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Results for “light-weighting”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Friction stir processing: A thermomechanical processing tool for high pressure die cast Al-alloys for vehicle light-weighting

This study uses friction stir processing (FSP) for thermomechanical processing of high-pressure die-casting (HPDC) to modify microstructure and improve mechanical properties. FSP is carried out on two different HPDC aluminum alloys: (a) general-purpose, high-iron, HPDC A380 alloy and (b) premium quality, low-iron HPDC Aural-5 alloy in thin wall, flat plate geometry. Subsequent mechanical testing shows ~30 % and ~65 % enhancement in yield strength and tensile ductility. In addition, FSP leads to ~10 times improvement in fatigue life for A380 alloy and ~70 % improvement in fracture toughness for Aural-5 alloy. These findings emphasize the capability of FSP to modify the microstructure of HPDC Al-alloys-based structural components so that they can demonstrate a good combination of strength, ductility, fracture toughness, and high fatigue properties for long-term durability and reliability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Challenges and Opportunities Specific to Microreactors: Compact and Light-Weight Shielding During Operation and Transportation

The problem of designing a shield for a mobile microreactor has been addressed. The principal challenges encountered in this endeavor are the dual goals of increasing radiation protection and decreasing weight. It is recognized that these two goals are contradictory. Increasing shielding naturally increases weight. Conversely, decreasing weight naturally calls for decreasing material inventory, including possibly decreasing shield mass. The operational and regulatory drivers for shielding and transportation constraints are identified and summarized. The main constraints pertain to volume, mass, radiation dose, material feasibility and availability, and decommissioning expectations. The latter are limits on residual contamination and dose rates after the reactor is removed. Progress toward solving the challenge of shielding a transportable microreactor is made by considering a tungsten tetraboride (WB4) shell surrounding the reactor vessel. The shield and a generic microreactor were modeled using the MCNP code. It was determined that the presence of a 16-cm-thick WB4 shield reduces the dose equivalent rate during operations to 3.6 mrem/h just outside of a concrete vault and dome and soil berm surrounding the reactor, which is very near the occupational dose rate limits. Without the WB4 layer, the dose rate at the same location outside the berm would be 120 mrem/h. Most importantly, the presence of the WB4 shield substantially protects the surrounding concrete and soil from activation, thus decreasing the duration of administrative control for the site following removal of the reactor from 16 to 3.4 years. At that point, the site may be decommissioned and returned to unrestricted public access. A limitation on the incorporation of a WB4 shield as an intrinsic component of a microreactor is that it results in a design that is transportable only by using the largest road conveyances and that the load would require special permits for transit through the U.S. highway system. New directions for further improvements and possibly more effective solutions to the shielding problem of a mobile microreactor are discussed in the conclusion section.

Microreactor↗
DOE OSTI2025

LightMat Seedling Project: Enabling the Development of High Strength Magnesium Alloy Sheet for Light-Weighting Applications

It is well known that a 10% reduction in vehicle weight can result in a 6-8% fuel economy improvement in gasoline/diesel vehicles. Replacing steel and aluminum with magnesium can result in weight savings between 25 and 75% and hence magnesium alloys have been considered for multiple body-in-white components to reduce the weight of the glider. For example, magnesium sheet has been considered for decklid inner panels, rear seatback panels, roof panels, and door inners.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coarse-grained molecular dynamics simulation of solvent-dependent cellulose nanofiber interactions

Associations between cellulose are important both in biofuel production and in the use of cellulose for biomaterials. Cellulose nanofibers (CNFs) are sustainable, strong, light-weight alternatives to traditional materials in manufacturing, but are challenging to obtain due to irreversible aggregation in solution during preparative fibrillation. Therefore, it is imperative to understand the underlying factors driving aggregation with a view to designing solvents that can effectively compete with interfiber interactions, hence reducing aggregation. Molecular dynamics (MD) simulation at atomic detail can provide useful information on local interactions. However, the length and timescales accessible are too short to fully capture association processes. Here, we provide a method for accessing the longer length and timescales required using coarse-grained (CG) MD simulations with a MARTINI force field to calculate the interaction behavior of CNFs in three selected solvents: NaOH-urea-water, acetone, and neat water. The CG results are consistent with our prior all-atom MD and with previous experimental results. While acetone is found not to be an effective solvent, urea and ionic moieties in NaOH-urea-water not only solvate the fibrils but also improve the confinement of water molecules around them as shown by the solvent residence times and mean-square displacements. Overall, the presence of urea and ions reduces the likelihood of aggregation in multi-CNF systems relative to neat water irrespective of whether the hydrophobic or hydrophilic CNF surfaces are interacting. In conclusion, the CG method shows clear promise for selecting potential high-performance solvents for experimental prioritization in bioenergy and biomaterials research in a relatively fast manner as well as for understanding the aggregation and rheological behavior of CNF-solvent systems.

