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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 667 records · Page 37

Tool Use Within NASA Software Quality Assurance

As space mission software systems become larger and more complex, it is increasingly important for the software assurance effort to have the ability to effectively assess both the artifacts produced during software system development and the development process itself. Conceptually, assurance is a straightforward idea - it is the result of activities carried out by an organization independent of the software developers to better inform project management of potential technical and programmatic risks, and thus increase management's confidence in the decisions they ultimately make. In practice, effective assurance for large, complex systems often entails assessing large, complex software artifacts (e.g., requirements specifications, architectural descriptions) as well as substantial amounts of unstructured information (e.g., anomaly reports resulting from testing activities during development). In such an environment, assurance engineers can benefit greatly from appropriate tool support. In order to do so, an assurance organization will need accurate and timely information on the tool support available for various types of assurance activities. In this paper, we investigate the current use of tool support for assurance organizations within NASA, and describe on-going work at JPL for providing assurance organizations with the information about tools they need to use them effectively.

software assurance↗

Developing a 300C Analog Tool for EGS

This paper covers the development of a 300°C geothermal well monitoring tool for supporting future EGS (enhanced geothermal systems) power production. This is the first of 3 tools planed. This is an analog tool designed for monitoring well pressure and temperature. There is discussion on 3 different circuit topologies and the development of the supporting surface electronics and software. There is information on testing electronic circuits and component. One of the major components is the cable used to connect the analog tool to the surface.

15 GEOTHERMAL ENERGY↗

Tool-Based Case Studies on Strategic Deployment of Untapped Micro-Pumped Hydro Storage in Michigan

With most classical hydropower sites already utilized and the global push for rapid integration of renewable energy sources accelerating, there is a critical need to identify alternative energy storage solutions. Pumped hydro energy storage, which accounts for the vast majority of global grid-scale storage, remains one of the most cost-effective and long-duration storage technologies available. Hence, this study presents a novel tool designed to assess the untapped potential of inland lakes and reservoirs for micro-PSH, using Michigan’s relatively flat landscape as a case study due to its extensive but underutilized water infrastructure. To ensure accuracy and reliability, the tool incorporates extensive data gathered from authorized sources, covering more than 420 water facilities and potential reservoirs in the state. The tool evaluates key parameters such as horizontal and vertical distances, volume, and the total storage capacity of each reservoir. Its robust assessment framework integrates these metrics to evaluate each site’s potential. The tool’s intuitive interface and geospatial visualizations support actionable insights for planners and scalable deployment of distributed storage infrastructure.

13 HYDRO ENERGY↗

Investigating Formal Methods Tools and their Applicability for Hardware Vulnerability Remediation

Formal methods use mathematical logic and equations to prove that a system or code is secure. In this poster, I examine existing formal methods tools and their application for projects working to remediate vulnerabilities in hardware and hardware description language. This poster is focused on the tools ReWire and AutoGenILA and I hope to evaluate their benefits and weaknesses with the intention of creating an internal report on the application and weaknesses of existing formal methods tools and identifying gaps for future formal methods tool creation.

97 - MATHEMATICS AND COMPUTING↗

Fleet Tools; NREL (National Renewable Energy Laboratory)

From beverage distributors to shipping companies and federal agencies, industry leaders turn to the National Renewable Energy Laboratory (NREL) to help green their fleet operations. Cost, efficiency, and reliability are top priorities for fleets, and NREL partners know the lab’s portfolio of tools can pinpoint fuel efficiency and emissions-reduction strategies that also support operational the bottom line. NREL is one of the nation’s foremost leaders in medium- and heavy-duty vehicle research and development (R&D) and the go-to source for credible, validated transportation data. NREL developers have drawn on this expertise to create tools grounded in the real-world experiences of commercial and government fleets. Operators can use this comprehensive set of technology- and fuel-neutral tools to explore and analyze equipment and practices, energy-saving strategies, and other operational variables to ensure meaningful performance, financial, and environmental benefits.

33 ADVANCED PROPULSION SYSTEMS↗

Multi‐objective optimization for cost‐efficient and resilient machining under tool wear

Abstract With the onset and rapid growth of smart manufacturing, there is a constant increase in the demand for automation technologies to enhance productivity while providing uninterrupted, cost‐efficient, and resilient machining. Traditional manufacturing systems, however, suffer from several losses due to machine faults and degradation. Specifically, tool wear directly impacts the precision and quality of the milled parts, which causes an increase in the scrap production. Hence, more attempts are required to meet the desired quota of successful parts, which in turn results in wasted material, longer delays, further tool degradation, and higher energy, machining, and labor costs. As such, this paper develops a multi‐objective optimization framework to generate the optimal control set points (e.g., feed rate and width of cut) that minimize the total cost of machining operations resulting from multiple contradictory cost functions (e.g., material, energy, tardiness, machining, labor, and tool) in the presence of tool wear. Notably, we estimate the total expected cost in dollars, which provides automatic and intuitive weighting in this multi‐objective formulation. The optimization framework is tested on a high‐fidelity face milling model that has been validated on real data from industry. Results show significant dollar savings of up to as compared to the default control scheme.

