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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 325 records · Page 18

Computational micromechanics model based failure criteria for chopped carbon fiber sheet molding compound composites

Chopped carbon fiber sheet molding compound has a great potential in lightweight automotive, marine, and aerospace applications. One of the most challenging tasks is to predict the failure strength of the material due to its anisotropy and heterogeneity, as well as complex stress states in real-world working conditions. In this work, a novel constitutive model of carbon fiber chip is proposed to capture the pre- and post-failure behaviors under different loading modes. On this basis, we propose a new computational micromechanics model, which is calibrated and validated by uniaxial tensile, compressive, and in-plane shear experiments. Furthermore, a set of microstructures representative volume element (RVE) models under complex loading conditions are reconstructed to understand the relationship between the microstructure characteristics and the failure envelopes. Finally, several modified versions of classical failure criteria are proposed for anisotropic materials with consideration of the fiber orientation tensor. The modified Tsai-Wu failure criterion, which shows the best accuracy among all failure criteria, is highlighted in the comparative study.

36 MATERIALS SCIENCE↗

Innovative large overbraided carbon fiber composite beams in historical Friendship Bell Pavilion

The International Friendship Bell Pavilion located in the City of Oak Ridge, Tennessee symbolizes the spirit of the peace and friendship shared by the city of Oak Ridge and city of Naka, Japan. The Bell Pavilion features an 8000-pound bronze cast bell along with futuristic materials and advanced manufacturing technologies. The team has developed innovative overbraided carbon fiber arched beams in conjunction with the bronze bell. Carbon fiber was utilized in these beams because of its lightweight, strong, stiff, and durable characteristics. A sandwich design used a high-performance foam core, overbraided with triaxial carbon fibers. This is the world’s largest overbraided composite structure for parks and recreation. For the first time in such an application, 17 free floating, 33-foot (10 m) long arched carbon fiber composite beams cantilever from a central concrete-steel superstructure over the bronze bell. The arc radius of the bottom of each beam is uniquely different giving an appearance of an open dome when standing underneath the structure.

Parks and Recreation↗

Performance assessment of 3D printed multi-material energy absorber for automotive bumper: pedestrian lower extremity protection

Designing an energy absorber for automotive bumpers involves balancing low-speed and high-speed impacts to ensure safety, reduce repair costs, and meet regulatory standards. Here, this study explores a novel design using multi-material 3D printing and structural optimization to fabricate a lightweight and cost-efficient energy absorber. The design effectively dissipates energy in low-speed collisions and minimizes force transmission in high-speed pedestrain impacts, helping to meet both safety and performance requirements. The energy absorber design combines 20% carbon fiber-reinforced acrylonitrile butadiene styrene (CF-ABS) and thermoplastic polyurethane (TPU) for optimal stiffness and flexibility. It uses 3D-printed lattice structures optimized through finite element simulations to help meet both low-speed and high-speed impact requirements. Full-scale energy absorbers were 3D-printed using optimized CF-ABS/TPU blends and tested under high-speed impact using the Flexible Pedestrian Legform Impactor (Flex-PLI). For fair comparison, a baseline bumper with a traditional triangular lattice structure, also 3D-printed from the same CF-ABS/TPU materials, was similarly tested. Interestingly, both the optimized and baseline 3D-printed energy absorbers showed nearly identical performance, successfully meeting injury limits. Their performances were also benchmarked against an injection-molded energy absorber. While both 3D-printed and injection-molded designs met injury limits, the 3D-printed absorber exhibited a higher tibia bending moment, indicating an opportunity for further optimization. A Techno-Economic Analysis compared the costs of producing energy absorbers using traditional manufacturing and 3D printing. The analysis highlighted that 3D printing offers cost benefits for low to medium production volumes, with the total cost per energy absorber at ∼ $\$$74, compared to traditional methods that become economical beyond 2000 units.

Additive manufacturing↗

Novel application of the modal strain energy technique for state-of-the-art damping predictions

Structural damping, which measures the energy dissipation of a vibrating structure, is a key modeling input for lightweight structures but is notoriously hard to predict. This work utilizes vibration-based measurements of centimeter-scale coupons and the modal strain energy approach to predict structural damping of a lightly damped structure. The approach was originally validated with panels shorter than a meter in length. This work extends the validation to a 2.75 m beam made of unidirectional and biaxial glass fiber laminates bonded by adhesive. The comparison between three-dimensional finite element model predictions and full-scale experimental measurements of damping show an average error of 5.2% for the first five modes. Additionally, the modal strain energy approach is newly applied with a one-dimensional geometrically exact beam theory model and a two-dimensional sectional analysis solver. This beam approach accurately predicts the damping behavior of the first bending modes but loses accuracy for higher order modes that are dominated by three-dimensional effects. This novel approach provides faster simulations while allowing arbitrary beam cross sections. The paper also investigates traditional and high-force dynamic mechanical analysis to measure structural damping of coupons. Both alternatives show significant errors in attempted validation against the theoretical thermoelastic damping of aluminum coupons.

