Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Generation limits”

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.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design, optimization, and validation of a triply periodic minimal surface based heat exchanger for extreme temperature applications

Heat exchanger (HX) innovation offers potential for significant improvements in energy efficiency for a host of applications including but not limited to aviation and power generation cycles. Triply Periodic Minimal Surfaces (TPMS) have received significant attention in recent years due to their incredibly high surface area density, which makes them very attractive from a heat transfer point of view. Recent efforts have largely focused on thermal-hydraulic characterization of the many available TPMS and the testing of small-scale HX prototypes. However, practical implementation remains largely unexplored, partially due to the extreme computational cost associated with accurately simulating these complex structures. In this work, we present the design, simulation, and optimization of a TPMS-HX for high temperature (900 °C) and pressure (25 MPa) applications. Detailed analysis of HX sub-sections is conducted to define the smallest repeatable section which may be used to characterize the thermal-hydraulic performance of the entire HX, enabling rapid design and iteration with significantly reduced computational cost. Compared to preliminary results for a water-to-water experiment, calibrated heat transfer and pressure drop predictions were within ±5 % and ±10 %, respectively. Optimization results show a 10x increase in volumetric power density over the initial design, which is verified against a parametric exhaustive search of the HX design space. Furthermore, it was found that reducing the unit cell hydraulic diameter cell plays the largest role in increasing heat transfer, increasing the surface area density and enabling a more compact and efficient HX.

42 ENGINEERING↗
DOE OSTI2023

A reduced-order model of concentration polarization in reverse osmosis systems with feed spacers

Feed spacers in reverse osmosis systems generate complex fluid flows that limit computational fluid dynamics (CFD) simulations to small length and time scales. That limits our ability to simulate mineral scaling and other membrane fouling phenomena, which occur over longer length and time scales. Thus motivated, we develop a reduced model that replaces the CFD simulation of the velocity field with an analytical model that mimics spacers. This focuses the remaining numerical effort on simulating the advection–diffusion equation governing solute transport. We motivate and validate the model with CFD simulations and bench-scale experiments of spacer filaments in three different arrangements, including cases of unsteady vortex shedding. We show that the model produces a roughly 10,000-fold speedup compared to CFD, and accurately reproduces CFD predictions of not only the average and maximum concentrations, but also the local concentration distribution along the membrane. Here, we also demonstrate the model for simulating a feed channel with a length-to-height ratio of 200. The model provides a simple testbed for exploratory studies of multispecies transport, precipitation, and membrane fouling phenomena for which simulating spacers is often prohibitive.

Computational fluid dynamics↗
DOE OSTI2026

Evaluating the Transport Mechanism for Lignocellulosic Inhibitors in Zymomonas mobilis

The conversion of lignocellulosic biomass to biofuels and bioproducts is limited by small inhibitory molecules generated during the pretreatment process. The diverse compounds within the cell wall hydrolysate including aldehydes, carboxylic acids, phenolics, and alcohols inhibit microbial growth by disrupting microbial membranes. Although Zymomonas mobilis combines high ethanol productivity with hopanoid-rich membranes that confer solvent tolerance, hydrolysate compounds still inhibit microbial growth. One proposed mitigation strategy is to pump these molecules out through active transport processes, reducing direct toxicity. However, if passive permeation rates are high, active transport would create a futile cycle where the exported molecules diffuse back in, creating a net drag on fitness. To investigate this hypothesis, we measure the passive permeation for thirty-three lignocellulose derived compounds using atomistic molecular dynamics simulations with enhanced sampling. Permeability coefficients determined spanned more than eight orders of magnitude driven largely by the balance between hydrophobicity and polarity. Hydrophobic inhibitors such as aromatic acids, aldehydes, and short chain alcohols readily partitioned into the membrane and showed high permeability consistent with rapid passive influx and strong toxicity. Most polar molecules have lower but still appreciable permeation rates, with only the most polar sugars having low permeabilities. By integrating these predictions together with hydrolysate composition information, we find that most of these molecules are so permeable that futile cycles where passive permeation overwhelms efflux is highly likely. These findings provide a predictive framework for strain engineering, highlighting that, for highly permeable inhibitors, reducing extracellular inhibitor concentrations through hydrolysate detoxification, pretreatment optimization, or dilution may be necessary to mitigate futile cycling and improve microbial productivity in industrial biorefineries.