Wilson, James P.↗

Regulatory Tools for Controlling Gene Expression in Cyanobacteria

Cyanobacteria are attractive hosts for converting carbon dioxide and sunlight into desirable chemical products. To engineer these organisms and manipulate their metabolic pathways, the biotechnology community has developed genetic tools to control gene expression. Many native cyanobacterial promoters and related sequence elements have been used to regulate genes of interest, and heterologous tools that use non-native small molecules to induce gene expression have been demonstrated. Overall, IPTG-based induction systems seem to be leaky and initially demonstrate small dynamic ranges in cyanobacteria. Consequently, a variety of other induction systems have been optimized to enable tighter control of gene expression. Tools require significant optimization because they function quite differently in cyanobacteria when compared to analogous use in model heterotrophs. We hypothesize that these differences are due to fundamental differences in physiology between organisms. This review is not intended to summarize all known products made in cyanobacteria nor the performance (titer, rate, yield) of individual strains, but instead will focus on the genetic tools and the inherent aspects of cellular physiology that influence gene expression in cyanobacteria.

59 BASIC BIOLOGICAL SCIENCES↗

Towards High-Speed friction stir welding of 25 mm Thick AA2139-T8: tool innovation and process development

Joining thick plates (≥ 12 mm) of aluminum (Al) alloys is challenging due to high tool forces, uneven material flow, and non-uniform heat distribution through the material’s thickness. Recent advancements in tool design and welding parameters for friction stir welding (FSW) in thick plates butt joining have encountered a developmental plateau, highlighting the need for innovative approaches to overcome existing limitations. Here, this study focuses on the systematic development of single-pass and double-pass FSW processes for high-strength aluminum alloy AA2139-T8, to improve joint efficiency and enable high-speed welding capabilities. Experimental evidence is presented for a novel tool design with opposing pin threads, enabling high-speed (178 mm/min) single-pass friction stir butt welding of 25 mm thick AA2139-T8. A series of FSW trials was conducted both in air and with a trailing water spray, using steel backing plates (BPs) to investigate the impact of quenching and cooling rates on process response and joint performance. A joint efficiency of 83% was attained using the novel tool features and effectively controlling process forces and thermal boundary conditions.

AA2139-T8↗

SyReNN: A tool for analyzing deep neural networks

Deep Neural Networks (DNNs) are rapidly gaining popularity in a variety of important domains. Unfortunately, modern DNNs have been shown to be vulnerable to a variety of attacks and buggy behavior. This has motivated recent work in formally analyzing the properties of such DNNs. Furthermore, this paper introduces SyReNN, a tool for understanding and analyzing a DNN by computing its symbolic representation. The key insight is to decompose the DNN into linear functions. Our tool is designed for analyses using low-dimensional subsets of the input space, a unique design point in the space of DNN analysis tools. We describe the tool and the underlying theory, then evaluate its use and performance on three case studies: computing Integrated Gradients, visualizing a DNN’s decision boundaries, and repairing buggy DNNs.

97 MATHEMATICS AND COMPUTING↗

Effects of High Current Pulsed Electron Beam Irradiation on the Mechanical Properties and Cutting Performance of TiAlN-Coated Tools

Commercial TiAlN-coated carbide tools were post-treated using the high current pulsed electron beam irradiation method. The influence of the energy density of the electron beam on the morphology, phase composition, surface roughness and Vickers hardness were investigated. The higher energy density imposed on TiAlN-coated carbide tools resulted in a flatter and harder modified surface. After the beam irradiation, the XRD diffraction peak intensity of the hardening phase (Ti,Al)N was changed, and the diffraction peak position was shifted; these changes are attributed to the improved microhardness of the irradiated coatings. Investigations on the cutting experiments of turning Ti-6Al-4V alloy showed that the irradiated TiAlN-coated carbide tool exhibited longer cutting life and better wear resistance than those of an unirradiated tool. This improvement is attributed to the combined effect of low surface roughness and high microhardness that resulted from the high current pulse electron beam irradiation.

36 MATERIALS SCIENCE↗

Finite Element Simulation and Optimization of Gas-Quenching Process for Tool Steels

Various gas-quenching processes, including marquenching, were investigated to optimize gas-quenching processes in terms of distortion and hardness by means of numerical and experimental analyses. The temperature, microstructure, hardness, and distortion during the various gas-quenching processes of a tool steel block were simulated using a finite element method based on a coupled thermo-metallurgical–mechanical model. The predicted temperature, hardness, and distortion agreed well with the experimental data. The tool steel block (200 × 150 × 70 mm{sup 3}) quenched under 10 bar pressure of nitrogen gas (Case 2) had higher hardness due to the higher martensite fraction and larger distortion owing to the higher thermal stress induced by faster cooling, compared to the block quenched under 2 bar pressure of nitrogen gas (Case 1). The tool steel block marquenched under 10 bar pressure of nitrogen gas interrupted by isothermal holding at 500 °C (Case 3) had 30% smaller distortion with a negligible loss of hardness compared to Case 2. Furthermore, the simulation results could provide an optimized process condition to minimize distortion of the gas-quenched tool steel block while satisfying the hardness requirement.

