Results for “Aerospace engineering” — Page 4

DOE OSTI2024

Design and Development of a Fixtureless, Pass-through Machine Tool for Extrusion Machining

The aerospace, construction/architecture, and transportation manufacturing industries rely heavily on the mass production of near-net shape metallic and composite extrusions. While the production of raw extrusions is a relatively fast process, adding functional features such as holes and slots require additional time, cost, and energy to produce. To compensate for the inherent flexibility of extrusions, conventional machining requires rigid purpose-built fixtures for operations such as trimming, drilling and thinning. This approach requires that the machine tools be as large or larger than the parts themselves. This results in the need for excess shop floor space, energy for auxiliary equipment and motion systems, and significant capital expenditure. Considerable engineering expense and time involved in the designing, building, and proving out of part-specific fixtures for holding the components in specific configurations while machining add to the overall manufacturing cost. The primary objective of the technical collaboration between Oak Ridge National Laboratory and Fairmount Technologies (FT) is to improve the XM-3, a fixtureless CNC milling machine designed by FT. The machine was developed to trim, drill, and thin extrusions without part specific fixturing to make the manufacturing process more efficient and flexible. Dynamic measurements of the existing structure were collected, and modeling efforts were made to evaluate optimal machining parameters for the current system. Areas of improvement to increase the system stiffness, manufacturability, and machining efficiency were evaluated and highlighted for the next generation design. The impact of this effort may enable agile manufacturing across the commercial and defense aerospace industries, and other industries where extrusions are utilized like in the construction, architecture, and transportation industries.

42 ENGINEERING↗

DOE OSTI2025

Design and Development of a Fixtureless, Pass-through Machine Tool for Extrusion Machining

The aerospace, construction/architecture, and transportation manufacturing industries rely heavily on the mass production of near-net shape metallic and composite extrusions. While the production of raw extrusions is a relatively fast process, adding functional features such as holes and slots require additional time, cost, and energy to produce. To compensate for the inherent flexibility of extrusions, conventional machining requires rigid purpose-built fixtures for operations such as trimming, drilling and thinning. This approach requires that the machine tools be as large or larger than the parts themselves. This results in the need for excess shop floor space, energy for auxiliary equipment and motion systems, and significant capital expenditure. Considerable engineering expense and time involved in the designing, building, and proving out of part-specific fixtures for holding the components in specific configurations while machining add to the overall manufacturing cost. The primary objective of the technical collaboration between Oak Ridge National Laboratory and Fairmount Technologies (FT) is to improve the XM-3, a fixtureless CNC milling machine designed by FT. The machine was developed to trim, drill, and thin extrusions without part specific fixturing to make the manufacturing process more efficient and flexible. Dynamic measurements of the existing structure were collected, and modeling efforts were made to evaluate optimal machining parameters for the current system. Areas of improvement to increase the system stiffness, manufacturability, and machining efficiency were evaluated and highlighted for the next generation design. The impact of this effort may enable agile manufacturing across the commercial and defense aerospace industries, and other industries where extrusions are utilized like in the construction, architecture, and transportation industries.

