SEARCH · Engineering Papers

Results for “flux optimization”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50

All sources NASA NTRS DOE OSTI

NASA NTRS2017

Toward Large FOV High-Resolution X-Ray Imaging Spectrometer: Microwave Multiplexed Readout of 32 TES Microcalorimeters

We performed a small-scale demonstration at GSFC of high-resolution x-ray TES microcalorimeters read out using a microwave SQUID multiplexer. This work is part of our effort to develop detector and readout technologies for future space based x-ray instruments such as the microcalorimeter spectrometer envisaged for Lynx, a large mission concept under development for the Astro 2020 Decadal Survey. In this paper we describe our experiment, including details of a recently designed, microwave-optimized low-temperature setup that is thermally anchored to the 50 mK stage of our laboratory ADR. Using a ROACH2 FPGA at room temperature, we simultaneously read out 32 pixels of a GSFC-built detector array via a NIST-built multiplexer chip with Nb coplanar waveguide resonators coupled to RF SQUIDs. The resonators are spaced 6 MHz apart (at approx. 5.9 GHz) and have quality factors of approximately 15,000. Using flux-ramp modulation frequencies of 160 kHz we have achieved spectral resolutions of 3 eV FWHM on each pixel at 6 keV. We will present the measured system-level noise and maximum slew rates, and briefly describe the implications for future detector and readout design.

Yoon, Wonsik↗

DOE OSTI2021

Process Intensification and Scale-Up of a Continuous Enzymatic Hydrolysis and Separation Process

Combining separate unit operations into one where the best of each part can be maximized is one of the benefits of process intensification. An example is the combination of lignocellulosic biomass enzymatic hydrolysis with the downstream solid-liquid separation step to produce clarified sugars ready for fermentation or catalytic upgrading. The productivity and endpoint yield of enzymatic hydrolysis both enjoy the benefits of reduced feedback inhibition through the continuous removal of sugars by incorporating separations into the reactor. Likewise, the efficiency of recovering clarified sugars from the enzymatic hydrolysis slurry can be enhanced by operating separations equipment at steady-state conditions simultaneously with the continuously fed hydrolysis process. A key parameter that enables greater processing capacity while also raising the risks of failure is the solids loading or concentration. Higher solids loading allows for smaller reactor vessels and results in clarified sugars of higher concentration; however, required pumping power increases, reactor agitation may become ineffective, and membrane flux suffers. Feedstock material attributes influenced by upstream pretreatment must also be scrutinized more carefully: dilute-acid pretreated and deacetylated-and-disc-refined feedstocks exhibit different characteristics that affect agitation and pumping. The authors invite you to further explore the process science enabling the scale-up of this technology from conceptual work at the bench to pilot-scale industrially-relevant equipment where the challenges and solutions of integration and process optimization are expounded upon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Development of a three-dimensional APOLLO3 neutrons deterministic scheme for the CABRI reactor

CABRI is an experimental reactor to study the fuel behavior during reactivity injection transients. These transients being highly multiphysics, the development of suitable modeling and simulation tools to simulate them is important for the optimization of the tests and the control of the experimental conditions. This paper focuses on the development of an APOLLO3 deterministic core calculation tool dedicated to the CABRI transient analysis. It represents the first stage of the incremental process for the implementation of a multiphysics time-dependent modeling of the CABRI transient. The neutron calculation scheme is based on a classical two-step approach. The first step consists of a 281-energy group calculation flux with the TDT-MOC (Method Of Characteristics) solver for cross-section space and energy (23 groups) collapsing for the CABRI different assembly clusters. The bias on a 2D core neutron calculation due to the self-shielding calculation and collapsing on a restricted pattern are investigated thanks to a comparison with a direct full 2D calculation on a quarter of core. The second step relies on a pin-resolved transport 3D transport core calculation with the SN solver MINARET. A progressive numerical validation process is followed to quantify the calculation biases on reactivity and reaction rates at each step using reference calculations with the stochastic code TRIPOLI4. The next development stage toward a multiphysics scheme will be the implementation of the 3D-kinetics equation resolution and the coupling with a core thermal-hydraulics model. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1973