aggregation↗
DOE OSTI2024

Electrical property enhancement of non-heat-treatable wrought aluminum alloys using graphene additives

With growing efforts of electrification, aluminum’s role as a light-weight conductor material has become increasingly prominent. There is a critical need to improve the electrical performance of aluminum at room temperature and high operating temperatures. In this study, the effect of graphene nanoparticle additives on the electrical performance of a non-heat treatable alloy were (AA3003) explored. Graphene’s unusual structure and electronic properties were used to improve AA3003 properties. Here, in this work, the effects of graphene on the evolution of electrical properties and microstructural features have been explored on lab scale hot extruded AA3003-graphene composites. Hot pressing schedules and extrusion temperatures were varied to investigate changes in intermetallic dispersion characteristics in the presence of dispersed graphene. We measured a reduction of 10.3 % in the temperature coefficient of resistance in the AA3003 sample with 0.05 wt% graphene extruded at 400 °C, along with a maximum increase of 1.1 % in electrical conductivity at 20 °C. Increasing the hot-pressing times up to 8 hours was also found to consistently increase the electrical conductivity, due to increased precipitation of intermetallic phases. Despite being a non-heat treatable alloy, AA3003 displays interesting precipitation dynamics and grain recrystallization trends that can be modulated with varying levels of heat treatment, graphene concentrations, and hot extrusion process parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ambient energy for buildings: Beyond energy efficiency

The following Key Messages comprise the salient findings of this study: 1. Ambient energy (from sun, air, ground, and sky) can heat and cool buildings; provide hot water, ventilation and daylighting; dry clothes; and cook food. These services account for about three-quarters of building energy consumption and a third of total US demand. Biophilic design (direct and indirect connections with nature) is an intrinsic adjunct to ambient energy systems, and improves wellness and human performance. 2. The current strategy of electrification and energy efficiency for buildings will not meet our climate goals, because the transition to an all-renewable electric grid is too slow. Widespread adoption of ambient energy is needed. Solar-heated buildings also flatten the seasonal demand for electricity compared to all-electric buildings, reducing required production capacity and long-term energy storage. In addition, ambient-conditioned buildings improve resilience by remaining livable during power outages. 3. National policies, incentives, and marketing should be enacted to promote ambient energy use. Federal administrative priorities should reflect the importance of ambient energy for buildings. Use of ambient energy should be encouraged through existing and new building codes and standards. 4. Ambient energy system design tools are needed for architects, engineers, builders, building scientists, realtors, appraisers, and consumers. PVWatts is used over 100 million times per year for photovoltaic system design. A similar, simple, and accessible tool for ambient design is crucial. 5. Training on ambient energy is needed throughout secondary, post-secondary, and continuing education for workforce development. Currently, only about 10% of colleges teach courses on passive heating and cooling systems. 6. Ambient-conditioned buildings should be demonstrated in all US climate zones. Performance should be monitored and reported, with quantitative case studies made widely available. 7. While current technology is sufficient to build high-performance ambient buildings now, research is needed to develop new technologies to harness ambient energy more effectively and more economically. Such advancements will facilitate adoption of ambient energy technologies in a wider range of buildings, including retrofits. Examples include windows with much lower thermal losses, use of the building shell as thermal storage, alternative light-weight thermal storage systems, sky radiation cooling systems, automated controls for solar gains and passive cooling, and ground coupling.