42 ENGINEERING↗

DOE OSTI2026

Rapid Evaluation Framework for the CMIP7 Assessment Fast Track

As Earth system models (ESMs) grow in complexity and in volume of output data, there is an increasing need for rapid, comprehensive evaluation of their scientific performance. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require expeditious response for model analyses designed to inform and drive integrated Earth system assessments. To meet this challenge, the Rapid Evaluation Framework (REF), a community-driven platform for benchmarking and performance assessment of ESMs, was designed and developed. The initial implementation of the REF, constructed to meet the near-term needs of the CMIP7 Assessment Fast Track, builds upon four disparate community evaluation and benchmarking tools that are coupled together using the Coordinated Model Evaluation Capabilities (CMEC) framework. The REF runs within a containerized workflow for portability and reproducibility and is aimed at generating and organizing diagnostics covering a variety of model variables. The REF leverages well documented observational datasets to provide assessments of model fidelity across a collection of diagnostics. All diagnostics were identified and selected with community involvement and consultation. Operational integration with the Earth System Grid Federation (ESGF) will permit automated execution of the REF for selected diagnostics as soon as model output data are published on ESGF by the originating modeling centers. The REF is designed to be portable across a range of current computational platforms to facilitate use by modeling centers for assessing the evolution of model versions or gauging the relative performance of CMIP simulations before being published on ESGF. When integrated into production simulation workflows, results from the REF provide immediate quantitative feedback that allows model developers and scientists to quickly identify model biases and performance issues. After the REF is released to the community, its subsequent development and support will be prioritized by an international consortium of scientists and engineers, enabling a broader impact across Earth science disciplines. For instance, the REF will facilitate improvements to models and will enhance confidence in model projections through process-based selection of models based on their performance with respect to observations. Production of reproducible diagnostics and community-based assessments are key features of the REF. Furthermore, providing interoperability with existing evaluation packages assures that contributions from previous community efforts will be available for use in future model intercomparison projects.

Hoffman, Forrest [ORNL] (ORCID:0000000158024134)↗

DOE OSTI2024

2024 Sustainable Aviation Energy Conference: 5 Key Messages From the Sustainable Aviation Fuel Workshop

At the 2024 Sustainable Aviation Energy Conference, more than 100 aviation leaders gathered in Dallas, Texas, to discuss collaboration and research needed to clear the path to widespread adoption of sustainable aviation technologies. During open workshops, participants from state and federal agencies; airports; aircraft and engine manufacturers; liquid fuel producers; and other stakeholder groups brainstormed the biggest barriers and opportunities for realizing a sustainable aviation ecosystem. This fact sheets presents five key messages and discussion points that emerged during a workshop on sustainable aviation fuel.

advanced air mobility↗

DOE OSTI2024

2024 Sustainable Aviation Energy Conference: 5 Key Messages From the Airport Enabling Efforts Workshop

At the 2024 Sustainable Aviation Energy Conference, more than 100 aviation leaders gathered in Dallas, Texas, to discuss collaboration and research needed to clear the path to widespread adoption of sustainable aviation technologies. During open workshops, participants from state and federal agencies; airports; aircraft and engine manufacturers; liquid fuel producers; and other stakeholder groups brainstormed the biggest barriers and opportunities for realizing a sustainable aviation ecosystem. This fact sheets presents five key messages and discussion points that emerged during a workshop on airport enabling efforts.

advanced air mobility↗

DOE OSTI2024

2024 Sustainable Aviation Energy Conference: 5 Key Messages From the Alternative Fueling (Energy) Infrastructure Workshop

At the 2024 Sustainable Aviation Energy Conference, more than 100 aviation leaders gathered in Dallas, Texas, to discuss collaboration and research needed to clear the path to widespread adoption of sustainable aviation technologies. During open workshops, participants from state and federal agencies; airports; aircraft and engine manufacturers; liquid fuel producers; and other stakeholder groups brainstormed the biggest barriers and opportunities for realizing a sustainable aviation ecosystem. This fact sheets presents five key messages and discussion points that emerged during a workshop on alternative fueling (energy) infrastructure.

advanced air mobility↗

DOE OSTI2026

Capture, storage, and re-use of liquid hydrogen boil-off for aviation and aerospace applications

Despite major interest in the use of liquid hydrogen as a fuel for aviation and aerospace sectors, loss of hydrogen through boil-off continues to be a hurdle as it causes financial loss, indirect greenhouse gas emissions, and safety concerns. Herein, we perform techno-economic analysis, calibrated with experimental measurements, to assess the use of sorbents to capture and condition hydrogen boil-off events in the range of 1.5 to 70 tonnes per day at launch sites and airports. We evaluate the direct delivery of captured boil-off to combustion engines and fuel cells, comparing against boil-off re-liquification and compression. Results indicate probable cost-effectiveness at delivered liquid hydrogen prices above 0.9 U.S. dollar ($) per kg H2 at airports, and above 10 $ per kg H2 at launch sites where 10% or more of hydrogen is lost to boil-off.