OGO-6 gas-surface energy transfer experiment

The kinetic energy flux of the upper atmosphere was analyzed using OGO-6 data. Energy transfer between 10 microwatts/sq cm and 0.1 W/sq cm was measured by short-term frequency changes of temperature-sensitive quartz crystals used in the energy transfer probe. The condition of the surfaces was continuously monitored by a quartz crystal microbalance to determine the effect surface contamination had on energy accommodation. Results are given on the computer analysis and laboratory tests performed to optimize the operation of the energy transfer probe. Data are also given on the bombardment of OGO-6 surfaces by high energy particles. The thermoelectrically-cooled quartz crystal microbalance is described in terms of its development and applications.

Mckeown, D.↗

NASA NTRS2001

Predicting Turbulent Convective Heat Transfer in Fully Developed Duct Flows

The performance of an explicit algebraic stress model (EASM) is assessed in predicting the turbulent flow and forced heat transfer in both straight and wavy ducts, with rectangular, trapezoidal and triangular cross-sections, under fully developed conditions. A comparison of secondary flow patterns. including velocity vectors and velocity and temperature contours, are shown in order to study the effect of waviness on flow dynamics, and comparisons between the hydraulic parameters. Fanning friction factor and Nusselt number, are also presented. In all cases. isothermal conditions are imposed on the duct walls, and the turbulent heat fluxes are modeled using gradient-diffusion type models. The formulation is valid for Reynolds numbers up to 10(exp 5) and this minimizes the need for wall functions that have been used with mixed success in previous studies of complex duct flows. In addition, the present formulation imposes minimal demand on the number of grid points without any convergence or stability problems. Criteria in terms of heat transfer and friction factor needed to choose the optimal wavy duct cross-section for industrial applications among the ones considered are discussed.

Rokni, Masoud↗

DOE OSTI2025

Design considerations for optimizing the transient CHI injector on QUEST

Transient coaxial helicity injection (transient CHI) on the QUEST (Q-shu University Experiment with Steady-State ST) spherical tokamak (ST) has recently validated the floating biased electrode configuration for solenoid-free plasma startup. In support of a significant divertor upgrade on QUEST, the details of the transient CHI injector geometry on QUEST have been examined more closely using tokamak simulation code (TSC) simulations. QUEST uses a HIT-II-like (Helicity Injected Torus) injector configuration in which the injector region is comprised of coaxial injector electrodes located in the lower part of the machine. TSC simulations indicate high injector flux operation may benefit from an increased gap between the coaxial electrodes. This is the first study to examine the differences between an open and closed electrode configuration for solenoid-free plasma startup using transient CHI. Results show that both configurations can generate similar levels of closed flux, but the closed configuration may be easier to implement in some ST designs as a much smaller portion of the injector needs to be close to the injector flux coil. Results show that increasing the electrode gap width from the present 10.8 cm to about 15–20 cm would increase the closed flux fraction by about 40%. The results presented in this paper are generally applicable to the CHI design for other STs.

coaxial helicity injection↗

DOE OSTI2026

ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized nonlinear conservation laws from sparse and noisy data

Multi-query applications such as parameter estimation, uncertainty quantification and design optimization for parameterized partial differential equation (PDE) systems are expensive. While reduced/latent state dynamics approaches for parameterized PDEs offer a viable alternative, these approaches rely on high-quality data and struggle with highly sparse spatiotemporal noisy measurements typically obtained from experiments. Furthermore, there is no guarantee that these models satisfy governing physical conservation laws. In this article, we propose a reduced state dynamics approach, referred to as ECLEIRS, that embeds exact conservation in the solution and flux representation by utilizing a space-time divergence-free neural network formulation. We compare ECLEIRS with other reduced state dynamics approaches, those that do not enforce any physical constraints and those with physics-informed loss functions, for three shock-propagation problems: 1-D advection, 1-D Burgers and 2-D Euler equations. In conclusion, the numerical experiments conducted in this study demonstrate that ECLEIRS provides the most accurate prediction of dynamics for unseen parameters even in the presence of highly sparse and noisy data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Enhancing Steam-Side Heat Transfer via Microdroplet Ejection using Inorganic Coatings