14 SOLAR ENERGY↗
DOE OSTI2024

Additive manufacturing of an ultrastrong, deformable Al alloy with nanoscale intermetallics

Abstract Light-weight, high-strength, aluminum (Al) alloys have widespread industrial applications. However, most commercially available high-strength Al alloys, like AA 7075, are not suitable for additive manufacturing due to their high susceptibility to solidification cracking. In this work, a custom Al alloy Al 92 Ti 2 Fe 2 Co 2 Ni 2 is fabricated by selective laser melting. Heterogeneous nanoscale medium-entropy intermetallic lamella form in the as-printed Al alloy. Macroscale compression tests reveal a combination of high strength, over 700 MPa, and prominent plastic deformability. Micropillar compression tests display significant back stress in all regions, and certain regions have flow stresses exceeding 900 MPa. Post-deformation analyses reveal that, in addition to abundant dislocation activities in Al matrix, complex dislocation structures and stacking faults form in monoclinic Al 9 Co 2 type brittle intermetallics. This study shows that proper introduction of heterogeneous microstructures and nanoscale medium entropy intermetallics offer an alternative solution to the design of ultrastrong, deformable Al alloys via additive manufacturing.

Science & Technology - Other Topics↗
DOE OSTI2025

Teacher-student training improves the accuracy and efficiency of machine learning interatomic potentials

Machine learning interatomic potentials (MLIPs) are revolutionizing the field of molecular dynamics (MD) simulations. Recent MLIPs have tended towards more complex architectures trained on larger datasets. The resulting increase in computational and memory costs may prohibit the application of these MLIPs to perform large-scale MD simulations. Herein, we present a teacher-student training framework in which the latent knowledge from the teacher (atomic energies) is used to augment the students' training. We show that the light-weight student MLIPs have faster MD speeds at a fraction of the memory footprint compared to the teacher models. Remarkably, the student models can even surpass the accuracy of the teachers, even though both are trained on the same quantum chemistry dataset. Our work highlights a practical method for MLIPs to reduce the resources required for large-scale MD simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The hyperplane of early-type galaxies: using stellar population properties to increase the precision and accuracy of the fundamental plane as a distance indicator

ABSTRACT We use deep spectroscopy from the SAMI (Sydney-AAO Multi-object Integral) Galaxy Survey to explore the precision of the fundamental plane (FP) of early-type galaxies as a distance indicator for future single-fibre spectroscopy surveys. We study the optimal trade-off between sample size and signal-to-noise ratio (SNR), and investigate which additional observables can be used to construct hyperplanes with smaller intrinsic scatter than the FP. We add increasing levels of random noise (parametrized as effective exposure time) to the SAMI spectra to study the effect of increasing measurement uncertainties on the FP- and hyperplane-inferred distances. We find that, using direct-fit methods, the values of the FP and hyperplane best-fitting coefficients depend on the spectral SNR, and reach asymptotic values for a mean $\langle \mathrm{ SNR} \rangle =40\, \mathrm{\mathring{\rm A}}^{-1}$. As additional variables for the FP we consider three stellar-population observables: light-weighted age, stellar mass-to-light ratio, and a novel combination of Lick indices ($I_\mathrm{age}$). For an $\langle \mathrm{ SNR} \rangle =45~\mathrm{\mathring{\rm A}}^{-1}$ (equivalent to 1-h exposure on a 4-m telescope), all three hyperplanes outperform the FP as distance indicators. Being an empirical spectral index, $I_\mathrm{age}$ avoids the model-dependent uncertainties and bias underlying age and mass-to-light ratio measurements, yet yields a 10 per cent reduction of the median distance uncertainty compared to the FP. We also find that, as a by-product, the $I_\mathrm{age}$ hyperplane removes most of the reported environment bias of the FP. After accounting for the different SNR, these conclusions also apply to a 50 times larger sample from SDSS-III (Sloan Digital Sky Survey). However, in this case, only $\mathrm{ age}$ removes the environment bias.

