SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This Tech. Note describes the SVD technique in the Lorentz force numerical solver zgoubi. It has been used as a tool to study the effect of vertical orbit perturbation on polarization transmission in RHIC, and for the study of the compensation of orbit defects resulting from stray fields in the EIC RCS.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
REopt(R) is a mixed-integer optimization model that minimizes the lifecycle cost of serving energy loads at a site. This work provides and introduction to the model along with its key workflow, techno-economic inputs, key outputs, and key caveats for readers to understand REopt the when, why, how of using this model. This resource also includes helpful links related to REopt model and the data sources it uses during the optimization.
This project is part of a nationwide effort to highlight the advantages of incorporating low-temperature geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). The initiative aims to hasten the nation's decarbonization process by exploring the potential for using low-temperature geothermal resources (< 150 Degrees Celsius) in selected sedimentary basins that have several population centers. The Play Fairway Analysis (PFA) techniques were modified from earlier studies of sedimentary basin geothermal play types (SBGPTs) that assessed the viability of low-temperature resources. The decision-making process for leveraging low-temperature geothermal resources for GDU and CHP applications is complex and considers a variety of factors, including geological, economic, and risk criteria. This study covers workflows, relevant datasets, python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. The proposed geothermal PFA approach for low-temperature geothermal resources includes: (1) identifying available relevant data and grouping data sets into PFA criteria (e.g., geological, economic, and risk criteria); (2) analyzing data gaps enable future focalized exploration; (3) performing uncertainty quantification; (4) weighting relevant data; (5) developing favorability and common risk maps for low-temperature geothermal resources to identify potential locations for more focused data collection. This project will facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.
Explore the source record for details and available documents.
The phenomenon of random fluctuations in the amplitude and phase of received transionospheric radio frequency (RF) signals is well known and documented. For wide band signals, sometimes a set of frequencies in the the band or even the whole band can suffer degradation or complete drop out at the receiver. The former is known as frequency selective scintillation where only a fraction of the signal bandwidth is affected, whereas the latter is known as flat fading.
U.S. Forest Service (USFS) wildfire base camps use portable power for electrical needs, including yurts and trailers from which logistics staff work during the incident. These yurts and trailers are conventionally powered by portable diesel generators. Hybrid portable power systems consisting of a combination of solar photovoltaics (PV), battery energy storage systems (BESS), and/or backup diesel generators have been used in recent years and were piloted by the National Technology and Development Program (NTDP) on incidents in fall 2024 as part of NTDP's Portable Power Project. As part of that project, this work included the development of two Excel-based tools and two reports explaining the tools. The first tool, the Incident Energy Systems Model, is an Excel-based tool that models the power output of hybrid portable power systems powering yurts and/or trailers at fire camps over a typical day. The associated report (published separately) outlines a user guide for the model and walks through two scenarios. The two scenarios are 1) trailers powered by rooftop solar PV, batteries, and a back-up diesel generator, and 2) trailers powered by ground mount solar PV, batteries, and a back-up diesel generator. The second tool is a high-level cost-benefit analysis of the same two types of portable power systems, and is location independent.
U.S. Forest Service (USFS) wildfire base camps use portable power for electrical needs, including yurts and trailers from which logistics staff work during the incident. These yurts and trailers are conventionally powered by portable diesel generators. Hybrid portable power systems consisting of a combination of solar photovoltaics (PV), battery energy storage systems (BESS), and/or backup diesel generators have been used in recent years and were piloted by the National Technology and Development Program (NTDP) on incidents in fall 2024 as part of NTDP's Portable Power Project. As part of that project, this work included the development of two Excel-based tools and two reports explaining the tools. The first tool, the Incident Energy Systems Model, is an Excel-based tool that models the power output of hybrid portable power systems powering yurts and/or trailers at fire camps over a typical day.
Explore the source record for details and available documents.
The mechanical properties derived from simple tensile tests are uniquely important in the design and qualification of load bearing metallic components. The tensile properties in standards for wrought metallic materials are generally accessible for design and simulation engineers, but this is not the case for additively manufactured metals. This work investigates the influence of tensile specimen geometry on the mechanical properties of laser powder bed fusion (LPBF) additively manufactured Ti-6Al-4V, particularly in relation to properties measured from specimens excised from an exemplar part. A comprehensive analysis was conducted across various specimen geometries, considering factors such as thermal history, cross-sectional area, shape, and surface roughness. Key findings reveal that sample size, particularly cross-sectional area, significantly affects reported tensile properties, with ASTM E8 flat and round specimens exhibiting differences in elastic modulus (13%), yield strength (17%), ultimate tensile strength (UTS) (14%), and elongation to failure (11%). Additionally, surface roughness was found to have a limited impact on ASTM round geometries, but it becomes critical in thin-walled and small high-throughput samples. The ASTM flat samples closely matched the properties of samples excised from the exemplar part, underscoring the necessity of testing witness samples that accurately represent end-use conditions. Furthermore, mechanical properties of samples built within the stitch zone of the exemplar part demonstrated reduced ductility, highlighting the importance of laser alignment and qualification in multi-laser additive manufacturing processes. Overall, this study emphasizes the need for careful consideration of specimen geometry and testing conditions to ensure accurate reporting of mechanical properties in LPBF Ti-6Al-4V.
This presentation details mission-driven data science initiatives at Jefferson Lab and the Joint Institute for Advanced Computing on Environmental Studies (ACES). JLab, a U.S. Department of Energy Office of Science national laboratory, operates the Continuous Electron Beam Accelerator Facility (CEBAF), and is the lead institute for the new High Performance Data Facility (HPDF) Hub. The Joint Institute for ACES brings together interdisciplinary teams in health informatics, climate modeling, computer science, and physics to address environmental challenges, including flood modeling. The Hampton Roads region, particularly Norfolk and Virginia Beach, faces increasing flood risks, motivating the need for rapid, reliable, and risk-aware decision support. ACES’s flooding work has a focus on uncertainty quantification (UQ) and machine learning (ML) for coastal flood management. The work is motivated by the increasing vulnerability of communities such as Norfolk and Virginia Beach, Virginia, to frequent coastal flooding events, and the need for rapid, reliable decision support. The research develops computationally efficient ML surrogate models to forecast water levels and flooding risk. A central theme is the quantification and calibration of predictive uncertainty, especially for out-of-distribution (OOD) scenarios, using techniques such as Monte Carlo Dropout, Deep Ensembles, Gaussian Processes, and Deep Quantile Regression (DQR). The study demonstrates that distance-aware UQ is critical for reliable scientific AI, particularly in high-dimensional, safety-critical, and real-time applications.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Effective stakeholder engagement in decisions about complex systems involving sustainable agribusiness requires substantial time and resources by both the managers involved in a supply chain and their stakeholders. Therefore, it is important to understand how to design and implement business strategies that integrate stakeholder perspectives as the project develops. The objective of this article is to explore how actors interested in sustainable and resilient agribusinesses can effectively involve stakeholders in supporting strategies to advance a circular carbon bioeconomy. We consider an approach for stakeholder engagement based on six principles: diversity, listening, value, trust, accountability, and flexibility/ adaptability. Practical means for agribusinesses to apply the six principles to the circular carbon bioeconomy are discussed along with challenges encountered when applying them. Managerial choices and engagement designs and practices are specific to each type of agribusiness. Employing this approach can help project developers prioritize, prepare, and sustain stakeholder engagement, and build local capacities for continual improvement and informed decisions aligned with more sustainable business strategies.