Zymomonas mobilis↗
DOE OSTI2021

Optical shock-enhanced self-photon acceleration

Photon accelerators can spectrally broaden laser pulses with high efficiency in moving electron density gradients driven in a rapidly ionizing plasma. When driven by a conventional laser pulse, the group velocity walk-off experienced by the accelerated photons and deterioration of the gradient from diffraction and plasma-refraction limit the extent of spectral broadening. In this work, we show that a laser pulse with a shaped space-time and transverse intensity profile overcomes these limitations by creating a guiding density pro le at a tunable velocity. Self-photon acceleration in this profile leads to dramatic spectral broadening and intensity steepening, forming an optical shock that further enhances the rate of spectral broadening. In this new regime, multi-octave spectra extending from 400nm to 60nm wavelengths, which support near-transform limited < 400 as pulses, are generated over < 100 μm of interaction length.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Surface Merging Technique to Design GA-Optimized Heat Sinks

High-power density inverters require efficient and small heat dissipation systems. For liquid cooling systems, an effective heat sink design is important to enable higher heat transfer and keep the pressure drop within reasonable limits. A heat sink geometry generated from an extruded, 1D fast Fourier transform can achieve more even temperature distribution and improved heat transfer than a conventional heat sink. Building on this concept, this paper proposes a new heat sink geometry creation algorithm. Instead of one plane profile being extruded, multiple plane profiles, each created from the fast Fourier transform method, are subsequently merged by smooth surfaces along the flow direction of the heat sink. Thus, a 3D heat sink geometry is created that enables 3D coolant flow and efficient heat transfer. The volume of this design was reduced by 50% compared with pin fin heat sinks. Compared with extruded 1D fast Fourier transform heat sinks, the proposed design showed an approximately 5% device temperature reduction and a 20% pressure drop reduction.

Barua, Himel↗
DOE OSTI2024

A Time-Domain Protection Approach for AC Transmission Systems With Grid-Forming Resources

Ac transmission protection must reliably detect, classify, and locate short-circuit faults from voltage and current measurements. At present, these functionalities, which have been classically engineered using phasors approaches, are being challenged by the dynamic behavior and fault-current limits of converter-based generation. This paper tackles these challenges by engineering a time-domain protection approach that leverages the classical Bergeron model in a new manner. Low- and high-impedance faults are detected and classified by ascertaining how well line voltage and current measurements match the Bergeron equations. Faults are located by posing a novel one-variable optimization problem, whereas voltage and current waveforms at the fault location are estimated by unveiling rigorous relationships. The proposed elements are secure against external faults, measurement errors, and variation of line parameters and sampling time. Furthermore, these advances are tested via electromagnetic transient simulations and are significant to satisfy IEEE and North American Electric Reliability Corporation requirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Photocatalytic C–H activation and the subtle role of chlorine radical complexation in reactivity

A complex role for chlorine radicals Radicals are atoms or molecules that are highly reactive because they have an unpaired electron. A common means of investigating whether they are involved in a particular reaction is to try to trap them with an acceptor compound. Yang et al. reinvestigated a photoinduced alkane oxidation reaction for which a trapping study had previously implicated alkoxy radicals. Their spectroscopic, kinetic, and isotopic labeling studies revealed that chlorine, rather than alkoxy, was the key radical intermediate; the prior trapping results had stemmed from its complexation with alcohols. Science , abd8408, this issue p. 847

Science & Technology - Other Topics↗
DOE OSTI2023

Targeted metagenomic assessment reflects critical colonization in battlefield injuries

Current diagnostics and clinical management strategies for combat wounds are based on decisions made by expert clinicians. However, even in the hands of experienced surgeons, wounds from combat injuries can exhibit failed healing and complications related to limitations in the rapid and comprehensive generation of diagnostic information. Previous studies have demonstrated the possible use of genomic sequencing approaches to detect microbial signatures involved in combat casualty care. While effective, whole metagenome sequencing is limited by the depth required to confidently detect all relevant signatures. To address this, we developed a targeted capture sequencing panel to detect microbial signatures relevant to wound healing. These targets include known microbial nosocomial pathogens, wound colonizers, and genes involved in virulence and antimicrobial resistance. A bioinformatics pipeline was built to identify genomic regions of interest and over 8,000 oligonucleotide probes were designed for capture. The panel was synthesized and validated using control reference genomes in human background and on wound-effluent samples from a cohort of combat-injured U.S. service members. Our panel was sensitive against wound-colonizing species, Acinetobacter baumannii and Pseudomonas aeruginosa, and was specific in detecting corresponding virulence and antimicrobial-resistance genes as well as other pathogenic species present in microflora mixtures. Random forest feature permutation confirmed the prevalence of Acinetobacter and Pseudomonas in critically colonized wounds and wounds that failed to heal, respectively. Our results demonstrate the capability of targeted sequencing tools and analysis platforms to profile and deliver information on pathogenic factors influencing wound progression, thereby guiding therapeutic intervention.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