D’Eugenio, Francesco (ORCID:0000000323888172)↗
DOE OSTI2025

Hybrid PDES Simulation of HPC Networks Using Zombie Packets

Although high-fidelity network simulations have proven to be reliable and cost-effective tools to peer into architectural questions for high-performance computing (HPC) networks, they incur a high resource cost. The time spent in simulating a single millisecond of network traffic in the highest detail can take hours, even for static, well-behaved traffic patterns such as uniform random. Surrogate models offer a significant reduction in runtime, yet they cannot serve as complete replacements and should only be used when appropriate. Thus, there is a need for hybrid modeling, where high-fidelity simulation and surrogates run side-by-side. Here, we present a surrogate model for HPC networks in which: packets bypass the network, while the network state is left untouched, i.e., suspended. To bypass the network, we use historical data to estimate the arrival time at which every packet should be scheduled at; to suspend the network, all in-flight packets are scheduled to arrive at their destinations, and are kept in the system to awaken as zombies when switching back to high-fidelity. Speedup for a hybrid model is relative to the proportion of surrogate to high-fidelity. This light-weight surrogate obtained up to 76× speedup. Keeping the zombies in the network showed an increase in the accuracy of the high-fidelity simulation on restart when compared to restarting the network from an empty state.

HPC networks↗
DOE OSTI2024

MAPSTER

MAPSTER Observer is a light-weight software package that can be installed on field deployed computers which automatically manages data and creates metadata packages designed to organize large datasets, making them easy to retrieve and share.

Larson, MatthewD↗
DOE OSTI2024

Distribution System Dataset Generator for AI Applications [SWR-24-75]

This software is a simple, light-weight python package to generate pytorch compatible machine learning graph dataset representing electric power distribution system. User is able to use these graph datasets to test their graph generation artificial intelligence (AI) models, link prediction AI models, graph classification AI models and so much more. This package uses grid-data-models (https://github.com/NREL-Distribution-Suites/grid-data-models) as input data format for power distribution system. NREL-Ditto (https://github.com/NREL-Distribution-Suites/ditto) tool can be leveraged to transform popular distribution system file formats such as opendss, cyme and synergi to grid-data-models.

Duwadi, Kapil↗
DOE OSTI2024

High Performance Metal-Supported SOFC System for Range Extension of Commercial Aviation

The DOE ARPA-E REEACH program [1] has enabled this Phase 1 study that conceptualizes a commercial 154 passenger electric aircraft using renewable aviation fuel for range extension while meeting similar mission performance levels as current commercial aircraft. Commercial aviation accounts for about 2.5% of global CO2 emissions, and close to 5% of overall anthropogenic climate change due to the added accounting of contrail’s effects [2]. The sector has adopted a goal of carbon neutrality by 2050 [3]. 110 nations, and recently the new US administration, have embarked on work to address this important challenge. The US DOE has released a roadmap to enable the further development of sustainable aviation fuel (SAF) in the hopes that it could meet all of aviation’s fuel needs by 2050 [4]. However, SAF fuel price and sufficient future feedstock availability remains a concern [5]. Considering the first commercial biofuel flight demonstration 14 years ago [6] and that SAF still only comprises less than 0.1% of jet fuel use, the question arises as how it can ramp up to 100% use in the next 27 years. One option that has the potential to substantially reduce the need for SAF is to implement light-weight Solid Oxide Fuel Cells (SOFCs) that can efficiently utilize SAF or other sulfur-free hydrocarbon fuels. As opposed to lower temperature PEM (Proton Exchange Membrane) fuel cells that can use high-purity hydrogen, SOFC’s fuels are very flexible, ranging from low cost liquefied natural gas (LNG), renewable liquefied natural gas (RLNG), to SAF, to generate clean electrical power for use in aviation propulsion and auxiliary power units [7] [8]. Research progress is needed to enable SOFCs to achieve 3.0 kW/kg power density, making them viable for aviation [9]. The DOE’s Advanced Research Projects Agency – Energy (ARPA-E) has therefore initiated an aviation SOFC R&D program that is anticipated to dramatically reduce aircraft fuel use though the implementation of “Range Extenders for Electric Aviation with low Carbon and High efficiency” (REEACH) [1] for medium range commercial aircraft. This report summarizes the progress during phase 1 of the REEACH program.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Segmentation Model Distillation [Poster]

