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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

“Hybridizing heat-integrated 3D printed modules with mass manufacturable, low pressure drop fiber sorbents” (Final Report)

The overall objective of this proposal was to research, develop, and evaluate a modular direct air capture (DAC) system that is simple and scalable. This system was based on the adsorption of CO 2 into commercial polyamines supported by porous fiber sorbents, which can be produced at kilometer per hour scales using our pre-pilot spinning line. We have housed these fiber materials in novel 3D printed modular housing systems that provide easy-to-manufacture and localized heat integration and flow control. This hybridization of fiber sorbent technology with modular housing provided several advantages that led to lower air pressure drops, higher sorbent productivity, as well as ease of manufacturing and assembly unrivaled by existing and emerging heat integrated contactor designs. The modular housing was fabricated with the following features, at a minimum: (i) a tapered air intake to reduce pressure drop related to entrance effects, (ii) a structured network of heat transfer channels to enable localized cooling and heating during adsorption and desorption, respectively, and (iii) low pressure drop supports for the fiber sorbents. This hybrid manufacturing approach provides a facile method for taking fiber sorbents from lab scale to pilot scale as it dramatically simplifies the fabrication of heat integrated contactor structures.

42 ENGINEERING↗
DOE OSTI2024

Drop Tower Statement of Work

This document details the needs and requirements for a propulsion-assisted drop tower system (further referenced simply as Drop Tower) to perform hardware testing at Lawrence Livermore National Laboratory (LLNL). LLNL is managed and operated by Lawrence Livermore National Security, LLC (LLNS) for the Department of Energy (DOE). LLNL requires a robust testing platform that will allow for the characterization of interactions between objects of interest. The initial siting of the equipment will be located in an existing test facility (B191). When another test facility becomes online, the objective will be to move the test capability to the new facility as a final location (B132N). The Drop Tower will be a cornerstone capability for testing and model validation for LLNL interested programs.

42 ENGINEERING↗
DOE OSTI2024

Optimization of Triply Periodic Minimal Surface Heat Exchanger to Achieve Compactness, High Efficiency, and Low-Pressure Drop

With advancements in additive manufacturing (AM) techniques, high-quality triply periodic minimal surface (TPMS) structures can now be produced. TPMS walled heat exchangers (HX) hold significant potential for industrial applications and are receiving increasing attention. This paper explores the impact of various TPMS design variables on flow and thermal performance to optimize TPMS heat exchangers for compactness, high efficiency, and low pressure drop. The design variables examined include the type of TPMS lattice, unit cell size, wall thickness, aspect ratio, TPMS orientation, and equivalent thickness. The study reveals that the flow and heat transfer performance of TPMS structures are significantly affected by these design variables. For the Gyroid, Diamond, and SplitP lattices, performance is nearly identical when the surface-to-volume ratio is kept constant. The average velocity of the fluid in the TPMS HX should be 0.3 m/s. The corresponding Re is between 300~800. Thin wall thickness, small equivalent thickness, and flat lattice configurations can significantly reduce pressure drop while maintaining the overall heat transfer coefficient. Additionally, the angle between the flow direction and TPMS orientation can increase pressure drop. Three aluminum heat exchangers were successfully printed using an AM machine, and testing results are comparable with theoretical prediction.

42 ENGINEERING↗
DOE OSTI2026

Flow Boiling Pressure Drop Characteristics of Next-generation Refrigerants in a Micro‑fin Copper Tube

This paper presents experimental frictional pressure-drop data for flow boiling of R-410A, R-134a, and next-generation alternatives R-454C, R-455A, R-1234yf, and R-1234ze(E) in a horizontal micro-fin copper tube. Tests were conducted over a range of mass fluxes and evaporation temperatures to characterize refrigerant-dependent two-phase pressure-drop behavior. The results show that frictional pressure gradient increased with mass flux and vapor quality and generally increased as evaporation temperature decreased, with liquid viscosity strongly affecting the observed trends. Among the evaluated correlations, the Goto et al. (2001) model gave the best overall agreement with the measurements before optimization. Further optimization of the Kuo and Wang (1996) and Goto et al. (2001) models reduced the overall mean absolute deviation to below 15%, with the optimized Goto (2001) model providing the most consistent predictions across all six refrigerants. The results support improved pressure-drop prediction and evaporator design for next-generation refrigerants in micro-fin tubes.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2022

