Managing Sandia's Mission IT Software Portfolio through a Common Engineering Environment.
Abstract not provided.
Kuhlman, Philip S.↗
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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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Towards Sustainable Scientific Workflows: DevOps Infrastructure Development in the Engineering Common Model Framework Project .
Abstract not provided.
Milewicz, Reed↗
The Engineering Common Model Framework (ECMF) Project: Towards Scalable and Secure Cyberinfrastructure for Computational Model Sustainment
Explore the source record for details and available documents.
Brundage, Aaron↗
Common Engineering Machine Learning Environments
Overview of 9321's Computing Capabilities related to Machine Learning
Hughes, Bryan↗
TRUST Contact Thermal Conductance (CTC) Report
The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), and the test information management system (TIMS).
42 ENGINEERING↗
TRUST End-of-Year Report
The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), and the test information management system (TIMS). TRUST includes four testbeds and their associated engineering analysis baseline models (EABMs): 1. contact thermal conductivity (CTC); 2. nonlinear dynamics (ND); 3. sensors in environments for accelerometers (SEA); 4. sensors in environments for fiber optic displacement gages (SEFOD).
42 ENGINEERING↗
TRUST Nonlinear Dynamics (ND) Report
The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), and the test information management system (TIMS).
42 ENGINEERING↗
TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY2022
The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), test information management system (TIMS), and [WAVES] Analysis for Verified Engineering Simulation (WAVES).
42 ENGINEERING↗
TRUST Nonlinear Dynamics (ND) Report: FY22
The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainty in Simulations and Tests (TRUST) work package, is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are relevant to the current and future stockpile. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), and the test information management system (TIMS). Additionally, this work is being used to test a newly available framework in W-13, Weapons Analysis for Verified Engineering Simulation (WAVES).
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY23
The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) work package is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline training to provide engineers with experience in both numerical simulations and experimental methods. This work will use and provide feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development: engineering common model framework (ECMF), engineering quantification of margins and uncertainties (EQMU), test information management system (TIMS), and [WAVES] Analysis for Verified Engineering Simulation (WAVES).
42 ENGINEERING↗
Material Extrusion Printing of Poly(Acrylonitrile‐Styrene‐Acrylate) and Poly(Acrylonitrile‐Butadiene‐Styrene) Structures Reinforced with Poly(Phenylene Oxide) Additives for Improved Thermomechanical Properties and their Surface Analysis by Time‐of‐Flight Secondary Ion Mass Spectrometry
Fused filament fabrication offers the ability to 3D print complex geometries made from plastic filament materials; however, these parts are mechanically outperformed by parts created by traditional fabrication methods. To overcome this challenge, a high-performance polymer poly(2,6-dimethyl-1,4-phenylene oxide) (PPO) is incorporated as an additive into two common engineering thermoplastics, poly(acrylonitrile-styrene-acrylate) (ASA) and poly(acrylonitrile-butadiene-styrene) (ABS). Structures printed from these polymer blends are more mechanically robust compared to those prepared from the parent polymers, with low loading levels (1–5 wt%) of PPO improving the elastic strength by up to ≈30% relative to the parent terpolymers. Even at higher loading levels (10 and 20 wt% PPO), there is no evidence of additive aggregation in the model thin films, which is supported by compositional analysis of the copolymers and chemical analysis via time-of-flight secondary ion mass spectrometry. The enhancements in mechanical properties of ASA and ABS blends appear to be a consequence of homogeneous incorporation of the PPO additive. In conclusion, this work explores expanding materials-property space using miscible blends of engineering thermoplastics to improve mechanical performance as a general approach to overcoming challenges with parts created by melt-based material extrusion printing.
additive manufacturing↗
Unifying Energy-Management Problems for Inverter-Based Power Networks
This paper outlines a suite of energy-management problems for inverter-based power networks from the vantage point of optimal control and (non)linear optimization. The problems are categorized based on timescales dictated by the network dynamics, and organized methodologically based on the problem complexity. A growing body of literature has addressed problems in this domain, albeit, with poorly motivated assumptions and behavioral models that obscure precise device behavior. With a combination of circuit- and control-theoretic lenses, we establish appropriate dynamic models for the networked resources, illustrate how common engineering assumptions arise, uncover how problems are linked, and postulate open challenges.
(non)linear optimization↗
Improving the Transformation Efficiency of Synechococcus sp. PCC 7002 via Methylome-Guided Premethylation of DNA
Cyanobacteria are promising microbial platforms for a diverse set of biotechnology applications, from living materials to photosynthetic chemical production, but are less well characterized than commonly engineered microbes such as Escherichia coli. This study facilitates genetic engineering in Synechococcus sp. PCC 7002, a fast-growing, halotolerant, and naturally competent strain, by identifying ten native methylation motifs and designing shuttle strains that mimic the native methylation state by expressing a subset of heterologous methyltransferases. DNA methylation in E. coli with as few as two active methyltransferases increased transformation efficiency up to 30-fold across four distinct integration sites in PCC 7002. This work provides an experimental framework to bypass native restriction-modification systems for efficient genome editing and metabolic engineering in nonmodel bacteria.
