms to reach performance levels in terms of high probability of detection and low false alarm rates while the monitoring state of the object can be reported remotely.
No prior enabling funded work applicable to this proposal. Programming Protocol-independent Packet Processors (P4) is an open source, domain-specific programming language for network switching devices. P4 complements traditional Software Defined Networking (SDN) which is primarily concerned with the management of packets (e.g. routing/dropping decisions) rather than how each packet is processed. The introduction of P4 provided new capabilities (e.g. firewall, load balancing, enhanced security) but has primarily been deployed in data centers. This effort investigates ways to expand P4 into other niches such as ICS networks.
The purpose of this document is to detail the release of FAST-1.0 and the documents that accompany the development and testing of FAST-1.0. Design requirements were for FAST-1.0 developed in the NRC Statement of Work (SOW) for NRC Agreement Number NRC-HQ-25-14-D-001 and are transcribed to this document as part of the Software Quality Assurance Plan for the FAST Code System, PNNL-28767. FAST 1.0 represents the merger of the FRAPCON and FRAPTRAN codes and as such FAST-1.0 performs steady state and transient fuel performance calculations described below. FAST-1.0 calculates the steady state response of light-water reactor fuel rods during long-term burnup. The code calculates temperature, pressure, and deformation of a fuel rod as functions of time-dependent fuel rod power and coolant boundary conditions. The phenomena modeled by the code include: 1) heat conduction through fuel and cladding to the coolant; 2) cladding elastic and plastic deformation; 3) fuel-cladding mechanical interaction; 4) fission gas release from the fuel and rod internal pressure; and 5) cladding oxidation. FAST is used to perform independent calculations for regulatory evaluations of fuel performance under normal operation and anticipated operational occurrences (AOOs).
Neuromorphic systems can be realized by a variety of algorithms and architectures. A common understanding is that spiking neuromorphic designs, which encode information into spatio-temporal spiking events, are both a biologically-accurate and efficient way of processing information. However, representing the information through timing relationships induces sophisticated circuit designs in traditional CMOS-based implementations. In recent years, high-capacity resistive memory (RRAM, aka, memristor) has demonstrated great potential in mimicking synaptic behaviors. Several RRAM-based spiking neuromorphic designs exist, most of which focus on rate coding schemes. These designs simplify circuit implementations of neuron models and explore challenges such as unsatisfactory speed, resolution, and performance. As an alternative, we will explore temporal coding spiking neuromorphic systems that encode information as the relative timing of neuron activations (spikes), which have been proven to be more adaptive and energy-efficient. Developing a neuromorphic system for spiking neural network (SNN) inference and online training, however, faces some major technical challenges: (1) It lacks circuit implementation support for temporal-coding SNN to achieve satisfying power efficiency and accuracy; (2) Although existing research works have investigated memristive synapse and neuron designs for spike-timing-dependent plasticity, the non-ideal conditions in implementation, such as device variations and signal degradation, degrade online learning accuracy of large scale systems; and (3) Non-optimized, inter-layer data traffic in SNNs, leads to unnecessary data communication costs. In this project, we plan to address these challenges by a hardware and software co-design framework that incorporates solutions at the circuit, architecture, and algorithm levels. At the circuit-level, we will elaborate on the in-situ SNN processing element designs for supporting both inference and online training modes. Variation-aware schemes will be studied to improve reliability. At the architecture level, we propose a pipelined, asynchronous architecture to retain the timing resolution of spikes. At the algorithm level, we will investigate an innovative SNN training algorithm for enabling activation sparsification and reducing unnecessary data communication costs. This neuromorphic system will provide an effective solution to real-life energy-constrained applications and significantly contribute to the exploration of next-generation high-performance computing systems under the DOE context.
In order to characterize US communities in terms of social and environmental determinants of health (EDH) that affect veterans, the Social and Environmental Determinants of Health (SEDH) project, a collaboration between the Veterans Affairs (VA) Social Department and the Oak Ridge National Laboratory (ORNL), aims to identify, extract, and prepare datasets that include community variables known to be associated with health outcomes in veterans. The EDH project's responsibilities include investigating SEDH data, providing technical documentation for SEDH datasets, and automating the download, extraction, and preparation of the data through the creation of a software pipeline framework.
The main objective of this research project was the development and application of a new theoretical/computational framework to model chemical transformations and electronic excitations in fluid mixtures across different phases. Our theoretical/computational framework combines our data-driven many-body (DD-MB) potentials representing molecular interactions with adaptive schemes for modeling chemical reactions in solution. The combination of these two components resulted in an adaptive quantum mechanics/many-body (adQM/MB) method that largely suppresses discontinuities between QM and MM regions, which affect existing QM/MM methods, and thus provides an accurate representation of both quantum mechanical and environmental effects through a rigorous description of mutual polarization between QM and MM regions. The implementation of our DD-MB potentials and adQM/MB method in popular software enabled computer simulations of solvation phenomena, reactive processes, and electronic excitations in fluid mixtures with chemical and spectroscopic accuracy, representing a major step toward realistic computer simulations of a wide range of molecular systems relevant to the DOE mission.
Support customizations of algorithms and raw data file structures to enhance software workflows for liquid chromatography (LC), mass spectrometry (MS) and ion mobility mass spectrometry (IM-MS)-based metabolite characterization. Evaluate and improve the integration of ion mobility to existing MS analysis methods of the Mass Profiler Professional workflow (Mass Profiler, ID Browser and Mass Profiler Professional).
The National Renewable Energy Laboratory (NREL) and Wrightsoft Corporation will advance commercialization of a residential building energy software product that uses DOE's flagship open-source OpenStudio and EnergyPlus simulation ecosystem for calculation of the Energy Rating Index (ERI).
To enhance solver capabilities, simulation flexibility and model validation within the MFiX software, the U.S. Department of Energy (DOE) is funding efforts to develop and integrate the glued-sphere discrete element method into the latest version of MFiX as a dedicated computational module. The glued-sphere discrete element method is a numerical technique to depict the behavior of non-spherical particles in granular flows or particulate systems by representing them as a collection of component spheres. These spheres are bonded together to approximate the shape and mechanical/chemical properties of a more complex particle. The method effectively reuses the existing sphere-sphere collision algorithm, interphase momentum and heat transfer calculations utilized in the traditional discrete element method, extending these capabilities to non-spherical particles. Additionally, this method explicitly resolves intra-particle temperature and species distributions. The MFiX glued-sphere computational module includes tools for generating glued sphere configurations, a dedicated solver, and visualization capabilities in post-processing. More specifically within the computational module, collision detection and calculations were first performed on component spheres and then mapped onto non-spherical particles. The linear spring-dashpot model was utilized to simulate the sphere-sphere interactions.