During condensation of water on a superhydrophobic nanostructured surfaces, droplets coalesce and jump (droplet ejection) due to the release of excess surface energy. Meticulously designed nanostructured surfaces or coatings capable of droplet ejection can enhance heat transfer performance by easy removal of droplets during condensation. In the present work, the capabilities of the Nelumbo droplet ejection coatings technology currently used in commercial heat exchangers are explored and optimized for materials and conditions relevant to steam condensers. Specifically, this includes (1) adapting and optimizing the procedures and chemistries to deposit droplet ejecting coatings on materials used in the steam condenser, (2) testing of the heat transfer, durability, and fouling of the fabricated coatings under a variety of steam condenser relevant conditions, and (3) modeling of the impact of droplet dynamics and interfacial properties on heat transfer in steam condensers. We experimentally demonstrated that at low supersaturation conditions (S~1.02), developed superhydrophobic nanostructured surface gives a 40% higher peak heat transfer flux and a 17% higher peak overall heat transfer coefficient (U) with droplet ejection mechanism compared to the dropwise condensation mechanism on the same nanostructured surface. Though the experimentally observed droplet ejection mechanism was short-lived (~3 min) due to the limitation of the chiller to maintain a constant supersaturation condition in fabricated steam condenser. And large variations in water inlet temperature (+ to - 2 degrees C) caused flooding of nanostructure (Wenzel state) at higher supersaturation (S > or = 1.12). This is an important finding because typical supersaturation levels in field operation are over 1.8 and as such, either the flooding potential for these materials should be improved or operation at lower supersaturation may be required to maximize heat transfer efficiency. If supersaturation conditions can be maintained reliably in the steam condenser in addition to droplet ejection mechanism during condensation, this could provide a potential 2% reduction in water flow rate which equates to a savings of over 3900 gallons of water per minute for a 500 MW steam turbine and over $0.3MM savings annually given a 0.02 cent marginal water withdrawal cost. It is also worth noting that these savings are based on improvement of droplet ejection coatings over coatings capable of performing consistent dropwise mechanism in in-field surface condensers. Savings due to the droplet ejections coatings when compared to bare substrates could be much higher. Additionally, the present work provides the importance of steam condenser operating conditions and insights into the challenges in modeling the condensing droplet dynamics on surfaces.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2023

Thermopile Energy Harvesting for Subsurface Wellbore Sensors (Final Report)

Robust in situ power harvesting underlies all efforts to enable downhole autonomous sensors for real-time and long-term monitoring of CO 2 plume movement and permeance, wellbore health, and induced seismicity. This project evaluated the potential use of downhole thermopile arrays, known as thermoelectric generators (TEGs), as power sources to charge sensors for in situ real-time, long-term data capture and transmission. Real-time downhole monitoring will enable “Big Data” techniques and machine learning, using massive amounts of continuous data from embedded sensors, to quantify short- and long-term stability and safety of enhanced oil recovery and/or commercial-scale geologic CO 2 storage. This project evaluated possible placement of the TEGs at two different wellbore locations: on the outside of the casing; or on the production tubing. TEGs convert heat flux to electrical power, and in the borehole environment, would convert heat flux into or out of the borehole into power for downhole sensors. Such heat flux would be driven by pumping of cold or hot fluids into the borehole—for instance, injecting supercritical CO 2 —creating a thermal pulse that could power the downhole sensors. Hence, wireless power generation could be accomplished with in situ TEG energy harvesting. This final report summarizes the project’s efforts that accomplished the creation of a fully operational thermopile field unit, including selection of materials, laboratory benchtop experiments and thermal-hydrologic modeling for design and optimization of the field-scale power generation test unit. Finally, the report describes the field unit that has been built and presents results of performance and survivability testing. The performance and survivability testing evaluated the following: 1) downhole power generation in response to a thermal gradient produced by pumping a heated fluid down a borehole and through the field unit; and 2) component survivability and operation at elevated temperature and pressure conditions representative of field conditions. The performance and survivability testing show that TEG arrays are viable for generating ample energy to power downhole sensors, although it is important to note that developing or connecting to sensors was beyond the scope of this project. This project’s accomplishments thus traversed from a low Technical Readiness Level (TRL) on fundamental concepts of the application and modeling to TRL-5 via testing of the fully integrated field unit for power generation in relevant environments. A fully issued United States Patent covers the wellbore power harvesting technology and applications developed by this project.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)