08 HYDROGEN↗

DOE OSTI2024

AI-assisted discovery of high-temperature dielectrics for energy storage

Abstract Electrostatic capacitors play a crucial role as energy storage devices in modern electrical systems. Energy density, the figure of merit for electrostatic capacitors, is primarily determined by the choice of dielectric material. Most industry-grade polymer dielectrics are flexible polyolefins or rigid aromatics, possessing high energy density or high thermal stability, but not both. Here, we employ artificial intelligence (AI), established polymer chemistry, and molecular engineering to discover a suite of dielectrics in the polynorbornene and polyimide families. Many of the discovered dielectrics exhibit high thermal stability and high energy density over a broad temperature range. One such dielectric displays an energy density of 8.3 J cc −1 at 200 °C, a value 11 × that of any commercially available polymer dielectric at this temperature. We also evaluate pathways to further enhance the polynorbornene and polyimide families, enabling these capacitors to perform well in demanding applications (e.g., aerospace) while being environmentally sustainable. These findings expand the potential applications of electrostatic capacitors within the 85–200 °C temperature range, at which there is presently no good commercial solution. More broadly, this research demonstrates the impact of AI on chemical structure generation and property prediction, highlighting the potential for materials design advancement beyond electrostatic capacitors.

25 ENERGY STORAGE↗

DOE OSTI2024

Physics-Guided Machine Learning (PGML) for Improved Aerostructure Manufacturing

The Physics-Guided Machine Learning (PGML) for Improved Aerostructure Manufacturing project objective is to automatically tune machining parameter predictions from physics-based models using process data and Bayesian machine learning. The intent is to enable a step change in aerospace manufacturing by combining machine learning, physics-based process models, and sensors/data in a comprehensive digital environment that simultaneously considers the computer numerically controlled (CNC) machining center capabilities, the workpiece material and geometry, and the workpiece support (fixturing). The project hypothesis is that this combination will enable improved performance in machining operations.

42 ENGINEERING↗

DOE OSTI2025

A Semi-supervised Hybrid Machine Learning Framework for the Qualification of Resistance Spot Welds

• Industries requiring high structural integrity, including automotive, aerospace, and construction, place considerable significance on weld quality classification. • The inspection normally involves human expertise through predefined quality metrics that are subjective, error-prone, and time-intensive • The challenge to classification model development is the scarcity of labeled data and imbalanced distributions in the data that are labeled. • This work develops a new hybrid methodology that achieves clustering using KMeans++ together with supervised classification to overcome these challenges. • The ensemble-based classifiers were identified as optimal, with accuracy enhancements of up to 8% using the pseudo-labeled dataset. • The work provides practical insight into feature engineering and machine learning integration in industrial quality assurance applications.

Rogers, Jeremy K. [Savannah River National Laborat↗

DOE OSTI2026

Nonlinear viscoelastic response of silicone additively manufactured direct ink write (DIW) foams under repetitive compression

To investigate dynamic fatigue behavior of foam in military protective applications, such as helmets, additively manufactured (AM) foams were compressively strained into the plateau region using a reduced design of experiments. A simple power law was found to govern the decline in dynamic stiffness (complex modulus) as the foams underwent the purchase order requirement of 10,000 cycles of small deformation in the plateau region. This rate of decline was newly found to correlate with the degree of nonlinearity in the material’s deformation, quantified using total harmonic distortion. Materials with low nonlinearity exhibited relatively stable stiffness across cycles, while those with high nonlinearity experienced greater losses. The observed nonlinearity depended on both applied stress and strain rate. A strong linear correlation (R 2 = 0.78) was identified between second-order nonlinearity and the time-dependent stiffness response. Two lattice structures were examined: face-centered tetragonal (FCT) and simple cubic (SC). The SC material exhibited higher total harmonic distortion (5%) and lower stiffness retention than the FCT (2%). In conclusion, these results suggest that for cyclic compression applications in a wide variety of industries such as packaging, personal protective equipment, or aerospace, selecting materials with lower stress and greater structural uniformity can enhance the stability of dynamic performance.