In Tube Condensation Heat Transfer and Pressure Drop for R454B and R32—Potential Replacements for R410A

The heating, ventilation and air conditioning (HVAC) industry in the United States seeks near-term alternative refrigerants to replace R-410A in unitary equipment. Two potential replacement refrigerants are R-454B and R-32. It is of interest to investigate the capability and accuracy of existing heat exchanger design methods when applied to these replacement refrigerants. To that end, this work presents empirical condensation quasi-local heat transfer coefficient and pressure drop data for R-454B and R-32. These data were obtained in a $\frac{3}{8}$ in. (9.52 mm) outside diameter (OD) smooth copper tube with a wall thickness of 0.032 in. (0.81 mm). The experimental variables and their ranges included refrigerant absolute pressure ( 1960 ≤ P a b s ≤ 3196 kPa), condensation temperature ( 35 ≤ T c o n d ≤ 50 °C), mass flux ( 100 ≤ G ≤ 200 kg m -2 s -1 ), vapor quality ( 0 ≤ x ≤ 1 ), and heat flux ( 32.9 ≤ q ″ ≤ 62.97 kW m -2 ). It was found that the heat transfer correlation developed by Cavallini et al. Cavallini et al. (2006) predicted the experimental condensation heat transfer data, for both R-454B and R-32, with the greatest accuracy. Using the Cavallini et al. correlation, it was found that the mean absolute percentage error (MAPE) was 10.5% and 15.1% for R-454B and R-32, respectively. Additionally, the pressure drop correlation developed by Friedel Friedel (1979) predicted the experimentally determined pressure gradient with a MAPE of 7.7% and 5.5% for R-454B and R-32, respectively. These results will assist the practicing thermal engineer to choose the most appropriate design correlation for these near-term replacement refrigerants.

42 ENGINEERING↗
DOE OSTI2022

Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar Data

Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter D m from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. Here, this estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Prospects for strong coupling measurement at hadron colliders using soft-drop jet mass

We compute the soft-drop jet-mass distribution from pp collisions to NNLL accuracy while including nonperturbative corrections through a field-theory based formalism. Using these calculations, we assess the theoretical uncertainties on an αs precision measurement due to higher order perturbative effects, nonperturbative corrections, and PDF uncertainty. We identify which soft-drop parameters are well-suited for measuring αs, and find that higher-logarithmic resummation has a qualitatively important effect on the shape of the jet-mass distribution. We find that quark jets and gluon jets have similar sensitivity to αs, and emphasize that experimentally distinguishing quark and gluon jets is not required for an αs measurement. We conclude that measuring αs to the 10% level is feasible now, and with improvements in theory a 5% level measurement is possible. Getting down to the 1% level to be competitive with other state-of-the-art measurements will be challenging.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Simulation of two nanoparticle melting to understand the conductivity drop of 3D-printed silver nanowires

The future flexible sensor technology will require low-temperature, fast processing 3D printing techniques that will rely heavily on the quality of nanoparticle (NP) Ink. Electrical conductivity has been found to decrease in majority of the 3D printed electronic wires. Herein we report a fundamental understanding in drop of electrical conductivity in processed silver (Ag) line wire, generally found in Ag-nanoparticle Ink, using large-scale atomistic molecular dynamics (MD) simulations of sintering of five different sizes of Ag NPs. To preserve the high conductivity of pure silver wires, the integrity of the pristine face-centered cubic (FCC) crystalline structure must be retained in the processed line wires. Simulations show that the pristine Ag FCC structures of the nanoparticles are not recovered after melting and resolidification, instead, the resolidified material is paracrystaline. The breakdown of pristine FCC structures might be the cause of the drop in conductivity of processed Ag wires. Simulation results suggest that the intermediate size nanoparticles retain highest percentage of the pristine silver face-centered cubic (FCC) structure after pulse treatments. Our results show that the most promising Ag-Ink should contain smaller to medium size silver NPs that can retain FCC structure after 3D printing of the Ag-Ink.