CAFE AU LAIT: Compute-Aware Federated Augmented Low-Rank AI Training

Federated finetuning is crucial for unlocking the knowledge embedded in pretrained Large Language Models (LLMs) when data are geographically distributed across clients. Unlike finetuning with data from a single institution, federated finetuning allows collaboration across multiple institutions, enabling the utilization of diverse and decentralized datasets while preserving data privacy. Given the high computing costs of LLM training and the emphasis on energy efficiency in Federated Learning (FL), Low-Rank Adaptation (LoRA) has emerged as a widely adopted algorithm due to its significantly reduced number of trainable parameters. However, this assumes that all data silos have the necessary computing resources to compute local updates of LLMs. Nevertheless, in practice, the computing resources across clients are highly heterogeneous: while some may have access to hundreds of GPUs, others might have limited or no GPU access. Recently, federated finetuning using synthetic data has been proposed, allowing clients to participate in a collaborative training run without training LLMs locally. However, our experimental results reveal a performance gap between models trained using synthetic data and those trained using local updates. Motivated by the observed heterogeneity in computing resources and the performance gap, we propose a novel two-stage algorithm that leverages the storage and computing capabilities of a strong server. In the first stage, under the coordination of the strong server, clients with limited computing resources collaborate to generate synthetic data, which is transferred to and stored on the strong server. In the second stage, the strong server uses this synthetic data on behalf of the resource-constrained clients to perform federated LoRA finetuning alongside clients with sufficient computing resources. This approach ensures that all clients can participate in the finetuning process. Experimental results demonstrate that incorporating local updates from even a small fraction of clients improves performance compared to using synthetic data for all clients. Furthermore, we incorporate the Gaussian mechanism in both stages to guarantee client-level differential privacy.

Wang, Jiayi [ORNL]↗
DOE OSTI2021

Updated Estimate of Tritium Permeation from TPBAR Disposal Containers in ILV (U)

A tritium source term analysis was performed for TPBAR disposal in the E-Area Intermediate Level Vaults for the E-Area Low-Level Waste Facility Performance Assessment (PA). This analysis is based on an earlier source term analysis which treated the bulk oft he tritium residual as tightly bound by the TPBAR getter material, with only a small fraction existing as tritiated moisture in the lithium aluminate ceramic pellets. Together with atmospheric moisture trapped in the free volume, the tritiated water vapor is assumed to corrode steel surfaces inside the disposal container, covering them with a magnetite film while generating hydrogen. The carbon steel walls of the disposal container are permeable to hydrogen, providing a path way for tritium to escape containment. The rate of hydrogen generation is assumed to be limited by the rate of corrosion, which is assumed to be governed by parabolic reaction kinetics obtained from the literature. This relies on the further assumption that the water vapor consumed by the corrosion reaction is continually replaced by moisture from the lithium aluminate pellets until all of that moisture is gone. In addition to tritium permeation, the analysis also includes a slow leak through the disposal container walls at the maximum allowable leak rate, 1 x 1CH standard cm3/s. Results were obtained for four different combinations of internal and container wall temperatures, established in an earlier thermal analysis that considered two different vault loadings and two different TPBAR activity levels. Instantaneous release rates for these four cases are plotted in Figure ES-1 below

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Physics of the Aurora: Laboratory Measurements of Electron Acceleration by Inertial Alfven Waves (Final Technical Report)

The physics of the aurora is one of the foremost unsolved problems of space physics. The mechanisms responsible for accelerating electrons that precipitate onto the ionosphere are not fully understood. For more than three decades, particle interactions with Alfven waves have been proposed as a possible means for accelerating electrons and generating auroras. Due to the limitations of spacecraft conjunction studies and other multi-spacecraft approaches, it is unlikely that it will ever be possible, through spacecraft observations alone, to confirm definitively the proposed electron acceleration mechanism by making simultaneous measurements of both the accelerated electrons and the inertial Alfven wave responsible for the acceleration. Here, we show laboratory measurements of the resonant transfer of energy from Alfven waves to electrons under conditions relevant to the auroral zone. Experiments are performed by launching Alfven waves and simultaneously recording the electron velocity distribution. Numerical simulations and analytical theory support that the measured energy transfer process produces accelerated electrons capable of reaching auroral energies. The experiments, theory, and simulations demonstrate a clear causal relationship between Alfven waves and accelerated electrons that directly cause auroras.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