42 ENGINEERING↗

DOE OSTI2025

Capacitated p -hub approach for park-and-ride facility location problem under nested logit demand function: polyhedral approaches

By generalizing the unconstrained p-hub approach for the park-and-ride (P&R) facility location problem under the multinomial logit demand function, the capacitated p-hub approach for the problem under the nested logit demand function captures a broader range of real-world cases. To solve this problem optimally, we introduce a mixed-integer linear program and accelerate its solution by enhancing the branch-and-cut procedure. To address the problem at a large scale, we introduce two other polyhedral approaches: variable neighborhood search (VNS) and adaptive randomized rounding (ARR). Downtown areas in Seoul have a high modal share of public transportation and congested road traffic, yet P&R has not been widely implemented. Therefore, we apply the ARR procedure to solve a real-world problem using traffic and geographic data from the Seoul metropolitan area. ARR performs better than VNS and addresses real-world cases. The solutions obtained by ARR present a phased expansion plan that encourages policymakers to start installing a small number of P&Rs immediately.

Capacitated p-hub approach↗

DOE OSTI2025

Spike-Free Adaptive Sliding Mode Control: Application to Permanent Magnet Synchronous Motors

A new methodology for adaptive sliding mode control (ASMC) has been widely used to improve the control performance in various systems. This method exhibits several advantages, including low sliding mode control (SMC) chattering, no knowledge of the system disturbance bound, and no overestimation of the control gain. Despite its advantages, this method can be hampered by the spike phenomenon, slow control gain convergence, and difficulty in achieving optimal performance under varying disturbances. Consequently, this article proposes a spike-free ASMC method with a disturbance observer (DOB) to address these problems. Previous ASMC methods have been analyzed via simulations to verify the aforementioned problems. Here, this analysis highlights the need for disturbance compensation and improvements in the SMC gain adaptation law. Therefore, a DOB is designed to mitigate the spike phenomenon by compensating for disturbances. Subsequently, an SMC gain adaptation law based on disturbance error estimation is designed to eliminate the spike phenomenon completely. The proposed adaptation law makes the SMC gain to converge to a slightly higher value than the disturbance estimation error. Consequently, the proposed method not only eliminates the spike phenomenon, but also ensures optimal performance under varying disturbances. The performance of the proposed method is experimen tally validated through a comparative study.

42 ENGINEERING↗

DOE OSTI2025

An evolving Coupled Model Intercomparison Project phase 7 (CMIP7) and Fast Track in support of future climate assessment

The Coupled Model Intercomparison Project (CMIP) coordinates community-based efforts to answer key and timely climate science questions, facilitate delivery of relevant multi-model simulations through shared infrastructure, and support national and international climate assessments. Generations of CMIP have evolved through extensive community engagement from punctuated phasing into more continuous support for the design of experimental protocols, infrastructure for data publication and access, and public delivery of climate information. We identify four fundamental research questions motivating a seventh phase of coupled model intercomparison relating to patterns of sea surface temperature change, changing weather, the water–carbon–climate nexus, and tipping points. Key CMIP7 advances include an expansion of baseline experiments, a focus on CO 2 -emissions-driven experiments, sustained support for community MIPs, periodic updating of historical forcings and diagnostics requests, and a collection of prioritized experiments, or the “Assessment Fast Track”, drawn from community MIPs to support climate research, assessment, and service goals across prediction and projection, characterization, attribution, and process understanding.