The process of training object detection (OD) or image segmentation model requires both a substantial amount of data and technical knowledge, which often creates challenges in applying these types of models to their full potential. In order to streamline the process of developing these models, we propose a new pipeline where a foundation model assists in the dataset generation. Then this resulting dataset is used to fine-tune a fast light-weight model to perform the custom segmentation or OD. This resulting model is also fit for real-time image segmentation, such as in a video stream.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quench process modeling & simulation in the heat-treatment of critical aerospace components

To manufacture light-weight, advanced metal alloy components for gas turbine engines, quench heat-treatment processes are typically used. By quenching the component from elevated temperatures, the alloy sometimes undergoes a solid-state phase transformation which produces special microstructures with the required, enhanced mechanical properties. However, the quenching can also lead to cracks forming in the component. Addressing the quench cracking problems adds a significant burden to the cost, schedule, and energy demand of manufacture. Currently, optimizing the quench process to mitigate or avoid the cracking is performed largely by trial-and-error, relying heavily on costly experimental (thermocouple)trials to understand the local thermal gradients which cause the cracks to form. In this first part (Phase 1) of the work, high-performance computing is employed to establish the ability of modern CFD (computational fluid dynamics) to alleviate or wholly replace the experimental quenching trials by virtual testing. A Baseline CFD model is defined and its accuracy established to be comparable to(and which usually exceeds) the accuracy of existing HTC (heat-transfer coefficient) based simulation methods of quenching. As a first-principles based approach, “calibration” of the Baseline CFD model is independent of the quench process itself, but instead relies on the accuracy of the underlying (modeled),generic two-phase fluid processes which cannot be currently resolved by CFD for large, industrial-scale cases. A novel, high-fidelity DNS capability has been developed and verified to examine and further improve upon the mean-field closure submodels on which the Baseline CFD approach is based.1

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Quench process modeling & simulation in the heat-treatment of critical aerospace components

To manufacture light-weight, advanced metal alloy components for gas turbine engines, quench heat-treatment processes are typically used. By quenching the component from elevated tempera-tures, the alloy sometimes undergoes a solid-state phase transformation which produces special microstructures with the required, enhanced mechanical properties. However, the quenching can also lead to cracks forming in the component. Addressing the quench cracking problems adds a significant burden to the cost, schedule, and energy demand of manufacture. Currently, optimizing the quench process to mitigate or avoid the cracking is performed largely by trial-and-error, relying heavily on costly experimental (thermocouple) trials to understand the local thermal gradients which cause the cracks to form. In this first part (Phase 1) of the work, high-performance computing is employed to establish the ability of modern CFD (computational fluid dynamics) to alleviate or wholly replace the experimental quenching trials by virtual testing. A baseline CFD model is defined and its accuracy established to be comparable to (and which usually exceeds) the accuracy of existing HTC (heat-transfer correlation) based simulation methods of quenching. As a first-principles based approach, “calibration” of the Baseline CFD model is independent of the quench process itself, but instead relies on the accuracy of the underlying (modeled), generic two-phase fluid processes which cannot be currently resolved by CFD for large, industrial-scale cases. A novel, high-fidelity DNS capability has been developed and verified to examine and further improve upon the mean-field closure submodels on which the Baseline CFD approach is based.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Variable Curvature Pultruded Vertical Axis Wind Blades

XFlow Energy is developing a floating offshore vertical-axis wind turbine (VAWT) enabling a 70% reduction in the levelized cost of energy compared to floating horizontal-axis wind turbines (HAWTs). While the wind industry has historically been successful at lowering the cost of terrestrial wind systems, there are no scalable, economically viable floating wind solutions on the market with the levelized cost of energy (LCOE) of current floating offshore solutions is $\$$200/MWh (Musial 2022). Low-cost blade production is one of the key technologies for realizing this target LCOE reduction. The proposed design uses a constant cross-section blade, enabling the use of pultrusion, a continuous, automated, mold-free production method. By employing blades with variable curvature, XFlow can minimize the bending stresses in the blades, allowing for light-weighting. Constant curvature pultrusion has been demonstrated on hollow sections. Variable curvature pultrusion has been demonstrated on solid sections. This project aims to develop a method of variable curvature pultrusion for hollow sections, as required for mass-optimal VAWT blades.

17 WIND ENERGY↗