This report documents the benchmarks being developed and simulations performed using tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, utilizing MSRE experimental data. In FY23, three main work scopes were investigated under the NEAMS MSR work package at ANL. The first scope investigated the Griffin-SAM coupling model for simulating the pump startup transient experiment of MSRE. The analyses start with a simple model (single-channel, single-lattice), gradually adding more details (multi-channel, full-core) into the model. The results show that the reactivity loss curve is very sensitive to the axial boundary conditions and the radial core discretization. The simple model can predict a similar reactivity trend as that of the more sophisticated model, which is likely due to error cancellation. Accurately modeling the axial boundary condition may further improve the reactivity trend but would require significant efforts to generate the mesh of the MSRE inlet and upper plenum. The core channel radial discretization for the Griffin-SAM coupled model also depends on the flow distribution. Given the complex geometry in the inlet plenum, the flow distribution needed to be calculated from CFD analysis, which was performed using the NekRS code. This analysis employed a MSRE CAD model developed by Copenhagen Atomics. The CAD model was disassembled to keep the inlet plenum region only, which was subsequently cleaned and modified so that the mesh generated is under the memory limit. The results are merged to a few radial regions to show that the flow rate is highest in the central region. This would be useful for future improvement of the Griffin-SAM coupling model of the MSRE core. The last task investigated is tritium transport modeling using the standalone SAM code. This task aimed to initiate the effort to demonstrate and validate the tritium transport model implemented in SAM. The preliminary investigation employed an MSRE model consisting of the primary loop. Three tritium transport pathways were examined including the retention in the graphite, the permeation through the HX tube wall, and the removal from the off-gas system. The results compare well with the MSRE data, but improvements are still needed on the initial conditions (i.e., the present state may not have reached equilibrium), the boundary conditions, the off-gas system modeling, and a better numerical strategy to reach the equilibrium state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Marine renewable energy for Arctic observations

Arctic observations are becoming increasingly valuable as researchers investigate climate change and its associated concerns, such as decreasing sea ice and increasing ship traffic. Networks of sensors with frequent sampling capabilities are needed to run forecast models, improve navigation, and inform climate research. Sampling frequency and deployment duration are currently constrained by battery power limitations. In-situ power generation using marine renewable energy sources such as waves and currents can be used to circumvent this constraint. Wave and current resources vary spatially and temporally in the Arctic, with some locations and seasons being better suited for marine renewable energy power generation. Locations and seasons with small resources may still be able to use marine renewable energy because of the low power requirements of the instruments. In this study, we describe the wave and current resources in the Arctic, outline the electricity generation developments that are needed to utilize the resources, and suggest use cases. Wave and current energy converters developed to power observations in the Arctic could also be used to power observations at lower latitudes. Marine renewable energy has the potential to decrease dependence on batteries and improve data collection capabilities in the Arctic; however, this would require the development of new low power technologies that can operate in extreme Arctic environments.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning

Quantifying methane emissions is essential for meeting near-term climate goals and is typically carried out using methane concentrations measured downwind of the source. One major source of methane that is important to observe and promptly remediate is fugitive emissions from oil and gas production sites but installing methane sensors at the thousands of sites within a production basin is expensive. In recent years, relatively inexpensive metal oxide sensors have been used to measure methane concentrations at production sites. Current methods used to calibrate metal oxide sensors have been shown to have significant shortcomings, resulting in limited confidence in methane concentrations generated by these sensors. To address this, we investigate using machine learning (ML) to generate a model that converts metal oxide sensor output to methane mixing ratios. To generate test data, two metal oxide sensors, TGS2600 and TGS2611, were collocated with a trace methane analyzer downwind of controlled methane releases. Over the duration of the measurements, the trace gas analyzer’s average methane mixing ratio was 2.40 ppm with a maximum of 147.6 ppm. The average calculated methane mixing ratios for the TGS2600 and TGS2611 using the ML algorithm were 2.42 ppm and 2.40 ppm, with maximum values of 117.5 ppm and 106.3 ppm, respectively. A comparison of histograms generated using the analyzer and metal oxide sensors mixing ratios shows overlap coefficients of 0.95 and 0.94 for the TGS2600 and TGS2611, respectively. Overall, our results showed there was a good agreement between the ML-derived metal oxide sensors’ mixing ratios and those generated using the more accurate trace gas analyzer. This suggests that the response of lower-cost sensors calibrated using ML could be used to generate mixing ratios with precision and accuracy comparable to higher priced trace methane analyzers. This would improve confidence in low-cost sensors’ response, reduce the cost of sensor deployment, and allow for timely and accurate tracking of methane emissions.