Tropical forest dynamics play a crucial role in the global carbon, water, and energy cycles. However, realistically simulating the dynamics of competition and coexistence between different plant functional types (PFTs) in tropical forests remains a significant challenge. This study aims to improve the modeling of PFT coexistence in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vegetation demography model implemented in the Energy Exascale Earth System Model (E3SM) land model (ELM), ELM-FATES. Specifically, we explore (1) whether plant trait relationships established from field measurements can constrain ELM-FATES simulations and (2) whether machine learning (ML)-based surrogate models can emulate the complex ELM-FATES model and optimize parameter selections to improve PFT coexistence modeling. We conducted three ensembles of ELM-FATES experiments at a tropical forest site near Manaus, Brazil. By comparing the ensemble experiments without (Exp-CTR) and with (Exp-OBS) consideration of observed trait relationships, we found that accounting for these relationships slightly improves the simulations of water, energy, and carbon variables when compared to observations but degrades the simulation of PFT coexistence. Using ML-based surrogate models trained on Exp-CTR, we optimized the trait parameters in ELM-FATES and conducted another ensemble of experiments (Exp-ML) with these optimized parameters. The proportion of PFT coexistence experiments significantly increased from 21 % in Exp-CTR to 73 % in Exp-ML. After filtering the experiments that allow for PFT coexistence to agree with observations (within 15 % tolerance), 33 % of the Exp-ML experiments were retained, which is a significant improvement compared to the 1.4 % in Exp-CTR. Exp-ML also accurately reproduces the annual means and seasonal variations in water, energy, and carbon fluxes and the field inventory of aboveground biomass. This study represents a reproducible method that utilizes machine learning to identify parameter values that improve model fidelity against observations and PFT coexistence in vegetation demography models for diverse ecosystems. Our study also suggests the need for new mechanisms to enhance the robust simulation of coexisting plants in ELM-FATES and has significant implications for modeling the response and feedbacks of ecosystem dynamics to climate change.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Hourly Carbon Fluxes Estimation Using the GOES Advanced Baseline Imager (ABI) Data Over the Conterminous USA

Tremendous efforts by Fluxnet scientists over the past few decades have made thousands of site-years of carbon flux observations available for advancing our understanding of carbon cycling in terrestrial ecosystems. One of key Fluxnet measurements is net ecosystem exchange (NEE) as it is directly related to carbon budget of terrestrial ecosystems. However, carbon flux estimation studies using satellite remote sensing have focused mainly on daily Gross Primary Production (GPP). The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. Because daily NEE is close to zero value, the carbon flux models using the polar orbiting satellite data have not been well used for NEE estimation. The new generation of geostationary satellite sensors (e.g., GOES Advanced Baesline Imager (ABI) and Himawari Advanced Himawari Imager (AHI)) provide frequent observations, often less than every 10 minutes. Here, we use GOES ABI data to estimate hourly NEE over the conterminous USA. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and, in particular, solar radiation that is directly derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Fluxnet data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

Geostationary satellite↗

DOE OSTI2026

A data-driven approach to real-time vertical position estimation for NSTX-U vertical stability control