17 WIND ENERGY↗

Python Group Additivity (pGrAdd) software for estimating species thermochemical properties

ncreasingly complex chemistry models require thermochemical data for many species often estimated from costly first-principles DFT computations. Here we introduce the Python Group Additivity software (pGrAdd) that implements comprehensive group additivity in a simple, modular, lightweight Python package that is extensible and easy to implement. It includes 6 group additivity databases for gas species and Pt(111) adsorbates allowing users to immediately compute thermochemical properties for a wide range of molecules and build new databases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

express: Extensible, high-level workflows for swifter ab initio materials modeling

In this work, we introduce an open-source Julia project, express, an extensible, lightweight, high-throughput, high-level workflow framework that aims to automate ab initio calculations for the materials science community. express is shipped with well-tested workflow templates, including structure optimization, equation of state (EOS) fitting, phonon spectrum (lattice dynamics) calculation, and thermodynamic property calculation in the framework of the quasi-harmonic approximation (QHA). It is designed to be highly modularized so that its components can be reused across various occasions, and customized workflows can be built on top of that. Users can also track the status of workflows in real-time, and rerun failed jobs thanks to the data lineage feature express provides. Finally, two working examples, i.e., all workflows applied to lime and akimotoite, are also presented in the code and this paper.

36 MATERIALS SCIENCE↗

Code modernization strategies for short-range non-bonded molecular dynamics simulations

Modern HPC systems are increasingly relying on greater core counts and wider vector registers. Thus, applications need to be adapted to fully utilize these hardware capabilities. One class of applications that can benefit from this increase in parallelism are molecular dynamics simulations. In this paper, we describe our efforts at modernizing the ESPResSo++ simulation package for molecular dynamics by restructuring its particle data layout for efficient memory accesses and applying vectorization techniques to benefit the calculation of short-range non-bonded forces, which results in an overall three times speedup and serves as a baseline for further optimizations. We also implement fine-grained parallelism for multi-core CPUs through HPX, a C++ runtime system which uses lightweight threads and an asynchronous many-task approach to maximize concurrency. Our goal is to evaluate the performance of an HPX-based approach compared to the bulk-synchronous MPI-based implementation. This requires the introduction of an additional layer to the domain decomposition scheme that defines the task granularity. On spatially inhomogeneous systems, which impose a corresponding load-imbalance in traditional MPI-based approaches, we demonstrate that by choosing an optimal task size, the efficient work-stealing mechanisms of HPX can overcome the overhead of communication resulting in an overall 1.4 times speedup compared to the baseline MPI version.

97 MATHEMATICS AND COMPUTING↗

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗

Dry-pressed lithium nickel cobalt manganese oxide (NCM) cathodes enabled by holey graphene host

There is an increasing demand for electric vehicle batteries with higher energy densities that can be manufactured with low cost utilizing environmentally friendly processes. Lithium nickel cobalt manganese oxides (NCM), such as LiNi(0.5)Co(0.2)Mr(0.3)O(2) (NCM523), are commonly used in commercial lithium ion batteries for electric vehicle applications. These cathodes are typically fabricated using environmentally hazardous, energy intensive, and time-consuming solvent-based slurry casting processes. Polymeric binders, also required for cathode preparation, add weight and can undergo parasitic reactions during battery cycling. Here we report a facile, solvent-free, binder-free, and rapid cold-press electrode fabrication process to prepare high mass loading NCM cathodes within minutes. This process is enabled by the use of holey graphene, a unique lightweight, compressible carbon nanomaterial that serves as both a binder and an electrically conductive matrix. NCM cathodes fabricated by this method are stable and exhibit good active material utilization. A significant advantage for the dry-press process is that the electrode mass loadings can be readily increased simply by adding more composite powder to the compression molding die, resulting in improved areal capacities that are attractive for applications requiring high energy per unit footprint. (C) 2020 Elsevier Ltd. All rights reserved.