42 ENGINEERING↗
DOE OSTI2025

Drop-in sustainable aviation fuels enabled by feedstock-agnostic lignin deoxygenation

Current sustainable aviation fuels (SAFs) require blending with petroleum-derived fuels due to incomplete hydrocarbon distributions, most notably a lack of aromatics. Lignin, the most abundant renewable source of aromatics, is a promising feedstock for addressing this limitation. Here, we demonstrate a sequential reductive catalytic fractionation and continuous hydrodeoxygenation process that converts multiple woody feedstocks into aromatic hydrocarbons at up to 93% of the theoretical carbon yield. Blending these products with commercial SAFs produces drop-in compatible fuels with elastomer swell performances equivalent to conventional aviation fuels. The process is adaptable across multiple biomass sources, yielding aromatic hydrocarbons with consistent enthalpic efficiencies and fuel properties. These findings establish a scalable route to 100% drop-in SAFs, leveraging lignin-derived aromatics within the existing biofuels infrastructure.

09 BIOMASS FUELS↗
DOE OSTI2025

Evaporation of a Reactive Nanofluid Sessile Drop: Capturing Rapid Emergence of Surface Crystals with In Situ Synchrotron X-ray Diffraction

Mechanisms for surface pattern formation from evaporation of a reactive nanofluid sessile drop are not well understood. In contrast to the coffee-ring effect from inert particles, rapid chemical and morphological transformation of reactive nanoparticles upon rapid evaporative drying are challenging to probe experimentally. Here, using grazing-incidence X-ray surface scattering, the nanostructure of nascent surface patterns has been probed as a ZnO nanofluid sessile drop rapidly dries. The high temporal resolution enabled by the high flux of synchrotron X-rays allows the observation of the emergence of Zn(OH) 2 surface crystals from the onset of evaporation and their rapid evolution into the final residual surface pattern, via transient layered complexes evident from the temporary appearance of X-ray diffraction peaks preceding Zn(OH) 2 formation. The results offer mechanistic insights of morphogenesis of surface patterns from evaporation-induced self-assembly and self-organization of reactive nanofluids, previously untenable using other experimental methods.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Impacts of Bulk Microphysics Scheme Structural Choices on Simulations of Rain Initiation Through Drop Coalescence

This study examines how different structural choices in bulk microphysics schemes impact the simulation of warm rain initiation. A single liquid category (SLC) approach prognosing up to four moments of a single drop size distribution (DSD) is compared to the traditional two-category, two-moment approach with separate DSDs for cloud and rain (four total prognostic variables). Different methods for calculating tendencies of the prognostic variables from drop collision-coalescence are also tested: a discretized numerical-integration approach, machine learning via neural networks, lookup tables, and traditional power law fits. Relative to simulations using a bin microphysics model, SLC gives smaller error overall than the two-category approach when numerical integration is used to calculate the collision-coalescence tendencies for both. Replacing the numerical integration with a pre-computed lookup table reduces computational cost with little loss of accuracy. However, using fitted power laws with SLC to represent the collision-coalescence tendencies substantially reduces accuracy and leads to an order of magnitude increase in error. It is also demonstrated that with SLC, reasonably accurate solutions are obtained using only three prognostic moments, while a two-moment SLC scheme leads to substantial error. Overall, both the choice of prognostic moments (e.g., SLC vs. two-category) and method to calculate the collision-coalescence tendencies are important to consider for minimizing errors in bulk schemes. SLC with a sufficiently detailed calculation of the collision-coalescence tendencies provides accurate solutions for a reasonable computational cost, providing a viable alternative to the traditional two-category, two-moment approach for bulk microphysics.

320 (cloud physics and chemistry)↗
DOE OSTI2022

Hanging drop sample preparation improves sensitivity of spatial proteomics

Spatial proteomics holds great promise for revealing tissue heterogeneity in both physiological and pathological conditions. However, one significant limitation of most spatial proteomics workflows is the requirement of large sample amounts that blurs cell-type-specific or microstructure-specific information. In this study, we developed an improved sample preparation approach for spatial proteomics and integrated it with our previously-established laser capture microdissection (LCM) and microfluidics sample processing platform. Specifically, we developed a hanging drop (HD) method to improve the sample recovery by positioning a nanowell chip upside-down during protein extraction and tryptic digestion steps. Compared with the commonly-used sitting-drop method, the HD method keeps the tissue pixel away from the container surface, and thus improves the accessibility of the extraction/digestion buffer to the tissue sample. The HD method can increase the MS signal by 7 fold, leading to a 66% increase in the number of identified proteins. An average of 721, 1489, and 2521 proteins can be quantitatively profiled from laser-dissected 10 μm-thick mouse liver tissue pixels with areas of 0.0025, 0.01, and 0.04 mm 2 , respectively. The improved system was further validated in the study of cell-type-specific proteomes of mouse uterine tissues.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Pressure Drop Correlation Improvement for the Near-Wall Region of Pebble-Bed Reactors

