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Development and Validation of the NASA Modified System Usability Scale (NMSUS): A Brief Summary
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Investigation of Droplet Deposition for Suspensions Usable for Thermoplastic 3D Printing (T3DP)
Thermoplastic 3D printing (T3DP) is an additive manufacturing (AM) technology, which can be used for the production of dense single- and especially multi-material components. This becomes possible because of the combination of the precise deposition of small droplets of molten thermoplastic suspensions containing ceramic or metal particles, and a curing mechanism caused on cool down increasing the viscosity. In this paper, the droplet formation behavior of zirconia suspensions for T3DP (82 and 84 wt.%) was investigated. The droplet fusion factor (dff) is introduced to calculate the necessary distance between two droplets to form filament-like structures by fusion of adjacent droplets. Filament-like structures with a smooth surface and a nearly homogeneous cross section were manufactured for both suspensions with a dff of 44% or higher.
Personal CO2 bubble: Context-dependent variations and wearable sensors usability
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Deployment priority of public charging speeds for increasing battery electric vehicle usability
To inform charger deployment decisions, this paper aims to understand the potential utilization and deployment priority for public charging infrastructure. A data-driven Cumulative Public Recharging (CPR) model is developed to explore the travel patterns by using 2017 National Household Travel Survey data. Given the daily trip sequence, trip distance, and dwell times, the study examines the daily expected driving range and BEV feasibility under different charging speeds, battery capacity, and charging behaviors. The results suggest that more advanced public chargers increase the daily expected driving range. Home charging is sufficient for most daily short-distance trips while public chargers are still needed for medium- and long-distance trips. Extreme fast charging (xFC) may not be necessary for people with home charging but could be more useful for people without home charging and for urgent charging. In conclusion, xFC becomes even less important to drivers with longer BEV ranges, a finding that contradicts conventional thinking.
Towards molecular simulations that are transparent, reproducible, usable by others, and extensible (TRUE)
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Lack of clear standards and usable comparisons of downscaled climate projections pose a roadblock for US climate discovery and adaptation
Abstract The release of global climate projections coupled with the demand for local-resolution climate-forced meteorology has prompted many research groups to downscale these projections using various statistical, dynamical, and current machine learning techniques. Such downscaled datasets are being used to plan infrastructure and other community needs over the coming decades. Faced with roughly a dozen available US downscaled datasets, many practitioners ask, ‘What are the relevant differences between datasets?’ This work highlights the difficulty of comparing downscaled datasets and illustrates ways in which datasets differ even when using identical climate model input data. We show that substantial variability in precipitation projections arises from downscaling alone and that the downscaled dataset agreement varies depending on global climate projection. This analysis emphasizes the need for greater coordination and movement toward rigorous benchmarking of downscaling strategies within the downscaling research community, à la the land-modeling community, to better quantify downscaling dataset differences, strengths, and weaknesses for practitioners.
Improving the Usability of Virtual Reality Neuron Tracing with Topological Elements
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A low-temperature, one-step synthesis for monazite can transform monazite into a readily usable advanced nuclear waste form
It has been demonstrated that monazite-type materials are excellent candidates for nuclear waste forms, and hence, their facile synthesis is of great importance for the needed sequestration of existing nuclear waste. The synthesis of monazite, LaPO 4 , requires inconveniently high temperatures near 1000°C and generally involves the conversion of the presynthesized rhabdophane, LaPO 4 •nH 2 O, to the LaPO 4 monazite phase. During this structure transformation, the rhabdophane converts irreversibly to the thermodynamically stable monoclinic monazite structure. A low-temperature (185° to 260°C) mild hydrothermal acid-promoted synthesis of monazite is described that can both transform presynthesized rhabdophane or assemble reagents to the monoclinic monazite structure. The pH dependence of this reaction is detailed, and its applicability to the LnPO 4 (Ln = La, Ce, Pr, Nd, Sm-Gd), Ca 0.5 Th 0.5 PO 4 , and Sr 0.5 Th 0.5 PO 4 systems is discussed. The crystal growth of Ca 0.5 Th 0.5 PO 4 and Sr 0.5 Th 0.5 PO 4 is described, and their crystal structures were reported. In situ x-ray diffraction studies, performed as a function of temperature, provide insight into the structure transformation process.
Using a Large Language Model as a Building Block to Generate Usable Validation and Verification Suite for OpenMP
In the HPC area, both hardware and software move quickly. Often new hardware is developed and deployed, the corresponding software stack, including compilers and other tools, are under active development while leading edge software developers are working to port and tune their applications, all at the same time. While the software ecosystem is in flux, one of the key challenges for users is obtaining insight into the state of implementation of key features in the programming languages and models their applications are using – whether they have been implemented, and whether the implementation conforms to the specification, especially for newly implemented features (less tested by widespread use). OpenMP is one of the most prominent shared memory programming models used for on-node programming in HPC. With the shift towards accelerators (such as GPUs and FPGAs) and heterogeneous programming OpenMP features are getting more complex. It is natural to ask whether generative AI approaches, and large language models (LLMs) in particular, can help in producing validation and verification test suites to allow users better and faster insights into the availability and correctness of OpenMP features of interest. In this work, we explore the use of ChatGPT-4 to generate a suite of tests for OpenMP features. We have chosen a set of directives and clauses, a total of 78 combinations, which first appeared in OpenMP 3.0 (released in May 2008) but are also relevant for accelerators. We prompted ChatGPT to generate tests in the C and Fortran languages, for both host (CPU) and device (accelerator). On the Summit super-computer using the GNU implementation, we found that, of the 78 generated tests 67 C tests and 43 Fortran tests compiled successfully and fewer than those executed to completion. On further analysis we show that not all generated tests are valid. We document the process, results, and provide detailed analysis regarding the quality of tests generated. With the aim of providing input to a production quality validation and verification suite, we manually implement the corrections required to make the tests valid according to the current OpenMP specification. We quantify this effort as small, medium, or large, and record the lines of code changed to correct the invalid tests. With the corrected tests we validate recent implementations from HPE, AMD, and GNU on the Frontier supercomputer. Our experiment and subsequent analysis show that although LLMs are capable of producing HPC specific codes, they are limited by their understanding of the deeper semantics and restrictions of programming models such as OpenMP. Unsurprisingly more commonly used features have better support, while some OpenMP 3.0 directives such as sections and tasking are not universally supported on accelerators. We demonstrate that successful compilation and execution to completion are inadequate metrics for evaluating generated code and that, at this time, commodity LLMs require expert intervention for code verification. This points to gaps in the training data that is currently available for HPC. We demonstrate that with "small" effort 37% of generated invalid C tests and 63% of generated invalid Fortran tests could be corrected. This improves productivity of test generation as we circumvent writing from scratch and the common programming errors associated with it.