25 ENERGY STORAGE↗

Effect of strain rate on the deformation of hollow CoS nanoboxes and doubly porous self-assembled films

Nanomaterials with multiscale porosity are attractive as lightweight structural materials because unique deformation mechanisms can be programmed at different length scales. Here, we explore this concept by investigating the mechanics of hollow nanoboxes, as well as films self-assembled from nanoboxes. Hollow CoS nanoboxes with lengths of 900 nm and <30 nm wall thickness are synthesized using colloidal methods. Individual nanoboxes are compressed inside a scanning electron microscope at strain rates of 0.001 s –1 , 0.01 s –1 , and 0.1 s –1 . Nanoboxes are found to have a first peak stress of 15 MPa and loading modulus of ~240 MPa regardless of strain rate. The nanoboxes deform through ductile, plastic bending of side walls at 0.001 s –1 strain rate, while brittle fracture occurs at the higher strain rates. Self-assembly of these nanoboxes results in films with relative density of <0.1. Nanoindentation shows strain rate independent behavior with average modulus and hardness of ~15 MPa and ~230 kPa, respectively. Furthermore, the mechanical behavior of the film is compared to that of the nanobox building blocks, cellular foams and granular materials.

36 MATERIALS SCIENCE↗

Thermoelectric air conditioning undergarment for personal thermal management and HVAC energy saving

Personal thermal management systems (PTMS) are highly desirable for improving individual thermal comfort and reducing indoor HVAC energy consumption. Although there have been many attempts in developing PTMS, existing PTMS are generally bulky, heavy or immobile. Besides, previous analysis on additional personal cooling and heating power required for maintaining thermal comfort in changing environments did not consider the individual difference in metabolism and the variability of comfort skin temperature with environmental conditions. In this paper, we report on the development of a novel lightweight (<1 kg) thermoelectric air conditioning undergarment system with a preferred design of branching tubing network (branching angle of 60° and diameter ratio of 0.782) for air distribution. Through thermal manikin and human subject tests, we demonstrated that the novel system is capable of providing a maximum of 15.5 W of personal cooling and 18.1 W personal heating with a coefficient of performance (COP) greater than 0.4, which is sufficient to the expansion of the indoor set-points by at least 2.2 °C (4 °F) on both sides without compromising thermal comfort and the potential saving of about 15% HVAC energy. Furthermore, our study improved the understanding of the required additional personal cooling and heating power for changing environmental conditions, which are essential guidelines for the further development of PTMS.

42 ENGINEERING↗

Evaluating cascaded and tunable phase change materials for enhanced thermal energy storage utilization and effectiveness in building envelopes

The incorporation of phase change materials (PCMs) in envelope is considered an effective thermal energy storage (TES) method for energy savings and load flexibility in buildings. However, an important limitation of PCMs is their fixed and narrow transition temperature range. Because the interior temperature setpoints are typically different in summer versus winter, and the exterior temperature varies substantially above and below the setpoints during the year, PCMs with a fixed transition temperature are utilized only during part of the year. In this paper, we provide an extensive numerical analysis of the performance of a lightweight building envelope containing three different types of PCMs: traditional single-layer PCM with a fixed transition temperature, novel cascaded two-layer PCM with different transition temperatures, and a "futuristic" tunable PCM whose transition temperature can be varied in-situ using external excitation. We compare their performances by evaluating the relationship between the PCM utilization and parameters such as latent heat, transition temperature range, PCM thickness, and PCM location. While traditional PCMs are mostly active during one season, properly designed cascaded and tunable PCMs can be active much longer, thereby allowing load shift and energy savings in both heating and cooling seasons. Under the operating conditions considered in this study, tunable PCMs performed best, providing the highest utilization (about 2 times the traditional PCMs) and enhanced effectiveness (up to 99% peak load reduction in cooling season and 34% peak load reduction in heating season) with the same amount of material as the traditional PCMs; however, cascaded PCMs can be a good alternative while tunable PCMs are unavailable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Keras2c: A library for converting Keras neural networks to real-time compatible C

With the growth of machine learning models and neural networks in measurement and control systems comes the need to deploy these models in a way that is compatible with existing systems. Existing options for deploying neural networks either introduce very high latency, require expensive and time consuming work to integrate into existing code bases, or only support a very limited subset of model types. We have therefore developed a new method called Keras2c, which is a simple library for converting Keras/TensorFlow neural network models into real-time compatible C code. It supports a wide range of Keras layers and model types including multidimensional convolutions, recurrent layers, multi-input/output models, and shared layers. Keras2c re-implements the core components of Keras/TensorFlow required for predictive forward passes through neural networks in pure C, relying only on standard library functions considered safe for real-time use. The core functionality consists of ~ 1500 lines of code, making it lightweight and easy to integrate into existing codebases. Keras2c has been successfully tested in experiments and is currently in use on the plasma control system at the DIII-D National Fusion Facility at General Atomics in San Diego.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Advanced strategies for the development of porous carbon as a Li host/current collector for lithium metal batteries