In this paper, a database of 77 996 plasma equilibrium reconstructions from 727 discharges during the initial operation of the NSTX-U spherical tokamak is analyzed to develop a statistically robust model of the plasma vertical position for real-time control. A variety of regression models are developed and tested, ranging in complexity from linear models to deep neural networks, and including input signals ranging from the four pairs of flux loops used historically on NSTX-U up to the full set of 389 real-time signals available to the plasma control system. A linear model based on 140 real-time magnetics signals is found to offer excellent accuracy, with a coefficient of determination R 2 = 0.906. The robustness of this model to limited training data, new operating scenarios, and signal errors is tested, and a procedure is demonstrated to tune the model parameters to optimize its robustness. A time-dependent plasma equilibrium solver, TokaMaker, is used to simulate vertical stability control in NSTX-U, demonstrating that it should be possible to iteratively tune the parameters of a linear vertical position model to stabilize both positive and negative triangularity plasmas in future experiments.

magnetic diagnostics↗

DOE OSTI2020

Inference offers a metric to constrain dynamical models of neutrino flavor transformation

The multimessenger astrophysics of compact objects presents a vast range of environments where neutrino flavor transformation may occur and may be important for nucleosynthesis, dynamics, and a detected neutrino signal. Development of efficient techniques for surveying flavor evolution solution spaces in these diverse environments, which augment and complement existing sophisticated computational tools, could leverage progress in this field. To this end we continue our exploration of statistical data assimilation (SDA) to identify solutions to a small-scale model of neutrino flavor transformation. SDA is a machine learning formula wherein a dynamical model is assumed to generate any measured quantities. Specifically, we use an optimization formulation of SDA wherein a cost function is extremized via the variational method. Regions of state space in which the extremization identifies the global minimum of the cost function will correspond to parameter regimes in which a model solution can exist. Our example study seeks to infer the flavor transformation histories of two monoenergetic neutrino beams coherently interacting with each other and with a matter background. We require that the solution be consistent with measured neutrino flavor fluxes at the point of detection, and with constraints placed upon the flavor content at various locations along their trajectories, such as the point of emission, and the locations of the Mikheyev-Smirnov-Wolfenstein resonances. We show how the procedure efficiently identifies solution regimes and rules out regimes where solutions are infeasible. Overall, results in this work intimate the promise of this “variational annealing” methodology to efficiently probe an array of fundamental questions that traditional numerical simulation codes render difficult to access.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Influence of Supplementary Blue and Far-Red Light on the Morphology and Texture of Ocimum basilicum L. Grown in Controlled Environments

Basil (Ocimum basilicum L.) is highly sensitive to environmental conditions and is an ideal candidate for cultivation in controlled environment agriculture (CEA). Light-emitting diode technology has become essential in CEA, offering precise control over light intensity, spectrum, and duration. This study investigated how supplemental blue light, far-red light, or their combination influences basil biomass, morphology, texture, and color when added to a white + red light spectrum. Basil ’Prospera’ and ’Amethyst’ were exposed to five light treatments for 14–28 days: white + red at 180 µmol∙m−2∙s−1 (W) as the control, and four treatments with an additional 60 µmol∙m−2∙s−1 of either white + red (+W60), blue (+B60), far-red (+FR60), or a combination of B and FR (+B30+FR30), for a total photon flux density of 240 µmol∙m−2∙s−1. The results demonstrated that +B60 and +W60 light treatments increased leaf thickness by 17–20% compared to the +FR60 treatment. Conversely, texture analysis revealed that +FR60-treated leaves had higher puncture resistance, with ’Amethyst’ and ’Prospera’ requiring 1.57 ± 0.43 N and 1.45 ± 0.35 N of force, respectively, compared to 1.19 ± 0.32 N and 1.1 ± 0.21 N under +B60. These findings suggest that tailored light recipes in CEA can optimize basil quality, allowing growers to modify traits like leaf color, thickness, and toughness.