36 MATERIALS SCIENCE↗

Effect of Tool Temperature on Microstructure and Properties of Tailored Hot Stamping Components

Traditional boron steel hot stamping technology can achieve components with full martensite and tensile strength of 1500 MPa. However, fully martensitic hot stamped components exhibit very low level of ductility and are rarely used in energy absorbing structures. Hot stamping with segmented heating and cooling tool can obtain multiphase quenched structures and the tailored mechanical properties. Hot stamping experiment of U-shape component was performed with segmented heating and cooling tool. Mechanical properties of the formed component were measured, and scanning electron microscope and color tint etching were used to quantify the quenched phases achieved under different tool temperatures. The results showed that hardness value decreased from 470 to 230 HV and tensile strength reduced about 50% from 1406 to 730 MPa and elongation increased from 4.19 to 10.20% as tool temperatures increased from 25 to 500 °C. Meanwhile, martensite decreased from 85 to 30% and bainite increased from 12 to 55%, and there was also a small increase in ferrite. In order to get the influence of quenched phases on the strength and hardness of tailored hot stamped component, linear fitting optimization was used to establish mathematical models for area fraction of quenched phases and strength and hardness.

36 MATERIALS SCIENCE↗

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗

eqtools: Modular, extensible, open-source, cross-machine Python tools for working with magnetic equilibria

As plasma physics research for fusion energy transitions to an increasing emphasis on cross-machine collaboration and numerical simulation, it becomes increasingly important that portable tools be developed to enable data from diverse sources to be analyzed in a consistent manner. This paper presents eqtools, a modular, extensible, open-source toolkit implemented in the Python programming language for handling magnetic equilibria and associated data from tokamaks. eqtools provides a single interface for working with magnetic equilibrium data, both for handling derived quantities and mapping between coordinate systems, extensible to function with data from different experiments, data formats, and magnetic reconstruction codes, replacing the diverse, non-portable solutions currently in use. Moreover, while the open-source Python programming language offers a number of advantages as a scripting language for research purposes, the lack of basic tokamak-specific functionality has impeded the adoption of the language for regular use. Implementing equilibrium-mapping tools in Python removes a substantial barrier to new development in and porting legacy code into Python. In this paper, we introduce the design of the eqtools package and detail the workflow for usage and expansion to additional devices. Additionally, the implementation of a novel three-dimensional spline solution (in two spatial dimensions and in time) is also detailed. Finally, verification and benchmarking for accuracy and speed against existing tools are detailed. Wider deployment of these tools will enable efficient sharing of data and software between institutions and machines as well as self-consistent analysis of the shared data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A decision support tool for e-waste recycling operations using the hen-and-chicks bio-inspired optimization metaheuristic

E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

WigglyRivers: A tool to characterize the multiscale nature of meandering channels

Channel sinuosity is ubiquitous along river networks, producing complex patterns that encapsulate and influence morphodynamic processes and ecosystem services. Accurately characterizing these patterns is challenging with traditional curvature-based algorithms. Here, in this study, we present WigglyRivers, a Python package that builds on existing wavelet-based methods to create an unsupervised meander identification and characterization tool. The package uses planimetric information the user provides or from the USGS’s High-Resolution National Hydrography Dataset to characterize individual reaches or entire river networks. WigglyRivers also includes a supervised river identification tool for manually selecting individual meandering features. Here, we provide examples of idealized river transects and show the capabilities of WigglyRivers. We also use the supervised identification tool to validate the unsupervised identification on river transects across the continental US. WigglyRivers is a tool to understand better the multiscale characteristics of river networks and the link between river geomorphology and river corridor connectivity.

54 ENVIRONMENTAL SCIENCES↗

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning↗

Integration of software tools for integrative modeling of biomolecular systems

Integrative modeling computes a model based on varied types of input information, be it from experiments or prior models. Often, a type of input information will be best handled by a specific modeling software package. In such a case, we desire to integrate our integrative modeling software package, Integrative Modeling Platform (IMP), with software specialized to the computational demands of the modeling problem at hand. After several attempts, however, we have concluded that even in collaboration with the software's developers, integration is either impractical or impossible. The reasons for the intractability of integration include software incompatibilities, differing modeling logic, the costs of collaboration, and academic incentives. In the integrative modeling software ecosystem, several large modeling packages exist with often redundant tools. So we reason, therefore, that the other development groups have similarly concluded that the benefit of integration does not justify the cost. As a result, modelers are often restricted to the set of tools within a single software package. The inability to integrate tools from distinct software negatively impacts the quality of the models and the efficiency of the modeling. As the complexity of modeling problems grows, we seek to galvanize developers and modelers to consider the long-term benefit that software interoperability yields. In this article, we formulate a demonstrative set of software standards for implementing a model search using tools from independent software packages and discuss our efforts to integrate IMP and the crystallography suite Phenix within the Bayesian modeling framework.

59 BASIC BIOLOGICAL SCIENCES↗