03 NATURAL GAS↗
DOE OSTI2025

Lithium Growth on Alloying Substrates and Effect on Volumetric Expansion

The widespread implementation of next-generation Li metal anodes is limited, in part, due to the formation of dendritic and/or mossy electrodeposits during cycling. These morphologies can lead to battery failure due to the formation of short circuits and significant volumetric expansion at the anode. One strategy to control the electrodeposition of Li metal is to use lithiophilic materials at the anode. Here, we evaluate the impact of Ag and Au on the early stages of Li metal electrodeposition and cycling. The alloying substrates decrease the voltage for Li reduction and improve Li wetting/adhesion. We probe volumetric expansion directly through dilatometry measurements and find that the degree of volumetric expansion is less when lithium is cycled on an alloying substrate compared to a non-alloying substrate (Cu). Dilatometry experiments reveal that Au has the least amount of volumetric expansion and coin cell cycling experiments indicate that Ag yields more stable cycling compared to Au or Cu. The evaluation of in situ cross-sectional images of cycled coin cells shows that Ag has the lowest volumetric expansion in a coin cell format.

alloys↗
DOE OSTI2024

Redesigning Photoelectrodes So They Can Work in the Light and Dark

Unassisted photoelectrochemical (PEC) reactions, such as H2 generation and CO2 reduction, are limited by the durability of the immersed photoelectrode. Small band gap semiconductors, like Si, are efficient at utilizing a large portion of the solar spectrum but are not stable in aqueous environments without protection. While great strides have been made to improve stability under constant illumination, dark stability remains relatively unexamined and presents great challenges for durable PEC systems. Cathodic protection is an established electrochemical method for preventing metal electrode degradation in harsh conditions. Similar protection strategies cannot be applied to traditional two-terminal (2T) semiconductor photoelectrodes because of their inability to pass reverse bias current in the dark. New, three-terminal (3T) photovoltaic (PV) architectures introduce additional degrees of freedom in traditional 2T PEC operations by adding an extra electrical contact for an alternative low resistance path to protect the photoelectrode and drive electrochemical reactions, even in the dark. Here, we investigate bare 3T Si PV devices operating as photocathodes in aqueous methyl viologen electrolyte. The 3T architecture provides additional capabilities to PEC systems such as cathodic protection, the ability to drive reactions with or without illumination, and in situ switching between different operational modes. We show that 3T-based Si photocathodes maintain PEC activity after several hours of light/dark cycling. This work helps advance PEC use in real-world conditions where variable illumination must be considered.

cathodic protection↗
DOE OSTI2025

Advanced Manufactured Strain Sensors for Extreme Environments

Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties). To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Advanced Manufactured Strain Sensors for Extreme Environments

Experimentation at irradiation test facilities are essential for reducing the innovation time of developmental fuels, fuel cladding, and structural materials employed in next-generation nuclear reactors. However, due to the harsh conditions generated in such reactors and limited instrumentation space, the evaluation of a material’s mechanical properties is often limited to characterization after the materials have been removed from reactor conditions, or post-irradiation examination. These experiments are costly, time-consuming, and fail to capture the critical time-evolving phenomena that occur during the irradiation experiments. Advanced manufactured digital image correlation patterns and strain sensor devices serve as two promising technologies that can be deployed in the confined and challenging orientations of these irradiation experiments while also providing key insight on salient materials phenomena (i.e., mechanical properties).To guide the development of the printed strain sensors prior to their deployment in critical experiments, the adhesion strength between the substrate and printed film interface is measured via tensile testing and a non-contact laser-induced spallation technique. The establishment of these process control steps helped guide the successful fabrication and testing of direct-write strain sensing devices discussed in this work. The fabrication process controls are necessary for enabling the sustained operation of these strain sensing device through experimentation and minimize the potential for premature failure.

36 - MATERIALS SCIENCE↗