59 BASIC BIOLOGICAL SCIENCES↗
An introduction to developing GitLab/Jacamar runner analyst centric workflows at Sandia
This document provides very basic background information and initial enabling guidance for computational analysts to develop and utilize GitOps practices within the Common Engineering Environment (CEE) and High Performance Computing (HPC) computational environment at Sandia National Laboratories through GitLab/Jacamar runner based workflows.
97 MATHEMATICS AND COMPUTING↗
Review of Low-Cost Organic and Inorganic Phase Change Materials with Phase Change Temperature between 0°C and 65°C
Phase change materials (PCMs) that undergo a phase transition may be used to provide a nearly isothermal latent heat storage at the phase change temperature. This work reports the energy storage material cost ($/kWh) of various PCMs with phase change between 0-65°C. Four PCM classes are analyzed for their potential use in building systems: 1) inorganic salt hydrates, 2) organic fatty acids, 3) organic fatty alcohols, and 4) organic paraffin waxes. Many salt hydrates have low material costs (0.09 - 2.53 $-kg-1), high latent heat of fusion (100-290 J-g-1), and high densities (1.3-2.6 g-cm-3), leading to favorable volumetric storage density and low energy storage costs, 50-130 kWh-m3 and 0.90-40 $-kWh-1, respectively. Some salts are notably more expensive due to their scarcity or pressures from competing industries such as lithium-based salts. Fatty acids have the lowest energy storage cost in the temperature range 8-17°C at 6.50 – 40 $-kWh-1. Despite favorable latent heat (125 – 250 J-g-1) their low density gives (0.9 g-cm3) gives poor volumetric storage capacity, 32 – 80 kWh-m3. Fatty alcohols generally have high material costs 2.50 – 200 $-kg-1 which leads to high energy storage costs, 40-3000 $/kWh. With latent heat and density similar to fatty acids, fatty alcohols have poor volumetric energy storage, 43 – 55 kWh-m-3.Paraffin waxes containing only a single length carbon chain have a higher energy cost (15 – 500 $-kWh-1) than generic paraffin waxes containing many lengths of carbon chains (7 – 30 $-kWh-1). Pure waxes have a discrete phase change temperature due to their homogeneity. In contrast, a less refined generic wax with several carbon chain lengths is more likely to have a pronounced temperature glide during its phase change. Pure single carbon chain waxes are generally required for applications <45°C as generic paraffin waxes melt between 45-70°C. For many waxes, a solid-solid transition occurs at temperatures below the solid-liquid phase change. For pure paraffins with carbon content ≥22 C atoms, these transitions may appear near the same temperature resembling a temperature glide.The challenges with fatty acids, fatty alcohols, and waxes are low thermal conductivity, low density, some flammability concerns, and compatibility issues with some common engineering materials such as polymers. Challenges with salt hydrates are pronounced supercooling (>5°C), incongruent melting, and corrosiveness. All PCMs may degrade if exposed to ambient conditions and therefore require proper sealing.
Hirschey, Jason↗
Oversizing and Part-Load Problems
Oversizing, the common engineering practice of specifying devices with capacity exceeding the actual load requirement, is a widespread practice across virtually all building technologies end-use categories, including HVAC, electrical systems, lighting, appliances, and plug loads. This practice, driven by factors like design uncertainty, institutional pressures, and risk aversion, results in wasted capital investment, control difficulties, and excessive energy consumption due to inefficient part-load operation. Part-load operation, where devices run below maximum capacity, is the dominant operating mode in most energy systems and presents a complex design challenge. Solutions to match output to load fall into three broad categories: constraining the output, adjusting the device’s internal behavior, and linking output to energy storage or other waste-heat reuse applications. The energy implications of part-load are critical, as efficiency often drops sharply as load decreases across a wide diversity of devices. To quantify the extent of this problem, we derive a dimensionless Part-Load Metric (PLM) based on device efficiency and its frequency distribution of operating hours at various output levels. The PLM quantifies the deviation of a device's actual efficiency from its maximum design efficiency. This metric also serves as a measure of "capital inefficiency," enabling engineers to compare the impact of different part-load solutions and providing a unified framework for evaluating performance across various devices and systems.
Meier, Alan↗
Common occupational classification system amendments for Accelerator Science and Engineering workforce
A common system to classify occupations and skills is essential to support accelerator workforce planning between the Department of Energy (DOE) National Laboratories. In 2025, ten DOE laboratories conducted a census of their accelerator science and engineering workforce and projected their accelerator workforce needs for the next ten years. To support this, revision 3 of the “Common Occupational Classification System” (COCS) was used as a common taxonomy. Modifications were made to include accelerator-specific skills and specialisms. COCS was originally developed for DOE Office of Environmental Restoration and Waste Management in 1996. The framework provides a high-level functional structure that can be expanded with further occupations and specialisms and remains well aligned to DOE laboratory roles nearly 30 years later. Accelerator occupations and specialisms were added to the framework for the 2025 effort to quantify the accelerator workforce. This document is a companion document to COCS and provides a definition for these new occupations and specialisms that do not appear in COCS. Proceeding with a stable taxonomy is seen as essential such that its use becomes easier each year; the taxonomy as used for the 2025 effort is recommended to be continued.
43 PARTICLE ACCELERATORS↗
Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers
The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.
24 POWER TRANSMISSION AND DISTRIBUTION↗