Packed beds play an important role in several engineering fields, with their applications in nuclear energy being driven by the development of next-generation reactors utilizing pebble fuel. The random nature of a packed pebble bed creates a flow field that is complex and difficult to predict. Porous media models are an attractive option for modeling pebble-bed reactors (PBRs), as they provide intermediate fidelity results and are computationally efficient. Porous media models, however, rely on the use of correlations to estimate the effect of complicated flow features on the pressure drop and heat transfer in the system. Existing correlations were developed to predict the average behavior of the bed, but they are inaccurate in the near-wall region where the presence of the wall affects the pebble packing. This work aims to investigate the accuracy of a porous media model using the Kerntechnischer Ausschuss (KTA) correlation, the most common pressure drop correlation for PBRs compared to the high-fidelity large eddy simulation (LES). A bed of 1568 pebbles is investigated at Reynolds numbers from 625 to 10 000. The bed is divided into five concentric subdomains to compare the average velocity, friction losses, and form losses between the porous media and LES codes. The comparison between the LES simulation and the KTA correlation revealed that the KTA correlation largely underpredicts the form losses in the near-wall region, leading to an overprediction of the velocity near the wall by nearly 30%. An investigation of the form losses across the range of Reynolds numbers in the LES results provided additional insight into how the KTA correlation may be improved to better predict these spatial effects in a pebble bed. These data suggest that the form coefficient near the wall must be increased by 48% while decreasing the form coefficient of the inner bulk region of the bed by 15%. The implementation of these improvements to the KTA correlation in a porous media model produced a radial velocity profile that saw significantly improved agreement with the LES results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Field-theoretic analysis of hadronization using soft drop jet mass

One of the greatest challenges in quantum chromodynamics is understanding the hadronization mechanism, which is also crucial for carrying out precision physics with jet substructure. In this paper, we bring together recent advancements in our understanding of nonperturbative structure of the soft drop jet mass based on field theory, with precise perturbative calculations at next-to-next-to-leading logarithmic accuracy of its multidifferential variants. This allows for a model-independent analysis of power corrections associated with hadronization in a systematic manner. We test and calibrate hadronization models and their interplay with parton showers by comparing our universality predictions with various event generators for quark and gluon initiated jets in both lepton-lepton and hadron-hadron collisions. Our findings reveal that hadronization models perform better for quark jets relative to gluon jets. Our results provide a valuable toolbox for precision studies with the soft drop jet mass and pave the way for future analyses using real-world collider data. The stringent constraints derived in our framework are useful for improving the modeling of hadronization and its interplay with parton showers in next-generation event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

FitCache: A Transparent Drop-In Framework for Multi-Tier Caching to Accelerate Distributed Deep Learning Workloads

Training in Deep learning (DL) remains highly compute- and data-intensive, with I/O becoming a critical bottleneck as models and datasets scale. Recent studies report that data loading can dominate training time, especially on large-scale HPC systems with shared parallel file systems (PFS). Existing caching approaches either rely on single-tier designs or require intrusive modifications to training pipelines, limiting their portability and effectiveness. In this work, we present FitCache, a transparent drop-in framework for multi-tier caching to accelerate distributed DL training by coordinating fast local memory (e.g., DRAM, Persistent Memory (PMem)) and NVMe as hierarchical caches atop PFS. Our design adapts to hardware diversity, i.e., if NVMe is missing, memory transparently acts as a caching tier, ensuring stable performance. FitCache transparently intercepts I/O requests and issues concurrent fetches across all tiers, returning data from the fastest responder without centralized metadata or static redirection paths. FitCache adapts to dynamic workloads and heterogeneous clusters while maintaining POSIX compatibility. Experiments on Frontier (2048 GPUs) and smaller research clusters show that FitCache reduces training time by up to 40% and per-batch I/O latency by up to 71.6% compared to Lustre Orion PFS, offering a drop-in solution for scalable DL training.