Environmental sciences↗

DOE OSTI2024

Minimization of Measurement Uncertainty in Optical Frequency Domain Reflectometry

Optical frequency domain reflectometry (OFDR) is a technique for interrogating optical fiber sensors to generate relative, quasi-distributed measurements. Although Optical frequency domain reflectometry (OFDR) is increasingly being adopted for aerospace, energy production, and structural monitoring applications, the quantification of uncertainty for OFDR measurements has not been developed beyond sparse empirical relationships. To address this knowledge gap, an uncertainty metric for OFDR measurements was developed. This uncertainty metric was applied to weight the edges between OFDR measurements on directed correlation graphs and analyzed to minimize the cumulative uncertainty. In conclusion, this work is the first to propose an uncertainty metric for OFDR and provides a generalized mathematical framework for optimizing OFDR hardware selection, optical fiber sensor selection, and postprocessing strategy.

42 ENGINEERING↗

DOE OSTI2026

Reliable statistics-based detection and investigation of anomalies in a SMART valve system

Reliable anomaly detection and diagnosis are critical for the safe operation of complex engineered systems. This study presents a unified framework that integrates statistical, model-based, and data-driven techniques for anomaly detection and investigation, demonstrated on SMART valve systems in hybrid energy applications. Four detection methods—mean deviation, seasonal extreme studentized deviate, ARIMA forecasting, and matrix profiling—were implemented and compared. Matrix profiling was particularly effective in revealing subtle deviations and hidden relationships among variables. Anomaly investigation was performed by analyzing variable-level and grouped signal profiles, with system topology incorporated to distinguish primary faults from propagated effects. Grouping signals by type enhanced interpretability, enabling accurate localization of anomalies across multi-dimensional datasets. Experimental results confirmed the framework's capability to consistently detect and isolate anomalies while providing actionable insights into system interdependencies. The proposed methodology offers a robust, interpretable, and scalable solution for condition monitoring, with potential applications in safety-critical domains such as nuclear energy, aerospace, and process industries.

ARIMA models↗

DOE OSTI2025

Snap-Through Buckling Pressure Prediction of Spherical Caps: A Comparison of Analytical, Implicit, and Explicit Methods

Snap-through buckling is a nonlinear and dynamic instability that occurs in curved shell structures such as domes, pressure vessels, and aerospace panels. Unlike classical linear buckling, it involves a sudden transition between equilibrium states caused by geometric nonlinearity and rapid strain-to-kinetic energy conversion (Timoshenko & Gere, 1961; Budiansky & Roth, 1962). This study investigates the snap-through behavior of thin spherical caps using both implicit and explicit solvers in ANSYS Workbench. While implicit analysis accurately captures quasi-static response, it struggles with convergence near instability. In contrast, explicit LS-DYNA simulation naturally handles the nonlinear dynamic event with minimal tuning and computational cost.

42 ENGINEERING↗

DOE OSTI2026

Influence of rolling reduction and annealing on recrystallization and grain structure in Ta-2.5W alloys

The microstructural evolution of wrought Tantalum - 2.5 wt% Tungsten (Ta-2.5W) alloys during thermomechanical processing is critical for optimizing their mechanical reliability in demanding applications such as aerospace, chemical processing, and nuclear technology. Despite the widespread use of Ta-W alloys, a comprehensive understanding of how rolling reduction, annealing temperature, and elemental inhomogeneity interact to determine recrystallization behavior and grain refinement remains incomplete. Here, in this study, we systematically investigate the effects of cold rolling and subsequent annealing on the microstructure of Ta-2.5W, with particular attention to grain orientation, stored energy, and elemental banding. Our results demonstrate that higher rolling reduction rates lower the onset and completion temperatures for recrystallization, resulting in finer and more homogeneous grain structures. Electron backscatter diffraction (EBSD) analysis reveals that grains with a 〈111〉 parallel to the plate normal possess higher stored energy and nucleate recrystallization more readily than grains with a 〈001〉 parallel to the plate normal. Elemental mapping shows that tungsten inhomogeneity leads to localized bands of accelerated recrystallization and hardness variation. These findings provide new insights into the mechanisms of microstructure refinement in Ta-2.5W alloys, offering guidance for tailoring processing routes to achieve superior performance in demanding engineering environments.

Annealing↗