GridPACK: Library Architecture and Usability Assessment
The LLNL team has carried out extensive analysis of GridPACK code, including two major code reviews (each being a 2-day event) and a vendor emulation exercise, where the team integrated GridPACK library within a third-party application. The code analysis identified a number of areas for improvement of GridPACK code architecture, but it did not find fundamental flaws in the GridPACK design. The team found the GridPACK strategy of developing a software development kit (SDK) for power systems application development to be sound and well aligned with Office of Electricity long term objectives. The SDK aims to provide power systems software vendors an easy access to high performance computing (HPC) libraries.
VeraShift Usability Updates for Production Releases of VERA for Ex-core Calculations
The recently developed capability to perform ex-core calculations in the Virtual Environment for Reactor Applications (VERA) with Shift is now available in production releases of VERA. To support these production releases, updates to the VeraShift interface are needed continually. The updates completed under this milestone are documented in this report, including improvements to memory usage and code robustness, as well as the resolution of issues with unexpected behavior that arose during testing.
Usable Data Abstractions for Next-Generation Scientific Workflows
Data- and computationally-intensive scientific research, such as numerical simulations and inversions or the training of large neural networks in machine learning applications, that are well suited for HPC environments also often require expert insight and evaluation throughout the computation which can be greatly facilitated with the use of interactive computing tools, such as those in the Jupyter ecosystem. HPC workflows and interactive workflows are typically treated as orthogonal, however, the next generation of research will require both. The first challenge we face in this project is thus designing the right level of abstractions to allow interactive capabilities in the JupyterLab environment to allow the working scientist to flexibly explore and query their data at multiple levels, with a minimal amount of customization required of the underlying optimized codes. In addition to these questions regarding the high-level representation of data for interactive use in HPC, we tackled two additional issues that are part of the entire lifecycle of research and that become particularly acute in HPC contexts: how to improve the experience of interfacing with the HPC system's scheduling environment for a scientist focused on exploratory questions, and how can that scientist then best share the results of their work with others in a self-contained, reproducible manner.
Increasing the Usability of Sockeye: Implementing Customer-Driven Modeling Improvements, Features, and Documentation of Sockeye
A number of tasks for the heat pipe simulation tool Sockeye were identified based on customer needs and included both user documentation and code development: (a) Implement saturation-dependence in the capillary pressure model; (b) Provide an analytic utility to analyze the frozen startup limit; (c) Demonstrate custom friction closures; (d) Develop examples for different types of heat transfer sources and boundary conditions; (e) Demonstrate the capillary and sonic limits; and (f) Provide discretization details in the theory manual. These tasks were all completed, and results are given where applicable.
Usability Enhancements for Refl1D Neutron and X-ray Reflectometry Modeling Software
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Researcher Views on Water Data Accessibility, Usability, and Dissemination
Ultimately, the challenges that researchers face with finding, accessing, using, and disseminating water data affect their ability to do mission critical research for DOE and other sponsors. We interviewed PNNL researchers who support DOE’s Water Power Technologies Office and summarize their views on issues pertaining to data access, use, and dissemination. We also take a closer look at approaches to disseminating data to help inform WPTO and lab researcher decisions about incorporating data dissemination into future projects.
Complete Demonstration of a Prototype Version of FORCE User Interface and Conduct Analyst Survey Collecting Feedback on Interface Features and Usability
In 2024 the US Department of Energy (DOE) Office of Nuclear Energy (NE) Integrated Energy System (IES) program continued to develop the Framework for Optimization of Resources and Economics (FORCE) analysis ecosystem into a more traditional toolset with simplified software installation, automated workflows, and interactive results visualization. The DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench continued to be leveraged for user input, application workflow and runtime environment, and interactive results visualization capabilities. This report documents the demonstration of a FORCE User Interface (UI) prototype and the results of a survey of analysts’ using the Holistic Energy Resource Optimization Network (HERON) tool in FORCE with the prototype UI.
Pyomo.DoE 2.0: Improved Usability and Computational Efficiency for Science-Based Design of Experiments (SBDoE)
Conference paper explaining the new user interface and software design for the Pyomo.DoE and ParmEst packages. An example utilizing these packages will be presented, showcasing modeling capabilities, and capabilities for handling complex models that have been developed within the PrOMMiS and CCSI2 ecosystems.