Lithium metal is considered a promising anode material for high-energy-density rechargeable batteries because of its high specific theoretical capacity (3860 mAh g -1 , low mass density (0.534 g cm -3 ), and low electrochemical redox potential (-3.04 V vs. the standard hydrogen electrode). However, the high reactivity of Li with the electrolyte leads to the formation of an unstable solid electrolyte interphase (SEI) and continuous side reactions. Also, the non-uniform lithium-ion flux and infinite volume expansion of Li metal cause the growth of Li dendrites. These pose significant safety challenges and cause rapid capacity fading of the lithium metal batteries (LiMBs). To resolve these issues, a low-cost, easily processed, lightweight, high-performance carbon-based porous matrix is considered promising to host Li metal deposition. The three-dimensional (3D) porous nano/microstructured carbon provides sufficient space for Li accommodation during Li plating, buffers the volume changes during Li plating/stripping, and lowers the effective current density contributing to dendrite-free Li deposition. Besides, the outstanding electrochemical and mechanical stability, flexibility and the high electronic conductivity enable the nano/microstructured carbon to serve as both Li host and current collector. The development of 3D carbon/Li composite by mechanical roll-press techniques not only eliminates the complex and risky procedure of making carbon/Li composite based on Li plating or molten Li infusion but also stabilizes the capacity at higher Li plating/stripping rates. Recently, there is an advancement in the lithiophilic decorations of 3D structure to introduce sufficient nucleation sites and the development of artificial SEI on top of the 3D matrix to suppress Li dendrite formation. Such 3D structural modifications create a uniform electric field, lower the Li nucleation overpotential, provide strong mechanical and chemical stability, and stabilize the interface thereby inhibiting the degradation of lithium and the electrolyte. Here we summarize the research progress on porous carbon/Li composites in terms of materials type, structure, fabrication technique, their electrochemical battery performance, and identify the critical challenges that need to be addressed for high-energy-density practical LiMBs.

25 ENERGY STORAGE↗

Advanced blade-shaped thermal energy storage device: Development and application

Thermal energy storage (TES) using phase change materials (PCMs) is a promising approach for capturing and reusing excess thermal energy, yet widespread adoption is limited by low thermal conductivity, bulky configurations, and inadequate scalability. Here, this study presents a modular, blade-shaped TES prototype designed to address these challenges. The device integrates a lightweight aluminum shell, an embedded serpentine coil for active or passive heat exchange, and a cost-effective corrugated metal mesh for enhanced PCM thermal conductivity. With thickness-to-length and thickness-to-width ratios of 0.03 and 0.08, respectively, the blade-shaped TES achieves a compact, modular form factor suitable for space-constrained applications. Experimental testing demonstrated the efficient charge and discharge behavior of blade-shaped TES, capturing PCM superheating, phase-change transitions, and subcooling dynamics, with charging and discharging efficiencies of 94.9% and 94.6%, respectively. Also, the system can potentially achieve higher energy density than that of conventional TES designs. When integrated into a household refrigerator during the study, three blade-shaped TES modules successfully shifted 100% of peak-time compressor operation to off-peak hours, reducing energy consumption while maintaining more stable compartment temperatures. The blade-shaped TES's thin geometry, modularity, and enhanced thermal performance support scalable deployment across residential, commercial, and industrial applications, providing a versatile, cost-effective solution for high-efficiency, demand-flexible thermal energy management.

Blade-shaped↗

Synergistic enhancement of nanocellulose foam with dual in situ mineralization and crosslinking reaction

Cellulose nanocrystals (CNCs) foams have recently gained research interests because they are renewable, abundant, biodegradable and exhibit high surface area. However, the application of CNCs-based foams is still challenging, which is attributed to its lack of effective entanglements between the CNCs particles, thus lowering foam properties. In this study, a synergistic enhancement strategy was proposed, based on the in situ mineralization with hydroxyapatite (HAP) layer onto the CNCs surface, followed by a chemical crosslinking reaction. The physical and chemical structures of the composites were analyzed with SEM, STEM, XRD, FTIR, and TGA. By controlling the amount of coated HAP and the crosslinker, it is possible to manufacture a series of CNCs-based foams that are lightweight (50–75 mg/cm 3 ), highly porous (~90%) with high water absorption (>1300%) and outstanding mechanical strength properties (as high as 1.37 MPa). Moreover, our study further indicated that these CNCs/HAP materials could increase the proliferation of rat osteoblast cells. The method developed in this study presents a novel approach to design improved networked CNCs foam, which has the potential to be used in thermal-retardant material, wastewater treatment, tissue engineering, and personal care applications.

59 BASIC BIOLOGICAL SCIENCES↗

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation↗