Hu, Guangxing [ORNL] (ORCID:0009000283203614)↗
DOE OSTI2025

Cooperative Merging via Online Speed Replanning: A Model-Free Approach With Vehicle-to-Vehicle Communication Packet Drop Compensation

On-ramp merging is a critical bottleneck in freeway traffic flow, contributing to congestion, accidents, and excessive fuel consumption. Although traditional ramp metering provides macroscopic control, it lacks the granularity for optimizing an individual vehicle’s trajectory. Cooperative merging, enabled by connected and automated vehicles, can potentially enhance traffic efficiency, safety, and fuel economy. However, existing research often neglects the influence of heterogeneous vehicle dynamics, unreliable vehicle-to-vehicle (V2V) communication, and real-time implementation challenges. Here, this paper introduces novel model-free online speed planners for cooperative on-ramp merging. The planners address these limitations by being agnostic to vehicle dynamics, effectively compensating for V2V communication packet drops and incurring only a light computational burden. Comprehensive evaluation, conducted on a real-time traffic-vehicle-communication co-simulation platform integrating high-fidelity vehicle dynamics, a traffic simulator, and recorded V2V communication footprints, demonstrates the effectiveness of the proposed speed planners. Simulation results reveal that the proposed method yields accurate tracking of desired speed and inter-vehicle distance, maintaining low fuel consumption even under high packet drop ratios, and demonstrating real-time implementation efficiency.

Wang, Zejiang [Univ. of Texas at Dallas, Richardso↗
DOE OSTI2023

Curb Allocation and Pick-Up Drop-Off Aggregation for a Shared Autonomous Vehicle Fleet

Advances in information technologies and vehicle automation have birthed new transportation services, including shared autonomous vehicles (SAVs). Shared autonomous vehicles are on-demand self-driving taxis, with flexible routes and schedules, able to replace personal vehicles for many trips in the near future. The siting and density of pick-up and drop-off (PUDO) points for SAVs, much like bus stops, can be key in planning SAV fleet operations, since PUDOs impact SAV demand, route choices, passenger wait times, and network congestion. Unlike traditional human-driven taxis and ride-hailing vehicles like Lyft and Uber, SAVs are unlikely to engage in quasi-legal procedures, like double parking or fire hydrant pick-ups. In congested settings, like central business districts (CBD) or airport curbs, SAVs and others will not be allowed to pick up and drop off passengers wherever they like. This paper uses an agent-based simulation to model the impact of different PUDO locations and densities in the Austin, Texas CBD, where land values are highest and curb spaces are coveted. In this paper 18 scenarios were tested, varying PUDO density, fleet size and fare price. The results show that for a given fare price and fleet size, PUDO spacing (e.g., one block vs. three blocks) has significant impact on ridership, vehicle-miles travelled, vehicle occupancy, and revenue. A good fleet size to serve the region’s 80 core square miles is 4000 SAVs, charging a $1 fare per mile of travel distance, and with PUDOs spaced three blocks of distance apart from each other in the CBD.

Hunter, Christian B.↗
DOE OSTI2021

Introduction of the PELICAN loop, a Full-Scale Pressure Drop Test Facility

The Versatile Test Reactor (VTR) is a test reactor currently under development by the US Department of Energy. This reactor will rely on fast neutrons enabling novel and wide-ranging experiment to support the development of the various advanced reactor technologies. With the high flux achievable, accelerated testing of fluid and materials will be made possible. To support VTR design efforts [1], an experimental facility has been designed and constructed at Argonne National Laboratory to recreate the hydraulic flow conditions within the VTR’s primary heat transport system (PHTS). This facility, the Pressure drop Experimental Loop for Investigations of Core Assemblies in advanced Nuclear reactors, PELICAN, measures the pressure drop across a full-scale fuel assembly containing prototypic axial reflectors, fuel, and plena components. Here, we first describe the design considerations required to recreate aspects of the VTR. Then we discuss the design and construction of PELICAN to address these design requirements, the design and construction of the test articles placed inside PELICAN’s test section, and finally present some of the first experimental results.

Grannan, A. M.↗