Oehler, Madison A. (ORCID:0000000297919667)↗

DOE OSTI2020

Kepler Data Analysis: Non-Gaussian Noise and Fourier Gaussian Process Analysis of Stellar Variability

We develop a statistical analysis model of Kepler stellar flux data in the presence of planet transits, non-Gaussian noise, and stellar variability. We first develop a model for the Kepler noise probability distribution in the presence of outliers, which make the noise probability distribution non-Gaussian. We develop a signal likelihood analysis based on this probability distribution, in which we model the signal as a sum of the star variability and planetary transits. We argue that these components need to be modeled together if optimal signal is to be extracted from the data. For the stellar variability model we develop an optimal Gaussian process analysis using a Fourier-based Wiener filter approach, where the power spectrum is non-parametric and learned from the data. We develop high dimensional optimization of the objective function, where we jointly optimize all the model parameters, including thousands of star variability modes, and planet transit parameters. We apply the method to Kepler-90 data and show that it gives a better match to the stellar variability than the existing methods, and robustly handles noise outliers. As a consequence, the planet radii have a higher value than what the existing methods give, including splines and celerite.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1993

Transient development of perturbations in stratified shear flow

Transient development of perturbations in inviscid stratified shear flow is investigated. Use is made of closed form analytic solutions that allow concise identification of optimally growing plane-wave solutions for the case of an unbounded flow with constant shear and stratification. For the case of channel flow, variational techniques are employed to determine the optimally growing disturbances. The maximum energy growth attained over a specific time interval decreases continuously with increasing stratification, and no special significance attaches to Ri = 0.25. Indeed, transient growth can be substantial even for Ri = O(1). A general lower bound on the energy growth attained by an optimal perturbation in a stratified flow over a given time interval is the square root of the growth attained by the corresponding perturbation in unstratified flow. Enhanced perturbation persistence is found for mean-flow stratification lying in the range Ri between 0.1 and 0.3. Small but finite perturbations in mean flow with Ri less than 0.4 produce regions with locally negative total density gradient, which are expected to overturn. Although the perturbations are of wave form, buoyancy fluxes mediate transfer between perturbation kinetic and potential energy during transient development, thus implying that buoyancy flux is not a determinative diagnostic for distinguishing between waves and turbulence in stratified flows.

Farrell, Brian F.↗

NASA NTRSDate not supplied

Fluid & Thermal Analysis of a Manifold Microchannel Heat Sink

A three-dimensional (3-D) numerical model has been developed to study the fluid flow and heat transfer through a manifold-microchannel (MMC) heat sink, a microfluidic cooling system designed as a heat dissipation solution for compact, high-powered electronic systems. An MMC consists of a 3-D manifold structure that distributes working fluid through alternating inlet and outlet manifold channels that guide the fluid to and from the microchannels, shortening the flow length and thereby, reducing the pressure drop across the system. Wide bandgap semiconductors such as silicon carbide (SiC) are increasingly utilized due to their ability to enable smaller electronic devices and components to operate more efficiently at higher frequencies. These semiconductors can greatly benefit from the MMC, which can extract all the heat produced by compact, high-powered electronics, enabling them to achieve optimal performance. The MMC also utilizes an embedded cooling approach which allows for fabrication directly within SiC-based electronics, resulting in significant mass and weight savings and lower thermal resistance than conventional heat sink designs. This paper outlines the methods used to conduct fluid and thermal analysis of different MMC configurations for flow parameters such as flow rate and inlet flow conditions. This study involves both steady state and transient thermal analysis as a gradually increasing heat flux is applied to the system over time, which is representative of the heat dissipation from the electronics over a given period. Results from the analysis show that the MMC is capable of effectively dissipating heat flux of ~100 W/cm2 while maintaining considerably low pressure drop (< 1 kPa) and thermal resistance (< 1 K/W) for certain single-phase working fluids.

manifold microchannel↗

NASA NTRSDate not supplied

Fluid & Thermal Analysis of a Manifold Microchannel Heat Sink

manifold microchannel↗